钛合金切削温度-振动相关性及加工优化研究
Study on Cutting Temperature-vibration Correlation of Titanium Alloys and Machining Optimization
李松原 1李顺才 2刘志 3胡雨婷1
作者信息
- 1. 江苏师范大学 机电工程学院,江苏徐州 221116
- 2. 江苏师范大学 机电工程学院,江苏徐州 221116;江苏师范大学 江苏圣理工学院,江苏徐州 221116
- 3. 江苏师范大学 江苏圣理工学院,江苏徐州 221116
- 折叠
摘要
钛合金作为"21 世纪战略金属"在航空领域应用广泛,其加工质量至关重要.因此,对钛合金进行切削加工优化具有重要的研究意义.本文搭建切削温度和切削振动同步测量系统.通过红外热像仪和三向加速度传感器采集车刀尖端附近的温度和振动信号.建立基于切削温度和切削振动多特征融合优化模型,并运用粒子群优化灰狼算法对多特征融合优化模型进行求解,获得最优的切削参数.研究表明:在试验设计的切削参数范围内,切削参数的最优解为:切削速度753.98 m/s,进给速度30 mm/min,切削深度0.4 mm,所做研究为优化钛合金加工质量提供理论指导.
Abstract
As a"21st century strategic metal",titanium alloy is widely used in the aviation field,and its processing quality is very important.Therefore,it is of great significance to optimize the machining of titanium alloys.In this paper,a synchronous measurement system for cutting temperature and vibration is built.The temperature and vibration signals near the tip of the turning tool are collected by an infrared thermal imager and a three-way acceleration sensor.A multi-feature fusion optimization model based on the cutting temperature and vibration is established,and the particle swarm optimization gray wolf algorithm is used to solve the multi-feature fusion optimization model to obtain the optimal cutting parameters.The study shows that within the range of cutting parameters designed by the experiment,the optimal solution of cutting parameters is 753.98 m/s of cutting speed,30 mm/min of feed rate,0.4 mm of cutting depth,and provides a theoretical basis for optimizing the machining quality of titanium alloys.
关键词
钛合金/切削温度/切削振动/灰色相对关联度/多特征融合优化模型/粒子群优化灰狼算法Key words
titanium alloy/cutting temperature/cutting vibration/gray relative correlation/multi-feature fusion optimization model/particle swarm optimization gray wolf algorithm引用本文复制引用
基金项目
江苏省自然科学基金面上项目(BK20231173)
徐州市科技计划(KC23054)
出版年
2024
国家科技期刊平台
NSTL
万方数据