A Novel Intelligent Fault Diagnosis Method for Rolling Bearings Based on Compressed Sensing and Stacked Multi-Granularity Convolution Denoising Auto-Encoder

This paper investigates the unsupervised automatic feature extraction method with a large amount of unlabeled data for the fault diagnosis of rolling bearings in automobile production line, where the fault information is hard to identify due to the low-level features of a single category and the mas...

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Autores principales: Chuang Liang, Changzheng Chen, Ye Liu, Xinying Jia
Formato: article
Lenguaje:EN
Publicado: IEEE 2021
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Acceso en línea:https://doaj.org/article/5bbc5421dfed4c67898e0a2af66bb1f1
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