Three-Dimensional Reconstruction of Road Structural Defects Using GPR Investigation and Back-Projection Algorithm
Ground-Penetrating Radar (GPR) has demonstrated significant advantages in the non-destructive detection of road structural defects due to its speed, safety, and efficiency. This paper proposes a three-dimensional (3D) reconstruction method for GPR images, integrating the back-projection (BP) imaging...
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MDPI AG
2024-12-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/25/1/162 |
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| author | Lutai Wang Zhen Liu Xingyu Gu Danyu Wang |
| author_facet | Lutai Wang Zhen Liu Xingyu Gu Danyu Wang |
| author_sort | Lutai Wang |
| collection | DOAJ |
| description | Ground-Penetrating Radar (GPR) has demonstrated significant advantages in the non-destructive detection of road structural defects due to its speed, safety, and efficiency. This paper proposes a three-dimensional (3D) reconstruction method for GPR images, integrating the back-projection (BP) imaging algorithm to accurately determine the size, location, and other parameters of road structural defects. Initially, GPR detection images were preprocessed, including direct wave removal and wavelet denoising, followed by the application of the BP algorithm to effectively restore the defect’s location and size. Subsequently, a 3D data set was constructed through interpolation, and the effective reflection data were extracted by using a clustering algorithm. This algorithm distinguished the effective reflection data from the background data by determining the distance threshold between the data points. The 3D imaging of the defect was then performed in MATLAB. The proposed method was validated using both gprMax simulations and laboratory test models. The experimental results indicate that the correlation between the reconstructed and actual defects was approximately 0.67, demonstrating the method’s efficacy in accurately achieving the 3D reconstruction of road structural defects. |
| format | Article |
| id | doaj-art-c202a0ffd05c4e89acaaf1f2b60fc4de |
| institution | DOAJ |
| issn | 1424-8220 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj-art-c202a0ffd05c4e89acaaf1f2b60fc4de2025-08-20T02:47:10ZengMDPI AGSensors1424-82202024-12-0125116210.3390/s25010162Three-Dimensional Reconstruction of Road Structural Defects Using GPR Investigation and Back-Projection AlgorithmLutai Wang0Zhen Liu1Xingyu Gu2Danyu Wang3Department of Roadway Engineering, School of Transportation, Southeast University, Nanjing 211189, ChinaDepartment of Roadway Engineering, School of Transportation, Southeast University, Nanjing 211189, ChinaDepartment of Roadway Engineering, School of Transportation, Southeast University, Nanjing 211189, ChinaDepartment of Roadway Engineering, School of Transportation, Southeast University, Nanjing 211189, ChinaGround-Penetrating Radar (GPR) has demonstrated significant advantages in the non-destructive detection of road structural defects due to its speed, safety, and efficiency. This paper proposes a three-dimensional (3D) reconstruction method for GPR images, integrating the back-projection (BP) imaging algorithm to accurately determine the size, location, and other parameters of road structural defects. Initially, GPR detection images were preprocessed, including direct wave removal and wavelet denoising, followed by the application of the BP algorithm to effectively restore the defect’s location and size. Subsequently, a 3D data set was constructed through interpolation, and the effective reflection data were extracted by using a clustering algorithm. This algorithm distinguished the effective reflection data from the background data by determining the distance threshold between the data points. The 3D imaging of the defect was then performed in MATLAB. The proposed method was validated using both gprMax simulations and laboratory test models. The experimental results indicate that the correlation between the reconstructed and actual defects was approximately 0.67, demonstrating the method’s efficacy in accurately achieving the 3D reconstruction of road structural defects.https://www.mdpi.com/1424-8220/25/1/162ground-penetrating radarnon-destructive testingthree-dimensional reconstructionBP imaging |
| spellingShingle | Lutai Wang Zhen Liu Xingyu Gu Danyu Wang Three-Dimensional Reconstruction of Road Structural Defects Using GPR Investigation and Back-Projection Algorithm Sensors ground-penetrating radar non-destructive testing three-dimensional reconstruction BP imaging |
| title | Three-Dimensional Reconstruction of Road Structural Defects Using GPR Investigation and Back-Projection Algorithm |
| title_full | Three-Dimensional Reconstruction of Road Structural Defects Using GPR Investigation and Back-Projection Algorithm |
| title_fullStr | Three-Dimensional Reconstruction of Road Structural Defects Using GPR Investigation and Back-Projection Algorithm |
| title_full_unstemmed | Three-Dimensional Reconstruction of Road Structural Defects Using GPR Investigation and Back-Projection Algorithm |
| title_short | Three-Dimensional Reconstruction of Road Structural Defects Using GPR Investigation and Back-Projection Algorithm |
| title_sort | three dimensional reconstruction of road structural defects using gpr investigation and back projection algorithm |
| topic | ground-penetrating radar non-destructive testing three-dimensional reconstruction BP imaging |
| url | https://www.mdpi.com/1424-8220/25/1/162 |
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