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

Method for measuring motion characteristics of moving contact of circuit breaker based on deep learning

A technology of deep learning and motion characteristics, applied in instruments, image analysis, biological neural network models, etc., can solve the problems of large amount of calculation, matching accuracy and speed need to be improved, slow speed, etc., to compress the amount of calculation, enhance size adaptation ability, the effect of reducing the amount of calculation

Pending Publication Date: 2022-07-01
NORTH CHINA ELECTRIC POWER UNIV (BAODING)
View PDF0 Cites 2 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

In addition, using the gray pixel value of the image for image matching has the problems of large amount of calculation and slow speed, and the matching accuracy and speed need to be improved

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 measuring motion characteristics of moving contact of circuit breaker based on deep learning
  • Method for measuring motion characteristics of moving contact of circuit breaker based on deep learning
  • Method for measuring motion characteristics of moving contact of circuit breaker based on deep learning

Examples

Experimental program
Comparison scheme
Effect test

Embodiment

[0052] figure 1A block diagram of a method for measuring the motion characteristics of a circuit breaker moving contact based on deep learning of the present invention, as shown in the figure, a method for measuring the motion characteristics of a circuit breaker moving contact based on deep learning, the specific steps are as follows:

[0053] Step S1: setting auxiliary markers and collecting high-speed image sequences.

[0054] Step S11: respectively set the first auxiliary marker 2 and the second auxiliary marker 1 on the insulating rod 4 and the rotating shaft 5 that move synchronously with the moving contact of the circuit breaker, such as figure 2 shown, figure 2 This is the location diagram of the auxiliary marker and the high-speed camera of the present invention. A first auxiliary marker 2 is arranged on the linearly moving insulating pull rod 4 , and two second auxiliary markers 1 are arranged on the rotating shaft 5 .

[0055] Step S12: Adjust the position and f...

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 circuit breaker moving contact motion characteristic measurement method based on deep learning, and the method specifically comprises the following steps: S1, setting an auxiliary marker, and collecting a high-speed image sequence; s2, inputting the high-speed image sequence into the trained deep learning model, and tracking the motion trail of the auxiliary marker; and S3, calculating the travel time curve of the moving contact of the circuit breaker according to the track of the auxiliary marker. According to the circuit breaker moving contact motion characteristic measurement method based on deep learning, non-contact measurement is adopted, and a component which moves synchronously with the circuit breaker moving contact is tracked to measure the motion characteristic of the circuit breaker moving contact, so that the problems of target size change, background color interference and camera shaking can be effectively solved; and accurate tracking is realized.

Description

technical field [0001] The invention relates to the technical field of circuit breaker moving contact detection, in particular to a method for measuring the motion characteristics of a circuit breaker moving contact based on deep learning. Background technique [0002] In the power system, the high-voltage circuit breaker is very important. Once it fails, it may cause hidden dangers in the operation of the power grid and even threaten the life safety of the relevant personnel. The reliability assessment of high-voltage circuit breakers by the International Conference on Large Power Grids shows that 64.8% of the main faults of circuit breakers are operating mechanical faults. Measuring the motion characteristic parameters of the moving contact of the circuit breaker can evaluate the operating performance of the circuit breaker, which is an important technical means to detect the mechanical failure of the circuit breaker. [0003] At present, most of the mature measurement to...

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): G06T7/246G06V10/764G06V10/766G06V10/80G06V10/44G06V10/82G06N3/04G06K9/62
CPCG06T7/246G06T2207/10016G06T2207/20084G06T2207/30241G06N3/048G06N3/045G06F18/24G06F18/253
Inventor 崔克彬崔叶微刘智萍牛为华袁和金
Owner NORTH CHINA ELECTRIC POWER UNIV (BAODING)
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