Detection of rolling element bearing defects by adaptive filtering

Most of the difficulties encountered when detecting initial bearing defects are due to the presence of noise in the measured signals. In the present paper, we show the effectiveness of using Adaptive Noise Cancellation techniques, in enhancing the vibration signal which is corrupted with noise in the low frequency spectrum. Two algorithms have been used in the paper, the Adaptive Noise Cancellation (ANC) and the Adaptive Self-Tuning filter (AST). The two algorithms have been first of all tested on a computer simulated signals; then, applied on measured signals on a bearing fault simulator. It has been found that adaptive filtering increases the signal to noise ratio for both simulated and measured signals.