基于PCA和BP神经网络的故障诊断仿真系统

Fault diagnosis simulation system based on PCA and BP neural network

随着人们越来越重视机械安全运行,人们对机械故障诊断关注程度也越来越高。为了提高机械故障诊断的效率和准确率,提出一种融合PCA和BP神经网络的故障诊断方法。利用PCA对故障诊断特征进行降维,再利用BP神经网络进行故障诊断。采用Matlab软件实现了基于PCA和BP神经网络的故障诊断仿真系统。运行结果表明,该系统界面友好、使用简便,对故障诊断的准确率较高等优点。

As people pay more and more attention to the operation of the mechanical safety, people pay more attention to the mechanical fault diagnosis. In order to improve the efficiency and accuracy of mechanical fault diagnosis, a new fault diagnosis method base on PCA and BP neural networks is proposed. The proposed method Used PCA to reduce the fault diagnosis feature, and then used BP neural network for fault diagnosis. The fault diagnosis system based on PCA and BP neural network was implemented by using MATLAB software. The results showed that the system has the advantages of friendly interface, easy use, and higher accuracy for fault diagnosis.