Cheng Xiaolei
Intelligent Information Department, Wanbo Institute of Science and Technology, Hefei 230031, Anhui, China.
Hefei University of Technology, Hefei 230009, Anhui, China.
Comput Intell Neurosci. 2022 Apr 12;2022:7062052. doi: 10.1155/2022/7062052. eCollection 2022.
The current pipeline surface generation algorithm cannot get the angle information of the corner of complex pipeline surface, which leads to the poor accuracy of the algorithm, the slow speed of 3D point cloud intelligent mosaic, and the large number of effective points. Therefore, a CAD surface generation algorithm for complex pipeline model under the background of Industry 4.0 is designed, extracting and rendering the wireframe model and extracting background of the complex pipeline video. We obtain the angle information of the corner points of the complex pipeline surface, extract and match the feature of the dense point cloud, and construct the 3D point cloud data mosaic model. The pipe surface is generated by using double-nodal B-spline. The experimental results show that the precision and stability of the proposed method are high. In the early stage, the proposed method uses ISS feature extraction algorithm to extract feature of point cloud data, which improves the positioning accuracy effectively and enhances the 3D point cloud intelligent stitching speed.
当前的管道曲面生成算法无法获取复杂管道曲面拐角处的角度信息，导致算法精度较差、三维点云智能拼接速度缓慢且有效点数较多。因此，设计了一种工业4.0背景下复杂管道模型的CAD曲面生成算法，提取并渲染复杂管道视频的线框模型和背景。我们获取了复杂管道曲面拐角点的角度信息，提取并匹配密集点云的特征，构建了三维点云数据拼接模型。通过双节点B样条曲线生成管道曲面。实验结果表明，该方法的精度和稳定性较高。在前期，该方法使用ISS特征提取算法提取点云数据的特征，有效提高了定位精度并提升了三维点云智能拼接速度。
