摘要
首先对滚动轴承振动信号进行前期处理(包括粗大误差处理和通过小波变换对信号消噪),然后提取出能反应轴承运行状态的特征向量作为RBF网络的输入量,采用RBF网络对滚动轴承进行了故障诊断.仿真结果表明,该方法实用有效.
Through the pre-treatment to the vibration signals of the rolling bearing（including gross error handling and wavelet transform denoising）, then extracting eigenvectors which represent operating state of the rolling bearing as the input of the RBF network, we can use RBF network for fault diagnosis. The simulation results show that, this method is effective.
出处
《陕西科技大学学报（自然科学版）》
2008年第2期90-92,96,共4页
Journal of Shaanxi University of Science & Technology
关键词
故障诊断
RBF网络
小波去噪
滚动轴承
fault diagnosis
RBF network
waveleic transform denoising
rolling bearing
