Time Domain Analysis of Sound Signals for Bearing Damage Identification

Muhammad Aswin, ING Wardana, Yudy S. Irawan, Hadi Suyono

Abstract


Time domain analysis requires less computational time compared to the frequency domain. Analysis is performed directly on the signal without any conversion at all. This paper describes high-frequency signal analysis on sound produced by rotated bearing. Three bearing conditions - normal, damaged, and badly damaged - was chosen to obtain the characteristics of high frequency sound. From the entire spectrum of the recorded sound, the higher frequency range looks very different for the three conditions bearing. Phisically, more damage rotated bearing, the disturbance sound heard more loudly. Bearings were rotated at various rpm, from low to high, to ensure the similarities and differences in characteristics. Average energy and standard deviation were calculated as bearing damage indication.

Keywords


bearing; damage identification; sound signal; time domain.

References


Samanta, B., Al-Balushi, K.R, “Artificial Neural Network Based Fault Diagnosis of Rolling Element Bearings Using Time-Domain Features”. Journal of Sound and Vibration Vol. 12 Part. 2 pp 317-328 (2003).

Mba, D., “Acoustic Emissions and Monitoring Bearing Health”. Tribology Transaction Vol. 46 pp 447-451 (2003).

Rosero, J., L. Romeral, E. Rosero, J. Urresty, “Fault Detection in Dynamic Conditions by Means of Discrete Wavelet Decomposition for PMSM Running Under Bearing Damage”. Twenty-Fourth Annual IEEE Applied Power Electronics Conference and Exposition. Washington, DC: IEEE Press. Institute of Electrical and Electronics Engineers, pp. 951-956 (2009).

Al-Ghamd, Abdullah M, dan David Mba, “A comparative experimental study on the use of acoustic emission and vibration analysis for bearing defect identification and estimation of defect size”. Journal of Mechanical Systems and Signal Processing Vol. 20 pp.1537–1571 (2006).

Bellini, A., Fabio Immovilli, Ricardo Rubini, “Diagnosis of Bearing Fault in Induction Machines by Vibration or Current Signal: a Critical Comparison”. IEEE Transactions on Industry Applications (Impact Factor: 1.66). 09 (2010).

McInerny, S.A., Dai, Y, “Basic Vibration Signal Processing for Bearing Fault Detection”. IEEE Transaction on Education Vol. 46 No. 1 (2003).

Aswin, M., Wardana, I.N.G., Irawan, Y.S., Suyono, H, “Bearing Damage Detection Based on Sound Signal”. Applied Mechanics and Materials Vols. 548-549 (2014) pp 698-702 (2014).


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