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Analysis of Weak Fault in Hydraulic System Based on Multi-scale Permutation Entropy of Fault-Sensitive Intrinsic Mode Function and Deep Belief Network

1
Urumqi Campus, Engineering University of PAP, Urumqi 830001, China
2
College of Field Engineering, Army Engineering University of PLA, Nanjing 210007, China
3
Second Institute of Engineering Research and Design, Southern Theatre Command, Kunming 650222, China
*
Authors to whom correspondence should be addressed.
Entropy 2019, 21(4), 425; https://doi.org/10.3390/e21040425
Received: 15 March 2019 / Revised: 11 April 2019 / Accepted: 17 April 2019 / Published: 22 April 2019
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Abstract

With the aim of automatic recognition of weak faults in hydraulic systems, this paper proposes an identification method based on multi-scale permutation entropy feature extraction of fault-sensitive intrinsic mode function (IMF) and deep belief network (DBN). In this method, the leakage fault signal is first decomposed by empirical mode decomposition (EMD), and fault-sensitive IMF components are screened by adopting the correlation analysis method. The multi-scale entropy feature of each screened IMF is then extracted and features closely related to the weak fault information are then obtained. Finally, DBN is used for identification of fault diagnosis. Experimental results prove that this identification method has an ideal recognition effect. It can accurately judge whether there is a leakage fault, determine the degree of severity of the fault, and can diagnose and analyze hydraulic weak faults in general. View Full-Text
Keywords: hydraulic system; leakage fault; multi-scale permutation entropy; fault-sensitive IMF; deep belief network hydraulic system; leakage fault; multi-scale permutation entropy; fault-sensitive IMF; deep belief network
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Huang, J.; Wang, X.; Wang, D.; Wang, Z.; Hua, X. Analysis of Weak Fault in Hydraulic System Based on Multi-scale Permutation Entropy of Fault-Sensitive Intrinsic Mode Function and Deep Belief Network. Entropy 2019, 21, 425.

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