Interference Detection Algorithm of Aircraft Components Assembly based on Measured Data
- DOI
- 10.2991/nceece-15.2016.162How to use a DOI?
- Keywords
- Point cloud; Assembly; Feature; Interference detection; Algorithm
- Abstract
Parts manufacture deviation may cause interference in aircraft components assembly, and the handling of interference is a complex work. In order to solve this problem, the paper proposes an interference detection method based on measured data. First, the assembly feature was obtained by fitting the point cloud (PC) data, then the feature was used to align PC model with theoretical assembly model, so that the PC model could be placed at theoretical position. Furthermore, individual parts were marked and paired in accordance with whether they form interfaces (only direct surface-to-surface contact between components), and the interfaces were regionally partitioned from the complete model. Finally, a series of parallel sections were used to perform intersection operation on the fitted surfaces, and the intersecting point set on each section needed curve fitting so as to calculate the interference and clearance values. This method can quickly calculate the interference distribution of actual assembly parts. Based on the interference, the handling of follow-up assembly could be guided quantitatively. The feasibility and validity of this method are demonstrated by an aircraft wing box case, proving that it can improve the efficiency of aircraft components assembly.
- Copyright
- © 2016, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Wei Zhang AU - Luling An AU - Qilin Jiang AU - Ruiheng Xiao PY - 2015/12 DA - 2015/12 TI - Interference Detection Algorithm of Aircraft Components Assembly based on Measured Data BT - Proceedings of the 2015 4th National Conference on Electrical, Electronics and Computer Engineering PB - Atlantis Press SP - 892 EP - 898 SN - 2352-5401 UR - https://doi.org/10.2991/nceece-15.2016.162 DO - 10.2991/nceece-15.2016.162 ID - Zhang2015/12 ER -