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

Method for predicting radio disturbance of electric transmission line by using improved BP (back propagation) neural network

A BP neural network and radio interference technology, which is applied in forecasting, instrumentation, data processing applications, etc., can solve problems such as large prediction errors

Active Publication Date: 2015-05-20
STATE GRID CORP OF CHINA +1
View PDF3 Cites 20 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Since the radio interference of transmission lines is also affected by environmental and geographic location factors, and the influence of these factors on the radio interference value shows a high degree of nonlinearity and uncertainty, it faces the constraints of applicable conditions and the prediction error is too large. The application in the actual circuit design will be limited to a certain extent

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 predicting radio disturbance of electric transmission line by using improved BP (back propagation) neural network
  • Method for predicting radio disturbance of electric transmission line by using improved BP (back propagation) neural network
  • Method for predicting radio disturbance of electric transmission line by using improved BP (back propagation) neural network

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0110] Such as Figure 1-2 As shown, the inventive method of this example is: obtain the factors that have influence on the radio interference Y of the transmission line as input data, including: voltage X 1 , current X 2 , wire diameter X 3 , wire section X 4 , split number X 5 , Splitting distance X 6 , soil resistivity X 7 , wire-to-ground distance X 8 , The distance between the wire and the measuring point X 9 , temperature X 10 , Humidity X 11 , air pressure X 12 , altitude X 13 ;

[0111] The input data contains 13 neurons, and the order of magnitude differs greatly. In order to ensure the equal status of each factor and speed up the convergence speed, the normalized preprocessing method is used to preprocess the input data and normalize the data to [-1 ,1] in the interval.

[0112] 1. Improved simulated annealing algorithm

[0113] Improved annealing process steps:

[0114] 1) given temperature t 0 , the initial state S is randomly generated, and the ini...

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 method for predicting radio disturbance of an electric transmission line by using an improved BP (back propagation) neural network. The method comprises the following steps of acquiring and preprocessing data parameters; establishing a BP neural network predicting model of the data parameters; performing optimal training on the BP neural network by using a genetic algorithm and a simulated annealing algorithm; and predicting radio disturbance of the electric transmission line by using the network. The method is high in prediction precision, high in convergence and high in stability; the problem that the BP neural network is caught in a local minimum point is solved; and the method has a great guiding significance on prediction of radio disturbance of the electric transmission line and research on reduction of radio disturbance.

Description

Technical field: [0001] The invention relates to a radio interference prediction method, more particularly to an improved BP neural network transmission line radio interference prediction method. Background technique: [0002] With the increase of the voltage level of the transmission line, the radio interference generated by the transmission line has aroused widespread concern. Reducing the electromagnetic environment impact of transmission lines and reducing the radio interference around the line is the work that designers in various countries have been studying, and how to accurately predict the radio interference of the line is the premise of the research work. At present, transmission line radio interference is predicted based on the empirical formula method and excitation function method recommended by CISPR. However, the mechanism of radio interference is very complicated, affected by many factors such as voltage, current, wire cross section, wire layout, meteorologi...

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): G06Q50/06G06Q10/04G06N3/12
Inventor 马潇刘蕊莫娟段舒宁金欢方正刚刘铭
Owner STATE GRID CORP OF CHINA
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