Detection of Self-Aligning Roller Bearing Fault by Asynchronous Adaptive Noise Cancelling Technology

Abstract

An effective method for improving the signal-to-noise ratio from measurements of bearing housing vibration is presented.The method is based on the conventional adaptive noise cancelling (ANC) technique principle;it varies the main signal input and reference signal input.Since the main and reference inputs signals are collected at different times, this method is called asynchronous adaptive noise cancelling (AANC).It can improve the signal-to-noise ratio, as in the case of the detecting bearing faults when vibration signals of machinery are collected under low-frequency noise condition.In combination with AANC, statistical analysis, enveloping spectrum analysis techniques are used for detection of bearing fault and diagnosis.Experimental result has shown that these techniques can be made more effective only after AANC has reduced the background noise from the diagnostic signals.A new approach is proposed to the traditional fault detecting for self-aligning roller bearings when the shaft speed is low (250rpm) or high (1000rpm) condition.