A Comparative Study on Multiwavelet Construction Methods and Customized Multiwavelet Library for Mechanical Fault Detection

Inner product transform principle reveals that the basis functions most relevant or similar to the fault features are pivotal to the meaningful fault detection. Customized multiwavelet methods and practices have continued to improve over the recent years, focused on two-scale similarity transform (TST), lifting transform (LT), and lifting scheme (LS). Due to the respective advantages and disadvantages, a comparative study on the multiwavelet construction methods by TST, symmetric and dissymmetric LT, and LS is discussed in the paper, covering the differences of construction theories, the synthetic analyses of construction strategies, and the comparison of waveform characteristics along with their applicable occasions. Comprehensively utilizing the capabilities of the construction methods, a novel customized multiwavelet library is established for the accurate fault detection. The proposed method is applied to incipient fault detection of rolling bearing for electric locomotive to verify the effectiveness and feasibility.

[1]  M. SIAMJ.,et al.  RAISING MULTIWAVELET APPROXIMATION ORDER THROUGH LIFTING , 2001 .

[2]  Amir Averbuch,et al.  Lifting scheme for biorthogonal multiwavelets originated from Hermite splines , 2002, IEEE Trans. Signal Process..

[3]  Yongsheng Gao,et al.  Recognition of driving postures by multiwavelet transform and multilayer perceptron classifier , 2012, Eng. Appl. Artif. Intell..

[4]  D. Hardin,et al.  Fractal Functions and Wavelet Expansions Based on Several Scaling Functions , 1994 .

[5]  W. Dahmen,et al.  Biorthogonal Multiwavelets on the Interval: Cubic Hermite Splines , 2000 .

[6]  Yanyang Zi,et al.  Multiwavelet construction via an adaptive symmetric lifting scheme and its applications for rotating machinery fault diagnosis , 2009 .

[7]  Zhengjia He,et al.  An adaptive inverse iteration algorithm using interpolating multiwavelets for structural eigenvalue problems , 2011 .

[8]  Emanuele Trucco,et al.  Retinal vessel segmentation using multiwavelet kernels and multiscale hierarchical decomposition , 2013, Pattern Recognit..

[9]  Hongkai Jiang,et al.  An improved EEMD with multiwavelet packet for rotating machinery multi-fault diagnosis , 2013 .

[10]  Yanyang Zi,et al.  Construction and selection of lifting-based multiwavelets for mechanical fault detection , 2013 .

[11]  Y. Zi,et al.  Adaptive multiwavelets via two-scale similarity transforms for rotating machinery fault diagnosis , 2009 .

[12]  Vasily Strela,et al.  Multiwavelets: Regularity, Orthogonality, and Symmetry via Two–Scale Similarity Transform , 1997 .

[13]  Amir Averbuch,et al.  Multiwavelet Frames in Signal Space Originated From Hermite Splines , 2007, IEEE Transactions on Signal Processing.

[14]  Jiawei Xiang,et al.  A Class of Wavelet-Based Rayleigh-Euler Beam Element for Analyzing Rotating Shafts , 2011 .

[15]  Yanyang Zi,et al.  The principle of second generation wavelet for milling cutter breakage detection , 2008 .

[16]  Y. Zi,et al.  Gear fault detection using customized multiwavelet lifting schemes , 2010 .

[17]  C. Fei,et al.  Wavelet Correlation Feature Scale Entropy and Fuzzy Support Vector Machine Approach for Aeroengine Whole-Body Vibration Fault Diagnosis , 2013 .