n-sapkota/Fault-Detection-wind-turbine
Wind turbine fault detection using one class SVM
This project helps wind farm operators and maintenance engineers proactively identify mechanical faults in wind turbines before they lead to costly breakdowns. By analyzing operational data from the turbines, it tells you when a specific turbine is starting to behave unusually, indicating a potential issue. The primary users are professionals responsible for the uptime and maintenance scheduling of wind farms.
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Use this if you manage wind turbines and want an automated way to flag individual turbines that are beginning to show signs of mechanical problems based on their operational data.
Not ideal if you need a detailed diagnostic report specifying the exact type of fault (e.g., 'gearbox wear' vs. 'blade imbalance') or if you don't have access to continuous operational sensor data from your turbines.
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Language
Jupyter Notebook
License
AGPL-3.0
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Last pushed
Feb 17, 2022
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