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

作者：Wu Xi Xi^*; Gao Hong Li; Yan Ji Ming; Zhao Min; Huang Bai Quan; Xu Ming Heng

来源：Computer Integrated Manufacturing Systems, 2010, 16(12): 2661-2667.

• Band energy
• Classifier models
• Correlation parameters
• Fault diagnosis
• Fault diagnosis technology
• Fault sample
• Feature vectors
• Hyper-sphere
• Machine screws
• Model parameters
• NC machine tools
• Novel methods
• Numerical control
• Numerical control machines
• Sphere support vectors
• Test results
• Wavelet packet
• Wavelet Packet Decomposition

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.

• 出版日期2010
• 单位西南交通大学