Journal of the Korean Society of Safety (한국안전학회지)

The Korean Society of Safety (한국안전학회)
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Fault Detection and Classification of Faulty Induction Motors using Z-index and Frequency Analysis

Z-index와 주파수 분석을 이용한 유도전동기 고장진단과 분류

  • Lee, Sang-Hyuk (Department of Electrical Engineering, Pusan National University)
  • 이상혁 (부산대학교 전기공학과)
  • Published : 2005.09.30
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Abstract

In this literature, fault detection and classification of faulty induction motors are carried out through Z-index and frequency analysis. Above frequency analysis refer Fourier transformation and Wavelet transformation. Z-index is defined as the similar form of energy function, also the faulty and healthy conditions are classified through Z-index. For the detection and classification feature extraction for the fault detection of an induction motor is carried out using the information from stator current. Fourier and Wavelet transforms are applied to detect the characteristics under the healthy and various faulty conditions. We can obtain feature vectors from two transformations, and the results illustrate that the feature vectors are complementary each other.

Keywords

References

  1. P. Vas, Parameter Estimation, Condition Monitoring, and Diagnosis of Electrical Machines, Clarendron Press, 1993
  2. N. Arthur, J. Penman, A. McLean and A. Parsons, 'Induction machine condition monitoring with higher order spectra Part 1: fundamentals and fixed frequency operation', IECON'98 Proceedings of the 24th Annual Conference of the IEEE, pp. 1889-1894, 1998 https://doi.org/10.1109/IECON.1998.723030
  3. M. Haji and H.A. Toliyat, 'attern recognition-A technique for Induction Machines Rotor Fault Detection Eccentricity and Broken Bar Fault', Conference Record of the 2001 IEEE Induxtry Applications Conference, Vol. 3, pp. 1572-1578, 30 Sept.- 4 Oct. 2001
  4. S. Nandi, H.A. Toliyat, 'ondition Monitoring and Fault DIagnosis of Electrical Machines-A Review' IEEE Induxtry Applications Conference, vol. 1, pp. 197-204,1999
  5. B. Yazici, G. B. Kliman, 'An Adaptive Statistical Time-Frequency Method for Detection of Broken Bars and Bearing Faults in Motors using Stator Current,' IEEE Trans. On Industry Appl. Vol. 35, No. 2, pp. 442-452, 1999 https://doi.org/10.1109/28.753640
  6. K. Abbaszadeh, J. Milimonfared, M. Haji, and H.A. Toliyat, 'roken Bar Detection in Induction Motor via Wavelet Transformation', IECON'01: The 27th Annual Conference of the IEEE Industrial Electronics Society, pp. 95-99, 2001 https://doi.org/10.1109/IECON.2001.976461
  7. R. Bracewell, The Fourier Transformation and Its Applications, 3rd ed. New York, McGraw-Hill, 1999
  8. I. Daubechies, Ten Lectures on Wavelets, The Society for Industrial and Applied Mathematics, 1992
  9. S. Mallat, ' theory for multiresolution signal decomposition: the wavelet representation', IEEE Trans. On Pattern analysis and machine intelligence, Vol. 11, No. 7, pp. 674-693, 1989 https://doi.org/10.1109/34.192463