Czasopismo | PRZEGLĄD ELEKTROTECHNICZNY | Rocznik 2016 - zeszyt 11

Experimental Comparison of Vibration and Acoustic Emission Signal Analysis Using Kurtosis-Based Methods for Induction Motor Bearing Condition Monitoring

10.15199/48.2016.11.51

nr katalogowy: 101993
10.15199/48.2016.11.51

Vibration and acoustic emission (AE) signal measurement are established tools in condition monitoring of bearings. This paper presents a comparison between two statistical methods, i.e. kurtosis, and another kurtosis based method called I-kaz using simultaneous signal of vibration and AE. The existence of harmonics fault frequencies in envelope spectrums also have been discussed. The results reveal that both signals are suitable for induction motor bearing fault detection. Streszczenie. W artykule przedstawiono porównanie dwóch metod statystycznych, kurtozy oraz I-kaz używająnych do diagnostyki łożyskowania maszyn elektrycznych. Jako sygnały diagnostyczne wykorzystuuje się pomiar wibracji i emisji akustycznej.(Eksperymentalne porównanie drgań i analizy sygnałów emisji akustycznej do monitorowania stanu łożysk). Keywords: bearing fault, kurtosis, I-kaz. Słowa kluczowe: monitorowanie stanu łożyska, kurtoza, I-kaz. 1. Introduction Bearing is one of important components in rotating machines that enable smooth acceleration and reduce friction. Ball and roller bearing are common type of bearing used in induction motors. Normally, an induction motor has two bearings supporting the rotor shaft; at the fan-end side, and at the drive-end side. The faulty bearing can cause major defects to motor if not fixed in a timely manner. The common failure observed in bearing elements are inner race fault and outer race fault. Vibration analysis is the most widely used technique for fault detection of rotating machineries and components such as bearings and gears. As vibration can be represented by the displacement, velocity or acceleration, any sensor that measure any of these variables can be used. Piezoelectric accelerometer is the most popular detector used to measure vibration because of rugged, small and relatively inexpensive [1]. Therefore, this study focused on acceleration measurement using an accelerometer. Acoustic emission (AE) is the p[...]

Bibliografia

[1] R. Bogue, “Sensors for condition monitoring: a review of technologies and applications," Sens. Rev., vol. 33, no. 4, pp. 295-299, 2013.
[2] Y. He, X. Zhang, and M. I. Friswell, “Defect Diagnosis for Rolling Element Bearings Using Acoustic Emission," Journal of Vibration and Acoustics, vol. 131, no. 6. p. 061012, 2009.
[3] S. Al-Dossary, R. Hamzah, and D. Mba, “Observations of changes in acoustic emission waveform for varying seeded defect sizes in a rolling element bearing," Appl. Acoust., vol. 70, no. 1, pp. 58-81, 2009.
[4] A. M. Al-Ghamd and D. Mba, “A comparative experimental study on the use of acoustic emission and vibration analysis for bearing defect identification and estimation of defect size," Mech. Syst. Signal Process., vol. 20, no. 7, pp. 1537-1571, 2006. 212 PRZEGLĄD ELEKTROTECHNICZNY, ISSN 0033-2097, R. 92 NR 11/2016
[5] B. Eftekharnejad, M. R. Carrasco, B. Charnley, and D. Mba, “The application of spectral kurtosis on Acoustic Emission and vibrations from a defective bearing," Mech. Syst. Signal Process., vol. 25, no. 1, pp. 266-284, 2011.
[6] X. Liu, X. Wu, and C. Liu, “A comparison of acoustic emission and vibration on bearing fault detection," in 2011 International Conference on Transportation, Mechanical, and Electrical Engineering (TMEE), 2011, pp. 922-926.
[7] N. Tandon and A. Choudhury, “A review of vibration and acoustic measurement methods for the detection of defects in rolling element bearings," Tribol. Int., vol. 32, no. 1999, pp. 469-480, 2000.
[8] D. Dyer and R. Stewart, “Detection of Rolling Element Bearing Damage by Statistical Vibration Analysis," J. Mech. Des., vol. 100, no. 2, pp. 229-235, 1978.
[9] W. Guo, P. W. Tse, and A. Djordjevich, “Faulty bearing signal recovery from large noise using a hybrid method based on spectral kurtosis and ensemble empirical mode decomposition," Meas. J. Int. Meas. Confed., vol. 45, no. 5, pp. 1308-1322, 2012.
[10] V. C. M. N. Leite, J. Guedes, G. Francimeire, C. Veloso, L. Eduardo, S. Member, G. Lambert-torres, E. L. Bonaldi, L. Ely, and D. L. De Oliveira, “Detection of Localized Bearing Faults in Induction Machines by Spectral Kurtosis and Envelope Analysis of Stator Current," IEEE Trans. Ind. Electron., vol. 62, no. 3, pp. 1855-1865, 2015.
[11] X. Zhang, J. Kang, L. Xiao, J. Zhao, and H. Teng, “A New Improved Kurtogram and Its Application to Bearing Fault Diagnosis," Shock Vib., vol. 2015, p. 22 pages, 2015.
[12] Y. Lei, J. Lin, Z. He, and Y. Zi, “Application of an improved kurtogram method for fault diagnosis of rolling element bearings," Mech. Syst. Signal Process., vol. 25, no. 5, pp. 1738-1749, Jul. 2011.
[13] M. Z. Nuawi, M. J. M. Nor, N. Jamaludin, S. Abdullah, F. Lamin, and C. K. E. Nizwan, “Development of integrated Kurtosis-based Algorithm for Z-filter technique," J. Appl. Sci., vol. 8, no. 8, pp. 1541-1547, 2008.
[14] N. I. I. Mansor, M. J. Ghazali, M. Z. Nuawi, and S. E. M. Kamal, “Monitoring bearing condition using airborne sound," Int. J. Mech. Mater. Eng., vol. 4, no. 2, pp. 152-155, 2009.
[15] M. Z. Nuawi, S. Abdullah, A. R. Ismail, R. Zulkifli, M. K. Zakaria, and M. F. H. Hussin, “A Study on Ultrasonic Signals Processing Generated From Automobile Engine Block Using Statistical Analysis," WSEAS Trans. Signal Process., vol. 4, no. 5, pp. 279-288, 2008.
[16] S. Abdullah, M. Z. Nuawi, M. Z. Nopiah, and A. Ariffin, “Study on correlation between strain and vibration signal using hybrid I-Kaz method," Contin. Mech. Fluids, Heat, vol. 6, no. 3, pp. 79-88, 2010.
[17] M. Z. Nuawi, F. Lamin, A. R. Ismail, S. Abdullah, and Z. Wahid, “A Novel Machining Signal Filtering Technique: Znotch Filter," World Acad. Sci. Eng. Technol. 54, vol. 3, no. 6, pp. 24-29, 2009.
[18] M. A. F. Ahmad, M. Z. Nuawi, S. Abdullah, Z. Wahid, Z. Karim, and M. Dirhamsyah, “Development of Tool Wear Machining Monitoring Using Novel Statistical Analysis Method, I-kazTM," Procedia Eng., vol. 101, pp. 355-362, 2015.
[19] J. A. Ghani, M. Rizal, A. Sayuti, M. Z. Nuawi, M. N. Ab. Rahman, and C. H. Che Haron, “New Regression Model and I-Kaz Method for Online Cutting Tool Wear Monitoring," World Acad. Sci. Eng. Technol. 60, no. 2008, pp. 420-425, 2009.
[20] M. B. Ali, S. Abdullah, M. Z. Nuawi, M. M. Padzi, and K. A. Zakaria, “Experimental Analysis of an Instrumented Charpy Impact Using Statistical Study Based Data Analysis," Int. J. Mech. Mater. Eng., vol. 6, no. 2, pp. 260-268, 2011.

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