WP Soundbrush 2013

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LMS SoundBrush: a new source identification

technology for stationary noise sources

A Siemens Business

Karl Janssens, Dirk De Weer & Fabio Bianciardi - LMS, A Siemens Business, Interleuvenlaan 68, 3001 Leuven, Belgium

Thomas Søndergaard - G.R.A.S. Sound & Vibration, Skovlytoften 33, DK-2840 Holte, Denmark


http://slidepdf.com/reader/full/wp-soundbrush-2013 2/82LMS, A Siemens Business | [email protected] | www.lmsintl.com

Continuing legislative pressure and increasing consumer and end user focus on noise pollution continuously stretches the

challenges in acoustic design of products and machinery, their noise sources and the propagation of sound from these

noise sources into the air space around them. This paper presents a new SoundBrush measurement technology for source

investigation, detection and propagation of stationary noise sources. A handheld measurement instrument combines a

position and orientation tracking device on top of which a 3D sound intensity sensor antenna can be mounted. While

moving the probe freely around the test object, the sound field is visualized on-line in 3D. The real-time representation

immediately focuses the measurement on the areas of interest requiring further in-depth analysis. The tool is setup rapidly,

provides an intuitive workflow and shows results in real-time, making it widely applicable in many industrial applications.

This paper explains the working principle and characteristics of SoundBrush and shows some application examples on a

diversity of test objects.

1. SOUNDBRUSH TECHNOLOGY AND OPERATING

PRINCIPLES

Nowadays acoustic investigation and analysis is an increasingly demanding

but important discipline across many industries. This paper presents a new

patented1 SoundBrush measurement technology that visualizes stationary

sound fields in full 3D while measuring.

The core of the technology is a handheld measurement instrument shown

in Fig. 1. The measurement instrument combines an on-line position and

orientation tracking system with a 3D sound intensity sensor antenna

which is mounted on top of the device. The measured sound field is

visualized in 3D while moving the probe around the test object.

Fig. 1 - LMS SoundBrush handheld measurement instrument

The 3D sound intensity sensor antenna is a solid sphere with four phase-

matched microphones in tetrahedron configuration. The sensor antenna is

manufactured by G.R.A.S. Sound & Vibration. A picture is shown in Fig. 2.

Fig. 2 - 3D sound intensity probe from G.R.A.S. Sound & Vibration

The 3D position of the SoundBrush probe is measured with an optical

position tracking system. The probe comprises an illuminated sphere with

45 mm diameter which is continuously tracked by a camera. During set-up,

the sphere color is automatically adjusted to provide the highest contrast

with the environment. The 3D orientation of the probe is measured with an

inertial system consisting of accelerometers and gyroscopes.

Typical measurement accuracy is 3-5 cm up to a distance of 1.5 m from

the camera. The workable area is 2.5 by 2 m at 2.5 m distance from the

camera.

The SoundBrush measurement device contains an integrated frontend

for acquisition of data. The system automatically recognizes the acoustic

sensor antenna. Push buttons allow full control of the measurement

process. LEDs provide on-line feedback on hardware status, measurement

levels and position tracking. All functions are combined in an ergonomic,

functional and lightweight design allowing easy handling during themeasurement. A standard USB cable connects the probe with the PC.

The acoustic measurement data is visualized on-line in 3D while brushing

the sound field. Powerful 3D data representations are provided in the

form of point clouds (sound pressure) and intensity vector plots (acoustic

intensity). The sound field is visualized around a 3D geometry model of

the test object. Fig. 3 shows the working principle, while Fig. 4 shows two

illustrative examples. The first example visualizes the measured 3D sound

pressure field in front of a speaker panel, while the second one shows the

intensity vector field of a small electric engine.

4

1

2

3

Fig. 3 - LMS SoundBrush working principle: 1) camera tracks position of

illuminated sphere on measurement probe; 2) embedded gyroscopes and

accelerometers measure orientation of probe; 3) coordinate transformation to

sensor tip; 4) visualization of measured acoustic field

The on-line 3D data visualization allows an immediate and quick

interpretation of the measurement data enabling an efficient acoustic

troubleshooting. All resulting data can be viewed from any possible angle.

One can freely rotate the test object and zoom in on a specific hotspot or

run a section plane through the measurement data to make an interpolated

contour plot. By focusing on the areas of interest, troublesome areas can

be identified that require further in-depth analysis.

Fig. 4 - Two examples of 3D vector intensity field

The key applications are three-fold:

• Sound source localization: understand where the noise comes

from; investigate the main contributors to the noise radiated from

a test object by scanning over the sur face.

• Leak detection: investigate the efficiency of an enclosure toshield from noise sources within or outside the enclosure.

• Sound propagation: investigate how the sources interact and

propagate into the far-field.



(3)

(2)

(1)

2. THE 3D TETRAHEDRON SOUND INTENSITY

PROBE

2.1. Tetrahedron microphone configuration

In a close collaboration between LMS International and G.R.A.S. Sound &

Vibrations a 3D sound intensity sensor antenna was developed. It consists

of four phase-matched microphones in tetrahedron configuration mounted

in a rigid sphere with a diameter of 30 mm. The tetrahedron configuration2 is represented schematically in Fig. 5.

Fig. 5 - Tetrahedron configuration

Fig. 6 - Diffraction effect of the solid sphere for a plane wave of 20 kHz

The sound intensity vectors along the x, y and z axes in the local coordinatesystem of the sensor antenna can be calculated from the sound pressure

measurements p1(t), p

2(t), p

3(t) and p

4(t) by using Eqn. (1). The first terms

represent the pressure averaged along the axes; the integral terms

represent the particle velocity; ∆r is the spacer distance between the

microphones considering the presence of the sphere;ro is the air density3.

The frequency domain formulation is given in Eqn. (2), with the cross-

power spectrum between the averaged microphone pressures.

The magnitude of the resulting sound intensity vector can be obtained

using Pythagoras’s theorem. The direction in the global coordinate system

can be reconstructed by applying a roto-translation taking into accountthe 3D orientation (measured with the inertial system) and offset (to the

illuminated sphere) of the sensor antenna.

2.2. Sources of error and correction functions

The i) diffraction effects by the solid sphere, ii) finite difference

approximation of the particle velocity and iii) phase mismatch are three

important sources of error that need to be accounted for when doing

sound intensity measurements with the G.R.A.S. probe.

Diffraction effects

The rigid sphere represents an obstacle to the sound propagation. The

pressure response of the four microphones is influenced by the diffraction

of the sound waves impinging the sphere4. The diffraction effect is depicted

in Fig. 6 for a plane wave of 20 kHz. The influence on the individual

microphone responses depends on the incidence angle of the sound wave.

From this figure one can observe that the microphones facing the origin

of the sound waves experience an increase in sound pressure level, while

the microphones in the ‘shadow’ region are attenuated as a result of the

solid sphere.

An analytical model was developed to study the diffraction effects and

their influence on the sound intensity measurements. The model was used

to simulate the sound pressure for various sound wave incidence angles,

ranging from 0 to 180 degrees in steps of 30 degrees. The diffraction

effects become noticeable from 1 kHz on. The deviations in sound

pressure due to diffraction remain within 2 dB up to 2.5 kHz for all sound

incidence angles. The diffraction effects also introduce phase errors onthe microphone responses which obviously have an impact on the sound

intensity calculation results.

In order to compensate for the diffraction effects, we assume a frequency

dependent spacer distance in the sound intensity calculations, as shown

in Eqn. (3). The frequency profile of is shown in Fig. 7.

Fig. 7 - Frequency dependent spacer distance to correct for diffraction effects

Finite difference approximation error

The finite difference approximation of the particle velocity is another

important source of error5. This type of error also occurs in a traditional

P-P intensity probe with three orthogonal pairs of microphones. However,in the case of the tetrahedron configuration, the finite difference

approximation error is insensitive to the incidence angle of the sound wave

and can therefore be corrected.

The finite difference approximation error of the G.R.A.S. probe and

traditional P-P sound intensity probe was numerically simulated. For

a solid sphere, the decrease in amplitude can be well approximated by

the sinc function in Eqn. (4). For traditional intensity sensors this curve is

orientation dependent and, as a result, cannot be compensated for.

The angle independent finite difference approximation error is a unique

property of the G.R.A.S tetrahedron probe. Because of this property,

the magnitude of the sound intensity vector can be corrected for all

orientations of the probe with the sinc function shown in Fig. 8. This allows

accurate sound intensity measurements in a large frequency range, well

above the upper frequency limit of a traditional probe with the same spacer

distance. Traditionally, the rule of thumb requires the spacer distance to be

less than one sixth of the wavelength6. This restriction in frequency range

no longer holds for the tetrahedron configuration and can be considered

as a great advantage.





3. APPLICATION EXAMPLES

3.1. Measurement on a car door

In the example, the front passenger door of a car was measured. In the

setup, the car audio system was used as a sound source, playing a simple

wave file containing pink noise. The measurement was done at the outside

of the car, where the front passenger door on the right side of the vehicle

was measured using SoundBrush.Two measurements were done: one with all doors and windows completely

closed and another one where the front right window was opened with 1 cm.

Fig. 12 - Measurement on passenger door, window closed

Fig. 13 - Measurement on passenger door, window 1 cm open

When comparing both measurements (Fig. 12 and 13) the window leak

is clearly visible as a sound source. However, the measurements also

clearly show an effect of acoustic resonance below the car. The speakers

excite the cavity between the car body and the road surface, and the

sound further flows upwards and away from the door. When the window isslightly opened, the second sound source quite expectedly appears but the

dominant source still remains at the bottom of the car.

In order to investigate this phenomenon in further detail, SoundBrush

can be used to investigate the sound field under the car. This example

demonstrates the SoundBrush capabilities to further analyse key acoustic

phenomena thanks to its quick setup and its capability to measure in

difficult to reach locations. In addition the representation of the sound field

with a 3D vector cloud provides more insight in the acoustic phenomena at

hand when compared with traditional intensity measurement techniques

providing 2D representations (Fig. 14 and 15).

Fig. 14 - 2D representation of measurement, window closed

Fig. 15 - 2D representation of measurement, window 1 cm open

3.2. Measurement on an industrial cleaning machine

SoundBrush was used in an analysis of acoustic hotspots on an industrial

cleaning machine. Different regimes are available with this cleaner:

brushing, water cleaning, vacuuming, brushing and vacuuming … In the

plot below, the result is shown for the regime ‘vacuuming’. During the test,

one side of the cleaning machine was measured using SoundBrush.

Fig 16 clearly reveals the maximum sound intensity at the location of the

vacuum mouth in the back of the equipment, just above the floor.

Fig. 16 - 2D representation of SoundBrush measurement on an industrial

cleaning machine (left) and camera view of the hotspot region in the lower

left of the 2D image (right)

From the analysis of the frequency content, a single frequency source of250 Hz and lower amplitude is visible at some measurement locations.

When zooming in on the 250 Hz 1/3rd octave band, a sound source at the

back of the equipment becomes visible (see Fig. 17).

The ability of SoundBrush to view results in real-time allows a fast

identification of sound sources. In addition, spectral results help identifying

tonal components that provide the highest contribution to the noise

emitted from different sources inside the device under test.

Fig. 17 - 2D representation of measurement results on industrial cleaning

machine for the 1/3rd octave band at 250 Hz.

3.3. Car dashboard measurements.

Car dashboards are complex surfaces incorporating different sound

sources in sometimes very difficult to reach locations.

An in-car measurement was performed on a car ventilation system using

SoundBrush.

The sound field was measured above the dashboard (just below thewindscreen) as well as in front of the central ventilation openings in the

middle of the dashboard.

The car engine was in a stationary regime, running idle at 800 RPM, with

the ventilation system activated at full power. Fig. 18 clearly identifies

the two ventilation openings in the middle of the dashboard as sources of

noise of the ventilation system.

Fig. 18 - 2D representation of acoustic measurement around ventilation

openings in car dashboard



Fig. 19 allows identification of the windshield ‘defrost’ sleeve at the top

of the dashboard (right below the windshield) as an important noise

source. SoundBrush is capable to measure in hard to reach locations such

as the area between the dashboard and the windshield that allows easy

identification of all relevant noise sources.

Fig. 19 - 3D view of SoundBrush measurement of a car dashboard (left) and

2D representation of a section plot around the defrost sleeve (right)

3.4. Laptop loudspeaker measurement.

In computer business, sound characteristics become increasingly

important.

A laptop was used for a SoundBrush measurement, to identify noise

sources from the laptop speakers left and right of the keyboard. The left

speaker signal contained a 500 Hz signal (and lower amplitude harmonicsof this signal); the right speaker signal consisted of a pure 2000 Hz signal.

The figures 20 to 22 show the SoundBrush results for a broadband

measurement, a filtered result from 315 to 630 Hz and a filtered result

from 1600 to 2500 Hz. The first plot clearly shows the two sound

sources, whereas the filtered results put emphasis on the left or right plot

respectively.

Fig. 20 - measurement on laptop with side speakers, 500 Hz on left speaker

and 2000 Hz on right speaker – broadband result


and 2000 Hz on right speaker – filtered between 315 and 700 Hz


and 2000 Hz on right speaker – filtered between 1600 and 2500 Hz

Next to each 3D plot, the 2D color map (interpolated results of the

SoundBrush measurements) reveals the same sound sources, but only in

a 2D representation. The 3D visualization of the sound field around an

object by the SoundBrush software provides more insight in the acoustic

phenomena of importance in each frequency of interest. The arrow

representation of SoundBrush reveals the orientation and propagation of

the sound waves emanating from a source, for both unfiltered and filtered

measurements.

3.5. Laundry dryer measurements.

Measurements with SoundBrush on a household laundry drying machine

provide a good example of the typical acoustic challenges faced in designing

white goods. A drying machine is investigated by first using SoundBrush on

the different sides of the machine followed by a finer measurement around

the door in order to analyze the efficiency of the door seal to isolate for

sources inside the dryer.

Fig. 23 reveals sound sources at the bottom right back side of the dryer

from the side panel measurements. The hot air exhaust was at the bottom

left back side (not shown on the image) and also clearly reveals a sound

source.

Fig. 23 - measurement on household drying machine (left: 3D model of the

dryer; right: SoundBrush measurements on different sides of the dryer)

In a next set of measurements, an investigation of the front side of the

dryer was performed in order to find sources of noise originating from this

side of the dryer.

Fig. 24 shows two sound sources: one around the door and one at the

bottom of the dryer.

Fig. 24 - SoundBrush measurement on drying machine – front side only (left:3D results; right: 2D representation of front side measurement)

Finally, a measurement was done of the dryer door seal.

Fig. 25 shows the frequency range from 100 to 4000 Hz, where the door

seal seems to have a more or less equal insulation effect over the door

circumference. However, Fig. 26 shows the results when filtering on the

200 Hz peak.

Fig. 25 - Dryer measurements around door seal: broadband result

Fig. 26 - Dryer measurements around door seal: result at 200 Hz

This figure shows two sound sources: one located at the left side of the

door, around the door hinge and one located at the right side of the door,

around the door lock.The hinge and lock of the dryer door seem to close less firmly, causing

noise to leak more easily at this location of the door.



The ability of SoundBrush to quickly scan different sides of the dryer

in a single measurement session results in considerable time savings

compared to comparable measurements using traditional techniques or

using sound masking techniques. The SoundBrush measurement on the

dryer took ½ day, where other methods typically require 2 days or more.

4. CONCLUSIONS

A new SoundBrush measurement system was developed to brush andvisualize the 3D sound field of noise producing machinery. The system

consists of a handheld measurement probe integrating a 6 DOF tracking

system and 3D sound intensity sensor antenna. The sound intensity

vectors are visualized on-line in 3D while the operator moves the

probe around the test object. The measurement system is an efficient

acoustic troubleshooting tool for stationary applications allowing a quick

identification of the main sources, their interaction and propagation into

the far field. The 3D sound intensity vector field is precisely measured up

to 4 kHz with an accuracy of 1 dB in magnitude and 2.5 degrees standard

deviation in direction (maximum error 10 degrees).

The LMS SoundBrush can be used for acoustic testing and analysis in a

diversity of applications like source localization, leak detection, sound

propagation. The 3D positioning technology provides new insights in

acoustic phenomena and the sound flow around a device under test. Itsergonomic design allows measurement of acoustic problems in difficult

to reach locations and around complex surfaces. Finally, its intuitive user

interface and fast setup reduce typical measurement time drastically

in comparison with other acoustic measurement techniques such as

traditional intensity probes or acoustic array measurements.

5. ACKNOWLEDGEMENTS

This research is conducted in the context of the research project SOUND

BRUSH. The financial support of the Flemish Institute for Promotion of

Innovation (IWT) is gratefully acknowledged.

6. REFERENCES

1. EP1913346B1, “Device and method for determining scalarquantities or vector quantities”

2. G. Rasmussen, “Measurement of vector fields”, Proceedings

of the 2nd International Congress on Acoustic Intensity, pages

53-58, 1985

3. F. Jacobsen, “Sound Intensity and its measurement and

applications”, Technical University of Denmark, 2011

4. G. Krishnappa, “Interference effects in the two-microphone

technique of acoustic intensity measurements”, Noise Control

Engineering Journal 21, 126-135, 1983

5. U.S. Shirahatti and M.J. Crocker, “Two-microphone finite

difference approximation errors in the interference fields

of point dipole sources”, Journal of the Acoustical Society of

America 92, 258-267, 1992

6. F. Fahy, “Sound intensity”, E&FN Spon, London, 2

nd

edition, 19957. V. Trinh, “Measurement of sound intensity and sound power”,

DSTO Material research laboratory, 1994

8. 8. K. Janssens, D. De Weer, F. Bianciardi and T. Søndergaard,

“Online Sound Brush Measurement Technique for 3D Noise

Emission Studies”, Proceedings 13NVC-0192 of the SAE Noise

and Vibration Conference, May 2013



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