Radial Ball Bearing Inner Race Defect Width Measurement using Analytical Wavelet Transform of Acoustic and Vibration Signal
In the present work, an experiment is carried out with a customized test setup where the seeded defects are introduced in the form of an axial groove on the inner race of a radial ball bearing. The nature of the acoustic and vibration signal bursts, and their correlation with the inner race defects, are established and estimated. Experimental investigation reveals that the analytical wavelet transform (AWT) is an effective tool for analyzing the acoustic and vibration signals, transmitted from the bearing, in order to characterize and measure the defect size. In the recent work, AWT followed by the time marginal integration (TMI) have been implemented on acoustic and vibration signals of a defective radial bearing. Size of the defect in the inner race of bearing is corroborated well with AWT scalogram. The segregation of the defect is carried out on TMI graph across the highest amplitude spike, which is due to signal burst (due to a contact of ball with bearing inner race defect). This manual demarcation on TMI graph in time axis provides the time duration (contact between a ball and the inner race defect). Using this time duration of the ball passed over bearing inner race defect, RPM of shaft mounted across bearing, and the fundamental train frequency, the defect width is estimated. The deviation of the measured width from the actual, using the proposed method, is sought below 5%. Summarizing, the proposed method can be reckoned a suitable and reliable measurement of radial bearing inner race defect width from acoustic and vibration signal.
Orhan, S., Akturk, N., Celik, V. (2006). Vibration monitoring for defect diagnosis of rolling element bearings as a predictive maintenance tool: Comprehensive case studies. NDT&E International, 39, 293-298.
Zarei, J., Poshtan, J. (2009). An advanced Park's vectors approach for bearing fault detection. Tribology International, 42, 213-219.
National Instruments. (2007). LabVIEW - Advance Digital Signal Processing User Manual.
Ban, J. E., Rho, B. H., Kim, K. W. (2007). A study on the sound of roller bearings operating under radial load. Tribology International, 40, 21-28.
Kumar, R., Jena, D. P., Bains, M. (2010). Identification of inner race defect in radial ball bearing using acoustic emission and wavelet analysis. In ISMA 2010 : International Conference on Noise and Vibration Engineering, 20-22 September 2010. Leuven, Belgium, 2883-2891.
Messer, S. R., Agzarian, J., Abbott, D. (2011). Optimal wavelet denoising for phonocardiograms. Microelectronics Journal, 32, 931-941.
Al-Ghamd, M., Mba, D. (2006). A comparative experimental study on the use of acoustic emission and vibration analysis for bearing defect identification and estimation of defect size. Mechanical Systems and Signal Processing, 20, 1537-1571.
Bozchalooi, S., Liang, M. (2008). A joint resonance frequency estimation and in-band noise reduction method for enhancing the detectability of bearing fault signals. Mechanical Systems and Signal Processing, 22, 915-933.
Al-Dossary, S., Raja Hamzah, R. I., Mba, D. (2009). Observations of changes in acoustic emission waveform for varying seeded defect sizes in a rolling element bearing. Applied Acoustics, 70, 58-81.
Prabhakar, S., Mohanty, A. R., Sekhar, A. S. (2002). Application of discrete wavelet transform for detection of ball bearing race faults. Tribology International, 35, 793-800.
Junsheng, Ch., Dejie, Y., Yu, Y. (2007). Application of an impulse response wavelet to fault diagnosis of rolling bearings. Mechanical Systems and Signal Processing, 21, 920-929.
Rai, V. K., Mohanty, A. R. (2007). Bearing fault diagnosis using FFT of intrinsic mode functions in Hilbert-Huang transform. Mechanical Systems and Signal Processing, 21, 2607-2615.
Karacay, T., Akturk, N. (2009). Experimental diagnostics of ball bearings using statistical and spectral methods. Tribology International, 42, 836-843.
Stein, G. J., Chmúrny, R., Rosík, V. (2011). Compact vibration measuring system for in-vehicle applications. Measurement Science Review, 11 (5), 154-159.
Patil, D., Das, N., Routray, A. (2011). Implementation of Fast-ICA: A performance based comparison between floating point and fixed point DSP platform. Measurement Science Review, 11 (4), 118-124.
Du, Q., Yang S. (2007). Application of the EMD method in the vibration analysis of ball bearings. Mechanical Systems and Signal Processing, 21, 2634-2644.
Kim, J., Welcome, D. E., Dong, R. G., Song, W. J., Hayden, Ch. (2007). Time-frequency characterization of hand-transmitted, impulsive vibrations using analytic wavelet transform. Journal of Sound and Vibration, 308, 98-111.
Khorrami, H., Moavenian, M. (2010). A comparative study of DWT, CWT and DCT transformations in ECG arrhythmias classification. Expert Systems with Applications, 37, 5751-5757.