Predicting 3-DoF motions of a moored barge by machine learning  

作　　者：Yu Yang Tao Peng Shijun Liao 

机构地区：[1]State Key Laboratory of Ocean Engineering,Shanghai 200240,China [2]Center of Marine Numerical Experiment,School of Naval Architecture,Ocean and Civil Engineering,Shanghai Jiao Tong University,Shanghai 200240,China

出　　处：《Journal of Ocean Engineering and Science》2023年第4期336-343,共8页海洋工程与科学（英文）

基　　金：supported by Shanghai Pilot Program for Basic Research-Shanghai Jiao Tong University (No.21TQ1400202).

摘　　要：The real-time prediction of a floating platform or a vessel is essential for motion-sensitive maritime activ-ities.It can enhance the performance of motion compensation system and provide useful early-warning information.In this paper,we apply a machine learning technique to predict the surge,heave,and pitch motions of a moored rectangular barge excited by an irregular wave,which is purely based on the mo-tion data.The dataset came from a model test performed in the deep-water ocean basin,at Shanghai Jiao Tong University,China.Using the trained machine learning model,the predictions of 3-DoF(degrees of freedom)motions can extend two to four wave cycles into the future with good accuracy.It shows great potential for applying the machine learning technique to forecast the motions of offshore platforms or vessels.

关 键 词：BARGE Wave-excited motion Machine learning Motion prediction 

分 类 号：TP183[自动化与计算机技术—控制理论与控制工程] U66[自动化与计算机技术—控制科学与工程]