基于小波分析的转炉轴承在线振动故障诊断系统

Online Fault Diagnosis System Based on Wavelet Analysis for Converter Roller Bearing

利用计算机实时数据采集对攀枝花新钢钒炼钢厂4,5号提钒转炉轴承实施在线振动故障诊断监测。根据小波分析对提钒转炉轴承故障发生时其相应的部位将产生周期性的特征振动信号进行多层次多频带分解,分离特征频率与噪音的频率段,达到去除噪音的目的。信号重构后再进行频谱分析准确地判断出轴承发生故障的准确部位。

A real-time fault diagnosis system for converter roller bearing was constructed by wave analysis in New Steelworks of Panzhihua. The fault characteristic signal would be gathered when the fault occurred on roller bearing by the system. In order to separate signal from noise, wavelet analysis was applied to decomposes signal and noise on multi-level and multi-frequency. Then, system could diagnosis where the fault occurs on converter roller bearing when spectrum analysis is carried through on reconstructed signal.