Condition Monitoring of Rotating Electrical Machines
2: Kinectrics Inc., Toronto, ON, Canada
Condition monitoring of engineering plant has increased in importance as engineering processes are automated and manpower is reduced. However, electrical machinery receives attention only at infrequent intervals when plant is shut down and the application of protective relays to machines has also reduced operator surveillance. A first edition of Condition Monitoring of Electrical Machines, written by Tavner and Penman, was published in 1987. The economics of industry have now changed, as a result of the privatisation and deregulation of the energy industry, placing emphasis on the importance of reliable operation of plant, throughout the whole life cycle, regardless of first cost. The availability of advanced electronics and software in powerful instrumentation, computers, and digital signal processors (DSP) has simplified our ability to instrument and analyse machinery. As a result condition monitoring is now being applied to a wider range of systems, from fault-tolerant drives of a few hundred watts in the aerospace industry, to machinery of a few hundred megawatts in major capital plant. In this new book the original authors have been joined by Ran, an expert in power electronics and control, and Sedding, an expert in the monitoring of electrical insulation systems. Together the authors have revised and expanded the earlier book, merging their own experience with that of machine analysts to bring it up to date. The book is aimed at professional engineers in the energy, process engineering and manufacturing industries, plus research workers and students.
Inspec keywords: electric machines; condition monitoring
Other keywords: rotating electrical machines; condition monitoring
Subjects: a.c. machines
- Book DOI: 10.1049/PBPO056E
- Chapter DOI: 10.1049/PBPO056E
- ISBN: 9780863417412
- e-ISBN: 9780863419911
- Page count: 304
- Format: PDF
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Front Matter
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1 Introduction to condition monitoring
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Rotating electrical machines permeate all areas of modern life at both the domestic and industrial level. The average modern home in the developed world contains 20-30 electric motors in the range 0-1 kW for clocks, toys, domestic appliances, air conditioning or heating systems. Modern cars use electric motors for windows, windscreen wipers, starting and now even for propulsion in hybrid vehicles. A modern S-series Mercedes-Benz car is reported to incorporate more than 120 separate electrical machines.
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2 Construction, operation and failure modes of electrical machines
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This chapter shows the common structure present in electrical machines regard less of their size. The construction of electrical machines has also been demonstrated with an indication of the effect of operational service on failure modes. The importance of the insulation system of the machine has also been considered and discussed. Finally, typical failures in service have been shown to identify the most common failure modes that an engineer will encounter, starting with those originating in the insulation system but then expanding to consider other sources. The failure modes demonstrate how faults may be detected in their early stages by monitoring appropriate parameters. In the next chapter we will describe reliability analysis. which will connect root causes to failure modes and shows how condition monitoring can be directed to address particular components in the electrical machine.
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3 Reliability of machines and typical failure rates
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It is necessary to identify the condition monitoring that needs to be applied to detect those faults covered in the previous chapter. Condition monitoring has been seen primarily as the province of those who analyse fault signals and interpret results. However, interpretation must be informed by causality and the authors' view is that one of the important changes to occur in condition monitoring over the last 30 years is ensuring that it is firmly directed towards the root causes of machine failure. In so doing, successful condition monitoring directly addresses machine unreliability or, more importantly for the operator, lack of availability. This chapter sets out the issues concerned with this causality.
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4 Instrumentation requirements
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This chapter shows the wide range of instrumentation and data acquisition techniques now available to monitor electrical machines. Modern techniques and methods have been shown and in the following chapter we show how the signals from these sensors can be processed to provide condition-monitoring information.
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5 Signal processing requirements
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This chapter describes the signal processing methods now available for computer monitoring electrical machines. The following five chapters describe the major temperature, chemical, mechanical and electrical techniques available for monitoring.
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6 Temperature monitoring
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This chapter shows that temperature measurement can yield very valuable bulk indications of the condition of an electrical machine using simple sensors and narrow bandwidth (< 1 Hz), low -data-rate signals and, because temperature limits the rating of a machine, over-temperature is a valuable condition-monitoring signal. Temperature detection has repeatedly been shown to be an effective global monitoring technique for electrical machines, but has been neglected as a monitoring method. Temperature measurement is usually done in traditional and rather antiquated ways, and there are some simple changes that could be made in existing practice to make more sense of it. These changes are generally in the area of signal processing and in particular the importance of presenting temperature rises to the operator, rather than absolute temperature. There are also advances in the application of modern sensors, which will allow temperature measurements to be made closer to the active parts of a machine, and these should be exploited.
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7 Chemical monitoring
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This chapter shows that chemical and wear analysis have been demonstrated to be effective global monitoring techniques for electrical machines which can produce narrow bandwidth (<1 Hz) signals. Chemical degradation of insulating materials and lubricants are detectable and can give bulk indications of the condition of an electrical machine. This is particularly important when it is considered how central insulation and lubrication integrity are to the long-term life of a machine. However, the detectability criteria for these techniques are difficult, the chemical analysis processes involved are complex and expensive, and the quantity of data generated by chemical analysis currently confine their application to only the largest machines.
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8 Vibration monitoring
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Vibration measurement is at the heart of the monitoring of rotating machines. Although electrical machines are generally low-vibration devices, they may be coupled to high-vibration prime movers or driven plant via flexible couplings and mounted on separate foundations via resilient mounts. The excitation of electrical machine vibration is generally mechanical unbalance or harmonic electromagnetic forces originating from the machine airgap. The response of the machine to these exciting forces depends on the precise coupling and mounting of the machine. Vibration monitoring and shock pulse analysis are non-invasive but use a number of specialised sensors, broad bandwidth and complex analysis. The precise selection and location of sensors is very important. However, because of its wide application in other rotating machines vibration analysis has established itself as a reliable and widely accepted technique for electrical machines and shock pulse analysis, and also (particularly for bearings) because it is capable of differentiating between mechanical and electromagnetic excitation forces, which is invaluable in detecting root causes before they develop into failure modes. Motor speed has been analysed using instantaneous angular speed to detect rotor electrical faults but has not been widely used by operators. This chapter shows the close relationship between vibration and electrical monitoring of the machine.
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9 Electrical techniques: current, flux and power monitoring
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This chapter shows that electrical techniques are powerful tools for the condition monitoring of electrical machines, particularly axial leakage flux, current and power, offering the potential to provide a general condition-monitoring signal for the machine. The availability of high-quality, digitally sampled mechanical vibration and electrical terminal data from electrical machines opens the possibility for more comprehensive monitoring of the machine and prune mover or driven machine combinations. However, these signals generally require broad bandwidth (>50 kHz) and a high data rate for adequate analysis. Therefore the principal difficulty of applying these techniques is the complexity of the necessary spectral analysis and interpretation of their content. This situation is made more difficult if variable speed drives are involved because tune domain signals may no longer be stationary and will also be polluted by harmonics from the power electronic drive. Comprehensive monitoring of an electrical machine can be achieved by measuring shaft flux, current, power and electrical discharge activity. These are broad bandwidth (generally >50 kHz) signals requiring complex analysis. Shaft flux, current and power signals are capable of detecting faults in both the electrical and mechanical parts of a drive train. Shaft voltage or current is an ineffective condition monitoring technique for electrical machines. Shaft flux monitoring is non-mvasive and uses a single sensor but it is complex to analyse and untested in the field. Current monitoring is also non-mvasive, but uses existing sensors and has established itself as motor current spectral analysis, a reliable and widely accepted technique for machine monitoring. Power monitoring is also non-mvasive, uses existing sensors but requires less bandwidth (<10 kHz) and less complex spectral interpretation to detect faults but is not yet widely accepted, so it deserves investigation for future development.
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10 Electrical techniques: discharge monitoring
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This chapter deals with a more specialised terminal analysis than considered in Chapter 9, which has the potential to detect those discharge activities present in the machine winding insulation, particularly in high voltage machines. One of the reasons this technique has received so much attention is because the insulation system lies at the heart of every electrical machine, as described in Chapter 2, and its deterioration can be relatively slow, as described in Chapter 3. Therefore it should be a good target for condition monitoring.
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11 Application of artificial intelligence techniques
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The techniques of artificial intelligence have been seen as potentially valuable for the condition monitoring of electrical machines because the underlying physics of machine operation and dynamics, as shown in Chapters 8 and 9, is so rich in fundamental rules, and these could be exploited by an expert system. This chapter shows that these techniques can be used to improve the signal-to noise ratio in a fault situation, particularly in the complex area of monitoring terminal conditions and the difficult subset of that, the detection and measurement of partial discharge activity. However, the development of artificial intelligence for electrical machine condition monitoring is still in its infancy and despite the considerable work that has been done in this area, much more is required to bring such techniques into the mainstream of condition monitoring. An abiding lesson from this chapter is to understand the importance in condition monitoring of relating various monitoring signals with one another, what was described in the first edition of this text as multi-parameter monitoring. It is clear, however, that the future of machine condition monitoring will be heavily affected by multi-parameter monitoring and by the application of artificial intelligence to that process.
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12 Condition-based maintenance and asset management
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This book is concerned with the process of early detection but greater benefits could be achieved from condition monitoring if the information from monitoring is used to schedule maintenance, allowing planned shut-downs so that the life of plant, of which the electrical machine forms a part, can be extended. This is the process of condition-based maintenance, first described in Chapter 1. However, further benefits could be realised from condition monitoring if the total life-cycle costs of the machine and the plant it serves could be reduced by its application. This in turn requires an estimate of the running costs of plant and forecasts of its variation throughout its life. In the light of this knowledge the plant or asset owner can operate, maintain, renew or dispose of that asset on the basis of the information made available through these processes. This is asset management. This chapter describes how these techniques could be applied to rotating electrical machines.
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Appendix: Failure modes and root causes in rotating electrical machines
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This appendix presents the machine structure, the failure mode and root causes in rotating electrical machines which are shown in figures 2.10 and 3.7.
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Back Matter
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