Condition monitoring analysis methods for electrical machines: A review

 
 
 
  • Abstract
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  • References
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  • Abstract


    This paper provides a review on condition monitoring analysis methods for electrical machines. An overview of condition monitoring is provided where online as well as offline monitoring is discussed. A section on vibration monitoring is included, since vibration monitoring is one of the most important online monitoring techniques. As part of vibration monitoring, background vibration, the effect of machine speed and load and variation of a signal at constant operating conditions are discussed. The paper further discussed time and process domain averaging, temperature effects, spurious low frequency ‘ski-slope’ effect and evaluation standards related to vibration monitoring. Various analysis methods exist for the condition monitoring of machines. These analysis methods are divided and discussed in this paper as deterministic and non-deterministic (or statistical analysis approach) methods. The paper ends with sections on condition monitoring measurements and noise filtering during condition monitoring.

  • References


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      References

      [1] B.K.N. Rao, Handbook of condition monitoring, First Edition, Elsevier Advanced Technology, 1996.

      [2] T.G. Habetler, “On-line condition monitoring and diagnostics of electric machines,” School of Electrical and Computer Engineering, Power Electronics and Motor Diagnostics Laboratory, Georgia Institute of Technology, 2005.

      [3] ISO 7919-2, Mechanical vibration — Evaluation of machine vibration by measurements on rotating shafts — Part 2: Land-based steam turbines and generators in excess of 50 MW with normal operating speeds of 1500 r/min, 1800 r/min, 3000 r/min and 3600 r/min, 2002.

      [4] ISO 7919-5, Mechanical vibration – Evaluation of machine vibration on rotating shafts – Part 5: Machine sets in hydraulic power generating and pumping plants, 2005.

      [5] ISO 9000, Quality management and quality assurance, International Organization for Standardization, p. 704, 2003.

      [6] ISO 10816-1, Mechanical vibration – Evaluation of machine vibration by measurements on non-rotating parts – Part 1: General guidelines, 1995.

      [7] ISO 10816-3, Mechanical vibration – Evaluation of machine vibration by measurements on non-rotating parts – Part 3: Industrial machines with nominal power above 15 kW and nominal speeds between 120 r/min and 15 000 r/min when measured in situ, 1998.

      [8] Pruftechnik Group, Condition monitoring support. [Online]. Available: www.pruftechnik.com.

      [9] Future Fibre Technologies Pty. Ltd., Machine condition monitoring. [Online]. Available: www.fftsecurity.com.

      [10]A. Korde, “Online condition monitoring of motors using electrical signature analysis,” Proceedings of the Advances in Condition-Based Plant Maintenance Seminar, Diagnosis Technologies India Ltd., Mumbai, May 2002.

      [11]T. Lindh, “Condition monitoring of induction machines,” Lappeenranta University of Technology, 2003.

      [12]V. Kokko, “Condition monitoring of squirrel-cage motors by axial magnetic flux measurements,” Acta Universitatis Ouluensis C179, Oulu, ISBN: 951-42-6937-3, 2003.

      [13]J.Shiroshi, Y. Li, S. Liang, and T. Kurfess, “Bearing condition diagnostics via vibration and acoustic emission measurements,” Mechanical Systems and Signal Processing, vol. 5, no. 11, pp. 693–705, 1997.

      [14]T. Honkanen, “Modelling industrial maintenance systems and the effects of automatic condition monitoring,” Helsinki University of technology, Feb. 2004.

      [15]C.W. Reeves, The vibration monitoring handbook, First Edition, Coxmoor Publishing, Oxford, UK, 1998.

      [16]D.G. Dorrell, W.T. Thomson, and S. Roach, “Combined effects of static and dynamic eccentricity on airgap flux waves and the application of current monitoring to detect dynamic eccentricity in 3-phase induction motors,” Seventh International Conference on Electrical Machines and Drives, pp. 151-155, 1995.

      [17]P.J. Tavner and J. Penman, Condition monitoring of electric motors, First Edition, Research Studies Press Ltd., England, ISBN: 0-86380-061-0, 1987.

      [18]P.L. Tímár, A. Fazekas, and J. Kiss, “Noise and vibration of electrical machines,” Studies in Electrical and Electronic Engineering 34, Elsevier, Amsterdam, 1989.

      [19]J.I. Taylor, “The vibration analysis handbook,” Vibration Consultants, 1994.

      [20]G. Yen and K. Lin, “Wavelet packet feature extraction for vibration monitoring,” IEEE Transactions on Industrial Electronics, vol. 47, no. 3, June 2000.

      [21]L. Cohen, “Time-frequency distributions - a review,” Proceedings of the IEEE, vol. 77, no. 7, pp. 941-981, 1989.

      [22]P.D. McFadden and M.M. Toozhy, “Application of signal averaging to vibration monitoring of rolling element bearings,” Report no. OUEL 2216/99, University of Oxford, Department of Engineering Science, Oxford, 1999.

      [23]Z. Shi, M. Zha, and H. Peng, “The monitoring system of the PCU for the 10 MW high temperature gas-cooled reactor,” Second International Topical Meeting on High Temperature Reactor Technology, Beijing, CHINA, Sep. 22-24, 2004.

      [24]S.W. Lang and J.H. Mcclellan, “Frequency estimation with maximum entropy spectral estimators,” IEEE Transactions on Acoustic, Speech, and Signal Processing, vol. 28, no. 6, pp. 716-724, 1980.

      [25]J. Partanen, L. Tuomo, and J. Pertti, “Intelligent applications for the management of electrical systems in industrial plants,” Proceedings of Intelligent System Application to Power Systems (ISAP'99), Rio de Janeiro, Brazil, Apr. 1999.

      [26]R.O. Duda, D.G. Stork, and P.E. Hart, Pattern classification, John Wiley & Sons Inc., ISBN: 0471056693, 2000.

      [27]K. Kyusung and A.G. Parlos, “Induction motor fault diagnosis based on neuropredictors and Wavelet signal processing,” IEEE Transactions on Mechatronics, vol. 7, no. 2, June 2002.

      [28]A.C. Balbahadur, “A thermo-elasto-hydrodynamic model of the Morton effect operating in overhung rotors supported by plain or tilting pad journal bearings,” Faculty of the Virginia Polytechnic Institute and State University, Blacksburg, Virginia, Feb. 2001.

      [29]K. Fukunaga, Introduction to statistical pattern recognition, Second Edition, Academic Press, 1990.

      [30]H.M. Islam and M.G. Mostafa, “Novel microprocessor based negative phase current relay and meter,” Electrical Power and Energy Systems, vol. 18, no. 8, pp. 547-552, 1996.

      [31]G.B. Kliman and W.J. Premerlani, “Recent development in on-line motor diagnostics,” ICEM conference proceedings, Istanbul, pp. 471-475, 1998.

      [32]C.K. Mechefske, “Objective machinery fault diagnosis using fuzzy logic,” Mechanical Systems and Signal Processing, no. 12, pp. 855-862, 1998.

      [33]M.E.H. Benbouzid and H. Nejjari, “A simple fuzzy logic approach for induction motors stator condition monitoring,” International Electric Machines and Drives Conference (IEMDC), pp. 634-639, 2001.

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Article ID: 29345
 
DOI: 10.14419/ijet.v7i4.29345




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