Abstract
Digital Image Correlation (DIC) has proven itself to be a highly versatile and accurate method to measure 2D and 3D displacement, deformation, and strain in a wide range of structures and objects. A major advantage is that it is a non-contact, full-field measurement technique; it measures phenomena across the entire target object without having to attach sensors directly to the object. Despite the ability to measure many static and dynamic phenomena, the cameras and data acquisition equipment are almost exclusively set up in a static configuration. The cameras are often mounted on tripods and remain positioned in the same location while taking measurements. Such an immobile measurement platform prevents DIC from being employed to measure objects in inaccessible locations, such as bridges and tall buildings. An unmanned aerial vehicle carrying digital image correlation cameras has high mobility and can easily access regions on structures that would otherwise be too expensive or dangerous to measure with conventional static camera setups. This paper presents the development and testing of a prototype mobile digital image correlation platform. The resulting platform carries all of the necessary equipment on-board the drone and can be controlled by a single user with a remote control. It is shown that the prototype drone platform is capable of taking accurate and repeatable measurements while airborne. This drone aims to be used for vibration measurement and structural health monitoring of structures such as wind turbines and bridges.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Anderson, K., Gaston, K.J.: Lightweight unmanned aerial vehicles will revolutionize spatial ecology. Front. Ecol. Environ. 11, 138–146 (2013)
Tang, L., Shao, G.: Drone remote sensing for forestry research and practices. J. For. Res. 26, 791–797 (2015)
Baqersad, J., Poozesh, P., Niezrecki, C., Avitabile, P.: Photogrammetry and optical methods in structural dynamics – a review. Mech. Syst. Signal Process. 86(1), 17–34 (2017.) https://doi.org/10.1016/j.ymssp.2016.02.011
Sarrafi, A., Poozesh, P., Mao, Z.: A comparison of computer-vision-based structural dynamics characterizations. In: Barthorpe, R., Platz, R., Lopez, I., Moaveni, B., Papadimitriou, C. (eds.) Model Validation and Uncertainty Quantification, Volume 3: Proceedings of the 35th IMAC, a Conference and Exposition on Structural Dynamics 2017, pp. 295–301. Springer International Publishing, Cham (2017). https://doi.org/10.1007/978-3-319-54858-6_29
Javh, J., Slavič, J., Boltežar, M.: Measuring full-field displacement spectral components using photographs taken with a DSLR camera via an analogue Fourier integral. Mech. Syst. Signal Process. 100, 17–27 (2018)
Javh, J., Slavič, J., Boltežar, M.: High frequency modal identification on noisy high-speed camera data. Mech. Syst. Signal Process. 98, 344–351 (2018)
Busca, G., Cigada, A., Mazzoleni, P., Tarabini, M., Zappa, E.: Static and dynamic monitoring of bridges by means of vision-based measuring system. In: Cunha, A. (ed.) Topics in Dynamics of Bridges, vol. 3, pp. 83–92. Springer, New York (2013). https://doi.org/10.1007/978-1-4614-6519-5_9
Lee, J.J., Shinozuka, M.: A vision-based system for remote sensing of bridge displacement. NDT & E International. 39, 425–431 (2006.) https://doi.org/10.1016/j.ndteint.2005.12.003
Busca, G., Cigada, A., Mazzoleni, P., Zappa, E.: Vibration monitoring of multiple bridge points by means of a unique vision-based measuring system. Exp. Mech. 54, 255–271 (2014). https://doi.org/10.1007/s11340-013-9784-8
Kim, S.-W., Kim, N.-S.: Dynamic characteristics of suspension bridge hanger cables using digital image processing. NDT & E International. 59, 25–33 (2013.) https://doi.org/10.1016/j.ndteint.2013.05.002
Baqersad, J., Poozesh, P., Niezrecki, C., Avitabile, P.: A noncontacting approach for full-field strain monitoring of rotating structures. J. Vib. Acoust. 138, 031008–031008 (2016). https://doi.org/10.1115/1.4032721
Baqersad, J., Niezrecki, C., Avitabile, P.: Full-field dynamic strain prediction on a wind turbine using displacements of optical targets measured by stereophotogrammetry. Mech. Syst. Signal Process. 62, 284–295 (2015). https://doi.org/10.1016/j.ymssp.2015.03.021
Baqersad, J., Niezrecki, C., Avitabile, P.: Extracting full-field dynamic strain on a wind turbine rotor subjected to arbitrary excitations using 3D point tracking and a modal expansion technique. J. Sound Vib. 352, 16–29 (2015). https://doi.org/10.1016/j.jsv.2015.04.026
Sarrafi, A., Poozesh, P., Niezrecki, C., Mao, Z.: Mode extraction on wind turbine blades via phase-based video motion estimation. In: SPIE Smart Structures and Materials+ Nondestructive Evaluation and Health Monitoring, pp. 101710E–1101712. International Society for Optics and Photonics. Portland, Oregon, United States (2017)
Poozesh, P., Sarrafi, A., Mao, Z., Avitabile, P., Niezrecki, C.: Feasibility of extracting operating shapes using phase-based motion magnification technique and stereo-photogrammetry. J. Sound Vib. 407, 350–366 (2017)
Lundstrom, T., Baqersad, J., Niezrecki, C.: Monitoring the dynamics of a helicopter main rotor with high-speed Stereophotogrammetry. Exp. Tech. 40(3), 907–919 (2015). https://doi.org/10.1111/ext.12127
Rizo-Patron, S., Sirohi, J.: Operational modal analysis of a helicopter rotor blade using digital image correlation. Exp. Mech. 57, 367–375 (2017). https://doi.org/10.1007/s11340-016-0230-6
Kim, J.-W., Kim, S.-B., Park, J.-C., Nam, J.-W.: The 2015 World Congress on Advances in Structural Engineering and Mechanics (ASEM15), Incheon, Korea, August 25–29 (2015)
Reagan, D., Sabato, A., Niezrecki, C., Yu, T., Wilson, R.: An autonomous unmanned aerial vehicle sensing system for structural health monitoring of bridges. Proc. SPIE. 9804, 980414–980411 (2016)
Lundstrom, T., Niezrecki, C., Avitabile, P.: Appropriate rigid body correction of Stereophotogrammetry measurements made on rotating systems. Exp. Tech. 39(6), 25–34 (2013). https://doi.org/10.1111/ext.12030
Lundstrom, T., Baqersad, J., Niezrecki, C., Avitabile, P.: Using high-speed stereophotogrammetry techniques to extract shape information from wind turbine/rotor operating data. In: 30th IMAC, A Conference on Structural Dynamics, 30 Jan 2012–2 Feb 2012, Springer New York, Jacksonville, pp. 269–275 (2012). https://doi.org/10.1007/978-1-4614-2419-2_26
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 The Society for Experimental Mechanics, Inc.
About this paper
Cite this paper
Catt, S., Fick, B., Hoskins, M., Praski, J., Baqersad, J. (2019). Development of a Semi-autonomous Drone for Structural Health Monitoring of Structures Using Digital Image Correlation (DIC). In: Niezrecki, C., Baqersad, J. (eds) Structural Health Monitoring, Photogrammetry & DIC, Volume 6. Conference Proceedings of the Society for Experimental Mechanics Series. Springer, Cham. https://doi.org/10.1007/978-3-319-74476-6_7
Download citation
DOI: https://doi.org/10.1007/978-3-319-74476-6_7
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-74475-9
Online ISBN: 978-3-319-74476-6
eBook Packages: EngineeringEngineering (R0)