Research On Fault Simulation And Diagnosis Of Wind Turbine Based Of GH Bladed

Since wind turbines are mostly located in harsh environments,the failure rate of wind turbines is high,and the causes and characteristics of the failures are also varied.The faults of the pitch system and the blade are very high of all the failure in the wind turbine.Most of the actual wind farms use SCADA data to diagnose pitch system faults.This method has many advantages in practical implementation and stability,but the fault threshold is set to be single and the accuracy needs to be improved.The failure of wind turbine blades in the actual unit fault diagnosis do not have good methods,most of the observation,image processing,acoustic emission treatment method,these methods have some limitations,for it needs good unit operating and environmental conditions and requires a lot of manual work,so it is not conducive to the application of promotion.Therefore,it is of great significance to study the pitch system and the blade failure diagnosis method.This paper introduces the current situation of the wind power industry and the present fault diagnosis methods for the wind turbines' pitch systems and blades,and simulates the common faults of the pitch system and the blades by GH Bladed software to simulate actual unit operation.Obtain relevant operating data.For all kinds of faults of pitch system,this paper mainly introduces the fault diagnosis method based on support vector machine,and uses particle swarm optimization algorithm to optimize it.The optimized diagnosis model has higher discrimination accuracy.In this paper,the GH Bladed software is used to simulate the damage of a certain element of the blade.Then,the energy spectrum of each band is obtained by wavelet packet decomposition of tip deflection.Based on the change of energy spectrum,the damage of the blade is preliminarily determined,In the event of damage,the specific damage cell of the blade is determined using the modal strain energy change rate method.The experimental results show that the above two methods can accurately and quickly judge the failure of the wind turbine pitch system and blade damage.