基于主元特征提取的汽轮机性能监测和故障诊断

Process Monitoring and Fault Identification of Turbine Generator Based on Principal Component Analysis and Similar Degree Analysis

提出了一种基于主元特征提取的汽轮机性能监测和故障诊断新方法,该方法充分利用了发电机的过程数据信息,通过计算监控统计量Hotelling’s T2和SPE来监测汽轮机的运行。若T2或SPE统计量超过置信上限,则判定系统存在故障或异常,可以通过相似度分析的方法来确定故障发生的原因,汽轮机历史故障数据集仿真试验验证了该方法的有效性。

A novel process monitoring and fault identification method based on principal component analysis and similar degree analysis is proposed.The basic idea of this method is to monitor the performance of turbine generator through T2 and SPE index.If T2 or SPE exceeds the 99% control limit,a fault may have occurred.Similar analysis is further used to perform fault diagnosis.Simulation results of the turbine generator＇s fault data set validate the effectiveness of proposed method.