E. Castaeda Moya

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A hybrid neural network-first principles modelling scheme is used in this paper, to model an induction motor and to develop a fault detection and isolation (FDI) scheme. The hybrid model combines a partial first principles model, which incorporates the available prior knowledge about the process being modelled, with a neural network which serves as an(More)
In this paper a new approach to fault diagnosis in an AC motor is introduced. This system combines a neuro-fuzzy system called FasArt (Fuzzy Adaptive System ART based) and the well-known fuzzy k nearest neighbor algorithm. A set of 15 types of non destructive faults has been tested, reaching a high degree of early fault detection and fault type recognition.(More)
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