土木工程与管理学报2025，Vol.42Issue(3)：1-15,15.DOI:10.13579/j.cnki.2095-0985.2025.20250087
面向智能运维的交通基础设施视觉感知与诊断
Visual Perception and Diagnosis of Transportation Infrastructure for Intelligent Operation and Maintenance
摘要
Abstract
With the burgeoning advancement of artificial intelligence(AI)technology,deep learning-based computer vision has evolved into an essential methodology for damage perception and diagnosis in transportation infrastructure.This paper systematically investigates research developments and ap-plication progress of computer vision technology in infrastructure damage assessment.By analyzing technical challenges confronting transportation infrastructure diagnostics,it provide an in-depth expo-sition of computer vision principles,dominant computational models,and critical implementation is-sues specific to infrastructure damage evaluation.Through a critical synthesis of application break-throughs in road networks,bridges,tunnels,and rail systems-coupled with an examination of intelli-gent maintenance equipment.This study demonstrates the transformative potential of computer vision in enhancing diagnostic precision,operational efficiency,and decision-making robustness.Further-more,it delineate cutting-edge technical advancements in large-scale pre-trained models and explore their prospective applications in structural surface damage characterization.The paper concludes with a forward-looking analysis of emerging research frontiers,particularly embodied intelligence systems,while proposing innovative trajectories for next-generation intelligent maintenance paradigms.This comprehensive investigation not only maps the current technological landscape but also establishes a conceptual framework for integrating advanced computer vision with infrastructure lifecycle management systems.关键词
交通基础设施/计算机视觉/损伤感知/损伤诊断/大模型/具身智能Key words
transportation infrastructure/computer vision/damage perception/damage diagnosis/large model/embodied intelligence分类
信息技术与安全科学引用本文复制引用
鞠定超,张云开,黄永,韩孜旭,王吕斐,张宇翔,潘保钰,李泓毅..面向智能运维的交通基础设施视觉感知与诊断[J].土木工程与管理学报,2025,42(3):1-15,15.基金项目
国家重点研发计划(2021YFF0501000) （2021YFF0501000）
