Multidisciplinary Collaborative Reliability Analysis of the Gear Reducer based on Inverse Reliability Strategy

To overcome the high computational cost of reliability analysis,a reliability analysis method which combines the multidisciplinary genetic algorithm collaborative optimization( GA- CO) based on the inverse reliability strategy( IRS) is proposed( IRS- GA- CO). The genetic algorithms- based collaborat...

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Main Authors: Wang Liangliang, Peng Jinshuan, Shao Yiming
Format: Article
Language:zho
Published: Editorial Office of Journal of Mechanical Transmission 2015-01-01
Series:Jixie chuandong
Online Access:http://www.jxcd.net.cn/thesisDetails#10.16578/j.issn.1004.2539.2015.07.004
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author Wang Liangliang
Peng Jinshuan
Shao Yiming
author_facet Wang Liangliang
Peng Jinshuan
Shao Yiming
author_sort Wang Liangliang
collection DOAJ
description To overcome the high computational cost of reliability analysis,a reliability analysis method which combines the multidisciplinary genetic algorithm collaborative optimization( GA- CO) based on the inverse reliability strategy( IRS) is proposed( IRS- GA- CO). The genetic algorithms- based collaborative optimization( GA- CO) is one of the improved forms of CO that overcomes the difficulty of convergence given the existing of highly nonlinear consistency constraints. The IRS- GA- CO,which not only lifted the coupling between all disciplines to improve the search most probable point,the burden of system- level optimizer also can be significantly reduced. Examples of speed reducer prove the efficiency and precision of the proposed method.What is more,this advantage in the design of large- scale complex engineering systems will be better reflected.
format Article
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institution DOAJ
issn 1004-2539
language zho
publishDate 2015-01-01
publisher Editorial Office of Journal of Mechanical Transmission
record_format Article
series Jixie chuandong
spelling doaj-art-200c9b542a1a4b68b0aeb142dc69df142025-08-20T02:47:39ZzhoEditorial Office of Journal of Mechanical TransmissionJixie chuandong1004-25392015-01-0139161929917774Multidisciplinary Collaborative Reliability Analysis of the Gear Reducer based on Inverse Reliability StrategyWang LiangliangPeng JinshuanShao YimingTo overcome the high computational cost of reliability analysis,a reliability analysis method which combines the multidisciplinary genetic algorithm collaborative optimization( GA- CO) based on the inverse reliability strategy( IRS) is proposed( IRS- GA- CO). The genetic algorithms- based collaborative optimization( GA- CO) is one of the improved forms of CO that overcomes the difficulty of convergence given the existing of highly nonlinear consistency constraints. The IRS- GA- CO,which not only lifted the coupling between all disciplines to improve the search most probable point,the burden of system- level optimizer also can be significantly reduced. Examples of speed reducer prove the efficiency and precision of the proposed method.What is more,this advantage in the design of large- scale complex engineering systems will be better reflected.http://www.jxcd.net.cn/thesisDetails#10.16578/j.issn.1004.2539.2015.07.004
spellingShingle Wang Liangliang
Peng Jinshuan
Shao Yiming
Multidisciplinary Collaborative Reliability Analysis of the Gear Reducer based on Inverse Reliability Strategy
Jixie chuandong
title Multidisciplinary Collaborative Reliability Analysis of the Gear Reducer based on Inverse Reliability Strategy
title_full Multidisciplinary Collaborative Reliability Analysis of the Gear Reducer based on Inverse Reliability Strategy
title_fullStr Multidisciplinary Collaborative Reliability Analysis of the Gear Reducer based on Inverse Reliability Strategy
title_full_unstemmed Multidisciplinary Collaborative Reliability Analysis of the Gear Reducer based on Inverse Reliability Strategy
title_short Multidisciplinary Collaborative Reliability Analysis of the Gear Reducer based on Inverse Reliability Strategy
title_sort multidisciplinary collaborative reliability analysis of the gear reducer based on inverse reliability strategy
url http://www.jxcd.net.cn/thesisDetails#10.16578/j.issn.1004.2539.2015.07.004
work_keys_str_mv AT wangliangliang multidisciplinarycollaborativereliabilityanalysisofthegearreducerbasedoninversereliabilitystrategy
AT pengjinshuan multidisciplinarycollaborativereliabilityanalysisofthegearreducerbasedoninversereliabilitystrategy
AT shaoyiming multidisciplinarycollaborativereliabilityanalysisofthegearreducerbasedoninversereliabilitystrategy