基于等离子体特征信息的激光焊缝熔透性监测方法

Method of laser weld penetration monitoring based on plasma characteristic information

激光焊接虽然效率高,但操作难度大,焊接的工件很容易出现缺陷,发生未熔透或过度熔透的问题,导致焊接质量不合格。面对这种情况,为实现对焊接工件的有效检验,实施激光焊缝熔透性监测是十分必要的。在研究中利用高速相机采集等离子体形貌图像采集并实施四项预处理,去除图像中的干扰信息。提取等离子体形貌图像的四种特征信息,包括质心宽度、质心高度、质心摆角、等离子体面积。基于BP神经网络来构建离子体特征信息与激光焊缝熔透性类型之间的映射关系模型,以特征信息为输入,输出熔透性概率值,概率值更接近1对应的类型就是监测出来的熔透性结果。

Although laser welding has high efficiency,it is difficult to operate.The welded workpiece is prone to defects,incomplete penetration or excessive penetration,leading to unqualified welding quality.Facing this situation,in order to realize the effective inspection of the welding workpiece,it is very necessary to implement the laser weld penetration monitoring.In the research,the height camera is used to collect the plasma topography image and carry out four pre-processing to remove the interference information in the image.Four kinds of feature information of plasma topography image are extracted,including centroid width,centroid height,centroid swing angle and plasma area.Based on BP neural network,the mapping relationship model between the ionomer feature information and the laser weld penetration type is constructed.With the feature information as the input,the penetration probability value is output.The type whose probability value is closer to 1 is the monitored penetration result.