Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Tunnel detection method and device based on unmanned aerial vehicle

A detection method, UAV technology, applied in computer parts, image analysis, instruments, etc., can solve problems such as recognition rate uncertainty

Active Publication Date: 2021-08-20
SHENZHEN UNIV
View PDF9 Cites 1 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0006] The main purpose of the present invention is to provide a tunnel detection method and device based on drones, aiming to solve the problem that traditional disease inspection mainly relies on visual inspection to determine the type of disease initially, and the recognition rate depends on the experience of the inspectors, and the recognition rate has large discrepancies. question of certainty

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Tunnel detection method and device based on unmanned aerial vehicle
  • Tunnel detection method and device based on unmanned aerial vehicle
  • Tunnel detection method and device based on unmanned aerial vehicle

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0040] In order to make the object, technical solution and advantages of the present invention more clear and definite, the present invention will be further described in detail below with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention.

[0041] Convolutional neural network is a kind of neural network method based on convolution operation, which is one of the representative networks of deep neural network. Convolutional neural network has the characteristics of parameter sharing, local perception and multi-core, and uses multiple volumes The product kernel is used for calculation, which can effectively extract different features. 3D-CNN usually consists of 3-dimensional convolution kernels. Two-dimensional convolution (CNN, Convolutional Neural Networks, Convolutional Neural Networks) is convolution in spatial dimensions,...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention discloses a tunnel detection method and device based on an unmanned aerial vehicle. The method comprises the following steps: receiving a video image of a tunnel acquired by the unmanned aerial vehicle; performing preprocessing and standardization processing on the video image; and inputting the preprocessed and standardized video image into a trained three-dimensional convolutional neural network (3D-CNN) model, wherein the three-dimensional convolutional neural network model outputs a tunnel disease detection result according to the video image. According to the method, the video image of the tunnel is acquired through the unmanned aerial vehicle, and the video image is input into the trained three-dimensional convolutional neural network model, so that the space and time features in the video can be better captured, the tunnel disease detection result is quickly output, the recognition rate, the detection frequency and the processing speed of the tunnel disease are improved, and the manual dependence degree is reduced.

Description

technical field [0001] The invention relates to the technical field of tunnel detection, in particular to a tunnel detection method and device based on an unmanned aerial vehicle. Background technique [0002] With the acceleration of urbanization, urban subways have developed rapidly, and more and more underground infrastructures have been built accordingly. In recent years, tunnel safety problems have occurred frequently, such as tunnel cracks, water leakage, settlement, lining peeling, falling blocks, etc., causing serious casualties and huge economic losses. Therefore, tunnel safety is a key issue during tunnel operation. [0003] Traditional manual inspection and closed-circuit television system will not find problems in time, which will lead to serious consequences. Tunnel disease inspection should be carried out by combining manual and information means. With the continuous development of UAV technology, UAV application fields are becoming more and more extensive, an...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/00G06K9/00G06N3/04
CPCG06T7/0002G06V20/10G06V20/40G06N3/045
Inventor 包小华李颖鹏崔宏志陈湘生贾金青
Owner SHENZHEN UNIV
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com