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