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Sumika Chauhan

2 papers here

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  • eess.SP2
ORCID 0000-0003-0367-4193

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most citedAn Adaptive feature mode decomposition based on a novel health indicator for bearing fault diagnosis

130 citations · 189 across the 2 of their papers we have counts for

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2 papers

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…

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