Bayesian Gaussian Mixture Model Classifier for Fault Detection in Induction Motors Using Start-Up Current Analysis

Induction motors constitute a major share of industrial drives, making reliable fault detection essential for maintaining operational continuity. This work develops a Bayesian classifier for identifying rotor-bar damage using start-up current measurements represented in the frequency domain. The spe...

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Egile Nagusiak:	Kacper Jarzyna, Michał Rad, Paweł Piątek, Jerzy Baranowski
Formatua:	Artigo
Hizkuntza:	Inglês
Argitaratua:	MDPI AG 2026-03-01
Saila:	Energies
Gaiak:	Bayesian analysis fault detection frequency-domain analysis Gaussian mixture models induction motors
Sarrera elektronikoa:	https://www.mdpi.com/1996-1073/19/5/1328
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