复杂曲面零件在机测量数据高效提取方法
陶冶*，吴年汉，熊艳
（四川大学 机械工程学院，四川 成都 610065）
摘要：针对复杂曲面零件“在机测量－数据处理－数控加工”一体化制造中海量密集点云数据的实时处理、存储与传输难题，以实现预设精度下数据高效精简为目标，提出了一种基于空间样条渐进细分法则的复杂曲面零件在机测量数据提取方法。该方法利用双三次空间样条对初始提取点集进行插值并求解偏差，在最大偏差处插入原始采样点以实现渐进细分，直至数据提取精度满足预设值。实验结果表明该方法较现有的弦高差方法具有更好的数据精简性能及误差分布光顺性。
关键词：数据提取；在机测量；空间样条；复杂曲面零件
中图分类号：TH124；P204 文献标志码：A doi：10.3969/j.issn.1006-0316.2019.10.001
文章编号：1006－0316 (2019) 10－0001－08
Efficient Data Extraction Method for On-Machine Measurement of Complex Surface Parts
TAO Ye，WU Nianhan，XIONG Yan
( School of Mechanical Engineering, Sichuan University, Chengdu 610065, China )
Abstract：In order to improve the performance of real-time processing, storage and transmission of massive dense point cloud data in the integrated manufacturing process which consists of on-machine measurement, data processing and CNC machining of complex surface parts, an efficient extraction method for on-machine measurement data of complex surface parts based on the rule of spatial spline progressive subdivision is proposed to achieve efficient extraction of point cloud data under preset accuracy. It uses the bi-cubic spatial spline to interpolate the initial set of extraction point and calculate the deviation, and then inserts the original sampling point where the deviation is largest to further the progressive subdivision until the data extraction precision reaches the preset value. The results show that the method has significantly improved data reduction efficiency compared with the traditional chord height difference method.
Key words：data extraction；on-machine measurement；spatial spline；complex surface parts
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收稿日期：2019－08－22
基金项目：国家自然科学基金项目（51505310）；四川省科技计划重点研发项目（2018GZ0282）
作者简介：陶冶（*通讯作者）（1984－），男，辽宁抚顺人，博士，副教授，主要研究方向为智能制造与智能装备、创新设计理论与方法、复杂机电系统精密测量与控制等。
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