Abstract: Support vector machine(SVM) is a new general machine-learning tool based on structural risk minimization principle that exhibits good generalization even when fault samples are few. Fault diagnosis based on support vector ma-chines is discussed. Since basic support vector machines is originally designed for two-class classification, while most of fault diagnosis problems are multi-class cases, a new multi-class classification algorithm named mesh support vector machines is presented to solve the multi-class recognition prob-lems. It is a mesh classifier in which every class constructs two-class SVM classifiers with less than 4 other classes. It is simple and extensible, and has little repeated training amount, so the rate of training and recognition is expedited. The effec-tiveness of the method is verified by the application to the multi-fault diagnosis for turbo pump test bed.

Key words: Mesh, Multi-class classification, Support vector machines, Turbo-pump