ORIGINAL RESEARCH article
Front. Neurorobot.
Volume 19 - 2025 | doi: 10.3389/fnbot.2025.1648713
NeuroVI-based Wave Compensation System Control for Offshore Wind Turbines
Provisionally accepted
- Fishery Machinery and Instrument Research Institute, Chinese Academy of Fishery Sciences, Shanghai, China
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In deep-sea areas, the hoisting operation of offshore wind turbines is seriously affected by waves, and the secondary impact is prone to occur between the turbine and the pile foundation. To address this issue, this study proposes an integrated wave compensation system for offshore wind turbines based on a neuromorphic vision (NeuroVI) camera. The system employs a NeuroVI camera to achieve noncontact, high-precision, and low-latency displacement detection of hydraulic cylinders, overcoming the limitations of traditional magnetostrictive displacement sensors, which exhibit slow response and susceptibility to interference in harsh marine conditions. A dynamic simulation model was developed using AMESim-Simulink co-simulation to analyze the compensation performance of the NeuroVIbased system under step and sinusoidal wave disturbances. Comparative results demonstrate that the NeuroVI feedback system achieves faster response times and superior stability over conventional sensors. Laboratory-scale model tests and real-world application in the installation of a 5.2 MW offshore wind turbine validated the system's feasibility and robustness, enabling real -time collaborative control of turbine and cylinder displacement to effectively mitigate multi-impact risks. This research provides an innovative approach for deploying neural perception technology in complex marine scenarios and advances the development of neuro-robotic systems in ocean engineering.
Keywords: Integrated installation of offshore wind turbine, Wave compensation system, neuromorphic vision (NeuroVI) camera, spiking neural networks(SNN), AMESim-Simulink co-simulation, synchronized motion control of displacements
Received: 17 Jun 2025; Accepted: 14 Jul 2025.
Copyright: © 2025 Ma, Liu, Xu and Ding. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Xiangyong Liu, Fishery Machinery and Instrument Research Institute, Chinese Academy of Fishery Sciences, Shanghai, China
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