Bearing Prognostics: An Instance-Based Learning Approach with Feature Engineering, Data Augmentation, and Similarity Evaluation

Bearing Prognostics: An Instance-Based Learning Approach with Feature Engineering, Data Augmentation, and Similarity Evaluation

We propose an instance-based learning approach with data augmentation and similarity evaluation to estimate the remaining useful life (RUL) of a mechanical component for health management. The publicly available PRONOSTIA datasets, which provide accelerated degradation test data for bearings, are us...

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Bibliographic Details
Main Authors: Jun Sun, Qiao Sun
Format: Article
Language:English
Published: MDPI AG 2021-10-01
Series:Signals
Subjects:
bearing faults
remaining useful life
prognostics
instance-based learning
data augmentation
spectrogram
Online Access:https://www.mdpi.com/2624-6120/2/4/40

Internet

https://www.mdpi.com/2624-6120/2/4/40

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