NeuroVI-based wave compensation system control for offshore wind turbines

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 non-contact, 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 NeuroVI-based 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.

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Publication Details

Journal
Frontiers in Neurorobotics
Published
2025-07-30
DOI
https://doi.org/10.3389/fnbot.2025.1648713
Primary Topic
Wave and Wind Energy Systems
Type
article
Field-Weighted Citation Impact
0.00

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article

NeuroVI-based wave compensation system control for offshore wind turbines

Zhiqiang Xu, Xiangyong Liu, Tianran Ding, Fengshuang Ma
Frontiers in Neurorobotics
Wave and Wind Energy Systems
article

NeuroVI-based wave compensation system control for offshore wind turbines

Zhiqiang Xu, Xiangyong Liu, Tianran Ding, Fengshuang Ma
article en

Abstract

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 non-contact, 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 NeuroVI-based 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.

Frontiers in NeuroroboticsVol. 19
Chinese Academy of Fishery Sciences (CN)
Central Public-interest Scientific Institution Basal Research Fund, Chinese Academy of Fishery Sciences
Life below water
Openalex Percentile: Top 78%
Wave and Wind Energy Systems
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