Degree project in

Acoustic Emission Properties ofPartial Discharges in the

time-domain and their applications

PATRICK JANUS

Stockholm, Sweden 2012

XR-EE-ETK 2012:004

Electromagnetic EngineeringMasters' Degree Project

Acoustic Emission Properties of Partial Discharges in the time-domain and their applications

PATRICK JANUS

Stockholm 2012

Electromagnetic Engineering

School of Electrical Engineering Kungliga Tekniska Högskolan

XR-EE-ETK 2012:004

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ABSTRACT A partial discharge (PD) is an unwanted phenomenon in electrical equipment. Therefore it is of great importance to identify different types of PD and assess their severity. This thesis investigates the acoustic emissions associated with PD from different types of sources in the time-domain and based on these results a low-cost detection system is designed, built and verified against much more expensive commercially available sensor platforms. The results are promising both for the detection of different types of PD and their classification. The low-cost detection system shows equal usefulness as commercially available systems and the system is also compared against other systems for detection. Also some investigation is carried out concerning the nature of the ultrasounds emitted by PD. The results from these experiments indicate that a description with the classical wave equation is inadequate. In order to explain the frequency content of acoustic PD signals at different distances away from the source, a more complex description in the form of nonlinear acoustic equations may be more accurate.

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ACKNOWLEDGEMENTS I would like to express my deepest gratitude towards Associate Professor Hans Edin for believing in me and giving me the opportunity to conduct this thesis. I would also like to thank him for showing great patience even towards the most craziest ideas and for his confidence in my abilities. I would also like to thank Msc, PhD student Mohamad Niasar Ghaffarian for his knowledge and help in the laboratory, no matter at what time. His selfless help and support aided me in the darkest hours of this thesis for which I am forever grateful. I wish to extend my gratitude towards the Innoenergy projects KIC-ASS and CIPOWER, whose financial aid has been invaluable for me as to the purchase of new sensors and equipment required for the thesis work. To the entire team working in the high voltage lab I wish to thank for the friendly and stimulating environment that they create. I wish to thank my friend, John Laury for his support and aid throughout all of this time that we have spent together, both in- and outside of school. Finally, but not least, I thank my loving wife Natalia for her outstanding patience with me working through the nights, late phone calls, and so on.

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TABLE OF CONTENTS 1. INTRODUCTION ................................................................................................................ 7

1.1 PD in a historical perspective ........................................................................................ 7 1.2 Classification of PD ........................................................................................................ 7 1.3 PD detection methods ..................................................................................................... 8

1.3.1 Electrical Detection ................................................................................................. 8 1.3.2 Chemical detection .................................................................................................. 9 1.3.3 Acoustic detection .................................................................................................... 9

1.4 Low-cost ultrasonic detectors ...................................................................................... 10 1.5 Data acquisition methods ............................................................................................. 10 1.6 Aims ............................................................................................................................... 11 1.7 Disposition ..................................................................................................................... 11

2. ULTRASOUND GENERATED BY PD ........................................................................... 13

2.1 Partial discharges and ultrasound .............................................................................. 13 2.2 The nature of ultrasound / nonlinear acoustics ......................................................... 13

2.2.1 Fubini’s solution .................................................................................................... 14 2.2.2. The Burgers equation ........................................................................................... 15 2.2.3. The KZK (Khokhlov-Zabolotskaya-Kuznetsov) equation ............................... 15

2.3 Detection of ultrasound ................................................................................................ 16 3. TRANSDUCERS ................................................................................................................ 18

3.1 Transducers used in thesis ........................................................................................... 18 3.2 Expected ultrasonic and electric parameters ............................................................. 19

4. AMPLIFIERS AND DETECTORS ................................................................................. 20

4.1 Overview of needed amplifiers and detectors ............................................................ 20 4.2 Band-pass detection system ......................................................................................... 20

4.2.1 Design aspects ........................................................................................................ 20 4.2.2 Modelling ................................................................................................................ 23 4.2.3 Implementation ...................................................................................................... 24 4.2.4 Verification ............................................................................................................ 25

4.3 Broadband amplifier .................................................................................................... 26 4.3.1 Design aspects ........................................................................................................ 27 4.3.2 Modelling ................................................................................................................ 28 4.3.3 Implementation ...................................................................................................... 29

5. LABORATORY SETUP FOR PD DETECTION USING ULTRASOUND ................ 31

5.1 Experimental setup ...................................................................................................... 31 5.2 Phase resolved PD measurement equipment ............................................................. 32 5.3 Test objects .................................................................................................................... 33

5.3.1. Test object for Corona in air ............................................................................... 33 5.3.2. Canonical Test objects for PD in transformers ................................................. 33

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6. Results ................................................................................................................................. 35 6.1 PD patterns for different situations ............................................................................ 35

6.1.1 Corona in air .......................................................................................................... 35 6.1.2 Corona in oil .......................................................................................................... 36 6.1.3 Surface discharge .................................................................................................. 37 6.1.4 Void discharge ....................................................................................................... 38

6.2 Frequency dependence in PD signals as function of the distance ............................ 38 6.3 Comparison of PD Patterns for different situations ................................................. 39 6.4 Comparison of different PD detection methods ........................................................ 40

6.4.1 Corona in oil .......................................................................................................... 40 6.4.2 Surface discharge in oil ......................................................................................... 42

7. CONCLUSIONS ................................................................................................................. 44 8. FUTURE WORK ............................................................................................................... 45 9. REFERENCES ................................................................................................................... 46 APPENDIX A: DESIGN PROCESS OF A TRANSISTOR AMPLIFIER ....................... 48 APPENDIX B: DESIGN OF NARROWBAND AMPLIFIER .......................................... 51 APPENDIX C: DATASHEETS FOR KNOWLES ACOUSTICS SPM0204UD5 ........... 56 APPENDIX D: DATASHEETS FOR MURATA MA40MF14-0B .................................... 57 APPENDIX E: DATASHEETS FOR PHYSICAL ACOUSTICS SENSORS .................. 58

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1. INTRODUCTION 1.1 PD in a historical perspective Even though electrical discharges have been known to man since the dawn of time in the form of lightnings, the study of partial discharges is a relatively new branch on the evolutional tree of electrical engineering. One milestone in the technical area came in 1963 with the release of the draft of VDE 0433/…63, part 4, “Guidelines for measuring set-ups for corona insulation tests” and part 5 “Guidelines for corona tests on power system equipments with alternating voltages up to 500 Hz.” In conjunction with this release a technical conference with the theme “Early recognition of defects in the insulation of windings” was held in Germany. This conference mainly addressed itself to the questions and problems of partial discharges in electrical apparatus, especially their measurement and evaluation. This meeting proved to be of great importance since it provided a forum for discussing questions which went well beyond the knowledge and experience of old-school power engineers. The greatest breakthrough of this conference was that it introduced the concept of non-destructive testing techniques that up until then had only been known to a certain group of technical persons was now introduced to a broader audience. The introduction of these testing techniques, for instance, lead to a drastic reduction of failures in epoxy insulated instrument transformers, which were till then very high and in some cases not at all understandable. [1] Since then a lot of work has been conducted to refine the techniques used for testing and also a great effort has been made to further understand the underlying mechanisms of discharges, but a lot of work still remains until all secrets of partial discharges will be revealed 1.2 Classification of PD The basis for the nomenclature on partial discharges (PD) is the IEC standard 60270 - High-Voltage Test Techniques – Partial Discharge Measurements, which contains among other things the basic definitions in context of partial discharges. The definition of a PD is according to IEC standard 60270, a localised dielectric breakdown of a small portion of a solid or fluid electrical insulation system under high voltage stress, which does not bridge the space between two conductors. The partial discharges are then divided into two major sub-groups, internal and external PD, depending on their occurrence in a particular set-up, as seen in fig. 1.

Fig 1: Terminology

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These two sub-groups are internal and external discharges. Each of these sub-groups can be represented by a number of different experimental set-ups which can be treated as typical cases which can be seen in fig. 2. These typical examples are of great significance when conducting laboratory experiments in order to simulate different situations in which PD may occur.

Fig 2: Idealized configurations for internal and external partial discharges used in laboratories [1]

1.3 PD detection methods Over time, electrical insulation subjected to high electrical fields begins to breakdown due to mechanical, thermal and electrical stress. Because partial discharges are both symptomatic of insulation breakdown and a mechanism for further insulation damage, PD detection is used to evaluate the condition of and diagnose problems with the insulation [2]. Over the past fifty years, several methods have been developed to detect PD. These methods fall into one of four categories: electrical, chemical, acoustical and optical. The optical detection method is not used to any known extent and is therefore omitted in the following description of the methods. 1.3.1 Electrical Detection Electrical detection is based on the electrical pulse created by the current streamer in the void. These single pulses last in the order of nanoseconds and have measurable frequency components in excess of 1 MHz [3]. The pulse shape, its relative phase location within the AC cycle, and the signal intensity all lead to information about the type of PD fault and the severity of the insulation damage. Electrical measurements are grouped into two categories, direct probing and RF emission testing. The direct probing method requires that capacitive couplers be connected to the phase terminals of the transformer. The second group, RF emission testing, is conducted by using antennas inside mainly transformers. The main problem with electrical detection is the equipment susceptibility to noise, which can lead to false detection of PD. Usually the equipment subjected to testing also needs to be taken off-line, energized from a high-voltage source and then tested, this requires a lot of time and equipment[4]. This in turn results in high cost for the owner [3]. Despite these draw-backs, this type of detection system is currently the most accurate and provides equipment managers with valuable information about the condition of equipment [5].

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1.3.2 Chemical detection Partial discharges can be detected chemically since current streamers break down the surrounding materials into different chemical components. The two primary chemical tests that are in use today are dissolved gas analysis (DGA) and high performance liquid chromatography (HPLC). It is worth mentioning that these tests only can be performed on oil-filled components, mainly transformers, which is a limitation in their application. The DGA test identifies gases dissolved in the oil produced by the breakdown of mineral oil. The test is performed by taking an oil sample and determining the levels of different dissolved gases, manly hydrogen but also acetylene, methane, carbon oxide, carbon dioxide, and ethylene [5]. This test indicates the presence of PD but also provides additional information because different levels of each of the gases can be correlated to a specific type of fault. HPLC test measure the by-products of transformer wall insulation breakdown, i.e. cellulose and its by-products. The disadvantage of this test is that glucose levels in the oil are very small and the degraded forms of glucose are not very stable. In addition, this test suffers the same uncertainty as DGA because there are no standard values for glucose concentration and it’s correlation to faults [5]. The limitations of chemical testing are that these methods do not provide any information about the position or extent of the PD and/or insulation damage. An interesting development in this field is currently being conducted by adding certain chemical “tags” to specific portions of the insulation. These tags are released in the oil when the insulation breaks down and can be detected. The problem with this method is that it has a fair amount of uncertainty regarding the severity of the PD activity, also that this method doesn’t provide instantaneous information about the state of the component being evaluated. [6] 1.3.3 Acoustic detection Acoustic detection is based on the phenomenon that PD emits sound. This sound, audible or not, is created when the current streamer is formed and the material surrounding the streamer is vaporized. This vaporization causes a rapid release of mechanical energy, which propagates in the form of a pressure field [7]. The best analogy which is easily understood is that of the formation of thunder after a lightning strike. Acoustic detection systems can be broken into two categories: external and internal systems. External acoustic detection systems, currently more utilized in power systems, employ sensors mounted to the outside of power equipment to detect the PD acoustic signal. Internal systems on the other hand use sensors placed inside of power equipment to directly measure the pressure wave. The primary advantage of acoustic detection over other methods is that positioning information is available by using sensors at multiple locations. This position information can help to identify the type of PD and the severity of an insulation fault. Another advantage of acoustic detection over electrical is its immunity to electromagnetic interference (EMI). This immunity to EMI makes acoustic detection ideal for online PD detection because a better signal to noise ratio (SNR) for the acoustic signal will lead to fewer false alarms. [8][9][10] But immunity to EMI does not mean that there is no acoustic noise in the system.

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Mechanical vibrations in transformer cores are the primary source of acoustic noise, but the frequency content of these vibrations are sufficiently lower than the PD acoustic signal. Acoustic detection also has its limitations. The main problem with acoustic detection is the complex nature of the acoustic propagation pathways, which is outlined later. There is also the problem that received acoustic signals have very low intensity so sensors must be very responsive to small changes in signal amplitude in order to detect a PD [5]. One other very important issue which currently limits the usefulness of acoustic PD detection equipment is the high price for these units. Therefore the question arises if such detection systems cannot be made cheaper by using mass produced components like commercially available piezoelectric transducers and other off-the-shelf components. 1.4 Low-cost ultrasonic detectors As a part of this thesis a low-cost but efficient PD detector was constructed and evaluated in conjunction with the commercially available systems in order to investigate if there are ways of making these sensor platforms interesting enough for commercial introduction. The benefits of cost-efficient systems are that grid and power company owners will have the opportunity to install them in places where up until now a surveillance system was too expensive to install. This will hopefully lead to a more reliable power system with fewer outages even in smaller components thanks to increased surveillance. As previously mentioned, this amplifier will be constructed so that the per-unit production cost is kept as low as possible. Therefore all of the components used for this sensor should be available in large quantities on the market at affordable prices. The detector should be able to detect both internal and external PD, both from AC and DC sources; it should have both electrical and acoustical means of detection. If a PD is detected an audible signal should be heard through a pair of headphones and a measurable electrical signal should be provided to an oscilloscope or similar device and the sensitivity should match that of commercially available sensor systems. 1.5 Data acquisition methods Signals from both electrical and acoustical measurements are in one way or another digitally processed, and here a brief explanation is given on the function of one such processing method which is common to all commercially available equipment for PD analysis.

Fig. 3: Typical emission signal characteristics Fig. 4: Phase-resolved PD pattern for a surface discharge in air on pressboard .

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The method in question, the hit principle, is outlined in fig. 3. The basis for this measurement is that the system reacts when the signal crosses a threshold and then it measures the following parameters: amplitude, rise time and duration. In order for this system to be accurate a good SNR (signal-to-noise) ratio is necessary. The better this ratio is, the more sensitive the apparatus gets. [11] By grouping these parameters according to their specific parameters and their relative position against the supply voltage, a chart can be produced, and from patterns within these charts it is possible to draw conclusions as to the type of PD, and the severity of such discharges. Such a phase-resolved partial discharge pattern (PRPD) is presented in fig. 4. 1.6 Aims The main goal of this thesis is to investigate the following aspects of partial discharge detection using acoustic emission techniques

1) Distinguish different types of PD using acoustic emission techniques according to the time-domain behaviour of individual pulses.

2) Design and implement a cost-effective detector for acoustic detection of PD using off-

the-shelf components and evaluate its usefulness compared to commercially available systems.

3) For the commercially available transducers a preamplifier with an adjustable gain of

20, 40 and 60 dB is needed. Since these preamplifiers cost several hundred Euros and the budget for the thesis is limited a selectable-gain amplifier will be constructed based on the technical specifications of the commercially available amplifiers.

The first issue is of interest since few efforts have been made to explain the time-domain behaviour of an acoustic PD signal and the type of PD associated with it. The second issue is of interest since commercially available sensors are so expensive that it isn’t cost-effective to mount these in remote places and in small installations. If a sensor could be developed cheap enough with adequate performance it could help increasing the safety of power system by alerting of possible faults where they now only are discovered when something really breaks and causes outages and/or disruptions. The third issue is connected to the second, since the cost of commercially available components is very high, and this thesis consists in part to lower the cost of such devices and to demonstrate how this can be achieved. 1.7 Disposition This thesis is organized into 9 chapters as follows. Chapter 1: Introduction and general information which covers the basics concerning PD and motivation for the thesis work. Chapter 2: This chapter contains a more theoretical description of ultrasonic phenomena in connection to partial discharges and how these are detected.

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Chapter 3: Describes the transducers used for this thesis work and their expected working parameters. Chapter 4: Describes the amplifiers and detectors which were designed and built during the course of this master thesis. The first part gives a short outline and motivation for the different types which is then explained in more detail Chapter 5: First the current lab environment with all the necessary auxiliary equipment is and then the experimental set-ups used for experiments within this thesis are described. Chapter 6: Results obtained from the experiments are presented, starting with an analysis of different types of PD and then continuing with a comparison of different patterns and detection methods. Chapter 7: A discussion of the work conducted for this thesis is carried out and the results are summarized and reviewed. Chapter 8: This chapter contains identified areas of future research which will help improving the understanding of acoustic emissions from PD. Chapter 9: Contains all scientifical references used during the duration of the master thesis work.

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2. ULTRASOUND GENERATED BY PD 2.1 Partial discharges and ultrasound As stated earlier there is a relationship between ultrasound and PD[7]. Usually the propagation of these ultrasonic waves away from the PD source is described by combining three basic equations describing continuity, conservation of momentum and elasticity of the medium which form the general differential equation of acoustic wave motion:

pctp 222

2

∇=∂∂ Eq. 1

Where p is the acoustic pressure and c is the speed of sound. However there have been several simplifications when this equation was derived, and also there has been an assumption made that there are no non-linear effects occurring and not even that there is an attenuation of the wave as it travels through the medium. The last statement would for example imply that someone standing in Kiruna could talk to someone in Malmö, which is approximately thousands of kilometres away. This is obviously not true. The previously explained simplifications also create problems when certain experimental results obtained in experiments are being explained. These results mainly considers the frequencies associated with PD activity, as different papers report completely different frequency spectrums of PD activity, ranging from 20 kHz up to 1 MHz [4][10][12]. This cannot be explained by the classical wave equation in which frequency is treated as constant. There have been certain attempts as to explain this phenomenon by assuming that the insulating materials features a low-pass character for ultrasonic waves [13], but up until now no satisfactory explanation has been given. However an interesting discovery has been made by acoustic researchers dealing with wave propagation in oil, which is an identical situation to a PD in a power transformer. These discoveries might account for the large spreading in frequency spectra which cannot be explained by classical phenomena like scattering, diffraction, etc. 2.2 The nature of ultrasound / nonlinear acoustics First of all a brief intuitive explanation of what is going on is given, then the formal expressions and equations are presented that better model the wave propagation of ultrasounds emitted by PD. It should be noted that the phenomena that is called sound is actually a pressure wave propagating through a material as a localized pressure change. Next, from basic physics, it should be realised that increasing pressure of a gas increases its temperature and that the speed of sound in a compressible material increases with temperature.

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A result of the previous statements is that waves travel faster during the high pressure phase of the oscillation than during the low pressure phase. This affects the wave's frequency structure; for example, in a plane sinusoidal wave of a single frequency, the peaks of the wave travel faster than the valleys, and the signal becomes more like a sawtooth wave. In doing so, other frequency components are introduced, which can be expanded into Fourier Series. This phenomenon is characteristic of a non-linear system, in comparison to a linear acoustic system which only responds to the driving frequency.[14]

Additionally, waves of different amplitudes will generate different pressure gradients, contributing to the non-linear effect.[14]

The pressure changes within a medium cause the wave energy to transfer to higher harmonics. Since attenuation generally increases with frequency, a counter effect exists that changes the nature of the nonlinear effect over distance. To describe their level of nonlinearity, materials can be given a nonlinearity parameter, AB . The values of A and B are the coefficients of the first and second order terms of the Taylor series expansion of the equation relating the material's pressure to its density. [14] In order to account for these type of phenomena a lot of research has been carried out in the area of non-linear acoustics and here three fundamental equations from this research field are presented: The Fubini’s solution, the Burgers equation and the KZK equation. 2.2.1 Fubini’s solution The Fubini solution solves the problem of nonlinear propagation of monofrequency sources only before shock formation, basically meaning that it is valid to a distance where the wave develops a vertical tangent, i.e. the beginning of becoming a shock wave. The pressure distribution is expressed by an infinite sum of weighted Bessel functions:

∑∞

=

′=′1

0 )sin()(2),(n

n tnnJn

ptp ωσσ

σ Eq. 2

Where 0/ cxtt −=′ is the retarded time, 0p is the initial amplitude of the sinusoidal wave,

nJ is the Bessel function of order n and xx/=σ where x is the chock formation distance, meaning that the equation is valid as long as 1<σ . Also it might be worth noticing that t′ represents a reference frame moving at speed 0c i.e. at the speed of sound. The Fubini’s solution is easily calculated but has its limitations. Nevertheless it gives a fair understanding of the demodulation phenomena previously described. As an example a simulation has been performed and shown in fig. 5 of a decaying sine wave calculated with Fubini’s solution.

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Fig 5: Decay of a sine-wave calculated with Fubini’s solution

2.2.2. The Burgers equation The Burgers equation is an approximation to a more exact second-order equation which can be solved exactly. It properly describes the combined effects of nonlinearity and losses for plane progressive waves. The equation has the following appearance:

tp

ctp

cxp

′∂∂

=′∂

∂−

∂∂ 2

300

2

2

30 22 ρ

βδ Eq. 3

Where ζ is the sound diffusivity, 0/ cxtt −=′ is the retarded time, β is a nonlinearity coefficient of the medium, 0c is the speed of sound and 0ρ is the ambient density of fluid. It is also worth noting that the above equation can be extended the generalized Burgers equation which can handle convergence (or divergence) of both progressive spherical and cylindrical waves. 2.2.3. The KZK (Khokhlov-Zabolotskaya-Kuznetsov) equation The large spectrum in which PD occur might have an explanation in the above mentioned mechanisms. As stated earlier the classical wave propagation model cannot account for different frequencies obtained with basically the same type of experimental set-up, but in the late 1990s a new model which describes the propagation of ultrasonic waves was introduced which is an augmentation compared to the Burgers equation. This model is the KZK (Khokhlov-Zabolotskaya-Kuznetsov) nonlinear parabolic wave equation with the following appearance:

2

22

300

3

3

30

202

222 tp

ctp

cpc

tzp

r ′∂∂

+′∂

∂+∇=

′∂∂∂

ρβδ Eq. 4

where ( )rrrr ∂∂+

∂∂=∇

12

22 Eq. 5

In the equation p denotes the sound pressure, z is the coordinate along the axis of the beam, r is the transverse radial coordinate (the soundbeam is assumed to be axisymmetric),

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0/' cztt −= is the retarded time and 0c is the sound speed. The strength of this equation is that it accounts for diffraction (first term of right hand side), thermoviscous attenuation (second term on right-hand side, δ is the diffusivity of sound) and the third term accounts for quadratic nonlinearity of the fluid ( β is the coefficient of nonlinearity and 0p is the ambient density of fluid). [15] The most interesting part of this equation is that not only does it account for diffraction and attentuation, but the third term also accounts for quadratic non-linearity of the material in which the wave travels. The interesting influence of this third term is that it demodulates waves travelling in a non-linear medium. This means that a wave travelling in the medium will shift its frequency spectrum to lower frequencies as it propagates away from the source. This is illustrated in fig. 6, where experimental results are compared to theoretical models of such a demodulation process for pressure waves travelling in oil. [15]

Fig 6:Experimental and theoretical results of the demodulation processes occurring for a pulse travelling in a

thermoviscous fluid, in this case oil [15] Since an in-depth analysis of the KZK-equation is far beyond the scope of this thesis only a simple experiment will be carried out to evaluate if there is some evidence as to claim that ultrasonic signals emitted from a PD source behaves as suggested by nonlinear acoustics. 2.3 Detection of ultrasound The problem with ultrasonic detection of PD is the very small sound pressures generated. In some reports the measured rms sound pressure is reported to be 0.2 Pa at 100 millimeter from a 1-pC discharge and a meter away it will be 0.02 Pa in oil[16]. These very small pressures are usually measured by piezo-electric transducers (illustrated in fig. 7). Their principle of operation is that they convert mechanical energy (movement, pressure) into electrical energy, using piezo-electric crystals, which is then measured.

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Fig 7: Inside of a transducer[17] Fig 8: Inside of a transducer[17] What is needed to know about the construction of this type of transducer is that the piezoelectric element is cut to 1/2 the desired wavelength. To get as much energy out of the transducer as possible, an impedance matching is placed between the active element and the face of the transducer. Optimal impedance matching is achieved by sizing the matching layer so that its thickness is 1/4 of the desired wavelength. This keeps waves that were reflected within the matching layer in phase when they exit the layer (as illustrated in fig. 8). For contact transducers, the matching layer is made from a material that has an acoustic impedance between the active element and steel. Immersion transducers have a matching layer with an acoustic impedance between the active element and water. Contact transducers also incorporate a wear plate to protect the matching layer and active element from scratching. The backing material supporting the crystal has a great influence on the damping characteristics of a transducer. Using a backing material with an impedance similar to that of the active element will produce the most effective damping. Such a transducer will have a wider bandwidth resulting in higher sensitivity. As the mismatch in impedance between the active element and the backing material increases, material penetration increases but transducer sensitivity is reduced. [17]

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3. TRANSDUCERS 3.1 Transducers used in thesis For this thesis four transducers are used, two of them from Physical Acoustics, the first is a R15α Sensor with an operating frequency range from 50 to 200 kHz, the second, WSα sensor with an operating frequency range of 100 to 1000 kHz. For this master thesis one other design has to be introduced. Since the thesis include the construction of a low-cost PD detector, a sensor had to be found since the above mentioned transducers have a price range of 300-800 Euro. The solution was a sensor which has only recently been introduced to the market. This is a so-called MEMS (MicroElectroMechanical System) sensor, which means that it is constructed with methods usually found in semiconductor production like deposition, pattering and etching. This also means that the sensor will be much cheaper than a conventional transducer, which makes them interesting for the design of a low-cost detector. The sensor selected for this thesis is the Knowles Acoustics SPM0204UD5

Also a fourth kind of transducer was used, namely a Murata MA40MF14-0B ultrasonic sensor. This is a narrow-band type contact sensor with a center frequency around 40 kHz and -87 dB sensitivity. The basic construction is very similar to that of the sensors from Physical Acoustics, but with a narrow working range. These sensors will be used as contact sensors for the cost-efficient detector.

SENSOR MODEL MANUFACTURER

FREQUENCY RANGE COST APPEARANCE

R15 alpha Physical acoustics 50-200 kHz 3 610 SEK WS alpha Physical acoustics 100-1000 kHz 4 300 SEK SPM0204UD5 Knowles Acoustics 10-65 kHz 95,60 SEK

MA40MF14-0B Murata 40 kHz 153 SEK

Table 1: Features of all sensors used for the experiments

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3.2 Expected ultrasonic and electric parameters First of all the sensitivity of the transducers is recalculated so that it is given in mV/Pa. As the sensitivity for the α15R - sensor is -63 dB (in barV µ/ ) and -62 dB (in barV µ/ ) for the

αWS - sensor, and barPa 51011 −⋅= , gives that the sensitivity for the α15R is PamVbarV /08.7/1008.710 420

63=⋅≈ −− µ , and PamVbarV /94.7/1094.710 420

62=⋅≈ −− µ for

the αWS . For the Knowles Acoustics SPM0204UD5 the sensitivity will be approx. PamV /47.410 20

47≈

− And finally for the Murata MA40MF14-0B it will be PamV /446.01010 20

87≈⋅

− . As mentioned earlier, the measured rms sound pressure is reported to be 0.2 Pa at 100 millimetres from a 1-pC discharge and a meter away it will be 0.02 Pa in oil. Unfortunately these reports seem somewhat questionable since the reference article [13] that is supposed to contain this information doesn’t support these claims. However there is an article [18] by the same author and with a similar name, but there the electrical charge is related to relative acoustic signal measured in mV, unfortunately denoted as p, which might have lead to a misinterpretation since p usually denotes pressure. Without more precise information about the sound pressure generated it is assumed that the sound generated at a distance of 100 mm from the source generate sound pressures of around 1 Pa. The desired output of the electrical pre-amplifier which is used in between the sensors and the oscilloscope used to record the readings, is in the range of volts. This means that the amplifier for the Knowles SPM0204UD5 needs amplification of 310 times, and for the Murata MA40MF14-0B of 410 times. For the Physical Acoustics transducers there is a preamplifier commercially available with a adjustable gain of 20, 40 and 60 dB. Since these cost several hundred Euros a selectable-gain amplifier was constructed based on the technical specifications of the commercially available amplifiers, but at a significantly lower cost.

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4. AMPLIFIERS AND DETECTORS 4.1 Overview of needed amplifiers and detectors This chapter describes the different types of amplifiers and detectors that were constructed within the master thesis. First the tuned bandpass detector with a high Q-value for the low-cost sensor system is described. This detector/amplifier was used together with the Murata and Knowles sensors. The Second one is the selective-gain broadband amplifier used with the Physical acoustics transducers which was built since the commercially available amplifiers for these transducers come at a very high price and it was decided that a cheaper solution had to be found, therefore one was built based on the technical specifications of the amplifier intended for use together with these transducers. 4.2 Band-pass detection system The amplifier used for the low-cost detector design will be designed as a narrow-band amplifier with a centre frequency of 40 kHz. The choice of 40 kHz as the centre frequency is made for two reasons. The first is that almost all low-cost transducers have a gain peak at this frequency and this frequency is also relatively free of ambient noise. The second reason was that there is strong evidence that acoustic PD signals occur at this frequency [4][10][12]. As stated earlier this circuit should also have the ability to present detected acoustic emissions in the form of audible sound, therefore there should be some sort of demodulation circuit which brings down the high frequencies of the ultrasound to audible frequencies. According to these specifications the layout of fig. 9 was devised and then implemented.

Fig 9: Principle of detector operation 4.2.1 Design aspects Ultrasonic transducer For this detector the transducers Knowles Acoustics SPM0204UD5 and Murata MA40MF14-0B will be used. The first is constructed to detect a wide range of acoustic signals propagating through air. The second, designed as a surface mounted sensor will be used for detecting signals propagating in solids or liquids. Preamplifier The preamplifier must be able to amplify a very small signal, in the order of a few microvolts, a couple of hundred times without adding interference. In this step no filtering can be applied

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since the signal is so weak that there is a risk that any filtering will diminish the desired signal beyond measurability. Another aspect of this part that needs to be considered is the capacitive nature of the sensors used. A low input impedance is therefore desired on the preamplifier so that ringing in the capacitive circuit can be eliminated faster. In order to fulfil these specifications a CE-step was chosen as preamplifier since it possesses all the features required: adjustable input impedance, high amplification and low distortions. After performing the design process outlined in appendix A, the circuit shown in fig. 10 was obtained.

Fig. 10 The preamplifier, a CE-step with a low input impedance

and an amplification of about 100 times For a detailed circuit analysis and design method outline the reader is referred to the appendix, but the most important aspects of this design is that the input impedance is approximately300 Ω , which is rather low for an amplifier, and the amplification is around 100 times. Bandpass amplifier The amplifier consists of four coupled operational amplifier steps, each based on a modified Deliyannis filter [18]. The filters are based on the TL074 operational amplifier, which together with a couple of passive components form a second order narrow bandpass filter. In this application the Q factor and gain are set to 10. The reason for this is that a small amplification is desired in every step and the operational amplifiers only have a certain margin of amplification that cannot be passed (in this case approximately 75 times amplification), there are also certain stability issues involved in higher gains and Q-factors. After that the design process has been performed as outlined in appendix B the circuit shown in fig. 11 is obtained.

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Fig. 11 One part of the narrowband amplifier based on a Deliyannis second

order bandpass filter

Each step is also separated from the next one in terms of DC-component by adding a blocking 68 nF capacitor at the input of each amplifier step. It should also be mentioned that there was a deliberate choice of not including any inductances in the circuit for two reasons, first to avoid any coupling to the high electrical and magnetic fields present in the vicinity of the amplifier, and also because inductors are hard to produce with a given inductance, and therefore are expensive. Multiplier The multiplier is a circuit that multiplies two signals with each other. The concept which is utilized in this case is called heterodyning. The basic idea is to demodulate the high frequency ultrasonic sounds picked up by the transducer to the audible range. This is done by multiplying the amplifier output signal with a reference signal. In the case of two sinusoidal input signals to the multiplier the following trigonometric identity can be used:

)cos(21)cos(

21sinsin ϕθϕθϕθ +−−= Eq. 6

or

( ) ( ) [ ] [ ]tfftfftftf )(2cos21)(2cos

212sin2sin 212121 +−−= ππππ Eq. 7

This states that two sine wave signals multiplied with each other produce two signals, one with the frequency 21 ff − , and the second with the frequency 21 ff + . In this case we know that the amplified transducer signal will be at =1f 40 kHz, and then we choose the external clock signal to =2f 38 kHz, we will get two signals at the output. The first at 2 kHz, which is in the audible range, and the second at 78 kHz, which is unwanted and can be filtered away by a simple RC low-pass filter at the multiplier output. As a note it might be mentioned that the external clock signal in this case was provided by a function generator outside the circuit for easy tuning purposes, but it can easily be implemented on the circuit itself with a Wien-bridge oscillator for a sine wave signal or a NE555-timer for a square-wave signal. For use as a multiplier in this application the AD633JNZ produced by Analog devices was chosen mainly for its comparatively low cost and large availability on the market.

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Audio amplifier The audio amplifier selected in this design is the LM386, a low-cost, low-voltage audio power amplifier which is sufficient to power a pair of headphones. It also requires a very small number of components in order to operate. Power supply The entire circuit was fed from a split power supply consisting of two standard 9V batteries, except for the Knowles SPM0204UD5, which requires a voltage source of 1,5-3 volts to operate. This was first realized by a voltage regulator, but since this introduced a lot of ripple in the supply voltages thus affecting the amplifier a separate power source consisting of two 1,5 V batteries was used. 4.2.2 Modelling To simulate the circuit behaviour the preamplifier and narrowband amplifier were simulated in the Orcad Pspice simulator. The simulation of the circuits yielded the following gain and phase margin curves for the CE-step used as preamplifier:

Fig 12: Gain curve of preamplifier

Fig 13: Phase curve of the preamplifier

The gain curve in fig. 12 show that the amplifier gain starts at around -60dB, crosses unity gain at 200 Hz and stabilizes at 40 dB around 10 kHz. The phase curve in fig. 13 indicates that the phase margin is acceptable, and that the circuit is closed-loop stable.

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As to the narrowband amplifier, the simulation results were as follows:

Fig 14: Gain curve for each amplification step of the narrowband amplifier

Fig 15: Zoomed in gain curve for each amplification step of narrowband amplifier

Fig 16: Phase curve of one amplifier step

From the gain curve it is easy to determine that the amplifier indeed will feature a band-pass character with a relatively high Q-factor. Due to the narrow band-pass character the amplifier is expected to have a small phase margin, which is also verified in the simulation. Due to this, the amplifier will be prone to oscillations when operating. This also gives an indication of that the amplifier is operating on its stability margin which was mentioned earlier. 4.2.3 Implementation

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The biggest issue discovered during implementation which didn’t occur during simulation was ripple found in the supply voltages. This ripple in turn caused stability issues in the narrowband amplifier, therefore the transducer received a separate power supply and coupling capacitors were introduced to the power rails of the operational amplifiers in order to reduce the ripple in supply voltage, which eventually solved the problem. Another issue was the audio output of the detector. The problem was to find suitable parameters for the reference clock, which was done by tuning the signal generator to different frequencies and simultaneously adjusting the voltage. Finally it was decided that the best audibility was achieved at 37 kHz with a 200=ppV mV on the reference clock. There also were some problems with the narrow-band amplifier, since the components used (i.e. resistors and capacitors) have a certain tolerance. This caused the peak frequencies of each step to be shifted from the ideal of 40 kHz. 4.2.4 Verification The verification was made in such way that the part of the detector circuit tested was fed by a well-defined input signal delivered by a function generator, and the output(s) were measured with an oscilloscope. This procedure yielded the following results shown in fig. 17-18.

Fig. 17: Gain curve of preamplifier

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Fig. 18: Gain curve of narrowband amplifier

From the above curves it is noted that both the preamplifier and the narrowband amplifier are in good agreement with the simulated results. Also as expected the narrowband amplifier has the peaks of each amplifier step at different frequencies which deviate from the simulated results. From the measurements it was assessed that the narrowband amplifier had an overall peak response for 37 kHz, and not 40 kHz as designed. 4.3 Broadband amplifier The broadband amplifier, intended for use together with the transducers from Physical Acoustics, is a fairly straightforward construction with a flat gain in the frequency range from 10 kHz to 1 MHz, a high input impedance, low noise and a Common-mode rejection ratio (CMRR) of 42 dB. The gain also has to be adjustable in the range 20, 40 and 60 dB. The overall design concept is presented in fig. 24. The Common-mode rejection ratio (CMRR) of the amplifier is a very useful feature which usually isn’t considered when operational amplifiers are being used, but in certain applications it needs to be considered. In this case it is of interest since there will be large voltage swings in the last amplifier and therefore it might be easier for that amplifier to saturate, which is an undesired situation. First of all the equation which considers the common-mode has the following appearance:

)(2

)( −+−+ ++−= VVAVVAV cmdout Eq. 8

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In this equation the desired differential gain is denoted dA and the undesired common-mode gain is denoted cmA . Intuitively this equation can be understood as that the output of an amplifier is the difference on the input multiplied with differential gain plus the sum of the inputs times the common-mode gain. Usually the common-mode gain is much lower than the differential gain, and from this relation the common-mode rejection ratio is defined as:

=

cm

d

AACMRR 10log20 Eq. 9

4.3.1 Design aspects The implementation of this amplifier requires a better operational amplifier than the previously used TL074, since the amplifier needs to produce a gain in a higher frequency range. Therefore the AD817 operational amplifier is chosen as the main component since it features all the necessary specifications. It has a CMRR of 100 dB, the unity gain bandwidth is 50 MHz, and the input impedance is 300 k Ω .

Fig 19: Non-inverting amplifier

The amplifiers will be connected in a non-inverting configuration, presented in fig. 19, and then series connected, as shown in fig. 20, with tapping of the signal at each of the amplifier output terminals. The gain is set by

inout VRRV

+=

1

21 Eq. 10

Since the gain is supposed to be 20dB (10 times) per step, the resistors are chosen as

181 =R Ωk and 1802 =R Ωk . This gives a gain of 11. This little higher gain is chosen so that the effect of the DC blocking capacitors in between every step is compensated. A low-pass network is added on the output terminal in order to limit the bandwidth of the amplifier to approximately 1 MHz. This network consists of an RC-link in series between the output terminal of the operational amplifier and ground, as seen in fig. 21. This network will have a cut-off frequency equal to 4.723)1022102/(121 9 =⋅⋅⋅⋅== −ππRCfc kHz . Another very important aspect of this amplifier is that the positive input of the operational amplifier has a resistance of 18 Ωk to ground, which is equal to the ground resistance of the negative input. The reason for this seemingly unnecessary resistance is that it ensures that the bias currents of the inputs are equal, thus ensuring that the offset voltage on the output is kept minimal.

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Fig 20: Principle of amplifier operation

4.3.2 Modelling The amplifier is modelled using the Orcad Pspice simulator which gives the results presented in fig. 21-23.

Fig 21: schematic view of the cascaded broadband amplifier

Fig 22: Gain curve of broadband amplifier

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Fig 23: Phase curve of broadband amplifier

The simulation shows that the gain is as expected in the desired interval. From the phase curve the amplifiers are judged to be very stable, and therefore with little or no oscillations due to instability. 4.3.3 Implementation The main difference between the simulation and implementation was that decoupling capacitors were added on the power rails in order to eliminate ripple in the supply voltages. One problem which was discovered in the implementation was that whenever one of the operational amplifiers saturated there was a significant amount of ripple in the supply voltages. The solution to this problem was to add another switch which allowed the last amplifier to be disconnected, which solved the problem with saturation and power rail ripple. Another issue was that the low-pass links were removed since it was realised that the cut-off at higher frequencies was unnecessary to implement, since it had no impact on the desired measurements. Another major issue which was discovered during the implementation was that there was large capacitive coupling present in the circuit which demonstrated itself as lower gains at increasing frequencies, unfortunately this problem was never resolved mainly because it was judged that the impact on the overall performance was negligible. 4.3.4 Verification

Fig. 24 Gain curve of broadband amplifier

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The verification shows that the amplifier is working almost as expected. However compared to the simulations the gain in lower frequencies is approximately 57 dB, which is slightly lower than the expected value, as shown in fig. 24. Another interesting aspect is the decrease in gain at frequencies above 500 kHz for the last amplifier. This is caused by stray capacitances within the circuit, which were introduced when the last amplifier was connected to a switch and long connection leads were required in order to achieve that. This is a perfect example of a type of phenomenon that cannot be simulated with Spice. Despite of the shortcomings in the last amplifier step the design is still useful. It provides sufficient amplification up to a frequency where most of the signal is expected to be. In order to cure this problem, methods that eliminate the stray capacitances should be applied. These methods include using as short interconnecting leads as possible together with a ground plane. However since time was limited, the decision was made that the amplifier is good enough to use.

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5. LABORATORY SETUP FOR PD DETECTION USING ULTRASOUND 5.1 Experimental setup For the practical experiments two separate voltage sources were used to generate the high voltages necessary, the first source is a TREK 30/30 High Voltage amplifier, controllable both in voltage and frequency, which can deliver up to 30 kV. This source was used for corona in air experiments, since this type of discharge doesn’t require voltages above 30 kV due to the lower PD inception field strength of air compared to oil. The second source is a 100 kV transformer which is controllable in voltage. The main detection system used in the experimental setup is an ICM system provided by Power Diagnostix, seen in fig. 31. The ICM system is decoupled with a H.V. capacitor in order to protect the system in case of a full breakdown in the test specimen. This capacitor can bee seen as the red column standing on the right in fig. 27, also the H.V. transformer can be seen in the picture appearing as a blue barrel standing on the left. The test chamber where the experimental setups were exposed to high voltages consisted of a transformer oil-filled 33x33x33 cm grounded steel tank with circular observation windows mounted on two sides. The contact transducers used for the experiment were attached to these observation windows with duct tape (fig. 27) and a viscous gel was applied to the sensors to ensure proper acoustical coupling. The Knowles sensor used to detect PD through air was placed at a distance of approx. 1 meter away from the test chamber (fig. 28), and a funnel belonging to another ultrasonic measurement instrument was placed as a waveguide in front of the sensor. For the experiment where the Knowles sensor was used to detect corona in air (fig. 29) there were two reference instruments used to detect PD, first as in the previously mentioned experiment the ICM system was connected but also a second instrument which detects ultrasonic waves was used as a reference. This instrument, provided by Tettex (fig. 30), gave some reference as to how the audible detection was working. Also waveguides belonging to this instrument was used to increase the gain of the ultrasounds emitted for both instruments.

Fig 25: Experimental setup in laboratory [19] Fig 26: Experimental setup used for thesis

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Fig 27: Sensor attached to steel tank Fig 28: Air sensor used together with attached sensor

Fig 29: Test setup for testing corona in air. ICM system and voltage source also visible

Fig 30: Tettex ultrasonic detector Fig 31: ICM system 5.2 Phase resolved PD measurement equipment The ICM system from Power Diagnostix as seen in fig. 31 is used as a reference in the laboratory experiments. It is a digital partial discharge detector which detects the current pulses that are generated by a PD. This instrument is widely used in both academical and commercial applications.

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This instrument is designed in such a way that PD’s are logged and categorized accordingly to its apparent charge and the occurrence relative the phase of the supply voltage. This is then displayed as a phase-resolved PD pattern as can be seen in fig. 4. 5.3 Test objects For the experiments a couple of different test setups were used in order to simulate different situations in which PD occur and these are listed below. 5.3.1. Test object for Corona in air The test object which was used to simulate corona discharges in air is a modified point-plane setup with a steel hemisphere used as ground plane and a needle connected to high voltage placed in the center of the hemisphere which can bee seen in fig. 32. This set-up has an apparent charge for negative PD of 200 pC.

Fig. 32: Air-corona source

5.3.2. Canonical Test objects for PD in transformers The other test objects used were immersed in the steel tank in order to investigate void, surface and corona discharges in oil. For simulation of void discharges a stack of 15 transformer insulation papers with air bubbles trapped between the papers was mounted between two brass electrodes and then immersed in oil. For surface discharges two brass electrodes were used where a pressboard placed in between the electrodes guaranteed that no full breakdown of the gap could occur. The last setup used consisted of a needle-plane setup for simulating corona discharges. Once again a pressboard was used to prevent a full breakdown of the gap.

Fig 33: Test setups for Surface, Void and Corona discharges, with expected PD activity marked in red

5.3.3. Test object for investigation of distance dependence of frequency spectra For the experiment where the dependence between frequency and distance was tested, the experimental setup, schematically drawn in fig. 34, consisted of a movable PD source immersed in a transformer-oil filled Plexiglas pipe with a diameter of 10 cm and energized by a 100 kV transformer. At the bottom a WSα and a α15R transducer from Physical Acoustics

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connected in parallel to the amplifier was mounted on the surface of the lid. The reason for using multiple sensors is their respective bandwidth, since if the two sensors are combined the detection system will have a bandwidth from 50 kHz to 1 MHz, which was done in order to investigate as broad spectrum as possible. A proper acoustical coupling was guaranteed by adding a viscous gel between the lid and the sensors. The PD source itself consists of a PVC pipe with a High-voltage centred electrode surrounded by a grounded copper shield, which is visible in fig. 35. This PD source will generate corona discharges when exposed to high voltages. The frequency spectrum emitted by the PD source will then be investigated, and if the frequency spectrum tends to move to lower frequencies as the PD source is moved away from the transducer this is a strong indication of non-linear demodulation processes. On the other hand, if the PD follows classical wave propagation models, the received spectrum will be similar independently of the distance from the source.

Fig 34: Schematic figure of experimental setup for testing Fig. 35 Cross-sectional view of the PD source itself. frequency dependence

Fig 36: Experimental setup for testing frequency dependence

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6. Results 6.1 PD patterns for different situations Here follows a presentation of the waveforms acquired during the experiments and their comparison to the reference measurement instrumentation already in use where applicable. 6.1.1 Corona in air

Fig 37: background noise (electrical and acoustical) Fig 38: Detected PD compared to the supply line voltage 1 meter from PD source 1,5 meters away from PD source

Fig 39: Detected PD under AC supply voltage Fig 40: Detected PD under DC supply voltage 1 meter from PD source 1 meter from PD source The experiments proved that a 200 pC PD could be clearly detected up to 1,5 meters away from the actual discharge site (fig. 38). This was a better result than could be obtained with the Tettex ultrasonic sensor which only detected the discharge at a range of 75 centimetres. This also suggests that low-cost MEMS-based sensors are a viable alternative for detecting PD in air. Unfortunately no waveforms from the Tettex instrument could be acquired since it is only equipped with a pair of earphones through which the operator can hear the PD. The assumption that an acoustic PD contains a 40 kHz component also was confirmed. Also as it can be seen in the oscilloscope figures there was a sufficiently large signal to noise ratio when discussing in terms of ambient noise, which can bee seen in fig. 37 compared to fig. 38. It should be noted that no special precautions were made to eliminate background noise since the conditions for testing should be as similar as possible to a field measurement situation. One feature that should be noticed is that in fig. 38 there is almost a phase-shift of 90 degrees between where the PD actually occurred (in the peak of the negative voltage) and the measured acoustic PD signal. This difference is mainly caused by finite sound propagation speed and a delay in the amplifier circuit. Unless care is taken when analyzing such signals

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one can be mislead to think that the PD displayed in fig 38 is caused by a void discharge which in this case is incorrect. The experiment also shows that the Knowles sensor is useful both for AC and DC corona, the latter demonstrated in fig 40, but if the noise level from fig. 37 is unknown, DC corona may be dismissed as background noise, which would be incorrect. 6.1.2 Corona in oil

Fig 41: Negative corona, amplifier gain 60 dB, leading edge Fig 42: Negative corona, amplifier gain 60 dB, full signal

Fig 43: Positive corona, amplifier gain 60 dB , full signal Fig 44: Positive corona, amplifier gain 60 dB, leading edge The results from the experiments where corona in oil occurred showed that both positive and negative corona could be detected, the differences noticeable were that positive corona generated higher signal peaks than negative corona, which was sometimes barely distinguishable from the background noise. Also the signal from positive corona faded more slowly than the signal from negative corona, as seen in fig. 43. Both of these results suggest that positive corona contains more energy than negative, which already is known. Another interesting result in these experiments is that the bulk of the detected signal is preceded by a sharp spike occurring for both positive and negative corona, as seen in fig 41 and fig 44. The most probable explanation for this phenomenon is that it has something to do with how the acoustic wave propagates. The suspected mechanism is that the first high-frequency spike has travelled through a medium which has a small acoustic nonlinearity and high wave propagation speeds, in this case the setup frame and steel tank, and the second burst with a considerably lower frequency has travelled through a medium with high acoustic nonlinearity and lower wave propagation speeds, like the transformer oil.

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The experiment also suggests that there is a difference in the acoustic emissions of positive and negative corona since the positive corona demonstrates an exponential decay visible in fig. 43 as the positive corona is more randomly distributed as in fig. 42. 6.1.3 Surface discharge

Fig 45: Suspected corona discharge, amplifier gain 60 dB Fig 46: Surface discharge, amplifier gain 60 dB with similar discharges both for negative and positive half-cycle

Fig 47: Surface discharge, amplifier gain 60 dB Fig 48: Acoustically well shielded surface discharge, amplifier gain 60 dB In the experiment involving surface discharges a wide variety of different signals was obtained. The most probable explanation is that other types of discharges than surface discharges were present during the experiment, like in fig. 45 which shows a greater resemblance to corona discharges than to a surface discharge in fig. 47. This is probably due to the fact that there are corona discharges present at the edges of the brass electrodes due to carbonization of the pressboard layer or possibly gas bubbles within the setup. An interesting aspect visible in fig. 46 is that it appears that the acoustic energy contained in both positive and negative surface discharges is similar, but the experiment also indicates that there is a difference in discharge strength probably connected to where the discharge takes place, deep inside the test setup or somewhere near the edge. The acoustic PD signals from the surface discharges also suggest that there are two separate bulks of the signal. The first larger in amplitude than the second, both with a somewhat random waveform.

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As it is shown in fig. 48, some discharges are more or less acoustically shielded, this in turn affects the properties of the registered waveforms, sometimes occurring like large spikes in the oscilloscope pictures. 6.1.4 Void discharge This experimental setup yielded no result for the acoustical detection methods. There were discharges present which could be recorded through the ICM system, but not on any of the acoustical sensors. This is probably due to the screening effect of the insulation paper used, which doesn’t allow the pressure waves formed to exit the test setup. Basically this experiment shows that acoustic detection of void discharges seem to be impractical. There has been some research into this field [20] which suggests that the minimum value that can be detected for void discharges at a range of 100 cm is approx. 1000 pC, or even up to 10 000 pC if the discharge site is well shielded, which is a very powerful and completely unacceptable discharge within any type of high voltage apparatus. However the situation in the real world might be different from laboratory conditions, since in a transformer where void discharges usually occur there might be a better acoustic coupling due to the core or the windings being closer to the discharge site thus allowing acoustic waves to pass through them and further on to the sensors by the transformer tank wall. 6.2 Frequency dependence in PD signals as function of the distance The experiment was conducted so that the waveforms were acquired with two simultaneously connected sensors from Physical acoustics for negative corona discharges with the Agilent oscilloscope at a sample rate of 50 Msamples/sec, and then the FFT transform was applied in a Matlab environment, which gave the following frequency spectras:

Fig 49: Time domain signal and frequency domain distribution for the short distance

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Fig 50: Time domain signal and frequency domain distribution for the long distance

The two previous signals were chosen as representative for the test runs. From their frequency distribution it is clear that the distance has an impact on the frequency distribution of the signal. This impact is also as predicted by non-linear acoustics, which suggests that demodulation processes in a non-linear medium will shift the frequency spectrum towards lower frequencies with increasing distance. This is a clear indication that there are demodulation processes present and that these should be considered when discussing frequency spectras of PD, which up until now seems to have been unknown to the community studying PD. These tests should however be concerned as a strong indication of demodulation processes, but still not treated as conclusive evidence. Further investigations are required in order to eliminate other possible mechanisms that affect the test results. It should also be mentioned that the test setup itself is much idealized in comparison to real world situations where the wave propagation paths are usually very complex and passing through several different types of materials like paper, copper aluminium and so on. Also the oil itself was kept at the same temperature, but in real transformers there is always a temperature distribution with hot oil at the top, and colder oil at the bottom, not to mention that usually the oil also has a certain flow. 6.3 Comparison of PD Patterns for different situations When comparing different acoustic PD patterns obtained during the experiments there are some features that might allow different types of PD to be distinguished from each other. In the experiments conducted for this thesis the corona discharges were clearly distinguishable because the main signal was preceded by a sharp high-frequency spike. However since only one type of source was used for corona there is a lack of evidence that

-40-

this is a feature characterizing all types of corona discharges or only the particular set-up used in the experiments. Surface discharges seem to be more oscillative in their nature, generating more random signals than the exponentially decaying signals produced by corona discharges. The length of the signal itself may also provide some information as to the type of PD generated, since corona discharges seem to generate shorter bursts of acoustic energy than surface discharges. Another source of information might lie in the energy contained within a PD signal. Corona discharges clearly have a bigger acoustic energy than surface discharges because the PD event is more acoustically exposed in the case of corona than the surface discharge. Since no data is available for void discharges there is no basis to conduct an analysis. However a more fundamental investigation should be conducted using many types of different voids, both in size and material in order to fully discard the usefulness of acoustic measurements of void discharges. Also as discussed earlier there might a somewhat different situation in a real transformer which might facilitate void discharge measurements. 6.4 Comparison of different PD detection methods A comparison of all available sensors was also made for the cases of corona in oil and surface discharge in oil. 6.4.1 Corona in oil For this experimental set-up a comparison was conducted between the ICM system (green traces in the oscillograms), the Physical Acoustics 1MHz sensors (Red traces in the oscillograms) and the Murata MA40MF14-0B (Blue traces in the oscillogram). These experiments yielded the results presented in fig. 51-55:

Fig 51: Negative corona detected by three separate sensor arrays Fig 52: Negative corona with large spikes on acoustic sensors

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Fig 53: Void discharges detected by ICM system, but no Fig 54: Negative corona detected by the broadband acoustic discharges within the test object sensor

Fig 55: Negative corona which is acoustically detectable, but not electrically

The results obtained showed that the acoustical methods are more sensitive than the electrical measurements (fig. 51), and that discharges that are barely detectable electrically give rise to high acoustic peaks (fig. 52 and 55), and sometimes the corona cannot be detected at all electrically (fig 54-55). This is caused by the fact that the ICM system signal has a too high noise level to distinguish these PDs and therefore doesn’t react since the signal is buried in the noise. Another very interesting aspect which shows the strength of acoustic PD measurement are the electrical spikes detected by the ICM system at zero crossings (fig. 53-54), these are caused by a void somewhere in the setup, but the acoustic detection allows us to eliminate the test setup as the source of these void discharges. This is a common problem which is often encountered during electrical PD measurements on real equipment that PD pulses are propagated within electrical systems and give false readings as to the tested object. This error source can be eliminated with acoustic measurement since these measurements are measuring the actual source and cannot be influenced by other components which might be located as far as a couple kilometres away from the test object. Another test that was performed on corona in oil was to investigate if it is possible to detect corona discharges outside of the test tank at a certain distance with the air coupled sensor. This was done by placing the Knowles SPM0204UD5 sensor at a distance of approximately 50 cm from the transformer tank and simultaneously read the Physical Acoustics sensor placed on the tank wall with the Knowles sensor. This yielded the following result with green traces belonging to the Physical Acoustics sensor and yellow traces belonging to the Knowles sensor:

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Fig 56: Negative corona, electrically detected Fig 57: Negative corona, electrically detected

Fig 58: Positive corona, detected both Fig 59: Positive corona, detected both electrically and acoustically electrically and acoustically The results showed that negative corona could not be detected with the Knowles sensor (fig. 56-57). However, positive corona was detectable (fig. 58-59) which proves the concept that measurement sensors don’t have to be directly coupled to the test object in order to detect PD. The benefit being that even equipment under high voltage can be monitored for PD activity without using costly setups to allow the PD sensors to be mounted in areas with strong electrical fields. 6.4.2 Surface discharge in oil For this set-up a comparison was conducted for the ICM system (green traces in the oscillograms), the Physical Acoustics 1MHz sensors (Red traces in the oscillograms) and the Murata MA40MF14-0B (Blue traces in the oscillogram). These experiments yielded the results shown in fig. 60-63.

Fig 60: void discharges detected by two arrays Fig 61: positive and negative surface discharges

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Fig 62: positive and negative surface discharge Fig 63: Void discharges, propably not present within the test setup The results from this experiment indicates that all three sensors were able to detect PD under both positive and negative voltage. What is even more interesting are the void discharges that were present during this test run. These were formed after that the test object had been stressed with high voltage for some time, and at first only the ICM system detected these voids (fig. 63) but after a while there was acoustical signals present as well (fig. 60). Another interesting aspect is the difference between fig. 61 and fig. 62, where the surface discharges are at first detectable with both of the acoustical sensors and only 6 seconds later they are only detectable on the tuned 40 kHz-sensor. If the assumption is made that the signal follows nonlinear acoustic principles this suggests that the PD signal received in fig. 62 has travelled a longer distance in the oil or through an acoustically more non-linear media. This insight seems to be a completely new approach on how PD sources can be localized within a test sample based on the frequency content of the received signal. Up until now the most common method to position PD with the use of acoustic sensors is based on triangulation schemes which requires three or more transducers and some signal processing, but if the frequency content of the signal could be used for this purpose one sensor and one signal could be sufficient to give a good estimation as to where in the test specimen PD occurs.

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7. CONCLUSIONS The work conducted during this thesis fulfils the criteria’s that were set as goals. The difference in the acoustic signature of different types of discharges has been investigated and with a good certainty these results hold. Also a proof of concept has been mad as to the low-cost detector solutions and their usefulness has also been demonstrated within the work. Two amplifiers have been constructed which meet the desired specifications and it has also been verified accordingly. However there is still much work that can be done to the narrowband amplifier in order to get a better signal-to-noise ratio and an overall better and maybe cheaper design. Also field testing is required in order to verify the usefulness of these amplifiers, since there still might be aspects which cannot be simulated in the laboratory but rather needs to be field tested. This might include EMI and other disturbance sources, both electrical and acoustical. There is still a lot of work to be done in order for the amplifiers to be mass-produced, since right now they are mounted on a lab experimental board with a lot of wiring which is unacceptable in a finished product. Some consideration as to the choice of components also has to be done since it might be easier and cheaper to produce amplifier boards with surface mounted components which is a path that has not been pursued in this thesis. Another path which couldn’t be fully pursued is the issue of wave propagation within oil, but the experiment conducted within the frame of this thesis showed that there is a correlation between the distance from a PD source and the frequency spectrum from its acoustical emissions, which suggest a nonlinear acoustic behaviour of acoustic PD signals The conclusions that can be drawn from the work conducted is that acoustic emission detection has been proved to be a powerful method for detection and classification of PD, but from the work done the conclusion is also drawn that the more information from many different sources that is available the easier it is to characterize the PD. Therefore acoustic emission detection from PD sources can and should be used as one method of detecting PD, but an effort to increase the knowledge of the underlying mechanisms should be performed.

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8. FUTURE WORK There still remains a lot of work to be done to fully understand the acoustical emissions of partial discharges. A more thorough investigation of the propagation paths of these emissions should also be carried out in order to develop the understanding of how different materials affect the frequency content of signals. Another interesting aspect is that most of the fundamental work on PD has been conducted almost 40 years ago. Therefore there is an interest in repeating these old experiments but with equipment which is available today, i.e. fast oscilloscopes, computers, better sensors, etc.

-46-

9. REFERENCES [1]D. König, Y.N. Rao, Partial Discharges in Electrical Power Apparatus. Berlin; Offenbach: VDE-Verlag, 1993, pp. 15-36 [2] Stone, G.C.; , "Partial discharge. VII. Practical techniques for measuring PD in operating equipment," IEEE Electrical Insulation Magazine, vol.7, no.4, pp.9-19, July-Aug. 1991 [3] Boggs, S.A.; , "Partial discharge: overview and signal generation," IEEE Electrical Insulation Magazine, , vol.6, no.4, pp.33-39, July-Aug. 1990 [4] Howells, E.; Norton, E. T.; , "Detection of Partial Discharges in Transformers Using Acoustic Emission Techniques," IEEE Transactions on Power Apparatus and Systems, vol. PAS-97, no.5, pp.1538-1549, Sept. 1978 [5] Kemp, I.J.; , "Partial discharge plant-monitoring technology: present and future developments," IEEE Proceedings - Science, Measurement and Technology, vol.142, no.1, pp.4-10, Jan 1995 [6] Duval, M.; Dukarm, J.; , "Improving the reliability of transformer gas-in-oil diagnosis," IEEE Electrical Insulation Magazine, vol.21, no.4, pp.21-27, July-Aug. 2005 [7] Lundgaard, L.E.; , "Partial discharge. XIII. Acoustic partial discharge detection- Fundamental considerations," IEEE Electrical Insulation Magazine, vol.8, pp.25-31, Sept.-Oct. 1992 [8] Anderson, J. G.; , "Ultrasonic Detection and Location of Electric Discharges in Insulating Structures," Power Apparatus and Systems, Part III. Transactions of the American Institute of Electrical Engineers , vol.75, no.3, pp.1193-1198, Jan. 1956 [9] Lundgaard, L.E.; , "Partial discharge. XIV. Acoustic partial discharge detection-practical application," IEEE Electrical Insulation Magazine, vol.8, no.5, pp.34-43, Sept.-Oct. 1992 [10] Markalous, S.; Tenbohlen, S.; Feser, K.; , "Detection and location of partial discharges in power transformers using acoustic and electromagnetic signals," IEEE Transactions on Dielectrics and Electrical Insulation, , vol.15, no.6, pp.1576-1583, December 2008 [11]Sarathi, R.; Singh, P.D.; Danikas, M.G.;, “Characterization of partial discharges in transformer oil insulation under AC and DC voltage using acoustic emission technique” Journal of electrical engineering, vol.58, no.2, pp.91-97, 2007 [12] Harrold, R.T.; , "Ultrasonic Spectrum Signatures of Under-Oil Corona Sources," IEEE Transactions on Electrical Insulation, vol.EI-10, no.4, pp.109-112, Dec. 1975 [13]Beyer, M.; Borsi, H.; Hartje, M.;, “Some aspects about possibilities and limitations of acoustical partial discharge (PD) measurements in Insulation fluids”, 5th international symposium on High Voltage Engineering, Braunschweig, Germany, 24-28. August 1987 [14] Internet: http://en.wikipedia.org/wiki/Nonlinear_acoustics, march 9, 2012 [Apr. 27, 2012] [15] Averkiou, M.A.; Lee, Y-S.; Hamilton, M.F.;, “Self-demodulation of amplitude- and frequency-modulated pulses in a thermoviscous fluid” Journal of Acoustical society of America, pp. 2876-2883, 1993 [16] Mark MacAlpine, Zhao Zhiqiang, M. Suleyman Demokan, “Development of a fiber-optic sensor for partial discharges in oil-filled power transformers”, Electric Power System Research, vol. 63, pp. 27-36, 2002 [17] S. Joy. ”about instrumentation; A blog for Instrumentation engineering Students” Internet: http://aboutinstrumentation.blogspot.se/2012/01/piezoelectric-transducers.html, Apr. 14, 2012 [Apr. 14, 2012] [18] Sedra, A.; Ghorab, M.; Martin, K.; , "Optimum configurations for single-amplifier biquadratic filters," IEEE Transactions on Circuits and Systems, vol.27, no.12, pp. 1155- 1163, Dec 1980

-47-

[19] Niasar, M.G.; Edin, H;, ”Corona in Oil as a Function of Geometry, Temperature and Humidity”, KTH Electrical engineering, [20] Harrold, R.T.; , "The Relationship Between Ultrasonic and Electrical Measurements of Under-Oil Corona Sources," IEEE Transactions on Electrical Insulation, vol.EI-11, no.1, pp.8-11, March 1976

-48-

APPENDIX A: DESIGN PROCESS OF A TRANSISTOR AMPLIFIER In this appendix the outline for designing a Common Emitter amplifier is given. The design process of the amplifier used in the thesis is presented. The descriptions in this appendix are kept very short and in order to fully understand the concepts the reader is referred to a textbook on the subject [1]. The Common-Emitter amplifier basic outline is that of fig. 1 when using a NPN transistor. What has to be done is to choose suitable values of 121 ,,,, CRRRR EL and 2C . In the amplifier used for the PD detector the following design criteria are given:

- Input impedance of Ω300 - A signal gain of 100≈

Fig. A1: A CE-amplifier Fig. A2: A CE-amplifier with the nomenclature used below

First of all the AC properties of the amplifier are investigated. For that purpose the small signal model of the transistor is applied

Fig A3: Small signal model of Amplifier

After applying Kirchhoff’s Voltage and Current laws the following result is obtained:

ieoec

fec

in

outvs hhR

hRVVA

)1( +== Eq. A1

Then the values for the transistor used, 2N2222A, are obtained from the datasheet assuming a collector current of 10 mA:

Shhh oefeie µ113225750 ==Ω=

-49-

This in turn gives that

( )

( )3603803.346

1≈=

⋅⋅−

⋅

=

fe

oeievs

fe

ievs

c

hhhAh

hA

R Ω Eq. A2

Now in order to meet the desired AC input resistance at 300=inR Ω we conclude that

iein hRRR //// 21= , let 21 // RRReq = then:

500=−⋅

=⇔+⋅

=inie

inieeq

eqie

eqiein Rh

RhRRhRh

R Ω Eq. A3

The desired AC properties are now met, and therefore it is time to turn the attention to finding a suitable DC operating point for the amplifier. In order to do this the Thevenin-equivalent to the left of the x:es in fig 4 is applied to the circuit. This gives the resulting schematic as in fig. 5.

Fig A4: DC-biasing of the Fig 5: Thevenin-equivalent of the amplifier input CE-amplifier The values of eqV and eqR are given by

Ω=−⋅

= 500inie

inieeq Rh

RhR Eq. A4

)( 21

2

RRRVV cceq +

= Eq. A5

Applying Kirchoffs Voltage law around the input and output loops with the approximation that ec II −≈ and VVbe 65.0= gives the following equations:

eceqbeq

eccecccc

RIRIVRIVIRV

++=++=

65.0( )

)2(1

Eq. A6-A7

Since mAIc 10= and 44≈=⇒=fe

cbbfec h

IIIhI Aµ Eq. A8

-50-

If ceV now is chosen in the middle of the operating range, 5.42

92

===VVV cc

ce V , this allows

the input signal to operate within the linear region of the amplifier. The assumption made here is that the amplifier is fed from a 9 Volt DC source, and therefore 9=ccV V . If this value of

ceV is then inserted into equation (1) together with all other known values it gives that Ω≈Ω= 100103.6197 eR (Resistor value adapted to E12-series). With this resistor calculated

the value of eqV is calculated, which gives the value 7084.1=eqV V . This is then used to calculate 1R and 2R according to:

2.72.6340k1 ≈Ω=

−

+

−⋅

=

eqs

eq

eqeqs

eqeq

VVV

RVVRV

R Ωk Eq. A9

1501.61712 =−

=eqs

eq

VVV

RR 620≈Ω Ω Eq. A10

The values that are still left to decide are the ones of 1C and 2C . The first capacitor, 1C , is used to block DC voltages from the input of the amplifier. It should be chosen in such a way that it doesn’t block signals at the desired frequencies. In this case the desired frequency is exactly 40 kHz. In this case the capacitor 1C will form a high-pass filter together with the input resistance Ω= 300inR . We wish frequencies below 40 kHz to be blocked, therefore the

capacitor value is first calculated as 132

11

1

≈⇒= CCR

fin

c πnF . In order to have even

stronger signals passing through the capacitor, it is given the value of 68 nF in the final circuit, this is due to the definition of cf , since that is the frequency at which half of the input power is transmitted to the output of the RC high-pass filter . The second capacitor is used to give as large amplification as possible in the amplifier. The emitter resistor stabilizes the transistor's bias point for DC conditions, but it does this by introducing negative feedback at all frequencies. The capacitor "shorts out" the emitter resistor for AC signals above some frequency, and restores the lost AC gain above the "shorts out" frequency. In this circuit a value of 100 Fµ is chosen as a suitable value. This concludes the calculations necessary to implement the CE-amplifier. The values obtained are:

FnF

CCRk

RcRR e

µ

Ω

===

ΩΩΩ

===

10068

100

360620

7.2

2

12

1

REFERENCES [1] A.S. Sedra, K.C. Smith, Microelectronic circuits. Oxford; Oxford: Oxford university press, 2004

-51-

APPENDIX B: DESIGN OF NARROWBAND AMPLIFIER Introduction First of all it is recognized that the amplifier needs to have a high Q-value, a bandpass frequency peak at 49 kHz and be realized with as few and as cheap components as possible. From the different families of amplifier topologies the Deliyannis bandpass circuit [2] was chosen since it meets the specifications required. The Deliyannis topology belongs to a family called Single-amplifier biquadratic active filters[1][2]. These filters of the second order were chosen for their very economic use of operational amplifiers, since they only require one amplifier per second-order section. This is certainly a benefit in battery-operated system where the power-supply current needs to be conserved. The drawback of this second-order realization is that it suffers from a great dependence on the limited gain and bandwidth of the op-amp and can also be more sensitive to the unavoidable tolerances in the values of resistors and capacitors. Single-amplifier biquadratic active filter The first step of the process is to synthesise a feedback loop for the amplifier. Since the objective is to realize a pair of complex-conjugate poles, a bridged-T network is used since it is the simplest RC network that can realize this. In fig. 1 such a network is shown together with the transfer function from b to a, with a open-circuited. Another important aspect which is easily shown is that the filter poles are identical to the zeros of the RC network.

2143142313

2

2143321

2

1111

1111

)(

CCRRCRCRCRss

CCRRRCCss

st+

+++

+

++

= Eq. B1

Fig B1: bridged-T network with its transfer function From the transfer function above and the fact that the pole polynomial of the active-filter circuit will be equal to the numerator polynomial of the bridged-T network which gives that:

2143321

220

02 1111CCRRRCC

ssQ

ss +

++=++ ωω Eq. B2

If the above equation is remodelled then 0ω and Q can be obtained as:

1

213

2143

21430

11

1

−

+=

=

CCRCCRR

Q

CCRRω

Eq. B3-B4

-52-

Since 0ω and Q are given, and for easy component selection CCC == 21 is chosen and the resistors are denoted RR =3 and mRR /4 = , the above equations can be reformulated as:

0

2

24

ωQRC

Qm

=

= Eq. B5-B6

We conclude that if the Q-value is given the first of the above equations can be used to determine the ratio between the resistors. Then the values of 0ω and Q can be substituted in the second of the above equations to determine the time constant RC . Now the values of C and R can be chosen arbitrarily.

Fig. B2: Feedback loop with signal injection path

When the feedback loop has been designed, the input signal needs to be connected. For this reason the resistance 4R is divided into two parts as seen in fig. 2. These parts are

α4R and )1(4 α−R . Note that the parallel equivalent of these two is 4R . The reason for choosing 4R as where the signal is injected is that any circuit node connected to ground can instead be connected to an input voltage source without causing the poles in the transfer function to change.

Fig B3: Analysis of circuit to determine the voltage transfer function

A nodal analysis conducted in a manner as described in fig. 3, in the order of the encircled numbers where the final step, number 9, consists of writing the node equation at X and substituting for xV by the value determined in step 5 yields the following transfer function:

-53-

2143321

2

140

1111)(

CCRRRCCss

CRsVV

i +

++

−=

α Eq. B7

The above function is recognized as a bandpass function whose center frequency gain can be controlled by the value of α . As expected the denominator polynomial is identical to the numerator polynomial of )(st . Dimensioning the components – the easier way Since the Single-amplifier biquadratic active filters have been used for quite some time more or less useful guides have been developed to help facilitate the design of such filters. One of the better examples of such guides is a short paper entitled “Filter design in thirty seconds” written by Bruce Carter of Texas Instruments [3]. In this guide the following design procedure is introduced for a narrow bandpass filter:

Fig B4: Schematic of filter as recommended in “Filter design in thirty seconds”

Design Procedure: 1) Pick 21 CC =

2) CalculateFrequencyC

RR⋅⋅⋅

=12

141π

3) Calculate 1193 RR ⋅=

4) Calculate 19

12 RR =

This is a great simplification compared to the analysis and design procedure as described above. However this circuit has a smaller freedom than the one described previously since it has a Q which is set to 10. With this design approach there is also a relation between the gain and the Q factor which is:

GainQRRR

==⋅+

1243 Eq. B8

By using this design procedure a filter can be quickly implemented with no lengthy calculations but with the drawback that the gain and Q factor cannot be set independently. Choice of operational amplifier Up until now very little has been said about the operational amplifier itself, but a critical remark has been made that there is a great dependence on the limited gain and bandwidth of

-54-

the operational amplifier. Here this aspect will be developed in terms of the choice of operational amplifier. The gain and bandwidth of an operational amplifier under the assumption that bωω >> are coupled to each other by the approximate relation where 0A is the DC-gain of the amplifier and bω is the 3-dB frequency:

⇒≈+

=ωω

ωωω

jA

jAjA b

b

00

1)(

ωωω bAjA 0)( ≈ Eq. B9

From this relation it can be seen that that the gain A reaches unity (0dB) at a frequency denoted by tω and given by bt A ωω 0= . The frequency πω 2ttf = is usually specified in data sheets of commercially available operational amplifiers and is known as the unity-gain bandwidth. With bt A ωω 0= the above equation can be rewritten as

⇒=ω

ωωj

jA t)(ffjA tt =≈

ωωω)( Eq. B10

This equation has a high significance for choosing the operational amplifier used in the filter since a low unity-gain bandwidth won’t allow to have the desired amplification in the circuit. The TL074, chosen for this amplifier in the thesis, has a unity-gain bandwidth of 3 MHz, which means that in this application the maximum amplification is:

75403)( ==≅

kHzMHz

ffjA tω Eq. B11

Simulation of narrowband circuit used in thesis The circuit was also simulated in Matlab based on the last transfer function derived in the first section of the appendix and the component values used in the simulation were:

2143321

2

140

1111)(

CCRRRCCss

CRsVV

i +

++

−=

α Eq. B12

Ω==Ω=== 6.1990496453.08.761 4321 RkRnFCC α

-55-

Fig. B5: Gain and amplitude curve of narrowband amplifier transfer function

The conclusion of these simulations is that there is a good agreement between the simulated results both in Spice and Matlab, as well as with the practical measurements of the implemented circuit. REFERENCES [1] A.S. Sedra, K.C. Smith, Microelectronic circuits. Oxford; Oxford: Oxford university press, 2004 [2] Sedra, A.; Ghorab, M.; Martin, K.; , "Optimum configurations for single-amplifier biquadratic filters," IEEE Transactions on Circuits and Systems, vol.27, no.12, pp. 1155- 1163, Dec 1980 [3] Internet: www.ti.com/lit/an/sloa093/sloa093.pdf, december, 2001 [Apr. 27, 2012]

-56-

APPENDIX C: DATASHEETS FOR KNOWLES ACOUSTICS SPM0204UD5

SPM0204UD5

Knowles Acoustics, Revision: PRELIMINARY a division of Knowles Electronics, LLC Page 1 of 9

ULTRASONIC ACOUSTIC SENSOR

SPM0204UD5

Knowles Acoustics, Revision: PRELIMINARY a division of Knowles Electronics, LLC Page 2 of 9

1. DESCRIPTION AND APPLICATION

1.1. Description

Surface Mount Wide-Band Ultrasonic Acoustic Sensor

1.2. Applications Hand held telecommunication devices, Positioning Sensing, Pneumatic Flow Sensing

2. PART MARKING

3. TEMPERATURE RANGE

3.1. Operating Temperature Range: -40°C to +100°C

3.2. Storage Temperature Range: -40°C to +100°C

S123456

Tracking Number Convention S: Manufacturing Location 1-6: Job Identification Number

SPM0204UD5

Knowles Acoustics, Revision: PRELIMINARY a division of Knowles Electronics, LLC Page 3 of 9

4. ACOUSTIC AND ELECTRICAL SPECIFICATIONS

Limits Symbol Condition

Min. Nom. Max. Unit

Directivity Omni-directional

Frequency Range f 10k 65k Hz

Sensitivity S @ 1kHz (0dB=1V/Pa) -51 -47 -43 dB

Output impedance ZOUT @ 1kHz (0dB=1V/Pa) n/a n/a 300 Ω

Current Consumption IDSS across 1.5 to 3.6 volts 0.100 n/a 0.250 mA

Signal to Noise Ratio S/N @ 1kHz (0dB=1V/Pa) 55 59 n/a dB

Supply Voltage Vs 1.5 n/a 3.6 V

Typical Input Referred Noise

ENL A-weighted n/a 35 n/a dBA SPL

Sensitivity Loss across Voltage

Change in sensitivity over 3.6v to

1.5v No Change Across Voltage

Range dB

Maximum Input Sound Level

At 100dB SPL, THD < 1%

At 115dB SPL, THD = < 10% dB

5. FREQUENCY RESPONSE CURVE

Knowles Acoustic MEMS Ultrasonic SensorFrequency Response

(Nominal Sensativity 0 = -47dBv/Pa)

-30

-20

-10

0

10

20

30

10,000 20,000 30,000 40,000 50,000 60,000

Frequency(Hz)

Mag

nitude

(dB

)

SPM0204UD5

Knowles Acoustics, Revision: PRELIMINARY a division of Knowles Electronics, LLC Page 4 of 9

6. MECHANICAL SPECIFICATIONS

Note: Special care must be used so that the Acoustic Port Mesh area is not touched or

disturbed during application. (Tolerance +/-0.15mm unless otherwise specified)

PIN Designation Pin # Function 1 Output 2 Ground 3 Ground 4 Power

Item Dim. Tol. (+/-) Units

(H) Height 1.40 0.10 mm

(L) Length 4.72 0.10 mm

(W) Width 3.76 0.10 mm

Acoustic Area

(AW) Width 2.95 - mm

(AL) Length 3.12 - mm

Weight 0.07 g

Coplanarity <0.1 mm

1

4

2 3

Acoustic Port Mesh

SPM0204UD5

Knowles Acoustics, Revision: PRELIMINARY a division of Knowles Electronics, LLC Page 5 of 9

7. RECOMMENDED LAND PATTERN

!

"#

$%

8. RECOMMENDED INTERFACE CIRCUIT

External Gain (set by customer) = -R1/R2

Dotted Section Represents Ultrasonic Sensor

+

-

+

Vref

R

R

Term 4

Term. 3 Term. 2

Term. 1

• •

•

SPM0204UD5

Knowles Acoustics, Revision: PRELIMINARY a division of Knowles Electronics, LLC Page 6 of 9

9. PACKAGE DETAIL

&' (&)&' &*

+' *,

-#. //0. //

132 . 4/65 /. 27 /. /

28 . //9/. :

2 . ;49/. 2

-#. 2<

4. 28

4. 4/9/. /4

12 . 4/=/. :/>?> @ACB.

8 . //9/. /4

/. ;4

No consecutive empty pockets; No more than 3 empty pockets per reel. (Does not include empty pockets for leader/follower)

Empty Units

Label applied to external package and direct to reel. Per JEDEC.

Label

800mm or minimum of 100 empty pockets

Leader Length

4,800

1,200

Quantity per Reel

7” -2 SPM0204UD5

13” -6 SPM0204UD5

Reel Diameter

Suffix Model Number

SPM0204UD5

Knowles Acoustics, Revision: PRELIMINARY a division of Knowles Electronics, LLC Page 7 of 9

10. SOLDER REFLOW PROFILE

11. ADDITIONAL NOTES

(A) Packaging (reference SiSonic_Packaging_Spec.pdf) (B) Shelf life: Twelve (12) months when devices are to be stored in factory supplied,

unopened ESD moisture sensitive bag under maximum environmental conditions of 30ºC, 70% R.H.

(C) Exposure: Devices should not be exposed to high humidity, high temperature environment. MSL (moisture sensitivity level) Class 2.

(D) Out of bag: Maximum of 90 days out of ESD moisture sensitive bag, assuming maximum conditions of 30ºC/70% R.H.

Notes: • Do not pull a vacuum over the port hole of the microphone.

Pulling a vacuum over the port hole can damage the device.

• Do not board wash after the reflow process. Board washing and cleaning agents can damage the device. Do not expose to ultrasonic processing or cleaning.

• Number of Reflow = recommend no more than 3 cycles.

30 sec. 260 C maximum Peak

100 sec. Above 230 C Solder Melt

120 sec. 170 ~ 180 C Pre-heat

Time (maximum)

Temperature Profile

Stage

170–180°C

Solder Melt Pre-heat

260°C

230°C

100 sec. 120 sec.

SPM0204UD5

Knowles Acoustics, Revision: PRELIMINARY a division of Knowles Electronics, LLC Page 8 of 9

12. RELIABILITY SPECIFICATIONS Note: After test conditions are performed, the sensitivity of the microphone shall not deviate more than 3dB from its initial value.

Test Description

Thermal Shock Microphone unit must operate when exposed to air-to-air thermal shock 100 cycles, from –40ºC to +125ºC. (IEC 68-2-4),

High Temperature Storage Test

Microphone unit must maintain sensitivity after storage at +105ºC for 1,000 hours. (IEC 68-2-2 Test Ba)

Low Temperature Storage Test

Microphone unit must maintain sensitivity after storage at –40ºC for 1,000 hours. (IEC 68-2-1 Test Aa)

High Temperature Operating Test

Microphone unit must operate within sensitivity specifications for 1,000 hours at 105ºC. (IEC 68-2-2 Test Ba)

Low Temperature Operating Test

Microphone unit must operate within sensitivity specifications for 1,000 hours at –40ºC. (IEC 68-2-1 Test Aa)

Humidity Test Tested under Bias at 85ºC/85% R.H. for 1,000 hours. (JESD22-A101A-B)

Vibration Test Microphone unit must operate under test condition: 4 cycles, from 20 to 2,000 Hz in each direction (x,y,z), 48 minutes, using peak acceleration of 20 G (+20%, -0%). (MIL 883E, method 2007.2, A)

Electrostatic Discharge Tested to 8kV direct contact discharge to the case and tested to 2kV direct contact to I/O terminals.

Reflow Microphone is tested to 5 passes through reflow oven, with microphone mounted upside-down under conditions of 260ºC for 30 seconds maximum.

Mechanical Shock Microphone must operate after exposure to shock test of 10,000 G per IEC 68-2-27, Ea.

SPM0204UD5

Knowles Acoustics, Revision: PRELIMINARY a division of Knowles Electronics, LLC Page 9 of 9

13. SPECIFICATION REVISIONS

Revision Detailed Specification Changes Date

The information contained in this literature is based on our experience to date and is believed to be reliable and it is subject to change without notice. It is intended as a guide for use by persons having technical skill at their own discretion and risk. We do not guarantee favorable results or assume any liability in connection with its use. Dimensions contained herein are for reference purposes only. For specific dimensional requirements consult factory. This publication is not to be taken as a license to operate under, or recommendation to infringe any existing patents. This supersedes and voids all previous literature.

-57-

APPENDIX D: DATASHEETS FOR MURATA MA40MF14-0B

1/7

MURATA MANUFACTURING Co., LTD.

Product Specification for Reference Only

Issued Date: 19 April, 2011

Rev. : F

Pa r t Desc r ip t i on : U l t r a s o n i c S e n s o r

MURATA Par t No . : M A 4 0 M F 1 4 - 0 B

The product specification in this sheet is for reference only. The content of this specification is subject to change. You are requested to receive the latest specification and to return one copy of the specification to us with your receipt signature before going into mass production.

Product Engineering Section Sensor Products Department Sensor Products Division Device Unit

Murata MFG. Co.,Ltd.

2/7

MURATA MANUFACTURING Co., LTD.

Specification of Ultrasonic Transducer

Type : MA40MF14-0B 1. Scope

This product specification is applied to the water proof type ultrasonic transducer used for obstacle detection system around vehicle.

Please contact us when using this product for any other applications than described in the above.

2. Customer Part Number 3. Murata Part Number

MA40MF14-0B 4. Dimension as per Fig.1 5. Absolute Maximum Ratings

Items Specification Note 5-1 Maximum Input Voltage 160Vp-p Do not apply D.C. voltage. 5-2 Operating temperature range -40 to +85 deg C 5-3 Storage temperature range -40 to +85 deg C 6. Specifications (* Temperature 25±3 deg C, 45 to 60 % R.H, unless otherwise noted ）

Items Specification Note 6-1 Operation Frequency 40 kHz 6-2

Sound pressure Level

more than 101 dB

at 40kHz distance is 30cm, input voltage is 10Vrms 0 dB = 20 uPa (per measuring circuit Fig.2)

6-3

Sensitivity

more than –87 dB

at 40 kHz 0 dB = 10V/Pa (per measuring circuit Fig.3)

6-4 Beam pattern (Typical) (Typical) 110 deg x 50 deg

6dB down angle of overall sensitivity

6-5 Capacitance 2700 pF +/- 20% at 1kHz 6-6 Insulation Resistance 100 Mohm min. at 100V D.C.

Drawing No. P. 3/6

Reference Only

MURATA MANUFACTURING Co., LTD.

7. Environmental tests (Standard Test Condition: 25 ± 3 deg C, 45 to 60 % R.H) 7.1 Shock Test The variation of the Sound Pressure Level at 40 kHz is within 3dB compared with initial figures at 25 deg C after following test conditions

Acceleration : sine 980 m/s2 (100G), 6ms Direction : 3 directions Shock time : 3 times / directions

7.2 Vibration Test The variation of the S.P.L at 40 kHz is within 3dB compared with initial figures at 25 deg C after following test conditions

Vibration frequency: 10 to 200 Hz Sweep Period : 15 min. Acceleration : 43.12 m/s2 (4.4G) Directions : 3 directions Time : 96 hours / direction

7.3 Drop Test The variation of the S.P.L at 40 kHz is within 3dB compared with initial figures at 25 deg C after following test conditions

Height : 1 meter onto concrete floor Times : 10 times

7.4 Pull Strength There should be no substantial damage after 2.45 N of force. 7.5 High Temperature Test The variation of the S.P.L at 40 kHz is within 3dB compared with initial figures at 25 deg C in 24 hours after following test conditions

Temperature : +85 ± 2 deg C Time : 1000 hours

7.6 Low Temperature Test The variation of the S.P.L at 40 kHz is within 3dB compared with initial figures at 25 deg C in 24 hours after following test conditions

Temperature : -40 ± 3 deg C Time : 1000 hours

7.7 Humidity Test The variation of the S.P.L at 40 kHz is within 3dB compared with initial figures at 25 deg C in 24hours after following test conditions

Temperature : +65 ± 2 deg C Humidity : 90 to 95 % R.H. Time : 1000 hours

7.8 Heat Cycle Test The variation of the S.P.L at 40 kHz is within 3dB compared with initial figures at 25 deg C in 24hours after following test conditions

Temperature : +85 ± 3 deg C, 30 min -40 ± 3 deg C, 30 min Cycles : 1000 cycles

Drawing No. P. 4/6

Reference Only

MURATA MANUFACTURING Co., LTD.

8. Caution 8-1 Limitation of Applications Please don’t use for the applications listed below which require especially high reliability for the prevention of defects which might directly cause damage to the third party's life, body or property.

1) Aircraft equipment 2) Aerospace equipment 3) Undersea equipment 4) Power plant control equipment 5) Medical equipment 6) Transportation equipment (trains, ships, etc.) 7) Traffic signal equipment 8) Disaster prevention / crime prevention equipment 9) Data-processing equipment 10) Application of similar complexity and/or reliability requirement to the applications

listed in the above 8-2 Fail-safe Be sure to provide an appropriate fail-safe function on your product to prevent a second damage that may be caused by the abnormal function or the failure of our product. 9. Caution in use 9-1. Notice in design and usage

1) The transducer may generate surge voltage by mechanical or thermal shock. Care should be taken to protect from it in designing your application circuit.

2) Please do not apply an excessive stress to the transducer because the piezo electric element of the transducer might be damaged or inner cable might be disconnected.

3) The piezo electric element of the transducer may be damaged by force pressure from back of the transducer.

4) Please do not apply D.C.voltage to the transducer to avoid failure. Electrode of piezo electric element might be shorted out with electronic migration.

5) Please do not use the transducer in water. 6) Please hold the transducer with soft material such as rubber. The direct holding with hard

material will be cause of vibration leakage from, or into the transducer. It will be influenced to decay time and short distance detection.

7) Please avoid humid penetration at the rear of the transducer in order to avoid short circuit. Please use the transducer with waterproof design.

8) Please do not exceed 95 deg C / 120min in the assembly process and painting process to avoid malfunction.

9) The transducer is designed for dual use purpose. Please do not use the transducer only as receiver.

10) Care should be taken when select the material to hold, or cover backside of transducer. If it contains sulfur or sulfide, electrode on piezo-electric element may corroded and because of malfunction.

9-2. Notice in storage 1) The products should not be used or stored in a corrosive atmosphere, especially where

chloride gas, sulfide gas, acid, alkali or the like are present. Store the products in the room where is normal temperature and humidity, and avoid the sunlight, sudden changes in temperature and humidity. It may cause of failure or malfunction in such conditions.

2) Store the products where the temperature and relative humidity do not exceed -10 to 40 deg C, and 30 to 80%RH.Please Use the products within 6 months after receiving.

9-3. Notice in soldering and mounting

Drawing No. P. 5/6

Reference Only

MURATA MANUFACTURING Co., LTD.

1) Please do not clean the transducer with water or solvent. 2) Please do not solder the transducer with flow or reflow soldering. Do not exceed the

soldering iron temperature 350 deg C and 3 sec.

10. Note 1) Please make sure that your product has been evaluated in view of your specifications

with our product being mounted to your product. 2) You are requested not to use our product deviating from the agreed specifications. 3) We consider it not to appropriate to include any terms and conditions with regard to the

business transaction in the product specifications, drawings or other technical documents. Therefore, if your technical documents as above include such terms and conditions such as warranty clause, product liability clause, or intellectual property infringement liability clause, they will be deemed to be invalid.

Drawing No. P. 6/6

Reference Only

MURATA MANUFACTURING Co., LTD.

Dimensions

Aluminum case surface

NON Hexavalent Chrome for anti-corrosion

Epoxy primer and Black color paint.

unit : mm

Fig. 1

9 +/

- 0.1

3 +/

- 0.1

40

+/-

5

12 +/- 0.2

14 +/- 0.1

# : EIAJ code

#

Lead wire : Black, AWG 30

(Connected to Aluminum-case ) Lead wire : Red, AWG 30

Drawing No. P. 7/6

Reference Only

MURATA MANUFACTURING Co., LTD.

S.P.L.Test circuit

OSC.

Freq. Counter

U.S S.C.M

30cm

Amp.

Voltmeter

Fig. 2

OSC. : Oscillator (Brüel & Kjær 1013)

U.S : Ultrasonic Sensor

S.C.M : Standard Condenser Microphone (Brüel & Kjær 4135)

Amp. : Amplifier (Brüel & Kjær 2610)

Sensitivity Test circuit

SP. S.C.M.

30 cmU.S.

Amp.

OSC.

F req. Counter

Voltmeter

Fig. 3

O SC. : Oscilla tor (Brüel & Kjæ r 1013)

U.S. : Ultrasonic Sensor

S.C.M : Standard Condenser Microphone (Brüel & Kjæ r 4135)

Amp. : Amplifier (Brüel & Kjæ r 2610)

SP. : Tweeter

RL : 3.9 k ohm

RL

-58-

APPENDIX E: DATASHEETS FOR PHYSICAL ACOUSTICS SENSORS