Fast bearing fault diagnosis of rolling element using Lévy Moth-Flame optimization algorithm and Naive Bayes

• Autorzy: Sun Shuang , Przystupa Krzysztof , Wei Ming , Yu Han , Ye Zhiwei , Kochan Orest

Identyfikatory

DOI

10.17531/ein.2020.4.17

• Języki publikacji: EN

Abstrakty

EN

Fault diagnosis is part of the maintenance system, which can reduce maintenance costs, increase productivity, and ensure the reliability of the machine system. In the fault diagnosis system, the analysis and extraction of fault signal characteristics are very important, which directly affects the accuracy of fault diagnosis. In the paper, a fast bearing fault diagnosis method based on the ensemble empirical mode decomposition (EEMD), the moth-flame optimization algorithm based on Lévy flight (LMFO) and the naive Bayes (NB) is proposed, which combines traditional pattern recognition methods meta-heuristic search can overcome the difficulty of selecting classifier parameters while solving small sample classification under reasonable time cost. The article uses a typical rolling bearing system to test the actual performance of the method. Meanwhile, in comparison with the known algorithms and methods was also displayed in detail. The results manifest the efficiency and accuracy of signal sparse representation and fault type classification has been enhanced.

Słowa kluczowe

EN

malfunction diagnostics; naive Bayes; moth-flame optimization algorithm; ensemble empirical mode decomposition

• Wydawca: Polskie Naukowo-Techniczne Towarzystwo Eksploatacyjne
• Czasopismo: Eksploatacja i Niezawodność
• Rocznik: 2020
• Tom: Vol. 22, no. 4
• Strony: 730--740
• Opis fizyczny: Bibliogr. 50 poz., rys., tab.

Twórcy

autor

Sun Shuang

• School of Computer Science, Hubei University of Technology, Wuhan, Hubei, 430068, PR China

autor

Przystupa Krzysztof

• Lublin University of Technology, ul. Nadbystrzycka 36, 20-618, Lublin, Poland

autor

Wei Ming

• Wuhan Fiberhome Technical Services Co., Ltd., Wuhan FiberHome Telecommunication Technologies Co., Ltd., Wuhan, Hubei, 430074, PR China

autor

Yu Han

• Wuhan Fiberhome Technical Services Co., Ltd., Wuhan FiberHome Telecommunication Technologies Co., Ltd., Wuhan, Hubei, 430074, PR China

autor

Ye Zhiwei

• School of Computer Science, Hubei University of Technology, Wuhan, Hubei, 430068, PR China

autor

Kochan Orest

• Lviv Polytechnic National University, Karpinskoho str. 1, Lviv, Ukraine

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Uwagi

Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2021).