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DRONE-DARE - Drone imaging for Digital twinning and AI Reliability-based damage Evaluation
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Abstract
The project aims to advance damage detection techniques for aerospace structures using vibration-based and visual methodologies. The focus is assessing the health conditions of reinforced panels and wing boxes constructed from metallic or composite materials. The proposed approach involves measuring the structure's deformed configuration and dynamic characteristics. The collected data and high-fidelity numerical finite element solutions will be utilized to train a neural network, potentially within a probabilistic framework to enhance accuracy and account for uncertainties associated with operational conditions. This network will determine damage properties such as structural damage location and severity. In addition to utilizing data obtained through techniques like Digital-Imagine Correlation (DIC)and Operational/Experimental Modal Analysis, real-time images captured by a drone flying around the object will also be incorporated into the network.
People involved
- Erasmo Carrera (Principal Investigator)
- Matteo Filippi (Component of the research team)
- Alfonso Pagani (Component of the research team)
Structures
Partners
- POLITECNICO DI TORINO - AMMINISTRAZIONE CENTRALE - Coordinator
- TEORESI S.P.A.
- UNIVERSITA' DEGLI STUDI DI NAPOLI FEDERICO II
Keywords
ERC sectors
Sustainable Development Goals
Budget
| Total cost: | € 306,900.00 |
|---|---|
| Total contribution: | € 295,400.00 |
| PoliTo total cost: | € 149,250.00 |
| PoliTo contribution: | € 149,250.00 |