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Early prediction of wind turbine anomalies using 1D-CNN and temporal feature engineering on multi-source SCADA data

Mohamed Maher Ata1, Shorok Osama2, Mai Ramadan Ibraheem3

  • 1School of Computational Sciences and Artificial Intelligence (CSAI), Zewail City of Science and Technology, October Gardens, 6th of October City, 12578, Giza, Egypt. momaher@zewailcity.edu.eg.

Scientific Reports
|March 22, 2026
PubMed
Abstract

No abstract available in PubMed .

Keywords:
AttentionBi-LSTMCNNDeep learningGRU predictive maintenanceHybrid modelLSTMRNNRenewable EnergyTCNWind turbines

Related Concept Videos

Wind Turbine Machine Models01:24

Wind Turbine Machine Models

In the growing field of wind energy, incorporating wind turbine models into transient stability analysis is essential. Induction and synchronous machines are the primary models used, with induction machines being prevalent due to their simplicity and reliability.
Induction machines interact through the rotating magnetic field generated by the stator and the rotor. The key parameter is slip, which is the difference between synchronous speed and rotor speed relative to synchronous speed. Slip is...
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