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Stochastic Model based Fault Diagnosis System of Induction Motors using Online Probability Density Estimation  

Cho, Hyun-Cheol (동아대학교 전기공학과)
Kim, Kwang-Soo (동아대학교 전기공학과)
Lee, Kwon-Soon (동아대학교 전기공학과)
Publication Information
The Transactions of The Korean Institute of Electrical Engineers / v.57, no.10, 2008 , pp. 1847-1853 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 to demonstrate convergence property of the proposed estimation by using statistical convergence and system stability theory. We apply our fault diagnosis approach to three-phase induction motors and achieve real-time experiment for evaluating its reliability and practicability in industrial fields.
Keywords
Fault detection and diagnosis; Induction motor; Stochastic model; Probability density estimation;
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