摘要
汽油发动机出现故障的机率较高 ,一般占整车故障的 40 %左右 .研究汽油发动机故障诊断专家系统 ,可以及时准确地对发动机技术状况做出判断 ,指导调整其技术状态 ,这无疑增加了汽车使用的可靠性、经济性和安全性 .人工神经网络是基于数值计算的知识处理系统 .针对传统专家系统在处理故障诊断中的不足 ,提出了将人工神经网络技术与专家系统融合的模型 ,并将此模型应用到汽油机故障诊断中 .
As a very complex system, gasoline engine causes 40% of all the automobile faults. By means of fault diagnosis expert system of gasoline engine, users can analyze and diagnose the faults fast and easily. So it can decrease the blindness of repair, improve the repair quality, shorten the repair time, and cut the repair cost. In the light of the shortcomings of traditional expert system on fault diagnosis, a model for fault diagnosis expert system based on artificial neural network is proposed. This model is applied to diagnosis of gasoline engines.
出处
《科技通报》
2000年第2期93-96,共4页
Bulletin of Science and Technology
基金
浙江省科委资助项目!(96110 10 4 8)
关键词
神经网络
故障诊断
专家系统
汽车
汽油发动机
artificial neural network
fault diagnosis
expert system
gasoline engine
