Neural network-based power transmission line insulator pollution grade determination method

A pollution level and transmission line technology, applied in the field of level determination, can solve the problems of low accuracy and reliability of insulator pollution degree monitoring, and achieve the effect of ensuring safe and reliable operation, improving accuracy and reliability, and avoiding low reliability.

Active Publication Date: 2021-02-23
STATE GRID CORP OF CHINA +2
View PDF5 Cites 1 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] Therefore, it is necessary to propose a neural network model and a pollution level judgment method that comprehensively considers the correction of multiple environmental paramete

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
  • Neural network-based power transmission line insulator pollution grade determination method
  • Neural network-based power transmission line insulator pollution grade determination method
  • Neural network-based power transmission line insulator pollution grade determination method

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0041] Embodiments of the present invention are described below through specific examples, and those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. The present invention can also be implemented or applied through other different specific implementation modes, and various modifications or changes can be made to the details in this specification based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that the diagrams provided in the following embodiments are only schematically illustrating the basic concept of the present invention, and the following embodiments and the features in the embodiments can be combined with each other in the case of no conflict.

[0042] Wherein, the accompanying drawings are for illustrative purposes only, and represent only schematic diagrams, rather than physical drawings, and should...

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 neural network-based power transmission line insulator pollution grade determination method, and belongs to the field of power transmission line insulator detection. The method comprises the following steps: S1, building an insulator pollution degree experiment platform; S2, carrying out an artificial pollution experiment; S3, preprocessing data; S4, establishing a neural network model; S5, conducting model training and verification; and S6, determining the pollution grade. The invention provides a neural network model which comprehensively considers correction of multiple environmental parameters such as temperature, humidity and air pressure, and also provides a power transmission line insulator pollution grade judgment method based on the neural network model,so that the accuracy and reliability of insulator pollution degree monitoring can be effectively improved. Therefore, safe and reliable operation of the power transmission line is ensured.

Description

technical field [0001] The invention belongs to the field of transmission line insulator detection and relates to a method for judging the pollution level of transmission line insulators based on a neural network. Background technique [0002] High-voltage transmission lines are responsible for the important task of transmitting electric energy, and their safety and reliability will directly affect the power supply level of the power system. With the rapid development of the power network, the voltage level of the transmission line is getting higher and higher, and higher requirements are placed on the reliability of the power supply of the power company. However, with the continuous increase of atmospheric pollution, the pollution flashover phenomenon of transmission line insulators has become a major hidden danger that threatens the safe and stable operation of the power system. In view of the long-term exposure of insulators to harsh atmospheric environments with severe ...

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): G01R31/12G01D21/02G06N3/04G06N3/08
CPCG01R31/1245G01D21/02G06N3/04G06N3/08
Inventor 李朝晋陈怀科周渠王小祥牟飞陈志芬张闯
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