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http://dx.doi.org/10.5050/KSNVE.2015.25.9.637

Fault Diagnosis of Rotating System Mass Unbalance Using Hidden Markov Model  

Ko, Jungmin (School of mechanical engineering, Hanyang University)
Choi, Chankyu (School of mechanical engineering, Hanyang University)
Kang, To (Korea Atomic Energy Research Institute)
Han, Soonwoo (Korea Atomic Energy Research Institute)
Park, Jinho (Korea Atomic Energy Research Institute)
Yoo, Honghee (School of mechanical engineering,Hanyang University)
Publication Information
Transactions of the Korean Society for Noise and Vibration Engineering / v.25, no.9, 2015 , pp. 637-643 More about this Journal
Abstract
In recent years, pattern recognition methods have been widely used by many researchers for fault diagnoses of mechanical systems. The soundness of a mechanical system can be checked by analyzing the variation of the system vibration characteristic along with a pattern recognition method. Recently, the hidden Markov model has been widely used as a pattern recognition method in various fields. In this paper, the hidden Markov model is employed for the fault diagnosis of the mass unbalance of a rotating system. Mass unbalance is one of the critical faults in the rotating system. A procedure to identity the location and size of the mass unbalance is proposed and the accuracy of the procedure is validated through experiment.
Keywords
Hidden Markov Model; Fault Diagnosis; Feature Vector; Vector Quantization; Mass Unbalance; Rotating System;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
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