摘要
针对海洋工程中的波浪消能问题,该文提出了一种基于神经网络的反向式造波消波控制方法。利用PyTorch开源机器学习库构建神经网络模型,获取智能体与波浪的映射关系,通过大量数据训练使该模型可预测造波机的运动速度。根据神经网络模型预测得到的速度,该模型主动控制造波机生成与入射波相位相反的反向波,达到消波的效果。模型验证结果表明,该方法有较好的拟合效果,能够适用于不同造波机,可为海洋工程中的波浪消能问题提供一种新的解决思路。
Aiming at the wave energy dissipation problem in ocean engineering, an inverse wave-making and wave absorbing control method based on neural network is proposed in this paper. The PyTorch open-source machine learning library is used to construct a neural network model and obtain the mapping relationship between intelligences and waves. This model can predict the motion speed of the wave maker through a large amount of data training. According to the predicted speed of the neural network model, this model actively controls the wave maker to generate the reverse wave with the opposite phase to the incoming wave,achieving the effect of wave dissipation. The model validation results show that the prediction results of this method have a well-fitting effect on the actual values, and can be applied to different wave generators, which will provide a new solution idea for the wave energy dissipation problem in ocean engineering.
作者
曹娟
王臣
赵西增
魏唯嘉
谢玉林
范一帆
Cao Juan;Wang Chen;Zhao Xizengg;Wei Weijia;Xie Yulin;Fan Yifan(School of Naval Architecture and Maritime,Zhejiang Ocean University,Zhoushan 316022,China;Wuhan Changjiang Planning and Design Institute for Shipping Co.,Ltd,Wuhan 430030,China;School of Marine Engineering Equipment,Zhejiang Ocean University,Zhoushan 316022,China;Ocean College,Zhejiang University,Zhoushan 316021,China;Ocean Research Center of Zhoushan,Zhejiang University,Zhoushan 316021,China)
出处
《水动力学研究与进展（A辑）》
CSCD
北大核心
2024年第1期1-7,共7页
Chinese Journal of Hydrodynamics
基金
国家自然科学基金项目(51979245)
浙江省联合基金重点项目(LHZ22E090002)
中央引导地方科技发展资金项目(2023ZY1021)。
关键词
神经网络
反向式造波
主动控制
消波
Neural network
Inverse wave making
Active control
Wave absorbing
