Monitoring and Detection of Wind Turbine Vibration with KNN-Algorithm

Maintenance for wind turbines has been transformed using supervised machine learning techniques. This method of automatic and autonomous can identify, monitor, detect electrical mechanical components predict, detect, anticipate their degeneration. Using a classifier frequency analysis, we simulate two failure states caused by bearing vibrations. Implementing KNN facilitates efficient monitoring, fault-finding turbines. It is possible to reduce downtime, breakdowns, import offshore aspects through these technologies.