Cement pavement void detection algorithm based on GPR signal and continuous wavelet transform method

The dimension of the void area in pavement is crucial to its structural safety. However, there is no effective method to measure its geometric parameters. To address this issue, a void size extraction algorithm based on the continuous wavelet transform (CWT) method was proposed using ground-penetrat...

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Vydáno v:Scientific reports Ročník 13; číslo 1; s. 19710 - 15
Hlavní autoři: Yu, Qiuqin, Li, Youxin, Luo, Tingyi, Zhang, Jun, Tao, Liang, Zhu, Xin, Zhang, Yun, Luo, Liufen, Xu, Xinxin
Médium: Journal Article
Jazyk:angličtina
Vydáno: London Nature Publishing Group UK 12.11.2023
Nature Publishing Group
Nature Portfolio
Témata:
704/2151/214
704/2151/2809
Algorithms
Energy
Humanities and Social Sciences
Mathematical models
multidisciplinary
Science
Science (multidisciplinary)
Structural engineering
Wavelet transforms
ISSN:2045-2322, 2045-2322
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Shrnutí:The dimension of the void area in pavement is crucial to its structural safety. However, there is no effective method to measure its geometric parameters. To address this issue, a void size extraction algorithm based on the continuous wavelet transform (CWT) method was proposed using ground-penetrating radar (GPR) signal. Firstly, the finite-difference time-domain (FDTD) method was used to investigate the GPR response of void areas with different shapes, sizes, and depths. Next, the GPR signal was processed using the CWT method, and a 3D image based on the CWT result was used to visualize the void area. Based on the differences between the void and normal pavement in the time and frequency domains, the signal with maximum energy from the CWT time–frequency result was extracted and combined to reconstruct the new B-scan image, where void areas have energy concentration phenomenon. Based on this, width and depth of void detection algorithm was proposed to recognize the void area. Finally, the detection algorithm was verified both in numerical model and physical lab model. The results indicated that the CWT time–frequency energy spectrum can be used to enhance the void feature, and the 3D CWT image can clearly visualize the void area with a highlighted energy area. After fully testing and validating in numerical and lab models, our proposed method achieved high accuracy in void width and depth detection, providing a precise method for estimating void dimension in pavement. This method can guide DOT departments to carry out pre-maintenance, thereby ensuring pavement safety.
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ISSN:2045-2322
2045-2322
DOI:10.1038/s41598-023-46752-2