Fault diagnosis technology for NC machine screw based on hyper-sphere support vector machines

It was difficult to obtain fault samples and the samples were distributed unevenly in Numerical Control(NC) machine tool screw.To deal with these problems,a novel method for screw fault diagnosis based on wavelet packet decomposition and Hyper-Sphere Support Vector Machines(HSSVM) classifier was put forward.The decomposed frequency band energy of vibration signal was selected as feature vectors and was inputted to HSSVM classifier which realized faults pattern recognition.The important role of model parameters selection in HSSVM classifier constructions were studied by shifting correlation parameters.Test results showed that HSSVM classifier model structured could detect screw faults of NC machine tool effectively.