ASENKRON MOTOR EKSENEL KAÇIKLIK ARIZALARININ SHANNON ENTROPİSİ İLE ANALİZİ

Sanayide ve işletmelerde yoğun bir şekilde kullanılan asenkron motorların yaygın arızalarından bir tanesi de motorlarda meydana gelen eksenel kaçıklık arızalarıdır. Bu çalışmada üç fazlı sincap kafesli bir asenkron motorun eksenel kaçıklık arızaları Shannon entropisi ile incelendi. Eksenel kaçıklık arızaları asenkron motorun her iki kapağının iç kısmındaki rulman yatakları genişletilerek oluşturuldu. Genişletilen rulman yataklarına üç boyutlu yazıcıdan elde edilen bir burç yerleştirilerek rotorun eksenden 0,20 mm kaçık olarak çalışması sağlandı. Asenkron motor hem sağlam olarak hem de eksenel kaçıklık arızalı olarak %25, %50, %75 ve %100 yük altında çalıştırıldı. Her test durumu için stator akımı ve titreşim sinyalleri kaydedildi. Stator akımı ve titreşim sinyallerinin doğruluğu Fourier analizi ile kontrol edildi. Eksenel kaçıklık arızasının etkisi, motorun stator akımı ve titreşim sinyallerinin entropi değerleri hesaplanarak incelendi. Sağlam ve eksenel kaçıklık arızalı motorun akım ve titreşim sinyallerinin entropi değerleri karşılaştırıldı. Elde edilen sonuçlar; eksenel kaçıklık arızalarının titreşim sinyali entropi değerinde ciddi bir artışa sebep olduğu ancak stator akımı entropi değerinde anlamlı bir değişim göstermediğini göstermektedir. Elde edilen sonuçlardan titreşim sinyalleri entropi analizinin eksenel kaçıklık arızalarının tespitinde kullanılabileceği görülmektedir.

Anahtar Kelimeler:

Asenkron Motor, Eksenel Kaçıklık Arızaları, Entropi Analizi, Shannon Entropisi

Analysis of Eccentric Faults of Induction Motor by Using Shannon Entropy

One of the common faults of induction motors which are extensively used in industry and commercial applications is the axial misalignment faults in the motor. In this study, axial misalignment faults of a three-phase squirrel-cage induction motor was analyzed by Shannon entropy. The axial misalignment fault was created by the enlarging of the bearing shell inside the two end-bells of the induction motor. A special designed material manufactured by a 3D printer was placed inside the enlarged bearing shell. In this way, a 0.20 mm offset was created. Induction motor was tested both healthy and with axial misalignment fault under 25%, 50%, 75% and 100% loading conditions. The stator current and vibration signals were recorded for each test case. The validity of the stator current and vibration signals was checked by Fourier analysis. The axial offset effect was evaluated by calculating the entropy values of the stator current and vibration signals of the motor. Then entropy values were calculated for both the healthy and faulty motor. The results show that the axial misalignment faults cause an increase in the entropy value of the vibration signal significantly. The change in the entropy value of the stator current due to axial misalignment faults is not significant. Therefore it is shown that the entropy analysis of vibration signals can be used in the analysis eccentric fault of induction motors.

Keywords:

Induction Motor, Axial Misalignment Faults, Entropy Analysis, Shannon Entropy,

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Bafroui, H. H., ve Ohadi, A. (2014) Application of wavelet energy and Shannon entropy for feature extraction in gearbox fault detection under varying speed conditions, Neurocomputing, 133, 437-445. doi:0.1016/j.neucom.2013.12.018
Benbouzid, M. E. H. (2000) A review of induction motors signature analysis as a medium for faults detection, IEEE transactions on industrial electronics, 47(5), 984-993. doi:10.1109/41.873206
Bessous, N., Zouzou, S. E., Sbaa, S., ve Bentrah, W. (2017) A comparative study between the MCSA, DWT and the vibration analysis methods to diagnose the dynamic eccentricity fault in induction motors, 6th International Conference on Systems and Control (ICSC), 414-421. doi:10.1109/ICoSC.2017.7958655
Cabal-Yepez, E., Romero-Troncoso, R. J., Garcia-Perez, A., Osornio-Rios, R. A., ve Alvarez-Salas, R. (2011. Multiple fault detection through information entropy analysis in ASD-fed induction motors, 8th IEEE Symposium on Diagnostics for Electrical Machines, Power Electronics & Drives, 391-396. doi:10.1109/DEMPED.2011.6063653
Cabal-Yepez, E., Romero-Troncoso, R. J., Garcia-Perez, A., ve Osornio-Rios, R. A. (2012) Single-parameter fault identification through information entropy analysis at the startup-transient current in induction motors, Electric Power Systems Research, 89, 64-69. doi:10.1016/j.epsr.2012.02.016
Camarena-Martinez, D., Valtierra-Rodriguez, M., Amezquita-Sanchez, J. P., Granados-Lieberman, D., Romero-Troncoso, R. J., ve Garcia-Perez, A. (2016) Shannon Entropy and-Means Method for Automatic Diagnosis of Broken Rotor Bars in Induction Motors Using Vibration Signals, Shock and Vibration. 2016, 1-10. doi:10.1155/2016/4860309
Dinçer, G. (2005) Entropi Kavramının İstatistiksel Bazı Uygulamaları, Yüksek Lisans Tezi, Yıldız Teknik Üniversitesi Fen Bilimleri Enstitüsü, İstanbul.
Faiz, J., ve Moosavi, S. M. M. (2016) Eccentricity fault detection–From induction machines to DFIG—A review, Renewable and Sustainable Energy Reviews, 55, 169-179. doi:10.1016/j.rser.2015.10.113
Glowacz, A., Glowacz, W., Glowacz, Z., ve Kozik, J. (2018) Early fault diagnosis of bearing and stator faults of the single-phase induction motor using acoustic signals, Measurement, 113, 1-9. doi:10.1016/j.measurement.2017.08.036
Hegde, V., ve Maruthi, G. S. (2012) Experimental investigation on detection of air gap eccentricity in induction motors by current and vibration signature analysis using non-invasive sensors, Energy Procedia, 14, 1047-1052.
Kompella, K. D., Mannam, V. G. R., ve Rayapudi, S. R. (2016) DWT based bearing fault detection in induction motor using noise cancellation, Journal of Electrical Systems and Information Technology, 3(3), 411-427. doi:10.1016/j.egypro.2011.12.1053
Köse, R. K. (2004). Makine arızalarının belirlenmesinde titreşim analizi, Mühendis ve Makine Dergisi, 45, 538.
Li, S., Li, Y., ve Sarlioglu, B. (2016) Rotor unbalanced magnetic force in flux-switching permanent magnet machines due to static and dynamic eccentricity, Electric Power Components and Systems, 44(3), 336-342. doi:10.1080/15325008.2015.1111469
Obaid, R. R., ve Habetler, T. G. (2003) Current-based algorithm for mechanical fault detection in induction motors with arbitrary load conditions, 38th IAS Annual Meeting on Conference Record of the Industry Applications Conference, 2, 1347-1351. doi:10.1109/IAS.2003.1257726
Ojaghi, M., & Mohammadi, M. (2017) Unified modeling technique for axially uniform and nonuniform eccentricity faults in three-phase squirrel cage induction motors, IEEE Transactions on Industrial Electronics, 65(7), 5292-5301. doi:10.1109/TIE.2017.2760280
Pan, S., Han, T., Tan, A. C., & Lin, T. R. (2016). Fault diagnosis system of induction motors based on multiscale entropy and support vector machine with mutual information algorithm, Shock and Vibration. doi:10.1155/2016/5836717
Polat, A., Ertuğrul, Y. D., ve Ergene, L. T. (2015) Static, dynamic and mixed eccentricity of induction motor, IEEE 10th International Symposium on Diagnostics for Electrical Machines, Power Electronics and Drives (SDEMPED), 284-288. doi:10.1109/DEMPED.2015.7303703