Selection of mother wavelets for analyzing bearing vibration signals

Ball bearings are critical components in rotating machines and the prognosis of their health state is an important policy that increases reliability, availability and safety while minimizing costs. Wavelet Packet Decomposition (WPD) is a widely used method for the analysis of vibratory signals since it allows decomposing them in time and frequency domains. The choice of the analyzing wavelet and its order is an important step that affects the estimation of the Remaining Useful Life (RUL). In this paper, we compared several types of wavelets in order to choose the most suitable for predicting the RUL of the bearings. The utilized selection criteria were the Minimum Shannon Entropy Criteria (MSEC) and Maximum Energy to Shannon Entropy Ratio criteria (MEER). The tests were carried out on several bearings under different conditions where horizontal and vertical accelerations are measured.