Enhancement of Neural Networks Novelty Filters with Genetic Algorithms. | ||||
| MEJ- Mansoura Engineering Journal | ||||
| Article 6, Volume 22, Issue 4, December 1997, Page 14-23 PDF (86.17 K) | ||||
| Document Type: Research Studies | ||||
| DOI: 10.21608/bfemu.2021.150965 | ||||
 View on SCiNiTO | ||||
| Author | ||||
| Hamed Elsimary* | ||||
| Electronics Research Institute., Dokki, Giza., Egypt. | ||||
| Abstract | ||||
| In this paper a method for enhancing the capabilities of Neural Networks novelty filters using genetic algorithms is described, and a method for detecting shorted turns in rotating machines using such computational intelligence techniques (neural network and genetic algorithm) is presented. The methods of signal processing and detection of faults in operating machines is discussed. The use of novelty filters for the detection of shorted turns and mechanical failures in operating machines is described. Genetic algorithm has been used to train the neural network to enhance its Capabilities as a novelty detector. The proposed technique has been applied on an induction machine and the simulation results have been presented to show the effectiveness of the proposed technique. | ||||
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