基于数值模拟和决策树回归的金属切削力学性能预测

程一晋; 冯志强; 李燕

doi:10.21656/1000-0887.460102

基于数值模拟和决策树回归的金属切削力学性能预测

doi: 10.21656/1000-0887.460102

西南交通大学力学与航空航天学院，成都 611756

基金项目:

国家自然科学基金（12372142

12572232）

详细信息

作者简介:
程一晋(1996—)，男，博士(E-mail: yijin_cheng@my.swjtu.edu.cn)；冯志强(1963—)，男，教授(通信作者. E-mail: zhiqiang.feng@univ-evry.fr)；李燕(1991—)，女，副教授(E-mail: yanli@swjtu.edu.cn).

通讯作者:
冯志强(1963—)，男，教授(通信作者. E-mail: zhiqiang.feng@univ-evry.fr)

中图分类号: O343.3
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- 文章访问数: 19
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- PDF下载量: 3
- 被引次数: 0
出版历程
- 收稿日期: 2025-05-20
- 修回日期: 2025-07-30
- 网络出版日期: 2026-01-21
- 刊出日期: 2026-01-01

Mechanical Property Prediction of Metal Cutting Based on Numerical Simulation and Decision Tree Regression

School of Mechanics and Aerospace Engineering, Southwest Jiaotong University, Chengdu 611756, P.R.China

Funds:

The National Science Foundation of China(12372142

12572232)

摘要

摘要: 快速预测金属切削的各种力学性能对工业制造的优化设计和产能提高十分关键.当前相关预测模型通常需要昂贵且耗时的实验和分析过程.构建了一种基于金属切削模拟和决策树回归(decision tree regression, DTR)的预测模型，用于获取不同切削工况下的力学性能.首先，采用自适应光滑粒子流体动力学(adaptive smoothed particle hydrodynamics, ASPH)模拟金属切削过程，捕获了不同模拟参数下的多种力学性能，组成2 000种切削工况的模拟数据集；其次，利用DTR算法学习模拟数据集，训练和构建金属切削预测模型，并通过交叉验证和网格搜索评估了不同剪枝策略下预测模型的效果.结果表明，建立的预测模型可以快速地预测不同模拟参数下的多种力学性能，适宜的剪枝策略可以提升预测模型的准确度、泛化能力和稳定性.
- 金属切削 /
- 力学性能预测 /
- 数值模拟 /
- 自适应光滑粒子流体动力学 /
- 决策树回归
Abstract: Rapid prediction of mechanical properties of metal cutting is critical to optimal design and productivity improvement of industrial manufacturing. Current prediction models often require expensive and time-consuming experimental and analytical processes. A prediction model based on metal cutting simulation and decision tree regression was constructed to obtain mechanical properties under different cutting conditions. Firstly, the adaptive smoothed particle hydrodynamics (ASPH) was used to simulate the metal cutting process, capture a variety of mechanical properties under different simulation parameters, and form a simulation dataset of 2 000 cutting conditions. Secondly, the decision tree regression (DTR) was used to learn the simulation data set, train and construct the metal cutting prediction model, and evaluate the effect of the prediction model under different pruning strategies by cross-validation and grid search. The results show that, the established prediction model can quickly predict multi-mechanical properties under different simulation parameters, and the appropriate pruning strategy can improve the accuracy, generalization ability and stability of the prediction model.
- metal cutting /
- mechanical property prediction /
- numerical simulation /
- adaptive smoothed particle hydrodynamics /
- decision tree regression

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参考文献(36)

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基于数值模拟和决策树回归的金属切削力学性能预测

doi: 10.21656/1000-0887.460102

作者简介:
程一晋(1996—)，男，博士(E-mail: yijin_cheng@my.swjtu.edu.cn)；冯志强(1963—)，男，教授(通信作者. E-mail: zhiqiang.feng@univ-evry.fr)；李燕(1991—)，女，副教授(E-mail: yanli@swjtu.edu.cn).

通讯作者:
冯志强(1963—)，男，教授(通信作者. E-mail: zhiqiang.feng@univ-evry.fr)

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Mechanical Property Prediction of Metal Cutting Based on Numerical Simulation and Decision Tree Regression

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留言板

基于数值模拟和决策树回归的金属切削力学性能预测

doi: 10.21656/1000-0887.460102

作者简介: 程一晋(1996—)，男，博士(E-mail: yijin_cheng@my.swjtu.edu.cn)；冯志强(1963—)，男，教授(通信作者. E-mail: zhiqiang.feng@univ-evry.fr)；李燕(1991—)，女，副教授(E-mail: yanli@swjtu.edu.cn).

通讯作者: 冯志强(1963—)，男，教授(通信作者. E-mail: zhiqiang.feng@univ-evry.fr)

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出版历程

Mechanical Property Prediction of Metal Cutting Based on Numerical Simulation and Decision Tree Regression

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出版历程

目录

作者简介:
程一晋(1996—)，男，博士(E-mail: yijin_cheng@my.swjtu.edu.cn)；冯志强(1963—)，男，教授(通信作者. E-mail: zhiqiang.feng@univ-evry.fr)；李燕(1991—)，女，副教授(E-mail: yanli@swjtu.edu.cn).

通讯作者:
冯志强(1963—)，男，教授(通信作者. E-mail: zhiqiang.feng@univ-evry.fr)