Research On Fault Analysis And Diagnosis Method Of Wind Turbine Pitch System

Due to the rapid development of society,the use of a large amount of traditional fossil energy has caused a series of very serious environmental pollution problems.Therefore,the use of clean energy has received widespread attention and strong support from around the world.Wind energy,as a kind of clean renewable resource,is now widely used worldwide.As a clean and renewable resource,wind energy currently occupies a large proportion of energy use.With the continuous increase in the number of wind turbines put into operation,the third industry of wind turbine,which is mainly based on unit operation and maintenance,has become a new growth point.Higher failure rates have caused high maintenance costs.It is important to carry out wind turbine fault diagnosis and fault diagnosis research to monitor faults and operation and maintenance costs of units and improve the safety and economy of generators.Pitch system is one of the core components of wind turbines.Complex mechanical structures and frequent work orders have caused the failure rate of pitch system significantly higher than other systems such as yaw system and transmission system.The failure of the pitch system directly affects the quality of the wind turbine's use of wind energy.The faults of the pitch system mainly focus on pitch angle,pitch motor and pitch torque.In this article,the SINOVEL SL1500 wind turbine is taken as the research object.Firstly,the equipment of the unit is analyzed.The structure,working principle and operating status of the pitch system are mainly introduced.Secondly,the fault modes of the pitch system are taken as top events,and the bottom event of the fault and the minimum cut set of the fault are obtained through qualitative analysis by using the fault tree analysis method;then,the probability importance of each bottom event is obtained through quantitative analysis.Finally,Fisher discriminant analysis was used to analyze and diagnose the faults of the pitch system.The appropriate fault variables were selected.Based on the data of the SCADA system,the contribution rate of fault direction vectors and variables to failures is obtained.The size of the contribution rate directly reflects the probability of a failure.