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Woodpecker knocking artificial intelligence tunnel defect detection and recognition system

An artificial intelligence and woodpecker technology, applied in mining equipment, mining equipment, earthwork drilling and mining, etc., can solve the problems of inaccuracy and inconvenient manual identification of holes in the back, etc., and achieve broad application prospects, novel design concepts, guaranteed accuracy and effect of effect

Pending Publication Date: 2021-11-09
CHINA RAILWAY DESIGN GRP CO LTD
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] The present invention is proposed to solve the problem of inconvenient and inaccurate manual identification of the cavity behind the existing tunnel, and its purpose is to provide an intelligent tunnel defect detection and identification system to ensure the accuracy and efficiency of identification of the cavity behind the tunnel structure

Method used

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  • Woodpecker knocking artificial intelligence tunnel defect detection and recognition system
  • Woodpecker knocking artificial intelligence tunnel defect detection and recognition system
  • Woodpecker knocking artificial intelligence tunnel defect detection and recognition system

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Embodiment Construction

[0022] The technical solution of the present invention will be further described below in conjunction with the accompanying drawings. Apparently, the described embodiments are only some of the embodiments of the present invention, but not all of them. Based on the embodiments of the present invention, all other implementations obtained by persons of ordinary skill in the art without making creative efforts fall within the protection scope of the present invention.

[0023] Such as figure 1 As shown, the woodpecker knocks on the artificial intelligence tunnel defect detection system, the walking steel frame 1 and the hammering mechanical arm 3, the hammering mechanical arm 3 is slidably connected to the walking steel frame 1, and the hammering mechanical arm 3 Relative to the sliding route of the walking steel frame 1, it is basically parallel to the inner wall of the tunnel section. The hammer 9 is provided on the hammering mechanical arm 3, which can swing and strike the inn...

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Abstract

The invention provides a woodpecker knocking artificial intelligence tunnel defect detection and recognition system. The woodpecker knocking artificial intelligence tunnel defect detection and recognition system comprises a walking steel frame and a hammering mechanical arm, the hammering mechanical arm is slidably connected to the walking steel frame, and a sliding path of the hammering mechanical arm relative to the walking steel frame is basically parallel to the inner wall line of the tunnel section. The hammering mechanical arm is provided with a driving hammer which can swing and knock the inner wall of the tunnel, and is further provided with a sound wave collector, and the sound wave collector is used for collecting knocking sound wave signals of the driving hammer and feeding back the sound wave signals to an external control terminal. According to the woodpecker knocking artificial intelligence tunnel defect detection and recognition system, the accuracy and efficiency of tunnel structure back cavity recognition can be ensured.

Description

technical field [0001] The invention relates to the technical field of tunnel structures, in particular to a woodpecker-tapping artificial intelligence tunnel defect detection system. Background technique [0002] In the tunnel structure, over-excavation and under-excavation of surrounding rock, large deformation, groundwater seepage, primary support deterioration, and lining pouring defects, etc., will cause the lining structure and surrounding rock to be not tightly bonded, resulting in voids behind the lining, which in turn will cause damage to the tunnel structure. Uneven force makes it less safe. In order to ensure the safety of operation in the tunnel, it is necessary to identify the cavity behind the tunnel structure, determine the position and size of the cavity, and then provide a reliable basis for its disease control. At present, the commonly used identification methods for voids behind tunnels are manual tapping and electromagnetic ground penetrating radar. Thi...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): E21F17/18
CPCE21F17/18
Inventor 白鸿国孟庆余王旭吴强苏哿易志伟霍飞贾辉周艺万自强韩璐王喆
Owner CHINA RAILWAY DESIGN GRP CO LTD
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