Fault Diagnosis Method for Rolling Element Bearings Under Variable Speed Based on TKEO and Fast-SC
- PDF / 1,558,251 Bytes
- 6 Pages / 595.276 x 790.866 pts Page_size
- 76 Downloads / 203 Views
TOOLS AND TECHNIQUES
Fault Diagnosis Method for Rolling Element Bearings Under Variable Speed Based on TKEO and Fast-SC Dan-chen Zhu . Yong-xiang Zhang . Qun-wei Zhu
Submitted: 22 August 2017 / in revised form: 8 October 2017 Ó ASM International 2018
Abstract With rotating speed of rotating machinery, it is difficult to maintain stability in practical work which brings many difficulties to the condition monitoring of rotating machinery. When rolling element bearings work under variable speed, the corresponding vibration will contain obvious non-stationary characteristics, along with the presence of strong background noise, which makes it difficult for some traditional spectrum analysis methods to identify the characteristic frequency of bearings fault. In spite of the existence of strong non-stationary characteristics, the bearing fault signal has some hidden periodic components in the angle domain which makes it possible to extract the fault feature of bearings by means of spectral correlation analysis. Therefore, a fault feature extraction method based on Teager–Kaiser energy operator (TKEO) and fast spectral correlation (Fast-SC) in angle domain is proposed in this paper; Fast-SC is a newly proposed spectral correlation calculation method which can effectively improve the efficiency of computing; Teager–Kaiser energy operator can enhance the transient impact which also has a fast computing speed. In this paper, the instantaneous speed of each time is estimated by the time– frequency analysis method based on short-time Fourier transform and then, the original time-domain signal is resampled in angle domain; the TKEO is used to strengthen the fault impact components in signal; finally, the Fast-SC is applied to the strengthened signals, the enhanced envelope spectrum is calculated, and the fault features of rolling bearings are extracted. The effectiveness of the method is verified by measured signals. D. Zhu (&) Y. Zhang Q. Zhu Department of Power Engineering, Naval University of Engineering, Wuhan 430033, China e-mail: [email protected]
Keywords Teager–Kaiser energy operator Fast-SC Rolling element bearings Fault diagnosis
Introduction Vibration signals collected by sensors often contain abundant information about the operating status of the device. How to use these vibration signals for effective fault monitoring has been one of the main research contents in recent years. Working as an important component of rotating machinery, rolling element bearings have been widely used, but the working environment of rolling element bearings is usually very bad; fatigue spalling, wear and pitting often occur which have a great impact on the normal use of the bearings and the stable operation of the machine. Therefore, bearing fault diagnosis has always been a research hotspot and is still unresolved. Rolling element bearings usually work inside the machine, while most of the sensors used in vibration measurement can only placed on the surface of the equipment, which makes the measured vibration signal conta
Data Loading...
