STATOR FAULT DETECTION FOR A BLDC MOTOR USING AN ARTIFICIAL NEURAL NETWORK
This work addresses the problem of stator short-circuit fault detection for an in-wheel Brushless Direct Current (BLDC) motor using a perceptron artificial neural network. The proposed FD scheme was compared with the motor current signature analysis based on discrete Fourier transform and discrete wavelet transform. The algorithms were validated on a test rig with an in-wheel BLDC motor for light electric vehicles.
STATOR FAULT DETECTION FOR A BLDC MOTOR USING AN ARTIFICIAL NEURAL NETWORK
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DOI: 10.22533/at.ed.3172112224064
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Palavras-chave: Fault detection, BLDC Motor, artificial neural network, perceptron.
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Keywords: Fault detection, BLDC Motor, artificial neural network, perceptron.
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Abstract:
This work addresses the problem of stator short-circuit fault detection for an in-wheel Brushless Direct Current (BLDC) motor using a perceptron artificial neural network. The proposed FD scheme was compared with the motor current signature analysis based on discrete Fourier transform and discrete wavelet transform. The algorithms were validated on a test rig with an in-wheel BLDC motor for light electric vehicles.
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Número de páginas: 15
- Francisco Javier Villalobos Piña
- Ricardo Alvarez Salas
- Josue Augusto Reyes Malanche
- Carlos Humberto Saucedo Zárate
- J. A. Alvarez Salas
- A. Rodriguez Cobos
- Rodolfo Jauregui Acevedo
