基于AdvantEdge仿真和粒子群算法的切削参数优化方法

Cutting Parameters Optimization Based on AdvantEdge Simulation and Particle Swarm Optimization Algorithm

为了智能化地提供最优车削工艺参数,以碳排放低、加工时间短和加工成本低为目标,构建了车削加工的工艺参数优化模型,并应用多目标粒子群优化(MPSO)对模型进行求解。此外,考虑到目前切削力和切削温度的理论计算模型难以准确反映切削过程的热力场变化,通过切削仿真软件AdvantEdge进行仿真,获得切削参数与切削力、切削温度之间的关系。最后,以300M钢的加工为例对模型进行验证,通过CNC车床上的切削实验验证了由MPSO获得的切削参数,实验证明该研究方法提供的切削参数能很好的在碳排放、加工时间和加工成本间达到平衡,为车削加工选取合适的工艺参数提供了技术支持。

To provide the optimal turning parameters intelligently,the paper constructs the optimization model of turning parameters with the goal of low carbon emission,short processing time and low processing cost,and solves the model with multi-objective particle swarm optimization(MPSO).In addition,considering that the current theoretical calculation model of cutting force and cutting temperature is difficult to accurately reflect the thermal field changes in the cutting process,the relationship between cutting parameters and cutting force and cutting temperature is obtained through the simulation of professional cutting simulation software AdvantEdge.Finally,the model is verified by taking the machining of 300M steel as an example.The cutting parameters obtained by MPSO are verified by cutting experiments on CNC lathes.The experiments prove that the cutting parameters provided by the research methods in this paper can well balance carbon emissions,processing time and processing costs,and provide technical support for selecting appropriate process parameters for turning.