材料工程2025，Vol.53Issue(4)：23-34,12.DOI:10.11868/j.issn.1001-4381.2024.000847
基于Adaboost回归的6061铝合金单点增量成形最大成形深度预测
Prediction of maximum forming depth in single point incremental forming of 6061 aluminum alloy based on Adaboost regression
摘要
Abstract
Single point incremental forming(SPIF)is a highly flexible manufacturing process widely utilized in the aerospace industry,particularly suited for customized and small-batch production components.However,the appropriate range of process parameters suitable for different models remains undefined,necessitating extensive parameter testing.An orthogonal experiment is conducted to perform a multi-factor analysis of variance,discussing the influence of parameters such as sheet thickness,angle,incremental amount,feed rate,and rotational speed on the maximum forming depth.Based on the experimental results,a regression model using the Adaboost algorithm is developed to predict the forming depth of 6061 aluminum alloy thin sheets at the forming diameter of 100 mm.The results indicate that the influences of single factors on the maximum forming depth in descending order of significance are:thickness,layer increment,angle,feed rate,and rotational speed.Under the optimal forming conditions achieved at the fastest forming speed,the maximum forming angle is 70°,the sheet thickness is 1 mm,the layer increment is 0.2 mm,the feed rate is 2000 mm/min,and the rotational speed is 2000 r/min.Furthermore,the regression model created based on the orthogonal experiment demonstrates high accuracy,correlating well with both the Abaqus simulation results and the actual experimental outcomes.The maximum error between the four groups of tests and simulations is 4.24％,while the maximum error with the actual forming results is-2.45％.关键词
单点增量成形/工艺参数/6061铝合金/Adaboost算法/回归模型Key words
SPIF/process parameter/6061 aluminum alloy/Adaboost algorithm/regression model分类
金属材料引用本文复制引用
梁智凯,张志超,胡蓝,庞秋..基于Adaboost回归的6061铝合金单点增量成形最大成形深度预测[J].材料工程,2025,53(4):23-34,12.基金项目
国家自然科学基金(52075400) （52075400）
湖北省重点研发计划项目(2023BAB194) （2023BAB194）
湖北省自然科学基金(2023AFA069) （2023AFA069）
隆中实验室开放基金(2024KF-05,2024KF-06) （2024KF-05,2024KF-06）
