Partitioning Data Acquisition Systems (Design Conference 2013)

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Acquired analog signals can be manipulated and processed by either the analog or digital portions of a system, for example, through filtering, multiplexing, and gain control. The analog portions of a system can typically provide reasonably simple processing at fairly low cost, power, and overhead. Digital processing can provide far greater analysis power and can alter the nature of the analysis without changing hardware. Sampling theory, however, must be taken into account. This session covers the signal chain basics from signal to sensor to amplifier to converter to digital processor and back out again.

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Partitioning Data Acquisition Systems (Design Conference 2013)

  1. 1. Advanced Techniques of Higher Performance Signal ProcessingPartitioning Data AcquisitionSystems
  2. 2. Legal Disclaimer Notice of proprietary information, Disclaimers and Exclusions Of WarrantiesThe ADI Presentation is the property of ADI. All copyright, trademark, and other intellectual property andproprietary rights in the ADI Presentation and in the software, text, graphics, design elements, audio and allother materials originated or used by ADI herein (the "ADI Information") are reserved to ADI and its licensors.The ADI Information may not be reproduced, published, adapted, modified, displayed, distributed or sold inany manner, in any form or media, without the prior written permission of ADI.THE ADI INFORMATION AND THE ADI PRESENTATION ARE PROVIDED "AS IS". WHILE ADI INTENDS THEADI INFORMATION AND THE ADI PRESENTATION TO BE ACCURATE, NO WARRANTIES OF ANY KIND AREMADE WITH RESPECT TO THE ADI PRESENTATION AND THE ADI INFORMATION, INCLUDING WITHOUTLIMITATION ANY WARRANTIES OF ACCURACY OR COMPLETENESS. TYPOGRAPHICAL ERRORS ANDOTHER INACCURACIES OR MISTAKES ARE POSSIBLE. ADI DOES NOT WARRANT THAT THE ADIINFORMATION AND THE ADI PRESENTATION WILL MEET YOUR REQUIREMENTS, WILL BE ACCURATE, ORWILL BE UNINTERRUPTED OR ERROR FREE. ADI EXPRESSLY EXCLUDES AND DISCLAIMS ALL EXPRESSAND IMPLIED WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT OF ANY THIRD PARTY INTELLECTUAL PROPERTY RIGHTS. ADI SHALL NOT BERESPONSIBLE FOR ANY DAMAGE OR LOSS OF ANY KIND ARISING OUT OF OR RELATED TO YOUR USEOF THE ADI INFORMATION AND THE ADI PRESENTATION, INCLUDING WITHOUT LIMITATION DATA LOSSOR CORRUPTION, COMPUTER VIRUSES, ERRORS, OMISSIONS, INTERRUPTIONS, DEFECTS OR OTHERFAILURES, REGARDLESS OF WHETHER SUCH LIABILITY IS BASED IN TORT, CONTRACT OR OTHERWISE.USE OF ANY THIRD-PARTY SOFTWARE REFERENCED WILL BE GOVERNED BY THE APPLICABLE LICENSEAGREEMENT, IF ANY, WITH SUCH THIRD PARTY.©2013 Analog Devices, Inc. All rights reserved.2
  3. 3. Today’s AgendaThe dilemmas of system architecture and partitioningAnalog vs. digital signal processingThe perils of samplingDigital vs. digitalWhere to put all the processing functions Gain Sampling Filtering Multiplexing Special analog processing Isolation3
  4. 4. Analog to Electronic Signal ProcessingSENSOR(INPUT)DIGITALPROCESSORAMP CONVERTERACTUATOR(OUTPUT)AMP CONVERTER4
  5. 5. … in the Beginning …There was a sensor, mechanical driver, stylus, recording medium,playback stylus, and mechanical amplifier – it worked5
  6. 6. … and Then We Added Electronics …6
  7. 7. Current Day Integrated FunctionsAudio codecsSoundMAX® computer audiocodecsI/O portsMixed-signal front ends:modems, communications, CCDimaging, flat panel displaysTransmit and receive signalprocessorsDirect conversion radioEnergy meteringVideo encoders/decoders,codecsTouchscreen digitizersAnalog microcontrollers (highperformance ADCs, DACs, andARM µP core and flash memory)Blackfin® DSPs with on-boardADCs and DACsMotion sensors with embeddedADCs7
  8. 8. The Dilemmas of PartitioningWhy Digitize at All?Analog vs. Digital Processing Filtering Linearization DetectionMultiplexing Multiple amplifiers, filters, converters Simultaneous samplingSignal Control Gain ranging vs. high resolution Compression Filtering8
  9. 9. Analog and Digital DomainsWhy Convert to Digital?Analog signals are continuous and provide the entire signalDigital signals capture only a portion of the signalWhy digitize? Improved signal analysis potential More robust storage More accurate transmission Higher order filters implemented with less costDevelopment objective of sampled data systems is to minimizeeffect of the sampling process9
  10. 10. Analog vs. Digital DesignAnalog Design Advantages Simpler and quicker to implement Lower power Analog systems don’t crash and need rebootDisadvantages Difficult to change once in production – or at a customer Limited scaleDigital Design Advantages Changeable without hardware modification More filtering capability and scale Not sensitive to temperatureDisadvantages Initial software design takes longer More complex hardware Requires ADC that determines the SNR10
  11. 11. Digital vs. Digital DesignFPGA vs. DSPFPGA Pros Deliver higher performance through very high parallelism Flexible I/O to support high-speed analog interfaces Low fixed costs Quick design turns for hardware changesFPGA Cons Higher power in redundant logic Higher cost at volumeDSP Pros Programming is simpler – many libraries and third-party support companies Higher speed for straight processingDSP Cons Fixed hardware structure Limited scale for parallel processing11
  12. 12. The Costs of Digitizing SignalsYou need to learn sampling theoryThe input signal will be compromised – the goal is to determinewhat’s acceptableThe input signal needs to be filteredSignal reconstruction will require another data converter12
  13. 13. Many Types of Sampled Data SystemsAnalog-to-Digital ConvertersDigital-to-Analog ConvertersSample-and-Hold AmplifiersPeak DetectorsComparatorsSwitched Cap FiltersSamples a Continuous SignalDomain Conversion Analog to digital Digital to analog Continuous time to discrete time Continuous frequency to discretefrequencySampling Rate Continuous, discontinuous13
  14. 14. Sampled Data System: Samplingand QuantizationLPFORBPFN-BITADCDSPN-BITDACLPFORBPFfafs fstAMPLITUDEQUANTIZATION DISCRETETIME SAMPLINGfa1fsts=14
  15. 15. RESOLUTIONN2-bit4-bit6-bit8-bit10-bit12-bit14-bit16-bit18-bit20-bit22-bit24-bit2N416642561,0244,09616,38465,536262,1441,048,5764,194,30416,777,216VOLTAGE(10V FS)2.5 V625 mV156 mV39.1 mV9.77 mV (10 mV)2.44 mV610 V153 V38 V9.54 V (10 V)2.38 V596 nV*ppm FS250,00062,50015,6253,9069772446115410.240.06% FS256.251.560.390.0980.0240.00610.00150.00040.00010.0000240.000006dB FS– 12– 24– 36– 48– 60– 72– 84– 96– 108– 120– 132– 144*600nV is the Johnson Noise in a 10kHz BW of a 2.2k Resistor @ 25°CRemember: 10-bits and 10V FS yields an LSB of 10mV, 1000ppm, or 0.1%.All other values may be calculated by powers of 2.Quantization: The Size of a Least Significant Bit(LSB)15
  16. 16. Practical Resolution Needs for Data ConvertersInstrumentation Measurements Sensor resolution/accuracy of 0.5% = 1/200 8 bits equivalent to 1/256 -- digitizing will lose information 10x sensor resolution = 1/2000 -- 12 bits is 1/4096 Allows discrimination of small changes Can also be driven by display requirementsDynamic Signal Measurements Audio systems need better than 0.1% distortion at 5% of full scale Equivalent to 1/20,000 -- 16 bits is 1/65,53616
  17. 17. Ideal ADC Sampling3 Different Frequencies, Sampled the Same17
  18. 18. Ideal ADC SamplingOnce Sampled, Information Is Lost18
  19. 19. Baseband Antialiasing Filter RequirementsADRfsfa fs - fafs2STOPBAND ATTENUATION = DRTRANSITION BAND: fa to fs - faCORNER FREQUENCY: faAntialias Filter PreventsAliasingContributes to Dynamic RangeAntialias Filter Objectives Brick Wall (Steep/Deep Rolloff) Linear Passband Linear Phase19
  20. 20. A Key Partitioning Question—Where to Filter?Analog Filtering Hardware oriented—generally fixed designDigital Filtering Software oriented—offers more flexibility20
  21. 21. Purposes of FilteringNoise Reduction Typically low-passDiscrimination and Selection RF detection – channel separation Extracting small signals from noiseSignal Enhancement MusicFilter Complexity Derives from the Requirement21
  22. 22. Types of FiltersTypes of Analog filters Active More common at lower frequencies Passive More common at higher frequenciesTypes of Digital filters IIR (infinite impulse response) Based on analog filters More computationally efficient FIR (finite impulse response) Can be linear phase More computationally intensive Can provide more power and flexibilityDigital filtering requires digitizing—which requires an analog anti-aliasing filter before the analog-to-digital converter22
  23. 23. Comparing Analog and Digital FiltersAnalog No computational limitationsto limit high frequencyoperation Subject to component driftand accuracy Simpler circuit Unlimited dynamic range Basically no latencyDigital Computations must becompleted in sampling time—limits real-time operation Not subject to componentdrift and accuracy More complex circuit Requires antialiasing filter,ADC, DSP, DAC, andreconstruction filter Dynamic range limited byconverter resolution Much higher latency (delay) Some filter functions can onlybe done digitally23
  24. 24. Analog vs. Digital Filter FrequencyResponse Comparison
  25. 25. Digital Filtering
  26. 26. Throughput Considerations for Digital FiltersA digital biquad is a second-order recursive linear filter containingtwo poles and two zerosDetermine how many biquad sections (N) are requiredto realize the desired frequency responseMultiply this by the number of instruction cycles perbiquad for the DSP and add overhead cyclesThe result (plus overhead) is the minimum allowablesampling period (1 / fs) for real-time operation26
  27. 27. Comparison Between IIR and FIR Filters
  28. 28. Sigma-delta ADC -- the multi-purpose partSigma-delta ADCs span the analog and digital worldProvide customized filtering and high-resolution dataconversionThe core of digital audio processing28
  29. 29. 29Sigma-Delta ADC - First-Order Modulator  +_+VREF–VREFDIGITALFILTERANDDECIMATOR+_CLOCKKfsVINN-BITSfsfsAB1-BIT DATASTREAM1-BITDACLATCHEDCOMPARATOR(1-BIT ADC)1-BIT,KfsSIGMA-DELTA MODULATORINTEGRATOR
  30. 30. Sampled Data System:Sampling and Quantization
  31. 31. 31Simplified Frequency Domain Linearized Modelof a Sigma-Delta ModulatorANALOG FILTERH(f) = 1fX Y+_X – Y1f( X – Y )Q =QUANTIZATIONNOISEY =1f( X – Y ) + QREARRANGING, SOLVING FOR Y:Y =Xf + 1+Q ff + 1SIGNAL TERM NOISE TERMY
  32. 32. 32Oversampling, Digital Filtering,Noise Shaping, and Decimationfs2fsKfs2KfsKfsKfs2fs2fs2DIGITAL FILTERREMOVED NOISEREMOVED NOISEQUANTIZATIONNOISE = q / 12q = 1 LSBADCADCDIGITALFILTERSDMODDIGITALFILTERfsKfsKfsDECfsNyquistOperationOversampling+ Digital Filter+ DecimationOversampling+ Noise Shaping+ Digital Filter+ DecimationABCDECfs
  33. 33. Data Acquisition Subsystem ConfigurationMultiplexing Multiple preamps Multiple anti-alias filters Multiple ADCs Gain Adjustable gain per channel PGA vs. high resolution ADCSimultaneous Sampling Multiple signals correlated in timeNoise Reduction/Antialiasing Filter PlacementSpecial Analog ProcessingIsolation33
  34. 34. Data Acquisition Subsystem ConfigurationMultiplexingMultiplexing is done to reduce system cost by using fewer ADCs ADC is fast enough to handle all channels in sequence ADC errors are the same for all channelsMultiplexing issues Settling time after switching channels Multiplexer impedance may compromise signal Final buffer amplifier may be needed Multiplexer switching transientsCorrelated sampling may require a faster solution How close in time sampling needs to be done Nyquist theory determines how often each signal needs to be sampled Total signal throughput rate Simultaneous sampling at lower rates Simultaneous conversion at higher rates34
  35. 35. Simple ADC Multiplexing—AD72988 inputs plus temp sensor and single track/hold35
  36. 36. Simultaneous Sampling—AD76068 Track/Hold Inputs Sampled TogetherV1V1GNDRFB1MΩ1MΩ RFBCLAMPCLAMPSECOND-ORDER LPFT/HV2V2GNDRFB1MΩ1MΩ RFBCLAMPCLAMPSECOND-ORDER LPFT/HV3V3GNDRFB1MΩ1MΩ RFBCLAMPCLAMPSECOND-ORDER LPFT/HV4V4GNDRFB1MΩ1MΩ RFBCLAMPCLAMPSECOND-ORDER LPFT/HV5V5GNDRFB1MΩ1MΩ RFBCLAMPCLAMPSECOND-ORDER LPFT/HV6V6GNDRFB1MΩ1MΩ RFBCLAMPCLAMPSECOND-ORDER LPFT/HV7V7GNDRFB1MΩ1MΩ RFBCLAMPCLAMPSECOND-ORDER LPFT/HV8V8GNDRFB1MΩ1MΩ RFBCLAMPCLAMPSECOND-ORDER LPFT/H8:1MUXAGNDBUSYFRSTDATACONVST A CONVST B RESET RANGECONTROLINPUTSCLK OSCREFIN/REFOUTREF SELECTAGNDOS 2OS 1OS 0DOUTADOUTBRD/SCLKCSPAR/SER/BYTE SELVDRIVE16-BITSARDIGITALFILTERPARALLEL/SERIALINTERFACE2.5VREFREFCAPB REFCAPASERIALPARALLELREGCAP2.5VLDOREGCAP2.5VLDOAVCCAVCCDB[15:0]AD760608479-00136
  37. 37. Full High Speed Dual Sampling—AD96432 Complete Sampling ADCs at 170 MHz1414REFERENCESERIAL PORTSCLK SDIO CSB CLK+ CLK– SYNC1 TO 8CLOCKDIVIDERAD9643VIN+A D0±D13±DCO±OR±PDWNOEBVIN–AVIN+BVCMVIN–BNOTES1. THE D0± TO D13± PINS REPRESENT BOTH THE CHANNEL AAND CHANNEL B LVDS OUTPUT DATA.AVDD AGND DRVDD09636-001.....PARALLELDDR LVDSANDDRIVERSPIPELINE14-BITADCPIPELINE14-BITADC37
  38. 38. Positioning the Noise Reduction Filter toReduce the Effects of the Op Amp Noise ADCs often have very high input bandwidths, usually greater than fs/2 Low distortion drive amplifiers typically have high bandwidths Placing a simple LPF or BPF placed between the amp and the ADC isan excellent noise reduction technique Filter output impedance must be able to drive ADC The output capacitor of the filter absorbs some of the ADC inputtransient currents.2.38fFILTERAMPAMPLPFORBPFLPFORBPFADCADCfFILTERfsfsfCLfCLfADCfADC(A)(B)Amp noise integratedover amp BW or ADC BW,whichever is lessAmp noise integratedover filter noisebandwidth only
  39. 39. Where to Put the Gain?Partitioning question about using PGA vs. high resolution ADCPGA with wide-range gain steps can extend effective resolution ofADC Provides fine resolution Not an exact solution unless gain ranges are perfectly matched Nonlinearity induced between rangesNot as popular with advent of higher resolution ADCsStill useful in certain applications39
  40. 40. ADC Multiplexing with Programmable Gain—AD719416 inputs plus temp sensor and programmable gain amplifierAccommodates sensors with widely varying signal levels40DVDD DGND REFIN1(+) REFIN1(–)AIN1/P3AIN2/P2AIN3/P1/REFIN2(+)AIN4/P0/REFIN2(–)AINCOMAD7194SERIALINTERFACEANDCONTROLLOGICREFERENCEDETECTTEMPSENSORDOUT/RDYDINSCLKCSMCLK1 MCLK2CLOCKCIRCUITRYAVDD AGNDAIN5AIN16Σ-ΔADCPGAMUX08566-001AVDDAGND
  41. 41. Special Analog Processing and Special CasesCertain sensors require specialized analog processing to extractprecise measurements Thermocouples—cold-junction compensation Wide-dynamic-range photodiodes—signal compression LinearizationSome sensors require precision tuning per unit—others can betuned togetherCalibration and replacement issuesDigital options—store adjustment coefficients in softwareIsolation Analog or digital Power isolation41
  42. 42. ThermocouplesThermocouples require cold-junction compensation Traditionally done with specialized amplifiers with internal temperature sensors Newer techniques use high-accuracy temperature sensors and A-D convertersto allow compensation at the processorThermocouple non-linearity is non-linear Difficult to construct analog compensation Digital systems use look-up tablesDetailed analysis in the Low-Level Signal Acquisition session42
  43. 43. High Accuracy Multichannel ThermocoupleMeasurement Solution (CN0172)43
  44. 44. Log AmplifiersSignal compression Many applications must capture signals over a very wide dynamic range Radio antennas capturing broadcast signals Photomultipliers and photodiodes capture light signals over a very wide range To process and use these signals, they need to be compressed to a muchsmaller rangeLogarithmic amplifiers Log amplifiers compress signals over ranges of as much as 120db – a millionto one -- to a normal range of 1 to 10 volts Accuracy is typically 0.1 to 0.5 dB -- 1 to 5%Digital compression alternative Programmable gain amplifier combined with high-resolution ADC Can achieve range out to 120dB Limited at very high frequencies
  45. 45. Log Amp Transfer FunctionIDEALACTUALSLOPE = VY2VYVYIDEALACTUALVYLOG (VIN/VX)+-VIN=VXVIN=10VXVIN=100VXINPUT ONLOG SCALEVOUT = VY log100VINVXIDEALACTUALSLOPE = VY2VYVYIDEALACTUALVYLOG (VIN/VX)+-VIN=VXVIN=10VXVIN=100VXINPUT ONLOG SCALEVOUT = VY log100VINVX
  46. 46. Log Amplifier Accuracy54321–4–5500MHz100MHz10MHz–3–2–10–80 –70 –60 –50 –40 –30 –20 –10 0 10 20ERROR(dB)INPUT LEVEL (dBm)AD8307 covers 80dB with 0.5dB accuracy
  47. 47. AD8307 six-decade RF powermeasurementTOANTENNAVP604Ω100kΩ1/2WNC2kΩVR12kΩINT ±3dB51pF51pF0.1µFNCOUTPUTLEAD-THROUGHCAPACITORS,1nF1nFNC = NO CONNECT+5VVOUTAD8307INP VPS ENB INTINM COM OFS OUT8 7 6 52 3 4150Ω INPUTFROM P.A.1µW TO1kW22Ω
  48. 48. Oversampled SAR ADC with PGAAchieving Greater Than 125 dBDynamic Range (CN0260)Dynamic gain rangingFaster than high-resolution sigma deltaSampling rate up to 2.5MSPS48
  49. 49. Oversampled SAR ADC with PGA AchievingGreater Than 125 dB Dynamic Range(CN0260)49
  50. 50. Where to Put the Isolation?Isolation is used to galvanically separate systems Safety in patient monitoring High-voltage systems Remove high common-mode noiseMost commonly done at the digital level ADC converter signal to digital Transmitted across digital isolatorsProviding power to isolated circuits neededHigh-voltage amplifiers suitable in some motor control or powercontrol systemsMore detail in the Data and Power Isolation session50
  51. 51. 500 V Common-Mode Voltage Current Monitor(CN0218)51AD8212
  52. 52. 52Bidirectional Isolated High-Side Current Sensewith 270 V Common-Mode Rejection (CN0240)
  53. 53. Novel Analog-to-Analog Isolator Using anIsolated Sigma-Delta Modulator, IsolatedDC-to-DC Converter, and Active Filter (CN0185)53
  54. 54. Reverse PartitioningSmarter peripheral devices sensing local conditionsMake local decisions to off-load main processorReduce programming loadAutomatic gain controlPower control54
  55. 55. Reverse Partitioning—AD5755Quad 16-bit DAC for 4–20 mA industrial signalingDynamic power control for thermal managementOn-chip diagnostics55
  56. 56. Flexible 4-Channel Analog Front End for WideDynamic Range Signal Conditioning (CN0251)This circuit has it allMultiplexing front-endMultiplexer bufferInstrumentation amplifier for CMRRAnti-alias filterFunnel amplifier to fit ADC rangeInternal programmable gain amplifier Gain ranges trimmed and matchedSigma-delta ADC provides noise shaping56
  57. 57. Flexible 4-Channel Analog Front End for WideDynamic Range Signal Conditioning (CN0251)57
  58. 58. Tweet it out! @ADI_News #ADIDC13What We CoveredThe dilemmas of system architecture and partitioningAnalog vs. digital signal processingThe perils of samplingDigital vs. digitalWhere to put all the processing functions Gain Sampling Filtering Multiplexing Special analog processing Isolation58
  59. 59. Tweet it out! @ADI_News #ADIDC13Visit the Flexible 4-Channel Analog Front Endfor Wide Dynamic Range Signal Conditioning(CN0251) in the Exhibition RoomThis flexible signal conditioningcircuit is for processing signalsof wide dynamic range, varyingfrom several mV p-p to 20 V p-p.The circuit provides thenecessary conditioning andlevel shifting and achieves thedynamic range using the internalprogrammable gain amplifier(PGA) of the high resolutionanalog-to-digital converter(ADC).59Image of demo/boardThis demo board is available for purchase:www.analog.com/DC13-hardware
  60. 60. Tweet it out! @ADI_News #ADIDC13FMComms1 Demo in the Exhibition HallNew partitioning concepts for radioUbuntu Linux on ZC702FMComms1 on FMCHDMI Display and USBKeyboard/MouseFull Transmit and Receive60Image of demo/boardThis demo board is available for purchase:www.analog.com/DC13-hardware

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