RELIABILITY EVALUATION OF MULTIPLE PERFORMANCE AEROENGINES BASED ON Gamma PROCESS AND MIXED DISTRIBUTION UNDER COMPETITIVE FAILURE

In order to solve the reliability evaluation under the competitive failure of multiple performance aero-engines,multiple performance data was fused into an overall degradation data by the matrix similarity,and a nonlinear Gamma process with random effects was used to fit the overall degradation data...

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Language:zho
Published: Editorial Office of Journal of Mechanical Strength 2024-01-01
Series:Jixie qiangdu
Online Access:http://www.jxqd.net.cn/thesisDetails#10.16579/j.issn.1001.9669.2024.06.014
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description In order to solve the reliability evaluation under the competitive failure of multiple performance aero-engines,multiple performance data was fused into an overall degradation data by the matrix similarity,and a nonlinear Gamma process with random effects was used to fit the overall degradation data to obtain the reliability function under multivariate degradation.Assume that multiple performance of the aero-engines have sudden failures,the optimal sudden failure distribution was selected by Anderson-Darling(AD)distribution test,the reliability function under sudden failures was obtained by the mixed distribution.Assume that degradation failure and sudden failure were independent,the reliability evaluation of the multiple performance aeroengines under competitive failure was realized.Finally,the effectiveness and accuracy of the model were verified by the case analysis.
format Article
id doaj-art-9192e4291cd245419eb5538859cdfa5e
institution OA Journals
issn 1001-9669
language zho
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publisher Editorial Office of Journal of Mechanical Strength
record_format Article
series Jixie qiangdu
spelling doaj-art-9192e4291cd245419eb5538859cdfa5e2025-08-20T01:47:28ZzhoEditorial Office of Journal of Mechanical StrengthJixie qiangdu1001-96692024-01-01461375138098127158RELIABILITY EVALUATION OF MULTIPLE PERFORMANCE AEROENGINES BASED ON Gamma PROCESS AND MIXED DISTRIBUTION UNDER COMPETITIVE FAILUREIn order to solve the reliability evaluation under the competitive failure of multiple performance aero-engines,multiple performance data was fused into an overall degradation data by the matrix similarity,and a nonlinear Gamma process with random effects was used to fit the overall degradation data to obtain the reliability function under multivariate degradation.Assume that multiple performance of the aero-engines have sudden failures,the optimal sudden failure distribution was selected by Anderson-Darling(AD)distribution test,the reliability function under sudden failures was obtained by the mixed distribution.Assume that degradation failure and sudden failure were independent,the reliability evaluation of the multiple performance aeroengines under competitive failure was realized.Finally,the effectiveness and accuracy of the model were verified by the case analysis.http://www.jxqd.net.cn/thesisDetails#10.16579/j.issn.1001.9669.2024.06.014
spellingShingle RELIABILITY EVALUATION OF MULTIPLE PERFORMANCE AEROENGINES BASED ON Gamma PROCESS AND MIXED DISTRIBUTION UNDER COMPETITIVE FAILURE
Jixie qiangdu
title RELIABILITY EVALUATION OF MULTIPLE PERFORMANCE AEROENGINES BASED ON Gamma PROCESS AND MIXED DISTRIBUTION UNDER COMPETITIVE FAILURE
title_full RELIABILITY EVALUATION OF MULTIPLE PERFORMANCE AEROENGINES BASED ON Gamma PROCESS AND MIXED DISTRIBUTION UNDER COMPETITIVE FAILURE
title_fullStr RELIABILITY EVALUATION OF MULTIPLE PERFORMANCE AEROENGINES BASED ON Gamma PROCESS AND MIXED DISTRIBUTION UNDER COMPETITIVE FAILURE
title_full_unstemmed RELIABILITY EVALUATION OF MULTIPLE PERFORMANCE AEROENGINES BASED ON Gamma PROCESS AND MIXED DISTRIBUTION UNDER COMPETITIVE FAILURE
title_short RELIABILITY EVALUATION OF MULTIPLE PERFORMANCE AEROENGINES BASED ON Gamma PROCESS AND MIXED DISTRIBUTION UNDER COMPETITIVE FAILURE
title_sort reliability evaluation of multiple performance aeroengines based on gamma process and mixed distribution under competitive failure
url http://www.jxqd.net.cn/thesisDetails#10.16579/j.issn.1001.9669.2024.06.014