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Underground shallow seismic source positioning method based on deep learning

A technology of source location and deep learning, applied in seismic signal processing, seismology, scientific instruments, etc., can solve the problem of high-precision positioning of targets in shallow small areas, to expand the number and diversity, improve efficiency, and eliminate positioning. The effect of the blind spot

Active Publication Date: 2019-11-05
ZHONGBEI UNIV
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AI Technical Summary

Problems solved by technology

[0008] The present invention provides a method for locating underground shallow seismic sources based on deep learning. The technical problem to be solved is: the problem that targets in small shallow areas cannot be positioned with high precision

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  • Underground shallow seismic source positioning method based on deep learning
  • Underground shallow seismic source positioning method based on deep learning
  • Underground shallow seismic source positioning method based on deep learning

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Embodiment Construction

[0024] In order to make the purpose, content and advantages of the present invention clearer, the specific implementation manners of the present invention will be further described in detail below.

[0025] The present invention proposes a deep learning-based underground shallow seismic source location method, which is characterized in that it specifically includes the following steps:

[0026] S1. Arrange distributed shock sensor array

[0027] The coordinate origin is randomly preset in the monitoring area, and the n sensors are rotated at 10° intervals, with a growth radius of 1m, and the vibration sensors are arranged on the surface in a clockwise direction to form a spiral array, and the high-precision Beidou is used to obtain each sensor coordinate information (x j ,y j ,z j )(j=1,2,3,K,n); n=44;

[0028] S2. Generate learning samples

[0029] S2.1: Divide monitoring area grid:

[0030] Such as image 3 As shown, the monitored area is divided into grids, and (acco...

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Abstract

The invention relates to an underground shallow seismic source positioning method based on deep learning. The underground shallow seismic source positioning method comprises the following steps: arranging a distributed vibration sensor array, generating a learning sample, setting a seismic source bullet position corresponding to a three-dimensional energy field image sample as a training label, constructing a deep learning network framework, training a network, and positioning an actual explosion seismic source. According to the invention, the intermediate steps of positioning parameter extraction, positioning model modeling, positioning model calculation and the like in a traditional shallow seismic source positioning process are reduced. The method greatly improves the seismic source positioning efficiency, eliminates the positioning blind area, reduces the dependence of the channel reconstruction precision of a monitoring region on the seismic source positioning precision, and provides a new seismic source positioning method for the underground shallow seismic source positioning.

Description

technical field [0001] The invention belongs to the technical field of blasting vibration testing, and in particular relates to a method for locating underground shallow seismic sources based on deep learning, which is applicable to fixed-point group strike positioning under unknown geological structure conditions. Background technique [0002] Underground shallow seismic source refers to the events that occur in the space where the depth of the underground seismic source does not exceed 100m. Its passive positioning is the main way to solve the problem of underground explosive point positioning and penetration trajectory measurement of high-value ammunition in the military field; it is the realization of geological monitoring in the civilian field. Engineering blasting, anti-theft monitoring of cultural relics, coal mine survey, analysis of surface structure composition, geological structure exploration, underground rare mineral exploration, oil exploration and excavation an...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06N3/04G01V1/28
CPCG01V1/282G06N3/045
Inventor 李剑王彦博李冒金韩焱苏新彦王小亮莫璧铭李禹剑
Owner ZHONGBEI UNIV
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