Online from: 1929
Subject Area: Mechanical & Materials Engineering
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|Title:||Foreign object debris surveillance network for runway security|
|Author(s):||Weishi Chen, (School of Electronics and Information Engineering, Beihang University, Beijing, China), Qunyu Xu, (School of Electronics and Information Engineering, Beihang University, Beijing, China), Huansheng Ning, (School of Electronics and Information Engineering, Beihang University, Beijing, China), Taosheng Wang, (Communication Navigation and Command Automation Institute, Equipment Academy of Air Force, Beijing, China), Jing Li, (China Academy of Civil Aviation Science and Technology, Beijing, China)|
|Citation:||Weishi Chen, Qunyu Xu, Huansheng Ning, Taosheng Wang, Jing Li, (2011) "Foreign object debris surveillance network for runway security", Aircraft Engineering and Aerospace Technology, Vol. 83 Iss: 4, pp.229 - 234|
|Keywords:||Aerospace industry, Aviation, Aviation safety, Detection, Detection, FOD, Network, Security, Surveillance|
|Article type:||Research paper|
|DOI:||10.1108/00022661111138648 (Permanent URL)|
|Publisher:||Emerald Group Publishing Limited|
|Acknowledgements:||The authors wish to acknowledge the support from the 47th China Postdoctoral Science Foundation and the Important National Science & Technology Specific Projects on the development and application validation of the next generation sensing network for civil airport perimeter anti-intrusion monitoring.|
Purpose – Foreign object debris (FOD) poses a significant hazard to aviation safety and brings huge economic losses to the aerospace industry due to aircraft damage and out-of-service delays. Different schemes and sensors have been utilized for FOD detection. This paper aims to look into a video-based FOD detection system for airport runway security and propose a scheme for FOD surveillance network establishment.
Design/methodology/approach – The FOD detection algorithm for the system is analyzed in detail, including four steps of pre-processing, background subtraction, post-processing and FOD location.
Findings – The overall algorithm is applied to two sets of live video images. The results show that the algorithm is effective for FOD targets of different shades under different lighting conditions. The proposed system is also evaluated by the ground-truth data collected at Nanyang Airport.
Practical implications – The runway security can be greatly increased by designing an affordable video-based FOD detection system.
Originality/value – The paper presents critical techniques of video-based FOD detection system. The scheme for FOD surveillance network, as a significant part of aviation risk management at airports, is applicable and extensible.
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