Enhanced deep gated recurrent unit and complex wavelet packet energy moment entropy for early fault prognosis of bearing

Document identifier: oai:DiVA.org:ltu-76058
Access full text here:10.1016/j.knosys.2019.105022
Keyword: Engineering and Technology, Civil Engineering, Other Civil Engineering, Teknik och teknologier, Samhällsbyggnadsteknik, Annan samhällsbyggnadsteknik, Enhanced deep gated recurrent unit, Bearing, Early fault prognosis, Energy moment entropy, Modified training algorithm, Drift och underhållsteknik, Operation and Maintenance
Publication year: 2020
Abstract:

Early fault prognosis of bearing is a very meaningful yet challenging task to improve the security of rotating machinery. For this purpose, a novel method based on enhanced deep gated recurrent unit and complex wavelet packet energy moment entropy is proposed in this paper. First, complex wavelet packet energy moment entropy is defined as a new monitoring index to characterize bearing performance degradation. Second, deep gated recurrent unit network is constructed to capture the nonlinear mapping relationship hidden in the defined monitoring index. Finally, a modified training algorithm based on learning rate decay strategy is developed to enhance the prognosis capability of the constructed deep model. The proposed method is applied to analyze the simulated and experimental signals of bearing. The results demonstrate that the proposed method is more superior in sensibility and accuracy to the existing methods.

Authors

Shao Haidong

Luleå tekniska universitet; Drift, underhåll och akustik; State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body, Hunan University, Changsha, China. College of Mechanical and Vehicle Engineering, Hunan University, Changsha, China
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Cheng Junsheng

State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body, Hunan University, Changsha, China. College of Mechanical and Vehicle Engineering, Hunan University, Changsha, China
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Jiang Hongkai

School of Aeronautics, Northwestern Polytechnical University, Xi’an, China
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Yang Yu

State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body, Hunan University, Changsha, China. College of Mechanical and Vehicle Engineering, Hunan University, Changsha, China
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Wu Zhantao

State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body, Hunan University, Changsha, China. College of Mechanical and Vehicle Engineering, Hunan University, Changsha, China
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