Applications of K-nearest neighbor algorithm in intelligent diagnosis of wind turbine blades damage-Reference-Cited by-同舟云学术

Applications of K-nearest neighbor algorithm in intelligent diagnosis of wind turbine blades damage

Published:2023-08 Issue: Volume:212 Page:855-864
ISSN:0960-1481
Container-title:Renewable Energy
language:en
Short-container-title:Renewable Energy

Author:

Tang Yaochi^ORCID,Chang Yunchi^ORCID,Li Kuohao^ORCID

Funder

Ministry of Science and Technology, Taiwan

Publisher

Elsevier BV

Subject

Renewable Energy, Sustainability and the Environment

Reference27 articles.

1. Damage detection techniques for wind turbine blades: a review;Du;Mech. Syst. Signal Process.,2020

2. Charlotte bay hasager, christian bak, anna-maria tilg, jakob I.bech, saeed doagou rad, søren fæster, leading edge erosion of wind turbine blades: understanding, prevention and protection;Mishnaevsky;Renew. Energ. Pr.,2021

3. In-situ condition monitoring of wind turbine blades: a critical and systematic review of techniques, challenges, and futures;Sun;Renew. Sust. Energ. Rev. Pr.,2022

4. An experimental study on the data-driven structural health monitoring of large wind turbine blades using a single accelerometer and actuator;García;Mech. Syst. Signal Process.,2019

5. Non-contact vibration monitoring of rotating wind turbines using a semi-autonomous UAV;Khadka;Mech. Syst. Signal Process.,2020

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