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In this paper, the authors propose a method for the diagnosis of rotor bar failures in induction machines, based on the analysis of the stator current during the startup using the discrete wavelet transform (DWT). Unlike other approaches, the study of the high-order wavelet signals resulting from the decomposition is the core of the proposed method. After(More)
In this paper, a cutting-edge time-frequency decomposition tool, i.e., the <i>Hilbert-Huang</i> <i>transform</i> (HHT), is applied to the stator startup current to diagnose the presence of rotor asymmetries in induction machines. The objective is to extract the evolution during the startup transient of the left sideband harmonic (LSH) caused by the(More)
The aim of this paper is to present a new approach for rotor bar failure diagnosis in induction machines. The method focuses on the study of an approximation signal resulting from the wavelet decomposition of the startup stator current. The presence of the left sideband harmonic is used as evidence of the rotor failure in most diagnosis methods based on the(More)
Motor current signature analysis (MCSA) is a well-established method for the diagnosis of induction motor faults. It is based on the analysis of the spectral content of a motor current, which is sampled while a motor runs in steady state, to detect the harmonic components that characterize each type of fault. The Fourier transform (FT) plays a prominent(More)