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作 者:李鹏展 张丛 张永波 LI Pengzhan;ZHANG Cong;ZHANG Yongbo(Offshore Oil Shipping Center,Shengli Oilfield Branch of Sinopec,Yantai 265700,China;Marine Science Research Institute of Shandong Province,Qingdao 266104,China)
机构地区:[1]中国石油化工股份有限公司胜利油田分公司海洋石油船舶中心,山东烟台265700 [2]山东省海洋科学研究院,山东青岛266104
出 处:《舰船科学技术》2024年第18期138-142,共5页Ship Science and Technology
基 金:中央引导地方科技发展资金项目(YDZJ2022022)。
摘 要:大雾天气显著降低了能见度,使得激光雷达信号受到严重干扰,难以准确提取船舶信号变得困难。同时,船舶的动态变化导致边界识别困难,导致船舶碰撞风险识别精度较低。因此,提出大雾天气船舶碰撞风险激光雷达识别算法设计。在大雾天气条件下,对激光雷达信号预处理,得到高精度船舶信号,对得到的船舶信号数据基于尺寸信息执行边界运算,以获取船舶边界数据以及靠近速度,并以此作为船舶碰撞风险识别指标。依据隶属函数,结合风险识别指标建立判断矩阵,通过碰撞危险度量化,归一化处理及去模糊化运算,得出船舶碰撞风险等级。依据平均碰撞风险识别目标船舶整个航程的风险等级。实验结果表明,该算法对船舶碰撞风险识别精度高,整体性能强。The foggy weather significantly reduces the visibility,which makes the lidar signal severely disturbed,and it is difficult to accurately extract the ship signal.At the same time,the dynamic change of ship leads to the difficulty of boundary identification,resulting in the low accuracy of ship collision risk identification.Therefore,the design of liDAR identification algorithm for ship collision risk in foggy weather is proposed.In foggy weather conditions,the laser radar signal is pre-processed to obtain high-precision ship signals,and the ship signal data is obtained by boundary calculation based on the size information to obtain ship boundary data and approach speed,which is used as the identification index of ship collision risk.According to the membership function and risk identification index,the judgment matrix is established,and the collision risk level is obtained through the quantification,normalization and defuzzification of collision risk.Identify the risk level of the target ship throughout the voyage based on the average collision risk.Experimental results show that the algorithm has high accuracy and strong overall performance for ship collision risk identification.
关 键 词:大雾天气条件 船舶碰撞风险 激光雷达 风险识别指标 碰撞危险度
分 类 号:U698.2[交通运输工程—港口、海岸及近海工程]
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