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

A transmission line external damage prevention early warning method and system based on depth learning

A technology for preventing external force damage and power transmission lines, applied in neural learning methods, instruments, biological neural network models, etc., can solve problems such as missed detection, misjudgment, increased line inspection cost, and reduced line inspection efficiency. False alarm rate, guarantee real-time requirements, and reduce labor costs

Active Publication Date: 2019-01-29
FUZHOU UNIV
View PDF4 Cites 18 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, the large amount of image data obtained from inspections still requires several experienced professionals to spend several days on boring image retrieval and analysis tasks. In the process, missed inspections and misjudgments are prone to occur, which increases the cost of inspections and reduces the cost of inspection. Line tracking efficiency

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
  • A transmission line external damage prevention early warning method and system based on depth learning
  • A transmission line external damage prevention early warning method and system based on depth learning
  • A transmission line external damage prevention early warning method and system based on depth learning

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0033] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0034] It should be pointed out that the following detailed description is exemplary and is intended to provide further explanation to the present application. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs.

[0035] It should be noted that the terminology used here is only for describing specific implementations, and is not intended to limit the exemplary implementations according to the present application. As used herein, unless the context clearly dictates otherwise, the singular is intended to include the plural, and it should also be understood that when the terms "comprising" and / or "comprising" are used in this specification, they mean There are features, steps, operations, means, components and / or combina...

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 relates to a transmission line external damage early warning method and system based on depth learning, Firstly, a camera and a wireless communication module are mounted on more than oneUAV. Each UAV patrols the transmission line according to the preset route, height and shooting angle, and transmits the images taken in the target area to the server of the corresponding patrol station. Then the server of the patrol station builds the depth neural network for the image data transmitted by the UAV in real time by using the depth learning method, identifies the target intelligently, judges the location coordinates of the external force damage risk, and uploads it to the central console; the server of the patrol station builds the depth neural network for the image data transmitted by the UAV in real time by using the depth learning method. Finally, the central console receives the warning coordinates from each patrol station to alert the staff. The invention realizes a large range of transmission line anti-external force damage early warning by a UAV and a depth learning algorithm popularized in the market.

Description

technical field [0001] The invention relates to the field of transmission line protection, in particular to a deep learning-based early warning method and system for preventing external force damage of transmission lines. Background technique [0002] my country's transmission lines bear the heavy burden of transporting regional electric energy, so it is particularly important to ensure the stable operation of transmission lines. However, the speed of modernization is accelerating, and frequent engineering construction has seriously threatened the safety of transmission lines. External force damage has become the main factor affecting the safety of transmission lines, and the prevention of external force damage is imminent. However, most of the current anti-external damage methods rely on manual inspections and detection by the anti-external damage system, but manual inspections are not timely and inefficient, and cannot prevent external damage well and reduce losses; The p...

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): G06K9/00G06K9/62G06N3/04G06N3/08
CPCG06N3/08G06V20/13G06N3/045G06F18/214
Inventor 陈静林雅婷缪希仁江灏
Owner FUZHOU 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