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Compound Fault Diagnosis of Rolling Bearing Based on Singular Negentropy Difference Spectrum and Integrated Fast Spectral Correlation

Department of Mechanical Engineering, North China Electric Power University, Baoding 071000, China
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Entropy 2020, 22(3), 367; https://doi.org/10.3390/e22030367
Received: 21 February 2020 / Revised: 18 March 2020 / Accepted: 21 March 2020 / Published: 23 March 2020
(This article belongs to the Special Issue Entropy-Based Algorithms for Signal Processing)
Compound fault diagnosis is challenging due to the complexity, diversity and non-stationary characteristics of mechanical complex faults. In this paper, a novel compound fault separation method based on singular negentropy difference spectrum (SNDS) and integrated fast spectral correlation (IFSC) is proposed. Firstly, the original signal was de-noised by SNDS which improved the noise reduction effect of singular difference spectrum by introducing negative entropy. Secondly, the de-noised signal was analyzed by fast spectral correlation. Finally, IFSC took the fourth-order energy as the index to determine the resonance band and separate the fault features of different single fault. The proposed method is applied to analyze the simulated compound signals and the experimental vibration signals, the results show that the proposed method has excellent performance in the separation of rolling bearing composite faults. View Full-Text
Keywords: singular value decomposition; singular negentropy difference spectrum; integrated fast spectral correlation; rolling bearing; composite fault; fault separation singular value decomposition; singular negentropy difference spectrum; integrated fast spectral correlation; rolling bearing; composite fault; fault separation
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Tang, G.; Tian, T. Compound Fault Diagnosis of Rolling Bearing Based on Singular Negentropy Difference Spectrum and Integrated Fast Spectral Correlation. Entropy 2020, 22, 367.

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