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

Mishra, Subhash C.

doi:10.9790/1676-0862732

Cited by 2 publications

(1 citation statement)

References 24 publications

(50 reference statements)

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“…Again in [11], Khan et al showed the application of firefly algorithm (FF) in identifying fault in nonuniformly excited linear antenna array. In [12], a comparative study by Mishra et al on fault finding in antenna arrays using neural networks and genetic algorithms found both methods computationally intensive. Harrou and Nounou in [13] proposed an exponentially weighted moving average control scheme for detecting faults in linear antenna arrays, including full faults and partial faults.…”

Section: Patnaik Et Al Employed An Artificial Neural Network (Ann)mentioning

confidence: 99%

Evolutionary Algorithm-Inspired Binary Sequence-Based Hybrid Fault Detection Method for Nonuniformly Excited Linear Antenna Array

Mitra,

Chatterjee,

Chatterjee

et al. 2024

International Journal of RF and Microwave Computer-Aided Engine

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In this article, a novel method of fault detection in nonuniformly excited linear antenna array has been reported. This method uses an evolutionary algorithm-based technique to generate approximate radiation pattern in tune with reference faulty pattern for a nonuniformly excited linear antenna array. Based on the approximation, a binary sequence-based method of exact fault detection has been developed. In order to illustrate the effectiveness of the method, 12- and 20-element Dolph Tschebyscheff linear antenna array with amplitude fault has been considered. Superiority of the proposed method has been demonstrated through comparative study.

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Section: Patnaik Et Al Employed An Artificial Neural Network (Ann)mentioning

confidence: 99%

Evolutionary Algorithm-Inspired Binary Sequence-Based Hybrid Fault Detection Method for Nonuniformly Excited Linear Antenna Array

Mitra,

Chatterjee,

Chatterjee

et al. 2024

International Journal of RF and Microwave Computer-Aided Engine

View full text Add to dashboard Cite

show abstract

Evolutionary Algorithm Inspired Binary Sequence based Fault Detection in Uniformly Excited Linear Antenna Array

Chatterjee,

Mitra,

Chatterjee

et al. 2023

2023 IEEE Microwaves, Antennas, and Propagation Conference (MAPCON)

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

Cited by 2 publications

References 24 publications

Evolutionary Algorithm-Inspired Binary Sequence-Based Hybrid Fault Detection Method for Nonuniformly Excited Linear Antenna Array

Evolutionary Algorithm-Inspired Binary Sequence-Based Hybrid Fault Detection Method for Nonuniformly Excited Linear Antenna Array

Evolutionary Algorithm Inspired Binary Sequence based Fault Detection in Uniformly Excited Linear Antenna Array

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