基于数据分析的风电机组偏航机构异常感知方法研究

RESEARCH ON ANOMALY SENSING METHOD OF YAW MECHANISM OF WIND TURBINE BASED ON DATA ANALYSIS

针对风电机组偏航系统动作原理和故障产生原因进行分析,建立偏航机构跟随风向变化灵敏性函数模型;基于指数加权移动平均(EWMA)控制图法和K-S检验分析方法,甄别偏航机构中风向跟踪异常,并提高感知准确性;基于波动互相关分析方法,分析单机风向标数据与场群平均风向的相关性;基于运行数据统计,分析偏航机构跟随性概率分布函数,在异常识别基础上进行故障分类。经过理论分析和实验验证,通过数据统计分析方法,可有效实现偏航机构的异常感知,避免机组亚健康运行,有利于实施预测性维护。

In this paper,the operation principle of the yaw system of wind turbine as well as the failure causes are analyzed,based on which a function model is established to measure the sensitivity of the yaw mechanism in terms of following the wind direction change.Then,based on the EWMA control chart method and K-S test analysis method,anomalies of the yaw mechanism in wind direction tracking are identified and the sensing accuracy is improve.Moreover,the correlation between the individual wind vane data and the average wind direction of the field group is analyzed using the wave cross-correlation analysis method.Finally,the follow-up probability distribution function of the yaw mechanism is analyzed using the operation statistics of operating data,and the failure classification is performed based on the abnormality identification.In conclusion,theoretical analysis and experiments have proved that the statistical analysis method can effectively sense anomalies in the yaw mechanism,thus ensuring the sound operation of the unit,facilitating predictive maintenance and improving the power generation and operating reliability of wind turbines.