热成像
仿形(计算机编程)
目视检查
沥青路面
图像处理
热的
沥青
环境科学
无损检测
材料科学
计算机科学
人工智能
红外线的
图像(数学)
光学
气象学
物理
放射科
复合材料
操作系统
医学
作者
Aidin J. Golrokh,Xingyu Gu,Yang Lu
出处
期刊:Journal of Performance of Constructed Facilities
[American Society of Civil Engineers]
日期:2021-02-01
卷期号:35 (1)
被引量:11
标识
DOI:10.1061/(asce)cf.1943-5509.0001557
摘要
Infrared thermography is a cost-effective nonintrusive testing approach to assess surface and near-surface distresses, such as asphalt pavement surface cracks. However, the raw data collected by thermal cameras cannot be directly used for pavement surface distress inspection. Thus, advanced thermal image processing methods are desirable for extracting indicators of hidden flaws. The objective of this research was to develop an integrated system that combines infrared imaging, high-resolution visual imaging, real-time image processing, and data-rich analytics for automated inspection to support decision making for pavement preservative maintenance. This work developed a code that can integrate the characteristics captured by both thermal and visual images to provide a quantitative identification of the surface cracks and their severity. Field-test data were collected and a statistical analysis was conducted to correlate temperature gradient to the surface crack profile of asphalt pavement. It was found that the surface temperature distribution pattern has a direct correlation with pavement crack profile, and can be used as an indicator of crack depth. The proposed real-time thermal imaging-based system was found to be feasible for field inspection, and the three-dimensional (3D) crack profiling method can help produce fairly accurate measurements to enable fast and easy decision support for pavement preservation practices.
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