Remaining Useful Life Prediction via Frequency Emphasizing Mix-Up and Masked Reconstruction-Reference-Cited by-同舟云学术

Remaining Useful Life Prediction via Frequency Emphasizing Mix-Up and Masked Reconstruction

Published:2024-09 Issue:9 Volume:5 Page:4686-4695
ISSN:2691-4581
Container-title:IEEE Transactions on Artificial Intelligence
language:
Short-container-title:IEEE Trans. Artif. Intell.

Author:

Guo Haoren¹^ORCID,Zhu Haiyue²^ORCID,Wang Jiahui¹^ORCID,Prahlad Vadakkepat¹^ORCID,Ho Weng Khuen¹^ORCID,de Silva Clarence W.³^ORCID,Lee Tong Heng¹^ORCID

Affiliation:

1. College of Design and Engineering, Electrical and Computer Engineering, National University of Singapore, Singapore

2. Singapore Institute of Manufacturing Technology (SIMTech), Agency for Science, Technology and Research (A*STAR), Singapore

3. Department of Mechanical Engineering, University of British Columbia, Vancouver, BC, Canada

Funder

National University of Singapore

Singapore Institute of Manufacturing Technology (SIMTech), A*STAR

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/9078688/10673734/10518144.pdf?arnumber=10518144

Reference33 articles.

1. A Novel Unsupervised Deep Transfer Learning Method With Isolation Forest for Machine Fault Diagnosis

2. A survey of predictive maintenance: Systems, purposes and approaches;Ran,2019

3. Gated Dual Attention Unit Neural Networks for Remaining Useful Life Prediction of Rolling Bearings

4. Hybrid PSO–SVM-based method for forecasting of the remaining useful life for aircraft engines and evaluation of its reliability

5. Data-driven prognostic method based on Bayesian approaches for direct remaining useful life prediction

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