A Fault Detection and Diagnosis Method Base on Principal Component Analysis and Support Vector Classifier Apply to Valve
The principal component analysis and support vector multi-classifier of the fault diagnosis method is introduced, first of all, the failure data has been extracted PCA data sets and reduce the characteristics of the data dimension ,Second, the failure characteristics data has been classified by support vector classifier, final diagnosis failure by features. Some simulations were carried out on DAMADICS valve model and Lublin Sugar Factory failure data is used to further verify. The simulation results show that the method can detection and diagnosis failure fast and accurately.
principal component analysissupport vector machinesfault diagnosisvalve failure
国家科技期刊平台
NSTL
万方数据
维普
