测量点云数据残缺特征重建理论及方法

项目名称： 测量点云数据残缺特征重建理论及方法

项目编号： No.51305307

项目类型： 青年科学基金项目

立项/批准年度： 2014

项目学科： 机械、仪表工业

项目作者： 刘俊

作者单位： 武汉大学

项目金额： 24万元

中文摘要： 在复杂零件形状检测、反求工程等应用中存在大量点云数据，测量点云中往往存在数据残缺。本项目以现有研究为基础，分析残缺数据的工程实质，研究基于特征的测量点云残缺数据重建理论及方法；综合几何造型、特征识别、约束推理、知识融合等原理，探索残缺特征设计意图识别、残缺形状构造及工程约束恢复的有效方法，提出可靠的残缺特征重建理论及算法。该项研究有利于多学科知识的交叉融合，其成果可解决当前点云数据重建的技术难题，发展并完善 CAD 反求设计理论及方法，提高反求设计智能化程度，为产品创新设计提供更强大的工具，为后续CAPP/CAM提供完备的产品特征信息，有利于产品的快速制造。项目成果将为国产具有自主知识产权的数字化设计软件系统提供重要的理论和技术支撑。

中文关键词： 点云数据；残缺特征；特征重构；约束推理；

英文摘要： The reconstruction of incomplete feature in measuring point cloud data is a key issue to be resolved.Based on existing work, this project analysis the engineering essence of incomplete feature, study the theory and methods of feature-based reverse modeling. With the integrated use of geometric modeling,feature recognition, constraint reasoning and knowledge fusion, we sudy the design intent detection, shape reconstruction and engineering constraint restoration for incomplete feature, present reliable theory and method for incomplete feature reconstruction. On the basis of theoretical study, develop next generation prototype system of reverse design, and verify with typical mechanical products. This project will benefit the interdisciplinary integration , solve the technical problems of incomplete feature reconstrucion in reverse engineering, improve the theory and method of CAD reverse design, improve the level of intelligence for reverse design, provide a powerful tool for product innovative design, provide complete product feature information for downstream CAPP/CAM process, benefit the rapid manufacturing of products.Results of the project will provide important theoretical and technical support for the domestic digital design system with independent intellectual property rights.

英文关键词： point cloud data；incomplete feature；feature reconstruction；constraint reasoning；