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author:

Wang, X. (Wang, X..) [1] | Zheng, J. (Zheng, J..) [2] | Zhang, J. (Zhang, J..) [3]

Indexed by:

Scopus

Abstract:

As the prerequisite for obtaining the optimal demodulation frequency band (ODFB), the frequency band division model must be delicately constructed. The division models in existing methods of obtaining ODFB are vulnerable to the background noise and irrelevant components, which will cause an unsuitable demodulation frequency band. To improve the performance of frequency band division model, this paper proposes a fault diagnosis method called power spectrum screening combination-gram (Psscgram). Firstly, a frequency band screening combination model based on the auto-regressive (AR) power spectrum is established to obtain the frequency band group of vibration signal. Secondly, the negative entropy (NE) is used to quantify the fault characteristics of the frequency band group. The frequency band with the largest NE value is extracted from the frequency band group, whose characteristic frequency is calculated via envelope spectrum. Finally, the robustness and the anti-interference of the proposed method is verified by simulated signals with different signal-to-noise ratio. Moreover, the ODFB extraction ability of the proposed method is proved by the analyses of three sets of bearing experimental signals. © 2022 Elsevier Ltd

Keyword:

AR power spectrum; Fault diagnosis; Frequency band division; Negative entropy; Optimal demodulation frequency band

Community:

  • [ 1 ] [Wang, X.]School of Mechanical Engineering and Automation, Fuzhou University, Fuzhou, 350116, China
  • [ 2 ] [Zheng, J.]School of Mechanical Engineering, Anhui University of Technology, Maanshan, 243032, China
  • [ 3 ] [Zhang, J.]School of Mechanical Engineering and Automation, Fuzhou University, Fuzhou, 350116, China

Reprint 's Address:

  • [Zhang, J.]School of Mechanical Engineering and Automation, China

Email:

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Source :

Mechanical Systems and Signal Processing

ISSN: 0888-3270

Year: 2022

Volume: 174

8 . 4

JCR@2022

7 . 9 0 0

JCR@2023

ESI HC Threshold:66

JCR Journal Grade:1

CAS Journal Grade:1

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count: 13

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 0

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