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基于等离子体特征信号的激光焊接过程动态监控技术研究进展
引用本文:王 腾,陈珏铨,金小莉.基于等离子体特征信号的激光焊接过程动态监控技术研究进展[J].河北科技大学学报,2017,38(1):1-6.
作者姓名:王 腾  陈珏铨  金小莉
作者单位:;1.华南师范大学计算机学院
基金项目:国家自然科学基金(51505158);广东省自然科学基金(2014A030310153)
摘    要:在大功率激光焊接过程中,激光辐照金属材料气化而产生等离子体,影响激光能量与工件之间的耦合,从而最终直接影响到激光焊接质量。光致等离子体的研究是大功率深熔焊领域的一个热点,也是焊接过程质量检测自动化中一个很有潜力的研究方向。近年来,基于等离子体特征信号的激光焊接过程动态监控技术研究主要集中在等离子体信号检测和激光焊接过程建模的方向。介绍了激光焊接中的光致等离子体行为,并对基于等离子体特征信号的激光焊接过程动态监控技术的国内外研究现状进行了分析,总结了目前该领域存在的问题,提出了未来的发展方向。

关 键 词:模式识别  光致金属蒸气特征  大功率激光焊  最小二乘支持向量回归  多核学习
收稿时间:2015/10/19 0:00:00
修稿时间:2016/1/6 0:00:00

Research progress of laser welding process dynamic monitoring technology based on plasma characteristics signal
WANG Teng,CHEN Juequan and JIN Xiaoli.Research progress of laser welding process dynamic monitoring technology based on plasma characteristics signal[J].Journal of Hebei University of Science and Technology,2017,38(1):1-6.
Authors:WANG Teng  CHEN Juequan and JIN Xiaoli
Abstract:During the high-power laser welding process, plasmas are induced by the evaporation of metal under laser radiation, which can affect the coupling of laser energy and the workpiece, and ultimately impact on the reliability of laser welding quality and process directly. The research of laser-induced plasma is a focus in high-power deep penetration welding field, which provides a promising research area for realizing the automation of welding process quality inspection. In recent years, the research of laser welding process dynamic monitoring technology based on plasma characteristics is mainly in two aspects, namely the research of plasma signal detection and the research of laser welding process modeling. The laser-induced plasma in the laser welding is introduced, and the related research of laser welding process dynamic monitoring technology based on plasma characteristics at home and abroad is analyzed. The current problems in the field are summarized, and the future development trend is put forward.
Keywords:pattern recognition  characteristics of laser-induced metal vapor  high-power laser welding  least squares support vector regression  multiple kernel learning
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