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Fault Detection and Diagnosis Systems of Induction Machines using Real-Time Stochastic Modeling Approach  

Lee, Jin-Woo (동아대학교 전기공학과)
Kim, Kwang-Soo (동아대학교 전기공학과)
Cho, Hyun-Cheol (울산과학대학 전기전자학부)
Lee, Young-Jin (한국폴리텍 항공대학 항공전기과)
Lee, Kwon-Soon (동아대학교 전기공학과)
Publication Information
The Transactions of the Korean Institute of Electrical Engineers P / v.58, no.3, 2009 , pp. 241-248 More about this Journal
Abstract
This paper presents stochastic methodology based fault detection algorithm for induction motor systems. We measure current of healthy induction motors by means of hall sensor systems and then establish its probability distribution. We propose online probability density estimation which is effective in real-time implementation due to its simplicity and low computational burden. In addition, we accomplish theoretical analysis of the proposed estimation to demonstrate its convergence property by using statistical convergence and system stability theories. We apply our fault detection approach to three-phase induction motors and achieve real-time experiment for evaluating its reliability and practicability in industrial fields.
Keywords
Fault Detection; Induction Motor; Online Probability Density Estimation; Maintenance System;
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