Research On Wind Turbine Fault Early Warning Based On Monitoring Data

In recent years,with the increasing of environmental pollution and energy crisis,renewable energy sources such as wind energy are favored by many countries all over the world.The rapid development of China’s wind power industry,wind power generator as a rotating mechanical equipment,which has more parts of the structure is relatively complicated;at the same time,the wind turbine works in sparsely populated,poor natural conditions in the environment,leading to the fan in the operation process of the fault occurred frequently,frequent repair costs resulting in the wind field operation cost.Therefore,how to use intelligent monitoring means to reduce fan failure times in order to save the running cost of the wind farm,is currently an important issue urgently needs to solve the most of wind.Based on this background,it is of great significance to carry out intelligent fault diagnosis and remote monitoring.This paper studies the research status of domestic and foreign experts and scholars for the wind turbine generator fault warning and fault diagnosis;secondly,analysis of the fan working principle,components and typical faults,summarizes the reason of the fault;finally,the use of data mining technology in the extraction of correlation rules and related rules stored in the database by matching,fault query function.Focusing on fault warning wind generator,through the monitoring data acquisition system of SCADA,the correlation coefficient between the data calculated,analyzed the influence of relevant parameters of wind turbine temperature,and the formation of related variables.On the basis of the above analysis,a fault early warning model based on the temperature of wind turbine is established.The validity of the model is verified by the residual analysis of the predicted value and the actual value.This paper studies the research status of domestic and foreign experts and scholars for the wind turbine generator fault warning and fault diagnosis;secondly,analysis of the fan working principle,components and typical faults,summarizes the reason of the fault;finally,the use of data mining technology in the extraction of correlation rules and related rules stored in the database by matching,fault query function.This combination of Liaoning Longyuan Wind Power Co.,the company’s actual situation Faku wind farm,the design of the remote monitoring platform of wind farm.By using data mining,data acquisition,data transmission,data storage,data distribution and monitoring technology,the operation of the wind farm is monitored on the user’s mobile phone APP.The research results of this paper can play a guiding role in the design of other monitoring systems.