路面缺陷智能检测系统与方法综述  

Review of the Intelligent Pavement Defect Detection System and Methods

作　　者：易钰程 王靖智 朱路[1] 李霄 熊奎 叶盛涛 陈嘉豪 Yi Yucheng;Wang Jingzhi;Zhu Lu;Li Xiao;Xiong Kui;Ye Shengtao;Chen Jiahao(School of Information Engineering,East China Jiaotong University,Nanchang 330013,China;VKELINE Information Technology Co.,Ltd.,Nanchang 330038,China)

机构地区：[1]华东交通大学信息工程学院,江西南昌330013 [2]南昌市微轲联信息技术有限公司,江西南昌330038

出　　处：《华东交通大学学报》2023年第5期19-31,共13页Journal of East China Jiaotong University

基　　金：国家自然科学基金项目(61967007,61963016);江西省自然科学基金面上项目(20212BAB202005);江西省重点研发计划项目(20202BBEL53014,20201BBF61012)。

摘　　要：从路面缺陷检测系统组成和特点出发,首先简要回顾了路面缺陷检测系统与传统路面图像处理方法的发展过程。在此基础上,探讨了国内外典型路面缺陷检测系统的现状,包含重型道路状况智能检测系统、轻量化路面质量检测系统,并对检测系统的性能及部分参数进行了描述。然后,详细介绍了基于机器学习、深度学习理论的路面缺陷智能化检测方法的演变历程,重点分析了基于深度学习技术的路面缺陷智能化检测方法国内外的研究进展,主要包含基于区域卷积神经网络、单次多框检测器、YOLO目标检测、Transformer检测模型等路面缺陷智能检测方法。最后,从多模信息融合、双轻量化设备、稳健智能化算法等方面对路面缺陷智能化检测系统的发展趋势和应用前景进行了展望。Based on the composition and characteristics of pavement defect detection system,this paper briefly reviews the development process of the pavement defect detection system.On this basis,it analyzes the status quo of typical pavement defect detection systems at home and abroad,including the intelligent detection system of heavy pavement condition and lightweight pavement quality detection system,and describes the performance and some parameters of the detection system.Then emphatically introduces the evolution process of pavement defect detection technology and methods from traditional image processing to the intelligent pavement defect detection method based on machine learning and deep learning theory is explored.And,the research progress of intelligent pavement defect detection methods based on deep learning technology at home and abroad is comprehensively introduced,including pavement defect detection methods based on regional convolutional neural network,single multi-frame detector,YOLO target detection,Transformer detection model,etc.Finally,the development trend and application prospect of intelligent detection system for pavement defects are discussed from the aspects of multi-mode information fusion,dual lightweight design and robust intelligent algorithm.

关 键 词：路面缺陷检测系统 人工智能 深度学习 轻量化系统 多模信息融合 

分 类 号：U418[交通运输工程—道路与铁道工程]