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Parameter optimization of wire electric discharge machining process using GA and PSO

机译:基于GA和PSO的线放电加工工艺参数优化。

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Wire Electric Discharge Machining (WEDM) is one of the important non-traditional machining processes for machining of intricate profiles in conductive and difficult to machine materials. The machining performance of this process largely depends on various process parameters, such as applied voltage, ignition pulse current, pulse-off time, pulse duration, serve controlled reference mean voltage, servo-speed variation, wire speed, wire tension and injection pressure. As WEDM is a complex process, it is difficult to determine optimal parameters for improving cutting performance, which is cutting velocity and surface finish. It is important to note that it is not possible to have a unique set of optimal combination of cutting parameters as the influence of the above cutting parameters on both the responses are opposite to each other. The present paper deals with the multi-objective optimization of WEDM process using evolutionary algorithms, such as non-dominated sorted genetic algorithm and Practical Swarm Optimization. As the WEDM process contains two objectives, a multi-objective optimization criterion is used.
机译:线材放电加工(WEDM)是重要的非传统加工工艺之一,用于加工导电和难加工材料中的复杂轮廓。该过程的加工性能在很大程度上取决于各种过程参数,例如施加的电压,点火脉冲电流,脉冲关闭时间,脉冲持续时间,伺服受控参考平均电压,伺服速度变化,线速度,线张力和注射压力。由于WEDM是一个复杂的过程,因此很难确定用于提高切削性能的最佳参数,即切削速度和表面光洁度。重要的是要注意,不可能有一组唯一的切削参数的最佳组合,因为上述切削参数对两个响应的影响是相反的。本文采用进化算法,如非支配排序遗传算法和实用群算法,对电火花线切割工艺的多目标优化进行了研究。由于WEDM过程包含两个目标,因此使用了多目标优化准则。

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