基于数字图像信息分析的混凝土结构裂缝识别方法研究

Cao Wang, Tao Yang, Guodong Li, H. Yang, Fengting Li, Dapeng Liu
{"title":"基于数字图像信息分析的混凝土结构裂缝识别方法研究","authors":"Cao Wang, Tao Yang, Guodong Li, H. Yang, Fengting Li, Dapeng Liu","doi":"10.1117/12.2671444","DOIUrl":null,"url":null,"abstract":"Most of the subway stations are below the groundwater level, so it is particularly important to do a good job in waterproofing. For the leakage disease of subway station structure, detection is the method and identification is the purpose. There are many types of urban subway station structural leakage diseases, and it is not easy to identify the diseases in all directions. Based on the summary and analysis of the common identification methods of seepage water diseases in subway stations, the crack digital images obtained in a non-contact way are taken as the research objects. Starting from the crack characteristics and the principle of digital image processing algorithm, the traditional algorithm is improved and optimized to obtain a detection algorithm more suitable for the digital image of concrete structural cracks, which is applied to the identification of structural cracks in subway stations. Compared with other manual methods, this method is more accurate and can save a lot of time and cost.","PeriodicalId":120866,"journal":{"name":"Artificial Intelligence and Big Data Forum","volume":"61 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Research on crack identification method of concrete structure based on digital image information analysis\",\"authors\":\"Cao Wang, Tao Yang, Guodong Li, H. Yang, Fengting Li, Dapeng Liu\",\"doi\":\"10.1117/12.2671444\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Most of the subway stations are below the groundwater level, so it is particularly important to do a good job in waterproofing. For the leakage disease of subway station structure, detection is the method and identification is the purpose. There are many types of urban subway station structural leakage diseases, and it is not easy to identify the diseases in all directions. Based on the summary and analysis of the common identification methods of seepage water diseases in subway stations, the crack digital images obtained in a non-contact way are taken as the research objects. Starting from the crack characteristics and the principle of digital image processing algorithm, the traditional algorithm is improved and optimized to obtain a detection algorithm more suitable for the digital image of concrete structural cracks, which is applied to the identification of structural cracks in subway stations. Compared with other manual methods, this method is more accurate and can save a lot of time and cost.\",\"PeriodicalId\":120866,\"journal\":{\"name\":\"Artificial Intelligence and Big Data Forum\",\"volume\":\"61 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-03-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Artificial Intelligence and Big Data Forum\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1117/12.2671444\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Artificial Intelligence and Big Data Forum","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1117/12.2671444","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

大部分地铁站都在地下水位以下,所以做好防水工作就显得尤为重要。对于地铁车站结构渗漏病害,检测是方法,识别是目的。城市地铁车站结构渗漏病害的类型很多,各个方向的病害都不容易识别。在总结分析地铁车站渗水病害常用识别方法的基础上,以非接触方式获取的裂缝数字图像为研究对象。从裂缝特征和数字图像处理算法的原理出发,对传统算法进行改进和优化,得到更适合混凝土结构裂缝数字图像的检测算法,并应用于地铁车站结构裂缝的识别。与其他手工方法相比,该方法更加准确,可以节省大量的时间和成本。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Research on crack identification method of concrete structure based on digital image information analysis
Most of the subway stations are below the groundwater level, so it is particularly important to do a good job in waterproofing. For the leakage disease of subway station structure, detection is the method and identification is the purpose. There are many types of urban subway station structural leakage diseases, and it is not easy to identify the diseases in all directions. Based on the summary and analysis of the common identification methods of seepage water diseases in subway stations, the crack digital images obtained in a non-contact way are taken as the research objects. Starting from the crack characteristics and the principle of digital image processing algorithm, the traditional algorithm is improved and optimized to obtain a detection algorithm more suitable for the digital image of concrete structural cracks, which is applied to the identification of structural cracks in subway stations. Compared with other manual methods, this method is more accurate and can save a lot of time and cost.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信