基于BP神经网络算法的柔性制造系统故障诊断

在分析和研究人工神经网络的前提下,将BP神经网络作为故障诊断的技术指导,以本校柔性制造系统中的电源管理模块故障诊断为实例,构建其智能诊断系统。通过3层BP神经网络,将输入端传感器收集到的特征量经中间层信息处理和输出层的进一步处理,使其达到网络性能目标,最终得到诊断数据。比较诊断数据与标准故障集的类型,获得准确的结果。结果表明:利用BP神经网络可以构建一个智能诊断系统,实现故障准确快速自动识别。

Fault Diagnosis of Flexible Manufacturing System Based on BP Neural Network Algorithm

On the premise that the artificial neural network have been analyzed and studied,the BP neural network is taken as the technical guidance of fault diagnosis,and the fault diagnosis of the power management module in the flexible manufacturing system of our college is exampled to construct its intelligent diagnosis system.By means of a three-layer BP neural network,the characteristic quantity collected by the input sensor is processed by the middle layer and further processed by the output layer to achieve the network performance target and finally get the diagnostic data.The diagnostic data are compared with the types in the standard fault set to obtain accurate results.Experimental results show that BP neural network can be used to construct an intelligent diagnosis system and realize accurate,fast and automatic fault identification.