摘要
据统计,旋转机械的故障,30%是由滚动轴承故障引起的。因此,滚动轴承的故障诊断方法的研究得到各国专业技术人员的重视。对此,本文提出了一种新的关于滚动轴承故障的BP网络诊断方法,即通过建立相应的BP网络模型,并用BP算法对该网络进行训练,利用神经网络的智能性来判断轴承所属的故障类型。仿真结果表明,该方法实用有效。
A new BP network-based fault diagnosis method of ball bearing is presented. According to statistical, about 30% fault in rotating machinery is resulted from ball bearing fault. By established BP network model,and then train the network with BP algorithm.The pattern of ball bearing failure can be identified with the intellectual ability of BP neural network. The simulation result shows that the method presented in this paper is practical and effective.
出处
《新技术新工艺》
2007年第12期30-32,共3页
New Technology & New Process
