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dc.creatorShiroishi J.-
dc.creatorY. Li S. Liang-
dc.creatorDanyluk S.-
dc.creatorKurfess T.-
dc.descriptionThis paper investigates defect detection methodologies for rolling element bearings through vibration analysis. Specifically, the utility of a new signal processing scheme combining the High Frequency Resonance Technique (HFRT) and Adaptive Line Enhancer (ALE) is investigated. The accelerometer is used to acquire data for this analysis, and experimental results have been obtained for outer race defects. Results show the potential effectiveness of the signal processing technique to determine both the severity and location of a defect. The HFRT utilizes the fact that much of the energy resulting from a defect impact manifests itself in the higher resonant frequencies of a system. Demodulation of these frequency bands through use of the envelope technique is then employed to gain further insight into the nature of the defect while further increasing the signal to noise ratio. If periodic, the defect frequency is then present in the spectra of the enveloped signal. The ALE is used to enhance the envelope spectrum by reducing the broadband noise. It provides an enhanced envelope spectrum with clear peaks at the harmonics of a characteristic defect frequency. It is implemented by using a delayed version of the signal and the signal itself to decorrelate the wideband noise. This noise is then rejected by the adaptive filter that is based upon the periodic information in the signal. Results have been obtained for outer race defects. They show the effectiveness of the methodology to determine both the severity and location of a defect. In two instances, a linear relationship between signal characteristics and defect size is indicated.-
dc.publisherThe Brazilian Society of Mechanical Sciences-
dc.sourceJournal of the Brazilian Society of Mechanical Sciences-
dc.subjectBearing Vibration-
dc.subjectMachine Diagnostics-
dc.subjectMachine Monitoring-
dc.subjectSignal Processing-
dc.titleVibration analysis for Bearing outer race condition diagnostics-
Appears in Collections:Technology and Engineering

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