Christos Papavassiliou - Circuits and Systems | Faculty of Engineering | Imperial ...cas.ee.ic.ac.uk/people/dario/files/E302/1Sensorsslides.pdf · · 2010-10-13sensors/transducers,

Imperial College London – dept EEE 1

Autumn 2003

E302-AC4 InstrumentationAutumn 2010G1

Instrumentation

Christos PapavassiliouAutumn 2010


Autumn 2003


Course Details• Lecture: Tuesday 2pm, Wednesday 11am (403a)• Lecturer: Christos Papavassiliou,

room 915, email: [email protected]• Coursework (20%)

2 sets, 1 due week 5, one due week 11

• Course Homepage: Link from CP homepageWEBCT


Autumn 2003


Course Overview

• Aims:To give an overview of electrical measurement theory and practice, especially at GHz frequencies; provide an understanding of measurement principles, capabilities and limitations.

Objectives:Understand the operation and limitations of various measurement sensors/transducers, and design suitable circuits and procedures to optimise transducer performance. Apply Signal processing techniques to measurement.


Autumn 2003


Course Syllabus• Definitions and examples of measurements and their limitations:

– Resolution, accuracy, sensitivity. – DC and AC bridges.

• Noise in electronic systems and Amplifiers• Oscilloscopes: Analogue, Digital and Sampling. • Phase locked loops, Oscillators and synthesisers. Phase noise.• Sampling and Analogue to Digital conversion. Oversampling. • Counters, Timers: Time and Frequency measurement. • Coherent measurements and interferometry. Correlation techniques.• Microwave measurements: Network and spectrum analysers. • (if time permits) Time and Frequency Domain Reflectometry.


Autumn 2003


Course Outline

• 1. Sensors/Transducers; Bridges• 2. Noise, system noise, noise matching• 3. Signal Amplification; autozeroing and chopper amplifiers.• 4. Oscillators, synthesizers, integer and fractional PLL,

transfer oscillators.• 5. Frequency and time measurements• 6. Modelling and data fitting; Calibration• 7. Sampling, oversampling, subsampling. Aliasing and anti-

alias filters.• 8. A/D and D/A Converters. Quantisation noise.• 9. Synchronous measurements and Interferometry• 10. Radio frequency measurements


Autumn 2003


Metrology• The scientific study of measurement• The science of weights and measures• Metrology is an important part of semiconductor

manufacturing where high-resolution tools are required to measure the tiny elements in a chip that continue to decrease year after year.

• A measurement is a comparison to a standard. -- William Shockley


Autumn 2003


Calibration• The process of adjusting an instrument or compiling a deviation

chart so that its reading can be correlated to the actual value being measured.

• determination of the accuracy of an instrument, usually by measurement of its variation from a standard, to ascertain necessary correction factors

• Checking, adjusting and systematically standardizing the graduations of a device.

• is defined as the process of quantitatively defining the system response to known, controlled signal inputs.

• many more, similar, definitions.


Autumn 2003


The importance of calibration (1)There is much talk about the risks associated with inadequate calibration, but many people have asked whether the risks are real or just theoretical.

"Looks like someone forgot to calibrate the 'Instrument Landing System', captain."


Autumn 2003


The importance of calibration (2)

city police department's radar speed violation tickets were legally invalidated in court after somebody proved the calibration process for the radar guns wasn't traceable to national standards.

"Honestly officer, battery-powered milk floats can't do 75 miles per hour.... even downhill."


Autumn 2003


SI Base Units

QuantityUnit

Name Symbollength meter mmass kilogram kg

time seconds selectric current ampere Athermodynamic temperature kelvin Kamount of substance mole molluminous intensity candela cd


Autumn 2003


Unit Prefixes

μ


Autumn 2003


accuracy of terminology is important in engineering

•1 million microphones = 1 megaphone ?•1 million bicycles = 2 megacycles ?•52 cards = 1 decacards ?•1/2 lavatory = 1 demijohn ?•3-1/3 tridents = 1 decadent ?•10 monologs = 5 dialogues ?•2 monograms = 1 diagram ?•1 millionth of a fish = 1 microfiche ?•10 rations = 1 decoration ?•10 millipedes = 1 centipede ?


Autumn 2003


Introduction

• Instrumentation:– Physics (sensors-actuators)– Electronics (interfacing)– Signal Processing (both A + D)– Control (Feedback)– Modelling

• Metrology– The science of “correct” measurement

• Account for interactions, artifacts, make standards


Autumn 2003


Definitions

• Transducers (Energy converters)– Sensors (Physical Electrical)

• Active (own power)– Photovoltaic, Thermovoltaic

• Passive (change impedance)– Thermistor, Photodiode

– Actuators (Electrical Physical)• Servo motors, Loudspeakers• Feedback!


Autumn 2003


Sensors / Instruments

• Sensor + Electronics is an instrument• Most discussion applies to eitherA lot of the work of instrumentation is about modelling:

– Sensor is typically a Thevenin or Norton Circuit– V/I source may be dependent on stimulus– Impedance may be dependent on stimulus– Need to maximise power from stimulus to circuit– Need to minimise input noise power.– Sensor may be sensitive to other stimuli (cross-sensitivity)– Can exploit cross-sensitivity to increase SNR, by modulating

secondary stimuli.


Autumn 2003


Typical Instrument

Sensor/ Transdu cer

Input Functions

Signal Conditioning and Processing

Ou tput Functions

Real Tim e Display

Data Storage

Transdu cers

Feed back

Physical Signals

Noise


Autumn 2003


Ideal sensors

• An ideal sensor:– Does not disturb the system it measures– Does not absorb any energy from the system it measures– Can present an ideal source (V or I) at its output– It is perfectly linear: Output = constant * Input– Has no offset: Zero input zero output– Can respond to any stimulus no matter how small– Does not add any noise of its own to the measurement– Is monotonic (e.g. bigger input bigger output)– Only responds to the intended stimulus


Autumn 2003


Real sensors

• A real sensor is a transducer which:– Disturbs the system it measures– Absorbs energy from the system it measures– Present a finite impedance (Thevenin or Norton) at its output– It is never linear: Output = f(Input)– Has some zero offset: finite output for zero input– There is a minimum magnitude stimulus it can respond to– It adds noise of its own to the measurement– May not be always monotonic: increasing in decreasing out– responds to other stimuli (e.g. temperature dependence of a

pressure sensor)


Autumn 2003


Sensor description

We describe a sensor as a Taylor series response w/ noise:

• Sensitivity (Gain) – output /input – linear Taylor term• Threshold or detectivity – Constant Taylor term• Zero offset• Non-linearity• Memory:

– Linear– Non-linear

• Hysteresis


Autumn 2003


Illustration of a sensor

Detectivity

Input (x)

Output (y)

Noise Floor

Zero Error

Gain Error

Dynamic Range

Resolution


Autumn 2003


Illustration of linearity

Best Fit"Ideal" Linear responseO

utput


Autumn 2003


Illustration of hysteresis

Output


Autumn 2003


More on sensors• Cross-sensitivity• Resolution• Dynamic range• Non-Monotonicity• Accuracy


Autumn 2003


Some sensors

• Active (derive power from signal)– Photovoltaic– Piezoelectric– Thermoelectric– Electromagnetic

Model as a Thevenin or Norton controlled source– Source a function of stimulus– Internal Impedance important, may also be a function of the

stimulus!– Need to do impedance matching to maximise SNR


Autumn 2003


Photovoltaic

IV Characteristic of PN junction

I

V

dark

Illuminated

Dark current

Open circuit Voltage


Autumn 2003


Piezoelectric

• Polarized Materials• Develop voltage proportional to strain

– Strain is fractional elongation• Applications

– Displacement transducers • BOTH sensors and actuators


Autumn 2003


Thermoelectric

• Two different types of material in contact– Metal– Semiconductor

• Sensors – Thermocouples

• Actuators– Heaters (forward bias)– Coolers (Reverse bias)


Autumn 2003


Electromagnetic

• Coils• Sensors

– Field sensors– Motion sensors

• Actuators– Motors


Autumn 2003


Sensor Types (2)• Passive (derive power from circuit)

– Variable “resistance”• Resistive temperature detectors (RTD, thermistors)• Magnetoresistance (Hall, GMR)• Photoconductors • Strain gauges

– Variable Reactance • Capacitance • Inductance

Model as a variable Impedance– Impedance a function of stimulus– Need to do impedance matching to maximise SNR


Autumn 2003


Temperature detectors

• Metals have positive R tempco: 2 3

0R R aT bT cT= + + + +… • Semiconductors have negative R tempco.

/geV kTI e−∝ • PN junctions have V at I const. prop to T

/eV kT Ts

kTVI I e rI eI

∂⇒ = =

∂

• BUT: IS is strong function of T =>need 2 PNs


Autumn 2003


Photoconductors

• PN junctions• Metal Semiconductor Metal• PIN• Avalanche PD• Photomultipliers


Autumn 2003


Photomultiplier

At each dynode the current is multiplied by an average factor m. The totalgain after n dynodes is G=mn . i.e. for each photoelectrons mn electrodes reach the anode. This number is noisy by mn/2, so that SNR=mn/2


Autumn 2003


Photomultipliers


Autumn 2003


Strain Gauge

• A thin wire will alter its cross/section will alter its resistance when under tension.

• To a first approximation R proportional to elongation dL/L

• by Hooke’s law, elongation is proportional to the force.


Autumn 2003


Hall sensor• Sensitive Magnetic Field Sensor • Use Semiconductor (low N)

HBV I R INe

= =

V+

V-

I

xx xyL L

yx yyH H

R RV IR RV I⎡ ⎤⎡ ⎤ ⎡ ⎤

= ⎢ ⎥⎢ ⎥ ⎢ ⎥⎣ ⎦ ⎣ ⎦⎣ ⎦

, , XX YY YX XY HL WR R R R RW L

ρ ρ= = = − =


Autumn 2003


Variable capacitance

• Fluid sensors: – C=C0h/H

fluidh

H

• Pressure sensors

• C=C0+a(P-P0)

P P0


Autumn 2003


Variable Inductance

• Position Displacement sensors:– Self inductance

• Move core or coil (microphone, motor)– Mutual Inductance

• Move two coils relative to each other (phono cartr.)


Autumn 2003


Strange things

• Fundamental physics often leads to excellent sensors

• A few examples– Quantum Hall Effect– Josephson Junction– SQUID


Autumn 2003


Quantum Hall effect• Strange universal behaviour• SI Standard for resistance!

( ) ( ) ( )2

25.8 , 0HhR n k R n

nne= = Ω =


Autumn 2003


Josephson Junction• Sandwich of two superconductors and insulator• Magnetic field detector• Extremely sensitive!

– Josephson made a 10fV voltmeter


Autumn 2003


Josephson Junction in RF• IV curve dramatically modified• Allows frequency generation –measurement• Steps V=Nhf !!!


Autumn 2003


The SQUID• Superconducting Quantum Interference Device• Ring of two Josephson Junctions• Ultimate magnetic field sensor (MEG!)

• , Φ0=h/2e=2.68 x 10-15 Wb

• Sensitivity: 10fT• Earth’s field: 50uT (Aurora borealis: 1uT)• Heartbeat currents: 50 pT• Brain currents : approx 100 fT

00

sinI I π Φ=

Φ


Autumn 2003


The SQUID as RF Detector• Excellent microwave receiver• Tuneable (by B)


Autumn 2003


Bridge Circuits• The Wheatstone Bridge• Zi can be R, L, C• Balance condition: Z1Z4=Z2Z3• Can be used for R, C, L, f measurement

R1

R2

R3

R4 Sense

ExcitationVcc


Autumn 2003


Bridge circuits (2)

• Can be electronically balanced:

R1

R2

R3

R4

+V

–V

RAVrefVBVA

Call V- =0, and then treat Vref and V+ by superposition.


Autumn 2003


Bridge circuits (3)• Example: simple capacitance bridge• R1 var R, R3 fixed R, R4 fixed C, R3 unknown• Cx=CREFRVAR/RREF

R1

R2

R3

R4 Sense

ExcitationVcc


Autumn 2003


Bridge Circuits (4)

• Use one branch as a sensor• Self calibration:

– Identical sensor w/o stimulous on adj. branch• Offset null!

– If possible interchange roles• Gain self calibration!

– Or use standards on reference branch• Example: ice water in T sensors


Autumn 2003


Bridge Circuits (4)

• Can use L and C together – Make freq. dependent bridge– Refer your measurement to time domain

• Resonant condition• Frequency Deviation from measurement.• MUCH more accurate• MUCH higher resolution

– Extensive lit. on bridges. READ it !(would be half a course by itself)


Autumn 2003


Conclusion• Think of the application• Don’t solve a bigger problem than needed• Work out realistic specifications• Be cautious of marketing claims of suppliers• Account for non-idealities:

– Nonlinearity– Offset– Non-monotonicity

• Model sensors as controlled sources: Thevenin, Norton• Include Noise (next topic)• Model other effects: Time response. Complex Z or Y


Autumn 2003


Conclusion (2)• Measure by comparison:

– Use Bridges– Use Standards

• Reduce to a time measurement– Easier– More accurate (more later in course)

• For difficult measurements MODULATE or• TALK to an expert to see if better sensor exists :

– A Physicist– A Chemist– A Mechanical Engineer– A Chemical Engineer


Autumn 2003


CONCLUSION

Think of the system!

Circuit Design solves only

part of the problem!

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Documents

Christos Papavassiliou - Circuits and Systems | Faculty of Engineering | Imperial ...cas.ee.ic.ac.uk/people/dario/files/E302/1Sensorsslides.pdf · · 2010-10-13sensors/transducers,