基于神经网络推理的压缩机故障诊断专家系统

Expert System Based on Neural Network for Compressor Fault Diagnosis

设计了一种基于神经网络推理的汽车空调压缩机故障诊断专家系统。此系统将传统专家系统与神经网络技术科学地加以综合,弥补了传统专家系统的诸多缺陷。专家系统的知识库由两部分组成,即浅层知识库和深层知识库。推理过程由神经网络完成,并带有解释说明模块,主要说明诊断结果的判定依据。实践证明,这种方法能较好地解决传统专家系统存在的问题,提高系统的诊断速度和准确率。

Neural network system is applied to an expert system for the compressor fault diagnosis of vehicle＇ s air conditioning. The drawbacks in traditional expert system could be overcome by integrating expert system with neural network. The knowledge data of the system is made up of a simple one and deep one. The inferring course is finished by the neural network, and the results are interpreted by an explanation module. The traditional expert system would be improved by this method, and the rapidity and veracity be advanced greatly.