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

MLA

Biot-Monterde, Vicente, et al. “Automatic Classification of Rotor Faults in Soft-Started Induction Motors, Based on Persistence Spectrum and Convolutional Neural Network Applied to Stray-Flux Signals.” Sensors (14248220), vol. 23, no. 1, Jan. 2023, p. 316. EBSCOhost, https://doi.org/10.3390/s23010316.

APA

Biot-Monterde, V., Navarro-Navarro, A., Zamudio-Ramirez, I., Antonino-Daviu, J. A., & Osornio-Rios, R. A. (2023). Automatic Classification of Rotor Faults in Soft-Started Induction Motors, Based on Persistence Spectrum and Convolutional Neural Network Applied to Stray-Flux Signals. Sensors (14248220), 23(1), 316. https://doi.org/10.3390/s23010316

Chicago

Biot-Monterde, Vicente, Angela Navarro-Navarro, Israel Zamudio-Ramirez, Jose A. Antonino-Daviu, and Roque A. Osornio-Rios. 2023. “Automatic Classification of Rotor Faults in Soft-Started Induction Motors, Based on Persistence Spectrum and Convolutional Neural Network Applied to Stray-Flux Signals.” Sensors (14248220) 23 (1): 316. doi:10.3390/s23010316.