计算机应用与软件2025，Vol.42Issue(10)：24-29,101,7.DOI:10.3969/j.issn.1000-386x.2025.10.004
基于深度学习的隧道衬砌病害识别软件的开发与实现
DEVELOPMENT AND IMPLEMENTATION OF IDENTIFICATION SOFTWARE OF TUNNEL LINING DISEASES BASED ON DEEP LEARNING
摘要
Abstract
In order to solve the problem of rapid and real-time identification of tunnel lining diseases,deep learning method is adopted to compile a set of real-time identification and detection software for diseases,and to realize the alarm and counting functions of the first occurrence of new diseases.For the tunnel lining disease target detection frame instability phenomenon based on deep learning,the normalized product correlation threshold judgment method was introduced,by comparing the similarity of the two adjacent detection frames before and after the frame to discriminate whether it was a new disease.Through the experiment,we find the experimental value of the normalized product correlation threshold that can meet both the sensitivity and correctness of the new disease alarm,and the analysis of the possible influencing factors are discussed.An application example of the experimental conditions of this software is given.关键词
隧道工程/衬砌病害/识别与检测/深度学习/计算机视觉Key words
Tunnel engineering/Disease of tunnel lining/Identification and detection/Deep learning/Computer vision分类
信息技术与安全科学引用本文复制引用
刘金杉,卢昱杰,李元海..基于深度学习的隧道衬砌病害识别软件的开发与实现[J].计算机应用与软件,2025,42(10):24-29,101,7.基金项目
国家自然科学基金面上项目(52078374) （52078374）
上海市经信委专项资金项目(沪J-2018-27) （沪J-2018-27）
国家重点基础研究发展计划(973)项目(2014CB046905). （973）
