大功率盘形激光焊多特征参数同步检测  

Synchronous detection of multi-feature parameters during high-power disk laser welding

作　　者：孙燕[1,2] 高向东 萧振林[2] 陈晓辉 李秀忠 SUN Yan;GAO Xiangdong;XIAO Zhenlin;CHEN Xiaohui;LI Xiuzhong(School of Electromechanical Engineering,Guangdong University of Technology,Guangzhou 510006,China;GRG Banking Equipment Co.,Ltd.,Guangzhou 510663,China;Foshan Polytechnic,Foshan 528137,China)

机构地区：[1]广东工业大学广东省焊接工程技术研究中心,广东广州510006 [2]广电运通金融电子股份有限公司,广东广州510663 [3]佛山职业技术学院,广东佛山528137

出　　处：《电焊机》2018年第7期72-75,共4页Electric Welding Machine

基　　金：国家自然科学基金(51675104);广东省科技计划项目(2016A010102015);佛山市科技创新专项资金项目(2014AG10015)

摘　　要：以大功率盘形激光焊接304不锈钢为研究对象,分别使用近红外波段高速摄像机、紫外波段和可见光波段高速摄像机同时摄取焊接过程匙孔、金属蒸汽和飞溅瞬态图像。定义匙孔、金属蒸汽以及飞溅为焊接过程特征参数,并将其动态特征作为神经网络的输入参数,以焊缝宽度作为衡量焊接状态的参数和神经网络的输出参数,建立多特征参数同步采集的盘形激光焊接过程检测模型。与单一特征参数检测试验对比发现,多特征参数同步检测方法能够更好地反映大功率盘形激光焊接状态。During disk laser welding bead-on-plate welding of type 304 austenitic stainless steel plates,a near infrared band highspeed camera,an ultraviolet band high-speed camera and a visible light band high-speed camera are used to capture the dynamic images of the keyhole,plume and spatters in the laser welding at the same time. The keyhole,plume and spatters are defined as the characteristic parameters of welding process,and the dynamic characteristics are considered as the output parameters of the neural network,and the weld width is considered as a parameter reflecting the welding status and the input parameter of the neural network. A technique that uses multifeature information fusion of keyhole,plume and spatters to obtain the welding status of high-power disk laser welding based on neural network technology is presented. The defined keyhole,plume and spatters characteristic parameters are considered as inputs to calculate theoretical weld width. The proposed BP neural network has been successfully tested in a real time disk laser welding process.

关 键 词：大功率盘形激光焊 多特征参数 焊接状态 同步检测 

分 类 号：TG456.7[金属学及工艺—焊接]