基于数据驱动的激光切割工艺参数优化方法研究综述

Review on Data-driven Optimization for Laser-cutting Process Parameters

近年来,数据驱动的激光切割工艺参数优化方法受到广泛关注和研究。因此,对该领域的主要研究进展进行梳理。对比基于数据驱动和基于机理模型的激光切割工艺参数优化方法,并明确数据驱动方法的研究对象。从工艺参数和工艺质量两个方面归纳当前数据驱动激光切割工艺参数优化的研究思想及进展,并总结已有研究中采用的数据驱动方法。概述数据驱动激光切割工艺参数优化的具体实现手段。总结比较各种数据驱动参数优化方法的优劣,并展望该领域未来值得进一步研究的方向,包括完善数据获取和数据增强方法,加强模型和算法的评估,并探索更高效智能的实现手段。

In recent years,data-driven optimization methods for laser cutting process parameters have received extensive attention and research.Therefore,the major research advances in this field are summarized.Data-driven and mechanism model-based laser cutting process parameter optimization methods are compared,and the research object of data-driven methods is clarified.The current research ideas and progress of data-driven laser cutting process parameter optimization are summarized in terms of both process parameters and process quality,and the data-driven methods used in existing studies are characterized.The specific implementation means of data-driven laser cutting process parameter optimization is outlined.The advantages and disadvantages of various data-driven parameter optimization methods are summarized and compared.Future directions for further research in this area are outlined,including improving data acquisition and data enhancement methods,enhancing the evaluation of models and algorithms,and exploring more efficient and intelligent means of implementation.