Estimation method of radius of buried depth of underground metal circular pipe based on BP neural network

A BP neural network, circular tube technology, applied in the direction of reflection/re-radiation of radio waves, use of re-radiation, measurement devices, etc., can solve problems such as inability to meet high-precision estimation

Active Publication Date: 2017-11-28
CENT SOUTH UNIV
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Problems solved by technology

Such results cannot meet the purpose of GPR for high-precision estimation of par

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  • Estimation method of radius of buried depth of underground metal circular pipe based on BP neural network
  • Estimation method of radius of buried depth of underground metal circular pipe based on BP neural network
  • Estimation method of radius of buried depth of underground metal circular pipe based on BP neural network

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Embodiment 1

[0044] In this example, the value interval of the relative permittivity ε of the underground medium is [3.0,3.5,4.0,...,7.5], a total of 10 data. The radius range of the metal tube is [0.05, 0.08, 0.11, 0.14, 0.17], the unit is m, and there are 10 data in total. The value range of the buried depth of the metal circular pipe is [0.30,0.32,0.34,...,0.68], the unit is m, and there are 10 data in total. After the three vectors are combined, the capacity of the training data set sample is 1000. For each sample, use GPRMAX forward modeling software, set the transmitting antenna tx and receiving antenna rx at a height of 0.1m from the ground, the wavelet type is ricker wave, the center frequency is 1GHz, and the B-Scan echo data of the ground penetrating radar is obtained . The B-Scan data is extracted from the direct wave and the strongest energy channel, and the A-Scan data directly above the metal tube is obtained, and the feature extraction of the data is performed, and the tim...

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Abstract

The invention discloses an estimation method of the radius of the buried depth of an underground metal circular pipe based on the BP neural network. The method comprises steps of by use of ground penetrating radar to carry out direct simulation so as to obtain radar echo data of underground metal circular pipes with different radiuses and buried depths in different media; extracting the A-Scan echo peak value right above the metal circular pipes, peak value arrival time and an echo energy value in a preset time period, and based on the three parameters, constructing characteristic vectors so as to a form characteristic vector matrix; using the characteristic vector matrix as a data set of a training sample input part, wherein the data set of the training sample output part consists of the radiuses and the buried depths of the existing metal circular pipes and relative dielectric constants of background media; designing a structure of the BP neural network, and using training sample data to train the BP neural network; after the training is finished, inputting characteristic parameters of to-be-tested ground penetrating radar echo data into the BP neural network; and estimating the radiuses of the buried depths of the underground metal circular pipes. According to the invention, the radiuses of the buried depths of the underground metal circular pipes can be quickly and precisely estimated.

Description

technical field [0001] The invention belongs to the field of ground-penetrating radar non-destructive detection, in particular to a method for feature extraction of ground-penetrating radar echo signals and the radius and buried depth of underground metal circular pipes. Background technique [0002] Ground Penetrating Radar (GPR) is an effective and convenient non-destructive detection technology. It transmits broadband electromagnetic waves to the ground through the transmitting antenna, and then receives the scattered waves in the underground area at the receiving antenna end. When the electromagnetic wave propagates in the underground medium, it encounters electromagnetic differences and scatters at the interface, so that parameters such as the dielectric properties, spatial position, structural shape, and burial depth of the underground medium and the detection target can be inferred based on the waveform and characteristics of the received electromagnetic wave. [000...

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Application Information

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IPC IPC(8): G01S13/88
CPCG01S13/885G01S13/887
Inventor 雷文太左逸玮施荣华彭楠满敏梁琼
Owner CENT SOUTH UNIV
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