Prof. Cecilia Surace Profile

Prof. Cecilia Surace

at Politecnico di Torino

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Proceedings Article | 9 May 2024 Presentation + Paper

Enhancing dynamics measurement from moving cameras through sensor-fusion motion compensation approaches

Lorenzo Peretto, Marco Civera, Cecilia Surace, Alessandro Sabato

Proceedings Volume 12951, 129510Z (2024) https://doi.org/10.1117/12.3009913

KEYWORDS: Cameras, Sensors, Motion measurement, Unmanned aerial vehicles, Video, UAV imaging systems, Signal filtering, Prototyping, Motion estimation, 3D image processing

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The use of cameras has gained popularity in the engineering world due to their ease of use and non-contact nature. The combined use of cameras and Unmanned Aerial Vehicles (UAVs) allows performing complex acquisition in hard-to-reach locations. However, due to the motion of the UAV, measurements can be inaccurate. This study focuses on the mitigation of UAV-induced motion, to enhance the measurement precision for structural dynamic assessment by proposing a combination of sensor-based and algorithm-based camera motion compensation approaches. The sensor-based approach relies on the use of a novel system integrating an Inertial Measurement Unit and two laser distance sensors to account for the low-frequency components of the motion. An Extended Kalman Filter algorithm is then implemented to improve the accuracy of five of the six degrees of freedom of motion. Laboratory experiments were performed to compare the displacement measured with the moving camera post-processed using the proposed method against a reference stationary camera. The results of the experiments showed that the proposed motion-correction method provides displacements that are in good agreement with the stationary camera and show a significant reduction of the induced motion. Further developed, this technique can be used in various applications where motion-corrected data must be obtained for accurate assessment of the dynamic properties of the targeted system.

Proceedings Article | 5 April 2017 Paper

Non-destructive monitoring of a prestressed bridge with a data-driven method

M. P. Limongelli, M. Tirone, C. Surace

Proceedings Volume 10170, 1017033 (2017) https://doi.org/10.1117/12.2258381

KEYWORDS: Bridges, Nondestructive evaluation, Diagnostics, Sensor networks, Sensors, Data modeling, Finite element methods, Phase modulation, Computer simulations

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Non-destructive vibration based methods can be used as diagnostic tool to identify damage in structures. Periodic inspections or permanent monitoring networks of sensors can indicate the emergence of possible damage occurring during the structure lifetime. Several methods have been proposed in literature for damage identification purposes. Some of them allow detecting the existence of damage, others provide information about its location as well. Data driven method are able to localize damage based solely on responses recorded on the structure without the need of a Finite Element model. Many of these methods are based on the detection of irregularities in the deformed shape of the structure: modal or operational shapes have been proposed to this purpose by different authors. The reliability of the methods proposed in literature is often verified on numerical models that, by their nature, cannot reproduce all the sources of uncertainties - environmental, operational, experimental - that affect responses recorded of the structure. The availability of data recorded on real structures provides precious material for the check of damage identification methods. In this paper the performance of the Interpolation Method for damage localization is investigated with reference to the real case study of a prestressed concrete road bridge, the S101 Bridge in Austria. The bridge, built in the early 1960, is a typical example of a European highway bridge. Responses to ambient vibration have been recorded both in the undamaged and in several different damage scenarios artificially inflicted to the bridge. Damage was introduced by lowering one of the bridge piers and by cutting prestressing tendons of one beam of the bridge deck.

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