PointNet ++ Based Welding Fixture Parts Identification
Welding fixture is an important part in the welding production line of automobile body in white.Effective management and induction of welding fixture parts design modulus can significantly improve the design efficiency.In this paper,the original design model is discretized into a point cloud,and an intelligent classification method of welding fixture parts is discussed by using the point cloud data and Pointnet ++ deep learning network.By comparing the classification accuracy of each model,the single scale grouping(SSG)model with the highest operating efficiency and accuracy is selected to complete the classification of welding fixture parts.The training results show that the accuracy of the proposed method on the verifica-tion set is 97.5%,and the accuracy of the verification set of the type block,the connection block,the posi-tioning pin,the pin seat and the support are 92.5%,97.5%,100%,97.5%and 100%,respectively.These results show that the proposed method has high recognition accuracy and can meet the accuracy require-ments of welding fixture parts classification.
welding fixturethree-dimensional point cloudclassificationPointNet ++
NETL
NSTL
万方数据
