HOS-based nonparametric and parametric methodologies for machine fault detection

IEEE Transactions on Industrial Electronics

Volumn 47, Issue 5, 2000, Pages 1051-1059

  Chow, Tommy W S ^a   Tan, Hong Zhou ^b  

^a CITY UNIVERSITY OF HONG KONG   (Hong Kong)

^b UNIVERSITY OF MANITOBA   (Canada)

Author keywords

[No Author keywords available]

Indexed keywords

ELECTRIC MACHINERY TESTING; INDUCTION MOTORS; LINEAR NETWORK ANALYSIS; MATHEMATICAL MODELS; NONLINEAR NETWORK ANALYSIS; PARAMETER ESTIMATION; PHASE MEASUREMENT; REGRESSION ANALYSIS; ROTATING MACHINERY; VIBRATION MEASUREMENT;

HIGHER ORDER STATISTICS; MACHINE FAULT DETECTION; NONPARAMETRIC PHASE ANALYSIS; SYNTHETIC ELECTRICAL FAULTS; SYNTHETIC MECHANICAL FAULTS;

INDUSTRIAL ELECTRONICS;

EID: 0034294290     PISSN: 02780046     EISSN: None     Source Type: Journal    
DOI: 10.1109/41.873213     Document Type: Article

References (32)

1. K. Abed-Meraim, W. Qiu, and Y. Hua, "Blind system identification," Proc. IEEE, vol. 85, pp. 1310-1322, Aug. 1997.
2. I. E. Alguindigue, A. Loskiewicz-Buczak, and R. E. Uhrig, "Monitoring and diagnosis of rolling element bearings using artificial neural networks," IEEE Trans. Ind. Electron., vol. 40, pp. 209-217, Apr. 1993.
3. N. Arthur and J. Penman, "Supply invariant induction machine condition monitoring," in Proc. 8th Int. Conf. Electrical Machines and Drives, 1997, pp. 341-345.
4. R. W. Barker, G. Klutke, and M. J. Hinich, "Monitoring rotating tool wear using higher-order spectral features," Trans. ASME, J. Eng. Ind., vol. 115, pp. 23-29, 1993.
5. C. F. Beards, Engineering Vibration Analysis with Application to Control Systems. New York: Halsted, 1996.
6. H. F. Chen and L. Gou, Identification and Stochastic Adaptive Control. Boston, MA: Birkhauser, 1991.
7. M. Chow, P. M. Mangum, and S. O. Yee, "A neural network approach to real-time condition monitoring of induction machines," IEEE Trans Ind. Electron., vol. 38, pp. 448-453, Dec. 1991.
8. T. W. S. Chow and S. Y. Cho, "An accelerated recurrent network training algorithm using IIR filter model and recursive least squares method," IEEE Trans. Circuits Syst. I, vol. 44, pp. 1082-1085, Nov. 1997.
9. T. W. S. Chow, H. Z. Tan, and G. Fei, "Third-order cumulant RLS algorithm for nonminimum ARMA systems identification," Signal Process., vol. 61, no. 1, pp. 23-38, 1997.
10. [ 10] T. W. S. Chow and H. Z. Tan, "Semiblind identification of nonminimum phase ARMA models via order recursion with higher-order cumulants," IEEE Trans. Ind. Electron., vol. 45, pp. 663-671, Aug. 1998.
11. T. W. S. Chow and G. Fei, "Three phase induction machines asymmetrical faults identification using bispectrum," IEEE Trans. Energy Conversion, vol. 10, pp. 688-693, Dec. 1995.
12. J. W. A. Fackrell, P. R. White, J. K. Hammond, and R. J. Pinnington, "The interpretation of the bispcetra of vibration signals-I: Theory," Mech. Syst. Signal Process., vol. 9, no. 3, pp. 257-266, 1995.
13. "The interpretation of the bispcetra of vibration signals-II: Experimental results and applications," Mech. Syst. Signal Process., vol. 9, no. 3, pp. 267-274, 1995.
14. G. W. Irwin, K. Warwick, and K. J. Hunt, Neural Network Applications in Control. London, U.K.: IFF, 1995.
15. R. Isermann, "Supervision, fault-detection and fault-diagnosis methods-An introduction," Contr. Eng. Practice, vol. 5, no. 5, pp. 639-652, 1997.
16. R. Isermann and P. Balle, "Trends in the application of model-based fault detection and diagnosis of technical processes," Contr. Eng. Practice, vol. 5, no. 5, pp. 709-719, 1997.
17. J.-N. Juang, Applied System Identification. Englewood Cliffs, NJ: Prentice-Hall, 1994.
18. S. Leonhardt and M. Ayoubi, "Methods of fault diagnosis," Contr. Eng. Practice, vol. 5, no. 5, pp. 683-692, 1997.
19. J. L. Maryak, L. W. Hunter, and S. Favin, "Automated system monitoring and diagnosis via singular value decomposition," Automatica, vol. 33, no. 11, pp. 2059-2063, 1997.
20. A. C. McCormick and A. K. Nandi, "Neural network autoregressive modeling of vibrations for condition monitoring of rotating shafts," IEEE Int. Conf. Neural Networks, vol. 4, pp. 2214-2218, 1997.
21. R. Patton, P. Frank, and R. Clark, Fault Diagnosis in Dynamic Systems, Theory and Application. Englewood Cliffs, NJ: Prentice-Hall, 1989.
22. J. Penman, M. N. Dey, and A. J. Tait, "Condition monitoring of electrical drives," Proc. Inst. Elect. Eng., pt. B, vol. 133, no. 3, 1986.
23. A. Swami, G. B. Giannakis, and G. Zhou, "Bibliography on higher-order statistics," Signal Process., vol. 60, pp. 65-126, 1997.
24. H. Z. Tan and T. W. S. Chow, "Blind and total identification of ARMA models in higher-order cumulants domain," IEEE Trans. Ind. Electron., to be published.
25. "Blind identification of quadratic nonlinear models using neural networks with higher-order cumulants," IEEE Trans. Ind. Electron., vol. 47, pp. 687-696, June 2000.
26. H. Z. Tan, T. W. S. Chow, and K. T Ng, "A constrained neural networks based approach for blind identification of quadratic systems," Int. J. Knowl.-Based Intell. Eng. Syst., vol. 2, no. 2, pp. 111-119, 1998.
27. H. Tong, Nonlinear Time Series, A Dynamical System Approach. Oxford, U.K.: Oxford Univ. Press, 1990.
28. J. Y. F Yam and T. W. S. Chow, "Extended least squares based algorithm for training feedforward networks," IEEE Trans. Neural Networks, vol. 8, pp. 806-810, Aug. 1997.
29. S.-H. Yu and A. M. Annaswamy, "Adaptive control of nonlinear dynamic systems using 0-adaptive neural networks," Automatica, vol. 33, no. 11, pp. 1975-1995, 1997.
30. R. Zbikowski and K. J. Hunt, Neural Adaptive Control Technology. Singapore: World Scientific, 1996.
31. N. Arthur and J. Penman, "Induction machine condition monitoring with higher-order spectra Part I: Fundamentals and fixed frequency operation," in Proc. IEEE IECON'98, Aachen, Germany, Sept. 1998, pp. 1889-1994.
32. "Induction machine condition monitoring with higher-order spectra Part II: Variable frequency operation and automated diagnosis," in Proc. IEEE /ECCW98, Aachen, Germany, Sept. 1998, pp. 1895-1990.