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机构地区:[1]西安交通大学机械学院,西安710049 [2]上海交通大学机械学院,上海200030
出 处:《西安交通大学学报》2004年第7期661-664,共4页Journal of Xi'an Jiaotong University
基 金:国家高技术研究发展计划资助项目(2 0 0 2AA41 41 1 0 )
摘 要:在分析角度-弦高联合准则法和包围盒法的工程适用特点的基础上,提出了同时基于角度-弦高简化法和包围盒法的改进型数据的直接精简方法,即利用包围盒法构造分割面,利用分割面将数据点云处理成按扫描线存储的"结构化"测量数据,再利用角度-弦高联合准则法逐线精简.随后以铸造模板、汽车发动机罩及人头像为典型实例,分别对具有不同表面特征的测量数据点云进行了数据精简验证.结果表明,提出的方法同时具备2种数据精简方法的优点,且克服了该2种方法无法处理曲率变化大、附加特征多的表面测量数据的局限性,能够对测量数据进行直接而有效地简化,因此可以用于处理具有复杂附加特征的散乱测量数据.Based on analyzing the applicability of chord and angle-deviation criterion and enveloping box method, an improved direct data reduction method was proposed, in which two exiting combined-enveloping box methods was applied to construct the segmenting planes, then process the data cloud into structured measured data stored according to the scanning lines; the chord-angle deviation criterion was adopted to reduce the data sequentially. Some typical cases, such as casting molding board, automobile engine cover and human-head sculpture, were chosen to verify this data reduction method. It is found that newly proposed method possesses the advantages of both chord-angle deviation and enveloping box methods and breaks up the limitations of these two methods in case of sharp curvature variations and multiple additional features in measured data. Thus it can be utilized to reduce data directly and efficiently, especially the scattered data with complex additional features.
分 类 号:TH16[机械工程—机械制造及自动化]
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