Research on Normalized Histogram Characterization of Infrared Thermal Image of Rock Sample Damage
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摘要: 红外热像法是一种评估煤岩损伤有广阔应用前景的手段。通过红外热像中的关键信息进行识别和提取,从而对煤岩损伤状态进行判别。本文对岩样进行了单轴加载,同步采集红外热像和岩样表面裂隙发育图,采用归一化直方图的方式对红外热像进行了分析处理,并利用不同灰度值区间的像素占比对红外热像的细节信息进行了定量表征。结果表明,不同时刻红外热像的灰度值分布能良好反映试样受载破坏过程表面温度和应力值的变化,在主破裂发生时,灰度值区间[240, 255](岩样表面温度29.01℃~33.19℃)的像素点百分比较上一时刻增加13.85个百分点。另外,灰度值区间[224, 255]的像素占比随时间的变化趋势与岩样损伤变量呈高度相关性,这表明基于归一化直方图的红外热像能够很好表征岩样损伤破坏过程。Abstract: Infrared thermal imaging is a very promising method for evaluating coal and rock damage. To further process the infrared image and extract the key information, the damage status of coal and rock can be distinguished according to this quantitative information. With uniaxial loading, fracture development maps were developed, and synchronous acquisition of infrared images of the rock samples was carried out. The infrared images were analyzed and processed using a normalized histogram, and the details of the infrared images were quantitatively characterized. The results show that the gray value distribution of the infrared images at different times can reflect the surface temperature changes and stress values during the failure process of the sample. When the main fracture occurred, the percentage of pixels in the gray value interval [240, 255] (the surface temperature of the rock sample was 29.01℃-33.19℃) increased by 13.85% compared with that in the previous moment. In addition, the change trend of the proportion of pixels in the gray value interval [224, 255] over time is highly correlated with rock damage variables, which shows that the normalized histogram can characterize the damage and destruction process of the rock mass.
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Key words:
- infrared thermal image /
- normalized histogram /
- gray value /
- rock sample damage
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表 1 不同灰度值区间的像素点变化与损伤变量的相关性
Table 1. The correlation between the change of pixels in different gray values and damage variables
Gray value interval [224, 239] (28.73℃-29.00℃) [240, 255] (29.01℃-33.19℃) [224, 255] (28.73℃-33.19℃) Related coefficient 0.944 0.697 0.929 Correlation Height correlation Significant correlation Height correlation -
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