A HMM and Grey Model Based ERL Forecasting Method
This paper presents a hidden Markov model (HMM) based prognosis method for prediction of equipment health. HMM allows modeling the time duration of the hidden states and therefore is capable of prognosis.The estimated state duration probability distributions can be used to predict the remaining useful life of the systems.The previous HMM based prognosis algorithm assumed that the transition probabilities are only state-dependent.That is, the probability of making transition to a less healthy state does not increase with the age.In the proposed method,in order to characterize a deteriorating machine, an aging factor that discounts the probabilities of staying at current state while increasing the probabilities of transitions to less healthy states will be introduced.After the estimation of the aging factor, a grey model is used to calculate the expected residual life (ERL) by redefining the hazard rate.With the equipment health prognosis,we can predict the behavior of the equipment condition.
Prognosis model Hidden Markov model Hazard rate Grey model Ezpected residual life
Ying Peng Ming Dong
Department of Industrial Engineering and Management School of Mechanical Engineering Shanghai Jiao T Department of Operations Management Antai College of Economics & Management Shanghai Jiao Tong Unive
国际会议
2009 8th International Conference on Reliability,Maintainability and Safety(第八届中国国际可靠性、维修性、安全性会议)
成都
英文
208-212
2009-08-24（万方平台首次上网日期，不代表论文的发表时间）