Rolling element bearing diagnosis using convex hull

In this paper, we compare traditional classifiers, such as Linear and Quadratic Discriminant Classifiers and neural networks, with a one-class classifier, namely, convex hull. With reference to rolling element bearing diagnosis, we show that convex hull outperforms traditional classifiers in the classification of faults and different levels of fault severity not known during the training phase.