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Automatic Classification of Rotor Faults in Soft-Started Induction Motors, Based on Persistence Spectrum and Convolutional Neural Network Applied to Stray-Flux Signals

Vicente Biot-Monterde; Angela Navarro-Navarro; Israel Zamudio-Ramirez; Jose A. Antonino-Daviu; Roque A. Osornio-Rios (MDPI AG, 2023-01)

[EN] Due to their robustness, versatility and performance, induction motors (IMs) have been widely used in many industrial applications. Despite their characteristics, these machines are not immune to failures. In this ...
The Use of the Wavelet Approximation Signal as a Tool for the Diagnosis of Rotor Bar Failures

Riera-Guasp, Martín; Antonino-Daviu, J.; Roger-Folch, José; Molina Palomares, Mª Pilar (Institute of Electrical and Electronics Engineers, 2008)

[EN] 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 ...
Validation of a New Method for the Diagnosis of Rotor bar Failures via Wavelet Transformation in Industrial Induction Machines

Antonino-Daviu, J.; Riera-Guasp, Martín; Roger-Folch, José; Molina Palomares, Mª Pilar (Institute of Electrical and Electronics Engineers, 2006)

[EN] 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). ...

Mostrando ítems 1-3 de 3