摘要
用Nd…YAG脉冲激光器对0.5mm厚TC4钛合金薄板进行了焊接实验。设计了与光路同轴的机器视觉系统,并利用高速电荷耦合器件(CCD)实时获取焊斑图像。通过采用辅助照明光源有效提高了焊斑成像质量。采用基于细胞神经网络的算法进行焊斑边缘提取。通过对焊斑图像的分析可以获得薄板穿孔或熔深不足的信息,以此作为反馈控制信号对脉冲激光功率进行实时调整。实验证明,该方法可有效减少薄板穿孔和熔深不足缺陷的发生,提高TC4钛合金薄板激光焊接的质量。
TC4 titanium alloy thin plates with the thickness of 1.5 mm are welded by Nd…YAG pulsed laser.A coaxial machine vision system that used high speed charge coupled device（CCD） is designed to acquire welded spot pictures.The welded spot pictures quality is significantly improved with the help of auxiliary illuminant.The welded spot edges are extracted by means of cellular neural network algorithm.The information of thin plate fenestration or insufficient depth of fusion can be acquired by analysis of welded spot pictures,and it is used as an input signal for closed-loop control.Experimental results demonstrat that this method can efficiently reduce thin plate fenestration or insufficient depth of fusion improve the welding quality.
出处
《中国激光》
EI
CAS
CSCD
北大核心
2012年第1期71-74,共4页
Chinese Journal of Lasers
基金
天津市高校科技发展基金(20070809)资助课题
关键词
激光技术
激光焊接
机器视觉
细胞神经网络
闭环控制
laser technique
laser welding
machine vision
cellular neural network
closed-loop control
