Fault Diagnosis of Permanent Magnets Machines

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Author(s):	Faiz Faiz, Jawad
ISBN No.:	9781394424979
Pages:	448
Year:	202701
Format:	Trade Cloth (Hard Cover)
Price:	$ 205.67
Dispatch delay:	Dispatched between 7 to 15 days
Status:	Available (Forthcoming)

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Preface vii Acknowledgments ix Acronyms xi 1 Introduction 1 1.1 Motivation and Problem Statement 1 1.2 Importance of Fault Diagnosis in PM Motors 2 1.3 Industrial Applications and Economic Impact 4 1.4 Current State of PM Motor Technology 7 1.5 Overview of Fault Types in PM Motors 10 1.6 Challenges in Fault Detection and Diagnosis 15 1.7 Book Organization and Chapter Overview 18 2 Permanent Magnet Machines 25 2.

1 Historical Development of PM Machines 25 2.2 Applications and Advantages of PM Machines 28 2.2.1 Automotive Sector 28 2.2.2 Industrial Sector 29 2.2.3 Renewable Energy Sector 29 2.

2.4 Home Appliances and Consumer Electronics Sector 29 2.2.5 Medical Sector 29 2.2.6 Transportation Sector 30 2.2.7 Other Applications 30 2.

3 PM Machine Construction and Key Components 30 2.3.1 Basic Machine Structure 30 2.3.2 Stator Construction 31 2.3.3 Rotor Construction 33 2.3.

4 Air Gap 33 2.4 Permanent Magnet Materials and Properties 33 2.4.1 Residual Magnetic Flux Density Br and Coercive Force Hc 34 2.4.2 Received Energy and its Maximum Value 35 2.4.3 Curie Temperature 35 2.

4.4 Classification of PM Materials 35 2.5 Losses in PM Machines 36 2.6 Comparison of PMSM and Induction Machines 37 2.7 Classification of PM Machines and Machine Topologies 38 2.7.1 Classification of Electrical Machines 38 2.7.

2 Classification Based on Structure and Application 41 2.7.3 Rotor Structures and Magnet Placement Topologies 43 2.7.4 Radial Flux PM Machines 46 2.7.5 Axial-Flux PM Machines 47 2.7.

6 Special Topologies of PM Machines 50 2.8 Summary 52 3 Modelling and Simulation Techniques for Permanent Magnet Motors 59 3.1 Introduction 59 3.2 Lumped Parameter Models 62 3.2.1 Introduction 62 3.2.2 dq-axis Models 63 3.

2.3 abc Reference Frame Models with Voltage Behind Reactance 68 3.2.4 Model Selection Guidelines 73 3.3 Finite Element Method 75 3.3.1 Introduction 75 3.3.

2 Application to Fault Modeling 77 3.3.3 Advantages and Limitations 80 3.3.4 Role in Fault Diagnosis Workflow 83 3.4 Field Reconstruction Method 84 3.4.1 Introduction 84 3.

4.2 Mathematical Foundation 86 3.4.3 Implementation Methodology 88 3.4.4 Application to Fault Modeling 94 3.4.5 Advantages and Limitations 98 3.

4.6 Role in Fault Diagnosis Workflow 99 3.5 Winding Function Models 101 3.5.1 Introduction 101 3.5.2 Mathematical Foundation 101 3.5.

3 Advantages and Limitations 107 3.5.4 Application to Fault Modeling 108 3.5.5 Role in Fault Diagnosis Workflow 111 3.6 Magnetic Equivalent Circuit 113 3.6.1 Introduction 113 3.

6.2 Mathematical Foundation 116 3.6.3 Advantages and Limitations 124 3.6.4 Application to Fault Modeling 127 3.6.5 Role in Fault Diagnosis Workflow 127 3.

7 Machine Learning-Based Modeling 128 3.7.1 Introduction 128 3.7.2 Key Modeling Approaches 129 3.7.3 Neural Network Architectures for Sequential Motor Behavior 132 3.7.

4 Deep Operator Networks for Multi-Physics Modeling 137 3.7.5 Training Methodologies 138 3.7.6 Training Considerations 139 3.7.7 Digital Twin Concept 139 3.7.

8 Advantages and Limitations 140 3.7.9 Role in Fault Diagnosis Workflow 140 3.8 Simulation Validation and Verification 141 3.8.1 Purpose of Validation and Verification 142 3.8.2 Verification of Models 142 3.

8.3 Validation Against Experiments 143 3.8.4 Validation for Fault Diagnosis 145 3.8.5 Verification and Validation Plan 146 3.8.6 Documentation and Uncertainty Quantification 147 3.

9 Summary 147 4 Fault Diagnosis Techniques 157 4.1 PART A: INTRODUCTION & FOUNDATIONS 157 4.1.1 Introduction 157 4.1.2 Preprocessing Pipeline 158 4.1.3 Signal Processing Foundations 159 4.

1.4 Decision Logic Frameworks 163 4.1.5 Confounding Factors 164 4.1.6 Baseline Formation & Calibration 166 4.1.7 Validation Methodology 166 4.

1.8 Real-Time Implementation Considerations 168 4.2 PART B: DIAGNOSTIC TECHNIQUES 169 4.2.1 Motor Current Signature Analysis 169 4.2.2 Motor Flux Signature Analysis 172 4.2.

3 Zero Sequence Voltage Component Analysis 178 4.2.4 Extended Park Vector Approach 183 4.2.5 Model-based Parameter Estimation Methods 184 4.2.6 Instantaneous Power/Power-Factor Signature Analysis 192 4.2.

7 Acoustic and Vibration Signature Analysis 194 4.2.8 Data-driven & Hybrid Analytics 196 4.3 PART C: COMPARATIVE ANALYSIS 202 4.3.1 Comparative Summary of Techniques 202 4.3.2 Selection Guidelines 213 4.

3.3 Key Selection Principles 213 5 Eccentricity Faults 225 5.1 Introduction 225 5.2 Failure Modes and Mechanisms 226 5.2.1 Introduction to Air Gap Eccentricity 226 5.2.2 Static Eccentricity Faults 227 5.

2.3 Dynamic Eccentricity Faults 229 5.2.4 Mixed Eccentricity Faults 232 5.2.5 Axial Flux PM Machine Eccentricity 233 5.2.6 Other Air Gap Asymmetries 233 5.

2.7 Unbalanced Magnetic Pull 235 5.3 Modeling and Analysis 238 5.3.1 Analytical Modeling of Eccentricity Fault 238 5.3.2 FEM Simulation of Eccentric PM Motors 246 5.3.

3 Unbalanced Magnetic Forces Modeling 255 5.4 Fault Diagnosis 258 5.4.1 MCSA Application for Eccentricity Diagnosis 258 5.4.2 Vibration Analysis for Eccentricity Faults 263 5.4.3 Flux-Based Detection Methods 266 5.

4.4 EPVA Application for Eccentricity Diagnosis 268 5.4.5 Data-Driven and Machine Learning Classification Approaches 270 5.4.6 Experimental Validation Summary 271 5.5 Summary 272 6 Short-Circuit and Inter-Turn Faults 279 6.1 Introduction 279 6.

2 Failure Modes and Mechanisms 281 6.2.1 Inter-Turn Short Circuit Characteristics 281 6.2.2 Insulation System Materials and Properties 282 6.2.3 Insulation Temperature Classes 283 6.2.

4 Thermal Stress and the 10-Degree Rule 284 6.2.5 Electrical Stress from Inverter Operation 286 6.2.6 Fault Progression Mechanisms 288 6.2.7 Turn-to-Turn versus Turn-to-Ground Characteristics 289 6.2.

8 Phase-to-Phase Short Circuit Mechanisms 291 6.2.9 Mechanical Stress Factors in Winding Insulation Degradation 292 6.2.10 Phase-to-Phase Short-Circuit Fault Mechanisms 293 6.2.11 Turn-to-Ground Fault Analysis 301 6.3 Modeling and Analysis 309 6.

3.1 Reference Machine for Fault Analysis 309 6.3.2 Air Gap Modeling and Rotor-Stator Coupling 310 6.3.3 Mathematical Representation of Short-Circuit Faults 315 6.3.4 Model Validation and Parameter Studies 318 6.

4 Fault Diagnosis 324 6.4.1 Reference Frame Based Diagnostic Approaches 324 6.4.2 Experimental Validation of DQO Frame Methods 327 6.4.3 Experimental Validation and Phase Identification 334 6.4.

4 Model-Based Parameter Estimation for Inter-Turn and Short-Circuit Fault Diagnosis 345 6.5 Summary 348 7 Bearing Faults 355 7.1 Introduction 355 7.2 FAILURE MODES AND MECHANISMS 355 7.2.1 Bearing Construction and Components 355 7.2.2 Bearing Race Defects and Failure Mechanisms 356 7.

2.3 Ball/Rolling Element Defects 358 7.2.4 Cage Defects and Failure Modes 360 7.2.5 Lubrication-Related Failures 360 7.2.6 Contamination and Excessive Loading Effects 360 7.

2.7 Statistical Analysis of Bearing Failure Rates 362 7.3 MODELING AND ANALYSIS 365 7.3.1 Bearing Dynamics and Kinematic Modeling 365 7.3.2 Defect-Induced Force Modeling 374 7.3.

3 Vibration Transmission Path Analysis 378 7.3.4 Bearing-Motor Coupling Effects 378 7.3.5 FEM Analysis of Bearing-Induced Eccentricity 386 7.4 FAULT DIAGNOSIS 387 7.4.1 Vibration Monitoring Techniques for Bearing Faults 387 7.

4.2 MCSA Application for Bearing Defect Detection 392 7.4.3 Envelope Analysis and Demodulation Methods 395 7.4.4 Data-Driven and Machine Learning Approaches 399 7.4.5 Wavelet Transform and Time-Frequency Methods 401 7.

4.6 Multi-Signal Fusion for Bearing Diagnosis 403 7.4.7 Remaining Useful Life Estimation 404 7.4.8 Emerging Sensor Technologies and Non-Invasive Methods 405 7.4.9 Experimental Validation and Case Studies 407 7.

5 Summary 413 8 Demagnetization Faults 419 8.1 Introduction 419 8.2 FAILURE MODES AND MECHANISMS 420 8.2.1 Field-Induced Demagnetization 422 8.2.2 Thermal Stress-Induced Demagnetization 423 8.2.

3 Manufacturing Defect-Related Demagnetization 427 8.2.4 Partial vs. Complete Demagnetization Patterns 428 8.2.5 Progressive Demagnetization Mechanisms 432 8.2.6 Magnetic Flux Reduction and Electromagnetic Impact 434 8.

3 MODELING AND ANALYSIS 436 8.3.1 Finite Element Method for Demagnetization Analysis 436 8.3.2 Analytical Models for Demagnetization 437 8.3.3 Lumped-Parameter Model for Demagnetization 439 8.3.

4 FEM Simulation Case Studies 443 8.4 FAULT DIAGNOSIS 445 8.4.1 Back-EMF Analysis for Demagnetization Detection 445 8.4.2 MCSA Application for Demagnetization Signatures 453 8.4.3 Flux Monitoring Techniques 460 8.

4.4 Signal Injection Methods for Demagnetization Assessment 464 8.4.5 Model-Based Parameter Estimation for Flux Linkage 468 8.4.6 Multi-Signal Fusion for Demagnetization Diagnosis 472 8.4.7 Acoustic and Vibration Signatures 478 8.

4.8 Experimental Validation and Cas.

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