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Open-circuit fault diagnosis in three-phase induction motor using model-based technique

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
The presence of an open-circuit fault subjects a three-phase induction motor to severely unbalanced voltages that may damage the stator windings consecutively causing total shutdown of systems. Unplanned downtime is very costly. Therefore, fault diagnosis is essential for making a predictive plan for maintenance and saving the required time and cost. This paper presents a model-based diagnosis technique for diagnosing an open-circuit fault in any phase of a three-phase induction motor. The proposed strategy requires only current signals from the faulty machine to compare them with the healthy currents from an induction motor model. Then the errors of comparison are used as an objective function for a genetic algorithm that estimates the parameters of a healthy model, which they employed to identify and localize the fault. The simulation results illustrate the behaviours of basic parameters (stator and rotor resistances, self-inductances, and mutual inductance) and the number of stator winding turn parameters with respect to the location of an open-circuit fault. The results confirm that the number of stator winding turns are the useful parameters and can be utilized as an identifier for an open-circuit fault. The originality of this work is in extracting fault diagnosis features from the variations of the number of stator winding turns.
Rocznik
Strony
815--827
Opis fizyczny
Bibliogr. 16 poz., rys., tab., wz.
Twórcy
  • Department of Electrical Engineering, College of Engineering University of Baghdad Baghdad, Iraq
  • Department of Electrical Engineering, College of Engineering University of Baghdad Baghdad, Iraq
Bibliografia
  • [1] Sobański P., Orłowska-Kowalska T., Detection of single and multiple IGBTs open-circuit faults in a field-oriented controlled induction motor drive, Archives of Electrical Engineering, vol. 66, no. 1, pp. 89–104 (2017).
  • [2] Khalid Abdulhassan, Adel Obed, Sadiq Hassan, Stator Faults Diagnosis and Protection in 3-Phase Induction Motor Based on Wavelet Theory, Journal of Engineering, vol. 23, no. 11, pp. 130–149 (2017).
  • [3] Arkan M., Perovic D. K., Unsworth P., Online stator fault diagnosis in induction motors, IEE Proceedings-Electric Power Application, vol. 148, no. 6, pp. 537–547 (2001).
  • [4] M’hamed Drif, Heonyoung Kim, Jongwan Kim, Sang Bin Lee, Antonio J. Marques Cardoso, Active and Reactive Power Spectra-Based Detection and Separation of Rotor Faults and Low-Frequency Load Torque Oscillations, IEEE Transactions on Industry Applications, vol. 53, no. 3, pp. 2702-2710 (2017).
  • [5] Ali Karimabadi, Mohammad Ebrahim Hajiabadi, Ebadollah Kamyab, Prioritization approach for circuit breakers to equip with condition monitoring devices, Archives of Electrical Engineering, vol. 69, no. 2, pp. 403–422 (2020).
  • [6] Subhasis Nandi, Hamid A. Toliyad, Xiaodong Li, Condition Monitoring and Fault Diagnosis of Electrical Motors – A Review, IEEE Transactions on Energy Conversion, vol. 20, no. 4, pp. 719-729 (2005).
  • [7] Fernando F. J. T. E., Silva A.M., Almeida A. T., Single-Phasing Protection of Line-Operated Motors of Different Efficiency Classes, IEEE Transactions on Industry Applications, pp. 1–14 (2018), DOI: 10.1109/TIA.2018.2797884.
  • [8] Mohamoud Omran A. Alamyal, Evaluation of Stochastic Optimisation Algorithms for Induction Machine Winding Fault Identification, PhD Thesis, School of Electrical and Electronic Engineering, Newcastle University, United Kingdom (2012).
  • [9] Mahadev Kokare, Chandle J.O., Rahul Kavathe, Mayur Deokar, Fuzzy Logic Based Fault Diagnosis of Induction Motor Using MATLAB, International Journal of Research and Scientific Innovation, vol. V, iss. Vl, pp. 149–152 (2018).
  • [10] Rama Hammo, Faults Identification in Three-Phase Induction Motors Using Support Vector Machines, Master of Technology Management Plan II Graduate Projects, Browling Green State University, Ohio (2014).
  • [11] Arkan M., Kostic-perovic D., Unsworth P. J., Modelling and simulation of induction motors with inter-turn faults for diagnostics, Electric Power Systems Research, vol. 75, pp. 57–66 (2005).
  • [12] Ding S. X., Model-based Fault Diagnosis Techniques, Springer-Verlag (2008).
  • [13] Ladoukakis O., Tsitmidelis S., Ktena A., A New Genetic Algorithm for Motor Parameter Estimation, Proceedings of the 10th WSEAS International Conference on SYSTEMS, pp. 555–558 (2006).
  • [14] Hamid Reza Mohammadi, Ali Akvahan, Parameter Estimation of Three-Phase Induction Motor Using Hybrid of Genetic Algorithm and Particle Swarm Optimization, Journal of Engineering, pp. 1–6 (2014), DOI: 10.1155/2014/148204.
  • [15] Król K., Machczyński W., Optimization of electric and magnetic field intensities in proximity of power lines using genetic and particle swarm algorithms, Archives of Electrical Engineering, vol. 67, no. 4, pp. 829–843 (2018).
  • [16] Vasconcelos J. A., Ramírez J. A., Takahashi R. H. C., Saldanha R. R., Improvements in Genetic Algorithms, IEEE Transactions on Magnetics, vol. 37, no. 5, pp. 3414–3417 (2001).
Uwagi
Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2020).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-90c2569c-ec1b-47e9-85a7-78835ab687fb
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