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Optimization of the ultrasonic roll extrusion process parameters based on the SPEA2SDE algorithm

To obtain the optimal processing parameters of ultrasonic roll extrusion, 42CrMo bearing steel was taken as the research object, and the orthogonal test method was used to design an ultrasonic roll extrusion experiment with spindle speed, feed speed, static pressure and amplitude as parameters. Base...

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Autores principales: Wang, Xiaoqiang, Wang, Haojie, Wang, Paigang, Liu, Zhifei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8907186/
https://www.ncbi.nlm.nih.gov/pubmed/35264689
http://dx.doi.org/10.1038/s41598-022-07917-7
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author Wang, Xiaoqiang
Wang, Haojie
Wang, Paigang
Liu, Zhifei
author_facet Wang, Xiaoqiang
Wang, Haojie
Wang, Paigang
Liu, Zhifei
author_sort Wang, Xiaoqiang
collection PubMed
description To obtain the optimal processing parameters of ultrasonic roll extrusion, 42CrMo bearing steel was taken as the research object, and the orthogonal test method was used to design an ultrasonic roll extrusion experiment with spindle speed, feed speed, static pressure and amplitude as parameters. Based on the orthogonal test data, the prediction models of surface roughness, surface residual stress and surface hardness were established by a multiple regression method, and the reliability of the model was verified. An algorithm combining SPEA2 and the shift density estimation strategy (SPEA2SDE) was introduced. The performance of the SPEA2SDE algorithm, NSGA II algorithm and SPEA2 algorithm is tested and compared on a three-dimensional test function set to verify its effectiveness. The SPEA2SDE algorithm are used to solve the multi-objective optimization model to obtain the optimal combination of processing parameters, and the ultrasonic roll extrusion experiment is carried out. The research results show that the surface roughness, surface residual stress and surface hardness optimized by the SPEA2SDE algorithm are in good agreement with the experimental values, and the average error is controlled within 10%, which shows that the algorithm can achieve high precision. It can effectively solve the multi-objective optimization problem of ultrasonic roll extrusion process parameters and can be used to guide actual production machining.
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spelling pubmed-89071862022-03-10 Optimization of the ultrasonic roll extrusion process parameters based on the SPEA2SDE algorithm Wang, Xiaoqiang Wang, Haojie Wang, Paigang Liu, Zhifei Sci Rep Article To obtain the optimal processing parameters of ultrasonic roll extrusion, 42CrMo bearing steel was taken as the research object, and the orthogonal test method was used to design an ultrasonic roll extrusion experiment with spindle speed, feed speed, static pressure and amplitude as parameters. Based on the orthogonal test data, the prediction models of surface roughness, surface residual stress and surface hardness were established by a multiple regression method, and the reliability of the model was verified. An algorithm combining SPEA2 and the shift density estimation strategy (SPEA2SDE) was introduced. The performance of the SPEA2SDE algorithm, NSGA II algorithm and SPEA2 algorithm is tested and compared on a three-dimensional test function set to verify its effectiveness. The SPEA2SDE algorithm are used to solve the multi-objective optimization model to obtain the optimal combination of processing parameters, and the ultrasonic roll extrusion experiment is carried out. The research results show that the surface roughness, surface residual stress and surface hardness optimized by the SPEA2SDE algorithm are in good agreement with the experimental values, and the average error is controlled within 10%, which shows that the algorithm can achieve high precision. It can effectively solve the multi-objective optimization problem of ultrasonic roll extrusion process parameters and can be used to guide actual production machining. Nature Publishing Group UK 2022-03-09 /pmc/articles/PMC8907186/ /pubmed/35264689 http://dx.doi.org/10.1038/s41598-022-07917-7 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Wang, Xiaoqiang
Wang, Haojie
Wang, Paigang
Liu, Zhifei
Optimization of the ultrasonic roll extrusion process parameters based on the SPEA2SDE algorithm
title Optimization of the ultrasonic roll extrusion process parameters based on the SPEA2SDE algorithm
title_full Optimization of the ultrasonic roll extrusion process parameters based on the SPEA2SDE algorithm
title_fullStr Optimization of the ultrasonic roll extrusion process parameters based on the SPEA2SDE algorithm
title_full_unstemmed Optimization of the ultrasonic roll extrusion process parameters based on the SPEA2SDE algorithm
title_short Optimization of the ultrasonic roll extrusion process parameters based on the SPEA2SDE algorithm
title_sort optimization of the ultrasonic roll extrusion process parameters based on the spea2sde algorithm
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8907186/
https://www.ncbi.nlm.nih.gov/pubmed/35264689
http://dx.doi.org/10.1038/s41598-022-07917-7
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