摘要
滚动轴承振动信号被分析和处理后,提取出能够反映滚动轴承故障的特征参数,经归一化处理作为BP神经网络的输入,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的好坏。仿真结果表明,该方法实用有效。
After the vibration signals of the rolling bearing are analysed and processed, the feature parameters which represent operating state of the rolling bearing are extracted, and then are inputted to the BP neural network to train the network with BP algorithm by processing of normalization. Good roiling bearings and bad rolling bearings 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
《拖拉机与农用运输车》
北大核心
2008年第6期114-115,118,共3页
Tractor & Farm Transporter
关键词
滚动轴承
振动信号
特征参数
神经网络
Rolling bearing
Vibration signals
Feature parameters
Neural network
