Condition monitoring based on corrupted multiple time series with common trends-Reference-Cited by-同舟云学术

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Condition monitoring based on corrupted multiple time series with common trends

Published:2024-11 Issue: Volume:251 Page:110324
ISSN:0951-8320
Container-title:Reliability Engineering & System Safety
language:en
Short-container-title:Reliability Engineering & System Safety

Author:

Wei Yujie,Pan Ershun^ORCID,Ye Zhi-Sheng

Publisher

Elsevier BV

Reference49 articles.

1. An enhanced deep learning-based fusion prognostic method for RUL prediction;Huang;IEEE Transactions on Reliability,2019

2. Out-of-distribution detection-assisted trustworthy machinery fault diagnosis approach with uncertainty-aware deep ensembles;Han;Reliab Eng Syst Saf,2022

3. Cross-machine intelligent fault diagnosis of gearbox based on deep learning and parameter transfer;Han;Struct Control Health Monit,2022

4. A planetary gearbox fault diagnosis method based on time-series imaging feature fusion and a transformer model;Wu;Meas Sci Technol,2022

5. Unsupervised Bayesian change-point detection approach for reliable prognostics and health management of complex mechanical systems;Wu;Reliab Eng Syst Saf,2024

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