Manufacturing feature recognition based on point cloud deep learning

被引：0

作者：

Lyu C. ^{[1
]}

Huang D. ^{[1
]}

Liu T. ^{[1
]}

Zhou Y. ^{[1
]}

Bao J. ^{[1
]}

机构：

[1] School of Mechanical Engineering, Donghua University, Shanghai

来源：

Jisuanji Jicheng Zhizao Xitong/Computer Integrated Manufacturing Systems, CIMS | 2023年 / 29卷 / 03期

关键词：

3D object classification; deep learning; manufacturing feature recognition; point cloud;

D O I：

10.13196/j.cims.2023.03.006

中图分类号：

学科分类号：

摘要：

In computer aided design and manufacturing systems, the manufacturing feature recognition is a key technology. Aiming at the problems of poor scalability and robustness of traditional feature recognition technology, a manufacturing feature recognition method based on point cloud deep learning was proposed. A point cloud dataset of manufacturing features was constructed by sampling uniformly on the surface of manufacturing features. The K -nearest neighbor algorithm was used to construct a rotation-invariant representation of the point cloud, and a point cloud classification network incorporating geometric prior knowledge was proposed. For the point cloud data of the model with multiple features, an extraction method of the point cloud of manufacturing features and a separation method of intersecting features were proposed. Practical experiments were carried out to demonstrate the effectiveness of the proposed method, and the results illustrated that the method could effectively recognize single features and interacting features for CAD models. © 2023 CIMS. All rights reserved.

引用

页码：752 / 765

页数：13

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