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Erschienen in: Chinese Journal of Mechanical Engineering 4/2017

16.05.2017 | Original Article

Reliability Evaluation of Machine Center Components Based on Cascading Failure Analysis

verfasst von: Ying-Zhi Zhang, Jin-Tong Liu, Gui-Xiang Shen, Zhe Long, Shu-Guang Sun

Erschienen in: Chinese Journal of Mechanical Engineering | Ausgabe 4/2017

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Abstract

In order to rectify the problems that the component reliability model exhibits deviation, and the evaluation result is low due to the overlook of failure propagation in traditional reliability evaluation of machine center components, a new reliability evaluation method based on cascading failure analysis and the failure influenced degree assessment is proposed. A direct graph model of cascading failure among components is established according to cascading failure mechanism analysis and graph theory. The failure influenced degrees of the system components are assessed by the adjacency matrix and its transposition, combined with the Pagerank algorithm. Based on the comprehensive failure probability function and total probability formula, the inherent failure probability function is determined to realize the reliability evaluation of the system components. Finally, the method is applied to a machine center, it shows the following: 1) The reliability evaluation values of the proposed method are at least 2.5% higher than those of the traditional method; 2) The difference between the comprehensive and inherent reliability of the system component presents a positive correlation with the failure influenced degree of the system component, which provides a theoretical basis for reliability allocation of machine center system.

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Metadaten
Titel
Reliability Evaluation of Machine Center Components Based on Cascading Failure Analysis
verfasst von
Ying-Zhi Zhang
Jin-Tong Liu
Gui-Xiang Shen
Zhe Long
Shu-Guang Sun
Publikationsdatum
16.05.2017
Verlag
Chinese Mechanical Engineering Society
Erschienen in
Chinese Journal of Mechanical Engineering / Ausgabe 4/2017
Print ISSN: 1000-9345
Elektronische ISSN: 2192-8258
DOI
https://doi.org/10.1007/s10033-017-0144-y

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