Research on condition assessment method of submarine cable based on artificial intelligence algorithm

Guofeng Liu

doi:10.1117/12.2684543

19 October 2023 Research on condition assessment method of submarine cable based on artificial intelligence algorithm

Guofeng Liu

Proceedings Volume 12709, Fourth International Conference on Artificial Intelligence and Electromechanical Automation (AIEA 2023); 1270906 (2023) https://doi.org/10.1117/12.2684543
Event: Fourth International Conference on Artificial Intelligence and Electromechanical Automation (AIEA 2023), 2023, Nanjing, China

Abstract

Submarine cables can provide energy and communications for offshore platforms, offshore wind farms, and other offshore projects, and are known as the "Deep Sea Lifeline." It is of great significance to ensure the safety and reliability of deep-sea exploration and development to evaluate the health status of submarine cables, give early warning of their possible faults, and carry out targeted maintenance work accordingly. Therefore, this paper proposes a state assessment method for submarine cables based on long short-term memory (LSTM) network. Firstly, a submarine cable state evaluation index system considering dynamic and static data is constructed. Then, the prediction model of marine cable online monitoring data based on the LSTM network is established, and the ultra-short-term prediction value is obtained. Secondly, combined with the inspection and test data, the improved analytic hierarchy process (AHP) and entropy weight method were used to calculate the subjective and objective weights, and then the improved triangular trapezoid membership function and fuzzy statistical test method were used to finally get the multi-period state assessment results of submarine cables. Finally, the marine cable of an offshore oil and gas project is taken as an example to test the feasibility and effectiveness of the method.

Citation Download Citation

Guofeng Liu "Research on condition assessment method of submarine cable based on artificial intelligence algorithm", Proc. SPIE 12709, Fourth International Conference on Artificial Intelligence and Electromechanical Automation (AIEA 2023), 1270906 (19 October 2023); https://doi.org/10.1117/12.2684543

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