大型薄壁零件在机测量数据高效提取方法与关键技术研究

项目名称： 大型薄壁零件在机测量数据高效提取方法与关键技术研究

项目编号： No.51505310

项目类型： 青年科学基金项目

立项/批准年度： 2016

项目学科： 机械、仪表工业

项目作者： 陶冶

作者单位： 四川大学

项目金额： 19万元

中文摘要： 国防、航空航天领域的某类大型薄壁零件，随着其使役性能要求的提高，零件尺寸越来越大、相对制造精度越来越高，“在机测量-本机或远程在线数据处理-数控加工”的一体化制造方法是保证这类零件加工要求的有效技术手段。大空间尺寸薄壁零件在机测量中，若采用常规的数据采样和数据提取方法，会使数据点云急剧膨胀，造成数据本机存储或在线远程传输的阻塞、丢失。因此，探求大型薄壁零件的在机测量数据高效提取方法极有必要。本项目面向测量-加工一体化制造和网络化制造中的测量数据可靠、高效获取需求，重点研究基于空间样条渐进细分法则的扫描数据在线提取、多参量测量数据耦合映射机理及其关联描述、共性设计特征驱动的相似密集点云数据精炼表示、基于本体映射的测量数据网络化协同优化等新方法和新技术，并以火箭共底构件、导弹战斗部壳体为典型件进行综合实验和应用验证。本项目的研究工作对于提升我国大型薄壁零件的高质高效制造技术水平具有积极意义。

中文关键词： 数据提取；大型薄壁零件；在机测量；本体映射

英文摘要： There are certain types of large thin-walled parts in defense and aerospace. With the improvement of performance requirements, the size of parts becomes larger and the manufacturing precision becomes higher. ‘On-machine measuring, local or remote-online data processing, CNC machining’ integrated manufacturing method is an effective technical means for ensuring processing requirements of these parts. In the measuring process, if we use conventional methods of data sampling and extraction, measuring data may be blocked or lost during the data storage stage or online remote transmission. Therefore, exploring efficient data extraction method for on-machine measurement is necessary. This project meets the needs of reliably and efficiently data obtaining for networked manufacturing and measurement integrated process, proposes a kind of on-line data extraction method based on space progressive spline segments, multi-parameter measuring data coupled-map mechanism and its associated data description, data refining of similar point cloud based on common design features, network collaborative optimization of measuring data based on ontology mapping, then take rocket common base component and missile warhead as typical parts for comprehensive test and application verification. This project will make a positive contribution to enhance the high quality and efficient manufacturing technology of large thin-walled parts in China.

英文关键词： data extraction;large thin-walled parts;on-machine measurement;ontology mapping