TIGPR: A Multi-View Ground Penetrating Radar Detection Data for Damage Assessment of Transportation Infrastructure

Published: 18 November 2024| Version 1 | DOI: 10.17632/ckgvrft232.1
Contributors:
Zhen Liu,
,

Description

The TIGPR dataset is a comprehensive collection of ground-penetrating radar (GPR) images for detecting damage in transportation infrastructure, including roads, bridges, tunnels, and airports. This dataset encompasses common types of damage found in transportation infrastructure, such as cracks, interlayer debonding, looseness, and voids. The images were collected from real-world surveys of highways, bridges, tunnels, and municipal roads in regions such as Guizhou, Jinhua, and Nanjing. The equipment used includes the 2D GPR equipment: IDS-FastWave and MALA GX750, as well as the 3D GPR equipment GeoScope 3D-Radar. The 2D GPR systems captured B-scan images with a resolution of 200 × 200 pixels, while the 3D GPR system provided both B-scan and C-scan images with a resolution of 320 × 320 pixels. The image dimensions correspond to actual infrastructure scales, with a length of 10 meters and a depth of 1 meter. This dataset integrates information from multiple damage types and views, supporting the development of deep learning models for the detection, classification, and segmentation of transportation infrastructure damage. It has the potential to enhance non-destructive testing and automated evaluation of transportation infrastructure.

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Institutions

Southeast University

Categories

Urban Infrastructure System, Ground-Penetrating Radar, Transport Infrastructure, Deep Learning, Damage Classification

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