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Remaining useful life prediction for rotating machinery using bidirectional LSTM: a comparative deep learning study

Published Online: 2026-03-30

Authors

Ghavidel, A. https://orcid.org/0009-0003-9798-8958
Park, H.

Kovacic, S.

Souza-Poza, A.
Funding

Funding for this research was provided by:

Military Sealift Command (FA807518D0006-FA807522F0054-P000143798)

National Science Foundation (1910397)
License Information

Text and Data Mining valid from 2026-03-30

Version of Record valid from 2026-03-30
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Article History

Received: 13 September 2025

Accepted: 12 March 2026

First Online: 30 March 2026

Declarations

:

: The authors declare no competing interests.

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