Data-driven Health Status Prediction of the Hydraulic Turbine Governing System

水轮机调速系统是水轮发电机组的关键控制系统。运用故障树与专家系统相结合的方法对调速系统可能发生的故障进行诊断,并基于历史数据,挖掘与故障相关的可能因素,对专家系统无法解决的故障进行分析,构建了基于数据驱动的水轮机调速系统健康状态预测系统。The hydraulic turbine governing system is the key control system of the hydro-turbine generator unit. In this paper,the fault tree method and the expert system are combined to predict the potential faults of the governing system.Based on the historical data,a data-driven health status prediction system is developed for the hydraulic turbine governing system to detect the possible factors of the faults and analyze the unsolved faults