Power Transformers Fault Diagnosis Based on DRNN
2014 ◽
Vol 960-961
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pp. 700-703
Keyword(s):
In recent years, improved three-ratio is an effective method for transformer fault diagnosis based on Dissolved Gas Analysis (DGA). In this paper, diagonal recurrent neural network (DRNN) is used to resolve the online fault diagnosis problems for oil-filled power transformer based on DGA. To overcome disadvantages of BP algorithm, a new recursive prediction error algorithm (RPE) is used in this paper.In addition, to demonstrate the effectiveness and veracity of the proposed method, some cases are used in the simulation. The simulation results are satisfactory.
2013 ◽
Vol 448-453
◽
pp. 2520-2523
2017 ◽
Vol 24
(5)
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pp. 2828-2835
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Keyword(s):
2013 ◽
Vol 20
(3)
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pp. 974-981
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Keyword(s):
2014 ◽
Vol 519-520
◽
pp. 98-101
Keyword(s):
Keyword(s):
2014 ◽
Vol 535
◽
pp. 157-161
Keyword(s):
Keyword(s):