Combination of mathematical indices and probabilistic neural network to detect the type of winding fault in transformers
Joint Authors
Bigdeli, Mahdi
Rahimpur, Ibrahim
Azizian, Davood
Source
Issue
Vol. 9, Issue 2 (30 Jun. 2013), pp.167-178, 12 p.
Publisher
Publication Date
2013-06-30
Country of Publication
Algeria
No. of Pages
12
Main Subjects
Telecommunications Engineering
Topics
Abstract EN
This paper presents a new method for determination the type of transformer winding fault through transfer function (TF) analysis.
For this purpose, probabilistic neural network (PNN) is used.
Outset of all, the required measurements are carried out on two groups of transformers, under both intact and faulted conditions of different degrees in axial displacement, radial deformation, disc space variation and short circuit on the winding.
Then, using algorithms based on mathematical methods, appropriate indices from frequency responses are extracted with the required accuracy.
The extracted features are finally used as the inputs to PNN classifier in order to perform the multi-category fault classification.
The obtained results reveal the ability of proposed method in comparison with two other distinguished methods.
American Psychological Association (APA)
Bigdeli, Mahdi& Rahimpur, Ibrahim& Azizian, Davood. 2013. Combination of mathematical indices and probabilistic neural network to detect the type of winding fault in transformers. Journal of Electrical Systems،Vol. 9, no. 2, pp.167-178.
https://search.emarefa.net/detail/BIM-328994
Modern Language Association (MLA)
Rahimpur, Ibrahim…[et al.]. Combination of mathematical indices and probabilistic neural network to detect the type of winding fault in transformers. Journal of Electrical Systems Vol. 9, no. 2 (Jun. 2013), pp.167-178.
https://search.emarefa.net/detail/BIM-328994
American Medical Association (AMA)
Bigdeli, Mahdi& Rahimpur, Ibrahim& Azizian, Davood. Combination of mathematical indices and probabilistic neural network to detect the type of winding fault in transformers. Journal of Electrical Systems. 2013. Vol. 9, no. 2, pp.167-178.
https://search.emarefa.net/detail/BIM-328994
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references : p. 178
Record ID
BIM-328994