《基于谐波小波滤波的旋转机械故障诊断新方法》

针对旋转机械非平稳信号的特点，提出采用谐波小波滤波对现场采集的振动信号进行故障诊断的新方法。该方法基于谐波小波良好的盒形频谱特性，将特定频率段的成分与信号的其它频率成分既不交叠又不遗漏地分解到相互独立的频带上，再进行重构就可将特定频率成分提取出来。仿真计算及实例验证表明，谐波小波滤波方法具有良好的滤波效果，能将有用频率成分提取出来，为初步故障诊断提供依据。该方法具有算法简单，运算速度快的特点。

New Method for Fault Diagnosis of Rotating Machines Based on Harmonic Wavelet Filtering

A new method of fault diagnosis of in-situ sampled vibration signals is introduced for the non-stationery signals of rotating machines by using the harmonic wavelet filtering. Based on the nice box-shaped characteristic of spectrum of harmonic wavelet, the components in prescribed frequency region and other frequency components are decomposed to independent frequency bands without any overlapping or leaking. Then the frequency components in the prescribed region can be extracted by data reconstruction. Simulation results and practical examples show that this method has good filtering effect. It can extract the valuable frequency components for elementary fault diagnosis. This method has the merits of simple algorithm and computer-time saving.