Fault Size Estimation in the Outer Race of Ball Bearing Using Discrete Wavelet Transform of the Vibration Signal

AbstractVibration signal analysis being one of the widely acceptable tools for bearing condition monitoring; the estimation of fault size from vibration signal is still a challenge and a subject of interest to the researchers. This work presents the decomposition of the vibration signal by using discrete wavelet transform assisted by sym5 wavelet. Symlet wavelet has a linear phase nature which maintains sharpness in the signal even when there is sudden change in the signal. The decomposed signal evidently splits the peak corresponding to the ball entry into and exit from the fault, enabling in an estimation of the defect size present in the bearing. Experiments conducted for different sizes of the defect present on the outer race of deep groove ball bearing affirm the efficacy of the applied technique for different vibration signals. The output of the proposed technique finds close correlation with the actual defect size measured from optical microscope with the maximum deviation in the result of 2.06%