贝叶斯网络在电子系统故障诊断中的应用研究

Study on fault diagnosis of electronic system using Bayesian network

电子系统大多结构复杂,各组成模块存在错综复杂、相互影响的关系,另外测点较少且测点数据常常是不完备的。针对此类情况,以某电源系统为研究对象,提出了基于贝叶斯网络的电子系统故障诊断方法。首先依据系统的结构获得其因果图,并对各测点信号进行离散化处理;其次建立用于故障诊断的贝叶斯网络模型,并且根据历史数据完成该网络的参数学习,最后利用获得的事实来实现故障的诊断。仿真结果验证了该方法的有效性,为电子系统的故障诊断提出了一种新的思路。

Electronic systems often own complex structures,and their sub-modules are interactional and anfractuous.Furthermore number of testing nodes is usually less and the testing data are incomplete.Aiming at these circumstances,the paper presents a new fault diagnosis approach based on Bayesian network for an electronic power.Firstly based on the original structure of elec- tronic power,authors gain cause-result graph and discretize all testing signals;then a Bayesian network is built for fault diagnosis and its parameters are studied through historical data;finally the Bayesian network is applied to diagnose true fault by using the actual data.Simulation experiments verify the effectiveness of the proposed approach,which provides a new way for fault diagnosis of electronic systems.