A Comparative Experimental Study of Vibration and Acoustic Emission on Fault Diagnosis of Low-Speed Bearing
Linjiang Tang, Xing Wu, Dongxiao Wang, Xiaoqin Liu
Abstract
Traditional bearing fault diagnosis mainly based on periodic feature extraction from bearing fault pulses. However, the diagnostic accuracy was limited due to the absence of rotation speed information. Firstly, through envelope analysis and order tracking to extract roller passing frequency (RPF) and fault order, this paper verifies the performance of vibration and acoustic emission signals (AE) on diagnosis of bearing fault in low-speed. Secondly, 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 short time autocorrelation function is proposed, which is verified to be efficient and reliable under different working conditions of low-speed bearings.