Wind Turbine Condition Monitoring
SpinScope is an autonomous AI agent that monitors every turbine in your fleet, catches anomalies before they become failures, and alerts your team before the expensive call-out happens.
How it works
SpinScope ingests 10-minute SCADA resolution data via CSV import or direct API. Power output, wind speed, bearing temps, rotor RPM — whatever your turbines log, SpinScope learns it.
Using ensemble ML models (XGBoost, Random Forest) trained on normal operating conditions, SpinScope builds a behavior baseline specific to each turbine in your fleet.
When a signal deviates beyond the anomaly threshold, SpinScope sends a daily digest email: which turbine, what changed, predicted failure window, recommended action.
Operators use the early warning to schedule maintenance during low-wind windows — converting reactive call-outs into planned interventions with parts already on order.
What SpinScope watches
Rising oil or bearing temps are the #1 precursor to gearbox failure. SpinScope tracks the slope, not just the threshold.
A turbine producing 5% below its weather-adjusted baseline often has a degradation problem weeks before alarms trigger.
Sudden changes in rotor speed under constant wind indicate mechanical load distribution problems — blades, pitch, or drivetrain.
Mismatch between expected and actual power at given wind speeds is a strong indicator of blade erosion or control system degradation.
Extended periods of off-axis yaw increase asymmetric load on the drivetrain. SpinScope flags extended events for inspection.
Extended restart sequences after grid disconnect events can indicate generator or power electronics faults requiring attention.
Built for wind farm operators who know the difference between a turbine running and a turbine healthy. No dashboards to check. No analyst to hire. Just a daily alert when something needs attention.
View Live Dashboard"We have SCADA data. We just don't have anyone watching it." — Every wind farm operator, every night shift