基于水下机器人与数字图像技术的混凝土结构表面裂缝检测方法

谢文高; 张怡孝; 刘爱荣; 傅继阳; 胡晓勇; 陈炳聪; 袁向荣

doi:10.6052/j.issn.1000-4750.2021.05.S010

基于水下机器人与数字图像技术的混凝土结构表面裂缝检测方法

doi: 10.6052/j.issn.1000-4750.2021.05.S010

1.
广州大学风工程与工程振动研究中心，广东，广州 510006
2.
广州市市政工程设计研究总院有限公司，广东，广州 510060

基金项目: 国家自然科学基金项目(51878188)；高等学校学科创新引智计划项目(111计划D21021)；广州市科技计划项目(20212200004)

详细信息

作者简介:
谢文高(1995−)，男，广东人，硕士，主要从事水下机器人和图像处理研究(E-mail: 544869735@qq.com)

张怡孝(1996−)，女，河南人，硕士，主要从事桥梁静力稳定性研究(E-mail: zhangyixiao0226@163.com)

傅继阳(1976−)，男，湖北人，研究员，博士，主要从事工程结构抗风研究(E-mail: jyfu@gzhu.edu.cn)

胡晓勇(1981−)，男，山西人，高工，硕士，主要从事桥梁水下结构检测实践研究(E-mail: 46364767@qq.com)

陈炳聪(1980−)，男，广东人，高级实验师，博士，主要从事装配式组合梁研究(E-mail: bc_chen@gzhu.edu.cn)

袁向荣(1957−)，男，河北人，教授，博士，博导，主要从事结构检测的数字图像技术研究(E-mail: rongxyuan@163.com)

通讯作者:
刘爱荣(1972−)，女，山西人，教授，博士，博导，主要从事桥梁稳定性研究(E-mail: liuar@gzhu.edu.cn)

中图分类号: U446；TP391.4；TP242
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- 文章访问数: 93
- HTML全文浏览量: 40
- PDF下载量: 49
- 被引次数: 0
出版历程
- 收稿日期: 2021-05-29
- 修回日期: 2022-03-02
- 网络出版日期: 2022-04-09
- 刊出日期: 2022-06-06

METHOD FOR CONCRETE SURFACE CRACKING DETECTION BASED ON ROV AND DIGITAL IMAGE TECHNOLOGY

1.
Research Center of Wind Engineering and Engineering Vibration, Guangzhou, Guangdong 510006, China
2.
Guangzhou Municipal Engineering Design and Research Institute Co. Ltd, Guangzhou, Guangdong 510060, China

摘要

摘要: 人工检测是目前桥梁水下结构病害检测的主要方式，存在着危险性高、效率低、准确性低等问题。针对以上问题，该文提出了采用搭载高清水下摄像头的水下机器人检测方法。该文在清水环境实验中对混凝土结构进行表观检测，通过图像处理、高斯滤波以及梯度计算的分权阈值法对存在裂缝的图像进行分析，提取裂缝边缘特征，提出基于斜率计算的欧氏距离下裂缝宽度计算方法实现对裂缝宽度的分析计算。实验结果表明：该文实验中裂缝检测结果精度较高，且裂缝的宽度参数计算精度可达规范要求。
- 水下机器人 /
- 桥梁检测 /
- 图像识别 /
- 裂缝检测 /
- 裂缝宽度
Abstract: Manual detection is the main disease detection way for bridge underwater structures, which has the problems of high risk, low efficiency and low accuracy. In response to the above problems, this paper proposes an underwater robot bridge detection method with high-definition underwater camera. The surface detection of concrete structures was carried out in clean water experiment. The image with cracks was analyzed by image processing, Gaussian filtering and gradient calculation of the weight threshold method, and the crack edge features were extracted; The calculation method of crack width under Euclidean distance based on slope calculation was adopted to realize the analysis and calculation of crack width. The experimental results show that the accuracy of crack detection results in this paper is high, and the calculation accuracy of crack width parameters can meet the requirements of code.
- underwater vehicle /
- bridge detection /
- image processing /
- crack detection /
- crack width

HTML全文

图 1 双目水下机器人

Figure 1. Binocular underwater vehicle

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图 2 机器人检测轨迹

Figure 2. Detection trajectory of ROV

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图 3 灰度图像

Figure 3. Gray image

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图 4 canny算子边缘提取流程

Figure 4. Edge extraction process of canny operator

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图 5 采用双阈值判断前

Figure 5. Before using double threshold judgment

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图 6 采用双阈值判断后

Figure 6. After double threshold judgment

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图 7 裂缝边缘识别图

Figure 7. Crack edge identification diagram

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图 8 裂缝边缘拾取图

Figure 8. Pick up drawing of crack edge

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图 9 裂缝宽度值　/mm

Figure 9. Value of crack width

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图 10 裂缝边缘拟合图

Figure 10. Crack edge fitting diagram

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图 11 裂缝宽度值变化图 /mm

Figure 11. Variation diagram of crack width

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表 1 裂缝宽度计算值与真实值对比

Table 1. Comparison between calculated value and real value of crack width

样本编号	计算宽度/mm		实际宽度/mm		误差/mm		相对误差/(%)
样本编号	最小值	最大值	最小值	最大值	最小值	最大值	相对误差/(%)
1	0.273	0.604	0.26	0.61	0.013	0.006	2.99
2	0.094	3.282	0.10	3.13	0.006	0.152	5.43
3	0.224	1.169	0.21	1.13	0.014	0.039	5.06
4	0.25	1.428	0.26	1.36	0.010	0.068	4.42
5	0.266	0.839	0.28	0.80	0.014	0.039	4.94
6	0.136	2.456	0.13	2.42	0.006	0.036	3.05
7	0.276	2.01	0.26	1.94	0.016	0.070	4.88
8	0.198	0.708	0.18	0.69	0.018	0.018	6.30
9	0.152	0.600	0.13	0.60	0.022	0.000	8.46
10	0.215	0.886	0.20	0.90	0.015	0.014	4.53
11	0.334	0.984	0.32	1.02	0.014	0.036	3.95
12	0.184	1.127	0.18	1.08	0.004	0.047	3.29
13	0.257	2.482	0.26	2.46	0.003	0.022	1.02

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