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Enhanced ANN with Ant Lion Optimization for Diagnose the Incipient Faults of Synchronous Generator


B. Vidyasagar and Dr.S.S. Tulasi Ram
Abstract

In the paper, an enhanced hybrid the Artificial Neural Network (ANN) and Ant Lion Optimization (ALO) technique based incipient fault detection and characterization are performed in the Synchronous Generator (SG). In this paper, the ALO algorithm is used to produce the ANN and the ANN exhibitions are enhanced. In the beginning time frame, the SG is investigated in the common condition. Starting now and into the foreseeable future, the issue is made and the framework practices are checked. Here, DWT is used to remove the highlights and structures the datasets which are sent to ANN classifier for orchestrating the kind of inadequacy. The proposed system is realized in MATLAB/Simulink stage and differentiated and the current methodologies, for example, DWT-ANN, DWT-ANN with GA and DWT-ANN with GSA strategies. To ensure the fairness of the proposed system, the factual measures are solved, for example, sensitivity, accuracy and specificity, mean, median and standard deviation.

Volume 11 | 10-Special Issue

Pages: 1509-1526

DOI: 10.5373/JARDCS/V11SP10/20192997