Artificial Intelligence (AI) driven 3D point scanner for monitoring soil plug hazards during the installation of suction caisson foundations

Williams, B. and Suryasentana, S. and Perry, M. and Donaldson, K. (2023) Artificial Intelligence (AI) driven 3D point scanner for monitoring soil plug hazards during the installation of suction caisson foundations. In: 9th International SUT OSIG Conference, 2023-09-12 - 2023-09-14.

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Abstract

Soil plug hazards pose a significant risk to the successful installation of suction caisson foundations but are currently inadequately monitored using only a single beam echosounder. To address this issue, a new artifi-cial intelligence (AI) driven three-dimensional (3D) point scanner is proposed for monitoring soil plug haz-ards. The proposed scanner is controlled using a Bayesian Optimisation (BO) algorithm, which automatical-ly adapts its data acquisition path in real-time based on previously acquired measurements. Preliminary la-boratory tests were conducted to assess the effectiveness of the proposed scanner. The results showed that the proposed scanner can accurately estimate 3D surfaces with fewer measurement points than a comparable scanner using the conventional scanning method, typically used in existing 3D point scanners. As the pro-posed scanner can estimate the state of the entire surface in much shorter time than existing sensors, it poten-tially offers a more effective method to monitor soil plug hazards.

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