摘要
为了有效提高船体分段测量点集与理论点集的精准匹配技术,提出了一种自动剔除错误点且考虑工程约束的船体分段点集匹配方法.该方法分为粗匹配与精匹配两步,粗匹配采用改进的随机抽样一致性算法实现了快速剔除错误点,同时基于奇异值分解法确定了刚性变换矩阵,获得了较准确的匹配初值;精匹配利用层次分析法自动获得了工程约束权值,采用权值向量将工程约束引入多目标函数中,通过求解多目标模型获得匹配结果.实例表明,该方法可快速自动剔除错误点,在考虑工程约束的条件下获得较精确的合理结果,为船体分段后续的搭载提供了依据.
In order to effectively improve the precision matching technique of measurement point set and design point set for hull blocks, a point set matching method for hull blocks with engineering constraints and automatic error points elimination is presented. The method is divided into two steps: coarse matching and fine matching. In the coarse matching stage, the improved random sample consensus (RANSAC) algorithm is used to eliminate error points rapidly, at the same time the rigid transformation matrix is determined by singular value decomposition (SVD) in this algorithm, so more accurate initial matching values are obtained. In the fine matching stage, the analytic hierarchy process (AHP) is used to obtain the weight value of each engineering constraint automatically, and then the engineering constraints with weight vector are introduced into the multi-objective function. By solving the multi-objective model, the more reasonable matching results are obtained. The examples prove that this method can quickly and automatically eliminate error points, and get more accurate and reasonable results meeting engineering constraints. It can provide the basis for the subsequent assembly of hull blocks.
作者
管官
廖红玲
杨蕖
GUAN Guan;LIAO Hongling;YANG Qu(Ship CAD Engineering Center, Dalian University of Technology, Dalian 116024, China;State Key Laboratory of Structural Analysis for Industrial Equipment, Dalian University of Technology,Dalian 116024, China)
出处
《大连理工大学学报》
EI
CAS
CSCD
北大核心
2019年第1期53-62,共10页
Journal of Dalian University of Technology
基金
国家自然科学基金资助项目(51609036)
中央高校基本科研业务费专项资金资助项目(DUT18JC05)
关键词
船体分段
点集匹配
剔除错误点
随机抽样一致性算法
工程约束
权值向量
层次分析法
hull blocks
point set matching
error points elimination
random sample consensus algorithm
engineering constraint
weight vector
analytic hierarchy process