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Method for identifying multi-insulated defect mode in GIS (gas insulated switchgear)

An insulation defect, pattern recognition technology, applied in character and pattern recognition, biological neural network models, instruments, etc.

Active Publication Date: 2013-06-12
ELECTRIC POWER RESEARCH INSTITUTE OF STATE GRID SHANDONG ELECTRIC POWER COMPANY +1
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Problems solved by technology

[0011] In order to solve the above problems, the method of the present invention discloses a multi-insulation defect pattern recognition method in GIS. On the basis of single insulation defect pattern recognition, it introduces a fast independent component analysis algorithm to extract the independent components in the mixed partial discharge signal (as a reference to the partial discharge signal). Estimation of single PD signals participating in the mixture); appropriate processing of the extracted independent components, followed by feature extraction and pattern recognition

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  • Method for identifying multi-insulated defect mode in GIS (gas insulated switchgear)

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Embodiment Construction

[0067] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0068] 1. Data preprocessing

[0069] Assume that the mixed fault signal matrix X obtained by the ultra-high frequency electromagnetic wave sensor is n×m dimensional, that is, there are n (n is a natural number) sensors to capture effective signals and the number of sampling points of the fault signal from each sensor is a positive integer m .

[0070] Find the correlation matrix R of the mixed signal matrix X, then R is located in the element R of the i-th row and the jth column (i, j=1, 2,..., m) ij for:

[0071] R ij = ζ ( x i , x j ) = | Σ k = 1 n ...

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Abstract

The invention relates to a method for identifying a multi-insulated defect mode in a GIS (gas insulated switchgear). The method comprises the following steps of: 1, acquiring a GIS mixed failure signal by using an ultrahigh frequency electromagnetic wave sensor; 2, whitening the mixed failure signal; 3, extracting independent components of the whitened mixed signal by using a rapid independent component analysis algorithm; 4, post-processing the extracted independent components through normalization and wavelet denoising, so as to eliminate the amplitude uncertainty of the extracted independent components; 5, describing the insulated defect type corresponding to each extracted independent component by using the characteristics (box dimension, vacancy rate and similarity coefficients of comparison models) of the independent components processed in the step 4, and eliminating the noise independent components by relying on the box dimension value of the independent components; and 6, classifying by a classifier. By the method, under the worse fault condition, the insulated defect types inducing partial discharge faults in the GIS can be identified. Furthermore, the invention provides a method for acquiring fault signals needed for classifier training; and the adaptive capacity of the acquired classifier on the actual GIS can be improved.

Description

technical field [0001] The invention relates to a GIS insulation defect pattern recognition method based on partial discharge ultra-high frequency electromagnetic wave signals in the GIS, in particular to a GIS multi-insulation defect pattern recognition method. Background technique [0002] GIS has been widely used in power systems at home and abroad because of its compact layout, small footprint, sealed operation, low failure rate, and long maintenance cycle. Partial discharge faults caused by GIS insulation defects (such as burrs, free particles, etc.) account for more than half of the existing statistical faults in GIS. At present, there have been a lot of recognized research results on the pattern recognition of partial discharge (PD) fault signal (single PD signal) caused by a single insulation defect in GIS at home and abroad, but it is rare for partial discharge faults induced by multiple insulation defects in GIS. The pattern recognition method published. [0003]...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01R31/12G06K9/62G06N3/02
Inventor 云玉新李世鹏李可军
Owner ELECTRIC POWER RESEARCH INSTITUTE OF STATE GRID SHANDONG ELECTRIC POWER COMPANY
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