基于支持向量回归的发电机温度预测方法

Generator Temperature Prediction Method Based on the Support Vector Regression

发电机运行参数能够反映发电机的运行状态,不同的性能参数所包含的发电机状态信息量不同。由于发电机工作状态环境复杂,发电机的某一类故障特征可能导致多种参数出现异常,进而使得监测参数之间呈现出非线性映射。文章提出了一种基于支持向量回归的发电机温度预测方法,可以有效识别机组异常状态,保障了机组的安全可靠运行。

The operating parameters of the generator are able to reflect the operating state of the generator while different performance parameters contain different amount of generator state information.Because of the complex working environment of the generator,a certain type of fault characteristics of the generator may lead to various types of abnormal parameters,which further make the monitoring parameters show a nonlinear mapping.This paper proposes a generator temperature prediction method based on the support vector regression,capable for effectively identifying the abnormal state of the unit,to ensure the safe and reliable operation of the unit.