# GPR-based Detection of Voids and Evaluation of Grouting Under Semi-rigid Basement

## TL;DR

This paper presents a comprehensive study on using GPR technology to detect, measure, and evaluate voids beneath semi-rigid road bases, including analysis methods and effects of data processing techniques.

## Contribution

It introduces new GPR-based detection and measurement methods for voids under semi-rigid bases, with detailed analysis of void characteristics and data processing impacts.

## Key findings

- GPR can identify void types and dimensions effectively.
- Detection methods for void height and horizontal size are validated.
- Data processing techniques significantly influence image clarity and detection accuracy.

## Abstract

The void underneath semi-rigid base is a common defect in roads. There are some difficulties in the detection and repair for this kind of hidden damage, as well as in the evaluation of the effects of grouting treatment. For the detection and maintenance of roads, it is essential to study the detection and judging for voids underneath base and the evaluation of the spread of grout. Through theoretical analysis, numerical simulation and analysis of real data, this research generated the characteristics of under-base voids of different types and dimensions on GPR images, proposed the detecting and dimension-measuring methods for under-base voids, and studied the process and effects of data analysis techniques. (1) The characteristics of under-base voids of different types (air-filled, water-filled or grout-treated) and dimensions (height and horizontal dimensions), on A-scan and B-scan GPR image respectively, were analyzed theoretically. (2) Approaches for detecting voids and for estimating its height were studied, focusing on voids with a height ranging from 0.01m to 0.3m. (3) The approach for estimating the horizontal dimension of voids was studied, focusing on voids with a length ranging from 0.04m to 0.52m. (4) The data processing process was discussed. Also, the effects of different data processing techniques were studied in terms of noise filtering and attenuation compensation, and their influence on the image characteristics was also discussed.

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Source: https://tomesphere.com/paper/1812.07495