Virtual simulation of weld morphology for V-groove multi-layer welding

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作者信息关键词期刊信息基础信息归属信息摘要

成果类型：

期刊论文

作者：

Li, Shichun;Zhou, Feisi;Ou, Min;Cai, Wenjing;Xiao, Gang;...

通讯作者：

Li, SC

作者机构：

[Li, Shichun; Xiao, Gang; Zhang, Hua; Li, SC] Hunan Univ Sci & Technol, Hunan Prov Key Lab High Efficiency & Precis Machin, Xiangtan 411201, Hunan, Peoples R China.

[Li, Shichun; Zhou, Feisi; Xiao, Gang; Ou, Min; Zhang, Hua; Chen, Changqing; Cai, Wenjing; Yang, Zhi] Hunan Univ Sci & Technol, Sch Mech Engn, Xiangtan 411201, Hunan, Peoples R China.

[Wei, Hua; Yang, Zhi] Hunan Elect Coll Technol, Coll Automot Engn, Xiangtan 411101, Hunan, Peoples R China.

[Chen, Changqing] Hunan City Univ, Sch Mech & Elect Engn, Yiyang 413000, Hunan, Peoples R China.

通讯机构：

[Li, SC ] H

Hunan Univ Sci & Technol, Hunan Prov Key Lab High Efficiency & Precis Machin, Xiangtan 411201, Hunan, Peoples R China.

语种：

英文

关键词：

Morphology;Multilayer neural networks;Welds;Characteristics parameters;Multilayer welding;Process parameters;Reconstruction model;V grooves;V-groove;Virtual models;Virtual simulations;Weld morphology;Weld morphology prediction;Forecasting

期刊：

Materials Today Communications

ISSN：

2352-4928

年：

2024

卷：

页码：

108593

DOI：

10.1016/j.mtcomm.2024.108593

基金类别：

This research was supported by the Natural Science Foundation of Hunan Province of China (Nos. 2022JJ30019 and 2023JJ60181), the Key Project of Scientific Research Foundation of Hunan Provincial Education Department of China (Nos. 21A0301), The Open Foundation of State Key Laboratory of Featured Metal Materials and Life-cycle Safety for Composite Structures at Guangxi University (No. 2022GXYSOF24), and the Open Foundation of Hubei Key Laboratory of Mechanical Transmission and Manufacturing Engineering at Wuhan University of Science and Technology (No. MTMEOF2020A01).

机构署名：

本校为其他机构

院系归属：

机械与电气工程学院

摘要：

In order to study the virtual simulation of weld morphology for V-groove multi-layer welding, the prediction of characteristic parameters for weld morphology was realized by constructing the neural network models between the characteristic parameters and process parameters of different layers. At the same time, the virtual models of different layers were established according to the characteristic parameters of weld morphology and the structure parameters of V-groove. Combined with the prediction model and the virtual model, the process paramet...

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Virtual simulation of weld morphology for V-groove multi-layer welding

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