Fault analysis and reliability evaluation for motorized spindle of cycloidal gear grinding machine based on multi-source bayes

• Autorzy: Wang Huiliang , Zhang Zhijie , Li Jie , Xin Wen , Han Chunyang

Identyfikatory

DOI

10.17531/ein/175010

• Języki publikacji: EN

Abstrakty

EN

A Monte Carlo simulation method based on multisource bayes is proposed to improve the reliability of motorized spindles in cycloid gear grinding machines and reduce their failure rate. Based on field investigations and motorized spindle maintenance records, a fault tree model of a motorized spindle was established, and the fuzzy importance of each bottom event was evaluated. The fault tree of a motorized spindle was used as a Monte Carlo reliability simulation model, and its importance was used as the input parameter for the simulation. The reliability evaluation index of the motorized spindle was obtained at different simulation times. The feasibility and accuracy of the reliability simulation were verified by comparing the importance and simulation importance. A vibration test was designed for bearing faults with high importance, and fault extraction was performed by combining the wavelet packet transform and empirical mode decomposition. This method can also be used to simulate and analyze the reliability of other equipment or machine tools.

Słowa kluczowe

EN

motorized spindle; cycloidal gear grinding machine; Monte Carlo simulation; reliability evaluation; multi-source bayes

• Wydawca: Polskie Naukowo-Techniczne Towarzystwo Eksploatacyjne
• Czasopismo: Eksploatacja i Niezawodność
• Rocznik: 2024
• Tom: Vol. 26, no. 1
• Strony: art. no. 175010
• Opis fizyczny: Bibliogr. 32 poz., rys., tab., wykr.

Twórcy

autor

Wang Huiliang

• School of Mechatronics Engineering, Henan University of Science and Technology, Luoyang, Henan Province, China
• State Key Laboratory of Intelligent Mining Heavy Equipment, Luoyang, Henan Province, China

• https://orcid.org/0000-0001-8456-4345

autor

Zhang Zhijie

• School of Mechatronics Engineering, Henan University of Science and Technology, Luoyang, Henan Province, China

autor

Li Jie

• AVIC Jonhon Optronic Technology Co., Ltd., Luoyang, Henan Province, China

autor

Xin Wen

• State Key Laboratory of Intelligent Mining Heavy Equipment, Luoyang, Henan Province, China

autor

Han Chunyang

• State Key Laboratory of Intelligent Mining Heavy Equipment, Luoyang, Henan Province, China

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