Bearing condition diagnostics via vibration and acoustic emission measurements

被引:192
作者
Shiroishi, J
Li, Y
Liang, S
Kurfess, T
Danyluk, S
机构
[1] GWW School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, GA
关键词
D O I
10.1006/mssp.1997.0113
中图分类号
TH [机械、仪表工业];
学科分类号
0802 ;
摘要
This paper investigates defect detection methods for rolling element bearings through sensor signature analysis, specifically the use of a new signal processing combination of the high-frequency resonance technique and adaptive line enhancer. Two transducers, the accelerometer and the acoustic emission sensor, are used to acquire data for this analysis. Experimental results are obtained for inner race and outer race defects. Results show the potential effectiveness of the signal processing technique to determine both the severity and location of a defect. (C) 1997 Academic Press Limited.
引用
收藏
页码:693 / 705
页数:13
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