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

Improved PCNN power fault image space positioning method based on boundary features

A power failure and image space technology, applied in image enhancement, image analysis, image data processing and other directions, can solve the problems of inaccurate acquisition of candidate target boundaries and uncertain effect of PCNN algorithm, and achieve the effect of improving adaptive processing capability.

Active Publication Date: 2020-02-11
WUHAN NARI LIABILITY OF STATE GRID ELECTRIC POWER RES INST +1
View PDF2 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The present invention mainly solves the problem of indeterminate effect of the PCNN algorithm due to the parameter setting of the number of iterations
[0005] The present invention also solves the problem that the acquisition of candidate target boundaries is not accurate enough

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
  • Improved PCNN power fault image space positioning method based on boundary features
  • Improved PCNN power fault image space positioning method based on boundary features
  • Improved PCNN power fault image space positioning method based on boundary features

Examples

Experimental program
Comparison scheme
Effect test

specific Embodiment approach

[0099] Combine below Figure 1 to Figure 8 Introduce the specific embodiment of the present invention: a kind of improved PCNN power fault image spatial positioning method based on boundary feature, specifically comprises the following steps:

[0100] Step 1: Build a PCNN processing model for power failure images;

[0101] Step 1.1, preferably, the PCNN model described in step 1 is:

[0102] The PCNN model consists of an input layer, a coupling layer and a pulse output layer;

[0103] In the input layer, each neuron corresponds to a pixel in the infrared image, thereby constructing a two-dimensional neural network, specifying that the feedback input F of the i-th row and j-column neuron receives the i-th row in the infrared image I region space The gray value I corresponding to the jth column i,j ;

[0104] f i,j [n]=I i,j ,i=1,...M,j=1,...,N

[0105] In the formula, M and N represent the rows and columns of the image, and n represents the number of iterations of the PC...

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 provides an improved PCNN power fault image space positioning method based on boundary features. The method comprises the following steps: constructing a power fault image PCNN processing model; enabling a PCNN model to carry out self-adaptive iteration to obtain an image result; introducing a Canny operator to estimate a plurality of regional boundaries to obtain regional edge pointinformation; and carrying out fault area positioning according to the area edge point information and a fault area judgment criterion. The PCNN model parameter design and the iterative mechanism canadapt to the infrared image, and the accuracy of fault area detection and positioning is improved.

Description

technical field [0001] The invention belongs to the field of electric fault detection. In particular, it relates to an improved PCNN power fault image space positioning method based on boundary features. Background technique [0002] Live fault state detection is a technology for status analysis and fault diagnosis of power distribution equipment in the state of no power failure, which can effectively prevent and avoid power distribution equipment accidents. In the existing live fault detection system, the infrared thermal imager has the advantages of fast detection speed, high accuracy, low cost, strong versatility and high safety. However, due to the differences in practical experience and professional level of inspectors, especially for inspectors who lack on-site experience, they only use their own vision to find and judge the power failure area, which not only takes a long time to diagnose, but also is prone to missed inspections. , and the input information is determ...

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): G06T7/00G06T7/13G06T7/11G06T5/00
CPCG06T7/0004G06T7/13G06T7/11G06T2207/20084G06T2207/10048G06T5/70
Inventor 许晓路龚浩程林罗传仙江翼吴念周正钦倪辉陈佳
Owner WUHAN NARI LIABILITY OF STATE GRID ELECTRIC POWER RES INST
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