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001 on1268121569
003 OCoLC
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006 m o d
007 cr |||||||||||
008 210830s2022 nju ob 001 0 eng
010 _a 2021041539
040 _aDLC
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066 _cZsym
020 _a9781119722823
_q(ebook)
020 _a1119722829
_q(ebook)
020 _a9781119722809
_q(pdf)
020 _a1119722802
_q(pdf)
020 _a9781119722786
_q(epub)
020 _a1119722780
_q(epub)
020 _z9781119722755
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024 7 _a10.1002/9781119722823
_2doi
029 1 _aAU@
_b000069860142
035 _a(OCoLC)1268121569
037 _a9635032
_bIEEE
042 _apcc
050 0 0 _aTK4058
082 0 0 _a621.46
_223
049 _aMAIN
100 1 _aStrangas, Elias,
_eauthor.
_910424
245 1 0 _aFault diagnosis, prognosis, and reliability for electrical drives :
_bfault diagnosis, failure prognosis and their effects on the reliability of electrical machines, drives and power electronics /
_cElias Strangas, Guy Clerc, Hubert Razik, Abdenour Soualhi.
263 _a2112
264 1 _aHoboken, NJ :
_bJohn Wiley & Sons,
_c2022.
300 _a1 online resource
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
504 _aIncludes bibliographical references and index.
520 _a"The progress in electrification of manufacturing processes, transportation, commercial and residential applications is accelerating exponentially. This movement is supported by an increasing acceptance and use of electrical drives, which have progressed in terms of cost, size, efficiency and performance. This progress enabled the use of drives in current and new applications that benefit from these characteristics. This resulted in lower environmental pollution, and applications requiring higher exibility, such as electric and hybrid vehicles, more electric airplanes and electric ships, new energy sources, industrial controls, consumer electronics, health devices, etc. Electrical drives that are of interest in this book are of widely varying sizes, from large wind generators and ship propulsion systems, down to miniature ones used in medical devices. The drives invariably use an electrical machine, power electronics, controllers, sensors, and occasionally batteries to operate."--
_cProvided by publisher.
588 _aDescription based on print version record and CIP data provided by publisher; resource not viewed.
590 _bWiley Frontlist Obook All English 2021
650 0 _aElectric driving.
_910425
650 7 _aElectric driving.
_2fast
_0(OCoLC)fst00904701
_910425
655 4 _aElectronic books.
_93294
700 1 _aClerc, Guy,
_eauthor.
_910426
700 1 _aRazik, Hubert,
_eauthor.
_910427
700 1 _aSoualhi, Abdenour,
_eauthor.
_910428
776 0 8 _iPrint version:
_aStrangas, Elias.
_tFault diagnosis, prognosis, and reliability for electrical drives
_dHoboken, NJ : John Wiley & Sons, 2022
_z9781119722755
_w(DLC) 2021041538
856 4 0 _uhttps://doi.org/10.1002/9781119722823
_zWiley Online Library
880 0 _6505-00/Zsym
_aContributors xiii -- Acknowledgments xv -- Acronyms xvii -- Introduction xxi -- 1 Basic Methods and Tools 1 -- 1.1 General Approach 1 -- 1.2 Feature Extraction: Signal and Preconditioning 2 -- 1.2.1 Raw Signals: What Kind of Signals and Sensors? 2 -- 1.2.1.1 Current Sensors 3 -- 1.2.1.2 Vibration Measurement and Accelerometers 13 -- 1.2.1.3 Temperature Sensors 14 -- 1.2.1.4 Field Sensors 16 -- 1.2.1.5 Acoustic Sensors 16 -- 1.2.1.6 Other Sensors 18 -- 1.2.2 Preconditioning 22 -- 1.2.2.1 Signal Features in the Time Domain 22 -- 1.2.2.2 Symmetric Component, Park Component 22 -- 1.2.2.3 Symmetric Component, Park Component 24 -- 1.2.2.4 Signal Features in the Frequency Domain 26 -- 1.2.2.5 Wavelet Analysis 34 -- 1.2.2.6 Instantaneous Amplitude and Frequency 35 -- 1.2.2.7 Bilinear Time-frequency Distributions or Quadratic -- Time-frequency Distributions: Cohen's Class 36 -- 1.2.2.7.a Uncertainty Principle of Heisenberg 37 -- 1.2.2.7.b General Representation 37 -- 1.2.2.7.c Properties 38 -- 1.2.2.7.d Different Representations 39 -- 1.2.2.8 Statistic Features 45 -- 1.2.2.9 Cyclostationarity 46 -- 1.2.3 Model Approach 48 -- 1.2.3.1 Kalman Observer 51 -- 1.2.3.2 Extended Observer 52 -- 1.2.3.3 Unscented Kalman Filter 55 -- 1.2.4 Parity Space 56 -- 1.3 Feature Reduction, Principal Component Analysis 60 -- 1.3.1 Principal Component Analysis: A Space Reduction and an Unsupervised Classification 60 -- 1.3.2 Intercorrelation 62 -- 1.3.2.1 Pearson Coefficient "r" 62 -- 1.3.2.2 Spearman Coefficient "̧œŒ" 63 -- 1.3.3 Information Content: Shannon Entropy 65 -- 1.3.4 Pattern Sizing Reduction for a Supervised Classification 65 -- 1.3.4.1 Selection Criteria 65 -- 1.3.4.2 Sequential Backward Feature Selection and Sequential Forward Feature Selection 67 -- 1.3.5 Pattern Sizing Reduction for an Unsupervised Classification: Laplacian Score 68 -- 1.3.6 Choice of the Number of Classes for an Unsupervised Classification 69 -- 1.3.6.1 Choice of the Number of Classes with a PCA 69 -- 1.3.6.2 General Case 70 -- 1.3.7 Other Quality Criteria of a Classification 71 -- 1.3.7.1 ̧'... 2 index 71 -- 1.3.7.2 Calinski-Harabasz Index 72 -- 1.3.7.3 Davies-Bouldin Index 73 -- 1.3.7.4 Silhouette Index 73 -- 1.3.7.5 Dunn Index 74 -- 1.4 Classification Methods 74 -- 1.4.1 Generalities 74 -- 1.4.1.1 Supervised and Unsupervised Clustering 75 -- 1.4.1.2 Measuring the Similarity: Different Distances 76 -- 1.4.2 Supervised Clustering 77 -- 1.4.2.1 k Nearest Neighbors 78 -- 1.4.2.2 Support Vector Machine 80 -- 1.4.2.3 Recurrent Neural Network 82 -- 1.4.3 Unsupervised Clustering 85 -- 1.4.3.1 Hierarchical Classification 86 -- 1.4.3.2 K-means and Centroid Clustering 89 -- 1.4.3.3 Self-organizing Map 90 -- 1.5 Prognosis Methods 93 -- 1.5.1 Prognosis Process 93 -- 1.5.2 Time Series Extrapolation Methods 95 -- 1.5.3 Bayesian Inference 101 -- 1.5.4 Markov Chain 103 -- 1.5.5 Hidden Markov Models 105 -- 1.5.6 Rainflow 110 -- 1.5.6.1 Hidden Semi-Markov Models 114 -- References 114 -- 2 Applications and Specifics 125 -- 2.1 General Presentation of Motor Drives 125 -- 2.2 Electrical Machines 126 -- 2.2.1 Basics 128 -- 2.2.2 Magnetic Steel and Magnets 129 -- 2.2.3 Windings and Insulation 133 -- 2.3 Machine Models, Operation, and Control 137 -- 2.3.1 Three-phase Windings 137 -- 2.3.2 Induction Machines 138 -- 2.3.2.1 Induction Machine Rotor Field Orientation 140 -- 2.3.2.2 Direct Torque Control 141 -- 2.3.3 Permanent Magnet AC Machines 144 -- 2.4 Faults in Electrical Machines 146 -- 2.4.1 Operational Variables and Measurements 147 -- 2.4.2 Supervision, Detection, and Fault Classification 149 -- 2.4.3 Bearings 153 -- 2.4.4 Insulation 169 -- 2.5 Open and Short Faults, Eccentricity, Broken Magnets and Rotor Bars 180 -- 2.5.1 Induction Machines 182 -- 2.5.1.1 Stator Fault Diagnosis 183 -- 2.5.1.2 Eccentricity 191 -- 2.5.1.3 Multi-fault Diagnosis with Stray Flux and Flux Sensor 193 -- 2.5.1.4 Open Faults in Windings and Inverter 195 -- 2.5.1.5 Broken Rotor Bars 196 -- 2.5.2 Permanent Magnet AC Machines 198 -- 2.5.2.1 Demagnetization of Permanent Magnets 198 -- 2.5.2.2 Open and Short Circuit 201 -- 2.5.3 Sensor Faults 208 -- 2.5.4 Fault Mitigation and Management 209 -- 2.6 Power Electronics and Systems 215 -- 2.6.1 A Brief Description of Power Electronics in AC drives 216 -- 2.6.2 A Brief Description of Static Switches 223 -- 2.6.2.1 MOSFET 223 -- 2.6.2.2 IGBT 230 -- 2.6.2.3 Si and SiC Technology 236 -- 2.6.2.4 Thermal Behavior 236 -- 2.6.3 A Brief Description of Capacitors 241 -- 2.6.3.1 General Description 241 -- 2.6.3.2 Different Kinds of Capacitors 245 -- 2.6.3.2.a Non-polarized Capacitors 245 -- 2.6.3.2.b Polarized Capacitors 251 -- 2.6.4 Device Faults and Their Manifestation 255 -- 2.6.4.1 Basic Notion 257 -- 2.6.4.2 On Chip Failures 258 -- 2.6.4.3 Packaging and Chip Environment Failures 259 -- 2.6.5 Capacitor Failure Modes 261 -- 2.6.5.1 Failure by Degradation 261 -- 2.6.5.2 Catastrophic Failure 262 -- 2.6.6 Diagnosis and Prognosis Techniques for Power Devices 262 -- 2.6.6.1 Introduction 262 -- 2.6.6.2 Failure Modes Indicators and TSEP for Power Electronic Devices 262 -- 2.6.6.3 Diagnosis of Failure Modes 269 -- 2.6.6.3.a Diagnosis based on the Direct Analysis of the Current 271 -- 2.6.6.3.b Diagnosis based on the Direct or Indirect Analysis of Junction Temperature 279 -- 2.6.6.3.c Diagnosis based on Signal Processing 284 -- 2.6.6.3.d Diagnosis based on Clustering 288 -- 2.6.6.3.e Diagnosis based on Neural Network 291 -- 2.6.6.3.f Synthesis 295 -- 2.6.6.4 Prognosis of Failure Modes 295 -- 2.6.6.4.a Prognosis based on Failure Mechanism and Statistical Data 295 -- 2.6.6.4.b Prognosis based on Failure Precursors 300 -- 2.6.7 Diagnosis and Prognosis Techniques for Capacitors 310 -- 2.6.7.1 Fault Diagnosis Techniques 310 -- 2.6.7.2 Methods for Predicting Electrolytic Capacitor Failures 318 -- Bibliography 324 -- 3 Fault Diagnosis and Prognosis for Reliability Enhancement 345 -- 3.1 Introduction 345 -- 3.2 Fundamentals 346 -- 3.2.1 The Pattern of Failures with Time for Non-Repairable Items 350 -- 3.2.2 Distribution Functions 350 -- 3.2.3 Confidence in Reliability and Prognosis 353 -- 3.3 Component Reliability 354 -- 3.4 Reliability of Subsystems and Systems 361 -- 3.4.1 Analysis Tools 361 -- 3.5 Lifetime, Reliability Prediction 365 -- 3.6 Fault Management and Mitigation 368 -- 3.7 Design and Manufacturing 371 -- 3.8 Applications and Case Studies 372 -- 3.9 Scheduled Maintenance, Condition-Based Maintenance 397 -- 3.9.1 Reliability and Costs 407 -- 3.10 Conclusions 409 -- Bibliography 410 -- Index 415.
942 _cEBK
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