A Comparative Experimental Study of Vibration and Acoustic Emission on Fault Diagnosis of Low-Speed Bearing

Traditional bearing fault diagnosis is mainly based on periodic feature extraction from bearing fault pulses. However, the diagnostic accuracy was limited due to the absence of rotational speed information. First, through envelope analysis and order tracking to extract roller passing frequency (RPF) and fault order, this article verifies the performance of vibration and acoustic emission (AE) signals on diagnosis of bearing fault in low speed. Second, the advantages of fault source localization of AE are also verified and analyzed. In order to accurately extract the pulse generated by the fault source, a method for AE event extraction using a short-time autocorrelation function (STAF) is proposed, which is verified to be efficient and reliable under different working conditions of low-speed bearings.