基于ICA和小波变换的滚动轴承故障诊断方法研究

提出了结合独立分量分析(ICA)和小波变换进行滚动轴承故障诊断的方法。在设计的系统平台上,首先对冲击脉冲信号进行预处理,使信号较好地满足独立分量分析的前提条件。然后,应用独立分量快速算法分离故障轴承的冲击脉冲信号,通过小波快速算法完成信号重构,实现滚动轴承故障的识别。实验结果表明,利用独立分量分析方法提取的故障状态特征向量与小波快速算法相结合可以有效、准确地识别滚动轴承的故障信号。

Research on Fault Diagnosis of Rolling Element Bearings Based on ICA and Wavelet Transform

A method of Fault diagnosis of rolling element bearings was proposed based on Independent component analysis （ICA） and wavelet transform. With the designed system platform, shock pulse signal was pretreated to meet the requisite of ICA. Then the fast algorithm for independent component is applied to separate the shock pulse signal of fault bearings. The fault identification of the rolling bearings wavelet fast algorithm. The experimental results show transform can effectively and accurately identify the fault is completed attributing signal reconstruction with Mallat the fault diagnosis method based on ICA and wavelet signals of rolling bearings