广东工业大学 计算机学院,广东,广州,510006
叶彬彬(1989–),男,硕士研究生,主要研究方向为控制理论与控制工程、算法分析与设计
刘富春(1971–),男,教授,博士生导师,主要研究方向为控制理论与控制工程、算法分析与设计. E-mail:fliu2011@163.com
网络首发:2018-11-23,
纸质出版:2018
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叶彬彬, 刘富春. 随机离散事件系统的故障预测[J]. 广东工业大学学报, 2018, 35(6): 83-89.
Ye Bin-bin, Liu Fu-chun. Failure Predictability of Stochastic Discrete Event Systems[J]. 2018, 35(6): 83-89.
叶彬彬, 刘富春. 随机离散事件系统的故障预测[J]. 广东工业大学学报, 2018, 35(6): 83-89. DOI: 10.12052/gdutxb.180030.
Ye Bin-bin, Liu Fu-chun. Failure Predictability of Stochastic Discrete Event Systems[J]. 2018, 35(6): 83-89. DOI: 10.12052/gdutxb.180030.
针对随机系统模型
提出一种随机离散事件系统的故障预测方法. 先对随机离散事件系统的故障可预测性进行形式化
再通过引入概率转移矩阵构建一个故障预测器自动机
得到关于随机离散事件系统的故障可预测性的充分必要条件. 由此
在故障预测器的基础上
通过计算其扩展马尔可夫矩阵
可判定随机离散事件系统是否具有故障可预测性
从而实现对故障事件在其发生之前的准确预测.
An approach for failure prediction for stochastic DESs modeled by stochastic finite state automata is proposed. Firstly
the notion of predictability of failure events of stochastic systems is formalized. Then a predictor automaton is constructed by introducing the probability transition matrix
and a necessary and sufficient condition of the predictability of stochastic systems is presented. Based on the fault predictor
a method for checking whether the considered stochastic DES has been equipped with the capability of failure prediction is developed by computing the extended Markov matrix
which results in the realization of accurate prediction of the failure events before occurring.
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