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Relevant bibliographies by topics / Broken rotor bars

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Academic literature on the topic 'Broken rotor bars'

Author: Grafiati

Published: 4 June 2021

Last updated: 3 February 2022

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Journal articles on the topic "Broken rotor bars"

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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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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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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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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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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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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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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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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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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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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Dissertations / Theses on the topic "Broken rotor bars"

1

Cho, Kyong Rae. "Detection of broken rotor bars in induction motors using parameter and state estimation." Thesis, Massachusetts Institute of Technology, 1989. http://hdl.handle.net/1721.1/14343.

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Dias, Cleber Gustavo. "Proposta de um novo método para a detecção de barras rompidas em motores de indução com rotor em gaiola." Universidade de São Paulo, 2006. http://www.teses.usp.br/teses/disponiveis/3/3143/tde-15092006-165225/.

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O estudo das condições de operação de um motor de indução em um ambiente industrial é indispensável, tendo em vista que eventuais problemas podem contribuir para um prejuízo na produção, ou ainda para custos adicionais relacionados à falta de manutenção dos equipamentos. Uma das principais falhas que podem ocorrer em um motor de indução do tipo gaiola de esquilo durante sua operação é o rompimento de uma ou mais barras que compõem o seu rotor. Apresenta-se neste trabalho um novo método para auxiliar na detecção de barras quebradas em um rotor tipo gaiola de esquilo, para um motor de grande porte, durante sua operação em regime permanente. A partir de um modelo matemático foi possível avaliar o rompimento de barras do rotor, detectando em uma posição específica, a variação da densidade de fluxo magnético resultante, produzida pela contribuição do fluxo de dispersão de cada barra do rotor, bem como pelo fluxo criado pelas correntes do estator. Um sensor de efeito Hall é instalado entre duas bobinas do estator, a fim de representar a posição onde é realizado o cálculo da densidade de fluxo magnético resultante pela modelagem matemática proposta. O sinal gerado pelo sensor a partir de uma falha é comparado com aquele obtido a partir do rotor saudável, para posterior análise. O trabalho sugere ainda a aplicação do método de detecção da falha em conjunto com uma técnica de inteligência artificial baseada nas redes neurais artificiais, a fim de contribuir para o diagnóstico da falha e estimativa do número de barras rompidas. Os resultados obtidos da simulação, bem como os dados obtidos durante o ensaio são apresentados e usados na validação do modelo matemático desenvolvido.
The study of operational conditions of an induction motor in an industrial environment is indispensable, once eventual problems can contribute for production losses, or still for additional costs related to the lack of equipments maintenance. Among the principal faults, in a squirrel cage induction motor can occur the breaking of one or more rotor bars. This work presents a new method in aid of detection of broken bars in a large squirrel cage induction motor during its operation in steady-state. A mathematical model is used to evaluate the broken rotor bars, detecting in a specific point, the resulting magnetic flux density produced by the leakage flux created by the rotor and stator currents. The Hall effect sensor is installed between two stator coils, in order to represent the position where the resulting magnetic flux density is calculated by the proposed mathematical model. The signal detected in the sensor during a fault, is compared to the obtained result of the magnetic flux density from a healthy rotor for analysis. The work still suggests the application of the artificial intelligence technique, based on artificial neural networks in the mathematical model, in order to aid on the fault detection and estimate of the number of broken bars. The simulation and experimental results are presented in order to validate the developed mathematical model.

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Vedreño, Santos Francisco Jose. "Diagnosis of electric induction machines in non-stationary regimes working in randomly changing conditions." Doctoral thesis, Universitat Politècnica de València, 2013. http://hdl.handle.net/10251/34177.

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Tradicionalmente, la detección de faltas en máquinas eléctricas se basa en el uso de la Transformada Rápida de Fourier ya que la mayoría de las faltas pueden ser diagnosticadas con ella con seguridad si las máquinas operan en condiciones de régimen estacionario durante un intervalo de tiempo razonable. Sin embargo, para aplicaciones en las que las máquinas operan en condiciones de carga y velocidad fluctuantes (condiciones no estacionarias) como por ejemplo los aerogeneradores, el uso de la Transformada Rápida de Fourier debe ser reemplazado por otras técnicas. La presente tesis desarrolla una nueva metodología para el diagnóstico de máquinas de inducción de rotor de jaula y rotor bobinado operando en condiciones no estacionarias, basada en el análisis de las componentes de falta de las corrientes en el plano deslizamiento frecuencia. La técnica es aplicada al diagnóstico de asimetrías estatóricas, rotóricas y también para la falta de excentricidad mixta. El diagnóstico de las máquinas eléctricas en el dominio deslizamiento-frecuencia confiere un carácter universal a la metodología ya que puede diagnosticar máquinas eléctricas independientemente de sus características, del modo en el que la velocidad de la máquina varía y de su modo de funcionamiento (motor o generador). El desarrollo de la metodología conlleva las siguientes etapas: (i) Caracterización de las evoluciones de las componentes de falta de asimetría estatórica, rotórica y excentricidad mixta para las máquinas de inducción de rotores de jaula y bobinados en función de la velocidad (deslizamiento) y la frecuencia de alimentación de la red a la que está conectada la máquina. (ii) Debido a la importancia del procesado de la señal, se realiza una introducción a los conceptos básicos del procesado de señal antes de centrarse en las técnicas actuales de procesado de señal para el diagnóstico de máquinas eléctricas. (iii) La extracción de las componentes de falta se lleva a cabo a través de tres técnicas de filtrado diferentes: filtros basados en la Transformada Discreta Wavelet, en la Transformada Wavelet Packet y con una nueva técnica de filtrado propuesta en esta tesis, el Filtrado Espectral. Las dos primeras técnicas de filtrado extraen las componentes de falta en el dominio del tiempo mientras que la nueva técnica de filtrado realiza la extracción en el dominio de la frecuencia. (iv) La extracción de las componentes de falta, en algunos casos, conlleva el desplazamiento de la frecuencia de las componentes de falta. El desplazamiento de la frecuencia se realiza a través de dos técnicas: el Teorema del Desplazamiento de la Frecuencia y la Transformada Hilbert. (v) A diferencia de otras técnicas ya desarrolladas, la metodología propuesta no se basa exclusivamente en el cálculo de la energía de la componente de falta sino que también estudia la evolución de la frecuencia instantánea de ellas, calculándola a través de dos técnicas diferentes (la Transformada Hilbert y el operador Teager-Kaiser), frente al deslizamiento. La representación de la frecuencia instantánea frente al deslizamiento elimina la posibilidad de diagnósticos falsos positivos mejorando la precisión y la calidad del diagnóstico. Además, la representación de la frecuencia instantánea frente al deslizamiento permite realizar diagnósticos cualitativos que son rápidos y requieren bajos requisitos computacionales. (vi) Finalmente, debido a la importancia de la automatización de los procesos industriales y para evitar la posible divergencia presente en el diagnóstico cualitativo, tres parámetros objetivos de diagnóstico son desarrollados: el parámetro de la energía, el coeficiente de similitud y los parámetros de regresión. El parámetro de la energía cuantifica la severidad de la falta según su valor y es calculado en el dominio del tiempo y en el dominio de la frecuencia (consecuencia de la extracción de las componentes de falta en el dominio de la frecuencia). El coeficiente de similitud y los parámetros de regresión son parámetros objetivos que permiten descartar diagnósticos falsos positivos aumentando la robustez de la metodología propuesta. La metodología de diagnóstico propuesta se valida experimentalmente para las faltas de asimetría estatórica y rotórica y para el fallo de excentricidad mixta en máquinas de inducción de rotor de jaula y rotor bobinado alimentadas desde la red eléctrica y desde convertidores de frecuencia en condiciones no estacionarias estocásticas.
Vedreño Santos, FJ. (2013). Diagnosis of electric induction machines in non-stationary regimes working in randomly changing conditions [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/34177
TESIS

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Lee, Ming-Yuan, and 李明遠. "A New Way to Detect Broken Rotor Bars of Induction Motors." Thesis, 2015. http://ndltd.ncl.edu.tw/handle/pjr4aq.

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碩士
國立高雄應用科技大學
電機工程系博碩士班
103
Motor invention has so far hundreds of years, are generally used in each industry, although today the advancement of technology, testing equipment constantly, but for this part of the copper squirrel cage rotor, the industry is still using the traditional maintenance mode. In order to change the past mode of operation, the use of digital technology to replace it. To plant five high-voltage squirrel cage motor experiment to measure all of the rotor slot conductor caused by the sense coil voltage magnitude, calculated the average and the lowest percentage of induced voltage, the rotor bar quality and reliability of digital indicators. From the experimental results that the detector can improve the reliability of the rotor fault detection, reducing the chances of the occurrence of sudden failure of the on-line, and indirectly reduce production costs, significant potential benefits.

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Welsh, Mark Steven. "Detection of broken rotor bars in induction motors using stator current measurements." Thesis, 1988. http://hdl.handle.net/10945/23014.

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This work proved the feasibility of an interferometric, high pressure sensor. A pressure measurement system based on a birefringent, compact, Fabry-Perot etalon was selected and designed. The temperature response of the reflectivity of the etalon was calibrated; a 1 C change in temperature was equivalent to a 1000 psi pressure change. Efficient coupling of the key components was demonstrated using a monolithic, single-frequency, diode-pumped ring laser (developed at Lightwave Electronics Corp. based on Stanford University research), a single-mode optical fiber, and a sapphire etalon. Successful experimental results demonstrated that an optical pressure transducer can be made that has the properties of compactness, wide pressure range, immunity to electro-magnetic interference, and low cost. Keywords: Pressure measurement, Fiber optics, Lasers, Etalon. (JHD)

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Dhuness, Kahesh. "An investigation into aspects of the online detection of broken rotor bars in induction motors." Thesis, 2008. http://hdl.handle.net/10210/411.

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Recent failures of large induction machines due to rotor bar breaks have become a major industrial concern in South Africa. These failures have occurred while applying current condition monitoring methods. This would imply that current theories are either inadequate or badly implemented. This thesis investigates two currently used condition monitoring strategies which focus on monitoring the stator current and axial vibration to detect bar breaks as well as a third method which involves putting destructive shaft voltages to good use and using this signal to diagnose rotor defects. This document begins by familiarizing the reader with two conventional approaches which involve monitoring the stator current and the axial vibration to detect rotor bar breaks. Thereafter the origins of shaft voltage are discussed and its use as a condition monitoring tool is first theoretically derived and then validated by finite element simulations. A thorough discussion of the measurement equipment required is presented and ultimately the performance of these three methods is tested by means of a laboratory measurement as well as two on-site measurements. The results from these measurements suggest that when making proper use of both conventional condition monitoring methods, these methods have a 50% success rate in the detection of rotor bar breaks. The alternative method investigated, which involves monitoring the shaft voltage, has a 75% success rate in the detection of rotor bar breaks. This highlights the use of shaft voltage as a condition monitoring tool.
Dr. S. R. Holm Prof. W. A. Cronje

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Ahmed, Intesar. "Investigation of single and multiple faults under varying load conditions using multiple sensor types to improve condition monitoring of induction machines." 2008. http://hdl.handle.net/2440/58576.

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Condition monitoring involves taking measurements on an induction motor while it is operating in order to detect faults. For this purpose normally a single sensor type, for example current is used to detect broken rotor bar using fault frequency components only under the full-load condition or a limited number of load cases. The correlations among the different types of sensors and their ability to diagnose single and multiple faults over a wide range of loads have not been the focused in previous research. Furthermore, to detect different faults in machines using any fault frequency components, it is important to investigate the variability in its amplitude to other effects apart from fault severity and load. This area has also often been neglected in the literature on condition monitoring. The stator current and axial flux have been widely used as suitable sensors for detecting different faults i.e. broken rotor bar and eccentricity faults in motors. Apart from detecting the broken rotor bar faults in generalized form, the use of instantaneous power signal has often been neglected in the literature condition monitoring. This thesis aims to improve machine condition monitoring and includes accurate and reliable detection of single and multiple faults (faults in the presence of other faults) in induction machines over a wide range of loads of rated output by using current, flux and instantaneous power as the best diagnostic medium. The research presents the following specific tasks: A comprehensive real database from non–invasive sensor measurements, i.e. vibration measurements, axial flux, 3-phase voltage, 3-phase current and speed measurements of induction motor is obtained by using laboratory testing on a large set of identical motors with different single and multiple faults. Means for introducing these faults of varying severity have been developed for this study. The collected data from the studied machines has been analysed using a custom-written analysis programme to detect the severity of different faults in the machines. This helps to improve the accuracy and reliability in detecting of single and multiple faults in motors using fault frequency components from current, axial flux and instantaneous power spectra. This research emphasises the importance of instantaneous power as a medium of detecting different single and multiple faults in induction motor under varying load conditions. This enables the possibility of obtaining accurate and reliable diagnostic medium to detect different faults existing in machines, which is vital in providing a new direction for future studies into condition monitoring. Another feature of this report is to check the variability in healthy motors due to: test repeatability, difference between nominally identical motors, and differences between the phases of the same motor. This has been achieved by conducting extensive series of laboratory tests to examine fault frequency amplitudes versus fault severity, load, and other factors such as test repeatability and machine phases. The information about the variations in the amplitudes of the fault frequency components is used to check the accuracy and reliability of the experimental set-up, which is necessary for the practical application of the results to reliably detect the different faults in the machines reliably. Finally, this study also considers the detection of eccentricity faults using fault frequency amplitudes as a function of average eccentricity, instead of as a function of load under different levels of loading. This has not been reported in previous studies.
http://proxy.library.adelaide.edu.au/login?url= http://library.adelaide.edu.au/cgi-bin/Pwebrecon.cgi?BBID=1298314
Thesis (Ph.D.)-- University of Adelaide, School of Electrical and Electronic Engineering, 2008

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Thusi, Lourenco Mafika. "Determining the optimal technique for early detection of broken rotor bars in medium voltage squirrel cage induction motors during operation." Thesis, 2010. http://hdl.handle.net/10539/7940.

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Electric motors play a pivotal role in various industrial plant processes for electrical to mechanical energy conversion. As a result their reliability and availability is of utmost importance to industries. The reliability and availability of plant electric motors can be achieved by early detection of any developing fault by performing condition monitoring and preventative maintenance on motors. An important motor failure mode, which has been quite challenging to detect, is cracking and subsequent breaking of rotor bars in induction motors. The existing condition monitoring techniques are incapable of positively detecting a cracked or single bar problem during operating conditions. Bars have broken, lifting out of the rotor slots and damaging all stator coils, consequently forcing the removal of the motor during plant operation and a complete rewind of the stator. This research is being conducted to ascertain, from existing conventional techniques, an optimal technique for the detection of a cracked rotor bar or a completely broken single rotor bar in induction motors under operating conditions. Furthermore, it explores non-conventional techniques, which can assist in detection of broken rotor bars. The report starts by presenting the literature on stator current and axial vibration analysis which are conventional rotor bat detection techniques. Thereafter, the Maxwell 2D simulation results which indicate stator current broken rotor bar detection frequencies are discussed, followed by the experimental measurement results and discussions. The conclusion drawn from the experimental results is that the stator current analysis is, presently, the optimal technique to detect a single broken rotor bar during a medium voltage induction motor operation. The axial vibration analysis is recommended as a secondary monitoring technique to solidify the stator current diagnosis. The shaft voltage analysis is introduced as a non-conventional technique and the shaft voltage results are discussed.

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Books on the topic "Broken rotor bars"

1

Welsh, Mark Steven. Detection of broken rotor bars in induction motors using stator current measurements. 1988.

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Zagirnyak, Mykhaylo V., Zhanna Iv Romashykhina, and Andrii P. Kalinov. Diagnostics of Induction Motor Broken Rotor Bars on the Basis of the Electromotive Force Analysis. Nova Science Publishers, Incorporated, 2017.

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Book chapters on the topic "Broken rotor bars"

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Kral, Christian, Anton Haumer, and Christian Grabner. "Broken Rotor Bars in Squirrel Cage Induction Machines – Modeling and Simulation." In Lecture Notes in Electrical Engineering, 81–91. Dordrecht: Springer Netherlands, 2010. http://dx.doi.org/10.1007/978-90-481-8776-8_8.

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Seera, Manjeevan, Chee Peng Lim, and Chu Kiong Loo. "Condition Monitoring of Broken Rotor Bars Using a Hybrid FMM-GA Model." In Neural Information Processing, 381–89. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-12643-2_47.

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Mazur, Damian. "Detection of Broken Rotor Bars in Induction Motors Using Unscented Kalman Filters." In Advances in Intelligent and Soft Computing, 503–11. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-28308-6_69.

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Verma, Alok, and Somnath Sarangi. "Fault Diagnosis of Broken Rotor Bars in Induction Motor Using Multiscale Entropy and Backpropagation Neural Network." In Intelligent Computing and Applications, 393–404. New Delhi: Springer India, 2015. http://dx.doi.org/10.1007/978-81-322-2268-2_41.

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Laribi, Souad Saadi, and Azzedine Bendiabdellah. "Induction Machine Rotor and Stator Faults Detection by Applying the N-F Network." In Advances in Computer and Electrical Engineering, 205–21. IGI Global, 2019. http://dx.doi.org/10.4018/978-1-5225-6989-3.ch010.

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This chapter focuses on the monitoring and diagnosis of induction machine faults, particularly the broken rotor bars. The design of a system for monitoring, detecting, and locating incipient faults for different loads of the machine is achieved by the use of advanced intelligent techniques based on ANFIS-based neuro-fuzzy network. The knowledge base is based on indicators derived from the stator current spectral analysis of the machine which in addition has to detect and assess the number of faulty bars.

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Boudinar, Ahmed Hamida, Azeddine Bendiabdellah, and Noureddine Benouzza. "Diagnosis of the Broken Rotor Bars Faults by Root-MUSIC Method." In Advances in Computer and Electrical Engineering, 59–88. IGI Global, 2019. http://dx.doi.org/10.4018/978-1-5225-6989-3.ch003.

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This chapter describes a new diagnosis approach, the Root-MUSIC (RM) method, for identification of the progressive cracking in the rotor of induction motors. This method used initially in the domain of RADAR for localizing mobile targets is being applied to the domain of induction motors diagnosis. This approach has several advantages compared to the conventional power spectral density estimation (PSD) by periodogram technique. Indeed, the main advantage of this approach is its very good frequency resolution for a very short acquisition time, something impossible to achieve with the conventional method. However, in order to reduce the computation time which is the main drawback of the RM method, this method will be applied to only a specified frequency band: one that carries information about the sought fault.

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Ishikawa, Takeo. "Failure Diagnosis of Squirrel-Cage Induction Motor with Broken Rotor Bars and End Rings." In Induction Motors - Applications, Control and Fault Diagnostics. InTech, 2015. http://dx.doi.org/10.5772/60964.

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Kumar, K. Vinoth, and Prawin Angel Michael. "Analysis of Sidebands Failures in Asynchronous Drives." In Strategic Applications of Measurement Technologies and Instrumentation, 62–76. IGI Global, 2019. http://dx.doi.org/10.4018/978-1-5225-5406-6.ch004.

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This chapter deals with the diagnosis of induction motors (IM) with the so-called motor current signature analysis (MCSA). The MCSA is one of the most efficient techniques for the detection and the localization of electrical and mechanical failures, in which faults become apparent by harmonic components around the supply frequency. This chapter presents a summary of the most frequent faults and its consequences on the stator current spectrum of an IM. A three-phase IM model was used for simulation taking into account in one hand the normal healthy operation and in the other hand the broken rotor bars, the shorted turns in the stator windings, the voltage unbalance between phases of supply, and the abnormal behavior of load. The MCSA is used by many authors in literature for faults detection of IM. The major contribution of this work is to prove the efficiency of this diagnosis methodology to detect different faults simultaneously, in normal and abnormal functional conditions. The results illustrate good agreement between both simulated and experimental results.

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"MCSA Case Histories-SCIM Drives With Slow Speed Gearboxes and Fluctuating Loads Can Give False Positives Of Broken Rotor Bars." In Current Signature Analysis for Condition Monitoring of Cage Induction Motors, 201–39. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2016. http://dx.doi.org/10.1002/9781119175476.ch8.

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Conference papers on the topic "Broken rotor bars"

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Pezzani, Carlos, Pablo Donolo, Guillermo Bossio, Marcos Donolo, Armando Guzman, and Stanley E. Zocholl. "Detecting broken rotor bars with zero-setting protection." In 2012 IEEE/IAS Industrial & Commercial Power Systems Technical Conference (I&CPS). IEEE, 2012. http://dx.doi.org/10.1109/icps.2012.6229616.

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Shi, Pu, Zheng Chen, Yuriy Vagapov, and Zoubir Zouaoui. "Optimal wavelets for broken rotor bars fault diagnosis." In 2013 9th IEEE International Symposium on Diagnostics for Electric Machines, Power Electronics and Drives - (SDEMPED 2013). IEEE, 2013. http://dx.doi.org/10.1109/demped.2013.6645696.

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Angelosante, D., A. Ukil, and A. Andenna. "Toward embedded broken rotor bars detection in induction machines." In 2012 IEEE International Conference on Industrial Technology (ICIT 2012). IEEE, 2012. http://dx.doi.org/10.1109/icit.2012.6210056.

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Ciobanu, Anca, Elena Helerea, and Ioan Peter. "An experimental comparative analysis for broken rotor bars diagnosis." In 2012 International Conference on Applied and Theoretical Electricity (ICATE). IEEE, 2012. http://dx.doi.org/10.1109/icate.2012.6403424.

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Mustafa, Mohammed Obaid, George Georgoulas, and George Nikolakopoulos. "Principal component analysis anomaly detector for rotor broken bars." In IECON 2014 - 40th Annual Conference of the IEEE Industrial Electronics Society. IEEE, 2014. http://dx.doi.org/10.1109/iecon.2014.7049012.

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Prins, Shruti, V. P. Mini, N. Mayadevi, and R. Harikumar. "Detection of Broken Rotor Bars Using Multilevel Wavelet Decomposition." In 2018 2nd International Conference on Trends in Electronics and Informatics (ICOEI). IEEE, 2018. http://dx.doi.org/10.1109/icoei.2018.8553821.

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Nemec, Mitja, Klemen Drobnic, Rastko Fiser, and Vanja Ambrozic. "Simplified model of induction machine with broken rotor bars." In 2016 IEEE International Power Electronics and Motion Control Conference (PEMC). IEEE, 2016. http://dx.doi.org/10.1109/epepemc.2016.7752145.

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Wangngon, B., and S. Ruangsinchaiwanich. "Multiple fault detection technique for identifying broken rotor bars." In 2013 International Conference on Electrical Machines and Systems (ICEMS). IEEE, 2013. http://dx.doi.org/10.1109/icems.2013.6713156.

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Salon, S. J., D. W. Burow, J. Selvaggi, and M. V. K. Chari. "Simulation of broken rotor bars in an induction motor." In 2009 IEEE International Electric Machines and Drives Conference (IEMDC). IEEE, 2009. http://dx.doi.org/10.1109/iemdc.2009.5075194.

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Imeryuz, M., A. F. Mergen, and O. Ustun. "A method to analyze asynchronous machines with broken rotor bars." In 2010 International Symposium on Power Electronics, Electrical Drives, Automation and Motion (SPEEDAM 2010). IEEE, 2010. http://dx.doi.org/10.1109/speedam.2010.5545157.

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