基于红外图像增强算法的混凝土内部缺陷检测研究

doi:10.3969/j.issn.1674-0696.2021.11.17

重庆交通大学学报（自然科学版） ›› 2021, Vol. 40 ›› Issue (11): 114-117.DOI: 10.3969/j.issn.1674-0696.2021.11.17

• 交通基础设施工程 • 上一篇

基于红外图像增强算法的混凝土内部缺陷检测研究

郑丹，谭帅帅

(重庆交通大学河海学院，重庆 400074)

收稿日期:2019-11-01 修回日期:2020-10-28 发布日期:2021-11-24
作者简介:郑丹（1979—），男，重庆万州人，博士，主要从事混凝土断裂与强度、混凝土结构动力分析方面的研究。E-mail:574626911@qq.com 通信作者：谭帅帅（1993—），男，江苏连云港人，硕士研究生，主要从事水工混凝土无损检测方面的研究。E-mail:541777261@qq.com
基金资助:
国家自然科学基金项目（51479013）；重庆青年科技人才培养计划项目（cstc2014kjrc-qnrc30001）

Concrete Internal Defect Detection Based on Infrared Image Enhancement Algorithm

ZHENG Dan, TAN Shuaishuai

(College of River and Ocean Engineering, Chongqing Jiaotong University, Chongqing 400074, China)

Received:2019-11-01 Revised:2020-10-28 Published:2021-11-24

摘要/Abstract

摘要： 由于混凝土的不良导热性能，传统红外检测方法分辨率低、缺陷特征不明显。针对上述问题，研究了结合红外热像和增强图像算法的混凝土内部缺陷检测方法；开展了混凝土中不同深度、大小的缺陷的红外检测试验，并采用时域拟合与限制对比度直方图均衡算法相结合的方式对红外检测图像进行处理；对比了处理前后的热像图缺陷识别效果。试验结果表明：算法应用后缺陷识别所需温差从0.3 ℃降至0.1 ℃，边缘细节得到优化，提高了红外图像混凝土内部缺陷检测的精度和实用范围。该方法拓展了红外热像在混凝土无损检测中的应用范围。

关键词: 水利工程；混凝土；红外缺陷检测；图像增强；限制对比度直方图均衡化

Abstract: The traditional infrared detection method has low resolution and its defect characteristics were not obvious on account of the poor thermal conductivity of concrete. In view of the problems above, a concrete internal defect detection method combining infrared thermal image and enhanced image algorithm was proposed. The infrared detection tests of concrete with defects of different depths and sizes were carried out. The infrared detection images were processed by means of combining time-domain fitting with CLAHE algorithm, and the defect recognition effects before and after processing were compared. The test results show that the temperature difference required for defect identification decreases from 0.3 ℃ to 0.1 ℃ after the application of algorithm and the edge details are optimized, which improves the accuracy and practical range of infrared image concrete internal defect detection. The proposed method expands the application range of infrared thermography in concrete nondestructive testing.

Key words: hydraulic engineering; concrete; infrared defect detection; image enhancement; CLAHE

中图分类号:

TV431

郑丹，谭帅帅. 基于红外图像增强算法的混凝土内部缺陷检测研究[J]. 重庆交通大学学报（自然科学版）, 2021, 40(11): 114-117.

ZHENG Dan, TAN Shuaishuai. Concrete Internal Defect Detection Based on Infrared Image Enhancement Algorithm[J]. Journal of Chongqing Jiaotong University(Natural Science), 2021, 40(11): 114-117.

参考文献

［1］戚磊，郭朝辉.混凝土内部缺陷红外无损检测多因素影响分析［J］.公路，2014(8)：234-240.
QI Lei, GUO Chaohui. Analysis of multi-factor impact on infrared thermal wave nondestructive testing of internal defects of concrete［J］. Highway,
2014(8): 234-240.
［2］王博正，董丽虹，王海斗，等.激光红外热成像技术在材料缺陷检测中的研究和应用现状［J］.材料导报，2020，34(5)：5127-5132.
WANG Bozheng, DONG Lihong, WANG Haidou, et al. Research and application of laser infrared thermography in material defect detection［J］.
Materials Reports, 2020,34(5): 5127-5132.
［3］袁昕，谢慧才，陈高峰.建筑物外墙饰面砖粘贴质量的红外热像检测试验研究［J］.四川建筑科学研究，2003，29(2)：43-45.
YUAN Xin, XIE Huicai, CHEN Gaofeng. Study of infrared thermography in non-destructive testing of building finish［J］. Building Science Research of
Sichuan, 2003, 29(2): 43-45.
［4］王振波，徐道远，王向东，等.混凝土热损伤试验研究［J］.河海大学学报，2001，29(6)：94-98.
WANG Zhenbo, XU Daoyuan, WANG Xiangdong, et al. Experime-ntal study on concrete thermal damage［J］. Journal of Hohai University, 2001, 29(6):
94-98.
［5］张兆礼，赵春晖，梅晓丹.现代图像处理技术及MATLAB实现［M］.北京：人民邮电出版社，2001：5-11.
ZHANG Zhaoli, ZHAO Chunhui, MEI Xiaodan. Modern Image Processing Technology and MATLAB Algorithm［M］. Beijing: Posts & Telecom Press,
2001: 5-11.
［6］ GONZLEZ R C, WOODS R E, EDDINS S L. Digital Image Processing Using MATLAB［M］. Upper Saddle River, New Jersey, America: Gatesmark
Publishing, 2009: 6-28.
［7］ WONG C Y, JIANG G, RAHMAN M A, et al. Histogram equalization and optimal profile compression based approach forcolour image
enhancement［J］. Journal of Visual Communication & Image Representation, 2016, 38: 802-813.
［8］ SINGH K, VISHWAKARMA D K, WALIA G S, et al. Contrast enhancement via texture region based histogram equalization［J］.Journal of Modern
Optics. 2016, 63(15): 1444-1450.
［9］邹樾旋.红外热像法在水工混凝土裂缝检测中的应用研究［D］.重庆：重庆交通大学，2017.
ZOU Yuexuan. Experimental Research of Nonlinear Coupling Creep and Damage in Concrete ［D］. Chongqing: Chongqing Jiaotong University, 2017.
［10］ CHENG C C, CHENG T M, CHIANG C H. Defect detection of conc-rete structures using both infrared thermography and elastic waves［J］.
Automation in Construction, 2008, 18(1): 87-92.
［11］ MAHMOOD Z, MUHAMMAD N, BIBI N, et al. Human visual enhancement using Multi Scale Retinex［J］. Informatics in Medicine Unlocked,
2018, 13: 9-20.
［12］陈永亮.灰度图像的直方图均衡化处理研究［D］.合肥：安徽大学，2014.
CHEN Yongliang. Gray Image Histogram Equalization Processing Research ［D］. Hefei: Anhui University, 2014.
［13］刘玉婷，陈峥，付占方，等.基于CLAHE的红外图像增强算法［J］.激光与红外，2016，46(10)：1290-1294.
LIU Yuting, CHEN Zheng, FU Zhanfang, et al. Infrared image enhancement algorithm based on CLAHE［J］. Laser ＆ Infrared. 2016，46(10):1290-1294.

[1]	董玉文1，彭亮2，谢辉1. 橡胶粉对混凝土抗冻耐久性的影响[J]. 重庆交通大学学报（自然科学版）, 2021, 40(07): 112-117.
[2]	董玉文1，余鑫2，秦瑶1,王宗波1. 冻融与锈蚀作用对钢筋混凝土黏结性能的影响[J]. 重庆交通大学学报（自然科学版）, 2021, 40(05): 81-86.

基于红外图像增强算法的混凝土内部缺陷检测研究

Concrete Internal Defect Detection Based on Infrared Image Enhancement Algorithm

PDF

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 2

编辑推荐

Metrics