基于WOA的焊接缺陷图像边缘检测  

Image Edge Detection for Welding Defects Based on WOA

作　　者：唐伟军[1] 薛鹏飞 曹绍林[1] 王家兴 汪小平 赵卫 TANG Wei-jun;XUE Peng-fei;CAO Shao-lin;WANG Jia-xing;WANG Xiao-ping;ZHAO Wei(Information Technology Institute of Jinan University,Guangzhou Shengtong Quality Testing of Construction Co,Ltd,Guangzhou 510075;MOE Key Laboratory of Disaster Forecast and Control in Engineering,School of Mechanics and Construction Engineering,Jinan University,Guangzhou 510632)

机构地区：[1]暨南大学信息技术研究所,广州市盛通建设工程质量检测有限公司,广州510075 [2]暨南大学“重大工程灾害与控制”教育部重点实验室,暨南大学力学与建筑工程学院,广州510632

出　　处：《广州建筑》2023年第6期110-113,共4页GUANGZHOU ARCHITECTURE

基　　金：国家自然科学基金项目(12072130)。

摘　　要：图形图像处理技术在工程质量检测的损伤评估中得到越来越广泛的应用,便于快速确定结构表面缺陷。图像的边缘特征是缺陷检测的前提和基础,本文针对钢结构工程中焊接质量检测问题,提出基于鲸鱼优化算法的焊接缺陷图像边缘检测技术,通过若干焊接缺陷图像边缘检测工程案例证明了所提出方法的抗噪性和有效性。该方法扩展了群智能算法在图像分析与处理领域的应用范围,可以为工程提供一定的参考价值。Graphic image processing technology has been more and more widely used in damage assessment of engineering quality inspection,which is convenient to quickly determine structural surface defects.Image edge features are the premise and basis of defect detection.Aiming at the welding quality detection problem in steel structure engineering,this paper proposes the edge detection technology of welding defect image based on whale optimization algorithm(WOA).Several welding defect image edge detection cases in engineering prove the anti-noise and effectiveness of the proposed method.This method extends the application scope of swarm intelligence algorithm in the field of image analysis and processing,and can provide some reference value for engineering.

关 键 词：边缘检测 鲸鱼优化算法 图像处理 焊接缺陷 

分 类 号：TU375[建筑科学—结构工程]