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

A Transformer Fault Diagnosis Method Based on Neural Network

A transformer fault, neural network technology, applied in biological neural network models, instruments, measurement of electrical variables, etc., can solve problems such as difficult neural network parameters, and achieve shortened training time, simple model, strong memory ability and robustness. Effect

Active Publication Date: 2018-07-31
NANJING UNIV OF POSTS & TELECOMM
View PDF6 Cites 3 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] In view of the above-mentioned technical problems, the technical problem to be solved by the present invention is to provide a transformer fault diagnosis method based on neural network, which not only solves the problem that the neural network parameters are difficult to optimize, but also improves the speed and accuracy of the global convergence of the neural network, and Improve the ability and accuracy of transformer fault diagnosis

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
  • A Transformer Fault Diagnosis Method Based on Neural Network
  • A Transformer Fault Diagnosis Method Based on Neural Network
  • A Transformer Fault Diagnosis Method Based on Neural Network

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0037] The specific implementation manners of the present invention will be further described in detail below in conjunction with the accompanying drawings.

[0038] like figure 1 As shown, the neural network-based transformer fault diagnosis method designed by the present invention includes the following steps in the actual application process:

[0039] Step 001. Extract the sample data of dissolved gas in the transformer oil with the preset group number V when the transformer fails, as each group of training sample data, that is, the V group of training sample data, and each group of training sample data includes respectively the specified dissolved gas The parameter data of each specified type; and obtain the internal fault types of the transformer corresponding to each group of training sample data; at the same time, extract the sample data of dissolved gas in the transformer oil with the preset number of groups when the transformer fails, as each group of test sample data...

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 transformer fault diagnosis method based on a neural network. The method comprises the following steps: analyzing fault reasons, and extracting a sample set of dissolved gas in transformer oil and a corresponding a fault type inside a transformer; determining the number of Neurons in a neural network hidden layer according to experience and a successive optimization searching method, and building a neural network; adopting an improved Cuckoo optimization algorithm to train the neural network; and finally utilizing the trained neural network to diagnose a fault of the transformer. The entire design method has the characteristics of high search precision and high global search capability, and effectively improves the accuracy of fault diagnosis for a transformer.

Description

technical field [0001] The invention relates to a transformer fault diagnosis method based on a neural network, belonging to the technical field of transformer fault processing. Background technique [0002] The power transformer is one of the important components of the power system. Its safety performance directly affects whether the electrical system in our country can operate reliably, and also indirectly affects the daily life of our residents. Therefore, the maintenance and testing of power transformers have become very urgent, but frequent disassembly and assembly of transformers will damage the equipment again and bury safety hazards for the equipment. With the increase of power consumption, the load on power transformers is also increasing. Therefore, it is necessary to monitor the operation status of power equipment in real time. Through real-time detection, early defects of electrical equipment can be found, so as to prevent accidents and reduce the risk of accide...

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): G01R31/00G06N3/02
CPCG01R31/00G06N3/02
Inventor 高浩岳东秦媛
Owner NANJING UNIV OF POSTS & TELECOMM
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