A Fault Diagnosis Strategy using Local Models, Fault Intensity and Boundary Models Based on SDG and Data-Driven Approaches

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 same fault but with differing intensities and making the decision tool to decide which a fault occurs.