Investigating the effectiveness of acoustic emission sensors in the study of natural degradation of angular contact bearings

In this study, the application of wavelet transform in the natural degradation of roller bearings based on the processing of acoustic emission signals has been investigated. In order to extract the bearing acoustic emission signals, a suitable laboratory arrangement and data collection equipment was used. The processing of acoustic emission signals in time-frequency domains was performed using wavelet transform analysis. In order to capturing the acoustic emission signals, three sensors namely Pico, R6α and WSα were applied. The results showed that the acoustic emission method is an efficient method for estimating the bearing natural degradation. In this study, to select the mother wavelet, the method of comparing the ratio of energy to converted signal entropy was used. Comparison of energy versus entropy for the 53 mother wavelets studied shows that the Bior 3.1 mother wavelet has the highest energy to Shannon entropy ratio and is selected as the best mother wavelet. Also, the performance analysis of the three sensors showed that all three sensors used are suitable for investigating the natural degradation of the bearing, however, the Pico sensor scored higher.