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首页> 外文期刊>Annals of the American Thoracic Society >A Linear Prediction and Support Vector Regression-Based Debonding Detection Method Using Step-Frequency Ground Penetrating Radar
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A Linear Prediction and Support Vector Regression-Based Debonding Detection Method Using Step-Frequency Ground Penetrating Radar

机译:基于线性预测和支持向量回归的基于回归的剥离检测方法穿透雷达

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摘要

In the field of civil engineering, ground penetrating radar (GPR) is a highly efficient nondestructive testing tool for sustainable management of pavement infrastructures. GPR allows to evaluate the structure of the roadway over large distances (with contactless configurations) and to detect significant subsurface defects. This letter presents a new method to detect thin debondings within pavement structures with the step-frequency GPR. The proposed method enables us to carry out the detection with only a small number of frequency samples and A-scans. It is based on the linear prediction and support vector regression theories. Two experimental results show its effectiveness.
机译:在土木工程领域,地面穿透雷达(GPR)是一种高效的无损性测试工具,可用于路面基础设施的可持续管理。 GPR允许评估大距离(具有非接触式配置)的道路结构,并检测显着的地下缺陷。 这封信介绍了一种新方法,可以使用梯度频率GPR检测路面结构中的薄剥离。 所提出的方法使我们只能用少量频率样本和扫描进行检测。 它基于线性预测和支持向量回归理论。 两个实验结果表明了其有效性。

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