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Porcelain insulator pollution grade detection method based on color characteristics

A color feature and detection method technology, applied in image data processing, instruments, calculations, etc., can solve the problems of non-contact and online efficient detection of gray density detection methods, and achieve low noise interference, improved prediction accuracy, and high precision Effect

Inactive Publication Date: 2017-10-24
XI'AN POLYTECHNIC UNIVERSITY
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Problems solved by technology

[0004] The purpose of the present invention is to provide a method for detecting the gray density of porcelain insulators based on color characteristics, which solves the problem that the existing gray density detection methods cannot be detected in a non-contact and online manner

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  • Porcelain insulator pollution grade detection method based on color characteristics
  • Porcelain insulator pollution grade detection method based on color characteristics
  • Porcelain insulator pollution grade detection method based on color characteristics

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Embodiment Construction

[0038] The present invention will be described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0039] The present invention is a method for detecting the gray density of porcelain insulators based on color features. After converting the color image channel to obtain the H component, the two-dimensional minimum error method combined with morphological filtering is used to segment and extract the insulator disk area, and then six channels are extracted from the disk surface area. The mean, maximum value, minimum value, range, variance, gray anisotropy, and gray entropy of the seven feature quantities are used to filter out the features with strong classification ability as gray density discriminant features, and finally the training set The discriminative features are used as input, and the gray density is used as output to train the BP neural network optimized by the thinking evolution algorithm MEA, and use the test set data for simulat...

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Abstract

The invention discloses a porcelain insulator pollution grade detection method based on color characteristics. The porcelain insulator pollution grade detection method comprises transforming a color image channel to obtain an H component, then segmenting the H component by means of a two-dimensional minimum error method combined with morphological filtering to extract an insulator disk area, extracting seven characteristic values including the mean value, the maximum value, the minimum value, the range, the variance, the grayscale anisotropy and the gray scale entropy of six channels of the disk area, and screening out characteristics which have high classification ability by means of a Fisher criterion function as pollution grade discrimination characteristics, finally taking the discrimination characteristics of the training set as an input and taking the pollution grade as an output to train a mind evolutionary algorithm (MEA) optimized BP neural network, carrying out simulation prediction by means of test set data and judging the accuracy, and achieving non-contact on-line and high-efficiency detection of the insulator pollution grade. By employing the porcelain insulator pollution grade detection method based on the color characteristics, the problem that the existing pollution grade detection method cannot achieve on-line detection is solved.

Description

technical field [0001] The invention belongs to the technical field of power transmission line image processing, and in particular relates to a method for detecting gray density of porcelain insulators based on color features. Background technique [0002] Insulators are important components that play a supporting and insulating role in high-voltage transmission lines, and their working status is directly related to the safe and stable operation of the entire power system. Due to the long-term action of pollutants such as dust in the air, a dirty layer will form on the surface of the insulator. When the air humidity is high, the pollution layer absorbs moisture, which leads to a significant decrease in the external insulation strength of the insulator, and pollution flashover accidents are very likely to occur, causing large-scale power outages. How to accurately, simply and reliably realize insulator pollution detection is an important issue concerned by the power sector, ...

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Application Information

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IPC IPC(8): G06T7/00G06T7/11G06T7/136
CPCG06T7/0004G06T7/11G06T7/136G06T2207/10004G06T2207/20081G06T2207/30108
Inventor 黄新波杨璐雅张烨张慧莹刘成周岩张峻歆黄典庆
Owner XI'AN POLYTECHNIC UNIVERSITY
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