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Article Dans Une Revue Engineering Applications of Artificial Intelligence Année : 2023

Using Conceptual Graph modeling and inference to support the assessment and monitoring of bridge structural health

Résumé

Effective bridge maintenance requires sufficient and accurate knowledge on structural health. However, despite the development of structural health monitoring (SHM) and inspection aids, bridge structural health monitoring remains challenging. This work proposes a comprehensive predictive description based on Conceptual Graphs (CG), of the bridge condition deterioration mechanism, with the formalization of the inspection history. The model combines formalized assumptions with several deterioration factors and expert knowledge to assess the evolution of the structural condition. The model is based on logical and graphical descriptions of the deterioration of the structural condition thanks to the use of the CG modeling. Through the graphical inference, the evolution of the apparent condition and the deterioration time can be assessed. The application to two bridge cases highlights the interest of this approach to help understanding the sequence of deterioration. The actual condition obtained and the formalized inspection history allow a better decision.
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Dates et versions

hal-04651910 , version 1 (17-07-2024)

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Sylvain Ndinga Okina, Franck Taillandier, Louis Ahouet, Quynh Anh Hoang, Denys Breysse, et al.. Using Conceptual Graph modeling and inference to support the assessment and monitoring of bridge structural health. Engineering Applications of Artificial Intelligence, 2023, 125, pp.106665. ⟨10.1016/j.engappai.2023.106665⟩. ⟨hal-04651910⟩
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