Imperial smelting furnace fault diagnosis based on rough set and least squares support vector machine
Shaohua Jiang · 2008
Due to the incompleteness and complexity of fault diagnosis for imperial smelting furnace,a method based on Rough Set(RS) and Least Squares Support Vector Machine(LS_SVM) is proposed to identify the fault of imperial smelting furnace.Firstly,the discretization for the continuous attributes data in diagnostic decision system uses equal frequency scale.Then,diagnostic decision-making is reduced based on rough sets theory,the noise and redundancy in the sample are removed and the key conditions for diagnosis are determined.The model for fault diagnosis is established by combining the reduction results and LS_SVM.The experiment system implemented by this method shows a good diagnostic ability.