基于小波分析的低速重载轴承故障诊断

Fault Diagnosis Based on Wavelet Analysis for Low-Speed Heavy-Duty Roller Bearing

从工程应用的角度研究了小波分析的信噪分离技术在低速重载轴承故障诊断中的应用·利用小波分解的多层次多频带特性和小波重构技术,建立了一种简单、精确和实用的低速重载轴承故障小波分析诊断方法·利用这一技术,诊断出其他方法无法诊断的低速重载轴承滚动体和内、外圈发生碰磨故障,检修拆卸时发现,上排滚动体有三个损坏,滚道出现磨损,验证了上述分析的正确性,成功地诊断出了具有低频特征的钢包回转台重载轴承碰磨故障·说明了小波分析用于提取弱信号,即信噪分离的有效性,这种方法可以弥补频谱分析法的不足·

In view of engineering applications, the separation of signal from noise by wavelet analysis is studied for the fault diagnosis system of low-speed heavy-duty roller bearings. By virtue of the features of multi-level and multi-frequency band of wavelet decomposition and wavelet restructuring technique, a simple, accurate and practical fault diagnosis method is developed. The new method is available to find out some troubles, which cannot be found by other ways, such as the impact/wear between rollers, and inner and/or outer race. Its advantage and availability have been proved by actual disassembling of a low-speed high-duty bearing used for a ladle turntable, during which three damaged bearing rollers were found in outer ring with the raceway worn out. An impact/wear fault characterized by low frequency was thus diagnosed successfully. The result indicated that the wavelet analysis can extract effectively weak signals or separate them from noise and that it can make up for the deficiency of frequency spectrum analysis.