首页|Tiny hole inspection of aircraft engine nacelle in 3D point cloud via robust statistical fitting
Tiny hole inspection of aircraft engine nacelle in 3D point cloud via robust statistical fitting
扫码查看
点击上方二维码区域，可以放大扫码查看
原文链接
NSTL
Elsevier
? 2022 Elsevier LtdIn the aircraft manufacturing industry, drilling hole inspection is a vital task for the noise reduction ability and the aircraft structure stability. Due to the complexity of the inner surface of the engine nacelle, inspecting drilling holes of a small size and a large number is fairly challenging. In this paper, we propose a framework for automatic hole inspection on composite flat parts. The raw data of traditional 3D laser scanning usually contain considerable noise and outliers, which has a great influence on tiny hole inspection. First, to perform measurement efficiently and to get raw data of good quality, we design a measurement platform to perform automatic measurement on a preset path. Instead of applying common boundary detection methods, we design a method to detect boundary points by evaluating the boundary possibility of each point, which is more likely to detect the points on a real hole boundary than noise. Based on the characteristics of laser scanning data, we then combine an effective algebraic circle fitting method with an iterative fitting strategy and develop a robust circle fitting method. The improved circle fitting method is capable of estimating a circle closest to the ground truth. Experiments demonstrate that our fitting method performs better than other common fitting methods for comparison under both synthetic and real scanning data.
NSTL
Elsevier
