基于BP神经网络的煤矿机械故障诊断专家系统的开发

Development of Expert System for Mechanical Fault Diagnosis Based on BP Neural Network

构建了基于BP神经网络的煤矿机械故障诊断专家系统的结构,以常见的20种故障诊断为研究对象,知识库、规则库和BP神经网络相结合进行推理,优化专家系统,提高了专家系统的响应速度和准确性。采用DreamWeaver、MatLab和.NET技术实现了专家系统的开发。并以一种煤矿机械为例,验证了整个系统的有效性和实用性。

This paper designs a kind of expert system for mechanical fault diagnosis based on BP neural network.Twenty kinds of mechanical faults as research objects are taken.The expert system consists of knowledge database,rules inference and BP neural network.It improves system real-time ability of expert system and has higher diagnostic accuracy than traditional expert system.The system is implemented by dreamweaver language,MatLab and.NET programming technology.The experiment results of mechanical shows that expert system is feasible and useful for mechanical fault diagnosis.