Abstract
Unmanned aerial vehicles (UAVs), known as drones, is an advanced remote sensing technology gaining much interest in the field of civil engineering in the last few years. According to the Association of Unmanned Vehicle Systems International, it is estimated that drones have the potential of reaching an economic benefit of US $82 billion by 2025. This paper investigates novel strategies for the visual inspection assessment and damage detection of bridge condition by maximizing the full potential of UAVs remote technology combined with advanced camera vision methods. The investigation starts by assessing the functionality of modern UAVs and matching the capabilities to the requirements of bridge monitoring. This is important as the driving force behind the technology development of drones has not come from bridge maintenance, but it is important that we exploit the new technologies and the same argument is also true for image processing. The paper explores how these assessment techniques can be transferred on to a UAV platform. The paper not only looks at the important technical issues such as camera stabilization both from flight control and image processing but also the use of UAVs as an inspection and measuring device. The investigation makes use of both laboratory experiments and field trials to assess the effectiveness of the proposed schemes.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Lydon D, Taylor SE, Robinson D, Lydon M, Hester, D (2017) Development of a vision based SHM for bridge damage identification. In: Proceedings of the 8th international conference on structural health monitoring of intelligent infrastructure. SHMII-8, Brisbane, Australia, pp 5–8
Hallermann N, Morgenthal G (2014) Visual inspection strategies for large bridges using unmanned aerial vehicles (UAV). In: 7th international conference on bridge maintenance, safety and management, IABMAS. IJCAI'81, Shanghai, China, pp 661–667
Spencer BF, Ruiz-Sandoval M, Kurata N (2004) Smart sensing technology for structural health monitoring. In: Proceedings of the 13th world conference on earthquake engineering. Vancouver, Canada, pp 1791–1803
Kim J-W, Kim S-B, Park J-C, Nam J-W (2015) Development of crack detection system with unmanned aerial vehicles and digital image processing. In: Proceedings of the world congress on advances in structural engineering and mechanics. ASEM15, Incheon, Korea, pp 25–29
Schauwecker K, Ke NR, Scherer SA, Zell A (2012) Markerless visual control of a quadrotor micro aerial vehicle by means of on-board stereo processing autonomous mobile systems. In: Proceedings of the autonomous mobile systems Conference. Berlin, Germany, pp 11–20
Hassanalian M, Abdelkefi A (2017) Classifications, applications and design challenges of drones: a review. Prog Aerosp Sci 91:99–131
Vergouw B, Nagel H, Bondt G, Custers B (2016) Drone technology: types, paylods, applications, frequency spectrum issues and future developments. In: Custers B (eds) The future of drone use. information technology and law series, vol 27. T.M.C. Asser Press, The Hague
Mittleider A, Griffin B, Detweiler C (2015) Experimental analysis of a UAV-based wireless power transfer localization system. Exp Robot 109:357–371
Polydorou E, Robinson D, Treanor G, Taylor S, McGetrick P (2019) A new method for vibration-based damage detection in structural health monitoring using autonomous UAVs. In: Proceedings of the bridge engineering institute conference. BEI, Honolulu, Hawaii
Polydorou E, Robinson D, Treanor G, Taylor S, McGetrick P (2018) Vision-based deformation and free vibration measurements of beams using unmanned aerial vehicles (UAVs). In: Proceedings of the civil engineering research in Ireland, Dublin, Ireland
Lydon M, Robinson D, Taylor SE, Amato G, Brien EJO (2017) Improved axle detection for bridge weight-in-motion systems using fiber optic sensors. J Civ Struct Heal Monit 7:325–332
Martinez J, Orrite C, Herrero JE (2007) An efficient particle filter for color-based tracking in complex scenes. In: Proceedings of the international conference on advanced video and signal-based surveillance, AVSS, IEEE. IEEE conference, London, U.K., pp 317–332
Tomasi C, Kanade T (1991) Detection and tracking of point features. Carnegie Mellon University Technical Report, pp 91–132
Bruce DL, Kanade T (1981) An iterative image registration technique with an application to stereo vision. In: Proceedings of the 7th international joint conference on artificial intelligence. IJCAI'81, Vancouver, Canada, pp 674–679
Ye Z, Wang L, Xu W, Gao Z, Yan G (2017) Monitoring traffic information with a developed acceleration sensing node. Sensors 17(12):1–16
Stauffer C, Grimson WEL (1999) Adaptive background mixture models for real-time tracking. In: Proceedings of the computer society conference on computer vision and pattern recognition. USA, pp 2246–2252
Girshick R, Donahue J, Darrell T, Malik J (2004) Rich feature hierarchies for accurate object detection and semantic segmentation. In: Proceedings of the conference on computer vision and pattern recognition, IEEE. IJCAI'81, Vancouver, Canada, pp 580–587
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2021 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
Polydorou, E., Robinson, D., Taylor, S., McGetrick, P. (2021). Health Monitoring of Structures Using Integrated Unmanned Aerial Vehicles (UAVs). In: Rainieri, C., Fabbrocino, G., Caterino, N., Ceroni, F., Notarangelo, M.A. (eds) Civil Structural Health Monitoring. CSHM 2021. Lecture Notes in Civil Engineering, vol 156. Springer, Cham. https://doi.org/10.1007/978-3-030-74258-4_17
Download citation
DOI: https://doi.org/10.1007/978-3-030-74258-4_17
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-74257-7
Online ISBN: 978-3-030-74258-4
eBook Packages: EngineeringEngineering (R0)