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IMAGE PROCESSING FOR THE ANALYSIS OF AN EVOLVING BROKEN-ICE FIELD IN MODEL TESTING

机译:模型测试中不断发展的残冰场分析的图像处理

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Dynamic positioning (DP) experiments in model ice were carried out in the ice tank at the Hamburg Ship Model Basin (HSVA) in the summer of 2011. In these experiments the behavior of two different ships in a broken-ice field were studied. One of the main parameters characterizing a broken-ice field is the ice concentration, defined as the fraction of the total water area covered by ice. In this paper, image processing techniques are applied to derive the ice concentration in the model basin. Several points in time are analyzed in order to describe the evolution of the ice field. The applied techniques include methods for identifying individual ice floes and calculating the ice concentration in the vicinity of the model ship. Ice floe boundaries are then obtained, and the ice floe size distribution and shape factor may further be extracted from the images. The image processing methods applied in this work are object extraction and edge detection algorithms, which are further customized to ice identification. The obtained results can be used for relating the ice field characteristics to the model test results, such as the vessel's displacements and the corresponding ice forces.
机译:2011年夏季,在汉堡船模型盆地(HSVA)的冰罐中进行了模型冰的动态定位(DP)实验。在这些实验中,研究了两种不同船在破冰场中的行为。表示碎冰场的主要参数之一是冰浓度,定义为冰所覆盖的总水面积的一部分。在本文中,图像处理技术被应用来推导出模型盆地中的冰浓度。为了描述冰原的演化,分析了几个时间点。所应用的技术包括用于识别单个浮冰并计算模型船附近的冰浓度的方法。然后获得浮冰的边界,并且可以从图像中进一步提取浮冰的尺寸分布和形状因子。在这项工作中应用的图像处理方法是对象提取和边缘检测算法,它们进一步针对冰块识别进行了定制。获得的结果可用于将冰场特性与模型测试结果相关联,例如船只的位移和相应的冰力。

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