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Title of Journal: J Fail Anal and Preven

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Abbravation: Journal of Failure Analysis and Prevention

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Springer US

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DOI

10.1016/0022-2828(88)91558-1

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1864-1245

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A New Spectral AverageBased Bearing Fault Diagnos

Authors: Brandon Van Hecke Yongzhi Qu David He Eric Bechhoefer
Publish Date: 2014/03/20
Volume: 14, Issue: 3, Pages: 354-362
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Abstract

The diagnosis of bearing health through the quantification of accelerometer data has been an area of interest for many years and has resulted in numerous signal processing methods and algorithms This paper proposes a new diagnostic approach that combines envelope analysis time synchronous resampling and spectral averaging of vibration signals to extract condition indicators CIs used for rollingelement bearing fault diagnosis First the accelerometer signal is digitized simultaneously with tachometer signal acquisition Then the digitized vibration signal is band pass filtered to retain the information associated with the bearing defects Finally the tachometer signal is used to time synchronously resample the vibration data which allows the computation of a spectral average and the extraction of the CIs used for bearing fault diagnosis The proposed technique is validated using the vibration output of seeded fault steel bearings on a bearing test rig The result is an effective approach validated to diagnose all four bearing fault types inner race outer race ball and cage


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