Stator Fault Diagnosis of a Permanent Magnet Synchronous Generator Using a Decision Tree Classifier

https://doi.org/10.58571/CNCA.AMCA.2024.068

Resumen: This work presents a decision tree-based classifier to diagnose short circuit faults between the stator’s turns in a permanent magnet synchronous generator. The generator currents are processed with the discrete wavelet transform to obtain features to feed the binary classifier that performs the diagnosis. Experimental results are presented to show the performance of the proposed scheme.

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Alvarez Salas, J.A., Alvarez Salas, R., González García, M.A., Villalobos Piña, F.J. & Cárdenas, V. (2024). Stator Fault Diagnosis of a Permanent Magnet Synchronous Generator Using a Decision Tree Classifier. Memorias del Congreso Nacional de Control Automático 2024, pp. 399-404. https://doi.org/10.58571/CNCA.AMCA.2024.068

Palabras clave

Binary classifier, decision tree, faults, permanent magnet synchronous generator

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