Fatigue life analysis based on six sigma robust optimization for pantograph collector head support

In this article, a new fatigue life analysis method based on six sigma robust optimization is proposed, which considers the random effects of material properties, external loads, and dimensions on the fatigue life of a pantograph collector head support. Some main random factors are identified throug...

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Main Authors: Yonghua Li, Mingguang Hu, Feng Wang
Format: Article
Language:English
Published: SAGE Publishing 2016-11-01
Series:Advances in Mechanical Engineering
Online Access:https://doi.org/10.1177/1687814016679314
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spelling doaj-b96b35bb83e14a17a5ae4b1a307b366d2020-11-25T03:43:56ZengSAGE PublishingAdvances in Mechanical Engineering1687-81402016-11-01810.1177/1687814016679314Fatigue life analysis based on six sigma robust optimization for pantograph collector head supportYonghua Li0Mingguang Hu1Feng Wang2School of Traffic and Transportation Engineering, Dalian Jiaotong University, Dalian, ChinaSchool of Traffic and Transportation Engineering, Dalian Jiaotong University, Dalian, ChinaCollege of Bullet Train Application and Maintenance Engineering, Dalian Jiaotong University, Dalian, ChinaIn this article, a new fatigue life analysis method based on six sigma robust optimization is proposed, which considers the random effects of material properties, external loads, and dimensions on the fatigue life of a pantograph collector head support. Some main random factors are identified through fatigue reliability sensitivity analysis, which are used as input variables during fatigue life analysis. The six sigma optimization model is derived using the second-order response surface method. The response surface is fitted by the Monte Carlo method, the samples are obtained by the Latin hypercube sampling technique, and the proposed model is optimized using the interior point algorithm. Through the optimization, the collector head support weight is reduced, the mean and the standard deviation of fatigue life have been decreased, and the effect of design parameter variation on the fatigue life is reduced greatly. The robustness of fatigue life prediction of collector head support is improved. The proposed method may be extended to fatigue life analysis of other components of electric multiple units.https://doi.org/10.1177/1687814016679314
collection DOAJ
language English
format Article
sources DOAJ
author Yonghua Li
Mingguang Hu
Feng Wang
spellingShingle Yonghua Li
Mingguang Hu
Feng Wang
Fatigue life analysis based on six sigma robust optimization for pantograph collector head support
Advances in Mechanical Engineering
author_facet Yonghua Li
Mingguang Hu
Feng Wang
author_sort Yonghua Li
title Fatigue life analysis based on six sigma robust optimization for pantograph collector head support
title_short Fatigue life analysis based on six sigma robust optimization for pantograph collector head support
title_full Fatigue life analysis based on six sigma robust optimization for pantograph collector head support
title_fullStr Fatigue life analysis based on six sigma robust optimization for pantograph collector head support
title_full_unstemmed Fatigue life analysis based on six sigma robust optimization for pantograph collector head support
title_sort fatigue life analysis based on six sigma robust optimization for pantograph collector head support
publisher SAGE Publishing
series Advances in Mechanical Engineering
issn 1687-8140
publishDate 2016-11-01
description In this article, a new fatigue life analysis method based on six sigma robust optimization is proposed, which considers the random effects of material properties, external loads, and dimensions on the fatigue life of a pantograph collector head support. Some main random factors are identified through fatigue reliability sensitivity analysis, which are used as input variables during fatigue life analysis. The six sigma optimization model is derived using the second-order response surface method. The response surface is fitted by the Monte Carlo method, the samples are obtained by the Latin hypercube sampling technique, and the proposed model is optimized using the interior point algorithm. Through the optimization, the collector head support weight is reduced, the mean and the standard deviation of fatigue life have been decreased, and the effect of design parameter variation on the fatigue life is reduced greatly. The robustness of fatigue life prediction of collector head support is improved. The proposed method may be extended to fatigue life analysis of other components of electric multiple units.
url https://doi.org/10.1177/1687814016679314
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AT mingguanghu fatiguelifeanalysisbasedonsixsigmarobustoptimizationforpantographcollectorheadsupport
AT fengwang fatiguelifeanalysisbasedonsixsigmarobustoptimizationforpantographcollectorheadsupport
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