Abstract: Due to the low extracting accuracy of sectional data segmentation point,which led to the poor precision of sectional curve reconstruction,a high-precision extraction method of segmentation point was proposed.The segmentation point of linear features and freeform features in G1 continuous was focused.The initial segmentation point was extracted according to curvature analysis and interactive experience,and the sectional data were divided based on the segmentation point.The linear features data were extracted and fitted,and the remaining data were fitted into spline curve.The judgment method was designed to obtain new and higher-precision segmentation point based on the fitted spline curve.By taking the new segmentation point as the boundary,the spline curve based on the tangency constraint with line was refitted.The proposed method could not only find segmentation point in existing data,but beyond the existing data points and find segment point more precisely between them.Examples showed that the extraction precision of segmentation point was greatly improved,and the reconstructed sectional curve was more suitable for the original design intent.

Key words: 2D cross-section, curve reconstruction, constrained optimization, segmentation point

摘要： 针对截面数据分段点提取精度不够而导致截面曲线重构精度差的问题,提出一种分段点精确提取方法。重点研究相邻特征为直线特征和自由特征在满足G1连续时分段点的精确提取。根据曲率分析并辅以交互经验提取初始分段点,以该分段点为界分割截面数据,提取出直线特征数据并拟合直线,剩余数据拟合样条曲线。根据拟合的样条曲线设计判定方法,得到新的精度更高的分段点。以新分段点为边界并基于与直线的相切约束重新拟合样条曲线。提出的分段点提取方法不但能够在现有数据中寻找分段点,而且可以超越现有数据点并在其之间寻找更精确的分段点。实例表明,该方法大大提高了分段点的提取精度,使重构的截面曲线更加符合初始设计意图。

关键词: 二维截面, 曲线重构, 约束优化, 分段点