Springback Control of Profile by Multi-Point Stretch-Bending and Torsion Automatic Forming Based on FE-BPNN

Springback control is a critical factor in profile stretch-bending-torsion forming. A new stretch-bending-torsion automatic forming method based on the mixture of finite element and BP neural network (FE-BPNN) is proposed. The method enhances the shape accuracy of profiles after single-step forming. Initially, the study introduces the 3D multi-point stretch-bending and torsion (3D MPSBT) forming machine and its forming principles. Subsequently, it details the springback prediction method and automatic forming control approach based on BPNN. A springback control model is established through numerical simulation and experiments. The proposed springback control method is compared with a springback factor-based approach from other researchers using hollow rectangular profiles undergoing combined bending and torsion deformation as the research object. The results validate the effectiveness and advantages of the proposed method.

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Publication Details

Journal
Metals
Published
2025-05-14
DOI
https://doi.org/10.3390/met15050544
Citations
2
Primary Topic
Advanced machining processes and optimization
Type
article
Field-Weighted Citation Impact
1.43
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article

Springback Control of Profile by Multi-Point Stretch-Bending and Torsion Automatic Forming Based on FE-BPNN

Ce Liang, Yu Wen, Yi Li, Jicai Liang
2 citations
Metals
Advanced machining processes and optimization
1.43
article

Springback Control of Profile by Multi-Point Stretch-Bending and Torsion Automatic Forming Based on FE-BPNN

Ce Liang, Yu Wen, Yi Li, Jicai Liang
article en
2 citations

Abstract

Springback control is a critical factor in profile stretch-bending-torsion forming. A new stretch-bending-torsion automatic forming method based on the mixture of finite element and BP neural network (FE-BPNN) is proposed. The method enhances the shape accuracy of profiles after single-step forming. Initially, the study introduces the 3D multi-point stretch-bending and torsion (3D MPSBT) forming machine and its forming principles. Subsequently, it details the springback prediction method and automatic forming control approach based on BPNN. A springback control model is established through numerical simulation and experiments. The proposed springback control method is compared with a springback factor-based approach from other researchers using hollow rectangular profiles undergoing combined bending and torsion deformation as the research object. The results validate the effectiveness and advantages of the proposed method.

MetalsVol. 15(5)
Jilin University (CN)
Openalex Percentile: Top 20%
Advanced machining processes and optimization
1.43
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