针对当前航空叶片检测需求日渐增大的问题,搭建了在线激光检测实验平台,开发设计了激光测量数据采集系统。对采集到的散乱点云数据进行了有效精简处理,并提出了一种入射倾角误差补偿策略。基于UG平台编写grip语言实现了理论轮廓线的快速提取。基本粒子群算法,探究了基于局部轮廓和整体轮廓的测量点集相对理论轮廓曲线的最优位姿匹配问题,实验结果表明选择基于整体轮廓可获得位姿匹配的最优解。对粒子群算法进行改进,求解了位姿匹配运动参数,结果表明,其计算精度明显高于基本粒子群算法的求解结果。

In view of the increasing demand for airborne blade measurement, an online laser detection experimental platform is established, and a laser measurement data acquisition system is developed. The collected scattered point cloud data are effectively reduced, and an incident tilt angle compensation strategy is proposed. Based on the UG platform, the grip language is used to realize the fast extraction of the theoretical contour. The basic particle swarm optimization algorithm is used to explore the optimal pose matching of the measured point set based on the local contour and the global contour. The experimental results show that the optimal solution of pose matching can be obtained by selecting the global contour. The particle swarm optimization algorithm is improved and the pose matching motion parameters are solved. The results show that, the computational accuracy is significantly improved compared with that by the basic particle swarm optimization algorithm.