为提高船舶初步设计效率，提出一种基于SQL数据库和KD-Tree算法的船舶型线快速匹配方法。针对船舶数据繁多复杂的问题，利用SQL语言保存、分类和提取船舶设计过程中的型线数据和特征线数据，提高了数据的存储和利用效率。针对船体复杂曲面的匹配问题，采取基于特征线描述船体特征，并求解特征线B样条控制点的方法保存船体的曲面特征数据。针对高维度变量的匹配问题，在不同大小的测试集中采用KD-Tree结构保存数据并采用最邻近搜索算法，能将船体型线的搜索匹配速度提高34.31%～84.16%。该方法对提高船舶初步设计效率提供有益的借鉴和帮助。
To enhance the efficiency of ship preliminary design, this study proposes a ship hull rapid matching method based on SQL database and KD-Tree algorithm. Addressing the challenge of numerous and complex ship data, the approach utilizes SQL language for the storage, categorization, and extraction of hull form and characteristic lines data, thereby amplifying data storage and utilization efficiency within the ship design process. Confronting the intricate matching complex posed by ship surfaces, the method employs a characteristic-lines-oriented strategy to delineate vessel characteristics. Additionally, this study archive surface characteristic data through the derivation of B-spline control points from characteristic lines. In addressing the matching complexity inflation problem posed by high-dimensional variables, the study integrates KD-Tree structure for data storage. Moreover, it utilizes the nearest neighbor search algorithm to notably increase the search matching velocity of ship hulls by 34.31% to 84.16% in test databases. This methodology holds substantive implications for advancing the efficiency of ship preliminary design processes.
2025,47(11): 8-14 收稿日期：2024-8-29
DOI：10.3404/j.issn.1672-7649.2025.11.002
分类号：U664
基金项目：工信部资助项目（ZTZB-23-990-030）
作者简介：余恺(1999-),男,硕士研究生,研究方向为船型数据库
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