Title :
Restoring current signals in real time using feedforward neural nets
Author :
Braun, U. ; Feser, K.
Author_Institution :
Stuttgart Univ., Germany
Abstract :
The paper reports about the application of artificial neural networks (ANN) as nonlinear filters. The ANNs are used to restore current waveforms distorted by saturation of current transducers. The paper presents the progress in this application of ANN.
Keywords :
feedforward neural nets; learning (artificial intelligence); power system computer control; power system protection; power system restoration; real-time systems; AI; application; busbar protection; current transducers; current waveforms; digital control; feedforward neural nets; learning; nonlinear filters; power system restoration; real time; saturation; Artificial neural networks; Convergence; Ear; Feedforward neural networks; Filters; Neural networks; Nonlinear distortion; Protection; Relays; Signal restoration;
Conference_Titel :
Neural Networks to Power Systems, 1993. ANNPS '93., Proceedings of the Second International Forum on Applications of
Conference_Location :
Yokohama, Japan
Print_ISBN :
0-7803-1217-1
DOI :
10.1109/ANN.1993.264308
