Bearing Damage Detection Based on Sound Signal

Abstract:

This paper presents a new method in damage detection by taking the sound signals of the rolling bearings in different levels. The tested bearing was put on the end of the shaft rotated by permanent magnet synchronous motor. The sound signal produced by this rig was recorded separately for each bearing condition with the same experimental environment. The sound data signals are compared each other. Based on the cross-correlation analysis, the recorded sound signal proved that the signals were recorded with the same environment. The power spectra calculation has shown different harmonic frequencies according to various bearing conditions. The total power of the sound is decreased along with the increasing damage. This is also confirmed by the auto-correlation of each sound signal that shows the appearance of the sounds impulse repetition with a wider period.

• Periodical: Applied Mechanics and Materials (Volumes 548-549)
• Pages: 698-702
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.548-549.698
• Online since: April 2014
• Authors: Muhammad Aswin*, I.N.G. Wardana, Yudy Surya Irawan, Hadi Suyono
• Keywords: Bearing, Correlations, Damage Detection, Sound Signal, Spectra

References

[1] 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).

DOI: 10.1006/mssp.2001.1462

[2] Mba, D.: Acoustic Emissions and Monitoring Bearing Health. Tribology Transaction Vol. 46 pp.447-451 (2003).

DOI: 10.1080/10402000308982649

[3] 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).

DOI: 10.1109/apec.2009.4802777

[4] 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 p.1537–1571 (2006).

DOI: 10.1016/j.ymssp.2004.10.013

[5] 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).

DOI: 10.1109/08ias.2008.26

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

DOI: 10.1109/te.2002.808234