2PTMC classification algorithm based on support vector machines and its application to fault diagnosis
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Support vector machines is a new general machine learning tool based on structural risk minimization principle that exhibits good generalization. Fault diagnosis based on support vector machines is discussed. Since SVM was originally designed for binary classification, while most of fault diagnosis problems are multi-class cases, a new multi-class classification named 2PTMC is presented. This classifier is a binary tree classifier composed of several SVMs organized by fault priority, which is simple and has little duplicating training samples. The application to fault diagnosis for diesel engine shows the effectiveness of the method.