Generator Temperature Prediction Method Based on the Support Vector Regression
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 mon-itoring 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.
support vector regressiontemperature predictionanomaly recognition
NETL
NSTL
万方数据
维普
