Intelligent recognition algorithm for hull segment closure surface components based on improved PointNet++
[Objectives]The point cloud data of hull segment closure obtained by a 3D scanner has such ad-vantages as high precision and large data volume,and can accurately reflect the construction status of segment closure.Since the existing PointNet++network is unable to process large-capacity point cloud data,an al-gorithm based on improved PointNet++is proposed to realize the intelligent recognition of components for large-capacity hull segment convergence surface point cloud data.[Methods]Based on the hypervoxel growth theory,the hull segment closure point cloud data is segmented and simplified,and a hull segment clos-ure point cloud data set is constructed and used to train a PointNet++network improved by deep learning the-ory.[Results]The convergence results of the network model on the training and testing sets of hull seg-ment closure surface point cloud data tend to be stable,achieving an accuracy rate of 90.012%on the testing set.[Conclusions]The proposed method has good recognition ability and can achieve the intelligent recog-nition of hull segment closure surface components.
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