基于关键数据挖掘的风力发电机组故障预测与诊断技术研究

Research on Fault Prediction and Diagnosis Technology of Wind Turbine Based on Key Data Mining

轴承作为风电机组中的关键性、精密型机械部件,在运行过程中易产生磨损,其可靠性直接关系到风电机组安全稳定运行,因此对其磨损状态进行监测是必要的。本文通过实例对几种典型的风电机组轴承磨损的油液监测方法进行了探索,证实了其可行性和有效性,对预警滚动轴承磨损和预防设备事故有重要的意义。

With the rapid development of wind power,the traditional fault maintenance mode has affected the efficiency of power generation and equipment safety.Therefore,it is urgent to predict the faults based on the historical operation of the wind turbines and the key data of the actual measurements,as well as predict the parts and the time of the failure in order to arrange the maintenance plan and purchase certain equipment in advance.In this paper,the method of data mining,using MATLAB to model,can predict the failure of wind turbine,can help the site in the spare parts before damage necessary maintenance,the loss caused by the failure to the minimum.