Abstract
In this paper, an integrated quantum inspired GA (QGA) based generalized neural network (QGA–GNN) has been developed. The QGA–GNN is used for estimation of stator resistance of a 5 hp three phase induction motor (3Φ I.M.) under different healthy and unhealthy working conditions. The experimentation is performed in the laboratory for estimating stator winding resistance under healthy and faulty (i.e., 10, 20, 30, or 40% short circuited) conditions. The motor current and motor speed are considered as input and stator resistance as output of the proposed technique. The results obtained from QGA–GNN are compared with the ANN and GNN. QGA–GNN is giving good results under different working conditions.
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