Bearing damage assessment using Jensen-Rényi Divergence based on EEMD

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Bearing damage assessment using Jensen-Rényi Divergence based on EEMD

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作者：Jaskaran Singh ^{Jaskaran.Singh@mech.iitd.ac.in" class="auth_mail" title="E-mail the corresponding author} ; A.K. Darpe ; ^{akdarpe@mech.iitd.ac.in" class="auth_mail" title="E-mail the corresponding author} ; S.P. Singh ^{singhsp@mech.iitd.ac.in" class="auth_mail" title="E-mail the corresponding author}
关键词：BDF ; Ball Defect Frequency ; CV ; Confidence Value ; EMD ; Empirical Mode decomposition ; EEMD ; Ensemble Empirical Mode Decomposition ; FFT ; Fast Fourier Transform ; IMFs ; Intrinsic Mode Function ; IRDF ; Inner Race Defect Frequency ; JRD ; Jensen-Ré ; nyi divergence ; ORDF ; Outer Race Defect Frequency ; PFI ; Probable Fault Index ; SNR ; Signal to Noise Ratio ; WPD ; Wavelet Packet Decomposition
刊名：Mechanical Systems and Signal Processing
出版年：2017
出版时间：15 March 2017
年：2017
卷：87
期：part_PA
页码：307-339
全文大小：4814 K

文摘

•: Quantification of bearing damage using Jensen-Rényi Divergence based on EEMD.
•: Structured sensitive IMF selection to account for variation in operating conditions.
•: Proposed two parameters which together classify the fault type.
•: A standardized index (CV) for online bearing degradation assessment.
•: Validated with simulations, seeded defect data and bearing run-to-failure test data.

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