Abstract
In this work, a strategy is proposed for the automatic diagnosis of failures in gearboxes using current signals from an induction motor. The stator currents were represented by the extended Park vector approach technique and decomposed by the wavelet packet transform. The calculation of the wavelet packet entropy promoted the distinction between broken tooth failures and the levels of severity of surface wear. The entropies of two wavelet details were used as inputs for a fuzzy inference for automatic classification of the gearbox condition. The experimental results presented a high rate of correctness in the fuzzy diagnosis, confirming the efficiency of the strategy for high rotation (60 Hz) and low rotation (20 Hz). The strategy presents simplicities related to the practical implementation and reduction of the amount of data analyzed.
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