Acoustic emission signature analysis on rolling element bearings due to localized defects

The interaction of surface asperities and
impingement of rolling element of bearing over the
defective races of rolling element bearings generate
Acoustic Emissions (AEs). Significant progress in the
capabilities of acoustic instrumentation, together with
signal processing techniques, made possible to extract
useful diagnostic information from acoustic signals. The
main advantage of AE is that it offers high Signal to Noise
Ratio (SNR), which is required for the precise detection of
faults. Rotating speed, radial load and size of localized
defect are the most influenced operating parameters on AE
amplitude. A bearing test-rig is designed and established to
study the various defect sizes on outer race of rolling
element bearings. AE signal generated from artificial line
defects in rolling element bearings (REBs) are
investigated. The AE signal was transformed through Fast
Fourier Transform (FFT) AE laboratory software, which is
supplied by AE instrument. Even though there were many
signatures of AE signals that can be used such as
amplitude, duration, counts and signal energy. AE
instrument with amplitude is used in this study, which
allows for the measuring of amplitude in the signal.
Experiments are performed using N312 REBs and results
have been presented. Experimental data is analyzed using
response surface methodology (RSM) to identify the
significant parameters on AE amplitude. Here, predictive
model like RSM is used to predict and optimize AE
amplitude in dB level