作　　者： ; ;

机构地区： 江南大学通信与控制工程学院

出　　处： 《控制与决策》 2010年第12期1853-1856,1865,共5页

摘　　要： 针对故障预报中系统剩余寿命难以精确估计的问题,提出基于隐半马尔可夫模型(HsMM)的系统在线故障预报方法.首先重新设计HsMM模型结构,利用模糊??均值聚类(FCM)方法化连续取值的系统输入输出变量为有限集合内取值,简化了建模计算过程.在实现对故障检测的同时,利用模型的状态驻留参数估计系统的剩余寿命,从而实现系统的故障预报.利用连续搅拌反应釜(CSTR)模型进行仿真验证,在输入输出数据含有噪声的情况下,较准确地估计了系统的剩余寿命,从而表明了方法的有效性. To solve the problem of accurate forecasting of remaining-useful-life,an on-line fault prediction method based on hiding semi Markov model（HsMM） is proposed in this paper.The fuzzy c-means（FCM） clustering algorithm is used to cluster the input-output data of system.The variables with continuous value are transformed to discrete value variables.Then,the structure of HsMM is redesigned,and the modeling process of HsMM is simplified.The fault detection is accomplished by the HsMM model which is established with data of normal system.At the same time,the remaining-useful-life can be forecasted by the time duration of the hidden states.In addition,the approximate time when the fault has established is estimated.Therefore,the fault prediction is also accomplished.By using the continuous stirred tank reactor（CSTR） as the simulation model,the proposed method can forecast the remaining-useful-life of failure system accurately when the data of system has noise.

关 键 词： 故障预报 剩余寿命 隐半马尔可夫模型 连续搅拌反应釜

领　　域： [自动化与计算机技术] [自动化与计算机技术]