학술논문

A Systematic Point Cloud Edge Detection Framework for Automatic Aircraft Skin Milling
Document Type
Periodical
Source
IEEE Transactions on Industrial Informatics IEEE Trans. Ind. Inf. Industrial Informatics, IEEE Transactions on. 20(1):560-572 Jan, 2024
Subject
Power, Energy and Industry Applications
Signal Processing and Analysis
Computing and Processing
Communication, Networking and Broadcast Technologies
Image edge detection
Milling
Skin
Aircraft
Point cloud compression
Three-dimensional displays
Aircraft manufacture
Accurate 3-D measurement
aircraft skin
automatic edge milling
edge detection
Language
ISSN
1551-3203
1941-0050
Abstract
The edge detection technique is an essential step for aircraft skin milling in aviation manufacturing. Most of the current detection methods focus on traditionally defined edge extraction tasks but disregard the crucial systematic requirement of edge milling. In this article, we proposed a novel edge detection framework for automatic edge milling of aircraft skins. First, an edge probability detector is proposed by the spatial tangent continuity to provide the essential reference. Second, we propose a hierarchical branch searching method to hierarchically strip the desired milling edges from the raw point cloud, which consists of the following three graded progressive steps: branch backbone generation, branch extension, and branch pruning. We demonstrate the performance of the proposed method on both synthetic models and aircraft skin workpieces. The proposed method outperforms the other baselines and shows accurate edges for the edge milling task.