摘要
本研究针对悬索桥弱光环境下主缆钢丝腐蚀监测难题,开发一套基于多摄像头模块与AI技术的腐蚀标准图集采集与分析系统。系统通过在主缆钢丝与保护外壳间隔布置54个小型摄像头,结合补光、调焦功能,实现弱光环境下的全面图像采集。采用YOLOv5等AI模型,优化腐蚀区域的自动检测与分类,准确率达到92.5%。开发的采集与分析程序集成多路摄像头控制、图像拼接与矫正、AI分析及标准图集生成等功能,为悬索桥主缆钢丝的腐蚀监测提供高效、可靠的技术方案。该系统无损检测、高效采集,并适应弱光环境,为桥梁维护的智能化发展提供重要技术支撑。
This study addresses the challenge of corrosion monitoring of main cable wires in suspension bridges under low-light conditions by developing a system for collecting analyzing corrosion standard images based on a multi-camera module and AI technology.The system,which involves the arrangement of 54 small cameras between the main cable wires and protective shell,combined with functions such as supplementary lighting and focusing,has achieved comprehensive image collection under low-light conditions.By using AI models such as YOLOv,the automatic detection and classification of corroded areas have been optimized,with an accuracy rate of 92.5%.The developed collection and analysis software integrates multiple,including multi-camera control,image stitching and correction,AI analysis,and standard image generation,providing an efficient and reliable technical solution for the corrosion monitoring of main cable in suspension bridges.This system,which is non-destructive,efficient in collection,and adaptable to low-light conditions,provides an important technical support for the intelligent development bridge maintenance.
作者
官华
闻洁静
GUAN Hua;WEN Jiejing(Zhejiang Zhoushan Cross-Sea Bridge Co.,Ltd.,Zhejiang Zhoushan 316000,China;Zhejiang Jinhua Yongjin Expressway Co.,Ltd.Hangzhou Science and Technology Branch,Hangzhou 310000,China)
出处
《交通工程》
2025年第3期21-26,共6页
Journal of Transportation Engineering
关键词
悬索桥
弱光环境
主缆钢丝腐蚀
suspension bridge
low light environment
corrosion of main cable steel wire
作者简介
官华(1983—),男,博士研究生,高级工程师,研究方向为桥梁检测与监测技术。E-mail:732820569@qq.com。
