Speed Estimation in Induction Motor Starting Transient using Wavelet Transform

Speed measurement in induction motors is of utmost importance for diagnosing the drive and adjusting its startup method. The use of sensors directly coupled to the motor can pose problems in the industry due to their fragility. In this context, sensorless speed estimation alternatives are of interest. This work tracks the positive sequence spectral components present in the stator currents associated with rotor speed. The continuous wavelet transform (CWT) is employed for this purpose, as it allows the analysis of non-periodic and rapidly varying functions. Results are presented for the startup of a 5.5 kW motor with a duration of 1.5 seconds and a 5.4 MW wound rotor motor with a liquid starter.

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Published
2024-09-18
DOI
https://doi.org/10.1109/argencon62399.2024.10735961
Primary Topic
Sensorless Control of Electric Motors
Type
article
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Speed Estimation in Induction Motor Starting Transient using Wavelet Transform

Cristian Ruschetti, Ricardo Lima, Carlos Verucchi, Matías Meira et al.
Sensorless Control of Electric Motors
article

Speed Estimation in Induction Motor Starting Transient using Wavelet Transform

Cristian Ruschetti, Ricardo Lima, Carlos Verucchi, Matías Meira, Lucas Puntano
article en

Abstract

Speed measurement in induction motors is of utmost importance for diagnosing the drive and adjusting its startup method. The use of sensors directly coupled to the motor can pose problems in the industry due to their fragility. In this context, sensorless speed estimation alternatives are of interest. This work tracks the positive sequence spectral components present in the stator currents associated with rotor speed. The continuous wavelet transform (CWT) is employed for this purpose, as it allows the analysis of non-periodic and rapidly varying functions. Results are presented for the startup of a 5.5 kW motor with a duration of 1.5 seconds and a 5.4 MW wound rotor motor with a liquid starter.

Consejo Nacional de Investigaciones Científicas y Técnicas (AR), Instituto Médico Río Cuarto (AR)
Affordable and clean energy
Openalex Percentile: Top 83%
Sensorless Control of Electric Motors
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