数据-机理混合驱动下考虑刀具柔性的柔性加工工艺参数能效优化方法

A Data and Model Hybrid Driven Cutting Parameter Energy-efficiency Optimization Method for Flexible Machining Process Considering Cutting Tool Flexibility

在柔性加工过程中,加工任务不断变换导致加工刀具更换频繁,现有研究主要面向固定加工刀具开展工艺参数能效优化,无法快速响应加工刀具频繁更换的加工环境。为更好的满足变刀具条件下柔性加工工艺参数能效优化的需求,提出一种数据-机理混合驱动下考虑刀具柔性的柔性加工工艺参数能效优化方法。首先揭示变加工刀具条件下柔性加工能耗特性,构建数据-机理混合驱动的柔性加工能效优化模型,然后融合马尔科夫理论和优势动作评论算法,提出考虑刀具柔性的柔性加工工艺参数能效优化方法,最后通过案例分析与算法对比,验证所提出方法能在变刀具条件下实现柔性加工工艺参数的高效优化决策。

The change of machining tasks leads to frequent replacement of cutting tools in the flexible machining process.The current studies mainly focus on cutting parameter energy-efficiency optimization based on fixed cutting tool,which cannot cope with the dynamic change of cutting tools.To meet the demand of energy efficiency optimization under the condition of multiple cutting tools,a data and model hybrid driven cutting parameter energy-efficiency optimization method considering cutting tool flexibility is proposed.Specifically,the correlation between the energy consumption and cutting parameters under the condition of multiple cutting tools is analyzed,and a data and model hybrid driven cutting parameter optimization model is formulated.Then,the cutting parameter energy-efficiency optimization method considering cutting tool flexibility is proposed based on Markov Decision theory and Advantage actor-critic algorithm.Finally,the proposed method is demonstrated by extensive comparative experiments,and the results show that the proposed optimization method can effectively carry out cutting parameter optimization adapted to the dynamic change of cutting tool.