反求工程中切片数据处理及断面特征曲线全局优化技术

SLICING DATA PROCESSING AND GLOBAL OPTIMIZATION OF FEATURE CURVE IN REVERSE ENGINEERING

针对基于特征的反求工程中,各种曲面特征处理技术的研究已经比较深入,平面切片数据的特征处理技术研究相对不足的现状,研究并实现了处理切片数据的离散曲率分析、数据分段、特征识别和基于连续性约束的断面特征曲线全局优化技术,使获得的断面特征曲线在满足约束的同时对数据点的逼近误差达到最小。应用实例表明,通过点云切片和断面特征曲线全局优化技术进行反求工程曲面模型重建,可以显著提高曲面重建的效率和曲面的质量。

In reverse engineering, so as to obtain a featurebased parametric model, surface feature extraction techniques are deeply studied in recent years. However, another same important problem that how to extract sectional feature curves from slicing data points is almost disregarded. Aiming at solving the issue, the discrete curvature estimating, data segmentation, feature recognition and constraint-based global optimization of slicing data are studied and realized. With these techniques, the best fitting curves can be acquired, and the continuity constraints between the curves can be satisfied too. The application proves that surface construction based on feature curves can greatly improve the efficiency of modeling and accuracy of model in reverse engineering.