基于双判定准则的航空发动机叶片缺陷孔洞的边界提取

航空发动机叶片缺陷孔洞的几何形状复杂、位置分布散乱且曲率变化明显,使用单一判定准则难以完整地提取其边界特征点。为实现叶片缺陷孔洞边界的精准提取和孔洞边界线的平滑拟合,提出了一种基于双判定准则的航空发动机叶片缺陷孔洞边界特征点的提取算法。该算法采用K–Dimension tree(K–D树)建立点云的空间拓扑结构,以采样点及其K邻域点为参考依据构建拟合平面,将采样点的空间坐标转化为平面坐标。通过融合采样点的法向夹角判定准则与邻域场力矢量和判定准则,采用加权的方式获得采样点的特征值与判别阈值作为边界特征点的判定依据。通过两组试验验证了该算法的有效性和准确性,试验结果表明,该方法可有效提取复杂缺陷孔洞模型的边界特征点。

Boundary Extraction of Defect Hole of Aero-Engine Blades Based on Double Decision Criteria

Due to the complex geometry,scattered position distribution,and obvious curvature change of the defect holes in aero-engine blades,it is difficult to extract the boundary feature points completely by using a single criterion.To realize the accurate boundary extraction of blade defect holes and smooth fitting of the holes boundary line,an algorithm for extracting boundary feature points of aero-engine blade defect holes based on double criteria was proposed.The fitting plane was established based on the spatial topological structure of the sampling point and its K neighborhood points,which transformed the three–dimensional coordinates into two–dimensional coordinates by the local coordinate system.By fusing the criterion of the normal angle of sampling points with the adjacent field power force criterion,the eigenvalue and discrimination threshold of sampling points are obtained by the weighted method,which can be used as the criterion for extracting boundary feature points.The validity and accuracy of the algorithm were verified by two sets of experiments,the experimental results demonstrate that the method can effectively extract the boundary feature points in complex holes model.