摘要
结合专家系统与模糊神经网络两种人工智能技术，通过对汽车发动机废气中ＨＣ、ＣＯ、ＣＯ２和Ｏ２含量的分析进行故障推理和诊断。专家系统与神经网络主要采用串型连接，由神经网络模块进行故障分类，再经专家系统给出解释并进一步推理，得到具体的诊断结果，从而实现发动机常见故障的快速、准确和智能化的诊断。
Combining fuzzy neural network (FNN) with expert system (ES), this paper used waste gas (HC, CO, CO 2, O 2) emitted by an gasoline engine to analyze and diagnose some typical faults of the engine. FNN module and ES module were connected generally in sequence. First, the classification to some faults relevant with waste gas was performed by FNN module. Then the explanations and the diagnostic results were given by ES module. So the fast, accurate and intelligent diagnosis was finished by this method. The function of self learning was realized by neural network module. A new way to diagnose the faults of an engine is provided by this paper.
出处
《农业机械学报》
EI
CAS
CSCD
北大核心
1998年第3期104-107,共4页
Transactions of the Chinese Society for Agricultural Machinery
基金
浙江省科委资助
关键词
神经网络
故障诊断
专家系统
发动机
汽车
Neural network, Gasoline engine, Waste gas, Fault diagnosis, Expert system
