Artificial neural network for detection of asynchronous state

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...

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Bibliographic Details
Main Author: Kostyła, Paweł
Format: Conference Proceeding
Language:English
Subjects:
Artificial neural networks
Circuits
DC generators
Machine windings
Magnetic flux
neural network
optimization problem
Parallel algorithms
Power generation
Rotors
signal processing
Signal processing algorithms
Stator windings
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Description
Summary: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.
DOI:10.1109/EEEIC.2010.5489953