Relevant bibliographies by topics / Condition monitoring; negative sequence current; induction motor

Academic literature on the topic 'Condition monitoring; negative sequence current; induction motor'

Author: Grafiati
Published: 10 December 2022
Last updated: 28 January 2023

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Journal articles on the topic "Condition monitoring; negative sequence current; induction motor"

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Bakhri, Syaiful, and Nesimi Ertugrul. "A Negative Sequence Current Phasor Compensation Technique for the Accurate Detection of Stator Shorted Turn Faults in Induction Motors." Energies 15, no. 9 (April 24, 2022): 3100. http://dx.doi.org/10.3390/en15093100.

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Stator faults are the most critical faults in induction motors as they develop quickly hence requiring fast online diagnostic methods. A number of online condition monitoring techniques are proposed in the literature to respond to such faults, including the signature analysis of the stator current, vibration monitoring, flux leakage monitoring, negative sequence components of voltage and current and sequence components monitoring based on the identification of asymmetrical behavior in a machine. Negative sequence components of voltage and current and sequence components monitoring are commonly considered for the identification of asymmetrical behavior of induction motors. Negative sequence current analysis is a sensitive technique for the detection of shorted turns as it directly measures the asymmetry produced by the fault. However, the technique is sensitive to other asymmetrical faults and disturbances, which can also produce negative sequence currents. These disturbances include sensor errors, inherent asymmetry and voltage unbalance. This paper provides a comprehensive investigation of the disturbances using a motor model along with experimental measurements under varying load conditions. Then, a new phasor compensation technique is explained to eliminate such disturbances effectively. This technique enables the accurate detection of even relatively small shorted turn faults, even at an early stage. The technique is tested experimentally, and a set of practical results are given to validate the methods developed.
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Rajamany, Gayatridevi, Sekar Srinivasan, Krishnan Rajamany, and Ramesh K. Natarajan. "Induction Motor Stator Interturn Short Circuit Fault Detection in Accordance with Line Current Sequence Components Using Artificial Neural Network." Journal of Electrical and Computer Engineering 2019 (December 11, 2019): 1–11. http://dx.doi.org/10.1155/2019/4825787.

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The intention of fault detection is to detect the fault at the beginning stage and shut off the machine immediately to avoid motor failure due to the large fault current. In this work, an online fault diagnosis of stator interturn fault of a three-phase induction motor based on the concept of symmetrical components is presented. A mathematical model of an induction motor with turn fault is developed to interpret machine performance under fault. A Simulink model of a three-phase induction motor with stator interturn fault is created for extraction of sequence components of current and voltage. The negative sequence current can provide a decisive and rapid monitoring technique to detect stator interturn short circuit fault of the induction motor. The per unit change in negative sequence current with positive sequence current is the main fault indicator which is imported to neural network architecture. The output of the feedforward backpropagation neural network classifies the short circuit fault level of stator winding.
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Van Cuong, Ngo, and Lidiia I. Kovernikova. "Analysis of the influence of non-sinusoidal and unbalanced network modes on induction motors." E3S Web of Conferences 289 (2021): 01002. http://dx.doi.org/10.1051/e3sconf/202128901002.

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The parameters of electrical network modes do not correspond the requirements GOST 32144-2013 of Russian and the National technical regulation of Vietnam. In real operating conditions in electrical networks in non-sinusoidal and unbalanced modes there are harmonic components of voltages and currents as well as voltages and currents of negative sequence. They cause additional losses of active power, which leads to additional heating and causes premature aging of the insulation, and as the result, the reduction in the service life of induction motors. Currently, we see that the process of formation of intelligent electrical power systems is underway. Systems for continuous monitoring of power quality indices and parameters of electrical systems modes are being developed. These systems can be supplemented with programs for calculating characteristics that issue the warning when the unfavorable influence of the parameters of non-sinusoidal and unbalanced modes is detected on various electrical equipment of both electrical power systems and consumers of electrical energy. The paper provides an overview of the characteristics used to analyze, assess and predict the influence of poor power quality associated with non-sinusoidal and unbalanced of currents and voltages on induction motors. A computer program was developed to calculate these characteristics. The program was used to study the influence of non-sinusoidal and unbalanced modes on the induction motors of the coal sorting plant of the Vietnamese company “Cua Ong-Vinacomin”.
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Zhang, Jian Hua, Hao Ran Shen, Lei Ding, and Chun Lei Dai. "The Transient Characteristics Analysis of Doubly-Fed Induction Generator during the Asymmetric Voltage Sag." Applied Mechanics and Materials 644-650 (September 2014): 3509–14. http://dx.doi.org/10.4028/www.scientific.net/amm.644-650.3509.

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In order to analyze the control strategy of the low voltage ride through (LVRT) of DFIG during the asymmetric voltage sag, it is necessary to analyze the transient performance of a DFIG during the asymmetric voltage sag. In this paper, analyzed the influence of the asymmetric grid voltage to DFIG and the analysis method of the asymmetric voltage sag, and on the basis of positive and negative sequence mathematical model, analyzed the composition of stator output active and reactive power under the condition of asymmetric grid voltage. And built a DFIG asymmetric voltage drop simulation model of 1.5MW in MATLAB/Simulink, the simulation results shows that the stator voltage, current, active power and reactive power all present a double frequency ripple during the asymmetric voltage sag, consistent with theoretical analysis. It can provide theoretical basis for double-fed motor control strategy of asymmetric LVRT.
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Derkachev, S. V. "Microprocessor protection of electrical motors against phase failure in external power supply network." Vestnik IGEU, no. 1 (February 28, 2022): 46–53. http://dx.doi.org/10.17588/2072-2672.2022.1.046-053.

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Nonsymmetrical modes in the external power supply network during operation can be caused by several reasons: phase failure due to strong wind or glaciation of overhead power lines, wire burnout due to persistent short circuits, open phase automatic reclosing. In case of open phase condition, the external power supply network, synchronous and asynchronous electric motors are powered along the two phases that are in operation. It leads to the negative sequence current, which poses maximum danger for electric motors, since it causes additional heating and, as a result, premature damage. Therefore, the currently important goal of the project is to study transient processes of the motor load when an open phase mode occurs in the external power supply network and to design microprocessor protection of electrical motors against phase failure in the supply network. To achieve the goal, a computer simulation method is used, based on mathematical models of the elements of electrical network presented as the systems of differential equations in a three-phase coordinate system. The regularities of the flow of transient processes in synchronous and asynchronous electric motors in case of open phase modes in both the internal and external power supply networks have been established. Thus, it is possible to develop an algorithm of the operation of microprocessor protection of electrical motors against phase failure in the external power supply network. The proposed algorithm is based on monitoring the negative sequence current level and the absence of current in one of the phases at the section input. The obtained results show that the proposed algorithm to protect electrical motors against open phase modes in an external power supply network has a high selectivity. Its use as a starting element of the fast-acting automatic transfer switch device allows you to provide uninterrupted power supply for enterprises with a continuous technological process.
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Dissertations / Theses on the topic "Condition monitoring; negative sequence current; induction motor"

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Wu, Long. "Separating Load Torque Oscillation and Rotor Faults in Stator Current Based-Induction Motor Condition Monitoring." Diss., Georgia Institute of Technology, 2006. http://hdl.handle.net/1853/14545.

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Stator current spectral analysis techniques are usually used to detect rotor faults in induction machines. Magnetic field anomalies in the airgap due to the rotor faults result in characteristic side-band harmonic components in the stator current spectrum, which can be measured as rotor fault signatures. A position-varying load torque oscillation at multiples of the rotational speed, however, has exactly the same effect. Stator current harmonics due to a load torque oscillation often obscure and even overwhelm rotor eccentricity fault detection since the magnitude of load oscillation induced harmonics is usually much larger. Although previous research has suggested some methods to differentiate between these two effects, most of them rely heavily on the accurate estimation of motor parameters. The objective of this research is to develop a far more practical and computationally efficient method to detect rotor faults effectively in the presence of a load torque oscillation. A significant advantage of the proposed scheme is that it does not need any knowledge of motor parameters. The normalized negative sequence information induced by a mixed rotor eccentricity in the stator current or terminal voltage space vector spectra, serves as a reliable rotor fault indicator to eliminate load oscillation effects. Detailed airgap magnetic field analysis for an eccentric motor is performed and all machine inductance matrices as well as their derivatives are reformulated accordingly. Careful observation of these inductance matrices provides a fundamental understanding of motor operation characteristics under a fault condition. Simulation results based on both induction motor dynamic model and Maxwell 2D Finite Element Model demonstrate clearly the existence of the predicted rotor fault indicator. Extensive experimental results also validate the effectiveness and feasibility of the proposed detection scheme.
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Bakhri, Syaiful. "Detailed investigation of negative sequence current compensation technique for stator shorted turn fault detection of induction motors." Thesis, 2013. http://hdl.handle.net/2440/83536.

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Online condition monitoring is preferred specifically in critical induction machines for timely analysis of their health and to predict any incipient failures. Negative sequence current monitoring is one of the well-known condition monitoring applications that capable of identifying stator faults in induction motor as well as producing fast and reliable results using a simple measurement technique. However, the technique is sensitive to asymmetrical sources of negative sequence, not only due to motor faults but also due to the disturbances such as sensor calibration, inherent non-idealities (such as inherent machine asymmetries), external effects (such as load change and supply voltage unbalances). This thesis addresses the limitations in shorted turn fault detection while considering real system disturbances and non-linearities using a dynamic motor model which is also verified by the experimental studies. The thesis provides a comprehensive investigation of various negative sequence contributors such as measurement asymmetry, inherent asymmetry, voltage unbalance, shorted turn faults, eccentricity and broken rotor bar faults under load variations, and presents practical results. To allow accurate shorted turn fault detection, this thesis also provides an effective phasor compensation technique for these disturbances. A new detailed compensation by demonstrating step-by-step disturbance extraction to obtain the real negative sequence current due to shorted turn faults are also presented. It is demonstrated that this technique allows even a single stator shorted turn faults to be detected as well as successfully eliminating the effect of inherent asymmetry and voltage unbalances under motor load variations.
Thesis (Ph.D.) -- University of Adelaide, School of Electrical and Electronic Engineering, 2013
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Conference papers on the topic "Condition monitoring; negative sequence current; induction motor"

1

Sridhar, S., K. Uma Rao, K. S. Harish, and Raksha Umesh. "Condition monitoring of induction motor using negative sequence component and THD of the stator current." In 2016 IEEE 7th Power India International Conference (PIICON). IEEE, 2016. http://dx.doi.org/10.1109/poweri.2016.8077416.

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Long Wu, Bin Lu, Xianghui Huang, T. G. Habetler, and R. G. Harley. "Improved online condition monitoring using static eccentricity-induced negative sequence current information in induction machines." In 31st Annual Conference of IEEE Industrial Electronics Society, 2005. IECON 2005. IEEE, 2005. http://dx.doi.org/10.1109/iecon.2005.1569167.

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