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数控加工是当今机械制造业系统中普遍采取的一种加工方法,为实现数控切削加工中的高效性及减少碳排放,建立以加工过程中最小加工时间和最小碳排放量为目标函数的的多目标的切削参数优化模型,综合考虑实际加工生产中的各种约束条件,实现基于多工步环境下对切削速度和进给量的同步优化。运用粒子群算法与人工鱼群算法融合以改善人工鱼群算法的优化性能,并将其用于对所建模型的优化,通过具体案例验证了改进的人工鱼群算法具有较高的精度和较好的收敛性。
CNC machining is a commonly used machining method in today’s machinery manufacturing system. In order to achieve high efficiency and reduce carbon emissions in CNC machining, it is suggested that the minimum machining time and the minimum carbon emission during machining be the objective function Target optimization model of cutting parameters, considering all kinds of constraints in actual machining production, to achieve synchronous optimization of cutting speed and feed rate based on multi-step environment. The particle swarm algorithm is combined with the artificial fish swarm algorithm to improve the performance of the artificial fish swarm algorithm, which is used to optimize the model. The improved artificial fish swarm algorithm is proved to have high precision Good convergence.