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Journal articles on the topic 'Broken rotor bars'

Author: Grafiati

Published: 4 June 2021

Last updated: 3 February 2022

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1

Nemec, Mitja, Vanja Ambrožič, Rastko Fišer, David Nedeljković, and Klemen Drobnič. "Induction Motor Broken Rotor Bar Detection Based on Rotor Flux Angle Monitoring." Energies 12, no. 5 (February 27, 2019): 794. http://dx.doi.org/10.3390/en12050794.

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This paper presents a method for the detection of broken rotor bars in an induction motor. After introducing a simplified dynamic model of an induction motor with broken cage bars in a rotor field reference frame which allows for observation of its internal states, a fault detection algorithm is proposed. Two different motor estimation models are used, and the difference between their rotor flux angles is extracted. A particular frequency component in this signal appears only in the case of broken rotor bars. Consequently, the proposed algorithm is robust enough to load oscillations and/or machine temperature change, and also indicates the fault severity. The method has been verified at different operating points by simulations as well as experimentally. The fault detection is reliable even in cases where traditional methods give ambiguous verdicts.

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2

Seera, Manjeevan, Chee Peng Lim, and Dahaman Ishak. "Detection and Diagnosis of Broken Rotor Bars in Induction Motors Using the Fuzzy Min-Max Neural Network." International Journal of Natural Computing Research 3, no. 1 (January 2012): 44–55. http://dx.doi.org/10.4018/jncr.2012010104.

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In this paper, a fault detection and diagnosis system for induction motors using motor current signature analysis and the Fuzzy Min-Max (FMM) neural network is described. The finite element method is first employed to generate experimental data for predicting the changes in stator current signatures of an induction motor due to broken rotor bars. Then, a series real laboratory experiments is for broken rotor bars detection and diagnosis. The induction motor with broken rotor bars is operated under different load conditions. In all the experiments, the FMM network is used to learn and distinguish between normal and faulty states of the induction motor based on the input features extracted from the power spectral density. The experimental results positively demonstrate that the FMM network is useful for fault detection and diagnosis of broken rotor bars in induction motors.

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3

Kabul, Ahmet, and Abdurrahman Ünsal. "Detection of broken rotor bars of induction motors based on the combination of Hilbert envelope analysis and Shannon entropy." tm - Technisches Messen 88, no. 1 (January 1, 2021): 45–58. http://dx.doi.org/10.1515/teme-2020-0066.

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Abstract Broken rotor bar (BRB) is one of the most common fault types of induction motors. One of the common methods to detect the broken rotor bars is the observation of the characteristic sideband frequencies in the stator current. If the motor is lightly loaded, the sideband harmonics are attached to the fundamental frequency of the main supply and the amplitudes of these harmonics are quite low. Therefore, it is difficult to detect the broken rotor bars under light loading conditions by using conventional motor current signature analysis (MCSA) methods. Moreover, in some cases, the sideband harmonics of fundamental frequency may exist although there is no rotor fault in induction motors due to load oscillations. Therefore, there is a risk for false broken rotor bars alarm with the existence of lower amplitude of harmonics. This paper provides an alternative approach for the detection of broken rotor bars by applying Hilbert envelope analysis along with Shannon entropy to stator current signals. The proposed method includes two-stage evaluation system to eliminate false BRB alarms such as detecting sidebands from envelope spectrum and calculating entropy rates from envelope signals. The results are verified experimentally under 25 %, 50 %, 75 % and 100 % loading conditions.

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4

Baranov, Georgii D., Erivelton G. Nepomuceno, Michail A. Vaganov, Valerii Y. Ostrovskii, and Denis N. Butusov. "New Spectral Markers for Broken Bars Diagnostics in Induction Motors." Machines 8, no. 1 (January 28, 2020): 6. http://dx.doi.org/10.3390/machines8010006.

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The paper discusses the spectral markers of fault rotor bars in induction motor current signature analysis (MCSA). The results of the simulation of the deterioration process for a single rotor bar, as well as the results of research for various mutual bracing of two broken bars, are reported. We proposed a simple empiric technique allowing one to obtain frequencies for spectrum markers of damaged rotor bars based on simulation analysis. The set of frequencies obtained in the experimental part of the study was compared with simulation results and the results of real-life measurements. The theoretical results were verified through the experiment with the real induction motor under load. Analysis of experimental results proved that the given algorithm for spectrum analysis is suitable for early detection of fault rotor bars in induction motors.

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5

Pezzani, Carlos, Pablo Donolo, Guillermo Bossio, Marcos Donolo, Armando Guzman, and Stanley E. Zocholl. "Detecting Broken Rotor Bars With Zero-Setting Protection." IEEE Transactions on Industry Applications 50, no. 2 (March 2014): 1373–84. http://dx.doi.org/10.1109/tia.2013.2276116.

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6

Xie, Ying, Jinpeng Guo, Peng Chen, and Zhiwei Li. "Coupled Fluid-Thermal Analysis for Induction Motors with Broken Bars Operating under the Rated Load." Energies 11, no. 8 (August 3, 2018): 2024. http://dx.doi.org/10.3390/en11082024.

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Thermal stress of the rotor in a squirrel cage induction motor is generated due to the temperature rise, it is also one of the factors causing the broken bar fault because the structure of the rotor would be destroyed if the stress of the rotor bars exceed the strength limit. The coupled fluid-thermal analysis for the induction motor with healthy and broken bar rotors is performed in this paper. Much concern has been committed to establishment of the fluid model on the basis of computational fluid dynamic (CFD) theory. The heat field of the prototypes is analysed so that the effect of the asymmetrical rotor on the motor heat performance can be investigated in depth. Eventually, the efficiency of the presented model and method, for the totally enclosed fan cooled (TEFC) induction motor, can be verified through experimental results. In addition, this paper reports a quantitative analysis of the heat flux distribution of the fault rotor, and the heat flux density of the bars is investigated in detail. Then, the part most likely to break in the rotor as a result of the thermal load is identified.

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7

Valtierra-Rodriguez, Martin, Jesus R. Rivera-Guillen, Jesus A. Basurto-Hurtado, J. Jesus De-Santiago-Perez, David Granados-Lieberman, and Juan P. Amezquita-Sanchez. "Convolutional Neural Network and Motor Current Signature Analysis during the Transient State for Detection of Broken Rotor Bars in Induction Motors." Sensors 20, no. 13 (July 3, 2020): 3721. http://dx.doi.org/10.3390/s20133721.

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Although induction motors (IMs) are robust and reliable electrical machines, they can suffer different faults due to usual operating conditions such as abrupt changes in the mechanical load, voltage, and current power quality problems, as well as due to extended operating conditions. In the literature, different faults have been investigated; however, the broken rotor bar has become one of the most studied faults since the IM can operate with apparent normality but the consequences can be catastrophic if the fault is not detected in low-severity stages. In this work, a methodology based on convolutional neural networks (CNNs) for automatic detection of broken rotor bars by considering different severity levels is proposed. To exploit the capabilities of CNNs to carry out automatic image classification, the short-time Fourier transform-based time–frequency plane and the motor current signature analysis (MCSA) approach for current signals in the transient state are first used. In the experimentation, four IM conditions were considered: half-broken rotor bar, one broken rotor bar, two broken rotor bars, and a healthy rotor. The results demonstrate the effectiveness of the proposal, achieving 100% of accuracy in the diagnosis task for all the study cases.

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8

Xie, Ying, Ze Wang, Xueting Shan, and Yangyang Li. "Investigation of rotor thermal stress in squirrel cage induction motor with broken bar faults." COMPEL - The international journal for computation and mathematics in electrical and electronic engineering 35, no. 5 (September 5, 2016): 1865–86. http://dx.doi.org/10.1108/compel-10-2015-0372.

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Purpose Thermal stress of the rotor in a squirrel cage induction motor is generated due to the temperature rise, and the structure of the rotor will be destroyed if the stress acted on the rotor exceeds its limits, so the thermal stress is also one of the main causes led to broken bar fault. The purpose of this paper is to report the thermal stress coupled analysis for the induction motor with healthy and faulty rotor, and to find the variation tendency of the temperature and thermal stress due to broken bars, and the part most likely to break in the rotor as a result of the thermal stress load are identified. Design/methodology/approach The steady temperature and thermal stress of the rotor in the case of the healthy and faulty conditions are calculated by finite element method, and the 3D model of the motor used in the experiments is established and the experimental results are presented for both healthy and faulty machines. Findings The influence of the broken bars fault on the motor thermal profile and thermal stress can be found, and it explains why the breaking point always appears in the joint of the bars and end rings. Originality/value The paper presents the 3D thermal stress coupled model and performance characteristics of induction motor with broken bars. The reasonable constraint is established according to the contact of components each other, and more reasonable fracture location is selected. The results obtained by the simulation model are in a good agreement with practical situation, because the effect of skewed rotor were taken into consideration in the process of simulation.

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9

Vaimann, Toomas, Ants Kallaste, and Aleksander Kilk. "Sensorless Detection of Induction Motor Rotor Faults Using the Clarke Vector Approach." Scientific Journal of Riga Technical University. Power and Electrical Engineering 28, no. 1 (January 1, 2011): 43–48. http://dx.doi.org/10.2478/v10144-011-0007-9.

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Sensorless Detection of Induction Motor Rotor Faults Using the Clarke Vector ApproachDue to their rugged build, simplicity and cost effective performance, induction motors are used in a vast number of industries, where they play a significant role in responsible operations, where faults and downtimes are either not desirable or even unthinkable. As different faults can affect the performance of the induction motors, among them broken rotor bars, it is important to have a certain condition monitoring or diagnostic system that is guarding the state of the motor. This paper deals with induction motor broken rotor bars detection, using Clarke vector approach.

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10

Chouidira, Ibrahim, Djalal Eddine Khodja, and Hani Benguesmia. "Detection and Diagnosis faults in Machine asynchronous based on single processing." International Journal of Energetica 4, no. 1 (June 30, 2019): 11. http://dx.doi.org/10.47238/ijeca.v4i1.89.

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In this work, we proposed multi-winding model for the simulation of broken bars in squirrel cage asynchronous machine, this model allows to study the influence of the broken bar defects on the behavior general of machines in different operating conditions (healthy and faulty). The breaking of the most frequent bars of the rotor causes oscillations of the torque, speed, and the current, the increase of the resistance of the rotor creates the defects proportional with the number of breaks bar K .The diagnosis fault using technique of single processing based on Spectrum analysis for detection broken bar. The results of the simulation obtained allowed us to show the importance of this technique for detection broken bar.

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11

Dias, Cleber Gustavo, and Ivan Eduardo Chabu. "Analysis of broken rotor bars in large induction motors." Exacta 4, no. 2 (March 24, 2008): 407–16. http://dx.doi.org/10.5585/exacta.v4i2.775.

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12

En, De, Xiao Long Shi, Huang He Wei, Na Na Wei, and Chang Sheng Zhou. "Adaptive Filter with Multiple-Scale Decomposition Rotor Broken Bars in Induction Fault Diagnosis." Applied Mechanics and Materials 273 (January 2013): 428–33. http://dx.doi.org/10.4028/www.scientific.net/amm.273.428.

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There is a very small additional current component of frequency in the stator current signal when motor has broken rotor bars.So adaptive notch filter is applied to process the signals of the stator current in induction motors.The variable step size LMS algorithm and the multiple-scale wavelet transform are merged into the adaptive filtering system.A method is proposed, that is a LMS adaptive filtering algorithm with modified variable step size based on multiple-scale wavelet transform(MSWT-MVSS-LMS).It can eliminate interference from power frequency component to frequency component of broken rotor bar and achieve precise identification to frequency component of broken rotor bar from FFT.The result is a great help to extract the feature component of rotor fault and improve the sensitivity of fault diagnosis.The simulation show that the method is valid and effective.

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13

Dias, Cleber Gustavo, Luiz Carlos da da Silva, and Ivan Eduardo Chabu. "Fuzzy-Based Statistical Feature Extraction for Detecting Broken Rotor Bars in Line-Fed and Inverter-Fed Induction Motors." Energies 12, no. 12 (June 20, 2019): 2381. http://dx.doi.org/10.3390/en12122381.

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This paper presents the use of a fuzzy-based statistical feature extraction from the air gap disturbances for diagnosing broken rotor bars in large induction motors fed by line or an inverter. The method is based on the analysis of the magnetic flux density variation in a Hall Effect Sensor, installed between two stator slots of the motor. The proposed method combines a fuzzy inference system and a support vector machine technique for time-domain assessment of the magnetic flux density, in order to detect a single fault or multiple broken bars in the rotor. In this approach, it is possible to detect not only the existence of failures, but also its severity. Moreover, it is not necessary to estimate the slip of the motor, usually required by other methods and the damaged rotor detection was also evaluated for oscillating load conditions. Thus, the present approach can overcome some drawbacks of the traditional MCSA method, particularly in operational cases where false positive and false negative indications are more frequently. The efficiency of this approach has been proven using some computational simulation results and experimental tests to detect fully broken rotor bars in a 7.5 kW squirrel cage induction machine fed by line and an inverter.

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14

Guellout, O., A. Rezig, S. Touati, and A. Djerdir. "Elimination of broken rotor bars false indications in induction machines." Mathematics and Computers in Simulation 167 (January 2020): 250–66. http://dx.doi.org/10.1016/j.matcom.2019.06.010.

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15

Kliman, G. B., R. A. Koegl, J. Stein, R. D. Endicott, and M. W. Madden. "Noninvasive detection of broken rotor bars in operating induction motors." IEEE Transactions on Energy Conversion 3, no. 4 (1988): 873–79. http://dx.doi.org/10.1109/60.9364.

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16

Climente-Alarcon, Vicente, Jose A. Antonino-Daviu, Francisco Vedreno-Santos, and Ruben Puche-Panadero. "Vibration Transient Detection of Broken Rotor Bars by PSH Sidebands." IEEE Transactions on Industry Applications 49, no. 6 (November 2013): 2576–82. http://dx.doi.org/10.1109/tia.2013.2265872.

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17

Lv, Feng, Hao Sun, Wen Xia Du, and Shue Li. "Fault Signature Analysis Based on Transient Current for Induction Motors." Applied Mechanics and Materials 44-47 (December 2010): 1807–11. http://dx.doi.org/10.4028/www.scientific.net/amm.44-47.1807.

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The characteristics of broken rotor bars in induction motors are reflected in the abnormal harmonic of the stator current. At present, fast Fourier transform( ) and time-varying frequency spectrum analysis method are used in such fault diagnosis, but non-stationary motors operation can bring a certain difficulties to the monitoring and diagnosis. This paper studies the basic characteristics of wavelet transform, adopting the wavelet analysis technologies of signal processing and selecting mother wavelet, the paper makes the multi-scale transformation to the motor starting current, excavates the harmonic informations on non-stationary condition, realizes fault diagnosis of motor broken rotor bars effectively, The consistent diagnostic results prove the effectiveness of the method.

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18

Kathir, I., S. Balakrishnan, and B. V. Manikandan. "Broken Rotor Bar Detection Using High Frequency Loss Calculation of Induction Motor." Applied Mechanics and Materials 573 (June 2014): 728–33. http://dx.doi.org/10.4028/www.scientific.net/amm.573.728.

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This paper proposes a technique for the identification of defects of three-phase squirrel cage induction motors. Simulations were performed using ANSYS finite element software package to obtain the flux density waveform in the air gap. Broken rotor bar fault was simulated by breaking rotor bars to see how the flux density is affected. In this paper, a new approach for the identification of broken rotor bar based on the calculation of high-frequency losses in induction motors is presented. The approach presented in this paper requires little time for loss calculation and fault identification.

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19

Abdi Monfared, Omid, Aref Doroudi, and Amin Darvishi. "Diagnosis of rotor broken bars faults in squirrel cage induction motor using continuous wavelet transform." COMPEL - The international journal for computation and mathematics in electrical and electronic engineering 38, no. 1 (January 7, 2019): 167–82. http://dx.doi.org/10.1108/compel-11-2017-0487.

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Purpose Squirrel cage induction motors suffer from several faults such as rotor broken bar. One of the powerful methods to detect induction motor faults is the line current signature analysis. This paper aims to present a novel algorithm based on continuous wavelet transform (CWT) to diagnose a rotor broken bar fault. Design/methodology/approach The proposed CWT has high flexibility in monitoring any frequency of interest in a waveform. Based on this transform, stator current frequency spectrum is analyzed to diagnose the rotor broken bar fault. The algorithm distinguishes the healthy motor from the faulted one based on a proper index. The method can be used in steady-state running time of induction motor and under different loading conditions. Experimental results are presented to show the validity of the proposed approach. Findings The proposed index considerably increases at the broken bars conditions compared to the healthy conditions. It can clearly diagnose the faulty conditions. The experimental results are found to be in good agreement with the theoretical and simulated results. The proposed method can reduce the noise and spectral leakage effects. Originality/value The main contribution of the paper are as follows: using CWT for detection of broken bar faults; introducing a proper index for diagnosing broken bars; and introducing a supplementary index to reduce the noise and spectral leakage effects.

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20

Li, Yong Xin, Ya Fei Wang, Xing Lai Ge, and Yang Lu. "Characteristic Performance Analysis of Traction Motor on EMU with Broken Bars Using FEM." Advanced Materials Research 1061-1062 (December 2014): 841–48. http://dx.doi.org/10.4028/www.scientific.net/amr.1061-1062.841.

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The calculation model of motor operating on asymmetric rotor was defined taking a traction squirrel-cage induction motor in Electric Multiple Units (EMU) as sample. Based on the basic principle of numerical analysis, magnetic field in the motor and current in the bar were calculated for both normal motor and broken-bar motor by using the Jmag software, and both the magnetic field variation and current variation in the bar were summed up. According to the EMU’s special control methods, the motor with two broken bars was simulated at different work point, and the characteristic component variation was presented. The works in this paper lay the foundation of diagnosis method for broken rotor bar fault, especially for traction motor in EMU.

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21

Eltabach, Mario, Jerome Antoni, Galyna Shanina, Sophie Sieg-Zieba, and Xavier Carniel. "Broken rotor bars detection by a new non-invasive diagnostic procedure." Mechanical Systems and Signal Processing 23, no. 4 (May 2009): 1398–412. http://dx.doi.org/10.1016/j.ymssp.2008.08.016.

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22

Bensaoucha, Saddam, Sid Ahmed Bessedik, Aissa Ameur, and Ali Teta. "Induction motors broken rotor bars detection using RPVM and neural network." COMPEL - The international journal for computation and mathematics in electrical and electronic engineering 38, no. 2 (March 4, 2019): 596–615. http://dx.doi.org/10.1108/compel-06-2018-0256.

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Purpose The purpose of this study aims to focus on the detection and identification of the broken rotor bars (BRBs) of a squirrel cage induction motor (SCIM). The presented diagnosis technique is based on artificial neural networks (NNs) that use as inputs the results of the spectral analysis using the fast Fourier transform (FFT) of the reduced Park’s vector modulus (RPVM), along with the load values in which the motor operates. Design/methodology/approach First, this paper presents a comparative study between FFT applied on Hilbert modulus, Park’s vector modulus and RPVM to extract feature frequencies of BRB faults. Moreover, the extracted features of FFT applied to RPVM and the load values were selected as NNs’ inputs for the detection of the number of BRBs. Findings The obtained simulation results using MATLAB (Matrix Laboratory) environment show the effectiveness and accuracy of the proposed NNs based approach. Originality/value The current paper presents a novel diagnostic method for BRBs’ fault detection in SCIM, based on the combination between the signal processing analysis (FFT of RPVM) and artificial intelligence (NNs).

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23

Faiz, Jawad, and B. M. Ebrahimi. "Locating rotor broken bars in induction motors using finite element method." Energy Conversion and Management 50, no. 1 (January 2009): 125–31. http://dx.doi.org/10.1016/j.enconman.2008.08.025.

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24

Laala, Widad, Salah-Eddine Zouzou, and Salim Guedidi. "Induction motor broken rotor bars detection using fuzzy logic: experimental research." International Journal of System Assurance Engineering and Management 5, no. 3 (June 18, 2013): 329–36. http://dx.doi.org/10.1007/s13198-013-0171-8.

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25

Sinha, Ashish Kumar, Ananda Shankar Hati, Mohamed Benbouzid, and Prasun Chakrabarti. "ANN-Based Pattern Recognition for Induction Motor Broken Rotor Bar Monitoring under Supply Frequency Regulation." Machines 9, no. 5 (April 27, 2021): 87. http://dx.doi.org/10.3390/machines9050087.

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The requisite of direct-on-line (DOL) starting for various applications in underground mines subjects the rotor bars of heavy-duty squirrel cage induction motors (SCIMs) to severe stresses, resulting in sustained fault in the rotor bars, unlike the applications where mostly reduced voltage starting is preferred. Furthermore, SCIMs working in underground mines are also affected by unforeseen frequency fluctuations. Hence, the paper proposes a discrete wavelet transform (DWT)-based broken rotor bar detection scheme using the stator current analysis of SCIM when subjected to a frequency regulation (±4% of 50 Hz supply) in steady-state, as prevalent in underground mines. In this regard, the level-seven detailed coefficient obtained by the DWT-based multi-resolution analysis of stator current corresponding to the healthy rotor is compared with that of the faulty rotor to extract the necessary features to identify the fault. Further implementation of the proposed scheme is done using artificial neural network (ANN)-based pattern recognition techniques, wherein both feed-forward backdrops and cascaded forward backdrop type ANNs have been used for fault pinpointing based on the feature extraction results obtained from DWT. The scheme is developed and analysed in MATLAB/Simulink using 5.5 kW, 415 V, 50 Hz SCIM, which is further validated using the LabVIEW-based real-time implementation.

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26

Kim, Jongbaeg, and Michael D. Bryant. "Bond Graph Model of a Squirrel Cage Induction Motor With Direct Physical Correspondence." Journal of Dynamic Systems, Measurement, and Control 122, no. 3 (January 4, 2000): 461–69. http://dx.doi.org/10.1115/1.1286600.

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An existing bond graph of a squirrel cage induction motor was modified to make the bond graph physically more representative. The intent was to form a one-to-one correspondence between motor components and bond graph elements. Components explicitly represented include the stator coils, the squirrel cage rotor bars, and the magnetic flux routing section. The final bond graph spans electrical, magnetic, and mechanical energy domains, and contains common motor faults. From this bond graph. state equations were extracted and simulations performed. Simulated were the response of healthy motors, and motors with shorted stator coils and broken rotor bars. [S0022-0434(00)01203-X]

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27

Asad, Bilal, Toomas Vaimann, Ants Kallaste, Anton Rassõlkin, Anouar Belahcen, and M. Naveed Iqbal. "Improving Legibility of Motor Current Spectrum for Broken Rotor Bars Fault Diagnostics." Electrical, Control and Communication Engineering 15, no. 1 (September 1, 2019): 1–8. http://dx.doi.org/10.2478/ecce-2019-0001.

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AbstractIn this paper, the harmonic contribution of the broken rotor bar of an induction machine is investigated using an effective combination of the fast Fourier transform (FFT) and a band stop filter. The winding, spatial, grid fed and fault-based harmonics are investigated. Since the fundamental component is the most powerful component as compared to the other frequencies, it decreases the legibility of spectrum, making logarithmic scale inevitable. It also remains a potential threat of burying the fault representative side band frequencies because of its spectral leakage. In this paper, a band stop Chebyshev filter is used to attenuate the fundamental component, which makes the spectrum clearer and easier to understand even on the linear scale. Its good transition band and low passband ripples make it suitable for attenuating the main supply frequency with low impact on the neighbouring side band frequencies. To study the impact of fault on magnetic flux distribution, simulation is done using finite element method with good number of mesh elements and very small step size. The line current is calculated and frequency spectrum is investigated to segregate the spatial and fault frequencies using the proposed technique. The results are further validated by implementing the algorithm on the data measured in the laboratory environment including the grid fed harmonics.

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28

Camarena-Martinez, David, Carlos Andres Perez-Ramirez, Martin Valtierra-Rodriguez, Juan Pablo Amezquita-Sanchez, and Rene de Jesus Romero-Troncoso. "Synchrosqueezing transform-based methodology for broken rotor bars detection in induction motors." Measurement 90 (August 2016): 519–25. http://dx.doi.org/10.1016/j.measurement.2016.05.010.

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29

B. M. Saied, Prof, Dr Y. M.Y. Ameen, and M. H. Saud. "Broken Rotor Bars Fault Detection of The Three-phase Induction Motor(Arabic)." AL-Rafdain Engineering Journal (AREJ) 20, no. 5 (October 28, 2012): 25–32. http://dx.doi.org/10.33899/rengj.2012.61020.

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30

Elkasabgy, N. M., A. R. Eastham, and G. E. Dawson. "Detection of broken bars in the cage rotor on an induction machine." IEEE Transactions on Industry Applications 28, no. 1 (1992): 165–71. http://dx.doi.org/10.1109/28.120226.

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31

Cupertino, F., E. deVanna, L. Salvatore, and S. Stasi. "Analysis Techniques for Detection of IM Broken Rotor Bars After Supply Disconnection." IEEE Transactions on Industry Applications 40, no. 2 (March 2004): 526–33. http://dx.doi.org/10.1109/tia.2004.824432.

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32

Penman, J., and A. Stavrou. "Broken rotor bars: their effect on the transient performance of induction machines." IEE Proceedings - Electric Power Applications 143, no. 6 (1996): 449. http://dx.doi.org/10.1049/ip-epa:19960777.

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33

Karami, Farzaneh, Javad Poshtan, and Majid Poshtan. "Detection of broken rotor bars in induction motors using nonlinear Kalman filters." ISA Transactions 49, no. 2 (April 2010): 189–95. http://dx.doi.org/10.1016/j.isatra.2009.11.005.

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34

An, Guoqing, and Hongru Li. "Stator and Rotor Faults Diagnosis of Squirrel Cage Motor Based on Fundamental Component Extraction Method." International Journal of Rotating Machinery 2017 (2017): 1–8. http://dx.doi.org/10.1155/2017/1576381.

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Nowadays, stator current analysis used for detecting the incipient fault in squirrel cage motor has received much attention. However, in the case of interturn short circuit in stator, the traditional symmetrical component method has lost the precondition due to the harmonics and noise; the negative sequence component (NSC) is hard to be obtained accurately. For broken rotor bars, the new added fault feature blanked by fundamental component is also difficult to be discriminated in the current spectrum. To solve the above problems, a fundamental component extraction (FCE) method is proposed in this paper. On one hand, via the antisynchronous speed coordinate (ASC) transformation, NSC of extracted signals is transformed into the DC value. The amplitude of synthetic vector of NSC is used to evaluate the severity of stator fault. On the other hand, the extracted fundamental component can be filtered out to make the rotor fault feature emerge from the stator current spectrum. Experiment results indicate that this method is feasible and effective in both interturn short circuit and broken rotor bars fault diagnosis. Furthermore, only stator currents and voltage frequency are needed to be recorded, and this method is easy to implement.

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35

Mesbeh, Amina, Marwen Jarboui, and Ahmed Masmoudi. "Broken bar and end-ring faults: analysis of their effects on the rotor cage currents." COMPEL: The International Journal for Computation and Mathematics in Electrical and Electronic Engineering 34, no. 6 (November 2, 2015): 1771–95. http://dx.doi.org/10.1108/compel-06-2015-0222.

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Purpose – The purpose of this paper is to investigate the effects of different faulty scenarios on the induction motor (IM) operation with emphasis on the currents in the rotor bar and end rings. Design/methodology/approach – The modeling of the IM followed by a graphical representation-based analysis of the rotor steady-state currents under healthy operation is treated. Then, a case study is considered in order to investigate different faulty scenarios with a focus on the rotor cage currents. Findings – It has been found that the rotor faults greatly affect the currents in the bars and in the end rings both in amplitude and in harmonic content. These vary according to the relative positions with respect to the fault such that: the currents in the bars adjacent to the faulty one(s) have the highest amplitudes with the lowest harmonic content; and the ones in the ring portions adjacent to the faulty one have the lowest amplitudes with the highest harmonic content. Research limitations/implications – Although the simulated model has confirmed the well known IM behavior under healthy operation, it would be appreciated if the obtained results under faulty operation would be validated by finite element analysis. Practical implications – It is of great interest to investigate the effects of faulty scenarios on the rotor cage currents, in order to take appropriate actions starting from the design of the IM. Originality/value – A deep investigation (including the waveforms, the phasor diagrams and the harmonic content) of the effects of different faulty scenarios on the IM rotor cage currents represents the major contribution of this work.

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36

Zhao, Zhike, Xin Wang, and Xiaoguang Zhang. "Fault Diagnosis of Broken Rotor Bars in Squirrel-Cage Induction Motor of Hoister Based on Duffing Oscillator and Multifractal Dimension." Advances in Mechanical Engineering 6 (January 1, 2014): 849670. http://dx.doi.org/10.1155/2014/849670.

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This paper is to propose a novel fault diagnosis method for broken rotor bars in squirrel-cage induction motor of hoister, which is based on duffing oscillator and multifractal dimension. Firstly, based on the analysis of the structure and performance of modified duffing oscillator, the end of transitional slope from chaotic area to large-scale cycle area is selected as the optimal critical threshold of duffing oscillator by bifurcation diagrams and Lyapunov exponent. Secondly, the phase transformation duffing oscillator from chaos to intermittent chaos is sensitive to the signals, whose frequency difference is quite weak from the reference signal. The spectrums of the largest Lyapunov exponents and bifurcation diagrams of the duffing oscillator are utilized to analyze the variance in different parameters of frequency. Finally, this paper is to analyze the characteristics of both single fractal (box-counting dimension) and multifractal and make a comparison between them. Multifractal detrended fluctuation analysis is applied to detect extra frequency component of current signal. Experimental results reveal that the method is effective for early detection of broken rotor bars in squirrel-cage induction motor of hoister.

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37

Samir, Hamdani, Touhami Omar, and Ibtiouen Rachid. "Generalized two axes model of a squirrel-cage induction motor for rotor fault diagnosis." Serbian Journal of Electrical Engineering 5, no. 1 (2008): 155–70. http://dx.doi.org/10.2298/sjee0801155s.

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A generalized two axes model of a squirrel-cage induction motor is developed This model is based on a winding function approach and the coupled magnetic circuit theory and takes into account the stator and the rotor asymmetries due to faults. This paper presents a computer simulation and experimental dynamic characteristics for a healthy induction machine, machine with one broken bar and a machine with two broken bars. The results illustrate good agreement between both simulated and experimental results. Also, the power spectral density PSD was performed to obtain a stator current spectrum.

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38

Boqiang Xu, Liling Sun, and Hui Ren. "A New Criterion for the Quantification of Broken Rotor Bars in Induction Motors." IEEE Transactions on Energy Conversion 25, no. 1 (March 2010): 100–106. http://dx.doi.org/10.1109/tec.2009.2032626.

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39

Aydin, Ilhan, Mehmet Karakose, and Erhan Akin. "A new method for early fault detection and diagnosis of broken rotor bars." Energy Conversion and Management 52, no. 4 (April 2011): 1790–99. http://dx.doi.org/10.1016/j.enconman.2010.11.018.

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40

Cho, K. R., J. H. Lang, and S. D. Umans. "Detection of broken rotor bars in induction motors using state and parameter estimation." IEEE Transactions on Industry Applications 28, no. 3 (1992): 702–9. http://dx.doi.org/10.1109/28.137460.

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41

Zhengping Zhang, Zhen Ren, and Wenying Huang. "A novel detection method of motor broken rotor bars based on wavelet ridge." IEEE Transactions on Energy Conversion 18, no. 3 (September 2003): 417–23. http://dx.doi.org/10.1109/tec.2003.815851.

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42

Guedidi, S., S. E. Zouzou, W. Laala, K. Yahia, and M. Sahraoui. "Induction motors broken rotor bars detection using MCSA and neural network: experimental research." International Journal of System Assurance Engineering and Management 4, no. 2 (March 13, 2013): 173–81. http://dx.doi.org/10.1007/s13198-013-0149-6.

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43

García-Escudero, Luis A., Oscar Duque-Perez, Daniel Morinigo-Sotelo, and Marcelo Perez-Alonso. "Robust condition monitoring for early detection of broken rotor bars in induction motors." Expert Systems with Applications 38, no. 3 (March 2011): 2653–60. http://dx.doi.org/10.1016/j.eswa.2010.08.055.

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44

Mustafa, Mohammed Obaid, Damiano Varagnolo, George Nikolakopoulos, and Thomas Gustafsson. "Detecting broken rotor bars in induction motors with model-based support vector classifiers." Control Engineering Practice 52 (July 2016): 15–23. http://dx.doi.org/10.1016/j.conengprac.2016.03.019.

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45

Fernandez-Cavero, Vanessa, Joan Pons-Llinares, Oscar Duque-Perez, and Daniel Morinigo-Sotelo. "Detection of Broken Rotor Bars in Nonlinear Startups of Inverter-Fed Induction Motors." IEEE Transactions on Industry Applications 57, no. 3 (May 2021): 2559–68. http://dx.doi.org/10.1109/tia.2021.3066317.

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46

Chen, Jiageng, Niaoqing Hu, Lun Zhang, Ling Chen, Bozheng Wang, and Yang Zhou. "A Method for Broken Rotor Bars Diagnosis Based on Sum-Of-Squares of Current Signals." Applied Sciences 10, no. 17 (August 29, 2020): 5980. http://dx.doi.org/10.3390/app10175980.

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Induction motors are mainstay power components in industrial equipment. Fault diagnosis technology of induction motors can detect the incipient fault and avoid the unplanned shutdown. The broken rotor bar is a significant fault mode of induction motors. Classical fault diagnosis methods always have complex principles and high computational costs, which leads to difficulties in understanding and calculation. In this paper, a method of broken rotor bar diagnosis based on the sum-of-squares of current signals is proposed. This method can eliminate the fundamental frequency and extract the signature frequency components by calculating the sum-of-squares of three-phase current signals. The signature frequency components are more apparent in the spectrum of the sum-of-squares of current signals. The effectiveness of the proposed method under different load levels and rotation motor speeds has been validated by two experiments. Compared with the classical diagnostic methods, the proposed method has better effectiveness and lower computation cost.

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47

Rayyam, Marouane, and Malika Zazi. "A novel metaheuristic model-based approach for accurate online broken bar fault diagnosis in induction motor using unscented Kalman filter and ant lion optimizer." Transactions of the Institute of Measurement and Control 42, no. 8 (December 30, 2019): 1537–46. http://dx.doi.org/10.1177/0142331219892142.

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This paper introduces a novel metaheuristic model-based scheme for fault monitoring in squirrel cage induction motors (SCIMs). This method relies on the combination of the ant lion optimizer (ALO) and the unscented Kalman filter (UKF) to detect and quantify the number of broken bars. Contrary to the UKF-based fault diagnosis, the improved ALO-UKF algorithm tunes optimally and automatically the noise covariance matrices Q and R, which reduces the estimation errors, and then obtains an effective and accurate fault diagnosis. Firstly, a mathematical model of the fault under study has been developed based on rotor parameter value as signature. Secondly, a sixth order ALO-UKF algorithm has been synthesized for simultaneous estimation of rotor resistance and speed. Several broken bar fault conditions have been simulated. Simulation results show the effectiveness and robustness of the proposed ALO-UKF scheme in broken bar detection and identification, and exhibit a more superior performance than the simple-UKF and EKF algorithms in term of stability, accuracy and response time.

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48

Tang, Jing, Jie Chen, Kan Dong, Yongheng Yang, Haichen Lv, and Zhigang Liu. "Modeling and Evaluation of Stator and Rotor Faults for Induction Motors." Energies 13, no. 1 (December 26, 2019): 133. http://dx.doi.org/10.3390/en13010133.

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The modeling of stator and rotor faults is the basis of the development of online monitoring techniques. To obtain reliable stator and rotor fault models, this paper focuses on dynamic modeling of the stator and rotor faults in real-time, which adopts a multiple-coupled-circuit method by using a winding function approach for inductance calculation. Firstly, the model of the induction machine with a healthy cage is introduced, where a rotor mesh that consists of a few rotor loops and an end ring loop is considered. Then, the stator inter-turn fault model is presented by adding an extra branch with short circuit resistance on the fault part of a stator phase winding. The broken rotor bar fault is then detailed by merging and removing the broken-bar-related loops. Finally, the discrete models under healthy and faulty conditions are developed by using the Tustin transformation for digital implementation. Moreover, the stator and rotor mutual inductances are derived as a function of the rotor position according to the turn and winding functions distribution. Simulations and experiments are performed on a 2.2-kW/380-V/50-Hz three-phase and four-pole induction motor to show the performance of the stator and rotor faults, where the saturation effect is considered in simulations by exploiting the measurements of a no load test. The simulation results are in close agreement with the experimental results. Furthermore, magnitudes of the characteristic frequencies of 2f1 in torque and (1 ± 2s)f1 in current are analyzed to evaluate the stator and rotor fault severity. Both indicate that the stator fault severity is related to the short circuit resistance. Further, the number of shorted turns and the number of continuous broken bars determines the rotor fault severity.

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Hou, Xin Guo, and Fan Bu. "The Motor Rotor Fault Diagnosis Method Based on Linear Mixing Blind Separation Model." Applied Mechanics and Materials 602-605 (August 2014): 2420–25. http://dx.doi.org/10.4028/www.scientific.net/amm.602-605.2420.

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The detection precision of fault diagnosis based on frequency spectral analysis of stator current is easily restricted by noise jamming and frequency resolution. A fault diagnosis method for induction motor based on linear mixing model is proposed to resolve this problem. The fault characteristic signals are separated from the motor stator current by Fast-ICA algorithm and its amplitude is calculated according to the estimated mixing matrix. The fault diagnosis is achieved by difference of the amplitude on the normal state and the fault state of the motor. In this paper, the fault diagnosis of the broken rotor bars faults is used as an example to explain the conclusion as mentioned. Experiment result shows that the broken-rotor-bar fault can be diagnosed by the algorithm with better effect on the condition of short data block.

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50

Misra, Rajul, and G. L. Pahuja. "Fuzzy Logic Based Rotor Health Index of Induction Motor." International Journal of Emerging Electric Power Systems 16, no. 5 (October 1, 2015): 443–49. http://dx.doi.org/10.1515/ijeeps-2015-0032.

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Abstract This paper presents an experimental study on detection and diagnosis of broken rotor bars in Squirrel Cage Induction Motor (SQIM). The proposed scheme is based on Motor Current Signature Analysis (MCSA) which uses amplitude difference of supply frequency to upper and lower side bands. Initially traditional MCSA has been used for rotor fault detection. It provides rotor health index on full load conditions. However in real practice if a fault occurs motor can not run at full load. To overcome the issue of reduced load condition a Fuzzy Logic based MCSA has been designed, implemented, tested and compared with traditional MCSA. A simulation result shows that proposed scheme is not only capable of detecting the severity of rotor fault but also provides remarkable performance at reduced load conditions.

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