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GIS device intelligent recognition method based on vector machine and artificial fish swarm optimization

A technology of artificial fish swarm and intelligent identification, which is applied in the direction of testing dielectric strength, etc.

Active Publication Date: 2012-05-09
云南电力试验研究院(集团)有限公司
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But so far, no one has applied the algorithm to determine the aspect of SVM parameter optimization

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  • GIS device intelligent recognition method based on vector machine and artificial fish swarm optimization
  • GIS device intelligent recognition method based on vector machine and artificial fish swarm optimization
  • GIS device intelligent recognition method based on vector machine and artificial fish swarm optimization

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Embodiment Construction

[0074] Such as figure 1 , figure 2 , image 3 , Figure 4 Shown, the GIS equipment intelligent identification method based on vector machine and artificial fish swarm optimization, the steps of the present invention are:

[0075] A. Partial discharge detection of GIS equipment;

[0076] B. Extracting spectral features from the detected partial discharge data;

[0077] C. Use the X-ray digital imaging detection system to visually image the partial discharge area and form an X-ray digital picture;

[0078] D. Carry out feature extraction from the X-ray digital pictures obtained by the X-ray digital imaging detection system;

[0079] E, utilize artificial fish swarm optimization algorithm to optimize the regularization parameter C " of SVM and kernel function parameter σ, determine the value of regularization parameter C " and kernel function parameter σ;

[0080] F. Extract the partial discharge pattern features and X-ray digital picture features of the GIS defect example...

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Abstract

The invention discloses a GIS (Geographic Information System) device intelligent recognition method based on vector machine and artificial fish swarm optimization. The method comprises the following steps of: A, detecting a GIS device; B, executing feature extraction on the detected data; C, imaging a discharge region and forming a digital picture; D, executing feature extraction on the digital picture; E, optimizing a regularization parameter C'' and a kernel function parameter sigma of a SVM (Support Vector Machine) by a artificial fish swarm optimization algorithm; F, extracting features of a GIS defect case base and features of an X-ray digital picture to train the SVM; G, inputting the newly detected features into the SVM for recognition, determining whether inside of the GIS device has defects, and further determining the property and the position of the defects. The method has the benefits of realizing the aim of visual intelligent recognition for inside defects of the GIS device, reducing influence on classification result caused by blind selection of SVM parameters, and improving recognition accuracy to inside defects of the GIS device.

Description

technical field [0001] The invention relates to a method for identifying internal defects of power equipment, in particular to the technical field of a visual intelligent identification method for internal defects of GIS equipment based on support vector machines and artificial fish swarm optimization. Background technique [0002] Gas Insulated Switchgear (GIS) has been widely used in substations and power plants of the power system. With the continuous improvement of the voltage level and capacity of the power grid, the failure rate of GIS equipment also increases. GIS equipment has the advantages of small footprint, convenient installation and high reliability. However, it is a fully enclosed composite structure equipment. Once a failure occurs, it will take a long time for maintenance, causing great impact and loss. Therefore, it is of great significance to grasp the running status of GIS equipment timely and accurately. [0003] During the manufacturing, installation, ...

Claims

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Application Information

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IPC IPC(8): G01R31/12
Inventor 王达达于虹魏杰赵现平谭向宇况华张少泉吴章勤刘荣海王进张永刚殷兰
Owner 云南电力试验研究院(集团)有限公司
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