Digital twins type fatigue damage predication method of low wind speed wind turbine

Abstract

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.

Description

technical field [0001] The invention relates to the field of wind turbines, in particular to a digital twin type fatigue damage prediction method for low wind speed wind turbines. Background technique [0002] With the continuous expansion of the number of wind turbines assembled, the capacity of a single unit and the diameter of the wind rotor continue to increase, which puts forward higher requirements for the adaptability and reliability of wind turbines. The main problem in the wind power industry is that it is impossible to understand the current operating status of the wind turbines and accurately predict and evaluate the operating status of the wind turbines in a digital way. [0003] This application is to create a low wind speed wind turbine digital twin type fatigue damage prediction method, so that it can apply the digital twin (Digital twin) technology to the wind turbine, and digitally simulate the operation behavior of the wind turbine in the real environment ...

AI Technical Summary

Problems solved by technology

[0004] The technical problem to be solved by the present invention is to provide a low wind speed wind turbine digital twin type fatigue damage prediction method, so that it can accurately predict the fatigue life and fatigue damage of the wind turbine through the digital twin model, thereby overcoming the existing wind turbine Insufficiency of lifespan assessment

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