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eess.SP2024★ 130 cited
An Adaptive feature mode decomposition based on a novel health indicator for bearing fault diagnosis
Sumika Chauhan, Govind Vashishtha, Rajesh Kumar +2
The vibration analysis of the bearing is very crucial because of its non-stationary nature and low signal-to-noise ratio. Therefore, a novel scheme for detecting bearing defects is…
eess.SP2023★ 59 cited
Non-parametric Ensemble Empirical Mode Decomposition for extracting weak features to identify bearing defects
Anil Kumar, Yaakoub Berrouche, Radosław Zimroz +5
A non-parametric complementary ensemble empirical mode decomposition (NPCEEMD) is proposed for identifying bearing defects using weak features. NPCEEMD is non-parametric because, u…