Partial discharge pattern recognition method based on mixed neural network algorithm

A hybrid neural network and partial discharge technology, which is applied in the direction of measuring electricity, measuring electrical variables, and testing dielectric strength, etc., can solve the problems of sensitive initial weight and threshold selection, easy to fall into local minimum, slow algorithm convergence speed, etc. , to achieve high recognition rate, solve the initial weight sensitivity and easy local convergence, and improve the effect of convergence speed

Inactive Publication Date: 2016-05-25
ANHUI UNIV OF SCI & TECH
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Problems solved by technology

The BP algorithm is relatively successful in local optimization, but it also has the following problems: 1) It is sensitive to the selection of the initial weight and thres

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  • Partial discharge pattern recognition method based on mixed neural network algorithm
  • Partial discharge pattern recognition method based on mixed neural network algorithm
  • Partial discharge pattern recognition method based on mixed neural network algorithm

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[0026] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention more clear, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention.

[0027] (1) Collect discharge signals of various typical discharge models in transformer oil

[0028] Construct 5 typical partial discharge models, including internal void type discharge model, creeping surface type discharge, floating potential body type discharge, oil-bubble type discharge, and oil-barrier type discharge. Each discharge model has more than 5 samples. These samples The material and structure are exactly the same, but there are certain differences in size and other aspects. The discharge capacity, discharge voltage, discharge time, discharge phase and discharge period of the discharge are measured by the partial discharge measurement system. F...

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Abstract

The invention discloses a partial discharge pattern recognition method based on a mixed neural network algorithm, the method comprises a judge process including extracting ultrahigh frequency partial discharge signal characteristic and establishing a value set library and discharge types; the method specifically comprises: establishing a typical partial discharge model firstly, acquiring a discharging ultrahigh frequency signal, and performing mixing frequency and reducing frequency process; then generating 5 kinds of two-dimension spectra according to the discharge signal, and extracting 37 kinds of statistical characteristic quantity (value set) to form the value set library; finally comparing the value set library and a value set corresponding to the statistical characteristic quantity calculated by a fault signal through the mixed neural network algorithm, and recognizing the partial discharge type of a transformer. According to the invention, the signal of partial discharge ultra wide band is fully ultilized, the single neural network pattern recognition problem is overcome, the partial discharge value set library of the transformer is established to perform pattern recognition for different kinds of discharging, the valuable data is provided for transformer partial discharge on-line monitor, and the method has good practical engineering value.

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Owner ANHUI UNIV OF SCI & TECH
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