动态辨识框架下条件证据更新的故障检测方法  

Fault detection and identification approach by using conditional probability update in dynamic frame of discernment

作　　者：吴祎[1] 周强[1] 吴文军 吴迪[3] 胡胜[4] 

机构地区：[1]陕西科技大学电气与信息工程学院,西安710021 [2]陕西延长石油安源化工有限公司,陕西榆林719319 [3]西安理工大学理学院,西安710054 [4]西安交通大学机械工程学院,西安710049

出　　处：《计算机应用研究》2015年第8期2370-2373,共4页Application Research of Computers

基　　金：陕西省科技统筹创新工程计划项目(2012KTCQ01-19);陕西省科技攻关项目(2011K06-06);西安市未央区科技计划项目(201304)

摘　　要：在分布式传感器网络中,各个子网往往具有不同的辨识框架,此时经典的证据理论无法处理。针对这一问题,提出一种动态辨识框下的证据融合理论和条件更新理论的故障检测方法。首先获取最新的观测证据,提出采用模糊隶属度函数作为信任转换的桥梁,完成动态辨识框架下的信任测度;然后利用新来证据的信任测度对已有的证据进行更新,以此进行各个观测区域的故障检测;最后通过构造两个传感器子网S1和S2的分布式检测与识别系统对所提方法进行验证,结果显示该方法在处理动态辨识框架和故障检测方面的有效性。In the distributed sensor networks, individual sensors always have different FoDs, this lead the classical evidence theory can not be used. In view of this problem,this paper proposed a fault detection algorithm in the dynamic FoD using conditional probabilistic approach. Firstly, it derived the new observed evidence and its belief measure. Secondly, it used the conditional probability of new evidence to update the old belief measure. Thus, it could use the new updated belief measure to detect fault. Finally,it constructed a two-sensors-subnets model to verify this approach. Simulation results demonstrate that the proposed method shows an effective ability in dealing with the dynamic FoD and fault detection.

关 键 词：故障检测 动态辨识框架 条件概率更新 置信测度 

分 类 号：TP277[自动化与计算机技术—检测技术与自动化装置]