Application of Maximum Probability Approach to the Fault Diagnosis of a Servo System  

最大概率方法在伺服系统故障诊断上的应用(英文)

作　　者：马东升[1] 胡佑德[1] 戴凤智 

机构地区：[1]北京理工大学自动控制系,北京100081 [2]大分大学电气电子工程系,日本大分8701124

出　　处：《Journal of Beijing Institute of Technology》2002年第1期29-32,共4页北京理工大学学报（英文版）

摘　　要：In an actual control system, it is often difficult to find out where the faults are if only based on the outside fault phenomena, acquired frequently from a fault system. So the fault diagnosis by outside fault phenomena is considered. Based on the theory of fuzzy recognition and fault diagnosis, this method only depends on experience and statistical data to set up fuzzy query relationship between the outside phenomena (fault characters) and the fault sources (fault patterns). From this relationship the most probable fault sources can be obtained, to attain the goal of quick diagnosis. Based on the above approach, the standard fuzzy relationship matrix is stored in the computer as a system database. And experiment data are given to show the fault diagnosis results. The important parameters can be on line sampled and analyzed, and when faults occur, faults can be found, the alarm is given and the controller output is regulated.为了解决实际控制系统中仅通过系统的故障现象难以确定系统故障元的难题 ,采用基于模糊识别和故障诊断理论的最大概率法 ,该方法仅仅依靠经验和统计数据 ,在外部故障现象和系统故障元之间建立模糊查询关系 ,从这一关系中可以获得最大故障概率点 .将一个标准模糊关系矩阵作为数据库存储在计算机中 ,并给出了一个系统故障诊断的实验结果 .通过以上方法 ,只要对系统的重要参数进行在线采集和分析 ,当发生故障时 ,就可以给出可能的故障元的故障概率 。

关 键 词：maximum probability approach fault diagnosis fault tree servo system 

分 类 号：TP277[自动化与计算机技术—检测技术与自动化装置]