Research on Detection Method of Weld Image Feature Information Based on YOLOv5
In order to meet the needs of automatic process and obtain more clear original images of welds,a feature point extraction algorithm based on YOLOv5 and structured light was proposed.Firstly weld images were obtained by laser vision system and pre-trained by the improved YOLOv5 algorithm.Then Steger algorithm was used to extract the structured light centerline,Harris algorithm was used to process the centerline image,and the coordinates of weld coordinate points were determined.Finally coordinate information was transmitted to PLC,and controled the cross slide table to drive the welding torch to track the welding seam.The experimental results show that the improved YOLOv5 algorithm has larger mAP value,higher stability and stronger robustness.
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