桂大伟, 庞小平, 艾松涛. 基于GPS数据的破冰船锚泊状态识别与特征分析[J]. 武汉大学学报 ( 信息科学版), 2019, 44(2): 166-171. DOI: 10.13203/j.whugis20170090
引用本文: 桂大伟, 庞小平, 艾松涛. 基于GPS数据的破冰船锚泊状态识别与特征分析[J]. 武汉大学学报 ( 信息科学版), 2019, 44(2): 166-171. DOI: 10.13203/j.whugis20170090
GUI Dawei, PANG Xiaoping, AI Songtao. Recognition and Feature Analysis of Anchoring Status from Icebreaker Based on GPS Data[J]. Geomatics and Information Science of Wuhan University, 2019, 44(2): 166-171. DOI: 10.13203/j.whugis20170090
Citation: GUI Dawei, PANG Xiaoping, AI Songtao. Recognition and Feature Analysis of Anchoring Status from Icebreaker Based on GPS Data[J]. Geomatics and Information Science of Wuhan University, 2019, 44(2): 166-171. DOI: 10.13203/j.whugis20170090

基于GPS数据的破冰船锚泊状态识别与特征分析

Recognition and Feature Analysis of Anchoring Status from Icebreaker Based on GPS Data

  • 摘要: 锚泊安全对于穿梭于南北两极、出入冰区等恶劣航行条件的“雪龙”号破冰船至关重要。从“雪龙”号第27次南极考察航迹数据入手,分析其锚泊过程中的GPS轨迹特征,基于决策树原理设计并实现了锚泊状态识别算法。利用最小二乘原理对锚泊轨迹点进行拟合,得到破冰船锚泊偏荡周期中的逐个锚位,分析发现了2011-02-14“雪龙”号停靠中山站锚地期间发生的走锚现象,结合气象数据进一步分析了走锚现象的成因,验证了利用拟合锚位监控锚泊状态的可行性。

     

    Abstract: Anchoring security is very important to the icebreaker Xuelong during the voyages of polar expeditions. To analyze the feature of anchoring status, we built a decision tree model to recognize the anchoring pattern from the historical trajectory data from the 27th Chinese National Antarctic Research Expedition. On the basis of the recognition model, we retrieve the anchor position during the yawing period using the least squares principle. The fitting anchor position illustrates that the drag-anchor phenomenon occurred when Xuelong was in Antarctic Zhongshan anchorage on February 14, 2011. Combining with the meteorological data, we discuss the cause of drag-anchor and verify the feasibility of near-real-time anchor monitoring by using the fitting anchor position method.

     

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