Extreme Learning Machine in the Breaker Fault Diagnosis
2014 ◽
Vol 960-961
◽
pp. 896-899
Keyword(s):
In order to improve the diagnosis method of the existing high-voltage circuit breaker fault, demonstrated a new diagnosis methord of mechanical failure of high voltage circuit breaker based on vibration signal. According to the factors of high voltage circuit breaker failure and the features of Single-hidden Layer Feedforward Neural Network, SLFN, a method of high voltage circuit breaker fault diagnosis proposed based on Extreme Learning Machine (ELM). Finally, the experiment proves the effectiveness of this method for breaker fault diagnosis based on vibration signal analysis and ELM.
2014 ◽
Vol 687-691
◽
pp. 1054-1057
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2019 ◽
Vol 21
(6)
◽
pp. 1665-1678
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2017 ◽
pp. 227-236
Keyword(s):
2019 ◽
Vol 15
(1)
◽
pp. 413-420
◽
Keyword(s):
2020 ◽
Vol 1601
◽
pp. 062048
Keyword(s):