Cooling fan bearing diagnosis based on AR& MED

Author

Liu, Chaoqin ; Zhou, Xue ; Yang, Shuai ; Liang, Wei ; Miao, Qiang

Author_Institution

Sch. of Mech., Electron. & Ind. Eng., Univ. of Electron. Sci. & Technol. of China, Chengdu, China

fYear

2012

fDate

15-18 June 2012

Firstpage

622

Lastpage

626

Abstract

To monitor the initial failure of cooling fan´s rolling bearing, this paper reviews the theory of autoregressive (AR) model and the minimum entropy deconvolution (MED) filtering technique. The AR method can remove the deterministic components of the original signal, and the MED filter could reduce the effect of the transmission path. These two filtering techniques were combined in this paper to pre-process the rolling bearing´s vibration signal, and then the envelope spectrum of the residual signal was analyzed. The method leads to efficient filtering result.

Keywords

autoregressive processes; cooling; deconvolution; entropy; failure (mechanical); fans; fault diagnosis; filtering theory; mechanical engineering computing; rolling bearings; vibrations; autoregressive model; cooling fan bearing diagnosis; deterministic component removal; envelope spectrum; failure monitoring; minimum entropy deconvolution filtering technique; residual signal; rolling bearing; transmission path; vibration signal preprocessing; Cooling; Deconvolution; Educational institutions; Entropy; Filtering; Rolling bearings; Vibrations; AR; MED; cooling fan; initial failure diagnosis;

fLanguage

English

Publisher

ieee

Conference_Titel

Quality, Reliability, Risk, Maintenance, and Safety Engineering (ICQR2MSE), 2012 International Conference on

Conference_Location

Chengdu

Print_ISBN

978-1-4673-0786-4

Type

conf

DOI

10.1109/ICQR2MSE.2012.6246310

Filename

6246310