Separation and extraction of electromechanical equipment compound faults using lifting multiwavelets

Compound faults of electromechanical equipment always occur simultaneously and in a cascading way. Based on signal matching, multiwavelets with good properties have several scaling functions and wavelet functions. Therefore, they could better match various features of compound faults, and separate and extract compound features at one time. The construction of multiwavelets based on lift frame does not depend on the Fourier transform, and the algorithm is simple and fast. Hence, multiwavelet transforms via lift frame like the second wavelet transforms are studied. Based on Hermite spline interpolation, the new multiwavelets with short support, biorthogonality, symmetry and fourth approximate order are designed, and the corresponding preprocessing algorithm is given. Aimed at the problem of compound faults, posttreatment procedure is modified and decoupled features are clearly presented in different channels of analysis results of multiwavelets. The proposed method is applied to compound faults diagnosis for bearing test bench and traveling unit of electric locomotive. The results show that this method can effectively separate and extract the features of bearing inner-race fault and shaft anomalous bending, and successfully decouple the bearing outer-race defect and roller defect of the locomotive.