小波分析在滚动轴承故障诊断中的应用

The Application of Wavelet Analysis to the Rolling Bearing Failure Diagnosis

滚动轴承是机械系统中非常关键的部件,它的运行好坏直接关系到整个机械系统的性能优劣,因此滚动轴承的故障诊断研究是非常具有实际意义的。本文对轴承早期损伤引起的故障信号进行了分析,通过比较频谱分析和小波分析的特点,采用小波分析技术对检测的信号进行处理,利用小波变换的分解和重构算法,对具有故障特征的信号进行重构,再通过希尔波特变换进行解调和细化频谱分析,有效地提取出噪声掩盖下的滚动轴承故障特征信号,从而实现对滚动轴承的故障诊断。

A rolling bearing is a crucial component of the mechanical system. Whether it works well or not is directly related to the performance of the whole mechanical system. Therefore, the study on the fault detection of the rolling beating is very practical. Initial fault feature of rolling bearing is analyzed, the characteristic of spectrum analysis and wavelet analysis are compared, a method of wavelet decomposing and signal reconstruction is proposed to extract shock signal from vibration signal of rolling bearing, which is concealed by noise. The fault of rolling beating component is diagnosed by extracting fault feature from rolling beating.