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A Feature Extraction Method of Cable Oscillating Wave Partial Discharge Signal

A partial discharge signal and feature extraction technology, applied in the direction of measuring electricity, measuring electrical variables, testing dielectric strength, etc., can solve the problems of high feature dimension, unsatisfactory classification and recognition effect, large redundancy, etc. Low dimensionality, avoidance of dimensional disaster, and low redundancy

Active Publication Date: 2018-06-15
YUNNAN POWER GRID CO LTD PUER POWER SUPPLY BUREAU +2
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Problems solved by technology

[0004] The purpose of the present invention is to overcome the existing technology for feature extraction of cable oscillating wave partial discharge signals, resulting in high feature dimension, large redundancy, unsatisfactory classification and recognition effects, etc., thereby providing an EEMD-DFA-based Feature Extraction Method of Cable Oscillating Wave Partial Discharge Signal

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  • A Feature Extraction Method of Cable Oscillating Wave Partial Discharge Signal
  • A Feature Extraction Method of Cable Oscillating Wave Partial Discharge Signal
  • A Feature Extraction Method of Cable Oscillating Wave Partial Discharge Signal

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Embodiment Construction

[0017] A kind of EEMD-DFA based cable oscillatory wave partial discharge signal feature extraction method, the present invention is characterized in that, comprises the following steps:

[0018] (1) Using Integrated Empirical Mode Decomposition (EEMD) to decompose the partial discharge signal to obtain the decomposition coefficient IMF;

[0019] (2) Using DFA method to optimize and rebuild IMF

[0020] (3) Extract and calculate the sample entropy and approximate entropy of each sub-band coefficient, and use it as a feature vector;

[0021] (4) Input the above feature parameters into the support vector machine classifier model to verify the effect of the extraction method.

[0022] The concrete method of described step (1) is:

[0023] The present invention first adopts integrated empirical mode decomposition (EEMD) to analyze the local characteristics of the signal. The EEMD decomposition steps are:

[0024] 1) Add a Gaussian white noise sequence with a relatively small ro...

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Abstract

The present invention discloses an EEMD (ensemble empirical mode decomposition)-DFA-based cable oscillation wave partial discharge signal feature extraction method. The method includes the following steps that: 1) ensemble empirical mode decomposition (EEMD) is adopted to perform partial discharge signal decomposition, so that a decomposition coefficient IMF is obtained; 2) a DFA method is adopted to optimize and reconstruct the IMF; and 3) the sample entropies and approximate entropies of each sub-band coefficient are extracted and calculated, the sample entropies and approximate entropies are adopted as feature vectors and are inputted into a support vector machine classifier model to verify the effect of the extraction method.

Description

technical field [0001] The invention relates to a cable partial discharge signal feature extraction technology under oscillatory wave voltage, in particular to a cable oscillatory wave partial discharge signal feature extraction method based on EEMD-DFA. Background technique [0002] Cross-linked polyethylene (XLPE) power cables have many advantages, such as simple manufacturing process, excellent electrical performance, convenient laying and installation, large transmission capacity, no hidden danger of oil leakage, and convenient operation and maintenance. Therefore, they have gradually become the mainstream of power cables. Widely used in domestic and foreign power transmission and distribution networks and engineering applications. However, XLPE cables can still have insulation defects which, if left unattended, will eventually lead to insulation breakdown, causing failure. In order to reduce and prevent failures, detection of partial discharges on cables is required. ...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G01R31/12G06F17/14
CPCG01R31/1272G06F17/14
Inventor 杨堂华杨忠才贾廷凯黄星王泽雄黄晟张冠一杨学东马春彦刘珊许永鹏
Owner YUNNAN POWER GRID CO LTD PUER POWER SUPPLY BUREAU
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