Data Acquisition and Signal Processing for Smart Sensors

291 Pages·2002·2.78 MB·English

by  Nikolay V. Kirianaki Sergey Y. Yurish Nestor O. Shpak Vadim P. Deynega

DataAcquisitionandSignalProcessingforSmartSensors
NikolayKirianaki,SergeyYurish,NestorShpak,VadimDeynega
Copyright2002JohnWiley&SonsLtd
ISBNs:0-470-84317-9(Hardback);0-470-84610-0(Electronic)
DATA ACQUISITION AND
SIGNAL PROCESSING
FOR SMART SENSORS
DATA ACQUISITION AND
SIGNAL PROCESSING
FOR SMART SENSORS
Nikolay V. Kirianaki and Sergey Y. Yurish
International Frequency Sensor Association, Lviv, Ukraine
Nestor O. Shpak
Institute of Computer Technologies, Lviv, Ukraine
Vadim P. Deynega
State University Lviv Polytechnic, Ukraine
Copyright2002byJohnWiley&Sons,Ltd
BaffinsLane,Chichester,
WestSussex,PO191UD,England
National 01243779777
International ([phone]
e-mail(forordersandcustomerserviceenquiries):[email protected]
VisitourHomePageonhttp://www.wileyeurope.com
AllRightsReserved.Nopartofthispublicationmaybereproduced,storedinaretrievalsystem,or
transmitted,inanyformorbyanymeans,electronic,mechanical,photocopying, recording,
scanningorotherwise,exceptunderthetermsoftheCopyright,DesignsandPatentsAct1988or
underthetermsofalicenceissuedbytheCopyrightLicensingAgencyLtd,90TottenhamCourt
Road,London,UKW1P0LP,withoutthepermissioninwritingofthePublisher.
NeithertheauthorsnorJonWiley&SonsLtdacceptanyresponsibilityorliabilityforlossor
damageoccasionedtoanypersonorpropertythroughusingthematerial,instructions,methodsor
ideascontainedherein,oractingorrefrainingfromactingasaresultofsuchuse.Theauthorsand
Publisherexpresslydisclaimallimpliedwarranties,includingmerchantabilityoffitnessforany
particularpurpose.
Designationsusedbycompaniestodistinguishtheirproductsareoftenclaimedastrademarks.In
allinstanceswhereJohnWiley&Sonsisawareofaclaim,theproductnamesappearininitial
capitalorcapitalletters.Readers,however,shouldcontacttheappropriatecompaniesformore
completeinformationregardingtrademarksandregistration.
OtherWileyEditorialOffices
JohnWiley&Sons,Inc.,605ThirdAvenue,
NewYork,NY10158-0012,USA
Wiley-VCHVerlagGmbH,Pappelallee3,
D-69469Weinheim,Germany
JohnWiley&SonsAustralia,Ltd,33ParkRoad,Milton,
Queensland4064,Australia
JohnWiley&Sons(Asia)PteLtd,2ClementiLoop#02-01,
JinXingDistripark,Singapore129809
JohnWiley&Sons(Canada)Ltd,22WorcesterRoad,
Rexdale,OntarioM9W1L1,Canada
LibraryofCongressCataloging-in-PublicationData
Dataacquisitionandsignalprocessingforsmartsensors/NikolayV.Kirianaki...[etal.].
p.cm.
Includesbibliographicalreferencesandindex.
ISBN0-470-84317-9(alk.paper)
1.Detectors.2.Microprocessors.3.Signalprocessing.4.Automaticdatacollection
systems.I.Kirianaki,NikolaiVladimirovich.
TA165.D382001
681(cid:1).2–dc21 2001046912
BritishLibraryCataloguinginPublicationData
AcataloguerecordforthisbookisavailablefromtheBritishLibrary
ISBN0470843179
Typesetin10/12ptTimesbyLaserwordsPrivateLimited,Chennai,India
PrintedandboundinGreatBritainbyBiddlesLtd,Guildford&King’sLynn
Thisbookisprintedonacid-freepaperresponsiblymanufacturedfromsustainableforestry,
inwhichatleasttwotreesareplantedforeachoneusedforpaperproduction.
CONTENTS
Preface ix
List of Abbreviations and Symbols xiii
Introduction xv
1 Smart Sensors for Electrical and Non-Electrical, Physical and
Chemical Variables: Tendencies and Perspectives 1
1.1 Temperature IC and Smart Sensors 8
1.2 Pressure IC and Smart Sensors and Accelerometers 14
1.3 Rotation Speed Sensors 18
1.4 Intelligent Opto Sensors 23
1.5 Humidity Frequency Output Sensors 24
1.6 Chemical and Gas Smart Sensors 24
Summary 27
2 Converters for Different Variables to Frequency-Time
Parameters of the Electric Signal 29
2.1 Voltage-to-Frequency Converters (VFCs) 29
2.2 Capacitance-to-Period (or Duty-Cycle) Converters 47
Summary 50
3 Data Acquisition Methods for Multichannel Sensor
Systems 51
3.1 Data Acquisition Method with Time-Division Channelling 52
3.2 Data Acquisition Method with Space-Division Channelling 55
3.3 Smart Sensor Architectures and Data Acquisition 57
3.4 Main Errors of Multichannel Data-Acquisition Systems 59
3.5 Data Transmission and Error Protection 61
3.5.1 Essenceofquasi-ternarycoding 62
3.5.2 Codingalgorithmandexamples 62
3.5.3 Quasi-ternarycodedecoding 65
Summary 67
vi CONTENTS
4 Methods of Frequency-to-Code Conversion 69
4.1 Standard Direct Counting Method (Frequency Measurement) 70
4.2 Indirect Counting Method (Period Measurement) 74
4.3 Combined Counting Method 79
4.4 Method for Frequency-to-Code Conversion Based on Discrete
Fourier Transformation 82
4.5 Methods for Phase-Shift-to-Code Conversion 85
Summary 86
5 Advanced and Self-Adapting Methods of Frequency-to-Code
Conversion 89
5.1 Ratiometric Counting Method 89
5.2 Reciprocal Counting Method 94
5.3 M/T Counting Method 94
5.4 Constant Elapsed Time (CET) Method 96
5.5 Single- and Double-Buffered Methods 96
5.6 DMA Transfer Method 97
5.7 Method of Dependent Count 98
5.7.1 Methodofconversionforabsolutevalues 99
5.7.2 Methodsofconversionforrelativevalues 100
5.7.3 Methodsofconversionforfrequencydeviation 104
5.7.4 Universalmethodofdependentcount 104
5.7.5 Exampleofrealization 105
5.7.6 Metrologicalcharacteristicsandcapabilities 107
5.7.7 Absolutequantizationerror(cid:1)q 107
5.7.8 Relativequantizationerrorδq 109
5.7.9 Dynamicrange 110
5.7.10 Accuracyoffrequency-to-codeconvertersbased
onMDC 112
5.7.11 Calculationerror 114
5.7.12 Quantizationerror(errorofmethod) 114
5.7.13 Referencefrequencyerror 114
5.7.14 Triggererror 115
5.7.15 Simulationresults 117
5.7.16 Examples 120
5.8 Method with Non-Redundant Reference Frequency 121
5.9 Comparison of Methods 123
5.10 Advanced Method for Phase-Shift-to-Code Conversion 125
Summary 126
6 Signal Processing in Quasi-Digital Smart Sensors 129
6.1 Main Operations in Signal Processing 129
6.1.1 Addingandsubtraction 129
6.1.2 Multiplicationanddivision 130
6.1.3 Frequencysignalunification 132
6.1.4 Derivationandintegration 135
CONTENTS vii
6.2 Weight Functions, Reducing Quantization Error 136
Summary 142
7 Digital Output Smart Sensors with Software-Controlled
Performances and Functional Capabilities 143
7.1 Program-Oriented Conversion Methods Based on Ratiometric
Counting Technique 145
7.2 Design Methodology for Program-Oriented Conversion Methods 150
7.2.1 Example 158
7.3 Adaptive PCM with Increased Speed 161
7.4 Error Analysis of PCM 164
7.4.1 Referenceerror 165
7.4.2 Calculationerror 171
7.4.3 ErrorofT02 forming 173
7.5 Correction of PCM’s Systematic Errors 174
7.6 Modified Method of Algorithm Merging for PCMs 175
Summary 182
8 Multichannel Intelligent and Virtual Sensor Systems 183
8.1 One-Channel Sensor Interfacing 183
8.2 Multichannel Sensor Interfacing 184
8.2.1 Smartrotationspeedsensor 185
8.2.2 Encoder 187
8.2.3 Self-adaptivemethodforrotationspeedmeasurements 188
8.2.4 Sensorinterfacing 190
8.3 Multichannel Adaptive Sensor System with Space-Division
Channelling 193
8.4 Multichannel Sensor Systems with Time-Division Channelling 197
8.5 Multiparameters Sensors 199
8.6 Virtual Instrumentation for Smart Sensors 199
8.6.1 Setofthebasicmodelsformeasuringinstruments 201
8.7 Estimation of Uncertainty for Virtual Instruments 215
Summary 224
9 Smart Sensor Design at Software Level 225
9.1 Microcontroller Core for Smart Sensors 225
9.2 Low-Power Design Technique for Embedded Microcontrollers 227
9.2.1 Instructionselectionandordering 234
9.2.2 Codesizeandspeedoptimizations 234
9.2.3 Jumpandcalloptimizations 236
9.2.4 Cycleoptimization 237
9.2.5 Minimizingmemoryaccesscost 239
9.2.6 Exploitinglow-powerfeaturesofthehardware 240
9.2.7 Compileroptimizationforlowpower 241
Summary 244
viii CONTENTS
10 Smart Sensor Buses and Interface Circuits 245
10.1 Sensor Buses and Network Protocols 245
10.2 Sensor Interface Circuits 248
10.2.1 Universaltransducerinterface(UTI) 248
10.2.2 Time-to-digitalconverter(TDC) 252
Summary 253
Future Directions 255
References 257
Appendix A What is on the Sensors Web Portal? 267
Glossary 269
Index 275
PREFACE
Smartsensorsareofgreatinterestinmanyfieldsofindustry,controlsystems,biomed-
ical applications, etc. Most books about sensor instrumentation focus on the classical
approachtodataacquisition,thatistheinformationisintheamplitudeofavoltageora
current signal. Only a few book chapters, articles and papers consider data acquisition
fromdigitalandquasi-digitalsensors.Smartsensorsandmicrosensorsincreasinglyrely
onresonantphenomenaandvariableoscillators,wheretheinformationisembeddednot
intheamplitude butinthefrequencyortimeparameteroftheoutput signal.Asarule,
the majority of scientific publications dedicated to smart sensors reflect only the tech-
nological achievements of microelectronics. However, modern advanced microsensor
technologies require novel advanced measuring techniques.
Because data acquisition and signal processing for smart sensors have not been
adequately covered in the literature before, this book aims to fill a significant gap.
Thisbookisbasedon40yearsoftheauthors’practicalexperienceinthedesignand
creation of sensor instrumentation as well as the development of novel methods and
algorithmsforfrequency–time-domainmeasurement,conversionandsignalprocessing.
Digitalandquasi-digital(frequency,period,duty-cycle,timeintervalandpulsenumber
output) sensors are covered in this book.
Research results, described in this book, are relevant to the authors’ international
research in the frame of different R&D projects and International Frequency Sensor
Association (IFSA) activity.
Who Should Read this Book?
This book is aimed at PhD students, engineers, scientists and researchers in both
academia and industry. It is especially suited for professionals working in the field
of measuring instruments and sensor instrumentation as well as anyone facing new
challenges in measuring, and those involved in the design and creation of new digital
smart physical or chemical sensors and sensor systems. It should also be useful for
students wishing to gain an insight into this rapidly expanding area. Our goal is to
providethereaderwithenoughbackgroundtounderstandthenovelconcepts,principles
and systems associated with data acquisition, signal processing and measurement so
that they can decide how to optimize their sensor systems in order to achieve the best
technical performances at low cost.
x PREFACE
How this Book is Organized
This book has been organized into 10 chapters.
Chapter 1, Smart sensors for electrical and non-electrical, physical and chemical
quantities: the tendencies and perspectives, describes the main advantages of
frequency–time-domain signals as informative parameters for smart sensors. The
chapter gives an overview of industrial types of smart sensors and contains
classifications of quasi-digital sensors. Digital and quasi-digital (frequency, period,
duty-cycle, time interval and pulse number output) sensors are considered.
Chapter 2, Convertersfordifferentvariablestofrequency–timeparametersofelec-
tric signals, deals with different voltage (current)-to-frequency and capacitance-to-
period (or duty-cycle) converters. Operational principles, technical performances and
metrological characteristics of these devices are discussed from a smart sensor point
of view in order to produce further conversion in the quasi-digital domain instead of
the analog domain. The open and loop (with impulse feedback) structures of such
converters are considered. (Figures 2.11, 2.12, 2.13, 2.14, 2.15 and some of the text
appearing in Chapter 2, section 2.1, are reproduced from New Architectures of Inte-
grated ADC, PDS ’96 Proceedings. Reproduced by permission of Maciej Nowinski.)
Chapter3,Dataacquisitionmethodsformultichannelsensorsystems,coversmulti-
channelsensorsystemswithcyclical,acceleratedandsimultaneoussensorpolling.Data
acquisition methods with time-division and space-division channelling are described.
The chapter contains information about how to calculate the time-polling cycle for
a sensor and how to analyse the accuracy and speed of data acquisition. Main smart
sensorarchitecturesareconsideredfromadataacquisitionpointofview.Datatransmit-
ting and error protection on the basis of quasi-ternary cyclic coding is also discussed.
Chapter 4, Methods of frequency-to-code conversion for smart sensors, discusses
traditional methods for frequency (period)-to-code conversion, including direct, indi-
rect, combined, interpolation, Fourier conversion-basedcounting techniques as well as
methodsforphase-shift-to-codeconversion.Suchmetrologicalcharacteristicsasquan-
tization error, conversion frequency range and conversion speed as well as advantages
and disadvantages for each of the methods are discussed and compared.
Chapter 5, Advanced and self-adapting methods of frequency-to-code conversion,
discusses reciprocal, ratiometric, constant elapsed time (CET), M/T, single-buffered,
double-bufferedand DMA transfer advanced methods. Comparative and cost-effective
analyses are given. Frequency ranges, quantization errors, time of measurement and
other metrological performances as well as hardware and software requirements for
realization from a smart sensor point of view are described. This chapter is very
important because it also deals with the concepts, principles and nature of novel self-
adapting methods of dependent count (MDC) and the method with non-redundant
reference frequency. The chapter covers main metrological performances including
accuracy,conversiontime,frequencyrangeaswellassoftwareandhardwareforMDC
realization. Advanced conversion methods for frequencies ratio, deviations and phase
shifts are also described. Finally, some practical examples and modelling results are
presented.
Chapter 6, Signal processing for quasi-digital smart sensors, deals with the main
frequencysignalmanipulationsincludingmultiplication,division,addition,subtraction,
derivation, integration and scaling. Particular attention has been paid to new methods