Diagnostics of Damage to the Rotor of an Induction Machine Using the Method of Instantaneous Power Analysis

Authors

  • Marjola Puka Department of Electrotechnics, Polytechnic University of Tirana, Tirana, Albania.
  • Astrit Bardhi Department of Automation, Polytechnic University of Tirana, Tirana, Albania.
  • Alfred Pjetri Department of Automation, Polytechnic University of Tirana, Tirana, Albania.
  • Aldi Mucka Department of Electrical Power Systems, Polytechnic University of Tirana, Tirana, Albania.

DOI:

https://doi.org/10.48161/qaj.v4n1a263

Abstract

The relevance of the problem under study is that in the modern world, where induction machines are widely used in industry, early detection of rotor damage using the method of instantaneous power analysis is critical to maintaining uninterrupted equipment operation and reducing operating costs. The purpose of this study is to investigate and determine the effectiveness of the method of instantaneous power analysis for diagnosing rotor damage in induction machines to improve their reliability and reduce the risk of production failures. The methods used include the analytical method, classification method, functional method, statistical method, synthesis method. In today’s industry, asynchronous machines play a central role, creating a high demand for their reliable and safe operation. Malfunctions and failures in the operation of these machines can lead to serious downtime and considerable losses that affect the financial position of the company. One method of accurate fault diagnosis is to analyses the theoretical components added to the motor current. The analysis revealed that the locus of the space vector, instantaneous power, and sideband frequencies around the fundamental frequency indicate possible broken rotor cores of an induction machine. These components become key indicators for fault detection in induction machines. Furthermore, the experiments on a three-phase squirrel-cage induction confirmed the theoretical analysis, reinforcing the practical significance of the developed methodology for early diagnosis and improving equipment reliability, as well as reducing maintenance and repair costs. The practical significance lies in the development of a methodology that can be used in the industry for early diagnosis of rotor damage in induction machines, ensuring increased equipment reliability and reduced maintenance and repair costs.

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References

Chaban A; Łukasik Z; Popenda A; and Szafraniec A. Mathematical modelling of transient processes in an asynchronous drive with a long shaft including cardan joints. Energies 2021, Volume 14, no. 18, article no. 5692.

Suárez PJO; Sagot B; and Romary L. Asynchronous pipeline for processing huge corpora on medium to low resource infrastructures. Proceedings of the Workshop on Challenges in the Management of Large Corpora (CMLC-7); Mannheim: Leibniz-Institut für Deutsche Sprache, 2019; pp. 9-16.

Harish V; Ansari MM; Tewari D; Yadav AB; Sharma N; Bawarig S; García-Betancourt ML; Karatutlu A; Bechelany M; and Barhoum A. Cutting-edge advances in tailoring size, shape, and functionality of nanoparticles and nanostructures: A review. J Taiwan Institute Chem Eng 2023, Volume 149, article no. 105010.

Purbowaskito W;. Lan CY; and Fuh K. The potentiality of integrating model-based residuals and machine-learning classifiers: An induction motor fault diagnosis case. IEEE Transactions on Industrial Informatics, 2023. https://doi.org/10.1109/TII.2023.3299111

Gundewar SK; and Kane PV. Condition monitoring and fault diagnosis of induction motor. J Vib Eng Technol 2021, Volume 9, pp. 643-674.

Ur Rehman A; Jiao W; Sun J; Sohaib M; Jiang Y; Shahzadi M; and Khan MI. Efficient fault detection of rotor minor inter-turn short circuit in induction machines using wavelet transform and empirical mode decomposition. Sensors 2023, Volume 23, no. 16, article no. 7109.

Rangel-Magdaleno J; Peregrina-Barreto H; Ramirez-Cortes J; Morales-Caporal R; and Cruz-Vega I. Vibration Analysis of Partially Damaged Rotor Bar in Induction Motor under Different Load Condition Using DWT. Shock Vib 2016, Volume 2016, pp. 1-11. https://doi.org/10.1155/2016/3530464

Resendiz-Ochoa E; Morales-Hernandez LA; Cruz-Albarran IA; and Alvarez-Junco S. Induction Motor Failure Analysis using Machine Learning and Infrared Thermography. IEEE International Autumn Meeting on Power, Electronics and Computing (ROPEC), 2022. https://doi.org/10.1109/ropec55836.2022.10018653

Djagarov N; Enchev G; and Djagarova J. Simulation of Broken Rotor Bar Fault by Asymmetric Induction Motor Model. International Conference on Diagnostics in Electrical Engineering (Diagnostika), 2022. https://doi.org/10.1109/diagnostika55131.2022.9905121

Yatsugi K; Pandarakone SE; Mizuno Y; and Nakamura H. Common Diagnosis Approach to Three-Class Induction Motor Faults Using Stator Current Feature and Support Vector Machine. IEEE Access 2023, Volume 11, 24945–24952. https://doi.org/10.1109/access.2023.3254914

Sabir H; Ouassaid M; and Ngote N. An experimental method for diagnostic of incipient broken rotor bar fault in induction machines. Heliyon 2022, Volume 8, no. 3, article no. e09136. https://doi.org/10.1016/j.heliyon.2022.e09136

Martinez-Herrera AL; Ferrucho-Alvarez ER; Ledesma-Carrillo LM; Mata-Chavez RI; Lopez-Ramirez M; and Cabal-Yepez E. Multiple Fault Detection in Induction Motors through Homogeneity and Kurtosis Computation. Energies 2022, Volume 15, no. 4, article no. 1541. https://doi.org/10.3390/en15041541

Panov V. The scientific process of two interferometers (optical) development and the mitigation of external influence. Sci Her Uzhhorod Univ Ser Phys 2023, Volume 53, pp. 19-30.

Bence N; Lengyel A; and Tarics Z. A simple model for describing the minimum differential cross-section of elastic proton scattering on protons at high energies. Sci Her Uzhhorod Univ Ser Phys 2022, Volume 51, pp. 30-38.

Yang R; Zhang Z; and Chen Y. Analysis of vibration signals for a ball bearing-rotor system with raceway local defects and rotor eccentricity. Mechanism and Machine Theory 2022, Volume 169, article no. article no. 104594.

Tytarenko V; and Tychkov D. Simulation model of the information-measuring system of electrical characteristics of functional coatings of electronic devices. Bull Cherkasy State Technol Univ 2022, Volume 3, 14-22.

Sin Win EP. Urban Road Change Detection using Morphological Processing. Qubahan Academic J 2021, Volume 1, no. 1, pp. 57–61,

Sathasivam K; Garip I; Althahabi AM; Mohammed S; Alanssari AI; Mezaal YS; Ameen Sulaiman JM; and Alawsi T. An analysis of the design of a low rotational speed permanent magnet generator that uses radial flux. Elect Power Compon Syst 2023, Volume 51, no. 18, article no. 2171-2180.

Ehya H; Nysveen A; Nilssen R; and Liu Y. Static and dynamic eccentricity fault diagnosis of large salient pole synchronous generators by means of external magnetic field. IET Elect Power Appl 2021, Volume 15, no. 7, pp. 890-902.

Gritsyuk V; Nevliudov I; Zablodskiy M; and Subramanian P. Estimation of eddy currents and power losses in the rotor of a screw electrothermomechanical converter for additive manufacturing. Mach Energetics 2022, Volume 13, no. 2, pp. 41-49.

Trokhaniak O. Estimation of eddy currents and power losses in the rotor of a screw electrothermomechanical converter for additive manufacturing. Mach Energetics 2022, Volume 13, no. 3, pp. 92-98.

Deepak Selvakumar R; Wu J; Ding Y; and Alkaabi AK. Melting behavior of an organic phase change material in a square thermal energy storage capsule with an array of wire electrodes. Applied Thermal Engineering 2023, Volume 228, article no. 120492.

Thamer HL; Al-Lamey BT; and Al-Thammer D. Diagnosing of bearing faults in induction motor by adopting DWT-based artificial neural network (ANN). J Phys Conf Ser 2021, Volume 1773, article no. 012005.

Ranzinger L; Uhrig S; Hinterholzer R; and Öttl F. Failure diagnosis in rotating machines using fra involving the rotation angle of the rotor. 22nd International Symposium on High Voltage Engineering (ISH 2021); Xian: Institution of Engineering and Technology 2021; pp. 486-491.

Agus Sumantri B; Suliyanto S; and Darmawati D. Village Unit Cooperatives on Dynamic Capability and Creative Capability Adaptation to Innovation Performance: The Role of Competitive Advantage. QUBAHAN ACADEMIC J 2023, Volume 3, no. 4, pp. 245-261.

Dadabaev ST; Islomovna TM; and Saidulloevna MD. Modeling of starting transition processes of asynchronous motors with reduced voltage of the supply network. Eur J Elect Eng 2020, Volume 22, no. 1, pp. 23-28.

Pirmatov N; and Panoev A. Frequency control of asynchronous motors of looms of textile enterprises. E3S Web Conf 2020, Volume 216, article no. 01120.

Mustafayeva E; Karimova N; Rahimova K; Novruzova U; İsmayilzade M; and Alirzayeva L. Mathematical modeling of damage of a cylindrically isotropic thick pipe under a complex stress state. Glob Stoch Anal 2022, Volume 9, no. 1, pp. 47-55.

Amidu MA; Ali M; Alkaabi AK; and Addad Y. A critical assessment of nanoparticles enhanced phase change materials (NePCMs) for latent heat energy storage applications. Sci Rep 2023, Volume 13, no. 1, article no. 7829.

Li Z; Che S; Wang P; Du S; Zhao Y; Sun H; and Li Y. Implementation and analysis of remanufacturing large-scale asynchronous motor to permanent magnet motor under circular economy conditions. J Clean Prod 2021, Volume 294, article no. 126233.

Qinglong W; Changzhou Y; and Shuying Y. Indirect field oriented control technology for asynchronous motor of electric vehicle. 2020 IEEE International Conference on Power, Intelligent Computing and Systems (ICPICS); Shenyang: IEEE, 2020; pp. 673-677.

Fayzullayev JS; and Jurayeva KK. The transfer function of a traction asynchronous motor controlled by a four-square converter. IOP Conf Ser Mater Sci Eng 2020, Volume 734, article no. 012195.

Badie Mahmood K; Ali Shaaban F; and Mohammed Sleman R. Diagnosing the statistical rates of traffic accidents in Dohuk Governorate during the period (2011-2020) / analytical study. QUBAHAN ACADEMIC J 2021, Volume 1, no. 2, pp. 47-54.

Ugwiri MA; Carratù M; Pietrosanto A; Paciello V; and Lay-Ekuakille A. Vibrations measurement and current signatures for fault detection in asynchronous motor. 2020 IEEE International Instrumentation and Measurement Technology Conference (I2MTC). Dubrovnik: IEEE, 2020; pp. 1-6.

Hrechko Ya; Sereda I; Babenko Ie; and Azarenkov M. Thermionic coating method with preliminary bombardment of the substrate surface with a stream of low energy ions. Sci Her Uzhhorod Univ Ser Phys 2023, no. 53, 9-8. https://doi.org/10.54919/physics/53.2023.09.

Pavliuk L. Electron modelling in conjunction with vacuum modelling. Sci Her Uzhhorod Univ Ser Phys 2022, no. 52, 27-35. https://doi.org/10.54919/2415-8038.2022.52.27-35.

Published

2024-02-23

How to Cite

Puka, M., Bardhi, A. ., Pjetri, A. ., & Mucka, A. . (2024). Diagnostics of Damage to the Rotor of an Induction Machine Using the Method of Instantaneous Power Analysis . Qubahan Academic Journal, 4(1), 150–166. https://doi.org/10.48161/qaj.v4n1a263

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