2026-04-20T21:14:48Zhttps://riubu.ubu.es/oai/requestoai:riubu.ubu.es:10259/99372025-01-16T01:05:51Zcom_10259_9931com_10259_4266com_10259.4_106com_10259_2604col_10259_9932
Repositorio Institucional de la Universidad de Burgos
author
Fernández Cavero, Vanesa
author
García Escudero, Luis Ángel
author
Pons Llinares, Joan
author
Fernández Temprano, Miguel Alejandro
author
Duque Pérez, Óscar
author
Morinigo Sotelo, Daniel
2025-01-15T13:27:50Z
2025-01-15T13:27:50Z
2021-04
http://hdl.handle.net/10259/9937
10.3390/app11093769
2076-3417
A proper diagnosis of the state of an induction motor is of great interest to industry given the great importance of the extended use of this motor. Presently, the use of this motor driven by a frequency converter is very widespread. However, operation by means of an inverter introduces certain difficulties for a correct diagnosis, which results in a signal with higher harmonic content and noise level, which makes it difficult to perform a correct diagnosis. To solve these problems, this article proposes the use of a time-frequency technique known as Dragon Transform together with the functional ANOVA statistical technique to carry out a proper diagnosis of the state of the motor by working directly with the curves obtained from the application of the transform. A case study is presented showing the good results obtained by applying the methodology in which the state of the rotor bars of an inverter-fed motor is diagnosed considering three failure states and operating at different load levels.
eng
Atribución 4.0 Internacional
Induction motors
Transient analysis
Fault diagnosis
Functional ANOVA
Diagnosis of Broken Rotor Bars during the Startup of Inverter-Fed Induction Motors Using the Dragon Transform and Functional ANOVA
info:eu-repo/semantics/article
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URL
https://riubu.ubu.es/bitstream/10259/9937/1/Fernandez-as_2021.pdf
File
MD5
55ba3012c1c0bbadaf89bc21820353bb
8713938
application/pdf
Fernandez-as_2021.pdf