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Early diagnosis of faults that might occur in industrial processes makes it possible to perform important preventative actions and therefore avoid the heavy economic losses involved in production stoppages and the replacement of elements and parts. The main idea of detecting shorted turns on rotor poles in hydrogenerators using artificial neural networks is to generate signals that reflect inconsistencies between nominal and faulty system operating conditions. Two types of nonlinear autoregressive networks with exogenous inputs (NARX) are used. In both cases one can successfully detect shorted turns on rotor poles

10.5937/zeint24-6596 = Detection of shorted turns on rotor poles in hydrogenerators using artificial neural networks