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

Cloud layer detection and classification method based on multi-cloud-layer features

A classification method and technology of multi-cloud layers, applied in the direction of instrument, character and pattern recognition, scene recognition, etc., can solve problems such as random fluctuation of photovoltaic output, and achieve the effect of efficient and accurate judgment

Inactive Publication Date: 2019-11-29
HOHAI UNIV CHANGZHOU
View PDF2 Cites 4 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] The technical problem to be solved by the present invention is to provide a cloud layer detection and classification method based on the characteristics of multi-cloud layers to achieve accurate detection and classification of sky clouds for the intermittent occlusion of clouds to cause random fluctuations in photovoltaic output

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
  • Cloud layer detection and classification method based on multi-cloud-layer features
  • Cloud layer detection and classification method based on multi-cloud-layer features
  • Cloud layer detection and classification method based on multi-cloud-layer features

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0061] The present invention will be further described below. The following examples are only used to illustrate the technical solution of the present invention more clearly, but not to limit the protection scope of the present invention.

[0062] The invention provides a cloud layer detection and classification method based on multi-cloud layer features. Firstly, the minimum cross-entropy algorithm is used to obtain the image segmentation threshold; and then the extraction and classification of sky image features are realized based on the KNN classification algorithm.

[0063] (1) Cloud image segmentation

[0064]Compared with RBR and RBD, the normalized red-blue ratio threshold method (NRBR) has stronger anti-noise ability, and avoids the situation that the RBR ratio is very large when the gray value of the blue channel is very small, resulting in false detection. Moreover, for thin clouds and surrounding sun scattering areas, NRBR has a better detection effect.

[0065] 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

The invention discloses a cloud layer detection and classification method based on multi-cloud-layer features, and the method comprises the steps: calculating the color, texture and shape feature quantities of a cloud picture, and building a cloud picture feature space; carrying out cloud layer pixel and sky pixel division on the shot current cloud picture by utilizing the optimal normalized red-blue ratio threshold value, and searching an optimal segmentation threshold value position on the normalized red-blue ratio histogram by adopting a minimum cross entropy method; and performing KNN classification on the currently photographed cloud picture according to the cloud picture feature space to obtain the type of the cloud layer to be shielded from the sun. According to the method, the cloud layer can be automatically and accurately detected based on the RGB characteristics of the cloud picture, the cloud layer characteristics are comprehensively extracted, and efficient and accurate judgment of the cloud layer type is achieved.

Description

technical field [0001] The invention discloses a cloud layer detection and classification method based on the characteristics of multi-cloud layers, and belongs to the technical field of solar irradiation and photovoltaic power generation. Background technique [0002] As solar photovoltaic power generation is connected to large power grids with a high proportion of power supply energy, the inherent volatility and randomness of photovoltaic power generation itself will inevitably bring new challenges to power electronic equipment and grid frequency. The power generation and load power in the power grid must be kept in balance at all times. If a high proportion of distributed photovoltaic power sources that fluctuate randomly due to the influence of live weather are injected into the power generation side, the randomness of the power generation side will greatly reduce the reliability of the power grid operation. In order to maintain the stable operation of the large power gr...

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 Applications(China)
IPC IPC(8): G06K9/00G06K9/46G06K9/62
CPCG06V20/13G06V10/507G06V10/44G06V10/56G06F18/24147
Inventor 张臻邵玺罗皓霖祝曾伟王磊李沁书张起源
Owner HOHAI UNIV CHANGZHOU
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