The invention discloses a digital twins type
fatigue damage predication method of a low
wind speed wind
turbine to realize
fatigue damage predication of the wind
turbine through adopting a digital twins model. The digital twins type
fatigue damage predication method comprises the following steps: establishing a wind wheel
simulation model of a virtual wind
turbine, and enabling the wind wheel
simulation model and the actually operated wind turbine to be consistent in
model parameters and operating characteristics through correcting the frequency, mode of vibration,
mass, rigidity, geometric dimension and the like of key components; establishing a load
database, and calculating a wind filed fatigue model; establishing a digital twins model by combining the actual operating data, the actualconstructed environmental conditions and the
machine-position distribution information, and establishing the load data of the actual operating wind turbine; and finally, predicating the fatigue life and the fatigue damage condition of the wind turbine, and monitoring the key components of the wind turbine. According to the digital twins type fatigue damage predication method, through the digital twins model technology, the operating behavior of the wind turbine in the realistic environment is really simulated, the fatigue damage of the wind turbine is predicated, the basis is provided for overhaul and
wind field optimization, and the optimal
electricity generation performance of the wind turbine is ensured.