基于同轴图像传感的激光焊接过程质量监测技术

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英文篇名：Quality monitoring technology of laser welding process based on coaxial image sensing 作者：宫建锋 ; 李慧知 ; 李俐群 ; 王刚 英文作者：GONG Jianfeng;LI Huizhi;LI Liqun;Wang Gang;State Key Laboratory of Advanced Welding and Joining,Harbin Institute of Technology;Xi'an Aerospace Power Test Technology Institute; 关键词：激光焊接 ; 同轴图像传感 ; 质量在线监测 ; 缺陷识别 英文关键词：laser welding;;coaxial image sensing;;online quality monitoring;;defect identification 中文刊名：HJXB 英文刊名：Transactions of the China Welding Institution 机构：哈尔滨工业大学先进焊接与连接国家重点试验室;西安航天动力试验技术研究所; 出版日期：2019-01-25 出版单位：焊接学报 年：2019 期：v.40 基金：国家重点研发计划支持项目(2016YFB1102100);; 国家自然科学基金资助项目(51675129) 语种：中文; 页：HJXB201901008 页数：8 CN：01 ISSN：23-1178/TG 分类号：43-48+168-169

摘要

针对激光焊接过程中由于参数不匹配、装配误差等原因造成的焊接过程不稳定等焊接缺陷,基于同轴图像传感技术,建立起一套激光焊接过程中的质量在线监测系统,对焊接过程中的熔池图像进行了采集分析及其熔池特征信息的提取.结果表明,在激光功率为1 500 W的不等厚不锈钢薄板激光焊接试验条件下,焊接过程中的不稳定、下塌缺陷以及焊偏现象与熔池形状各特征信息变化具有一定的相关性.结合BP神经网络算法对所提特征信息进行分类、识别,基于LabVIEW软件平台,可实现相应缺陷的自动化识别及报警功能.
        Aim at the welding defects,such as instability,due to parameter mismatch and assembly error during welding process,an online system for monitoring quality of laser welding was built based on coaxial image sensing technology to collect,which analyzed and extracted the characterisitic information from the welding pool during laser welding process.Results showed that instability,collapse defect and weld misalignment were associated with the characteristic of the welding pool in the condition of laser welding unequal thickness stainless steel sheet with laser power of 1 500 W.Combining BP neural networks algorithm,the monitoring system can realize the automatic identification and alarm function of the corresponding defects based on LabVIEW platform.

引文

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