A genetically trained neural network application for fault finding in antenna arrays

A Survey on Applications of Neural Networks and Genetic Algorithms in Fault Diagnostics for Antenna Arrays

“…Authors in [26] have extended the idea further to present a flexible approach of locating fault elements in antenna arrays using artificial neural networks employing MLPs trained in back propagation. Waveguide fed longitudinal slot array antennas: Fault diagnosis using measurements of input impedance [23] Genetic algorithm 12-slot linear array 5 Antenna array adjust with adaptive neuronal system [24] Adaline neural network 16-element linear array 6 Finding failed element positions in linear Antenna arrays using neural networks [25] Multi layer perceptron neural network 5-element array 7 An ANN application for fault finding in Antenna arrays [26] Multi layer perceptron neural network 16-element linear micro strip array, d=0.3λ 8 A comparison among several techniques for finding defective elements in antenna array [27] Case based reasoning, Neural networks, Genetic algorithm 100-element linear array, d=0.5λ 9 Element failure detection in linear antenna array using case based reasoning [28] Case based reasoning, SOM neural network 100-element linear array, d=0.5λ 10 A genetically trained neural network application for fault finding in antenna arrays [29] Multi layer perceptron with Genetic algorithm 16-element linear array, d=0.3λ…”

“…Faults in antennas distort the radiation pattern and cause sharp variations in the field intensity around an antenna array which increases the side lobes and ripple level of the power pattern [26] [29]. The patterns can be restored however through readjustment of the excitations of the non-defective elements to produce a pattern with respect to the original [21] [30].…”

“…This enables to obtain the number and the location of the defective elements. In the case of partial failures also, this chromosome is able to know the grade of failure of the array elements [20][21] [30].Genetic algorithms can also be used with neural networks for locating faults in arrays [29].…”

“…Genetic algorithms have also been very effectively used in fault diagnosis of arrays as mentioned ahead [20] [21][23] [30]. A combination suggested by authors in [29] utilizes features of both the approaches; the neural network and the genetic algorithm. Section II describes the mathematical nature of the fault finding problem.…”

“…This method has been found to be more effective with a success rate of around 93% as compared to 76.7 % for MLP 76.0 % for RBF. In [29], authors have presented the hybridization of the two approaches; the genetic algorithm (GA) and the back propagation network (BPN) employing a three layer multi layer perceptron (MLP). In this work, the fault finding in antenna arrays has been considered as a mapping and weight optimization problem.…”