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基于实际海况和气象条件的全尺寸操纵试验修正与运动建模

Full-Scale Maneuvering Trials Correction and Motion Modelling Based on Actual Sea and Weather Conditions.

作者信息

Mei Bin, Sun Licheng, Shi Guoyou

机构信息

Navigation College, Dalian Maritime University, Dalian 116026, China.

Collaborative Innovation Research Institute of Autonomous Ship, Dalian Maritime University, Dalian 116026, China.

出版信息

Sensors (Basel). 2020 Jul 16;20(14):3963. doi: 10.3390/s20143963.

DOI:10.3390/s20143963
PMID:32708706
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7412367/
Abstract

Aiming at the poor accuracy and difficult verification of maneuver modeling induced by the wind, waves and sea surface currents in the actual sea, a novel sea trials correction method for ship maneuvering is proposed. The wind and wave drift forces are calculated according to the measurement data. Based on the steady turning hypothesis and pattern search algorithm, the adjustment parameters of wind, wave and sea surface currents were solved, the drift distances and drift velocities of wind, waves and sea surface currents were calculated and the track and velocity data of the experiment were corrected. The hydrodynamic coefficients were identified by the test data and the ship maneuvering motion model was established. The results show that the corrected data were more accurate than log data, the hydrodynamic coefficients can be completely identified, the prediction accuracy of the advance and tactical diameters were 93% and 97% and the prediction of the maneuvering model was accurate. Numerical cases verify the correction method and full-scale maneuvering model. The turning circle advance and tactical diameter satisfy the standards of the ship maneuverability of International Maritime Organization (IMO).

摘要

针对实际海况中因风、浪、海流导致的操纵运动建模精度差且验证困难的问题,提出了一种新型的船舶操纵海上试验修正方法。根据测量数据计算风浪漂移力。基于稳定转向假设和模式搜索算法,求解风、浪和海流的调整参数,计算风、浪和海流的漂移距离和漂移速度,并对试验的轨迹和速度数据进行修正。通过试验数据识别水动力系数并建立船舶操纵运动模型。结果表明,修正后的数据比计程仪数据更准确,水动力系数能够完全识别,进距和战术直径的预测准确率分别为93%和97%,操纵模型预测准确。数值案例验证了该修正方法和实船操纵模型。回转圈进距和战术直径满足国际海事组织(IMO)船舶操纵性标准。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/214b/7412367/4429f65419fd/sensors-20-03963-g011.jpg
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