基于机器视觉的激光焊接熔池图像处理与特征提取

Image Processing and Feature Extraction of Laser Welding Pool Based on Machine Vision

基于机器视觉,对激光焊接熔池图像处理与特征提取进行了研究。结果表明,分析光纤激光深熔焊接熔池监测结果,包括熔透状态、焊接宽度焊缝偏差跟踪监测及线监测。在不同焊接速度及焊接功率条件下,搭建焊接监测系统可实现光纤激光深熔焊接熔池的实时监测,其精度可达到激光焊接的要求。熔池和热影响区在深熔焊接过程中,焊接速度变化对其焊接过程中显著的影响。熔透现象可改变散热条件造成熔池几何特征量的差异。提前对熔宽变化系数进行确定,对焊接过程中是否会因为激光深熔焊接导致的熔透现象进行分析研究。并且对亚像素角点的分布情况以及分布范围等进行实时追踪和监控,对于焊接缝隙的变化、熔池几何特征向量的变化情况,均可以通过焊缝偏差现象对焊接进行有效判断。

Based on machine vision, the image processing and feature extraction of laser welding pool were studied in this paper. The results show that the monitoring results of optical fiber laser deep penetration welding pool are analyzed, including penetration status, weld width deviation tracking monitoring and line monitoring. Under the condition of welding speed and different welding power, the welding monitoring system can realize the real-time monitoring of optical fiber laser deep penetration welding pool, and its accuracy can meet the requirements of laser welding. In the process of deep penetration welding, the change of welding speed has a significant effect on the welding process. The penetration phenomenon can change the heat dissipation condition and cause the difference of the geometrical characteristic quantity of the molten pool. Determine the coefficient of change of weld width in advance, and judge whether there is penetration in the welding process. Track and monitor the distribution range of sub-pixel corner points and the trend of weld pool characteristics, and effectively judge the welding through the phenomenon of weld deviation.