混凝土裂缝识别方法及程序开发

doi:10.3969/j.issn.1674-0696.2022.11.14

重庆交通大学学报（自然科学版） ›› 2022, Vol. 41 ›› Issue (11): 105-111.DOI: 10.3969/j.issn.1674-0696.2022.11.14

混凝土裂缝识别方法及程序开发

杨莎莎1,2，郝龙3，李瑛3，傅少君2,4，贺昌海5

(1. 延安大学石油工程与环境工程学院，陕西延安 716000； 2.西京学院陕西省混凝土结构安全与耐久性重点实验室，陕西西安 710123； 3. 中铁二十局集团第六工程公司，陕西西安 710032； 4. 武汉大学土木建筑工程学院，湖北武汉 430072； 5. 武汉大学水利水电学院，湖北武汉 430072)

收稿日期:2020-08-03 修回日期:2022-10-17 发布日期:2023-01-04
作者简介:杨莎莎(1988—)，女，陕西西安人，副教授，博士，主要从事混凝土结构稳定性研究。E-mail：515374102@qq.com 通信作者：傅少君(1968—)，男，重庆人，教授，博士生导师，主要从事高坝复杂岩石地基及水工结构数值方法研究。E-mail:sgjg@whu.edu.cn
基金资助:
西安市科技局高校院所科技人员服务企业项目（22GXFW0148）；陕西省教育厅2022年度一般专项科研计划项目（22JK0597）；国家自然科学基金项目（51879207）；西京学院高层次人才专项基金项目（XJ21B20）

Concrete Crack Identification Method and Program Development

YANG Shasha1,2, HAO Long3, LI Ying3, FU Shaojun2,4, HE Changhai5

(1. School of Petroleum Engineering and Environmental Engineering, Yanan University, Yanan 716000, Shaanxi, China; 2.Shaanxi Key Laboratory of Safety and Durability of Concrete Structures, Xijing University, Xian 710123, Shaanxi, China； 3. NO.6 Engineering Corporation Limited of CR20 G, Xian 710032, Shaanxi, China; 4. School of Civil Engineering, Wuhan University, Wuhan 430072, Hubei, China; 5. School of Water Resources and Hydropower Engineering, Wuhan 430072, Hubei, China)

Received:2020-08-03 Revised:2022-10-17 Published:2023-01-04

摘要/Abstract

摘要： 利用MATLAB软件对采集到的混凝土表面裂缝RGB图像进行灰度化、滤波及分割处理后得到二值灰度图像，再进行裂缝判断和片段连接处理，计算混凝土结构表面裂缝的面积、长度及最大宽度等参数，研制了基于数字图像的混凝土结构表面裂缝识别程序——IPCW；以某混凝土坝工程浅表性裂缝识别实例对IPCW进行了验证。结果表明：IPCW识别的裂缝宽度值与实测值的相对误差总体在11%以内，识别精度满足工程要求；IPCW对大范围搜索裂缝具有较大优势，可应用于土木工程结构的裂缝初查。

关键词: 水利工程；公路工程；土木工程；图像处理；混凝土；裂缝识别

Abstract: The acquired RGB image of concrete surface crack was grayed, filtered and segmented by MATLAB software to obtain a binary grayscale image. Then, crack judgment and segment connection processing were carried out. The crack area, length, maximum width and other parameters of concrete structure surface were calculated. A digital-image-based recognition program for surface cracks of concrete structures—IPCW was developed. The IPCW was verified by an example of shallow surface crack identification in a concrete dam project. The research indicates that the relative error between the crack width value identified by IPCW and the measured value is generally within 11%, and the identification accuracy meets the engineering requirements. IPCW has great advantages in searching for cracks in a wide range and can be applied to the preliminary inspection of cracks in civil engineering.

Key words: water conservancy engineering; highway engineering; civil engineering; image processing; concrete; crack recognition

中图分类号:

TV543.6

杨莎莎1,2，郝龙3，李瑛3，傅少君2,4，贺昌海5. 混凝土裂缝识别方法及程序开发[J]. 重庆交通大学学报（自然科学版）, 2022, 41(11): 105-111.

YANG Shasha1,2, HAO Long3, LI Ying3, FU Shaojun2,4, HE Changhai5. Concrete Crack Identification Method and Program Development[J]. Journal of Chongqing Jiaotong University(Natural Science), 2022, 41(11): 105-111.

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混凝土裂缝识别方法及程序开发

Concrete Crack Identification Method and Program Development

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