电焊机2024，Vol.54Issue(12)：35-41,7.DOI:10.7512/j.issn.1001-2303.2024.12.06
基于3D视觉的船体构件智能焊接研究及应用
Research and Application of Intelligent Welding Technology for Ship Components Based on 3D VisionTitle
摘要
Abstract
To address the issues of low precision,high labor intensity,and low efficiency in manual welding of ship hull structural components,a point cloud acquisition method based on line laser sensors combined with structured light sensors is proposed.This method collects multimodal point clouds through 3D vision sensors and large-range line laser sensors,ex-tracts complex welding-machining trajectories,and develops an unmanned intelligent welding robot workstation.The 3D vi-sion guides the welding robot to locate and identify weld seam information,generates executable welding trajectories,and combines prior welding processes for welding,achieving efficient,stable,and flexible intelligent welding and weld process-ing for small batches of various types of complex ship structural components.Experimental results show that this system can effectively improve welding accuracy and efficiency,reduce manual intervention,and meet the needs of large-scale complex structure welding in fields such as ship manufacturing.The study also addresses issues such as inaccurate extraction of weld seam point clouds and offset recognition of weld seams on complex irregular curved workpieces by 3D vision algorithms,adopting a new algorithm based on contour and weld seam point comparison,optimizing the welding robot's weld seam rec-ognition and feature extraction algorithms.Through technological breakthroughs in independently developed visual hard-ware integration and other aspects,it promotes the development of ship structures and welding robot products towards high-end and intelligence.关键词
线激光传感器/结构光传感器/3D视觉算法/特征提取Key words
line laser sensor/structured light sensor/3D vision algorithm/weld feature extraction分类
矿业与冶金引用本文复制引用
许曦,张兆彪,李俊渊,高建文,闫德俊,张弓..基于3D视觉的船体构件智能焊接研究及应用[J].电焊机,2024,54(12):35-41,7.基金项目
广东省舰船先进焊接技术企业重点实验室基金(2023B1212070026) （2023B1212070026）
