Vibration Analysis Methods in Bearing Damage Detection

Abstract:

The goal of vibration analysis is to extract features from the measurements x (t) or x (kT₀), T₀ sampling time, to be used for fault detection and diagnosis. The corresponding analysis methods operate in the time domain (autocorrelation functions, power cepstrum, crest and kurtosis factors), in the frequency domain (Fast Fourier Transform FFT, maximum entropy spectral estimation, envelope analysis) and recently in the time-frequency domain. Time-frequency analysis methods represent efficient alternatives to detect bearings damage due to non-stationary impact signals. In this case, the short-time Fourier transform (STFT) or the Wavelet transform are applied. The paper presents a comparative study of some methods used in bearing faults detection (the envelope spectrum and the wavelet transform). A monitoring tool acquires experimental data from a bearing vibration control test rig. An accelerometer captures the signal from the bearing outer ring then it is processed using PCI-4451 National Instruments data acquisition board and LabVIEW soft.

• Periodical: Applied Mechanics and Materials (Volume 371)
• Pages: 622-626
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.371.622
• Online since: August 2013
• Authors: Carmen Bujoreanu, Vasile Horga, Barbu Drăgan
• Keywords: Bearing Fault, Spectrum Envelope, Vibration, Wavelet Analysis

References

[1] R. Isermann, Fault-Diagnosis Systems, Springer, Germany, (2006).

[2] Rolf Isermann, Model-based fault-detection and diagnosis – status and applications, Annual Reviews in Control 29 (2005) 71–85.

DOI: 10.1016/j.arcontrol.2004.12.002

[3] Milind Natu, Bearing Fault Analysis using Frequency and Wavelet Techniques, International Journal of Computational Engineering & Management 15 issue 6, (2012), 72-74.

[4] B. Drăgan, Gh. Hagiu, Gear vibrations diagnosis with frequency spectrum envelope, Buletinul I.P. Iasi tom LII(LVI), (2006), 1-6.

[5] M. Lokesha, Manik Chandra Majumder, K. P. Ramachandran, Khalid Fathi Abdul Raheem, Fault diagnosis in gear using wavelet envelope power spectrum, International Journal of Engineering, Science and Technology vol. 3, no. 8, (2011), 156-167.

DOI: 10.4314/ijest.v3i8.13

[6] F.K. Omar, A. M Gaouda., Gearbox diagnostics using wavelet based windowing technique, Journal of Physics: Conference Series, 181 (2009) 51-59.

DOI: 10.1088/1742-6596/181/1/012089

[7] I.A. Abu-Mahfouz, Gearbox health monitoring experiment using vibration signals, Journal of Engineering Technology 24 no. 1 (2007) 26-31.

[8] Tahsin Doguer, Jens Strackeljan, Vibration Analysis using Time Domain Methods for the Detection of small Roller Bearing Defects, 8th International Conference on Vibrations in Rotating Machines, Vienna, Austria (2009).