Remaining Useful Strength (RUS) Prediction of SiC<sub>f</sub>-SiC<sub>m</sub> Composite Materials Using Deep Learning and Acoustic Emission

Remaining Useful Strength (RUS) Prediction of SiC<sub>f</sub>-SiC<sub>m</sub> Composite Materials Using Deep Learning and Acoustic Emission

Prognosis techniques for prediction of remaining useful life (RUL) are of crucial importance to the management of complex systems for they can lead to appropriate maintenance interventions and improvements in reliability. While various data-driven methods have been introduced to predict the remainin...

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Bibliographic Details
Main Authors: Steph-Yves M. Louis, Alireza Nasiri, Jingjing Bao, Yuxin Cui, Yong Zhao, Jing Jin, Xinyu Huang, Jianjun Hu
Format: Article
Language:English
Published: MDPI AG 2020-04-01
Series:Applied Sciences
Subjects:
remaining useful strength
remaining useful life
silicon carbide fiber reinforced silicon carbide matrix
acoustic emission
random-forest
convolutional neural network
Online Access:https://www.mdpi.com/2076-3417/10/8/2680

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