We show that simple vibration sensors on wind turbines can reveal how each machine is operating without relying on control system data. By learning patterns from short acceleration segments, our model identifies turbine behavior, detects changes in operation, and tracks events over time. These patterns also support estimating fatigue, providing a new way to understand turbine performance using only vibration measurements.