摘要
针对现有桥梁检测中人工判别病害工作量大、效率低的问题,以钢筋混凝土(RC)桥梁为对象,阐述了机器学习在RC桥梁病害检测中的应用。从现有桥梁病害检测方法、机器学习方法、机器学习在RC桥梁中的应用进展三个方面进行研究,结果表明,基于深度学习的病害检测方法能够自动从病害图像中提取特征,实现病害的分类和定位,提供了一种病害自动化检测场景,有利于桥梁智能化管养。
In view of the shortcomings of large workload and low efficiency of manual identification of defects in the existing bridge detection,this paper summarizes the application of machine learning in the detection of RC bridge diseases,taking reinforced concrete(RC)bridge as the object.This paper reviews three aspects of the existing bridge disease detection methods,machine learning methods,and the application progress of machine learning in RC bridges.The research shows that the disease detection method based on deep learning can automatically extract features from the disease image,realize the classification and location of the disease,and provide a disease automatic detection scene,which is conducive to the intelligent management and maintenance of the bridge.
作者
杨建华
邹俊志
YANG Jian-hua;ZOU Jun-zhi(CCCC Infrastructure Maintenance Group Ningxia Engineering Co.,Ltd.,Ningxia 750000,China;School of Civil Engineering,Chongqing Jiaotong University,Chongqing 400074,China)
出处
《北方交通》
2020年第6期18-20,25,共4页
Northern Communications
关键词
钢筋混凝土桥梁
机器学习
桥梁检测
深度学习
桥梁病害
Reinforced concrete bridge
Machine learning
Bridge detection
Deep learning
Bridge diseases
