Method for monitoring and predicting galloping of a transmission line in real time based on video analysis

A technique for analysis of power lines, video, and applications in forecasting, instrumentation, character and pattern recognition

Inactive Publication Date: 2014-05-07
STATE GRID CORP OF CHINA +2
View PDF2 Cites 25 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, the existing research schemes that only analyze two-dimensional images of conductor galloping have limited actual measurement results, which are not enough to fully reflect the state characteristics of conductor galloping, let alone predict and analyze future conductor galloping conditions.

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
  • Method for monitoring and predicting galloping of a transmission line in real time based on video analysis
  • Method for monitoring and predicting galloping of a transmission line in real time based on video analysis
  • Method for monitoring and predicting galloping of a transmission line in real time based on video analysis

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0064] (1) Collect the original image: use the video camera installed on the tower to collect the original image before the transmission wire dances; use the monitoring terminal to collect the micro-meteorological data at that time; and send the above data back to the monitoring center for storage through the transmission channel. as the original comparison data;

[0065] (2) Perform image processing on the original image at the monitoring terminal, including smoothing, grayscale, two-dimensional image segmentation, contour extraction, and contour tracking, and automatically identify the characteristic target points on the power transmission line analyzed after processing, respectively Obtain the position coordinates of the target point;

[0066] The two-dimensional image segmentation of the original image in step (2) is performed by combining the overall threshold and the local threshold.

[0067] Its algorithm flow is as follows figure 1 As shown, its main steps are:

[...

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 method for monitoring and predicting galloping of a transmission line in real time based on video analysis, which comprises the following steps of collecting an original image; carrying out image processing on the original image at a monitoring terminal, identifying characteristic target points, which are obtained after processing the original image, on the transmission line automatically, and acquiring position coordinates of the target points; analyzing the pre-processed image, acquiring position coordinates of the target points of the transmission line, and calculating the icing thickness of the line; calculating the number of continuous images between adjacent maximum values or minimal values according to vertical coordinates of the target points of continuous image files, and calculating the galloping frequency of the line according to the time interval of two adjacent images; and carrying out simulating and predicating analysis on the galloping condition of the transmission line in future. The method disclosed by the invention analyzes the galloping condition of the transmission line by using video image technologies, thereby avoiding installation of a large amount of hardware sensors on the transmission line, saving the expenditure of hardware, reducing extra hardware maintenance workload, and being convenient to manage.

Description

technical field [0001] The invention belongs to the technical field of transmission line operation and maintenance, in particular to a method for real-time monitoring and prediction of galloping of transmission wires based on video analysis. Background technique [0002] Galloping of transmission lines refers to a low-frequency (about 0.1-3Hz) and large-amplitude (approximately 1 / 2 of the diameter of the wire) produced by the wire when the wind acts on the transmission wire with a non-circular cross-section due to ice coating under certain conditions. 5 to 300 times) self-excited vibration phenomenon. When the wire gallops, the vibration peak value can usually reach more than 10 meters, so that it is easy to cause phase-to-phase flashover, damage to hardware, cause line tripping and power failure, or cause serious accidents such as burnt wires, tower collapse, wire breakage, etc., resulting in major economic losses. [0003] The research literature on the galloping phenome...

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): G06Q10/04G06K9/60
Inventor 游文霞谢学平任乔林杨帆马玉新周云海胡翔勇粟世玮
Owner STATE GRID CORP OF CHINA
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