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Acta Armamentarii ›› 2021, Vol. 42 ›› Issue (6): 1324-1330.doi: 10.3969/j.issn.1000-1093.2021.06.023

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Variational Nonlinear Chirp Mode Decomposition-synchroextracting Transform Method and Its Application in Fault Diagnosisof Rolling Bearing

LI Zhinong1,2, HU Zhifeng1, MAO Qinghua3, ZHANG Xuhui3, TAO Junyong2   

  1. (1.Key Laboratory of Nondestructive Testing of Ministry of Education, Nanchang Hangkong University, Nanchang 330063,Jiangxi, China;2.Laboratory of Science and Technology on Integrated Logistics Support, National University of Defense Technology, Changsha 410073, Hunan, China; 3.Shaanxi Key Laboratory of Mine Electromechanical Equipment Intelligent Monitoring, Xi'an University of Science and Technology, Xi'an 710054, Shaanxi, China)
  • Online:2021-07-19

Abstract: When the traditional synchroextracting transform (SET) method is used to process the multi-component non-stationary signals, the instantaneous frequency difference of adjacent components is greater than 2 times of the frequency support range of the window function. Otherwise the time-frequency result is prone to frequency aliasing. However, the actual signal often can not satisfy this condition. In additional, when traditional SET method is used to process complex signal with high noise, its time-frequency resolution is often not ideal. Based on this deficiency, the variational nonlinear chirp mode decomposition (VNCMD) is introduced into SET in this paper, and a fault diagnosis method of VNCMD-SET is proposed. In the proposed method, VNCMD is used to process non-stationary signals with close or even cross frequencies by combining demodulation and variational modal decomposition. The fault signal is decomposed and reconstructed by VNCMD, then the reconstructed signal is processed by SET. The proposed method was compared with the traditional SET method, and was verified through experiment. The simulated and experimental results show that the proposed VNCMD-SET method is superior to the traditional SET method and overcomes the deficiency in the traditional SET method; the proposed method can effectively extract the frequency characteristics of fault signal, suppresses the aliasing, and has a certain anti-noise performance.

Key words: faultdiagnosis, nonlinearfrequencymodulationmodedecomposition, synchroextractingtransform, rollingbearing

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