Journal of Electrical Engineering and Technology

  • 제4권3호
  • /
  • Pages.389-395
  • /
  • 2009
  • /
  • 1975-0102(pISSN)
  • /
  • 2093-7423(eISSN)
대한전기학회 (The Korean Institute of Electrical Engineers)
권호 표지
DOI QR코드

DOI QR Code

Induction Machine Fault Detection Using Generalized Feed Forward Neural Network

  • Ghate, V.N. (Dept. of Electrical Engineering, Govt. College of Engineering Amravati Maharashtra) ;
  • Dudul, S.V. (Dept. of Applied Electronic Engineering, Sant Gadge Baba. Amravati University)
  • 발행 : 2009.09.01
PDF 다운로드
⟨ 이전 논문 다음 논문 ⟩

초록

Industrial motors are subject to incipient faults which, if undetected, can lead to motor failure. The necessity of incipient fault detection can be justified by safety and economical reasons. The technology of artificial neural networks has been successfully used to solve the motor incipient fault detection problem. This paper develops inexpensive, reliable, and noninvasive NN based incipient fault detection scheme for small and medium sized induction motors. Detailed design procedure for achieving the optimal NN model and Principal Component Analysis for dimensionality reduction is proposed. Overall thirteen statistical parameters are used as feature space to achieve the desired classification. GFFD NN model is designed and verified for optimal performance in fault identification on experimental data set of custom designed 2 HP, three phase 50 Hz induction motor.

키워드

참고문헌

  1. R. Isermann, 'Supervision, fault-detection and faultdiagnosis methods-An introduction,' Control Eng. Practice, vol. 5, no. 5, pp.639-652, 1997 https://doi.org/10.1016/S0967-0661(97)00046-4
  2. S. Leohardt and M. Ayoubi, 'Methods of fault diagnosis,' Control Eng.Practice, vol. 5, no. 5, pp. 683-692, 1997 https://doi.org/10.1016/S0967-0661(97)00050-6
  3. R. Patton, P. Frank, and R. Clark, Fault Diagnosis in Dynamic Systems,Theory and Application. Englewood Cliffs, NJ: Prentice-Hall, 1989
  4. M.-Y Chow, Methedologies of using Neural Network and Fuzzy Logic for Motor Incipient Fault Detection, Singpore: World Scientific, 1997
  5. M. -Y. Chow, R. N. Sharpe, and J. C. Hung, 'On the application and design consideration of artificial neural network fault detectors,' IEEETrans. Ind. Electron., vol. 40, pp. 181-198, Apr. 1993 https://doi.org/10.1109/41.222639
  6. F. Filippetti, G. Franceschini, C. Tassoni, and P. Vas, 'Recent developments of induction motor drives fault diagnosis using AI techniques,' IEEE Trans. Ind. Electron., vol. 47, pp. 994-1004, Oct. 2000 https://doi.org/10.1109/41.873207
  7. G. K. Singh and S. A. S. Al Kazzaz, 'Induction machine drive condition monitoring and diagnostic research- a survey,' Electric Power Systems Research, vol. 64, no. 2, pp. 145-158, 2003 https://doi.org/10.1016/S0378-7796(02)00172-4
  8. Jarmo Ilonen, Joni-Kristian Kamarainen, 'Diagnosis Tool for Motor Condition Monitoring' IEEE Transactions Industry Applications, vol. 41, no. 4, pp 963-971 JULY/AUGUST 2005 https://doi.org/10.1109/TIA.2005.851001
  9. Onel I Y , EI Hachemi Benbouzid M., 'Induction Motor Bearing Failure Detection and Diagnosis: Park and Concordia Transform Approaches Comparative Study' IEEE Trans on Mechatronics, vol. 13, pp 257-262 April 2008 https://doi.org/10.1109/TMECH.2008.918535
  10. Tian Han,1 Bo-Suk Yang, 'Fault Diagnosis System of Induction Motors Based on Neural Network and Genetic Algorithm Using Stator Current Signals' Hindawi Publishing Corporation International Journal of Rotating Machinery Volume 2006, pp. 1-13 -2006
  11. M. S. Ballal , Z. J. Khan , H. M. Suryawanshi and R. L. Sonolikar 'Adaptive neural fuzzy inference system for the detection of inter-turn insulation and bearing wear faults in induction motor,' IEEE Trans. Ind. Electron., vol. 54, pp. 250, Feb. 2007 https://doi.org/10.1109/TIE.2006.888789
  12. M. Knight and S. P. Bertani 'Mechanical fault detection in a medium-sized induction motor using stator current monitoring,' IEEE Trans. Energy Convers., vol. 20, pp. 753, Dec. 2005 https://doi.org/10.1109/TEC.2005.853731

피인용 문헌

  1. A Fault Severity Index for Stator Winding Faults Detection in Vector Controlled PM Synchronous Motor vol.10, pp.6, 2015, https://doi.org/10.5370/JEET.2015.10.6.2326