Electric Machines

Electric Machines

by Hamid A. Toliyat, Subhasis Nandi, Seungdeog Choi, Homayoun Meshgin-Kelk
Released December 2017
Publisher(s): CRC Press
ISBN: 9781351837873

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Book description

In response to the multidisciplinary nature of fault diagnosis and condition monitoring, this text describes different types of faults in electric machines and the techniques employed in their detection. Representing an advance in the condition monitoring and diagnostics literature, this book concentrates on state-of-the-art noninvasive methods that can be utilized on running machines without interfering with their processes. The authors also explain how the availability of inexpensive yet powerful processing powers using digital signal processors makes it possible to seamlessly integrate the task of condition monitoring and fault diagnosis with machine control algorithms.

Table of contents

  1. Cover Page
  2. Title Page
  3. Copyright Page
  4. Contents
  5. Preface
  6. 1 Introduction
    1. References
  7. 2 Faults in Induction and Synchronous Motors
    1. 2.1 Introduction of Induction Motor Fault
      1. 2.1.1 Bearing Faults
      2. 2.1.2 Stator Faults
      3. 2.1.3 Broken Rotor Bar Fault
      4. 2.1.4 Eccentricity Fault
    2. 2.2 Introduction of Synchronous Motor Fault Diagnosis
      1. 2.2.1 Damper Winding Fault
      2. 2.2.2 Demagnetization Fault in Permanent Magnet Synchronous Machines (PMSMs)
      3. 2.2.3 Eccentricity Fault
      4. 2.2.4 Stator inter-Turn Fault
      5. 2.2.5 rotor inter-Turn Fault
      6. 2.2.6 Bearing Fault
    3. References
  8. 3 Modeling of Electric Machines Using Winding and Modified Winding Function Approaches
    1. 3.1 Introduction
    2. 3.2 Winding and Modified Winding Function Approaches (WFA and MWFA)
    3. 3.3 Inductance Calculations Using WFA and MWFA
    4. 3.4 Validation of Inductance Calculations
    5. References
  9. 4 Modeling of Electric Machines Using Magnetic Equivalent Circuit Method
    1. 4.1 Introduction
    2. 4.2 Indirect Application of Magnetic Equivalent Circuit for Analysis of Salient Pole Synchronous Machines
      1. 4.2.1 Magnetic Equivalent Circuit of a Salient Pole Synchronous Machine
      2. 4.2.2 inductance relations of a Salient Pole Synchronous Machine
      3. 4.2.3 Calculation of Inductances for a Salient Pole Synchronous Machine
      4. 4.2.4 Experimental Measurement of inductances of a Salient Pole Synchronous Machine
    3. 4.3 Indirect Application of Magnetic Equivalent Circuit for Analysis of Induction Machines
      1. 4.3.1 A Simplified Magnetic Equivalent Circuit of induction Machines
      2. 4.3.2 inductance Relations of induction Machines
      3. 4.3.3 Calculation of Inductance of an Induction Machine
    4. 4.4 Direct Application of Magnetic Equivalent Circuit Considering Nonlinear Magnetic Characteristic for Machine Analysis
    5. Appendix A: Induction Machine Parameters
    6. Appendix B: Node Permeance Matrices
    7. References
  10. 5 Analysis of Faulty Induction Motors Using Finite Element Method
    1. 5.1 Introduction
    2. 5.2 Geometrical Modeling of Faulty Induction Motors Using Time-Stepping Finite Element Method (TSFEM)
    3. 5.3 Coupling of Electrical Circuits and Finite Element Area
    4. 5.4 Modeling Internal Faults Using Finite Element Method
      1. 5.4.1 Modeling Broken Bar Fault
      2. 5.4.2 Modeling eccentricity Fault
        1. 5.4.2.1 Static Eccentricity
        2. 5.4.2.2 Dynamic Eccentricity
        3. 5.4.2.3 Mixed Eccentricity
    5. 5.5 Impact of Magnetic Saturation on Accurate Fault Detection in Induction Motors
      1. 5.5.1 Analysis of Air-Gap Magnetic Flux Density in Healthy and Faulty Induction Motor
        1. 5.5.1.1 Linear Magnetization Characteristic
        2. 5.5.1.2 Nonlinear Magnetization Characteristic
    6. References
  11. 6 Fault Diagnosis of Electric Machines Using Techniques Based on Frequency Domain
    1. 6.1 Introduction
    2. 6.2 Some Definitions and Examples Related to Signal Processing
      1. 6.2.1 Continuous versus Discrete or Digital or Sampled Signal
      2. 6.2.2 Continuous, Discrete Fourier Transforms, and Nonparametric Power Spectrum Estimation
      3. 6.2.3 Parametric Power Spectrum estimation
      4. 6.2.4 Power Spectrum estimation Using Higher-Order Spectra (HOS)
      5. 6.2.5 Power Spectrum Estimation Using Swept Sine Measurements or Digital Frequency Locked Loop Technique (DFLL)
    3. 6.3 Diagnosis of Machine Faults Using Frequency-Domain-Based Techniques
      1. 6.3.1 Detection of Motor Bearing Faults
        1. 6.3.1.1 Mechanical Vibration Frequency Analysis to Detect Bearing Faults
        2. 6.3.1.2 Line Current Frequency Analysis to Detect Bearing Faults
      2. 6.3.2 Detection of Stator Faults
        1. 6.3.2.1 Detection of Stator Faults Using External Flux Sensors
        2. 6.3.2.2 Detection of Stator Faults Using Line Current Harmonics
        3. 6.3.2.3 Detection of Stator Faults Using Terminal Voltage Harmonics at Switch-Off
        4. 6.3.2.4 Detection of Stator Faults Using Field Current and Rotor Search Coil Harmonics in Synchronous Machines
        5. 6.3.2.5 Detection of Stator Faults Using Rotor Current and Search Coil Voltages Harmonics in Wound Rotor Induction Machines
      3. 6.3.3 Detection of Rotor Faults
        1. 6.3.3.1 Detection of Rotor Faults in Stator Line Current, Speed, Torque, and Power
        2. 6.3.3.2 Detection of Rotor Faults in External and Internal Search Coil
        3. 6.3.3.3 Detection of Rotor Faults Using Terminal Voltage Harmonics at Switch-Off
        4. 6.3.3.4 Detection of Rotor Faults at Start-Up
        5. 6.3.3.5 Detection of Rotor Faults in Presence of Interbar Current Using Axial Vibration Signals
      4. 6.3.4 Detection of Eccentricity Faults
        1. 6.3.4.1 Detection of Eccentricity Faults Using Line Current Signal Spectra
        2. 6.3.4.2 Detection of Eccentricity Faults Based on Nameplate Parameters
        3. 6.3.4.3 Detection of Eccentricity Faults Using Mechanical Vibration Signal Spectra
        4. 6.3.4.4 Detection of Inclined Eccentricity Faults
      5. 6.3.5 Detection of Faults in Inverter-Fed Induction Machines
    4. References
  12. 7 Fault Diagnosis of Electric Machines Using Model-Based Techniques
    1. 7.1 Introduction
    2. 7.2 Model of Healthy Three-Phase Squirrel-Cage Induction Motor
    3. 7.3 Model of Three-Phase Squirrel-Cage Induction Motor with Stator Inter-Turn Faults
      1. 7.3.1 Model without Saturation
      2. 7.3.2 Model with Saturation
    4. 7.4 Model of Squirrel-Cage Induction Motor with Incipient Broken Rotor Bar and End-Ring Faults
    5. 7.5 Model of Squirrel-Cage Induction Motor with Eccentricity Faults
    6. 7.6 Model of a Synchronous Reluctance Motor with Stator Fault
    7. 7.7 Model of a Salient Pole Synchronous Motor with Dynamic Eccentricity Faults
    8. References
  13. 8 Application of Pattern Recognition to Fault Diagnosis
    1. 8.1 Introduction
    2. 8.2 Bayesian Theory and Classifier Design
    3. 8.3 Simplified Form for a Normal Distribution
    4. 8.4 Feature Extraction for Our Fault Diagnosis System
    5. 8.5 Classifier Training
    6. 8.6 Implementation
    7. References
  14. 9 Implementation of Motor Current Signature Analysis Fault Diagnosis Based on Digital Signal Processors
    1. 9.1 Introduction
      1. 9.1.1 Cross-Correlation Scheme Derived from Optimal Detector in Additive White Gaussian Noise (AWGN) Channel
    2. 9.2 Reference Frame Theory
      1. 9.2.1 Reference Frame Theory for Condition Monitoring
      2. 9.2.2 (Fault) Harmonic Analysis of Multiphase Systems
      3. 9.2.3 On-Line Fault Detection results
        1. 9.2.3.1 v/f Controlled Inverter-Fed Motor Line Current Analysis
        2. 9.2.3.2 Field-Oriented Control Inverter-Fed Motor Line Current Analysis
        3. 9.2.3.3 Instantaneous Fault Monitoring in Time-Frequency Domain and Transient Analysis
    3. 9.3 Phase-Sensitive Detection-Based Fault Diagnosis
      1. 9.3.1 Introduction
      2. 9.3.2 Phase-Sensitive Detection
      3. 9.3.3 On-Line Experimental Results
    4. References
  15. 10 Electric Implementation of Fault Diagnosis in Hybrid Vehicles Based on Reference Frame Theory
    1. 10.1 Introduction
    2. 10.2 On-Board Fault Diagnosis (OBD) for Hybrid Electric Vehicles (HEVs)
    3. 10.3 Drive Cycle Analysis for OBD
    4. 10.4 Rotor Asymmetry Detection at Zero Speed
    5. References
  16. 11 Robust Signal Processing Techniques for the Implementation of Motor Current Signature Analysis Diagnosis Based on Digital Signal Processors
    1. 11.1 Introduction
      1. 11.1.1 Coherent Detection
      2. 11.1.2 Noncoherent Detection (Phase Ambiguity Compensation)
      3. 11.1.3 Fault Frequency Offset Compensation
    2. 11.2 Decision-Making Scheme
      1. 11.2.1 Adaptive Threshold Design (Noise Ambiguity Compensation)
      2. 11.2.2 Q-Function
      3. 11.2.3 Noise Estimation
    3. 11.3 Simulation and Experimental Result
      1. 11.3.1 Modeled MATLAB Simulation result
      2. 11.3.2 Off-Line Experiments
        1. 11.3.2.2 Off-Line Results for Broken Rotor Bar
    4. 11.3.3 On-Line Experimental Results
    5. References
  17. Index

Product information

  • Title: Electric Machines
  • Author(s): Hamid A. Toliyat, Subhasis Nandi, Seungdeog Choi, Homayoun Meshgin-Kelk
  • Release date: December 2017
  • Publisher(s): CRC Press
  • ISBN: 9781351837873