Browse > Article
http://dx.doi.org/10.5207/JIEIE.2004.18.6.070

Fault Diagnosis of 3 Phase Induction Motor Drive System Using Clustering  

Park, Jang-Hwan (충주대학교 정보제어공학과)
Kim, Sung-Suk (충주대학교 정보제어공학과)
Lee, Dae-Jong (충주대학교 정보제어공학과)
Chun, Myung-Geun (충주대학교 정보제어공학과)
Publication Information
Journal of the Korean Institute of Illuminating and Electrical Installation Engineers / v.18, no.6, 2004 , pp. 70-77 More about this Journal
Abstract
In many industrial applications, an unexpected fault of induction motor drive systems can cause serious troubles such as downtime of the overall system heavy loss, and etc. As one of methods to solve such problems, this paper investigates the fault diagnosis for open-switch damages in a voltage-fed PWM inverter for induction motor drive. For the feature extraction of a fault we transform the current signals to the d-q axis and calculate mean current vectors. And then, for diagnosis of different fault patterns, we propose a clustering based diagnosis algorithm The proposed diagnostic technique is a modified ANFIS(Adaptive Neuro-Fuzzy Inference System) which uses a clustering method on the premise of general ANFIS's. Therefore, it has a small calculation and good performance. Finally, we implement the method for the diagnosis module of the inverter with MATLAB and show its usefulness.
Keywords
fault diagnosis; induction motor drive system; inverter; ANFIS;
Citations & Related Records
연도 인용수 순위
  • Reference
1 J. S. R. ANRS: Adaptive Network-based Fuzzy Inference System, Jang, IEEE trans. on System, Man, and Cybemetics, vol. 23, no. 3, pp. 665-685, 1993
2 J-S. R. Jang, C.T. Sun,. E. Mizutani, Neuro- Fuzzy and Soft Computing: A Computational Approach to Learning and Machine Intelligence, Prentice Hall, 1997
3 R. R. Yager, D. P. Filev, Generation of Fuzzy Rules by Mountain Clustering, Journal of Intelligent and Fuzzy System, vol. 2, pp. 209-219, 1994
4 Z. Ye, and B. Wu, Simulation of electrical faults of three phase induction motor drive system Power Electronics Specialists Conference, 2001, vol. 1, pp. 75-80, june 2001
5 P.J. Chrzan, and R. Szczesny, Fault diagnosis of Voltage-fed inverter for induction motor drive, ISIE '96., Proceedings of the IEEE International Symposium, vol. 2, vol. 2, pp. 1011-1016, june 1996   DOI
6 J. Klima. Analytical investigation of an induction motor drive under inverter fault mode operations, Electric Power Applications, lEE Proceedings, vol. 150, pp. 255-262, May 2003
7 Sung-Suk Kim, Keun-Chang Kwak, jeong-Woong Ryu, Myung-Ceun Chun, A Neuro-Fuzzy System Modeling using Gaussian Mixture ModeI and Clustering Method, KFIS, vol. 12, no. 6, pp. 571-578, 2002
8 A.G. Eason, R.L. Ribeiro, C.B. Jacobina, E.R.C. Silva, and A.M.N. Lima, Fault detection of open-switch damage in voltage-fed PWM motor drive systems, Power Electronics, lEEE: Transections, vol. 18, pp. 587-593, March 2003
9 R. Peuget, S. Coortine and J.P. Rognon, Fault Detection and Isolation on a PWM Inverter by Knowledge-Based Model, IEEE Transections. on Industry Applications, vol. 34, no.6, Nov/Dec 1998
10 Sung-Suk Kim, Keun-Chang Kwak, Jeong-Woong Ryu, Myung-Ceun Chun, A Neuro-Fuzzy Modeling using the Hierarchical Oustering and Gaussian Mixture ModeI, KFIS, vol. 13, no. 5, pp. 512-519, 2003