基于支持向量机与蛇优化算法的氧化锆陶瓷磨削工艺参数优化  

Optimization of Zirconia Ceramic Grinding Process Parameters Based on SupportVector Machine and Snake Optimizer Algorithm

作　　者：陶其赫 马廉洁 孙杨[1] 王乐 李文博[1] Tao Qihe;Ma Lianjie;Sun Yang;Wang Le;Li Wenbo

机构地区：[1]东北大学秦皇岛分校控制工程学院,河北省秦皇岛市066004 [2]白城师范学院机械与控制工程学院

出　　处：《工具技术》2024年第5期84-88,共5页Tool Engineering

基　　金：国家自然科学基金(51975113)。

摘　　要：为探究磨削工艺参数对氧化锆陶瓷的磨削温度和法向磨削力的影响,通过单因素实验和支持向量机方法建立磨削温度、法向磨削力的一元模型,模型决定系数均大于0.93。基于一元模型对多元模型进行假设,由正交实验结果和蛇优化算法求解得到多元模型,并对模型进行验证。以温度、法向磨削力的多元数值模型作为目标函数,对温度和法向磨削力进行优化;基于蛇优化算法对工艺参数进行双目标优化,获得磨削工艺参数的最优解,验证实验结果表明,模型具有较高的精度,得到的最优工艺参数合理。In order to explore the influence of grinding process parameters on the grinding temperature and normal grinding force of zirconia ceramics,a univariate model of grinding temperature and normal grinding force is established by single factor test and support vector machine method,and the model coefficients are greater than 0.93.According to the monary model,the hypothesis of the multivariate model is proposed,and the multivariate model is obtained by the orthogonal experimental results and the snake optimization algorithm,and the model is verified.The multivariate numerical model of temperature and normal grinding force is used as the objective function to optimize the temperature and normal grinding force.Based on the snake optimization algorithm,the process parameters are double-objective optimized to obtain the optimal solution of the grinding process parameters,and the experimental results verify that the model has high precision,and the optimal process parameters obtained are reasonable.

关 键 词：支持向量机 蛇优化算法 参数优化 氧化锆陶瓷 

分 类 号：TG58[金属学及工艺—金属切削加工及机床] TH161[机械工程—机械制造及自动化]