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

Modeling method and device for transformer oil density prediction model

A technology of transformer oil and prediction model, which is applied in prediction, neural learning method, biological neural network model, etc., can solve the problems that the transformer oil cannot accurately reflect the real oil density of the transformer, is time-consuming and labor-intensive, and achieves rapid adaptive learning ability and operation. Efficient and stable effect

Active Publication Date: 2020-11-10
GUANGDONG POWER GRID CO LTD +1
View PDF3 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The embodiment of the present application provides a transformer oil density prediction model modeling method and device, which solves the problem that the existing transformer oil density test method is time-consuming and laborious, and cannot monitor the transformer oil in real time and accurately reflect the real oil density of the transformer question

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
  • Modeling method and device for transformer oil density prediction model
  • Modeling method and device for transformer oil density prediction model
  • Modeling method and device for transformer oil density prediction model

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0067] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiment of the application will be clearly and completely described below in conjunction with the accompanying drawings in the embodiment of the application. Obviously, the described embodiment is only It is a part of the embodiments of this application, but not all of them. Based on the embodiments in the present application, all other embodiments obtained by persons of ordinary skill in the art without creative efforts fall within the protection scope of the present application.

[0068] This application designs a transformer oil density prediction model modeling method and device, optimizes the first transformer oil density regression prediction model established by the backpropagation neural network based on temperature compensation and genetic algorithms, and uses genetic algorithms to establish transformer oil multi-frequency T...

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

A method and apparatus for modeling a transformer oil density prediction model. Based on temperature compensation and genetic algorithm, the regression prediction model of the first transformer oil density established by back propagation neural network is optimized, the nonlinear mapping relationship between multi-frequency ultrasonic parameters of transformer oil and oil density is established bygenetic algorithm, and the temperature compensation is used to reduce the effect of temperature on the mapping relation, the regression prediction of transformer oil density is realized, high efficiency, fast and adaptive learning ability, and the transformer oil density can be monitored directly by regression prediction model, The transformer oil density can be obtained in real time, and the prediction result is accurate and reliable, which solves the technical problem that the existing transformer oil density measurement method is time-consuming and labor-consuming, and can not monitor thetransformer oil in real time and accurately reflect the real oil density of the transformer.

Description

technical field [0001] The present application relates to the technical field of transformer fault detection, in particular to a transformer oil density prediction model modeling method and device. Background technique [0002] Transformers play an indispensable role in the power grid. They are the core of energy conversion and transmission, and also the key hub equipment in the first defense system of power grid security. Transformer faults will not only bring economic losses, but also may cause panic and inconvenience to people due to blackouts. Therefore, fault diagnosis of transformers is required for the development of smart grids. The quality of the oil directly affects the operation status of the transformer, and the detection of the parameters of the transformer oil affects the validity of the determination of the operation status of the transformer, and even relates to the operation safety of the entire power grid. [0003] The traditional method to detect the dens...

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 Patents(China)
IPC IPC(8): G06Q10/04G06Q50/06G06N3/08
CPCG06N3/084G06N3/086G06Q10/04G06Q50/06
Inventor 赵耀洪钱艺华李丽范圣平
Owner GUANGDONG POWER GRID CO LTD
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