Condition monitoring of rotating electrical machines

Description

Cover Contents About the authors Preface Acknowledgements Nomenclature Abbreviations 1 Introduction to condition monitoring 1.1 Introduction 1.2 Need for monitoring 1.3 What and when to monitor 1.4 Technological timelines 1.5 Structure of text and bibliographies 2 Rotating electrical machines 2.1 Introduction 2.2 Electrical machines structures and types 2.3 DC machines 2.4 AC machines, synchronous 2.5 AC machines, asynchronous or induction 2.6 Permanent magnet or reluctance machines 2.7 Other machine types 2.7.1 Multi-phase machines 2.7.2 Doubly fed and variable-speed drive machines 2.8 Conclusions 3 Electrical machine construction, operation and failure modes 3.1 Introduction 3.2 Materials, strength and temperature 3.3 Electrical machine construction 3.3.1 General 3.3.2 Stator core and frame 3.3.3 Stator windings 3.3.4 Rotors and windings 3.3.5 Enclosures 3.3.6 Connections and heat exchangers 3.3.7 Summary 3.4 Machine specification and failure modes 3.5 Insulation ageing mechanisms 3.5.1 General 3.5.2 Thermal ageing 3.5.3 Electrical ageing 3.5.3.1 General 3.5.3.2 Partial discharges 3.5.3.3 Surface tracking and moisture absorption 3.5.3.4 Transient voltages 3.5.4 Mechanical ageing 3.5.5 Environmental ageing 3.5.6 Synergism between ageing stresses 3.6 Insulation failure modes 3.6.1 General 3.6.2 Stator winding insulation 3.6.2.1 General 3.6.2.2 Delamination and voids 3.6.2.3 Slot discharge 3.6.2.4 Stator end windings 3.6.2.5 End-winding stress grading 3.6.2.6 Repetitive transients 3.6.3 Stator winding faults 3.6.3.1 Winding faults (All machines) 3.6.3.2 Winding conductor faults (Generators) 3.6.3.3 Winding inter-turn faults (All machines) 3.6.3.4 End winding faults (All machines) 3.6.3.5 Winding coolant system faults (Large machines) 3.6.4 Rotor winding faults 3.6.4.1 General 3.6.4.2 Winding faults (Induction motors) 3.6.4.3 Winding faults (Turbo-generators) 3.6.4.4 Winding faults (DC machines) 3.7 Other failure modes 3.7.1 Stator core faults (Turbo-and hydro-generators) 3.7.2 Connection faults (HV motors and generators) 3.7.3 Water coolant faults (All machines) 3.7.4 Bearing faults (All machines) 3.7.5 Shaft voltages (Large machines) 3.8 Conclusions 4 Reliability of machines and typical failure rates 4.1 Introduction and business of failure 4.2 Definition of terms 4.3 Root cause and FMEA 4.3.1 General 4.3.2 Typical root causes and failure modes 4.3.3 Root causes 4.3.4 Failure modes 4.4 Reliability analysis 4.5 Machine structure 4.6 Typical failure rates and MTBFs 4.7 Conclusions 5 Signal processing and instrumentation requirements 5.1 Introduction 5.2 Spectral analysis 5.3 Higher-order spectral analysis 5.4 Correlation analysis 5.5 Vibration signal processing 5.5.1 General 5.5.2 Cepstrum analysis 5.5.3 Time averaging and trend analysis 5.6 Wavelet analysis 5.7 Model-based information extraction 5.7.1 Kalman filter 5.7.2 Observer 5.8 Temperature instrumentation 5.9 Vibration instrumentation 5.9.1 General 5.9.2 Displacement transducers 5.9.3 Velocity transducers 5.9.4 Accelerometers 5.10 Force and torque instrumentation 5.11 Electromagnetic instrumentation 5.12 Wear and debris instrumentation 5.13 Signal conditioning 5.14 Data acquisition 5.15 Conclusions 6 Online temperature monitoring 6.1 Introduction 6.2 Local temperature measurement 6.3 Hot-spot measurement and thermal images 6.4 Bulk measurement 6.5 Conclusions 7 Online chemical monitoring 7.1 Introduction 7.2 Insulation degradation 7.3 Factors that affect detection 7.4 Insulation degradation detection 7.4.1 Particulate detection – core monitors 7.4.2 Particulate detection – chemical analysis 7.4.3 Gas analysis offline 7.4.4 Gas analysis online 7.5 Lubrication oil and bearing degradation 7.6 Oil degradation detection 7.7 Wear debris detection 7.7.1 General 7.7.2 Ferromagnetic techniques 7.7.3 Other wear debris detection techniques 7.8 Conclusions 8 Online vibration monitoring 8.1 Introduction 8.2 Stator core response 8.2.1 General 8.2.2 Calculation of natural modes 8.2.3 Stator electromagnetic force wave 8.3 Stator end winding response 8.4 Rotor response 8.4.1 Transverse response 8.4.1.1 Rigid rotors 8.4.1.2 Flexible rotors 8.4.2 Torsional response 8.5 Bearing response 8.5.1 General 8.5.2 Rolling element bearings 8.5.3 Sleeve bearings 8.6 Monitoring techniques 8.6.1 Overall level monitoring 8.6.2 Frequency spectrum monitoring 8.6.3 Faults detectable from the stator force wave 8.6.4 Torsional oscillation monitoring (IAS) 8.6.5 Shock pulse monitoring 8.7 Conclusions 9 Online current, flux and power monitoring 9.1 Introduction 9.2 Generator and motor stator faults 9.2.1 Generator stator winding insulation detection 9.2.2 Stator current monitoring for stator faults 9.2.3 Brush-gear fault detection 9.2.4 Rotor-mounted search coils 9.3 Generator rotor faults 9.3.1 General 9.3.2 Earth leakage faults on-line 9.3.3 Turn-to-turn faults on-line 9.3.3.1 Air-gap search coils 9.3.3.2 Circulating current measurement 9.4 Motor rotor faults 9.4.1 General 9.4.2 Air-gap search coils 9.4.3 Stator current monitoring for rotor faults (MCSA) 9.4.4 Rotor current monitoring 9.5 Generator and motor comprehensive methods 9.5.1 General 9.5.2 Shaft flux 9.5.3 Stator and rotor currents 9.5.4 Power 9.5.5 Shaft voltage or current 9.5.6 Mechanical and electrical interaction 9.6 Conclusions 10 Online partial discharge (PD) electrical monitoring 10.1 Introduction 10.2 Background to discharge detection 10.3 Early discharge detection methods 10.3.1 RF coupling method 10.3.2 Earth loop transient method 10.3.3 Capacitive coupling method 10.3.4 Wide-band RF method 10.3.5 Insulation remanent life 10.4 Detection problems 10.5 Modern discharge detection methods 10.6 Conclusions 11 Online variable speed drive machine monitoring 11.1 Introduction 11.2 Operation and fault mechanisms 11.2.1 Insulation degradation mechanisms 11.2.2 Bearing current discharges 11.3 Bearing current discharge detection 11.4 Insulation degradation detection 11.4.1 PD measurement 11.4.2 Capacitance and dissipation factor measurement 11.4.3 Built-in winding insulation degradation detector 11.5 Control in-loop machine fault detection 11.6 Conclusions 12 Offline monitoring 12.1 Introduction 12.2 Stator core 12.2.1 General 12.2.2 Turbo-generators 12.2.3 Hydro-generators 12.3 Stator windings 12.3.1 Summary of offline tests 12.3.2 Frequency response analysis 12.4 Rotor windings 12.4.1 Summary of offline tests 12.4.2 Synchronous rotor surge tests 12.5 Conclusions 13 Condition-based maintenance and asset management 13.1 Introduction 13.2 Preventative maintenance 13.3 Condition-based maintenance 13.3.1 Signals and data for condition-based maintenance 13.3.2 Targeted monitoring 13.4 Economics of maintenance strategies 13.4.1 Basic economic justification 13.4.2 Life-cycle costing 13.4.3 Cost–benefit analysis of condition monitoring for CBM 13.4.4 Asset management 13.5 Conclusions 14 Application of artificial intelligence techniques to CM 14.1 Introduction 14.2 Multi-parameter monitoring 14.3 Expert systems 14.4 Fuzzy logic 14.5 Machine learning using ANNs 14.5.1 What can be learned for CM? 14.5.2 Supervised learning through ANN 14.5.3 Unsupervised learning 14.6 Deep learning with big data 14.7 An AI example 14.7.1 Systems incorporating AI 14.7.2 How an MBVI system works 14.7.3 An MBVI system and AI 14.8 Conclusions 15 Safety, training and qualification 15.1 Introduction 15.2 Safety 15.3 Training and qualification 15.3.1 Training and qualification categories 15.3.2 Category I – data collector 15.3.3 Category II – specialist 15.3.4 Category III – analyst 15.3.5 Category IV – expert 15.4 Conclusions 16 Overall conclusions 16.1 CM techniques 16.2 AI and ML 16.3 Standards, training, safety and qualification 16.4 The future importance References Standards Appendix A. Failure modes and root causes in the rotating electrical machines Appendix B. Draft CM good practice guide, MCSA B.1 Introduction B.1.1 What this series of guides is about B.1.2 What this particular guide is about B.2 Overall description B.3 Scope B.4 Expected outputs B.5 Controls and capabilities B.6 Issues B.7 How to apply MCSA B.8 Data communication B.9 Data interpretation B.10 Safety B.11 Skills, competence and training B.12 Taking readings Appendix C. Electrical machines, drives and condition monitoring timeline Index Back Cover