【摘要】 为了解决最佳小波基函数选择的问题,采用第2代小波变换的方法构造小波,从振动信号中提取机电设备故障信息.第2代小波变换与经典小波变换不同,它不依赖Fourier变换,所有的运算在时域上进行,通过设计预测算子和提升算子可以构造具有某种特性的小波.针对机电设备的状态监测和故障诊断,阐述了一种离线设计预测算子和提升算子的方法,通过求解线性方程组确定预测系数和提升系数,并在此基础上构造基于插值细分方法的第2代小波变换算法.在某炼油厂机组的状态监测和故障诊断中,采用该算法有效地提取了轴系不对中的故障信息.更多还原

【Abstract】 In order to fix the problem of selecting optimum wavelet basis,the second generation wavelet transform (SGWT) is employed to construct wavelet for extracting the fault information of mechanical equipment from vibration signal. SGWT is different from the classical wavelet transform:not relying on Fourier transform (FT),doing all calculation on timedomain, and constructing special property wavelet by designing predictor and updater. A design method of predictor and updater is described for mechanical equipment monitoring and fault diagnosis.Coefficients of predicting and updating are gained by solving linear equation sets, and then algorithm based on interpolating subdivision method is found by using these coefficients. The fault information of shafting misalingnment is efficiently extracted by applying the algorithm in a refinery.更多还原