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In this paper, we developed a fault diagnosis model based on signed digraph(SDG), support vector machine(SVM) and improved principal component analysis(PCA) method. In PCA, we set linear fault boundaries. By means of the system decomposition based on SDG, the local models of each measured variable are constructed and more accurate and fast models are using an SVM, which has no loss of information...
In this study, at first a hybrid local fault diagnostic model based on the signed digraph (SDG) which is a kind of model based approaches and a statistical learning model, support vector machine (SVM), would be proposed. And then, the fault intensity model and the fault boundary model were constructed for various fault intensities. Key aspects are the issue of resolving signatures resulting from the...
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