Detection of ball bearing defects using robust adaptive filter in noisy environment

Many problems arising in rotating machinery are linked to bearing defects. Hence the early detection of the bearing defects in rotating machinery is very important since the critical failure of bearing cause a machinery shutdown. However it is not easy to detect the vibration signal caused by the initial defects of bearing because of high level of broadband noise. A signal processing technique, called the adaptive line enhancer(ALE) as one of adaptive filter, is used in this study. This technique is to eliminate random noise with little a prior knowledge of the noise and signal characteristics. Also we propose the optimal methods for selecting the three main ALE parameters such as correlation length, filter order and adaptation constant. Vibration signals from three abnormal bearings, including inner and outer raceways and ball defects, were acquired by Anderon (angular derivative of radius on) meter. The experimental results showed that ALE is very useful for detecting the bearing defective signals overlapped with random noise.