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Slides electrical instrumentation lecture 7 version 2


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  • 1. ET8.017Delft University of Technology El. Instr. Electronic Instrumentation Lecturer: Kofi Makinwa K.A.A.Makinwa@TUDelft.NL 015-27 86466 Room. HB13.270 EWI building Teaching Assistant: Saleh Heidary S.H.Shalmany@TUDelft.NL 1 ET8.017Delft University of Technology Introduction El. Instr. Goal of a measurement system: – Get the most out of a measurement or sensor – in terms of information quality How? – Filtering (averaging) and shielding – Compensation (e.g. feed-forward) – Correction (e.g. auto-zeroing) – Feedback – Modulation and correlation 2 1
  • 2. Accuracy, precision ET8.017Delft University of Technology (resolution) and stability El. Instr. Precise but Not accurate and Accurate but Accurate and not accurate not precise not precise precise f f f f 0 Time Time Time Time Accurate Stable but Not stable and Stable and (on the average) not accurate not accurate accurate but not stable 4-2 3 ET8.017Delft University of Technology Signal processing techniques El. Instr. Add-on techniques: Built in techniques: filtering compensation – prefiltering – balancing – bridge – postfiltering – correlation feedback – requires an inverse correction transducer (actuator) – post-processing modulation (e.g. auto-zeroing, – chopping linearization) – spinning – swapping 4 2
  • 3. ET8.017Delft University of Technology Filtering: general principle El. Instr. prefilter postfilter interference measurand sensor processor out reduces additive errors in a specified frequency band reduces the effects of thermal noise 5 ET8.017Delft University of Technology Pre-filtering El. Instr. Pre-filtering (prior to transduction) Mitigates the effects of: – electrically induced signals (capacitive) ⇒ shielding – magnetically induced signals (inductive) ⇒ reducing loop area; shielding – changes in environmental temperature ⇒ isolation – unwanted optical input ⇒ optical filters – mechanical disturbances (shocks, vibrations) ⇒ dampers – ..... 6 3
  • 4. Electrically-induced ET8.017Delft University of Technology interference El. Instr. Cs sensor system interface system Vn,o Vn,i Cg Cs << C g Vn,i: voltage noise source Cs Vn ,o = Vn ,i Cs: capacitance between noise source and signal leads Cg Cg: capacitance between signal leads and ground 7 ET8.017Delft University of Technology Shielding El. Instr. Crest Cg Csh sensor system interface system Vn,o Vn,i Crest Vn ,o = Vn ,i → 0 Csh Crest: rest capacitance between noise source and signal leads Cg: capacitance between noise source and ground Csh: capacitance between shield and signal leads 8 4
  • 5. ET8.017Delft University of Technology Post-filtering El. Instr. post-filtering (after transduction) in the electrical domain – low pass, high pass, band pass – first order, .... higher order – characteristic (Butterworth, Bessel,...) – analog, digital – Matched filtering If the time-domain characteristics of the measurand are known, correlation and windowing techniques can be used 9 ET8.017Delft University of Technology Post-filtering El. Instr. High-pass filter removes 50Hz interference from ambient light sources 10 5
  • 6. ET8.017Delft University of Technology Correction El. Instr. Add-on to an existing system – model-based correction (after calibration) – correction of cross sensitivities (extra sensors) Correcting for additive errors – auto-zeroing – CDS Correcting for multiplicative errors – linearization – 3-signal method (calibration of linear systems) 11 ET8.017Delft University of Technology Correction - Overview El. Instr. measured model data data additional sensor interference measurand sensor processor out system reference Can cancel both additive and multiplicative errors But additional sensors and multiple errors limit the achievable accuracy 12 6
  • 7. ET8.017Delft University of Technology Compensation El. Instr. where? – pre-compensation (inherent design) – post-compensation (model-based signal correction) which strategy? – balancing – feedforward – feedback (with an actuator) 13 ET8.017Delft University of Technology Balancing: General principle El. Instr. interference sensor processor measurand out compensating element reduces (common) additive errors improves dynamic range Examples dummy sensor: used to compensate for environmental influences Extra temperature sensor: used to compensate for unwanted temperature dependencies 14 7
  • 8. ET8.017Delft University of Technology Bridge compensator El. Instr. • for accurate absolute measurements of resistances  R2 − R4  R3 Vo = V i R1  R1 + R2 R3 + R4  Vi Vo R2 R3 = R1R4 R2 ? R4 R2 = R1 ( R4 R3 ) • Insensitive to CM disturbances e.g. temperature • but requires an accurate, adjustable resistor 15 ET8.017Delft University of Technology Switched Cap “Resistor” El. Instr. Switched cap network emulates an adjustable resistance - Effective resistance value: Rref = Tclk/C2 M. Perrot et al., ISSCC 2012 16 8
  • 9. ET8.017Delft University of Technology Bridge indicator El. Instr. • measures small changes with respect to "an initial” value  R2 − R4  Vo = V i R1 R3  R1 + R2 R3 + R4  Vi Vo initially: resistances have values such that R2 R4 R02 R03 = R01R04 • but output is sensitive to drift and error in Vi 17 ET8.017Delft University of Technology Ratiometric readout El. Instr. ADC and bridge use the same reference voltage Vref ⇒ errors in Vref do not affect digital output 18 9
  • 10. ET8.017Delft University of Technology Assignment 8 El. Instr. Consider the ratiometric system shown on the previous slide. If the noise densities shown for the bridge, preamp and ADC, correspond to the situation when the bridge is balanced: 1. Calculate the resistance of each arm of the bridge 2. If the measurement BW is 10Hz, how many bits of resolution must the ADC have in order to ensure that the resolution of the system is determined by thermal noise rather than by quantization errors. 3. If the ADC has 20-bit resolution (not necessarily the answer to question 2 above) what percentage change in the resistance of a bridge element corresponds to a 1LSB change in its digital output. 19 ET8.017Delft University of Technology Differential measurements El. Instr. xn interference measurand sensor y1 xm ycomp processor out compensating sensor y2 Sm1: sensitivity sensor 1 to measurand y1 = S m1 xm + S n1 xn opposite sensitivity Sm2: sensitivity sensor 2 to measurand y2 = − S m 2 xm + S n 2 xn by design! Sn1: sensitivity sensor 1 to interference Sn2: sensitivity sensor 2 to interference ycomp = ( Sm1 + Sm 2 ) xm + ( Sn1 − Sn 2 ) xn  ∆S  CMRR = 2Sm ycomp = 2Sm xm + ∆Sn xn = 2Sm  xm + n xn  2Sm  ∆S n  20 10
  • 11. Differential capacitive ET8.017Delft University of Technology displacement sensor El. Instr. differential ∆x +Vi C1 Cf C2 -Vi C1 V1 Io C2 2 ∆C V2 I o = jω ⋅ ⋅Vi Cf 1 + 2 Co C f I 21 ET8.017Delft University of Technology Differential sensor interface El. Instr. C1 Cf Vi V -Vi Vo = − C1 + i C2 Cf Cf R C1 = Co + ∆C C2 Vi _ C 2 = C o − ∆C Vo + Vi Vo = 2 ∆C Cf The resistance R reduces drift But it introduces extra noise and gives rise to a frequency-dependent transfer function 22 11
  • 12. ET8.017Delft University of Technology The utility of feedback El. Instr. If A(f)•β >>1 ⇒ ACL ≅ 1/β. For moderate 1/β, op-amp DC gain is large enough! β ⇒ Resistor/Capacitor ratios. Resistors ⇒ 0.01%, 5 ppm/° C Capacitors ⇒ 1%, 500 ppm/° C ⇒ ACL can be very accurately defined. 23 ET8.017Delft University of Technology Feedback: General principle El. Instr. interference sensor processor out measurand feedback reduces multiplicative errors improves dynamic behaviour 24 12
  • 13. General application of ET8.017Delft University of Technology feedback El. Instr. xm yo S0 + S0 Sf = 1 + S0 ⋅ k − k dS f 1 dS = ⋅ 0 Sf 1 + k ⋅ S 0 S0 Prerequisites for effective error reduction are: – high forward path transfer – stable feedback path transfer 25 ET8.017Delft University of Technology Example 1: Accelerometer El. Instr. seismic mass V(∆C) sensor a interface Vo differential capacitor ∆x actuator ∆x ∆C VC Fi Fs a inertia spring sensor interface gain Vo + − Fa actuator 26 13
  • 14. Analysis of a feedback ET8.017Delft University of Technology accelerometer (1) El. Instr. ∆x ∆C VC Fi Fs a inertia spring sensor interface gain Vo + − Fa actuator HsHe Hi: transfer from acceleration a to inertial force Fi Vo = Hia 1+ Ha Hs He Hs: transfer from force Fs on sensor to displacement ∆x if : H a H s >> 1: He: transfer from displacement to output voltage Vo Ha: transfer of actuator: from output voltage Vo to Fa Hi Vo = a Ha Independent of system parameters of the spring, sensor, interface, gain factor Transfer function depends only on mass and actuator 27 ET8.017Delft University of Technology Example 2: Wind sensor El. Instr. 28 14
  • 15. ET8.017Delft University of Technology Thermal balancing El. Instr. Airflow Sensor Chip Cross- Section Heater Thermopile Heater δT Controller Airflow induces an on-chip temperature gradient δT This is sensed by an on-chip thermopile and cancelled by a pair of heaters Transfer function only depends on the heaters (resistors) and their supply voltage 29 ET8.017Delft University of Technology Wind sensor chip El. Instr. On-chip heaters Thermopiles ⇒ wind induced temperature differences δTNS & δTEW On-chip controllers nulls δTNS & δTEW |δP| ⇒ wind speed arg(δP) ⇒ wind direction 30 15
  • 16. ET8.017Delft University of Technology Smart wind sensor chip El. Instr. Digital outputs δPNS & δPEW After calibration: Speed error: ± 4% Angle error: ± 2° Comparable to conventional wind sensors But no moving parts! 31 ET8.017Delft University of Technology Modulation: General principle El. Instr. modulation demodulation interference measurand sensor processor out Basic ideas: shift information to a quiet frequency bands OR make information more robust Reduces additive errors In particular, offset, drift, LF noise and gain error 32 16
  • 17. ET8.017Delft University of Technology Modulation types El. Instr. in modulator out carrier AM modulation: Chopping, synchronous detection, dynamic element matching FM modulation: Used to make information more robust to amplitude variations Pulse-width (or duty-cycle) modulation: also used to make information more robust to amplitude variations, also used for simple digital-to-analog conversion 33 The Thermal Management ET8.017Delft University of Technology Challenge! El. Instr. Intel 45nm Xeon Courtesy of S. Rusu Intel SoCs and multi-core processors ⇒ multiple hot spots Hot spot location depends on (dynamic) workload ⇒ multiple (20+) temperature sensors 34 17
  • 18. ET8.017Delft University of Technology Thermal Diffusivity Sensing El. Instr. Heater generates small heat pulses (mWs) Temperature sensor picks up delayed pulses (mVs) Resulting thermal delay is temperature-dependent Exploits the strengths of CMOS technology: – Lithography accurate spacing s – Pure silicon substrate DSi is well-defined – Fast circuits accurate delay measurements 35 ET8.017Delft University of Technology A CMOS ETF El. Instr. • Heater = n+-diffusion resistor • Temp. sensor = p+/Al thermopile Heater Thermopile • Can be made in any IC process! S • Circular, differential 100 µm layout for maximum output 36 18
  • 19. ET8.017Delft University of Technology Smart TD Sensor El. Instr. φETF ∝ s f drive / DSi At room temp, s =20µm, f = 100kHz ⇒ φETF ~ 90° Quartz-crystal clock generates fdrive (typ. 100s of kHz) φETF is digitized by a phase-domain Σ∆ modulator Resolution is mainly limited by ETF’s thermal noise [van Vroonhoven, Makinwa, ISSCC 2008] 37 ET8.017Delft University of Technology Phase Digitizer El. Instr. How to accurately measure the phase of a small (1mVpp) and noisy signal? Use feedback, an ADC and a digital phase generator Then digitally filter the result (few Hz BW) 38 19
  • 20. ET8.017Delft University of Technology ∆ΣM Phase-Domain ∆Σ El. Instr. Since the sensor’s BW is so low, we can over-sample its output and then average ⇒ a 1-bit ADC is enough! This technique is known as sigma-delta modulation 12-bit resolution in 0.5Hz BW fs > 2kHz easy! 39 ET8.017Delft University of Technology Subtracting phase? El. Instr. Use a synchronous detector! DAC references are just phase-shifted copies of fdrive multiplier inputs are at same frequency DC ∝ cos(φETF – φfb ) = 0 when φfb = φETF – 90° Approx. linear close to (φETF – φfb ) = 90° 40 20
  • 21. ET8.017Delft University of Technology Performance El. Instr. Untrimmed spread is mainly limited by lithography – ±0.6ºC (3σ) in 0.7µm CMOS – ±0.2ºC (3s) in 0.18µm CMOS (same ETF layout) Accurate, and scales! 41 Overview: Signal processing ET8.017Delft University of Technology techniques El. Instr. modulation demodulation correction model measured prefilter postfilter data data interference measurand sensor processor out compensating sensor basic system additional systems feedback inherent design 42 21
  • 22. ET8.017Delft University of Technology THE END! El. Instr. 43 ET8.017Delft University of Technology Assignment 9 El. Instr. The thermal diffusivity of silicon is proportional to 1/T1.8 where T is absolute temperature If an electrothermal filter has a phase shift of 90° at 300K, calculate its phase-shift at the extremes of the military temperature range, i.e.-55°C and 125°C A smart TD sensor employs a phase digitizer. How many bits of resolution should it have in order to achieve a temperature-sensing resolution of 0.1°C? If the phase digitizer employs the feedback architecture shown on slide 38 and uses a chopper as a phase detector, what range of phases must its phase DAC provide in order for the sensor to cover the military range? 44 22