基于小波分析的轴承故障诊断研究

Research on Bearing Fault Diagnosis based on Wavelet

轴承故障诊断是大型矿山机械设备故障诊断的一个重要方面。基于轴承振动信号的非平稳特征及小波变换对非平稳信号分析的有效特性,在研究小波变换理论的基础上,提出了一种基于小波分析的轴承故障诊断方法。将振动信号进行小波分解与重构,然后对细节信号进行Hilbert包络检波和频谱分析,即可获取信号的特征频率。通过对球状点蚀故障诊断的实验仿真,验证了该方法有效可靠。

The diagnosis of bearing fault is an important aspect in the diagnosis of large - scale mining machinery equipment. On the basis of the theory of wavelet transform which is very effective for the analysis of non - stationary signals in the bearing vibration, a fault diagnosis technology have been proposed. The vibration signal is decomposed and reconstructed by using wavelet transform. Then the characteristic frequency of the signal can be got by using Hilber envelope detection processing and spectrum analysis. Through the ex- perimental simulation of spherical pitting failure verify that the method is effective and reliable.