Design of a novel noise resilient algorithm for fault detection in wind turbines on supervisory control and data acquisition system

Design of a novel noise resilient algorithm for fault detection in wind turbines on supervisory control and data acquisition system

Abstract Wind turbine faults, including electrical, mechanical or aerodynamics-related, can potentially reduce operational efficiency, causing downtimes or, in some cases, leading to severe damage. Hence, timely detection of these operational anomalies is crucial for optimizing performance and reduc...

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Bibliographic Details
Main Authors: Muhammad Irfan, Nabeel Ahmed Khan, Muhammad Abubakar, Zohaib Mushtaq, Tomasz Jakubowski, Paweł Sokołowski, Grzegorz Nawalany, Saifur Rahman
Format: Article
Language:English
Published: Nature Portfolio 2025-04-01
Series:Scientific Reports
Subjects:
Perturbed-Random forest
Supervisory control
Data acquisition
Kernel density
Wind turbine
Fault detection
Online Access:https://doi.org/10.1038/s41598-025-97663-3
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https://doi.org/10.1038/s41598-025-97663-3

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