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.
ORCID iDs
Williams, B., Suryasentana, S. ORCID: https://orcid.org/0000-0001-5460-5089, Perry, M. ORCID: https://orcid.org/0000-0001-9173-8198 and Donaldson, K.;-
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Item type: Conference or Workshop Item(Paper) ID code: 86356 Dates: DateEvent14 September 2023Published1 July 2023AcceptedSubjects: Technology > Engineering (General). Civil engineering (General) > Environmental engineering Department: Faculty of Engineering > Civil and Environmental Engineering Depositing user: Pure Administrator Date deposited: 02 Aug 2023 11:44 Last modified: 11 Nov 2024 17:09 URI: https://strathprints.strath.ac.uk/id/eprint/86356