基于贝叶斯网络的故障诊断专家系统

现代系统设备的日趋复杂化和自动化,对故障诊断技术提出了更高的要求;随着人工智能技术的发展,故障诊断技术向智能化方向发展,如何将人工智能技术应用到故障诊断中去,是当前研究的重点;为了实现对汽车发动机已发故障和潜在故障的快速高效诊断,根据发动机故障知识结构特性,将贝叶斯网络因果有向图的故障知识表示方法引入到专家系统中,并采用可在线监控和离线诊断的推理机制,在G2平台下实现了汽车发动机故障诊断专家系统,系统应用的效果表明了该方法的可行性.

Fault Diagnosis Expert System Based on Bayesian Network

Nowadays, the scale of fault diagnosis technology is increasing greatly, along with the industry equipment is being more complex and automatic. With the development of artificial intelligent technology, the fault diagnosis technology is developing forward to intelligent direction. Using the artificial intelligent technology in fault diagnosis becomes more and more important. In order to realize quick and efficient diagnosis of the already occurred and potential fault , of the automobile engine, according to the fault knowledge framework trait of the engine, combining the Bayesian network directed graph expression method of the fault knowledge with the expert system technology, realize the automobile engine fault diagnosis expert system based on G2, the running result of the system has proved the feasibility of the fault diagnosis method.