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为了精确预测小弯曲半径21-6-9不锈钢管材绕弯成形截面畸变行为，优化工艺参数以有效控制截面畸变行为，采用有限元数值模拟方法，结合正交实验设计的方差分析，研究了工艺参数对小弯曲半径21-6-9不锈钢管材绕弯成形截面畸变行为影响的显著性及规律。通过RapidMiner机器学习平台对显著性工艺参数和最大截面畸变率ΔDmax进行了智能优化和同步预测，并对机器学习的可靠性进行了验证。结果表明，影响截面畸变率的显著性工艺参数依次为：芯棒伸出量e、芯棒直径dm、管材与压块的间隙Cp、管材与防皱块的间隙Cw、管材与芯棒的摩擦因数fm和管材与弯曲模的间隙Cb;截面畸变率随着e、dm、Cw的增大或Cp、fm、Cb的减小而减小；优化的显著性工艺参数和最大截面畸变率ΔDmax分别为：Cb=0.08 mm、Cp=0.055 mm、dm=5.232 mm、e=1.493 mm、Cw=0.15 mm、fm=0.152和ΔDmax=2.5%;机器学习预测结果与有限元模拟预测结果的相对误差仅为3.29%,可用于快速准确地预测小弯曲半径21-6-9不锈钢管材绕弯成形截面畸变行为。
Abstract：To accurately predict cross section distortion behaviors of 21-6-9 stainless steel pipe during rotary draw bending with small bending radius and optimize process parameters to effectively control the cross section distortion behaviors, using the finite element numerical simulation method and combining with the variance analysis of orthogonal experimental design, the significance and law of the influence of process parameters on the cross section distortion behaviors of 21-6-9 stainless steel pipe during rotary draw bending with small bending radius were studied. The significant process parameters and the maximum cross section distortion ratio ΔDmax were intelligently optimized and synchronously predicted through the RapidMiner machine learning platform, and the reliability of the machine learning was verified. The results show that the significant process parameters affecting the cross section distortion ratio in sequence are mandrel extension length e, mandrel diameter dm, gap between the pipe and the pressure block Cp, gap between the pipe and the wiper die Cw, friction factor between the pipe and the mandrel fm, and gap between the pipe and the bending die Cb. The cross section distortion ratio decreases with the increase of e, dm, Cw or the decrease of Cp, fm, Cb. The optimized significant process parameters and the maximum cross section distortion ratio ΔDmax are Cb=0.08 mm, Cp=0.055 mm, dm=5.232 mm, e=1.493 mm, Cw=0.15 mm, fm=0.152 and ΔDmax=2.5%, respectively. The relative error between the machine learning prediction results and the finite element simulation prediction results is only 3.29%, which can be used to quickly and accurately predict the cross section distortion behaviors of 21-6-9 stainless steel pipe during rotary draw bending with small bending radius.
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基本信息:
中图分类号:TG306;TP181
引用信息:
[1]谢琪龙,方军,尚文瑄,等.基于机器学习的小弯曲半径管材绕弯成形截面畸变行为预测[J].塑性工程学报,2026,33(08):109-115.
基金信息:
江西省自然科学基金资助项目(20192BAB216022); 浙江省自然科学基金资助项目(LLSSZ26E050001); 全省航空金属管件弯曲成形技术与装备重点实验室开放基金资助项目(2025ZDSYS-KFKT05); 省级大学生创新训练计划项目(S202511318087)
2026-08-21
2026-08-21
2026-08-21