【摘要】 数控机床的能耗来源于工作时的电动机空载和切削过程中的负载消耗。分析切削过程中的切削速度、进给速度、切削深度等切削参数对数控机床能耗的影响;基于BP神经网络搭建数控机床能耗与切削参数的模型,简化了经验公式繁琐的计算过程;利用遗传算法对切削参数进行优化。对比试验表明:用优化后的参数进行加工,能明显地降低能耗,为加工过程能耗控制提供了一个良好的方案。更多还原

【Abstract】 The numerical control machine tool energy consumption is originated from the electric motor idle racing and the cutting process.The influences of cutting speed,feed speed,cutting depth on CNC machine tool energy consumption were analyzed.The model of CNC machine tool energy consumption and cutting parameters was established based on BP neural network,and calculating process of empirical formula was simplified.The cutting parameters were optimized by genetic algorithm.Experimental comparison shows energy consumption in cutting process can be significantly reduced by using optimized parameters.This method provides a good energy control scheme for machining process.更多还原