38 research outputs found
Detection of Broken Rotor Bars in Nonlinear Startups of Inverter-Fed Induction Motors
[EN] 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.Fernández-Cavero, V.; Pons Llinares, J.; Duque-Perez, O.; Morinigo-Sotelo, D. (2021). Detection of Broken Rotor Bars in Nonlinear Startups of Inverter-Fed Induction Motors. IEEE Transactions on Industry Applications. 57(3):2559-2568. https://doi.org/10.1109/TIA.2021.30663172559256857
A comparison of techniques for fault detection in inverter-fed induction motors in transient regime
"(c) 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works."[EN] Fault detection in induction motors operating in non-stationary regimes has become a need in today's industry. Most of the works published deal with line-fed motors. Nevertheless, the number of inverterfed induction motors has significantly increased in recent years. Therefore, several fault detection techniques have been proposed lately for this type of motors, based mainly on an adequate input signal processing to obtain fault signatures in the time-frequency domain. In this paper, a comparison of time-frequency techniques applied to fault detection in inverter-fed induction motors in a transient state is presented. For that purpose, the techniques are applied to two current signals acquired from two induction motors with two types of faults: bar breakage and mixed eccentricity. The paper shows the particularities and special difficulties of diagnosing under this type of feeding, reviewing the works related to each technique. The strengths and weaknesses of these techniques are discussed with the goal of providing a criterion for its application in an industrial environment and guidance for future developments in this field.This work was supported in part by the Spanish Ministerio de Economia y Competitividad and in part by the FEDER program in the framework of the Proyectos I+D del Subprograma de Generacion de Conocimiento, Programa Estatal de Fomento de la Investigacion Cientifica y Tecnica de Excelencia under Grant DPI2014-52842-P.Fernandez-Cavero, V.; Morinigo-Sotelo, D.; Duque-Perez, O.; Pons Llinares, J. (2017). A comparison of techniques for fault detection in inverter-fed induction motors in transient regime. IEEE Access. 5:8048-8063. https://doi.org/10.1109/ACCESS.2017.2702643S80488063
Reliable Detection of Rotor Bars Breakage in Induction Motors via MUSIC and ZSC Methods
"(c) 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works"[EN] Induction motors are used in a variety of industrial applications where frequent startup cycles are required. In those cases, it is necessary to apply sophisticated signal processing analysis methods in order to reliably follow the time evolution of fault-related harmonics in the signal. In this paper, the zero-sequence current (ZSC) is analyzed using the high-resolution spectral method of multiple signal classification. The analysis of the ZSC signal has proved to have several advantages over the analysis of a single-phase current waveform. The method is validated through simulation and experimental results. The simulations are carried out for a 1.1-MW and a 4-kW induction motors under finite element analysis. Experimentation is performed on a healthy motor, a motor with one broken rotor bar, and a motor with two broken rotor bars. The analysis results are satisfactory since the proposed methodology reliably detects the broken rotor bar fault and its severity, both during transient and steady-state operation of the induction motor.This work was supported in part by the Spanish Ministerio de Economia y Competitividad (MINECO) and in part by the FEDER program in the framework of the Proyectos I+D del Subprograma de Generacion de Conocimiento, Programa Estatal de Fomento de la Investigacion Cientifica y Tecnica de Excelencia under Grant DPI2014-52842-P.Morinigo-Sotelo, D.; Romero-Troncoso, R.; Panagiotou, P.; Antonino-Daviu, J.; Gyftakis, KN. (2018). Reliable Detection of Rotor Bars Breakage in Induction Motors via MUSIC and ZSC Methods. IEEE Transactions on Industry Applications. 54(2):1224-1234. https://doi.org/10.1109/TIA.2017.2764846S1224123454
Diagnosis of Broken Rotor Bars during the Startup of Inverter-Fed Induction Motors Using the Dragon Transform and Functional ANOVA
[EN] 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.This research has been partially funded by the University of Valladolid.Fernández-Cavero, V.; García-Escudero, LA.; Pons Llinares, J.; Fernández-Temprano, MA.; Duque-Perez, O.; Morinigo-Sotelo, D. (2021). Diagnosis of Broken Rotor Bars during the Startup of Inverter-Fed Induction Motors Using the Dragon Transform and Functional ANOVA. Applied Sciences. 11(9):1-12. https://doi.org/10.3390/app1109376911211
Very Accurate Time-Frequency Representation of Induction Motors Harmonics for Fault Diagnosis Under Load Variations
Induction motors work under steady-state in many applications. Nevertheless, in some cases they experience periodic load fluctuations, which generate constant frequency harmonics close to variable frequency bar breakage harmonics. In these cases, time-frequency (t-f) transforms are better suited than steady-state analysis since the fault harmonic frequencies change in time. Even if the healthy and faulty frequencies do not overlap in the spectrum, if the speed is unknown, it is difficult to distinguish the constant frequency healthy harmonic from the variable frequency bar breakage harmonic. On the other hand, transient techniques present in technical literature are not precise enough to deal with both the changing frequency of the bar breakage harmonic and a close constant frequency (as the one generated by most of the periodic load fluctuations). To achieve reliable results under these challenging situations, a very precise time-frequency transform must be used, enabling to simultaneously draw the constant and variable frequencies, even if they are very close in the t-f plane. The Dragon-Transform is here proposed to address the problem. It is shown through simulation and experimental results, how it enables to very accurately plot up to five faulty harmonics evolutions, distinguishing at the same time the constant frequency of the load oscillation, traced as a very thin horizontal line. Precision is so high that even the oscillations caused by ripple effect can be observed for the first time in technical literature, enhancing the reliability of the diagnosis performed, and opening the path for a true solution of the problem
Detection and quantification of bar breakage harmonics evolutions in inverter-fed motors through the dragon transform
[EN] 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.Fernández-Cavero, V.; Pons Llinares, J.; Duque-Perez, O.; Morinigo-Sotelo, D. (2021). Detection and quantification of bar breakage harmonics evolutions in inverter-fed motors through the dragon transform. ISA Transactions. 109:352-367. https://doi.org/10.1016/j.isatra.2020.10.02035236710