IEEE Prognostics & System Health Management Conference, PHM, Beijing, 2012

Fan Bearing Fault Diagnosis Based on Continuous Wavelet Transform and Autocorrelation

Lei Xie a, Qiang Miao a, Yi Chen a, Wei Liang a, and Michael Pecht b
aSchool of Mechanical, Electronic and Industrial Engineering, UESTC, Chengdu 611731, China
bCenter for Advanced Life Cycle Engineering (CALCE), University of Maryland, College Park, MD 20742, USA



Cooling fan is commonly used in electronic system, and it is crucial for guarantying the reliability of it. In a cooling fan assembly, fan bearing failure is a major part which causes noise, vibration; reduction in rotation speed, or even locks the motor. It is necessary to conduct research on the life assessment of fan bearings. This paper presents a vibration-based fan bearing prognosis and health evaluation through continuous-wavelet transform with ACFIs. The autocorrelation function indicator (ACFI) was used for determining the coefficients of continuouswavelet transform (CWT). A cooling fan accelerated life test was conducted to collect the lifetime vibration data of fan bearing. In addition, comparisons between the frequency spectrum of the proposed method and some commonly used methods were conducted to evaluate performance of this method. The work presented in this paper provides a promising way for finding the fault characteristic frequencies and detecting the work state of fan bearing.

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