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A hybrid hierarchical health monitoring solution for autonomous detection, localization and quantification of damage in composite wind turbine blades for tinyML applications

Crossref DOI link: https://doi.org/10.1038/s41598-025-95364-5

Published Online: 2025-04-11

Update policy: https://doi.org/10.1007/springer_crossmark_policy

Authors

Holsamudrkar, Nikhil

Sikdar, Shirsendu

Kalgutkar, Akshay Prakash

Banerjee, Sauvik

Mishra, Rakesh
Funding

Funding for this research was provided by:

University of Huddersfield’s URF Grant (QR24E025)

University of Huddersfield’s International Research Development Fund (QR24SR009)

RIKE University of Huddersfield
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Text and Data Mining valid from 2025-04-11

Version of Record valid from 2025-04-11
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Article History

Received: 8 October 2024

Accepted: 20 March 2025

First Online: 11 April 2025

Declarations

:

: The authors declare no competing interests.

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