摘要
在产品反求工程中,通过激光扫描所获取的数据点云通常十分庞大,且具有一定的杂乱性和冗余性,因此,如何处理这样大批量的数据点云便成为基于激光扫描测量造型的主要问题。文中在总结前人经验的基础上,提出一种自适应最小距离法数据精简准则。这种方法不但继承了最小距离法数据精简快速、高效的优点,而且更好地保留了原始数据的细节特征,同时也提高了CAD模型重构的速度和精度。通过实例详细阐述了该方法的算法原理和数据处理过程,并验证了其有效性。
In product reverse engineering, the data points obtained through laser surveying are enormous and eomplicated. So, how to dispose this kind of data points is becoming the main problem of basing laser surveying modeling. In view of the foundation of forefather experience, a kind of data reduction method -variable minimum distance method was proposed in this paper. Such as is the detailing process： At first, numbers of the nosing data points are filtered through human-computer interaction way; Then, the data points are divided into different zero by curvature analyzing; At last, to data points in different zero, appropriate minimum distance is selected to reduce. This kind of method not only follows the merits of the speeder and more effective of minimum distance method, but better preserves the detail character of initial data, at the same time, improves the speed and the precision of CAD model rebuilding. The algorithm prineiple and the data procedure are explanted in detail by example in this paper, and its validity is verified.
出处
《机械管理开发》
2011年第4期16-18,20,共4页
Mechanical Management and Development
关键词
反求工程
曲率分析
自适应最小距离法
数据精简
reverse engineering
curvature analyzing
adaptive minimum distance method
data reduction
