Predicting Remaining Useful Life of Rolling Bearings Based on Reliable Degradation Indicator and Temporal Convolution Network with the Quantile Regression

High precision and multi information prediction results of bearing remaining useful life (RUL) can effectively describe the uncertainty of bearing health state and operation state. Aiming at the problem of feature efficient extraction and RUL prediction during rolling bearings operation degradation...

Täydet tiedot

Bibliografiset tiedot

Päätekijät:	Qiaoping Tian, Honglei Wang
Aineistotyyppi:	Artigo
Kieli:	Inglês
Julkaistu:	MDPI AG 2021-05-01
Sarja:	Applied Sciences
Aiheet:	smart manufacturing remaining useful life prediction reliability features compression and computing quantile regression
Linkit:	https://www.mdpi.com/2076-3417/11/11/4773
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