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Road underground cavity detection early warning method based on deep learning and ground penetrating radar

A technology of ground penetrating radar and underground cavity, applied in neural learning methods, measurement devices, radio wave measurement systems, etc. Effect

Active Publication Date: 2021-06-22
CHANGAN UNIV
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  • Abstract
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  • Claims
  • Application Information

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Problems solved by technology

[0004] However, it is precisely because the detection principle of GPR is different from the conventional direct measurement method that the qualitative and quantitative analysis of a large number of underground diseases depends on the judgment of the inspectors, the detection accuracy is low, and there is no mature GPR at home and abroad. Automated Analysis Solution for Test Results

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  • Road underground cavity detection early warning method based on deep learning and ground penetrating radar
  • Road underground cavity detection early warning method based on deep learning and ground penetrating radar
  • Road underground cavity detection early warning method based on deep learning and ground penetrating radar

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Embodiment 1

[0050] See figure 1 , figure 1 It is a schematic flowchart of a method for detecting and early warning of road underground cavities based on deep learning and ground penetrating radar provided by an embodiment of the present invention. This embodiment proposes a road underground cavity detection and early warning method based on deep learning and ground penetrating radar. The road underground cavity detection and early warning method based on deep learning and ground penetrating radar includes the following steps:

[0051] Step 1. Collect the noisy ground penetrating radar echo signal of the actual road through the ground penetrating radar.

[0052] Specifically, see figure 2 , figure 2It is a schematic diagram of the scene of obtaining the echo signal of the ground penetrating radar provided by the embodiment of the present invention. In this embodiment, the echo signal of the ground penetrating radar with the underground hollow road is collected by the ground penetratin...

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Abstract

The invention discloses a road underground cavity detection early warning method based on deep learning and a ground penetrating radar. The method comprises the following steps: collecting a noisy ground penetrating radar echo signal of an actual road through the ground penetrating radar; filtering and smoothing the noise-containing ground penetrating radar echo signal to obtain a de-noised ground penetrating radar echo signal; performing augmentation processing on the de-noised ground penetrating radar echo signal by adopting a generative adversarial neural network to obtain a radar echo signal; and detecting the radar echo signal by using a fast regional convolutional neural network to obtain a first detection early warning result. According to the method, the GANs network is adopted to augment the underground hole data set, the problem that training samples are insufficient during underground hole detection based on deep learning is solved, meanwhile, the fast regional convolutional neural network model is adopted for detection, the learning ability of the network to signal features is improved, and the detection accuracy is improved. The deep learning technology is better applied to the radar signal detection technology, and nondestructive detection can be carried out on the road more accurately and quickly.

Description

technical field [0001] The invention belongs to the technical field of road detection, and in particular relates to a detection and early warning method for road underground cavities based on deep learning and ground penetrating radar. Background technique [0002] The roadbed needs to be inspected after the road is built or passed for a period of time. The quality of the roadbed is an important indicator to ensure road safety. Also known as ground penetrating radar and geological radar, it is a non-destructive detection method that uses high-frequency radio waves to determine the distribution of underground media. It can detect metal and non-metal objects, such as underground cement pipes, etc. [0003] With the gradual increase of the service life of the road, the road overload or the leakage of the underground pipeline can cause the damage of the road base, and the serious underground cavity will be generated, which can easily cause the road surface to collapse and cause ...

Claims

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Application Information

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IPC IPC(8): G01S7/41G01S13/88G06N3/04G06N3/08
CPCG01S7/417G01S13/885G06N3/08G06N3/048G06N3/045
Inventor 高尧李伟裴莉莉沙爱民孙朝云王飒耿方圆
Owner CHANGAN UNIV
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