The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Oct. 18, 2022

Filed:

Dec. 30, 2019
Applicant:

Wuhan University, Hubei, CN;

Inventors:

Yigang He, Hubei, CN;

Jiajun Duan, Hubei, CN;

Bolun Du, Hubei, CN;

Hui Zhang, Hubei, CN;

Liulu He, Hubei, CN;

Assignee:

WUHAN UNIVERSITY, Hubei, CN;

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G01R 31/62 (2020.01); G06F 17/14 (2006.01); G06N 3/08 (2006.01);
U.S. Cl.
CPC ...
G01R 31/62 (2020.01); G06F 17/14 (2013.01); G06N 3/08 (2013.01);
Abstract

The disclosure discloses a power transformer winding fault positioning method based on deep convolutional neural network integrated with visual identification, including 1) a winding equivalent circuit is established, and a transfer function thereof is calculated; 2) a sine wave excitation source is set at one end of the power transformer winding to obtain the amplitude-frequency characteristic curve of each winding node; 3) circuits under various fault statuses are subjected to scanning frequency response analysis to extract amplitude-frequency characteristics; 4) a feature matrix is established based on the obtained amplitude-frequency characteristics; 5) scanning frequency response analysis is performed on the diagnosed power transformer to form a feature matrix; 6) the feature matrix is converted into an image, simulation and historical detection data are used as a training set, and a deep convolutional neural network is input for training; 7) diagnosed transformer is subjected to fault classification and positioning.


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