2-D Magnetomechanical Transient Study of a Motor Suffering a Bar Breakage

© 1972-2012 IEEE. The analysis of the vibration response of electrical machines has importance in noise prediction and more recently, diagnosis of electrical faults, especially in the industrial environment, where it is a well-known technique. This work assesses the performance of a strongly coupled two-dimensional (2-D) magnetomechanical approach, as directly available in multiphysics software, for the simulation of an induction machine under heavy operational conditions: a direct-on-line startup. Both healthy and broken bar states are simulated in a time span long enough to allow the detailed study of the varying frequency components. The results yield, in addition to the usual electrical and magnetic quantities, electromagnetic-induced vibration components in the stator. A comparison with current and vibration experimental data is also performed showing a good agreement with variable frequency components and certain limitations concerning their amplitude

Study of thermal stresses developed during a fatigue test on an electrical motor rotor cage

© 2018 Structural defects in the rotor cage of large electrical machines significantly impact their expected operational lifetime. This work presents the results of simulating the thermal stresses developed in a rotor cage during a fatigue test in which a bar breakage was achieved. A combined model featuring electrical, thermal and mechanical stages as well as three different meshes reflecting a progressing narrowing of one of the bars in its junction to the end ring are used for this purpose. The experimentally implemented startup and plug stopping transients are reproduced as well as, for comparison, the stall operation. The resulting stress levels are in agreement with the progression of the damage and concur with the stator measurements. Based on the analysis of the simulated rotor magnitudes, a strategy to diminish the thermal stresses in a damaged cage is proposed

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

Air-gap force distribution and vibration pattern of Induction motors under dynamic eccentricity

[EN] A method for determining the signatures of dynamic eccentricity in the airgap force distribution and vibration pattern of induction machine is presented. The radial electromagnetic force distribution along the airgap, which is the main source of vibration, is calculated and developed into a double Fourier series in space and time. Finite element simulations of faulty and healthy machines are performed. They show that the electromagnetic force distribution is a sensible parameter to the changes in the machine condition. The computations show the existence of low frequency and low order force distributions, which can be used as identifiable signatures of the motor condition by measuring the corresponding low order vibration components. These findings are supported by vibration measurements and modal testing. The low frequency components offer an alternative way to the monitoring of slot passing frequencies, bringing new components that allow to discriminate between dynamic eccentricity and rotor mechanical unbalance. The method also revealed a non linear relationship between loading, stress waves and vibration during dynamic eccentricity.Jover Rodríguez, PV.; Belahcen, A.; Arkkio, A.; Laiho, A.; Antonino-Daviu, J. (2008). Air-gap force distribution and vibration pattern of Induction motors under dynamic eccentricity. Electrical Engineering. 90(3):209-218. doi:10.1007/s00202-007-0066-2S209218903Rao JS (2000). Vibratory condition monitoring of machines. CRC Pr. Llc., Boca RatonTavner P, Penman J (1987) Condition monitoring of electrical machines. Research Studies Press, Letchworth, pp 203–205Pöyhönen S, Negrea M, Jover P, Arkkio A and Hyötyniemi H (2003). Numerical magnetic field analysis and signal processing for fault diagnostic of electrical machines. COMPEL Int J Comput Math Elect Eng 22(4): 969–981Finley W, Hodowanec M, Holter W (2000) An analytical approach to solving motor vibration problems. IEEE Trans Industry Appl 363(5)Cameron JR, Thomson WT, Eng C, Dow AB (1986) Vibration and current monitoring for detecting airgap eccentricity in large induction motors. IEE Proc Inst Elect Eng 133(Pt. B, No. 3)Smith AC, Dorrell DG (1996) Calculation and measurements of unbalance magnetic pull in cage induction motors with eccentric rotors. Part 1: Analytical model. IEE Proc Elect Power Appl 143(3)Dorrell DG, Smith AC (1996) Calculation and measurements of unbalance magnetic pull in cage induction motors with eccentric rotors. Part 2: Experimental investigation. IEE Proc Elect Power Appl 143(3)Dorrell DG, Thomson WT and Roach S (1997). Analysis of airgap flux, current, and vibration signals as a function of a combination of static and dynamic eccentricity in 3-phase induction motors. IEEE Trans Indus Appl 33: 24–34Verma SP, Balan A (1994) Determination of radial forces in relation to noise and vibrations problems of squirrel cage induction motors. IEEE Trans Energy Convers 9(2)Vandevelde L, Melkebeek AA (2001) Numerical analysis of vibrations of squirrel-cage induction motors based on magnetic equivalent circuits and structural finite element models. In: Industry Application Conference, 2001. Thirsty-six IAS Annual Meeting. Conference records of the 2001 IEEE, vol 4, September/October 2001, pp 2288–2295Belahcen A, Arkkio A, Klinge P, Linjama J, Voutilainen V, Westerlund J (1999) Radial forces calculation in a synchronous generator for noise analysis. In: Proceeding of the Third Chinese International Conference on Electrical Machines, August 29–31, 1999, Xi’an, China, pp 199–122Jover Rodríguez P, Belahcen A, Arkkio A (2007) Signatures of electrical faults in force distribution and vibration pattern of induction motors. IEE Proc Elect Power Appl (in press)Arkkio A (1987) Analysis of induction motor based on numerical solution of the magnetic field and circuits equations. Acta Polytechn. Scand Electri Eng Serie 59:97. Available at  Ewings DG (2000). MODAL TESTING: theory, practice and application, 2nd edn. Research studies press Ltd., BaldockDeBertoli MJ, Salon SJ, Burow DW, Slavik CJ (1993) Effects of rotor eccentricity and parallel windings on induction machine behaviour: a study using finite element analysis. IEEE Trans Magnet 29(2)Arkkio A, Antila M, Pokki K, Lanto E (2000) Electromagnetic force in a whirling cage rotor. IEE Proc Elect Power Appl 147(5

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

Automatic Classification of Winding Asymmetries in Wound Rotor Induction Motors based on Bicoherence and Fuzzy C-Means Algorithms of Stray Flux Signals

(c) 2021 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] Wound rotor induction motors are used in a certain number of industrial applications due to their interesting advantages, such as the possibility of inserting external rheostats in series with the rotor winding to enhance the torque characteristics under starting and to decrease the high inrush currents. However, the more complex structure of the rotor winding, compared to cage induction motors, is a source for potential maintenance problems. In this regard, several anomalies can lead to the occurrence of asymmetries in the rotor winding that may yield terrible repercussions for the machine¿s integrity. Therefore, monitoring the levels of asymmetry in the rotor winding is of paramount importance to ensure the correct operation of the motor. This work proposes the use of Bicoherence of the stray flux signal, as an indicator to obtain an automatic classification of the rotor winding condition. For this, the Fuzzy C-Means machine learning algorithm is used, which starts with the Bicoherence calculation and generates the different clusters for grouping and classification, according to the level of winding asymmetry. In addition, an analysis regarding the influence of the flux sensor position on the automatic classification and the failure detection is carried out. The results are highly satisfactory and prove the potential of the method for its future incorporation in autonomous condition monitoring systems that can be satisfactorily applied to determine the health of these machines.This work was supported in part by Generalitat Valenciana, Conselleria de Innovacion, Universidades, Ciencia y Sociedad Digital, (project AICO/019/224) and in part by MEC under Project MTM2016-75963-P.Iglesias Martínez, ME.; Antonino-Daviu, JA.; Fernández De Córdoba, P.; Conejero, JA.; Dunai, L. (2021). Automatic Classification of Winding Asymmetries in Wound Rotor Induction Motors based on Bicoherence and Fuzzy C-Means Algorithms of Stray Flux Signals. IEEE Transactions on Industry Applications. 57(6):5876-5886. https://doi.org/10.1109/TIA.2021.3108413S5876588657

Comparative Experimental Investigation of Broken Bar Fault Detectability in Induction Motors

[EN] It has been shown in the past that the zero-sequence current spectrum can be reliably used to detect broken bar faults in induction motors. Previous work was carried out with extensive FEM analysis. Although it allows detailed study of spatial and time-dependent electromagnetic characteristics of induction motors, FEM is a heavily time-consuming tool and this limits full study. So, in this work, extensive experimental testing has been performed to validate the zero sequence current spectrum for detecting rotor asymmetries. Three identical induction motors have been used: one healthy, one with a broken rotor bar, and one with two broken rotor bars. The motors were tested under different voltage supply levels and with different mechanical loads. The zero-sequence current spectrum was calculated after measuring the three phase currents. It is for the first time experimentally shown that this approach offers greater diagnostic potential than traditional MCSA.This work was supported in part by the U.K. Engineering and Physical Sciences Research Council funded FUTURE Vehicles project (EP/I038586/1).Gyftakis, KN.; Antonino-Daviu, J.; Garcia-Hernandez, R.; Mcculloch, MD.; Howey, DA.; Marques Cardoso, AJ. (2016). Comparative Experimental Investigation of Broken Bar Fault Detectability in Induction Motors. IEEE Transactions on Industry Applications. 52(2):1452-1459. doi:10.1109/TIA.2015.2505663S1452145952