Operation reliability analysis based on fuzzy support vector machine for aircraft engines
Author(s) -
Jun Gao,
Huawei Wang
Publication year - 2015
Publication title -
eksploatacja i niezawodnosc - maintenance and reliability
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.47
H-Index - 27
eISSN - 2956-3860
pISSN - 1507-2711
DOI - 10.17531/ein.2015.2.3
Subject(s) - reliability (semiconductor) , reliability engineering , computer science , support vector machine , fuzzy logic , engineering , artificial intelligence , physics , power (physics) , quantum mechanics
The aircraft engine is a complex and repairable system, and the diversity of its failure modes increases the difficulty of operation reliability analysis. It is necessary to establish a dynamic relationship among monitoring information, failure mode and system reliability for achieving scientific reliability analysis for aircraft engines. This paper has used fuzzy support vector machine (FVSM) method to fuse condition monitoring information. The reliability analysis models including Gamma process model and Winner process model, respectively for different failure modes, have been presented. Furthermore, these two models have been integrated on the basis of competing failures’ mechanism. Bayesian model averaging has been used to analyze the effects of different failure modes on aircraft engines’ reliability. As a result of above, the goal of an accurate analysis of the reliability for aircraft engines has been achieved. Example shows the effectiveness of the proposed model.
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