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Entropy 2019, 21(1), 18; https://doi.org/10.3390/e21010018

Gearbox Composite Fault Diagnosis Method Based on Minimum Entropy Deconvolution and Improved Dual-Tree Complex Wavelet Transform

1
School of Mechanical, Electronic and Information Engineering, China University of Mining and Technology (CUMT), Xueyuan Road, Beijing 100083, China
2
Shanxi Institute of Energy, Daxue Road, Jinzhong 030600, China
*
Author to whom correspondence should be addressed.
Received: 21 November 2018 / Revised: 16 December 2018 / Accepted: 16 December 2018 / Published: 26 December 2018
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Abstract

Dual-tree complex wavelet transform has been successfully applied to the composite diagnosis of a gearbox and has achieved good results. However, it has some fatal weaknesses, so this paper proposes an improved dual-tree complex wavelet transform (IDTCWT), and combines minimum entropy deconvolution (MED) to diagnose the composite fault of a gearbox. Firstly, the number of decomposition levels and the effective sub-bands of the DTCWT are adaptively determined according to the correlation coefficient matrix. Secondly, frequency mixing is removed by notch filter. Thirdly, each of the obtained sub-bands further reduces the noise by minimum entropy deconvolution. Then, the proposed method and the existing adaptive noise reduction methods, such as empirical mode decomposition (EMD), ensemble empirical mode decomposition (EEMD), and variational mode decomposition (VMD), are used to decompose the two sets of simulation signals in comparison, and the feasibility of the proposed method has been verified. Finally, the proposed method is applied to the compound fault vibration signal of a gearbox. The results show the proposed method successfully extracts the outer ring fault at a frequency of 160 Hz, the gearbox fault with a characteristic frequency of 360 Hz and its double frequency of 720 Hz, and that there is no mode mixing. The method proposed in this paper provides a new idea for the feature extraction of a gearbox compound fault. View Full-Text
Keywords: improved dual-tree complex wavelet transform; minimum entropy deconvolution; gearbox composite fault; frequency mixing improved dual-tree complex wavelet transform; minimum entropy deconvolution; gearbox composite fault; frequency mixing
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Zhang, Z.; Zhang, X.; Zhang, P.; Wu, F.; Li, X. Gearbox Composite Fault Diagnosis Method Based on Minimum Entropy Deconvolution and Improved Dual-Tree Complex Wavelet Transform. Entropy 2019, 21, 18.

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