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Multi-sensor data fusion with AI-RBFN in settlement surveillance of embankment dams: application to a rockfill dam in Algeria

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Abstract

This article deals with the subject of monitoring the settlements of embankment dams, taking as an example Kerrada’s dam, located in Algeria, and made of rockfill with a central clay core. To analyse the evolution of the deformations, it proposes a multidisciplinary approach which combines geotechnical measurements of settlements and geodetic measurements of levelling. These two types of measurements are diagnosed by the so-called multi-sensor data fusion (MDF) method. In this method, we use “a first level of fusion” which allows us to estimate the settlements on the surface of the dam. Then this estimation is improved during fusion at “a second level” by introducing an interpolation by artificial intelligence of the radial basis functions of neural networks (AI-RBFN), with three AI-RBFNs algorithms, which are the conventional (Newrb), the exact (Newrbe) and the generalized regression of neural networks (Grnn). To generate the settlements of the entire surface of the dam. The goals of MDF use aims to provide better accuracy, robustness against uncertainty and reliable spatiotemporal integration. However, the appropriate surface interpolation by AI-RBFNs aims to handle cases of insufficiency in observations (spatiotemporal) and low-number sensors. The MDF results obtained, in terms of average displacement value and value of the empirical settlement index (SI), were found to be satisfactory. In addition, the MDF-AI-RBFNs model has achieved an improvement rate in the accuracy of 81% compared to that obtained with the geotechnical data only. These results reinforce the need to continue in the study of the optimization of the MDF model by the heuristic algorithm of AI.

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  1. Kaddour Chouicha

    Present address: Faculty of Civil Engineering and Architecture, Laboratory of Materials, Mohammed Boudiaf University of Sciences and Technology of Oran, BP 1505, 31000, Oran, Algeria

  2. Attaouia Belhadj, Salem Kahlouche & Bachir Gourine

    Present address: Centre of Space Techniques, Algerian Space Agency, Space Geodesy Department, BP 13, 31200, Arzew, Algeria

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  1. Faculty of Civil Engineering and Architecture, Laboratory of Materials, Mohammed Boudiaf University of Sciences and Technology of Oran, BP 1505, 31000, Oran, Algeria

    Attaouia Belhadj

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Belhadj, A., Chouicha, K., Kahlouche, S. et al. Multi-sensor data fusion with AI-RBFN in settlement surveillance of embankment dams: application to a rockfill dam in Algeria. J Civil Struct Health Monit 13, 1151–1170 (2023). https://doi.org/10.1007/s13349-023-00691-8

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