谐波小波在旋转机械故障诊断中的应用

Application of harmonic wavelet in rotating machinery fault diagnosis

为了对具有非平稳信号的旋转机械的轴心轨迹形状进行识别,提出一种基于谐波小波滤波提纯的方法.谐波小波具有明确的函数表达式,算法实现简单,具有良好的"盒形"频谱特性,能将信号不交叠且不遗漏地分解到相互独立的空间,便于信号特征的提取.采用谐波小波进行滤波提纯,可以将故障信息从原始轴心轨迹信号中分离出来,从而获得轴心轨迹的形状,为旋转机械的故障诊断提供了依据.大量仿真试验表明,该滤波提纯方法简单,具有较强的实用价值.

In order to identify the shaft orbit of rotating machinery with a non stationary signal,a filter purification method based on harmonic wavelet is developed.Harmonic wavelet has clear function expressions and simple algorithms.In addition,it owns a good box shape spectrum characteristic,and can decompose signal into independent space in a neither overlapping nor missing manner,which is convenient for extracting signal features.Harmonic wavelet filter purification can separate fault information from the original signals of shaft orbit.Therefore,the shape of the shaft orbit can be obtained,which provides the basis for fault diagnosis on rotating machinery.The simulation experiments show that the filter purification method is simple,and has a practical value.