Application of Second Generation Wavelet Transform to Fault Diagnosis of Rotating Machinery
Duan Chen-dong · Mechanical Science and Technology · 2004
Different wave features for different machinery faults are reflected in vibration signal, but an improper wavelet basis function for vibration signal can blur the informationof fault features and make diagnosis difficult. In the second generation wavelet transform(SGWT), wavelet basis function with some special characteristiccan be obtained by means of designing prediction and update coefficients. In this paper, the principle of SGWT is described, and the relationship among the prediction coefficients, the update coefficients and the coefficients of low-pass and high-pass filter is discussed. According to the feature of a given signal, a biorthogonal wavelet is constructed which is based on interpolating subdivision scheme, good results are obtained for shaftingfault diagnosis in rotatingmachinery.