DocumentCode :
2717056
Title :
Artificial neural network for detection of asynchronous state
Author :
Kostyla, Pawel
Author_Institution :
Dept. of Electr. Eng., Wroclaw Univ. of Technol., Wroclaw, Poland
fYear :
2010
fDate :
16-19 May 2010
Firstpage :
171
Lastpage :
174
Abstract :
An asynchronous state of a synchronic machine may be identified through determining the amplitudes of particular components of stator´s current provided that a constant slip value is assumed. Following a synchronism loss, this adopted value is assumed to be achieved and, for sure, exceeded. New parallel algorithms for detection of asynchronous state of synchronic machines, are proposed. The algorithms can be implemented by analogue adaptive circuits employing some neural networks principles. This chapter provides a description of artificial neural networks realising this task, whose operation algorithm is based on minimum square error criteria and maximum loss method.
Keywords :
Artificial neural networks; Circuits; DC generators; Machine windings; Magnetic flux; Parallel algorithms; Power generation; Rotors; Signal processing algorithms; Stator windings; neural network; optimization problem; parallel algorithms; signal processing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Environment and Electrical Engineering (EEEIC), 2010 9th International Conference on
Conference_Location :
Prague, Czech Republic
Print_ISBN :
978-1-4244-5370-2
Electronic_ISBN :
978-1-4244-5371-9
Type :
conf
DOI :
10.1109/EEEIC.2010.5489953
Filename :
5489953
Link To Document :
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