针对航空发动机叶片传统人工检测结果显示不直观、误检率和漏检率高的问题，开展了基于叶片超声点云的三维成像方法研究。通过对超声C扫成像原理、空间曲面显示技术、三维着色模型以及可视化技术的研究，完成了超声点云三维重建模型的显示。利用Delaunay三角剖分算法对叶片点云进行重构，结果显示该重构算法效果较好；建立了基于OpenGL的三维着色模型，将一般的着色映射空间由RGB颜色空间改为CIELAB颜色空间，使得缺陷区域的显示更加合理；采用C#.NET与软件MATLAB混合编程的方法完成了超声点云的解析和显示，所运用的三维可视化方法能直观显示叶片缺陷在整体模型中的具体位置，使检测人员能够对三维显示后的模型进行全方位观测，以便于对缺陷区域的快速定位和检测，极大地提高了检测的效率和准确性。

Aiming at the problems of being non intuitive, of high false detection rate and high undetected rate of traditional artificial detection results of aero-engine blades, a 3-D imaging method based on blade ultrasonic point cloud is proposed. The display of ultrasonic point cloud 3-D reconstruction model is completed through the research of ultrasonic C-scan imaging principle, space surface display technology, 3-D shading model and visualization technology. The results show that the reconstruction algorithm is effective by using Delaunay triangulation algorithm to reconstruct the blade point cloud. A 3-D shading model based on OpenGL is established, and the general shading mapping space is changed from RGB color space to CIELAB color space, which makes the display of defect area more reasonable. The analysis and display of ultrasonic point cloud are accomplished by using the method of mixed programming of C#.NET and MATLAB. The specific location of blade defects in the overall model can be visually shown by using the 3-D visualization method. It enables the inspectors to observe the 3-D model in an all-round way, which facilitates the rapid location and detection of defect areas, and greatly improves the efficiency and accuracy of detection.