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Rolling Bearing Localized Defect Evaluation by Multiscale Signature via Empirical Mode Decomposition
刊名：
Journal of Vibration and Acoustics
作者：
Qingbo He
（Department of Precision Machinery and Precision Instrumentation, University of Science and Technology of China）
Peng Li
（Department of Precision Machinery and Precision Instrumentation, University of Science and Technology of China）
Fanrang Kong
（Department of Precision Machinery and Precision Instrumentation, University of Science and Technology of China）
刊号：
780B0015
ISSN：
1048-9002
出版年：
2012
年卷期：
2012, vol.134, no.6
页码：
061013-1--061013-11
总页数：
11
分类号：
TH113; TB5
关键词：
Rolling element bearing
；
Localized defect evaluation
；
Empirical mode decomposition
；
Intrinsic mode function
；
Multiscale slope feature
参考中译：
语种：
eng
文摘：
Measured vibration signals from rolling element bearings with defects are generally nonstationary, and are multiscale in nature owing to contributions from events with different localization in time and frequency. This paper presents a novel approach to characterize the multiscale signature via empirical mode decomposition (EMD) for rolling bearing localized defect evaluation. Vibration signal measured from a rolling element bearing is first adoptively decomposed by the EMD to achieve a series of usable intrinsic mode functions (IMFs) carrying the bearing health information at multiple scales. Then the localized defect-induced IMF is selected from all the IMFs based on a variance regression approach. The multiscale signature, called multiscale slope feature, is finally estimated from the regression line fitted over logarithmic variances of the IMFs excluding the defect IMF. The presented feature reveals the pattern of energy transfer among multiple scales due to localized defects, representing an inherent self-similar signature of the bearing health information that is embedded on multiple analyzed scales. Experimental results verify the performance of the proposed multiscale feature, and further discussions are provided.
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