
Modern Measurements
Description
Alles über E-Books | Antworten auf Fragen rund um E-Books, Kopierschutz und Dateiformate finden Sie in unserem Info- & Hilfebereich.
More details
Other editions
Additional editions


Persons
Content
PREFACE xv
ACRONYMS xvii
I FUNDAMENTALS 1
1 MEASUREMENT MODELS AND UNCERTAINTY 3
Alessandro Ferrero and Dario Petri
1.1 Introduction 3
1.2 Measurement and Metrology 4
1.3 Measurement Along the Centuries 5
1.3.1 Measurement in Ancient Greece 6
1.3.2 Measurement in the Roman Empire 6
1.3.3 Measurement in the Renaissance Period 7
1.3.4 Measurement in the Modern Age 8
1.3.5 Measurement Today 9
1.4 Measurement Model 10
1.4.1 A First Measurement Model 11
1.4.2 A More Complex Measurement Model 16
1.4.3 Final Remarks 19
1.5 Uncertainty in Measurement 20
1.5.1 The Origin of the Doubt 21
1.5.2 The Different Effects on the Measurement Result 23
1.5.3 The Final Effect 25
1.6 Uncertainty Definition and Evaluation 27
1.6.1 The Error Concept and Why it Should be Abandoned 28
1.6.2 Uncertainty Definition: The GUM Approach 29
1.6.3 Evaluating Standard Uncertainty 31
1.6.4 The Combined Standard Uncertainty 35
1.7 Conclusions 39
Further Reading 40
References 41
Exercises 41
2 THE SYSTEM OF UNITS AND THE MEASUREMENT STANDARDS 47
Franco Cabiati
2.1 Introduction 47
2.2 Role of the Unit in the Measurement Process 48
2.3 Ideal Structure of a Unit System 50
2.4 Evolution of the Unit Definition 52
2.5 The SI System of Units 53
2.6 Perspectives of Future SI Evolution 59
2.7 Realization of Units and Primary Standards 62
2.7.1 Meter Realization and Length Standards 65
2.7.2 Kilogram Realization and Mass Standards: Present Situation 66
2.7.3 Kilogram Realization: Future Perspective 67
2.7.4 Realization of the Second and Time Standards 69
2.7.5 Electrical Unit Realizations and Standards: Present Situation 71
2.7.6 Electrical Units Realization and Standards: Future Perspective 76
2.7.7 Kelvin Realization and Temperature Standards: Present Situation 78
2.7.8 Kelvin Realization and Temperature Standards: Future Perspective 79
2.7.9 Mole Realization: Present Situation 80
2.7.10 Mole Realization: Future Perspective 81
2.7.11 Candela Realization and Photometric Standards 82
2.8 Conclusions 83
Further Reading 83
References 84
Exercises 84
3 DIGITAL SIGNAL PROCESSING IN MEASUREMENT 87
Alessandro Ferrero and Claudio Narduzzi
3.1 Introduction 87
3.2 Sampling Theory 88
3.2.1 Sampling and Fourier Analysis 89
3.2.2 Band-Limited Signals 92
3.2.3 Interpolation 95
3.3 Measurement Algorithms for Periodic Signals 96
3.3.1 Sampling Periodic Signals 97
3.3.2 Estimation of the RMS Value 99
3.4 Digital Filters 102
3.5 Measuring Multi-Frequency Signals 106
3.5.1 Finite-Length Sequences 107
3.5.2 Discrete Fourier Transform 111
3.5.3 Uniform Window 113
3.5.4 Spectral Leakage 114
3.5.5 Leakage Reduction by the Use of Windows 116
3.6 Statistical Measurement Algorithms 119
3.7 Conclusions 120
Further Reading 121
References 122
Exercises 122
4 AD AND DA CONVERSION 125
Niclas Björsell
4.1 Introduction 125
4.2 Sampling 125
4.2.1 Quantization 126
4.2.2 Sampling Theorem 129
4.2.3 Signal Reconstruction 130
4.2.4 Anti-Alias Filter 133
4.3 Analog-to-Digital Converters 133
4.3.1 Flash ADCs 133
4.3.2 Pipelined ADCs 134
4.3.3 Integrating ADCs 134
4.3.4 Successive Approximation Register ADCs 135
4.4 Critical ADC Parameters 135
4.4.1 Gain and Offset 136
4.4.2 Integral and Differential Non-linearity 137
4.4.3 Total Harmonic Distortion and Spurious-Free Dynamic Range 139
4.4.4 Effective Number of Bits 139
4.5 Sampling Techniques 139
4.5.1 Oversampling 139
4.5.2 Sigma-Delta, S¿ 140
4.5.3 Dither 141
4.5.4 Time-Interleaved 142
4.5.5 Undersampling 142
4.5.6 Harmonic Sampling 143
4.5.7 Equivalent-Time Sampling 143
4.5.8 Model-Based Post-correction 144
4.6 DAC 144
4.6.1 Binary-Weighted 144
4.6.2 Kelvin Divider 145
4.6.3 Segmented 145
4.6.4 R-2R 145
4.6.5 PWM DAC 145
4.7 Conclusions 146
Further Reading 146
References 146
Exercises 147
5 BASIC INSTRUMENTS: MULTIMETERS 149
Daniel Slomovitz
5.1 Introduction 149
5.2 History 150
5.3 Main Characteristics 153
5.3.1 Ranges 153
5.3.2 Number of Digits and Resolution 155
5.3.3 Accuracy 158
5.3.4 Loading Effects 159
5.3.5 Guard 160
5.3.6 Four Terminals 161
5.3.7 Accessories 162
5.3.8 AC Measurements 164
5.3.9 Safety 167
5.3.10 Calibration 170
5.3.11 Selection 171
5.4 Conclusions 171
Further Reading 172
References 172
Exercises 173
6 BASIC INSTRUMENTS: OSCILLOSCOPES 175
Jorge Fernandez Daher
6.1 Introduction 175
6.2 Types of Waveforms 176
6.2.1 Sinewave 176
6.2.2 Square or Rectangular Wave 176
6.2.3 Triangular or Sawtooth Wave 176
6.2.4 Pulses 177
6.3 Waveform Measurements 177
6.3.1 Amplitude 177
6.3.2 Phase Shift 177
6.3.3 Period and Frequency 177
6.4 Types of Oscilloscopes 177
6.5 Oscilloscope Controls 181
6.5.1 Vertical Controls 183
6.5.2 Horizontal Controls 184
6.5.3 Trigger System 185
6.5.4 Display System 187
6.6 Measurements 188
6.6.1 Peak-to-Peak Voltage 188
6.6.2 RMS Voltage 188
6.6.3 Rise Time 188
6.6.4 Fall Time 188
6.6.5 Pulse Width 188
6.6.6 Period 190
6.6.7 Frequency 190
6.6.8 Phase Shift Measurements 190
6.6.9 Mathematical Functions 190
6.7 Performance Characteristics 191
6.7.1 Bandwidth 191
6.7.2 Rise Time 191
6.7.3 Channels 193
6.7.4 Vertical Resolution 193
6.7.5 Gain Accuracy 193
6.7.6 Horizontal Accuracy 193
6.7.7 Record Length 193
6.7.8 Update Rate 194
6.7.9 Connectivity 195
6.8 Oscilloscope Probes 195
6.8.1 Passive Probes 196
6.8.2 Active Probes 197
6.9 Using the Oscilloscope 199
6.9.1 Grounding 199
6.9.2 Calibration 199
6.10 Conclusions 199
Further Reading 200
References 200
Exercises 201
7 FUNDAMENTALS OF HARD AND SOFT MEASUREMENT 203
Luca Mari, Paolo Carbone and Dario Petri
7.1 Introduction 203
7.2 A Characterization of Measurement 206
7.2.1 Measurement as Value Assignment 206
7.2.2 Measurement as Process Performed by a Metrological System 209
7.2.3 Measurement as Process Conveying Quantitative Information 209
7.2.4 Measurement as Morphic Mapping 210
7.2.5 Measurement as Mapping on a Given Reference Scale 213
7.2.6 Measurement as Process Conveying Objective and Inter-Subjective Information 215
7.2.7 The Operative Structure of Measurement 216
7.2.8 A Possible Definition of "Measurement" 219
7.2.9 Hard Measurements and Soft Measurements 220
7.2.10 Multidimensional Properties 222
7.3 A Conceptual Framework of the Structure of Measurement 223
7.3.1 Goal Setting 225
7.3.2 Modeling 228
7.3.3 Design 241
7.3.4 Execution: Setup, Data Acquisition, Information Extraction and Reporting 243
7.3.5 Interpretation 245
7.4 An Application of the Measurement Structure Framework: Assessing Versus Measuring Research Quality 246
7.4.1 Motivations for Research Quality Measurement 246
7.4.2 Measurement Goal Definition 247
7.4.3 Modeling 250
7.4.4 Design 252
7.4.5 Execution 254
7.4.6 Interpretation 255
7.5 Conclusions 256
Further Reading 257
References 257
Exercises 260
II APPLICATIONS 263
8 SYSTEM IDENTIFICATION 265
Gerd Vandersteen
8.1 Introduction 265
8.2 A First Example: The Resistive Divider 265
8.3 A First Trial of Estimators 267
8.4 From Trial-and-Error to a General Framework 268
8.4.1 Setting up the Estimator 269
8.4.2 Uncertainty on the Estimates 270
8.4.3 Model Validation 271
8.4.4 Extracting the Noise Model 274
8.5 Practical Identification Framework for Instrumentation and Measurements 277
8.5.1 Dynamic Linear Time-Invariant (LTI) Systems 277
8.5.2 From Linear to Nonlinear Systems 280
8.5.3 Sine Fitting 280
8.5.4 Calibration and Compensation Techniques 282
8.6 Conclusions 282
Further Reading 283
References 283
Exercises 285
9 RELIABILITY MEASUREMENTS 287
Marcantonio Catelani
9.1 Introduction 287
9.2 Brief Remarks on the Concept of Quality 288
9.3 Reliability, Failure and Fault: Basic Concepts and Definitions 288
9.4 Reliability Theory 292
9.4.1 Reliability Models and Measures Related to Time to Failure 292
9.4.2 Life Distributions 298
9.4.3 Reliability Parameters 300
9.4.4 The Bath-Tube Curve 302
9.5 System Reliability Assessment 303
9.5.1 Series Configuration 304
9.5.2 Parallel Configuration 305
9.5.3 k-out-of-n Configuration 307
9.6 Analysis Techniques for Dependability 310
9.6.1 Failure Modes and Effect Analysis 311
9.6.2 Fault Tree Analysis 312
9.7 Conclusions 313
Further Reading 314
References 314
Exercises 315
10 EMC MEASUREMENTS 317
Carlo Carobbi
10.1 Introduction 317
10.2 Definitions and Terminology 318
10.3 The Measuring Receiver 321
10.3.1 Quasi-Peak Measuring Receivers 321
10.3.2 Peak Measuring Receivers 329
10.4 Conducted Emission Measurements 329
10.4.1 The Artificial Mains Network 329
10.4.2 The Current Probe 332
10.5 Radiated Emission Measurements 333
10.5.1 Antennas for the 9 kHz to 30 MHz Frequency Range 334
10.5.2 Antennas for the Frequency Range Above 30 MHz 335
10.5.3 Measurement Sites 339
10.6 Immunity Tests 343
10.6.1 Conducted Immunity Tests 343
10.6.2 Radiated Immunity Tests 346
10.7 Conclusions 347
Further Reading 348
References 348
Exercises 351
PROBLEM SOLUTIONS 353
INDEX 371
CHAPTER 1
MEASUREMENT MODELS AND UNCERTAINTY
ALESSANDRO FERRERO1 and DARIO PETRI2
1Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, Milano, Italy
2Dipartimento di Ingegneria Industriale, Università degli Studi di Trento, Povo, Italy
1.1 INTRODUCTION
Nowadays, we are surrounded by measuring instruments and we use them several times a day, very often unconsciously and unaware of their complexity and accuracy. To realize how instruments have become a big part of our life, just think of how many times we read the speed indicator when we drive our car, the fuel indicator to know when we have to refill the tank, or, when we eventually refill it, the meter on the fuel pump.
Interestingly enough, we usually don't pay too much attention to the accuracy of the instruments we use, even if we rely on their indication to make important decisions, such as, for instance, driving safely or paying the right amount of money for the quantity of good we purchase. Even more strangely, the only instrument we generally adjust to a reference is our watch, which is probably the most accurate instrument we use in our everyday life: even the cheapest ones don't lag or lead for more than one second a day, which means that their relative accuracy is in the range of 1 · 10- 5!
The above examples give us clear evidence that we do use and read instruments, but they still leave an important question open: are we also making a measurement? Trying to answer this question opens also another fundamental question: which is the difference between reading an instrument and making a measurement?
This chapter is aimed at providing an answer to this question.
1.2 MEASUREMENT AND METROLOGY
To understand what measuring means, let's start from the definition of measurement, taken from the International Vocabulary of Metrology (VIM) [1].
Measurement
Process of experimentally obtaining one or more quantity values that can reasonably be attributed to a quantity.
So, a measurement process provides, as a part of the measurement result, one or more quantity values that can be attributed to a quantity intended to be measured, that is also called, always according to the VIM [1], measurand.
To fully understand this definition, we have to refer to the definition of quantity. We can find it again in the VIM.
Quantity
Property of a phenomenon, body, or substance, where the property has a magnitude that can be expressed as a number and a reference.
The VIM states that a reference can be a measurement unit, a measurement procedure, a reference material, or a combination of such.
When physical properties are considered, the reference is generally a measurement unit, whilst, when chemical measurement are considered, the reference is quite often a reference material.
The quantity values provided by the measurement are therefore a number and a reference together expressing the magnitude of a quantity [1].
Is this the measurement result? Or, better, can a measurement result be expressed only by a number and a reference? As we will see later in section 1.5 of this chapter, a measurement procedure cannot provide the "true" value of a measurand, due to a number of factors that we will thoroughly discuss later. This means that a measurement result can only provide a finite amount of information about the measurand, and we must know if that amount is enough for the intended use of the measurement result. Otherwise, the measurement result would be meaningless.
Therefore, any measurement result has to be provided with an attribute capable of quantifying how close to the measurand's value the obtained quantity value is. This attribute is called uncertainty, and the correct definition of measurement result, as provided by the VIM, is as follows.
Measurement result
Set of quantity values being attributed to a measurand together with any other available relevant information.
In a note to this general definition, the VIM states that:
A measurement result is generally expressed as a single measured quantity value and a measurement uncertainty.
The above general definitions have introduced a number of concepts (quantity value, reference, relevant information, uncertainty), that will be covered in the next Sections, and show that a measurement is a definitely more complex procedure than simply reading an instrument.
The science that includes all theoretical and practical aspects of measurement, regardless to the measurement uncertainty and field of application, is called metrology [1]. Its definition, as provided by the VIM, is as follows.
Metrology
Science of measurement and its application
As many other sciences that have a deep impact on human life, metrology finds its roots back into the ancient times, and the evolution of the human needs had a significant impact on its development, and its present formulation. Therefore, before analyzing the fundamental concepts of nowadays metrology, let us find an answer to two basic questions: why do we measure? And for what do we use our measurement results?
A quick glance into the past will help us to find the answers to these questions.
1.3 MEASUREMENT ALONG THE CENTURIES
At the beginning of the human adventure, the measurement concept did not exist and the experimental activity was confined to direct observations. Instruments did not exist, and our senses were the only available tools to observe and somehow quantify the reality.
The first physical quantity that was barely measurable with our senses and probably started metrology was time. We can only imagine that this interest was related to the impact that the night and day cycle, the lunar period and the rotation of seasons have on human life and the human ability of predict them to optimize all activities aimed at providing food, from hunting to agriculture and cattle breeding.
As a matter of fact, the archeological findings from prehistory show with little doubt that the first conceived measuring instruments were aimed at the measurement of time, through the observation of the stars or the sun. Although the most famous among these instruments is the Stonhenge Circle, its "operating principle" is not yet clear. On the other hand, many remains have been found from a later period, across prehistory and history, that proved how time was measured through the observation of the displacement of the shadow of a vertical device (the gnomon) created by the sun on the ground [2].
However, at that time, this activity was more of a religious and prophetic kind, rather than aimed at increasing knowledge. We had to wait until the organized social structures appeared to meet awareness of knowledge and a systematic discussion about its meaning.
1.3.1 Measurement in Ancient Greece
There is no doubt that ancient Greece was the cradle of philosophy, and philosophy was considered the most important means of knowledge. We have also evidence, from documents and archeological findings, that instruments were used, mainly for length and capacity measurements. However, the great philosophers of that time did not consider instruments as tools to advance knowledge.
The motivation can be found in the dichotomy between the world of philosophical abstractions and the empirical world of observations, clearly expressed by Socrates in the fifth century BC.
In Socrates' philosophy, we can build our knowledge by defining abstract models that allow us to explain, through suitable logical steps, what happens to us. In this way, we can build our own world of philosophical abstractions.
On the other hand, there is a physical world around us, that shows up through a number of occurrences, facts and events, and that, at Socrates' time, we could perceive only through our senses. This is the so-called empirical world and, according to Socrates, the abstractions were aimed at explaining the true essence of the empirical world. In his philosophy, abstract logical constructions were the only way to knowledge, and observations had the simple role of triggering speculation. The use of observation results as a way to validate abstract models was not part of Socrates' approach, and was not part of the scientific method at least until Galileo's time. The subordinate role assigned to observations with respect to logics has lasted for so many centuries that even now the word "empiricism" implies a negative connotation.
1.3.2 Measurement in the Roman Empire
We have to wait until the Roman Empire to discover, from the many available historical documents and texts, that they had a rather modern approach to measurement. Indeed, we know that they had standards (at least for length, mass, and capacity), these standards were approved, kept and maintained by the central government, and secondary standards were disseminated in the provinces of the empire.
Evidence of the importance assigned by Romans to measurement is given by the fact that the primary standards were kept in the temple of Iuno Moneta.1 Only valuable and important objects were kept in the house of a God. And only money-related objects were kept by the God of Money!
According to these facts, we expect to find several traces, in the Latin...
System requirements
File format: ePUB
Copy protection: Adobe-DRM (Digital Rights Management)
System requirements:
- Computer (Windows; MacOS X; Linux): Install the free reader Adobe Digital Editions prior to download (see eBook Help).
- Tablet/smartphone (Android; iOS): Install the free app Adobe Digital Editions or the app PocketBook before downloading (see eBook Help).
- E-reader: Bookeen, Kobo, Pocketbook, Sony, Tolino and many more (not Kindle).
The file format ePub works well for novels and non-fiction books – i.e., „flowing” text without complex layout. On an e-reader or smartphone, line and page breaks automatically adjust to fit the small displays.
This eBook uses Adobe-DRM, a „hard” copy protection. If the necessary requirements are not met, unfortunately you will not be able to open the eBook. You will therefore need to prepare your reading hardware before downloading.
Please note: We strongly recommend that you authorise using your personal Adobe ID after installation of any reading software.
For more information, see our ebook Help page.