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Open Access

Research on multimodal data fusion evaluation method for subsea structures based on acoustic-optical joint detection

Ledong Power Plant, China Energy Co. Ltd., Ledong 572500, China
Hainan Institute, Zhejiang University, Sanya 572025, China
Hainan Provincial Engineering Research Center for Marine Environment Monitoring and Detection Equipment, Sanya 572025, China
Hainan Zhihui Xiang Technology Co. Ltd., Haikou 570100, China
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Abstract

Offshore underwater artificial structures (e.g., sea transmit pipeline) are susceptible to instability due to long-term hydrodynamic impacts, biological attachment or blockage, which requires regular detection and precise inspection. Grounded in the concept of multi-source data fusion, this study proposes an acoustic-optical multimodal joint diagnostic methodology. By integrating three underwater monitoring technologies—multibeam bathymetry, dual-frequency imaging sonar, and optical imaging from remote operated vehicle (ROV)—an acoustic-optical-topographic comprehensive data evaluation framework is established, with spatiotemporal registration and dynamic quantitative analysis methods for multi-sensor. Field tests demonstrate that this approach enables accurate defect identification in certain complex marine conditions, significantly improves detection efficiency compared to conventional methods, and effectively mitigates reconstruction errors induced by scouring. The findings provide valuable insights for the intelligent operation and maintenance of marine engineering structures such as offshore wind turbine foundations and cross-sea tunnels.

CLC number: P756.2 Document code: A Article ID: 1004-1729(2026)02-0185-09

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Natural Science of Hainan University
Pages 185-193

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Cite this article:
LU M, LIU X, LIU H, et al. Research on multimodal data fusion evaluation method for subsea structures based on acoustic-optical joint detection. Natural Science of Hainan University, 2026, 44(2): 185-193. https://doi.org/10.65658/j.hndk.2025062701

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Received: 30 April 2025
Revised: 11 August 2025
Published: 25 April 2026
© The Author(s).

This is an open access article under the CC-BY license (http://creativecommons.org/licenses/by/4.0/).