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考虑生产实际的需求,综合最小变形误差、最大金属切除率和最大刀具耐用度建立端铣工艺参数多目标优化模型。通过对粒子群全局寻优能力和灰色理论的适应性综合分析,研究提出耦合粒子群算法(Particle Swarm Op-timization,PSO)和灰色关联(Gray Relevancy Analysis,GRA)的多目标工艺参数优化算法。该方法将多目标函数的优化问题转化为优化单项灰关联度,得到了多项工艺指标要求下的参数优化组合。将该方法应用在多目标工艺参数优化设计中取得了满意的结果,表明其具有很大的适应性。
Considering the practical needs of the production, the multi-objective optimization model of the end milling process parameters is established based on the minimum deformation error, the maximum metal removal rate and the maximum tool durability. Through comprehensive analysis of global optimization ability of particle swarm optimization and gray theory, the optimization algorithm of multi-objective process parameters of Particle Swarm Op-timization (PSO) and Gray Relevancy Analysis (GRA) is proposed. The method transforms the optimization problem of multi-objective function into the optimization of single gray relational degree, and obtains the optimal combination of parameters under the requirements of multiple technological indexes. The method has been applied to optimize the design of multi-objective process parameters and achieved satisfactory results, indicating that it has great adaptability.