Transactions of the Korean Society for Noise and Vibration Engineering (한국소음진동공학회논문집)

The Korean Society for Noise and Vibration Engineering (한국소음진동공학회)
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Application of Hidden Markov Model Using AR Coefficients to Machine Diagnosis

AR계수를 이용한 Hidden Markov Model의 기계상태진단 적용

  • 이종민 (한국과학기술연구원 Tribology 연구센터) ;
  • 황요하 (한국과학기술연구원 Tribology 연구센터) ;
  • 김승종 (한국과학기술연구원 Tribology 연구센터) ;
  • 송창섭 (한양대학교 기계공학부)
  • Published : 2003.01.01
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Abstract

Hidden Markov Model(HMM) has a doubly embedded stochastic process with an underlying stochastic process that can be observed through another set of stochastic processes. This structure of HMM is useful for modeling vector sequence that doesn't look like a stochastic process but has a hidden stochastic process. So, HMM approach has become popular in various areas in last decade. The increasing popularity of HMM is based on two facts : rich mathematical structure and proven accuracy on critical application. In this paper, we applied continuous HMM (CHMM) approach with AR coefficient to detect and predict the chatter of lathe bite and to diagnose the wear of oil Journal bearing using rotor shaft displacement. Our examples show that CHMM approach is very efficient method for machine health monitoring and prediction.

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References

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