Cargando…

An Entropy-Based Neighborhood Rough Set and PSO-SVRM Model for Fatigue Life Prediction of Titanium Alloy Welded Joints

In order to obtain comprehensive assessment of the factors influencing fatigue life and to further improve the accuracy of fatigue life prediction of welded joints, soft computing methods, including entropy-based neighborhood rough set reduction algorithm, the particle swarm optimization (PSO) algor...

Descripción completa

Detalles Bibliográficos
Autores principales: Zou, Li, Sun, Yibo, Yang, Xinhua
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7514600/
https://www.ncbi.nlm.nih.gov/pubmed/33266833
http://dx.doi.org/10.3390/e21020117
_version_ 1783586625577549824
author Zou, Li
Sun, Yibo
Yang, Xinhua
author_facet Zou, Li
Sun, Yibo
Yang, Xinhua
author_sort Zou, Li
collection PubMed
description In order to obtain comprehensive assessment of the factors influencing fatigue life and to further improve the accuracy of fatigue life prediction of welded joints, soft computing methods, including entropy-based neighborhood rough set reduction algorithm, the particle swarm optimization (PSO) algorithm and support vector regression machine (SVRM) are combined to construct a fatigue life prediction model of titanium alloy welded joints. By using an entropy-based neighborhood rough set reduction algorithm, the influencing factors of the fatigue life of titanium alloy welded joints such as joint type, plate thickness, etc. are analyzed and the reduction results are obtained. Fatigue characteristic domains are proposed and determined subsequently according to the reduction results. The PSO-SVRM model for fatigue life prediction of titanium alloy welded joints is established in the suggested fatigue characteristic domains. Experimental results show that by taking into account the impact of joint type, the PSO-SVRM model could better predict the fatigue life of titanium alloy welded joints. The PSO-SVRM model indicates the relationship between fatigue life and fatigue life influencing factors in multidimensional space compared with the conventional least-square S-N curve fitting method, it could predict the fatigue life of the titanium alloy welded joints more accurately thus helps to the reliability design of the structure.
format Online
Article
Text
id pubmed-7514600
institution National Center for Biotechnology Information
language English
publishDate 2019
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-75146002020-11-09 An Entropy-Based Neighborhood Rough Set and PSO-SVRM Model for Fatigue Life Prediction of Titanium Alloy Welded Joints Zou, Li Sun, Yibo Yang, Xinhua Entropy (Basel) Article In order to obtain comprehensive assessment of the factors influencing fatigue life and to further improve the accuracy of fatigue life prediction of welded joints, soft computing methods, including entropy-based neighborhood rough set reduction algorithm, the particle swarm optimization (PSO) algorithm and support vector regression machine (SVRM) are combined to construct a fatigue life prediction model of titanium alloy welded joints. By using an entropy-based neighborhood rough set reduction algorithm, the influencing factors of the fatigue life of titanium alloy welded joints such as joint type, plate thickness, etc. are analyzed and the reduction results are obtained. Fatigue characteristic domains are proposed and determined subsequently according to the reduction results. The PSO-SVRM model for fatigue life prediction of titanium alloy welded joints is established in the suggested fatigue characteristic domains. Experimental results show that by taking into account the impact of joint type, the PSO-SVRM model could better predict the fatigue life of titanium alloy welded joints. The PSO-SVRM model indicates the relationship between fatigue life and fatigue life influencing factors in multidimensional space compared with the conventional least-square S-N curve fitting method, it could predict the fatigue life of the titanium alloy welded joints more accurately thus helps to the reliability design of the structure. MDPI 2019-01-27 /pmc/articles/PMC7514600/ /pubmed/33266833 http://dx.doi.org/10.3390/e21020117 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Zou, Li
Sun, Yibo
Yang, Xinhua
An Entropy-Based Neighborhood Rough Set and PSO-SVRM Model for Fatigue Life Prediction of Titanium Alloy Welded Joints
title An Entropy-Based Neighborhood Rough Set and PSO-SVRM Model for Fatigue Life Prediction of Titanium Alloy Welded Joints
title_full An Entropy-Based Neighborhood Rough Set and PSO-SVRM Model for Fatigue Life Prediction of Titanium Alloy Welded Joints
title_fullStr An Entropy-Based Neighborhood Rough Set and PSO-SVRM Model for Fatigue Life Prediction of Titanium Alloy Welded Joints
title_full_unstemmed An Entropy-Based Neighborhood Rough Set and PSO-SVRM Model for Fatigue Life Prediction of Titanium Alloy Welded Joints
title_short An Entropy-Based Neighborhood Rough Set and PSO-SVRM Model for Fatigue Life Prediction of Titanium Alloy Welded Joints
title_sort entropy-based neighborhood rough set and pso-svrm model for fatigue life prediction of titanium alloy welded joints
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7514600/
https://www.ncbi.nlm.nih.gov/pubmed/33266833
http://dx.doi.org/10.3390/e21020117
work_keys_str_mv AT zouli anentropybasedneighborhoodroughsetandpsosvrmmodelforfatiguelifepredictionoftitaniumalloyweldedjoints
AT sunyibo anentropybasedneighborhoodroughsetandpsosvrmmodelforfatiguelifepredictionoftitaniumalloyweldedjoints
AT yangxinhua anentropybasedneighborhoodroughsetandpsosvrmmodelforfatiguelifepredictionoftitaniumalloyweldedjoints
AT zouli entropybasedneighborhoodroughsetandpsosvrmmodelforfatiguelifepredictionoftitaniumalloyweldedjoints
AT sunyibo entropybasedneighborhoodroughsetandpsosvrmmodelforfatiguelifepredictionoftitaniumalloyweldedjoints
AT yangxinhua entropybasedneighborhoodroughsetandpsosvrmmodelforfatiguelifepredictionoftitaniumalloyweldedjoints