摘要
为了实现无先验信息、无人工决策干预的船体小组立智能制造,采用机器视觉技术来实现小组立表面特征提取与定位。根据船体小组立智能生产线自动焊接定位的需求,设计对小组立工件激光扫描点云进行识别与提取的机器视觉方法,从降低复杂度和运算时间的角度对算法进行优化,并开发相应软件。通过不同小组立工件特征提取与定位试验,验证本文算法在无先验信息、无人工干预、工件随机摆放条件下的可靠性,表明机器视觉方法能够适应船体构件种类多、非标准件比例高、装配位置随机的特点,为船体智能制造的实现提供支持。
Feature detection of ship small assembly is prerequisite of ship small assembly intelligent manufacturing without prior knowledge or human-relied input.Methodology of machine vision system for small assembly recognition from point cloud are designed and optimized to reduce its complexity and time cost.A relative software is also developed.Experiments of random-positioned small assemblies are also conducted to approve reliabilility of the machine vision system without prior knowledge or human-relied input.The machine vision system can be suitable for the features of various kinds of ship hull structures,high proportion of non-standard parts and random assembly positions.The work helps to tackle problems in ship intelligent manufacturing.
作者
倪崇本
储云泽
丁金鸿
陈哲
NI Chongben;CHU Yunze;DING Jinhong;CHEN Zhe(Shanghai Jiao Tong University,a.State Key Laboratory of Ocean Engineering;b.School of Naval Architecture,Ocean & Civil Engineering,Shanghai 200240,China;Coliaborative Innovation Center for Advanced Ship and Deep-Sea Exploration (CISSE),Shanghai 200240,China;Shipbuilding Technology Research Institute,Shanghai 200032,China)
出处
《船舶工程》
CSCD
北大核心
2018年第11期12-17,共6页
Ship Engineering
