Title :
Neural network approach to diagnose faults in linear antenna array
Author :
Vakula, D. ; Sarma, NVSN
Author_Institution :
Nat. Inst. of Technol., Warangal, India
Abstract :
A novel approach using artificial neural network (ANN) is proposed to identify the faulty elements present in a non uniform linear array. The input to the neural network is amplitude of radiation pattern and output of neural network is the location of faulty elements. In this work, ANN is implemented with two algorithms; radial basis function neural network (RBF) and probabilistic neural network and their performance is compared. The network is trained with some of the possible faulty radiation patterns and tested with various measurement errors. It is proved that the method gives a high success rate.
Keywords :
electrical engineering computing; fault diagnosis; learning (artificial intelligence); linear antenna arrays; radial basis function networks; antenna radiation pattern; artificial neural network approach; fault diagnosis; linear antenna array; probabilistic neural network; radial basis function neural network; Antenna arrays; Antenna radiation patterns; Artificial neural networks; Fault diagnosis; Feeds; Linear antenna arrays; Neural networks; Neurons; Phased arrays; Testing;
Conference_Titel :
Electromagnetic Interference & Compatibility, 2008. INCEMIC 2008. 10th International Conference on
Conference_Location :
Bangalore
Print_ISBN :
978-81-903575-1-7