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LU Mingzhi, LIU Xiaoxiao, LIU Houhong, et al. Research on multimodal data fusion evaluation method for subsea structures based on acoustic-optical joint detectionJ. Natural Science of Hainan University, DOI:10.15886/j.cnki.hndk.2025062701. DOI: 10.15886/j.cnki.hndk.2025062701
Citation: LU Mingzhi, LIU Xiaoxiao, LIU Houhong, et al. Research on multimodal data fusion evaluation method for subsea structures based on acoustic-optical joint detectionJ. Natural Science of Hainan University, DOI:10.15886/j.cnki.hndk.2025062701. DOI: 10.15886/j.cnki.hndk.2025062701

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

  • 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.
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