https://hdl.handle.net/10259/4266 2026-04-20T06:11:24Z https://hdl.handle.net/10259/9948 Detection and quantification of bar breakage harmonics evolutions in inverter-fed motors through the dragon transform Fernández Cavero, Vanesa; Pons Llinares, Joan; Duque Pérez, Óscar; Morinigo Sotelo, Daniel The problem of detecting and quantifying bar breakage harmonics in inverter-fed induction motors has not been solved by the time–frequency transforms present in the technical literature. The paper proposes a new transform, called dragon transform, to solve this problem. The dragon atoms are defined with shapes perfectly adapted to the harmonic trajectories in the time–frequency plane, no matter how complex they are, enabling the precise tracing of the harmonics to be detected. A quantification method is also proposed, which obtains for the first time in the technical literature, the time evolutions of the harmonic amplitudes during a complex transient such as the start-up and the steady state of an inverter-fed motor. The transform performance is validated testing the induction motor under different load levels. 2021-03-01T00:00:00Z https://hdl.handle.net/10259/9945 Detection of Broken Rotor Bars in Nonlinear Startups of Inverter-Fed Induction Motors Fernández Cavero, Vanesa; Pons Llinares, Joan; Duque Pérez, Óscar; Morinigo Sotelo, Daniel Fault detection in induction motors powered by inverters operating in nonstationary regimes remains a challenge. The trajectory in the time–frequency plane of harmonics related to broken rotor bar develops very in proximity to the path described by the fundamental component. In addition, their energy is much lower than the amplitude of the first harmonic. These two characteristics make it challenging to observe them. The Dragon Transform (DT), here presented, is developed to overcome the described problem. In this article, the DT is assessed with nonlinear inverter-fed startups, where its high time and frequency resolutions facilitate the monitoring of fault harmonics even with highly adjacent trajectories to the first harmonic path. 2021-03-01T00:00:00Z https://hdl.handle.net/10259/9944 Broken Rotor Bar Detection in Closed Loop Inverter Fed Induction Motors Through Time-Frequency Techniques Mantione, Lorenzo; García Calva, Tomás; Fernández Cavero, Vanesa; Frosini, Lucía; Morinigo Sotelo, Daniel In traction,automotive,and some industrial processes,the operation of the induction motor is set using speed. This creates an additional control loop that is external to the current controller that inverters already possess. While the impact of the latter control loop on fault detection in induction motors has already been studied,the influence of closed-loop speed control has not been explored enough. This paper presents the findings on the impact of PID speed control on the broken rotor bar fault detection. The study reveals that the constant corrective actions of the PID controller to correct the speed cause an increase in the noise level and spectral leakage around the first harmonic in the stator current spectrum that prevents fault detection. It is concluded that it is necessary to use time-frequency analysis techniques with excellent spectral resolution,such as the Dragon Transform or the Min-Norm technique. 2024-10-01T00:00:00Z https://hdl.handle.net/10259/9937 Diagnosis of Broken Rotor Bars during the Startup of Inverter-Fed Induction Motors Using the Dragon Transform and Functional ANOVA Fernández Cavero, Vanesa; García Escudero, Luis Ángel; Pons Llinares, Joan; Fernández Temprano, Miguel Alejandro; Duque Pérez, Óscar; Morinigo Sotelo, Daniel 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. 2021-04-01T00:00:00Z