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Thin crack observation in a reinforced concrete bridge pier test using image processing and analysis

机译:钢筋混凝土桥墩试验中细裂纹的观察及图像分析

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摘要

In reinforced concrete (RC) structural experiments, the development of concrete surface cracks is an important factor of concern to experts. One conventional crack observation method is to suspend a test at a few selected testing steps and send inspectors to mark pen strokes on visible cracks, but this method is dangerous and labor intensive. Many image analysis methods have been proposed to detect and measure the dark shadow lines of cracks, reducing the need for manual pen marking. However, these methods are not applicable for thin cracks, which do not present clear dark lines in images. This paper presents an image analysis method to capture thin cracks and minimize the requirement for pen marking in reinforced concrete structural tests. The paper presents the mathematical models, procedures, and limitations of our image analysis method, as well as the analysis flowchart, the adopted image processing and analysis methods, and the software implementation. Finally, the results of applying the proposed method in full-scale reinforced concrete bridge experiments are presented to demonstrate its performance. Results demonstrate that this method can capture concrete surface cracks even before dark crack lines visible to the naked eye appear.
机译:在钢筋混凝土(RC)结构实验中,混凝土表面裂纹的发展是引起专家关注的重要因素。一种常规的裂纹观察方法是在几个选定的测试步骤中暂停测试,并派检查员在可见的裂纹上标记笔的笔划,但是这种方法很危险且劳动强度大。已经提出了许多图像分析方法来检测和测量裂纹的暗影线,从而减少了手动标记笔的需要。但是,这些方法不适用于细裂纹,细裂纹不会在图像中显示清晰的黑线。本文提出了一种图像分析方法,可以捕获细小裂缝并最大程度地减少钢筋混凝土结构测试中对笔标记的要求。本文介绍了我们的图像分析方法的数学模型,过程和局限性,以及分析流程图,采用的图像处理和分析方法以及软件实现。最后,提出了将该方法应用于大型钢筋混凝土桥梁试验的结果,以证明其性能。结果表明,该方法甚至可以在肉眼看不到深色裂纹线出现之前捕获混凝土表面裂纹。

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