Monitoring and Detection of Wind Turbine Vibration with KNN-Algorithm

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ISSN Print: 2327-5219
ISSN Online: 2327-5227
www.scirp.org/journal/jcc
E-mail: jcc@scirp.org

Citations

"Monitoring and Detection of Wind Turbine Vibration with KNN-Algorithm"
written by Javier Vives,
published by Journal of Computer and Communications, Vol.10 No.7, 2022

has been cited by the following article(s):

[1]	An Embedded Machine Learning Fault Detection System for Electric Fan Drive
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[2]	Comprehensive Fault Diagnostics and Performance Forecasting of Wind Turbines Through Condition Monitoring Solutions
	2023

[3]	Ordinal few-shot learning with applications to fault diagnosis of offshore wind turbines
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[4]	K-nearest neighbour and K-fold cross-validation used in wind turbines for false alarm detection
	Sustainable Futures, 2023

[5]	SVM-Algorithm for Supervision, Monitoring and Detection Vibration in Wind Turbines
	Journal of Computer and Communications, 2022

[6]	Sustainable Futures

[1]	Wind turbine fault prognosis using SCADA measurements, pre-fault labeling, and KNN classifiers robust against data imbalance Measurement, 2025 DOI:10.1016/j.measurement.2024.116202

[2]	An Embedded Machine Learning Fault Detection System for Electric Fan Drive Electronics, 2024 DOI:10.3390/electronics13030493

[3]	Ordinal few-shot learning with applications to fault diagnosis of offshore wind turbines Renewable Energy, 2023 DOI:10.1016/j.renene.2023.02.072

[4]	Ordinal few-shot learning with applications to fault diagnosis of offshore wind turbines Renewable Energy, 2023 DOI:10.1016/j.renene.2023.02.072

[5]	K-nearest neighbour and K-fold cross-validation used in wind turbines for false alarm detection Sustainable Futures, 2023 DOI:10.1016/j.sftr.2023.100132

[6]	Ordinal few-shot learning with applications to fault diagnosis of offshore wind turbines Renewable Energy, 2023 DOI:10.1016/j.renene.2023.02.072

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