| Title |
Stochastic Model based Fault Diagnosis System of Induction Motors using Online Probability Density Estimation |
| Authors |
조현철(Cho, Hyun-Cheol) ; 김광수(Kim, Kwang-Soo) ; 이권순(Lee, Kwon-Soon) |
| Keywords |
Fault detection and diagnosis ; Induction motor ; Stochastic model ; Probability density estimation |
| 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. |