基于神经网络的滚动轴承故障快速检测方法

Fast Detection Method of Rrolling Bearing Faults Based on BP Neural Network

为了实现滚动轴承故障的快速检测,提出了一种基于神经网络和轴承振动信号时域指标的滚动轴承故障检测方法。采用振动信号的偏态、峭度、峰值和裕度作为BP神经网络的输入,用BP算法对网络进行了训练。实验结果表明,利用该方法可以有效实现滚动轴承故障的快速检测。

A method of detection about rolling bearing faults based on BP neural network and time domain features of vibration signal is proposed to realize fast fault detection.The input vector of the BP neural network are skewness, kurtosis, crest and margin.The network is trained with BP algorithm.Experimental results show that with this method fast detection of rolling bearing faults can be realized effectively.