Adaptive Mask Signal-Based Local Characteristic-Scale Decomposition and Its Application
ZHENG Jin-de1, PAN Hai-yang1, TONG Jin-yu1, LIU Qing-yun1, DING Ke-qin2
1. School of Mechanical Engineering, Anhui University of Technology, Maanshan, Anhui 243032, China;
2. China Special Equipment Inspection and Research Institute, Beijing 100029, China
Abstract：Local characteristic-scale decomposition (LCD) is an adaptive signal decomposition method proposed to overcome the shortcomings of mean curve construction in empirical mode decomposition (EMD) and has been applied to mechanical fault diagnosis.However,LCD also has the mode mixing problem that exists in EMD.Based on the construction of masking signal with uniform phase difference,the adaptive mask signal ensemble local characteristic-scale decomposition (AMSELCD) is proposed in this paper to adaptively decompose a complex signal into several intrinsic mode functions and a residue,which can effectively alleviate the mode mixing phenomenon of LCD.AMSELCD is compared with various existing methods for restraining mode mixing through simulation signal analysis and the results show the effectiveness and superiority of the proposed method.Finally,aiming at the modulation characteristics of fault signals of rolling bearing and rotor rubbing,the proposed AMSELCD method is applied to the fault diagnosis of rotor rubbing and rolling bearing,and the experimental comparison analysis results further verify the effectiveness and superiority of AMSELCD.
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2020, Vol. 48 
