Introducing the Filtered Park’s and Filtered Extended Park’s Vector Approach to Detect Broken Rotor Bars in Induction Motors Independently from the Rotor Slots Number

[EN] The Park's Vector Approach (PVA), together with its variations, has been one of the most widespread diagnostic methods for electrical machines and drives. Regarding the broken rotor bars fault diagnosis in induction motors, the common practice is to rely on the width increase of the Park's Vector (PV) ring and then apply some more sophisticated signal processing methods. It is shown in this paper that this method can be unreliable and is strongly dependent on the magnetic poles and rotor slot numbers. To overcome this constraint, the novel Filtered Park's/Extended Park's Vector Approach (FPVA/FEPVA) is introduced. The investigation is carried out with FEM simulations and experimental testing. The results prove to satisfyingly coincide, whereas the proposed advanced FPVA method is desirably reliable. (C) 2017 Elsevier Ltd. All rights reserved.The authors acknowledge the support of the Portuguese Foundation for Science and Technology under Project No. SFRH/BSAB/118741/2016, and also the support of the Spanish 'Ministerio de Economia y Competitividad' (MINECO) and 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' (ref: DPI2014-52842-P).Gyftakis, KN.; Marques Cardoso, AJ.; Antonino-Daviu, J. (2017). Introducing the Filtered Park's and Filtered Extended Park's Vector Approach to Detect Broken Rotor Bars in Induction Motors Independently from the Rotor Slots Number. Mechanical Systems and Signal Processing. 93:30-50. https://doi.org/10.1016/j.ymssp.2017.01.046S30509

On the broken rotor bar diagnosis using time-frequency analysis:'Is one spectral representation enough for the characterisation of monitored signals?'

© 2019 Institution of Engineering and Technology. All rights reserved. This work enhances the knowledge of the diagnostic potential of the broken bar fault in induction motors. Since a series of studies have been published over the years regarding condition monitoring and fault diagnostics of these machines, it is essential to reach a common ground on why - sometimes - different techniques render different results. In this context, an investigation is provided with regards to the optimal window that should be adopted for the implementation of a proper time-frequency analysis of the monitored signals. On this agenda, this study attempts to set lower and upper bound limits for proper windowing from the digital signal processing point of view. This is done by proposing a formula for the lower limit, which is derived according to the specific frequencies one desires to put under inspection and which are the fault-related signatures. Finally, a discussion on the upper bound is put onwards; results from finite-element simulations are examined with the discussed approach in both the transient regime and the steady state, while experimental results verify the simulations with satisfying accuracy

A New Approach for Broken Rotor Bar Detection in Induction Motors Using Frequency Extraction in Stray Flux Signals

This paper offers a reliable solution to the detection of broken rotor bars in induction machines with a novel methodology, which is based on the fact that the fault-related harmonics will have oscillating amplitudes due to the speed ripple effect. The method consists of two main steps: Initially, a time-frequency transformation is used and the focus is given on the steady-state regime; thereupon, the fault-related frequencies are handled as periodical signals over time and the classical fast Fourier transform is used for the evaluation of their own spectral content. This leads to the discrimination of subcomponents related to the fault and to the evaluation of their amplitudes. The versatility of the proposed method relies on the fact that it reveals the aforementioned signatures to detect the fault, regardless of the spatial location of the broken rotor bars. Extensive finite element simulations on a 1.1 MW induction motor and experimental testing on a 1.1 kW induction motor lead to the conclusion that the method can be generalized on any type of induction motor independently from the size, power, number of poles, and rotor slot numbers

FEM approach for diagnosis of induction machines' non-adjacent broken rotor bars by short-time Fourier transform spectrogram

Rotor electrical faults are an issue frequently encountered when applying condition monitoring and fault diagnosis on induction machines. The detection via the analysis of the stator current becomes challenging when the rotor cage suffers from multiple breakages at non-adjacent positions. In that case, electromagnetic asymmetries induced by the broken bars can be masked in such a way, that the diagnostic ability is highly likely to be obscured, thus leading to misinterpretation of the monitored signals’ signatures. A new approach is proposed in this work to overcome this problem while the motor is at steady state. In this paper, an industrial 6.6kV, 1.1MW induction motor is simulated with Finite Element Analysis (FEM) and its electromagnetic variables are analysed and studied under healthy state and several faulty conditions. The analysis of the stator current and stray flux waveforms is executed in both the transient and the steady state and aims to diagnose the challenging cases where the rotor breakages are nonconsecutive with regards to their spatial location. The results show the potential of flux analysis to fault severity regardless of the spatial position of the broken bars

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