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Journal articles on the topic 'Induction motor failures'

Author: Grafiati

Published: 4 June 2021

Last updated: 1 February 2022

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1

Kocman, Stanislav, and Pavel Pecínka. "Modelling of Stator Coil–To–Ground Faults in Induction Motor." Renewable Energy and Power Quality Journal 19 (September 2021): 396–401. http://dx.doi.org/10.24084/repqj19.303.

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Three–phase squirrel cage induction motors are the most widespread types of electrical motors which can be found in both industrial and tertiary applications. There are some reasons why they are so often used, such as simple construction, nearly maintenance-free, advantageous price and the possibility to feed them directly from the AC network. Even if their reliability is very high, some unexpected breakdowns can occur during their operation. In this paper, coil–to–ground faults of motor stator winding have been taken into consideration. These failures have been modelled in several points of o

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2

Qi, Wei Min, Jie Xiao, and You Han Deng. "Induction Motor Protection System Based on Fuzzy Logic." Applied Mechanics and Materials 719-720 (January 2015): 584–89. http://dx.doi.org/10.4028/www.scientific.net/amm.719-720.584.

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The protection is very important to detect abnormal motor running conditions such as over current, over voltage, overload, over temperature, and so on. When a failure is sensed by the protection system, a time delay should be specified to trip the motor. In the classical systems, motors are stopped with the time delay, which is adjusted constantly without considering the fault level. This paper presents a fuzzy logic-based protection system covering six different fault parameters for induction motors. The paper focuses on a new time-delay calculation for stopping induction motor and improves t

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3

Alawady, A. A., M. F. M. Yousof, N. Azis, and M. A. Talib. "Phase to phase fault detection of 3-phase induction motor using FRA technique." International Journal of Power Electronics and Drive Systems (IJPEDS) 11, no. 3 (2020): 1241. http://dx.doi.org/10.11591/ijpeds.v11.i3.pp1241-1248.

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The purpose for preparing this paper is to innovate a new method to detection and diagnosis the three-phase induction motor electrical failures, especially the failures that occur in Stator winding. Stator winding breakdown largely contributes to induction motor failures. To understand internal fault in induction motors winding, four cases studies of different three-phase induction motors (TPIM) were analysed according to two conditions: normal winding condition and windings shorted between two phases. In this paper, the measurement of frequency response analysis (FRA) on the stator winding wi

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4

Gedzurs, Aleksejs. "Fault Diagnosis of Low-Power Three-Phase Induction Motor." Rural Sustainability Research 36, no. 331 (2016): 34–41. http://dx.doi.org/10.1515/plua-2016-0012.

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Abstract An Induction motor reliability survey at an egg processing plant shows that almost 50% of the total motor failures are fan induction motors. Visual investigations of the faulty fan motors show that the main cause of the induction motor failure is air gap eccentricity. In this study, experimental tests are performed on a 1.1kW three-phase induction motor to detect air gap eccentricity and overheating of the induction motor. Heating tests show that end shield housing temperature reaches 100°C with blocked air flow from the fan, which can reduce the lifespan of the bearing. Dimension mea

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Abitha, Memala W., and V. Rajini. "Virtual Instrumentation Based Analysis of Induction Motor." Advanced Materials Research 984-985 (July 2014): 970–76. http://dx.doi.org/10.4028/www.scientific.net/amr.984-985.970.

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The three phase induction motor is a popularly used machine in many of the industries, which is well known for its robustness, reliability, cost effectiveness, efficient and safe operation. The unnoticed manufacturing failure, mistakes during repair work, exceeding life time may be some of the causes of the induction motor failure, which may lead to the unknown shut down time of the industry. The condition monitoring plays important role as it has the influence on the production of materials and profit. In our work, the induction motor is modelled using stationary reference frame and analysed

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6

Boumous, Z., and S. Boumous. "New Approach in the Fault Tolerant Control of Three-Phase Inverter Fed Induction Motor." Engineering, Technology & Applied Science Research 10, no. 6 (2020): 6504–9. http://dx.doi.org/10.48084/etasr.3898.

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This article provides an improved fault-tolerant control scheme for inverter-powered induction motors. The proposed strategy addresses the cancellation of power switch failures (IGBTs) regardless of their location in a reconfigurable induction motor control. The proposed fault-tolerant topology requires only minimal hardware modifications of the conventional six-switch three-phase drive, mitigating IGBT failures through reconfiguration based on the substitution of an entire inverter arm. The detection mechanism is based on the tridimensional method from which a database will be used for the le

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Sun, Li Ling, and Bao Long Zhang. "Asynchronous Motor Bearing Fault Detection Methods." Advanced Materials Research 383-390 (November 2011): 5055–58. http://dx.doi.org/10.4028/www.scientific.net/amr.383-390.5055.

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Bearing, asynchronous deep groove ball bearings are widely used in induction motor field. Motor bearing failure probability is as high as 40% in asynchronous motor. It accounts for the largest proportion of failures in the motor. Therefore, people have been on studying motor bearing fault detection methods for further research. So far, people have studied a variety of modern detection methods.

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8

Cekic, Yalcin. "Bearing fault detection by four-band wavelet packet decomposition." Thermal Science 23, Suppl. 1 (2019): 91–98. http://dx.doi.org/10.2298/tsci180927333c.

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Bearing problems are by far the biggest cause of induction motor failures in the industry. Since induction machines are used heavily by the industry, their unexpected failure may disturb the production process. Motor condition monitoring is employed widely to avoid such unexpected failures. The data that can be obtained from induction machines are non-stationary by nature since the loading may vary during their operation. Wavelet packet decomposition seems to better handle non-stationary nature of induction machines, the use of this method in monitoring applications is limited, since the compu

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9

HASUIKE, K. "A Statistical Study of Small Induction Motor Coil Failures." Electric Machines & Power Systems 13, no. 6 (1987): 349–60. http://dx.doi.org/10.1080/07313568708909256.

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10

Goktas, Taner, and Müslüm Arkan. "Discerning broken rotor bar failure from low-frequency load torque oscillation in DTC induction motor drives." Transactions of the Institute of Measurement and Control 40, no. 1 (2016): 279–86. http://dx.doi.org/10.1177/0142331216654964.

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This paper proposes a method for separation of broken rotor bar failures from low-frequency load torque oscillation in direct torque control (DTC) induction motor drives by using vq voltage and iq current components’ spectra. The effect of load torque oscillation should be considered in induction motor drives for reliable broken bar fault detection. Induction machine drivers are run in DTC mode to control its torque and speed. In practice, the presence of load torque fluctuation may sometimes cause false positive alarms on stator current spectrum. However, discerning of broken rotor bar failur

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11

P.P.S Saputra. "Pendeteksian Misalignment Menggunakan Multi Level Transformasi Wavelet Haar dan Coiflet pada Motor Induksi." Jurnal JEETech 1, no. 1 (2020): 1–6. http://dx.doi.org/10.48056/jeetech.v1i1.1.

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Currently induction motors are widely used in industry due to strong construction, high efficiency, and cheap maintenance. Machine maintenance is needed to prolong the life of the induction motor. As studied, bearing faults may account for 42% -50% of all motor failures. In general it is due to manufacturing faults, lack of lubrication, and installation errors. Misalignment of motor is one of the installation errors. This paper is concerned to simulation of discrete wavelet transform for identifying misalignment in induction motor. Modelling of motor operation is introduced in this paper as no

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12

Trzynadlowski, Andrzej M. "Detection of Mechanical Abnormalities in Induction Motors by Electric Measurements." International Journal of Rotating Machinery 5, no. 1 (1999): 41–52. http://dx.doi.org/10.1155/s1023621x99000044.

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The paper gives an overview of the issues and means of detection of mechanical abnormalities in induction motors by electric measurements. If undetected and untreated, the worn or damaged bearings, rotor imbalance and eccentricity, broken bars of the rotor cage, and torsional and lateral vibration lead to roughly a half of all failures of induction motor drives. The detection of abnormalities is based on the fact that they cause periodic disturbance of motor variables, such as the speed, torque, current, and magnetic flux. Thus, spectral analysis of those or related quantities may yield a warn

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13

Garcia-Perez, Arturo, Rene J. Romero-Troncoso, Eduardo Cabal-Yepez, Roque A. Osornio-Rios, and Jose A. Lucio-Martinez. "Application of high-resolution spectral analysis for identifying faults in induction motors by means of sound." Journal of Vibration and Control 18, no. 11 (2011): 1585–94. http://dx.doi.org/10.1177/1077546311422925.

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Induction motors are critical components for most industries. Induction motor failures may yield an unexpected interruption at the industry plant. Several conventional vibration and current analysis techniques exist by which certain faults in rotating machinery can be identified. Ever since the first motor was built, plant personnel have listened to the noises emanating from machines; with enough experience, a listener may make a fairly accurate estimate of the condition of a machine. Although there are several works that deal with vibration and current analysis for monitoring and detection of

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14

Li, Shu Ying, Mu Qin Tian, and Lei Xue. "Fault Diagnosis of Induction Motor Based on Multi-Sensor Data Fusion." Applied Mechanics and Materials 651-653 (September 2014): 729–32. http://dx.doi.org/10.4028/www.scientific.net/amm.651-653.729.

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For the conclusions of single parameter fault feature diagnosis has some uncertainty, in induction motor early fault, we proposed the use of multi-sensor data fusion technology, acted signal processing to the collected current, vibration and temperature, extracted feature information failure, fused the evidence independent with each other using D-S evidence fusion rules. According to the final combination results of all the evidence, combined with intermediate results of the evidence combination, we achieved the accurate identification of induction motor rotor early failures and composite faul

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15

Rangel-Magdaleno, Jose, Hayde Peregrina-Barreto, Juan Ramirez-Cortes, Roberto Morales-Caporal, and Israel Cruz-Vega. "Vibration Analysis of Partially Damaged Rotor Bar in Induction Motor under Different Load Condition Using DWT." Shock and Vibration 2016 (2016): 1–11. http://dx.doi.org/10.1155/2016/3530464.

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The relevance of the development of monitoring systems for rotating machines is not only the ability to detect failures but also how early these failures can be detected. The purpose of this paper is to present an experimental study of partially damaged rotor bar in induction motor under different load conditions based on discrete wavelet transform analysis. The approach is based on the extraction of features from vibration signals at different level of damage and three mechanical load conditions. The proposed analysis is reliable for tracking the damage in rotor bar. The paper presents an ana

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16

Asad, Bilal, Toomas Vaimann, Anton Rassõlkin, Ants Kallaste, and Anouar Belahcen. "A Survey of Broken Rotor Bar Fault Diagnostic Methods of Induction Motor." Electrical, Control and Communication Engineering 14, no. 2 (2018): 117–24. http://dx.doi.org/10.2478/ecce-2018-0014.

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AbstractElectrical machines, induction motors in particular, play a key role in domestic and industrial applications. They act as a work horse in almost every industry and are responsible for a big proportion of total generated electricity consumption worldwide. The faults in induction motors are degenerative in nature and can lead to a catastrophic situation if not diagnosed earlier. The failures can cause considerable financial loss in the form of unexpected downtime. Broken rotor bar is a very common and frequently occurring fault in most of industrial induction motors. To select a better,

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17

Liu, Yiqi, Michael Stettenbenz, and Ali M. Bazzi. "Smooth Fault-Tolerant Control of Induction Motor Drives With Sensor Failures." IEEE Transactions on Power Electronics 34, no. 4 (2019): 3544–52. http://dx.doi.org/10.1109/tpel.2018.2848964.

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18

Bazan, Gustavo Henrique, Alessandro Goedtel, Marcelo Favoretto Castoldi, Wagner Fontes Godoy, Oscar Duque-Perez, and Daniel Morinigo-Sotelo. "Mutual Information and Meta-Heuristic Classifiers Applied to Bearing Fault Diagnosis in Three-Phase Induction Motors." Applied Sciences 11, no. 1 (2020): 314. http://dx.doi.org/10.3390/app11010314.

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Three-phase induction motors are extensively used in industrial processes due to their robustness, adaptability to different operating conditions, and low operation and maintenance costs. Induction motor fault diagnosis has received special attention from industry since it can reduce process losses and ensure the reliable operation of industrial systems. Therefore, this paper presents a study on the use of meta-heuristic tools in the diagnosis of bearing failures in induction motors. The extraction of the fault characteristics is performed based on mutual information measurements between the s

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19

Verma, Vimlesh. "Current sensorless vector controlled induction motor drive." IAES International Journal of Robotics and Automation (IJRA) 8, no. 1 (2019): 52. http://dx.doi.org/10.11591/ijra.v8i1.pp52-67.

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This paper presents a current sensorless vector controlled induction motor drive with only speed sensor present in the system. The same performance as that of normal vector control drives (which uses two current and one speed sensor) is achieved with the proposed current sensorless drive. Such an approach is suitable for applications, where speed sensor cannot be eliminated. Thus, elimination of current sensor results in reduction of cost, increases reliability, reduced size and noise immunity. A new current estimation algorithm is proposed in this paper. The current estimation algorithm, esti

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20

Kuroczycki, Sebastian, Konrad Górny, and Wojciech Pietrowski. "Assessment of failure to the stator winding of the induction motor by means of deep neural network." ITM Web of Conferences 28 (2019): 01049. http://dx.doi.org/10.1051/itmconf/20192801049.

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Due to the fact that inter-turn short-circuits are the ones of the most common causes of damage to stator of induction motors, research on their early detection is still gaining in importance. The scientific novelty in the presented article is an approach in which a decision element informing about the failure of stator of induction machine is a deep artificial neural network. In the learning process, torque waveforms subjected to a continuous wavelet transform were used. In order to classify of the stator winding failures the accelerator of artificial neural networks was used.

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21

Gonzalez-Jimenez, David, Jon del-Olmo, Javier Poza, Fernando Garramiola, and Izaskun Sarasola. "Machine Learning-Based Fault Detection and Diagnosis of Faulty Power Connections of Induction Machines." Energies 14, no. 16 (2021): 4886. http://dx.doi.org/10.3390/en14164886.

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Induction machines have been key components in the industrial sector for decades, owing to different characteristics such as their simplicity, robustness, high energy efficiency and reliability. However, due to the stress and harsh working conditions they are subjected to in many applications, they are prone to suffering different breakdowns. Among the most common failure modes, bearing failures and stator winding failures can be found. To a lesser extent, High Resistance Connections (HRC) have also been investigated. Motor power connection failure mechanisms may be due to human errors while a

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22

Skowron, Maciej, Marcin Wolkiewicz, Teresa Orlowska-Kowalska, and Czeslaw Kowalski. "Application of Self-Organizing Neural Networks to Electrical Fault Classification in Induction Motors." Applied Sciences 9, no. 4 (2019): 616. http://dx.doi.org/10.3390/app9040616.

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Electrical winding faults, namely stator short-circuits and rotor bar damage, in total constitute around 50% of all faults of induction motors (IMs) applied in variable speed drives (VSD). In particular, the short circuits of stator windings are recognized as one of the most difficult failures to detect because their detection makes sense only at the initial stage of the damage. Well-known symptoms of stator and rotor winding failures can be visible in the stator current spectra; however, the detection and classification of motor windings faults usually require the knowledge of human experts.

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23

Camarena-Martinez, David, Martin Valtierra-Rodriguez, Juan P. Amezquita-Sanchez, David Granados-Lieberman, Rene J. Romero-Troncoso, and Arturo Garcia-Perez. "Shannon Entropy andK-Means Method for Automatic Diagnosis of Broken Rotor Bars in Induction Motors Using Vibration Signals." Shock and Vibration 2016 (2016): 1–10. http://dx.doi.org/10.1155/2016/4860309.

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For industry, the induction motors are essential elements in production chains. Despite the robustness of induction motors, they are susceptible to failures. The broken rotor bar (BRB) fault in induction motors has received special attention since one of its characteristics is that the motor can continue operating with apparent normality; however, at certain point the fault may cause severe damage to the motor. In this work, a methodology to detect BRBs using vibration signals is proposed. The methodology uses the Shannon entropy to quantify the amount of information provided by the vibration

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24

Sinan Cabuk, Ali. "Data acquisition system for induction motors with arduino." International Conference on Technics, Technologies and Education, ICTTE 2019 (2019): 256–62. http://dx.doi.org/10.15547/ictte.2019.04.090.

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Data acquisition systems have been used for many years in order to conduct analyses to increase efficiency, measure performance and detect failures in electrical motors.High costs and not being of modular use have prevented these systems from being commonly used. Various methods were developed for data acquisition from electrical machines. This paper presents data acquisition analysing and monitoring system using Arduino platform. Vibration, temperature and current values of a 3 phase induction motor are obtained by this data acquisition system via USB port. A system compatiable with all sorts

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Skowron, Maciej, and Teresa Orłowska-Kowalska. "Efficiency of Cascaded Neural Networks in Detecting Initial Damage to Induction Motor Electric Windings." Electronics 9, no. 8 (2020): 1314. http://dx.doi.org/10.3390/electronics9081314.

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This article presents the efficiency of using cascaded neural structures in the process of detecting damage to electrical circuits in a squirrel cage induction motor (IM) supplied from a frequency converter. The authors present the idea of a sequential connection of classic neural structures to increase the efficiency of damage classification and detection presented by individual neural structures, especially in the initial phase of single or multiple electrical failures. The easily measurable axial flux signal is used as a source of diagnostic information. The developed cascaded neural networ

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Eldeeb, Hassan, Haisen Zhao, and Osama Mohammed. "Effect of Stator Insulation Failure on the Motor Drive System Performance." Applied Computational Electromagnetics Society 35, no. 11 (2021): 1370–71. http://dx.doi.org/10.47037/2020.aces.j.351154.

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This study investigates the influence of the stator’s turn-to-turn failures (TTFs) on the electromagnetic (EM) fields, such as air gap flux density, flux density in the stator, and rotor iron core inside of direct self-control (DSC) driven induction machines (IMs). The purpose of the investigation is to capture the fault signatures in the air gap EM flux for detecting the stator’s fault at its embryonic stage.

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Salah, Lachtar, Ghoggal Adel, Koussa Khaled, Bouraiou Ahmed, and Attoui Issam. "Broken rotor bar fault diagnostic for DTC Fed induction motor using stator instantaneous complex apparent power envelope signature analysis." International Journal of Power Electronics and Drive Systems (IJPEDS) 10, no. 3 (2019): 1187. http://dx.doi.org/10.11591/ijpeds.v10.i3.pp1187-1196.

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The broken rotor bar is an unexpected fault and a common cause of induction motor failures that threaten the structural integrity of electric machines. In this paper, a new approach to a broken rotor bar diagnosis, without slip estimation, based on the envelope of the stator instantaneous complex apparent power (SICAP) is proposed. The envelope is obtained from the SICAP modulation and then transferred to a computer for monitoring the characteristic frequency and its amplitude using the Fast Fourier Transform (FFT). For this purpose, the winding function approach (WFA) is used to simulate the

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Venkata Ramana, D., and S. Baskar. "Incipient Fault Detection of the Inverter Fed Induction Motor Drive." International Journal of Power Electronics and Drive Systems (IJPEDS) 8, no. 2 (2017): 722. http://dx.doi.org/10.11591/ijpeds.v8.i2.pp722-729.

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Inverter fed Induction motor drives are deployed across a variety of industrial and commercial applications. Although the drives in the question are well known for their reliable operation in any type of environment, it becomes an important daunting critical task to have them in continuous operation as per the applications’ requirement. Identifying the faulty behavior of power electronic circuits which could lead to catastrophic failures is an attractive proposition. The cost associated with building systems devoted for monitoring and diagnosis is high, however such cost could be justified for

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Safin, N. R., V. A. Prakht, and V. A. Dmitrievskii. "An investigation of the influence of bearing failures on the efficiency of an induction motor." Russian Electrical Engineering 88, no. 10 (2017): 692–96. http://dx.doi.org/10.3103/s106837121710011x.

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Skowron, Maciej, Marcin Wolkiewicz, Teresa Orlowska-Kowalska, and Czeslaw T. Kowalski. "Effectiveness of Selected Neural Network Structures Based on Axial Flux Analysis in Stator and Rotor Winding Incipient Fault Detection of Inverter-fed Induction Motors." Energies 12, no. 12 (2019): 2392. http://dx.doi.org/10.3390/en12122392.

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This paper presents a comparative study on the application of different neural network structures to early detection of electrical faults in induction motor drives. The diagnosis inference of the stator inter-turn short-circuits and broken rotor bars is based on the analysis of an axial flux of the induction motor. In order to automate the fault detection process, three different structures of neural networks were used: multi-layer perceptron, self-organizing Kohonen network and recursive Hopfield network. Tests were carried out for various levels of stator and rotor failures. In order to asse

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Dzwonkowski, Ariel, and Leon Swędrowski. "Uncertainty analysis of measuring system for instantaneous power research." Metrology and Measurement Systems 19, no. 3 (2012): 573–82. http://dx.doi.org/10.2478/v10178-012-0050-7.

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Abstract The electrical power drawn by an induction motor is distorted in case of appearance of a certain type of failures. Under spectral analysis of the instantaneous power one obtains the components which are connected with definite types of damage. An analysis of the amplitudes and frequencies of the components allows to recognize the type of fault. The paper presents a metrological analysis of the measurement system used for diagnosis of induction motor bearings, based on the analysis of the instantaneous power. This system was implemented as a set of devices with dedicated software insta

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Bensalem, Yemna, and Mohamed Naceur Abdelkrim. "Modeling and Simulation of Induction Motor based on Finite Element Analysis." International Journal of Power Electronics and Drive Systems (IJPEDS) 7, no. 4 (2016): 1100. http://dx.doi.org/10.11591/ijpeds.v7.i4.pp1100-1109.

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<p>This paper presents the development of a co-simulation platform of induction motor (IM). For the simulation, a coupled model is introduced which contains the control, the power electronics and also the induction machine. Each of these components is simulated in different software environments. So, this study provides an advanced modeling and simulation tools for IM which integrate all the components into one common simulation platform environment. In this work, the IM is created using Ansys-Maxwell based on Finite Element Analysis (FEA), whereas the power electronic converter is devel

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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 (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

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Patel, R. K., and V. K. Giri. "Condition monitoring of induction motor bearing based on bearing damage index." Archives of Electrical Engineering 66, no. 1 (2017): 105–19. http://dx.doi.org/10.1515/aee-2017-0008.

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Abstract The rolling element bearings are used broadly in many machinery applications. It is used to support the load and preserve the clearance between stationary and rotating machinery elements. Unfortunately, rolling element bearings are exceedingly prone to premature failures. Vibration signal analysis has been widely used in the faults detection of rotating machinery and can be broadly classified as being a stationary or non-stationary signal. In the case of the faulty rolling element bearing the vibration signal is not strictly phase locked to the rotational speed of the shaft and become

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Liu, Meng-Kun, Minh-Quang Tran, and Peng-Yi Weng. "Fusion of Vibration and Current Signatures for the Fault Diagnosis of Induction Machines." Shock and Vibration 2019 (September 19, 2019): 1–17. http://dx.doi.org/10.1155/2019/7176482.

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Induction machines are widely used in the industry as one of the major actuators, such as water pumps, air compressors, and fans. It is necessary to monitor and diagnose these induction motors to prevent any sudden shut downs caused by premature failures. Numerous fault detection and isolation techniques for the diagnosis of induction machines have been proposed over the past few decades. Among these techniques, motor current signature analysis (MCSA) and vibration analysis are two of the most common signal-based condition monitoring methods. They are often adopted independently, but each meth

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Araujo, Romero de Souza, Ronaldo de Araujo Rodrigues, Helder de Paula, Braz J. Cardoso Filho, Lane Maria Rabelo Baccarini, and Anderson Vagner Rocha. "Premature Wear and Recurring Bearing Failures in an Inverter-Driven Induction Motor—Part II: The Proposed Solution." IEEE Transactions on Industry Applications 51, no. 1 (2015): 92–100. http://dx.doi.org/10.1109/tia.2014.2331420.

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Tran, Cuong Dinh, Pavel Brandstetter, Minh Huu Chau Nguyen, Sang Dang Ho, Phuong Nhat Pham, and Bach Hoang Dinh. "An Enhanced Fault Tolerant Control Against Current Sensor Failures in Induction Motor Drive by Applying Space Vector." Journal of Advanced Engineering and Computation 4, no. 1 (2020): 51. http://dx.doi.org/10.25073/jaec.202041.269.

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In this paper, an enhanced active fault-tolerant control (FTC) is proposed to solve a current sensor failure in the induction motor drive (IMD) using two current sensors. The proposed FTC method applies only one observer to diagnose the faults and reconfigure the control signals by the space stator current. The diagnosis function is made up of a comparison algorithm between the measured current space vector and the estimated space vector. Then, incorrect feedback stator currents are replaced by the estimated values in the reconfiguration function. The amplitude of a healthy measured current is

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Skowron, Maciej, Teresa Orlowska-Kowalska, Marcin Wolkiewicz, and Czeslaw T. Kowalski. "Convolutional Neural Network-Based Stator Current Data-Driven Incipient Stator Fault Diagnosis of Inverter-Fed Induction Motor." Energies 13, no. 6 (2020): 1475. http://dx.doi.org/10.3390/en13061475.

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In this paper, the idea of using a convolutional neural network (CNN) for the detection and classification of induction motor stator winding faults is presented. The diagnosis inference of the stator inter-turn short-circuits is based on raw stator current data. It offers the possibility of using the diagnostic signal direct processing, which could replace well known analytical methods. Tests were carried out for various levels of stator failures. In order to assess the sensitivity of the applied CNN-based detector to motor operating conditions, the tests were carried out for variable load tor

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Pita, H., G. Zurita, and A. Villarroel. "Software development firmware system for broken rotor bar detection and diagnosis of induction motor through current signature analysis." Journal of Mechanical Engineering and Sciences 14, no. 2 (2020): 6917–33. http://dx.doi.org/10.15282/jmes.14.2.2020.30.0542.

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The induction motors (IMs) are undoubtedly the most used machines in industries because of the advantages they offer such as simplicity, service continuity and low cost. Due to wear and tear, the motor suffers different types of mechanical and electrical failures. Depending on the criticality of the plant motors, it could be necessary to implement predictive techniques in order to detect the faults before they can cause unnecessary downtime. Therefore, in this paper, the research approach was to develop a low cost measurement system based on a micro controller platform for machine diagnosis. T

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Lucas, Guilherme, Marco Rocha, Bruno Castro, José Leão, and André Andreoli. "Stator Winding Fault Phase Identification Using Piezoelectric Sensors in Three-Phase Induction Motors." Engineering Proceedings 2, no. 1 (2020): 32. http://dx.doi.org/10.3390/ecsa-7-08183.

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Three-phase induction motors (TIMs) play a key role in industrial production lines. Due to their robustness and versatility, TIMs are commonly used to drive different devices like fans, conveyors, sieves, and compressors. However, these devices are often exposed to mechanical and electrical faults. Among them, failures in stator winding insulation lead to severe damage to the TIMs and can cause operational interruptions. Therefore, several approaches have been developed to monitor electrical faults in induction motors. The acoustic emission (AE) stands out as an efficient non-invasive techniqu

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Sobański, Piotr, and Teresa Orłowska-Kowalska. "Detection of single and multiple IGBTs open-circuit faults in a field-oriented controlled induction motor drive." Archives of Electrical Engineering 66, no. 1 (2017): 89–104. http://dx.doi.org/10.1515/aee-2017-0007.

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Abstract In this paper a transistor open-circuit fault diagnosis method in a rotor field oriented controlled induction motor drive, fed by a two-level voltage inverter has been proposed. The diagnostic procedure ensures detection and localization of single or multiple power switch failures in time shorter than one period of a stator current fundamental harmonic, without regard to a drive operation point. A new simple scheme of the diagnostic system is proposed. In order to validate the proposed transistor fault diagnostic method, a detailed simulation as well as experimental tests of the field

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Araujo, Romero de Souza, Helder de Paula, Ronaldo de Araujo Rodrigues, Lane Maria Rabelo Baccarini, and Anderson Vagner Rocha. "Premature Wear and Recurring Bearing Failures in an Inverter-Driven Induction Motor—Part I: Investigation of the Problem." IEEE Transactions on Industry Applications 51, no. 6 (2015): 4861–67. http://dx.doi.org/10.1109/tia.2015.2456059.

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Farhadi, Masoud, Majid Tahmasbi Fard, Mehdi Abapour, and Mehrdad Tarafdar Hagh. "DC–AC Converter-Fed Induction Motor Drive With Fault-Tolerant Capability Under Open- and Short-Circuit Switch Failures." IEEE Transactions on Power Electronics 33, no. 2 (2018): 1609–21. http://dx.doi.org/10.1109/tpel.2017.2683534.

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Uddin, Jia, Myeongsu Kang, Dinh V. Nguyen, and Jong-Myon Kim. "Reliable Fault Classification of Induction Motors Using Texture Feature Extraction and a Multiclass Support Vector Machine." Mathematical Problems in Engineering 2014 (2014): 1–9. http://dx.doi.org/10.1155/2014/814593.

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This paper proposes a method for the reliable fault detection and classification of induction motors using two-dimensional (2D) texture features and a multiclass support vector machine (MCSVM). The proposed model first converts time-domain vibration signals to 2D gray images, resulting in texture patterns (or repetitive patterns), and extracts these texture features by generating the dominant neighborhood structure (DNS) map. The principal component analysis (PCA) is then used for the purpose of dimensionality reduction of the high-dimensional feature vector including the extracted texture fea

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Ramdane, Ahmed, Abdelaziz Lakehal, Ridha Kelaiaia, and Salah Saad. "A Bayesian Information System for Predicting Stator Faults in Induction Machines." Acta Universitatis Sapientiae Electrical and Mechanical Engineering 10, no. 1 (2018): 67–76. http://dx.doi.org/10.2478/auseme-2018-0004.

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Abstract The approach adopted in this paper focuses on the faults prediction in asynchronous machines. The main goal is to explore interesting information regarding the diagnosis and prediction of electrical machines failures by the use of a Bayesian graphical model. The Bayesian forecasting model developed in this paper provides a posteriori probability for faults in each hierarchical level related to the breakdowns process. It has the advantage that it can give needed information’s for maintenance planning. A real industrial case study is presented in which the maintenance staff expertise ha

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Adamczyk, Michal, and Teresa Orlowska-Kowalska. "Virtual Current Sensor in the Fault-Tolerant Field-Oriented Control Structure of an Induction Motor Drive." Sensors 19, no. 22 (2019): 4979. http://dx.doi.org/10.3390/s19224979.

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Designing electrical drives resistant to the failures of chosen sensors has recently become increasingly popular due to the possibility of their use in fault-tolerant control (FTC) systems including drives for electric vehicles. In this article, a virtual current sensor (VCS) based on an algorithmic method for the reconstruction of the induction motor (IM) phase currents after current sensor faults was proposed. This stator current estimator is based only on the measurements of the DC-bus voltage in the intermediate circuit of the voltage-source inverter (VSI) and a rotor speed. This proposal

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Kumar, K. Vinoth, S. Suresh Kumar, and A. Immanuel Selvakumar. "Spectrum Analysis of Sidebands in Industrial Drives." International Journal of Measurement Technologies and Instrumentation Engineering 5, no. 2 (2015): 1–13. http://dx.doi.org/10.4018/ijmtie.2015070101.

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This paper 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 paper 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 b

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Lopez-Ramirez, Misael, Rene J. Romero-Troncoso, Daniel Moriningo-Sotelo, Oscar Duque-Perez, David Camarena-Martinez, and Arturo Garcia-Perez. "Discriminating the lubrication condition from the rotor bearing fault in induction motors using Margenau-Hill frequency distribution and artificial neural networks." Industrial Lubrication and Tribology 69, no. 6 (2017): 970–79. http://dx.doi.org/10.1108/ilt-08-2016-0177.

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Purpose About 13 to 44 per cent of motor faults are caused by bearing failures in induction motors (IMs), where lubrication plays a significant role in maintaining rotating equipment because it minimizes friction and prevents wear by separating parts that move next to each other, and more than 35 per cent of bearing failures can be attributed to improper lubrication. An excessive amount of grease causes the rollers or balls to slide along the race instead of turning, and the grease will actually churn. This churning action will eventually wear down the base oil of the grease and all that will

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Boukadida, Souha, Soufien Gdaim, and Abdellatif Mtiba. "Sensor Fault Detection and Isolation Based on Artificial Neural Networks and Fuzzy Logic Applicated on Induction Motor for Electrical Vehicle." International Journal of Power Electronics and Drive Systems (IJPEDS) 8, no. 2 (2017): 601. http://dx.doi.org/10.11591/ijpeds.v8.i2.pp601-611.

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<p>Recently, research has picked up a fervent pace in the area of fault diagnosis of electrical vehicle. Like failures of a position sensor, a voltage sensor, and current sensors. Three-phase induction motors are the “workhorses” of industry and are the most widely used electrical machines. This paper presents a scheme for Fault Detection and Isolation (FDI). The proposed approach is a sensor-based technique using the mains current measurement. Current sensors are widespread in power converters control and in electrical drives. Thus, to ensure continuous operation with reconfiguration co

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Harzelli, Imadeddine, Abdelhamid Benakcha, Tarek Ameid, and Arezki Menacer. "Closed-Loop Drive Detection and Diagnosis of Multiple Combined Faults in Induction Motor Through Model-Based and Neuro-Fuzzy Network Techniques." Journal of Modeling and Optimization 13, no. 2 (2021): 58–79. http://dx.doi.org/10.32732/jmo.2021.13.2.58.

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In this paper, a fault detection and diagnosis approach adopted for an input-output feedback linearization (IOFL) control of induction motor (IM) drive is proposed. This approach has been employed to detect and identify the simple and mixed broken rotor bars and static air-gap eccentricity faults right from the start its operation by utilizing advanced techniques. Therefore, two techniques are applied: the model-based strategy, which is an online method used to generate residual stator current signal in order to indicate the presence of possible failures by means of the sliding mode observer (

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