Fault Detection Experiment of Unbalanced Voltage and Air Gap Eccentricity on Induction Motor Using a Flux Sensor

Nurul Husnah, Dimas Anton Asfani, I Made Yulistya Negara

Abstract


Abstract— The induction motor is one of the popular equipment used in various types of industrial sectors. It is necessary to monitor the condition of the induction motor to maintain its safety and performance of the induction motor. The most common damage to the induction motor is bearing failure reaches 40% resulting in air gap eccentricity. Most of the research to detect the occurrence of air gap eccentricity is carried out based on the analysis of motor current signals. To overcome the disadvantages of the above methods, the detection of air gap eccentricity using a sensor flux that can detect leakage flux from the motor body and the fault detection results by measuring the flux signal analyzed. Flux analysis using the Fast Fourier Transform (FFT) algorithm in balanced and unbalanced voltage conditions. Induction motor failure analysis compared normal motor conditions with an eccentricity of 0.1 mm and 0.2 mm. Eccentricity detection is done by monitoring the amplitude that emerges in the frequency spectrum with notice of the threshold. Detection results from the eccentricity fault showed that success is detected 100% using a sensor flux on unbalanced voltage (under voltage 5%) at a full-load condition.

Full Text:

PDF

References


N. R. Alham, D. A. Asfani, I. M. Yulistya N, and B. Y. A. N. Dewantara, “Analysis of Load and Unbalance Voltage on Air gap Eccentricity in detection of Three Phase Induction Motor,” Int. Conf. Inf. Commun. Technol., pp. 566–571, 2018.

D. G. Dorrell, W. T. Thomson, S. Member, and S. Roach, “Analysis of Airgap Flux, Current, and Vibration Signals as a Function of the Combination of Static and Dynamic Airgap Eccentricity in 3-Phase Induction Motors,” IEEE Trans. Ind. Appl., vol. 33, no. 1, pp. 24–34, 1997.

D. Hwang et al., “Detection of air-gap eccentricity and broken-rotor bar conditions in a squirrel-cage induction motor using the radial flux sensor,” Am. Inst. Physics., vol. 131, no. 2008, pp. 129–132, 2012.

M. Djamal, Suyatno, Yulkifli, and R. N. Setiadi, “SENSOR MAGNETIK FLUXGATE KARAKTERISTIK DAN APLIKASINYA,” J. Sains Mater. Indones, pp. 207–214, 2007.

F. E. Prahesti, D. A. Asfani, I. Made Yulistya Negara, and B. Y. Dewantara, “Three-Phase Induction Motor Short Circuit Stator Detection Using an External Flux Sensor,” Proc. - 2020 Int. Semin. Intell. Technol. Its Appl. Humanification Reliab. Intell. Syst. ISITIA 2020, pp. 375–380, 2020.

C. T. Kowalski and W. Kanior, “Effectiveness of the frequency analysis of the stator current in the rotor fault detection of induction motors,” Proc. IEEE Int. Conf. Ind. Technol., pp. 1–5, 2008.

R. Romary, R. Corton, D. Thailly, and J. F. Brudny, “Induction machine fault diagnosis using an external radial flux sensor,” Eur. Phys. J. Appl. Phys., vol. 132, pp. 125–132, 2005.

O. Vitek, M. Janda, V. Hajek, and P. Bauer, “Detection of eccentricity and bearings fault using stray flux monitoring,” SDEMPED 2011 - 8th IEEE Symp. Diagnostics Electr. Mach. Power Electron. Drives, pp. 456–461, 2011.

I. Nurhadi, A. I. Mahyuddin, and M. Ahmarudin, “Ciri Getaran Mekanik dan Arus Catu Pada Motor Listrik Induksi 3-Fasa Akibat Eksentrisitas Celah Udara.” Departemen Teknik Mesin, FTI-ITB, Bandung, pp. 18–26, 1997.

H. Henao, G.-A. Capolino, and C. Demian, “A Frequency-Domain Detection of Stator Winding Faults in Induction Machines Using an External Flux Sensor,” IEEE Trans. Ind. Appl., vol. 39, no. 5, pp. 1272–1279, 2003, doi: 10.1109/icit.2004.1490276.

I. Ozelgin, “Analysis of magnetic flux density for airgap eccentricity and bearing faults,” Int. J. Syst. Appl. Eng. Dev., vol. 2, no. 4, pp. 162–169, 2009

Hufri, Yulkifli, and M. Djamal, “Desain dan Pengembangan Sensor Magnetik Fluxgate Sensitivitas Tinggi Menggunakan Model Ellips-Multicore Double Pick-up dan Aplikasinya,” Padang, 2009.

S. M. A. Cruz and A. J. M. Cardoso, “Multiple reference frames theory: A new method for the diagnosis of stator faults in three-phase induction motors,” IEEE Trans. Energy Convers., vol. 20, no. 3, pp. 611–619, 2005, doi: 10.1109/TEC.2005.847975.

R. M. Utomo, I. Made Yulistya Negara, D. A. Asfani, and N. R. Alham, “Wavelet Filter Selection Analysis for Air Gap Eccentricity in Three Phase Induction Motor,” Proceeding - 2018 Int. Semin. Intell. Technol. Its Appl. ISITIA 2018, pp. 199–204, 2018.

B. Yazici and G. B. Kliman, “An adaptive statistical time-frequency method for detection of broken bars and bearing faults in motors using stator current,” IEEE Trans. Ind. Appl., vol. 35, no. 2, pp. 442–452, 1999.


Refbacks

  • There are currently no refbacks.


Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.