2026-04-20T21:14:13Zhttps://riubu.ubu.es/oai/request

oai:riubu.ubu.es:10259/99372025-01-16T01:05:51Zcom_10259_9931com_10259_4266com_10259.4_106com_10259_2604col_10259_9932

00925njm 22002777a 4500 dc 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 author 2021-04 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. http://hdl.handle.net/10259/9937 10.3390/app11093769 2076-3417 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