Application of infrared thermography in concrete bridge deck inspection: current practices, challenges and future needs

热成像 桥(图论) 计算机科学 无损检测 分层(地质) 图像处理 环境科学 建筑工程 数据科学 遥感 工程类 人工智能 红外线的 地质学 图像(数学) 构造学 光学 物理 内科学 放射科 古生物学 医学 俯冲
作者
Abdelazim Ibrahim,Nour Faris,Tarek Zayed,Abdul Hannan Qureshi,Sherif Abdelkhalek,Eslam Mohammed Abdelkader
出处
期刊:Nondestructive Testing and Evaluation [Informa]
卷期号:: 1-44
标识
DOI:10.1080/10589759.2024.2443810
摘要

Concrete bridges are vital infrastructures and maintaining their functionality is of utmost importance. Infrared thermography (IRT) has emerged as a promising nondestructive evaluation for examining concrete bridges. However, a comprehensive review of its application in concrete bridge inspections is lacking. This study addresses this gap by employing a mixed methodology approach, integrating scientometric and systematic analyses. The analysis encompassed 110 documents from Scopus and Web of Science databases, revealing a notable increase in publications since 2017, with 66.36% of the total publications produced after this year. The USA played a leading role in this research area, contributing 49 studies. The findings demonstrated the effectiveness of using IRT in detecting shallow defects, particularly delamination (56.92% of studies). However, it faced challenges in identifying deeper defects and accurately estimating their depth. Various IRT data analysis approaches, including statistical analysis, image processing, deep and machine learning and numerical analysis, were examined under two main scopes: defect detection and detectability conditions. Among these methods, image processing emerged as the most widely used technique, accounting for 51% of applications. Factors influencing IRT performance were categorised into environmental, physical and technical groups. Notably, factors such as depth-to-size ratios and environmental conditions (e.g. temperature and solar radiation) were found to highly reduce the accuracy of defect detection. Overall, the findings underline the need to address limitations in defect depth detection, develop standardised analysis protocols and explore automated techniques for processing large areas of images. Furthermore, investigating the interplay of environmental factors and the effect of overnight cooling could further refine IRT's application, enhancing its reliability for practical bridge inspection.

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