Research on on-line intelligent diagnosis system of coal mill based on PCA-SVM
In this paper,a fault diagnosis method based on PCA-SVM is proposed for the problems of frequent faults of coal mills in coal-fired power plants and poor real-time performance of manual monitoring.First,a fault diagnosis model of coal mills based on PCA-SVM is constructed,and the collected normal data is brought into the model training to obtain the characteristic values of the data set,and intelligent diagnosis and prediction are carried out according to the characteristic values.After that,the accuracy of the model is veri-fied by the test set,and the experimental verification shows that the accuracy rate can reach 99.6%.The method has high accuracy and reliability in the intelligent diagnosis and prediction of coal mills.At the same time,the online diagnosis function of coal mills is realized by updating parameters in the field.
万方数据
维普
