Mountain fire image identification method of image monitoring system of electric transmission line tower

A transmission line and image monitoring technology, applied in character and pattern recognition, fire alarms, instruments, etc., can solve the problems of lack of timeliness, reduced reliability, and high cost of mountain fire early warning

Inactive Publication Date: 2014-05-07
SOUTH CHINA UNIV OF TECH +1
View PDF3 Cites 56 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0002] At present, the early warning of wildfires in China mostly uses forestry department personnel to patrol, rent high-altitude aircraft monitoring and other means, all of which have the problems of limited monitoring scope and time, high cost, vulnerable to climatic conditions, and unable to carry out all-weather monitoring
The Ministry of Forestry rents two satellites from the National Oceanic and Atmospheric Administration of the United States to monitor wildfires in my country in the form of infrared i

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
  • Mountain fire image identification method of image monitoring system of electric transmission line tower
  • Mountain fire image identification method of image monitoring system of electric transmission line tower
  • Mountain fire image identification method of image monitoring system of electric transmission line tower

Examples

Experimental program
Comparison scheme
Effect test

Embodiment

[0081] Image recognition principle:

[0082] The feature recognition of wildfires mainly includes flame features and smoke features. The process of wildfire image recognition can be divided into four stages: abnormal situation diagnosis, abnormal situation (flame or smoke) recognition, flame and smoke image segmentation, and mountain fire image recognition. Fire signature detection and early warning.

[0083] Abnormal condition diagnosis:

[0084] Under normal circumstances, the image content of the fixed area captured by the camera should have a high similarity within a certain time interval. In the early stage of a wildfire, the large-area spread of smoke will block a large area of ​​the background. At the same time, due to the light refraction caused by the airflow disturbance above the fire point, the color and illuminance of this area on the image will change significantly compared with the reference image.

[0085] Therefore, the difference operation of the image can b...

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 mountain fire image identification method of an image monitoring system of an electric transmission line tower. The mountain fire image identification method comprises the following steps that firstly, the forest fire danger rating is evaluated by means of data of a microclimate on-line monitoring system on the electric transmission line tower, and the image collecting frequency of the on-line monitoring system is adjusted according to rating evaluation; secondly, abnormal situations of an image are detected by the image difference principle; thirdly, skyline segmentation is conducted on the image; fourthly, whether the image has a flame region is judged; fifthly, whether the image has a smoke region is judged; sixthly, whether a fire occurs is judged. The mountain fire image identification method has the advantages that remote early warning of mountain fire of an electric transmission line is achieved, and safe and stable operation of the electric transmission line of an electric system is guaranteed.

Description

technical field [0001] The invention relates to an image recognition technology for on-line monitoring of transmission lines, in particular to a mountain fire image recognition method for a power transmission line tower image monitoring system. Background technique [0002] At present, the early warning of wildfires in China mostly uses forestry department personnel to patrol and rent high-altitude aircraft to monitor. There are problems such as limited monitoring scope and time, high cost, and being easily affected by climate conditions, making all-weather monitoring impossible. The Ministry of Forestry rented two satellites from the National Oceanic and Atmospheric Administration of the United States to monitor wildfires in my country in the form of infrared imaging, but they can only scan designated areas 4 times a day, and the early warning of wildfires lacks timeliness. [0003] Domestic companies mostly use smoke sensors to provide early warning of wildfires in the onl...

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
IPC IPC(8): G06K9/00G06K9/46G08B17/00
Inventor 郝艳捧阳林罗健斌史尊伟曹敏杨家全
Owner SOUTH CHINA UNIV OF TECH
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

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

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap