Fewer bridges collapsing thanks to artificial intelligence?

(28-06-2021) In her PhD thesis 'Monitoring Vietnamese Bridges Using Vibration Based Damage Detection Method and Machine Learning’, Huong Duong Nguyen investigates how AI can contribute to faster bridge damage detection.

Bridge operators monitor the condition of existing bridges. This inspection of bridges is often done with non-destructive methods, such as X-ray, ultrasound and visual inspection. With these methods, bridge operators can only detect damage on or near the surface of the structure.

However, vibration-based damage detection (VBDD) methods can look deeper into the structure and identify damage early, thusreducing maintenance costs and extending the service life of structures.

The aim of this thesis is to detect damage to bridges and structures using vibration measurement data in combination with the use of machine learning or artificial intelligence.

Machine learning means that computers discover how to perform tasks without being explicitly programmed to do so. In this process, computers learn from the data provided to perform certain tasks.

"With my research, I want to contribute to more sustainable and safer bridges in the future", concludes Huong Duong Nguyen.


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Contact: Huong Duong Nguyen

Huong Duong Nguyen


Editor: Jeroen Ongenae - Final editing: Ilse Vercruysse - Illustrator: Roger Van Hecke