摘要
针对传统隐半马尔科夫模型(HSMM)在故障诊断和预测应用中存在的不足,对传统HSMM做了以下改进:一是将状态持续时间概率分布和监测值概率分布连续化,并假定其服从威布尔分布;二是基于状态开始时间的识别,提出了状态剩余持续时间;三是提出了时变转移概率的概念,给出了各时刻转移概率的计算方法。确立了基于改进HSMM的故障诊断和预测的方法体系,给出了故障诊断判据和设备剩余寿命的计算式。案例研究表明方法是合理有效的。
To the four deficiencies of traditional HSMM applied in fault diagnosis and prognosis,the HSMM was improved as following.Firstly,the distribution of the state durations and detected value were continuous and parametric,the prior distribution was setted to Weibull distribution;secondly,the state residual durations was proposed based on the starting time of the state;thirdly,the time-varying transition probability was proposed and the formula of transition probability was given.The method of fault diagnosis and prognosis based on improved HSMM was setup,and the formulas of fault diagnosis criteria and Remaining Useful Life（RUL） of the equipment were presented.The rationality and the validity of this method was verified through an example.
出处
《现代制造工程》
CSCD
北大核心
2011年第8期118-122,共5页
Modern Manufacturing Engineering
基金
国防十一五预研项目(1010503020303)
