智能刀柄高应变灵敏度结构多目标优化设计

姜飞跃; 李鹏南; 李树健; 邱新义

doi:10.13433/j.cnki.1003-8728.20230205

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智能刀柄高应变灵敏度结构多目标优化设计

更新时间：2026-04-23

- 智能刀柄高应变灵敏度结构多目标优化设计
- Multi-objective Optimization Design of High Strain Sensitivity Structure of Smart Tool Holder
- 机械科学与技术 2025年44卷第5期页码：824-832
- 作者机构：
  
  湖南科技大学机构机电工程学院,湖南,湘潭,411201
- 作者简介：
  
  [ "姜飞跃，硕士研究生，" ]
  [ "李鹏南，教授，博士生导师，博士，" ]
- 基金信息：
  
  国家自然科学基金项目（52275423，51975208，52105442）
- DOI：10.13433/j.cnki.1003-8728.20230205
  中图分类号：
- 纸质出版：2025
- 稿件说明：
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姜飞跃, 李鹏南, 李树健, 等. 智能刀柄高应变灵敏度结构多目标优化设计[J]. 机械科学与技术, 2025,44(5):824-832.

姜飞跃, 李鹏南, 李树健, et al. Multi-objective Optimization Design of High Strain Sensitivity Structure of Smart Tool Holder[J]. Mechanical Science and Technology for Aerospace Engineering, 2025, 44(5): 824-832.
姜飞跃, 李鹏南, 李树健, 等. 智能刀柄高应变灵敏度结构多目标优化设计[J]. 机械科学与技术, 2025,44(5):824-832. DOI： 10.13433/j.cnki.1003-8728.20230205.

姜飞跃, 李鹏南, 李树健, et al. Multi-objective Optimization Design of High Strain Sensitivity Structure of Smart Tool Holder[J]. Mechanical Science and Technology for Aerospace Engineering, 2025, 44(5): 824-832. DOI： 10.13433/j.cnki.1003-8728.20230205.

摘要

为获得智能刀柄高应变灵敏度结构参数最优值，以刀柄轴向应变灵敏度、轴向刚度、扭转刚度最大为优化目标，以一阶固有频率在设计要求范围内为约束条件，基于响应曲面法建立优化目标近似响应面模型，分析设计变量与优化目标之间的关系，并采用改进的非支配排序遗传算法对刀柄结构进行多目标优化设计，获得刀柄结构参数Pareto最优解。相比标准刀柄，优化后刀柄轴向应变灵敏度提高了32.8%、轴向刚度降低了14.8%、扭转刚度降低了18.2%，1阶固有频率降低了10.1%。

Abstract

In order to obtain the optimal structural parameters of high strain sensitivity of smart tool holder

this paper takes the maximum axial strain sensitivity

axial stiffness and torsional stiffness of the tool holder as the optimization objectives

and takes the first natural frequency of the tool holder within the design requirements as the constraint condition

the approximate response surface model of optimization objectives was established based on the response surface method

and the relationship between design variables and optimization objectives was analyzed. The multi-objective optimization design of the smart tool holder structure was carried out by non-dominated sorting genetic algorithm-Ⅱ

and the Pareto optimal solution of smart tool holder structure parameters was obtained. Compared with the standard tool holder

the axial strain sensitivity of the optimized tool holder is increased by 32.8%

the axial stiffness is reduced by 14.8%

the torsional stiffness is reduced by 18.2%

and the first natural frequency is reduced by 10.1%.

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