PSI - Issue 17

Francisco Barros et al. / Procedia Structural Integrity 17 (2019) 986–991 Author name / Structural Integrity Procedia 00 (2019) 000 – 000

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4. Conclusions

A workflow for digital image correlation using video sequences captured by a moving camera and relying on features found in background objects for calibration has been demonstrated. It enables the DIC analysis to be performed without a calibration procedure, as long as there are fixed objects that can be seen behind or near the area to be analysed. It is expected that the developed method is applicable to structural monitoring in locations of difficult access which could be reached by a UAV carrying a camera. Unlike a UAV carrying a stereo camera system, it cannot deal with transient loads, as the stereo images are taken at different times; however, the implementation is simpler and more versatile, and there are no restrictions with regards to the distance between cameras, which, in the case of an integrated stereo system, has to be small enough that a single UAV can carry the entire system. After the application of the speckle pattern and a reference of known size before testing starts, no further preparation of the monitored structure or object is necessary. For a test at a certain point in time to be made, it is only necessary to capture an image-pair which shows the speckled surface from two distinct positions while also containing some of the objects initially used as references for calibration. The authors gratefully acknowledge the funding of Project NORTE-01-0145-FEDER-000022 - SciTech - Science and Technology for Competitive and Sustainable Industries, co-financed by Programa Operacional Regional do Norte (NORTE2020) through Fundo Europeu de Desenvolvimento Regional (FEDER). Pedro J. Sousa gratefully acknowledges the FCT (Fundação para a Ciência e a Tecnologia) for the funding of the PhD scholarship SFRH/BD/129398/2017. Dr. Moreira acknowledges POPH - QREN-Tipologia 4.2 - Promotion of scientific employment funded by the ESF and MCTES. Pedro Moreira and Paulo Tavares further acknowledge FEDER through Programa Operacional Competitividade e Internacionalização – Compete2020 and Fundos Nacionais through FCT – Fundação para a Ciência e a Tecnologia through project PTDC/EME-EME/29339/2017 - Monitorização Multiescala de Fendas. References Hartley, R., & Zisserman, A. (2003). Multiple View Geometry in Computer Vision. Cambridge University Press. Khadka A., D. Y. (2019). Structural Health Monitoring of Wind Turbines Using a Digital Image Correlation System on a UAV. Em B. J. Niezrecki C., Rotating Machinery, Optical Methods & Scanning LDV Methods. Cham: Springer. Lowe, D. G. (2004). Distinctive Image Features from Scale-Invariant Keypoints. International Journal of Computer Vision, 60 (2), 91-110. Reagan, D. S. (2018). Feasibility of using digital image correlation for unmanned aerial vehicle structural health monitoring of bridges. Structural Health Monitoring, 17 (5), 1056 – 1072. Wu, C. (2013). Towards Linear-Time Incremental Structure from Motion. 2013 International Conference on 3D Vision - 3DV 2013 , (pp. 127-134). Seattle. Acknowledgements