Advanced Lifetime Prediction for Wind Turbine Gearboxes: Integrating Non-linear Damage Models with Industry Standards

This research presents a Python-based tool designed to improve fatigue life predictions for wind turbine drivetrain components by integrating industry-standard methods with a non-linear fatigue damage accumulation model. The tool applies the L10 method (IEC 61400, ISO 281) for bearings and ISO 6336 for gears, accounting for variable load, speed, and torque spectra. Enhanced by the Aeran damage model, the tool provides a more accurate reflection of damage interactions across stress levels, overcomming the limitations of traditional Miner's rule.