Fault Diagnosis of CNC Machine Using Hybrid Neural Network

摘要：

This paper proposed a technology of fault diagnosis for CNC machine based on hybrid neural network. Before the fault diagnosis was made, the fault patterns were firstly obtained from technical manuals and field experience to build a sample set, and then they were classified and coded according to the rule. In order to improve diagnosis speed, the fault diagnosis system was designed as a hybrid neural network system which consists of two-grade neural networks. When the fault pattern was input the system, the fault was first classified by the firstgrade BP network, and according to the fault type, the corresponding second-grade ART network was activated to perform fault diagnosis. In this paper, the train algorithms of two kinds of neural networks were programmed by MATLAB. Comparing with the traditional diagnosis method, the presented technology possesses advantages of automatic fault diagnosis and ability for self-learning and selforganization.

关键词： CNC machine Fault diagnosis BP neural network ART neural network

作者: Juan DU Xianguo YAN Nasha Wei

作者单位: College of Mechanical Engineering, Taiyuan University of Science and Technology, taiyuan,Shanxi, 030 College of Mechanical Engineering,Taiyuan University of Science and Technology, taiyuan,Shanxi, 0300

会议类型: 国际会议

会议名称: 4th International Conference on Measuring Technology and Mechatronics Automation(第四届检测技术与机电自动化国际会议 ICMTMA 2012)

会议地点: 三亚

会议语种:英文

页码: 865-869

在线出版日期: 2012-01-06（万方平台首次上网日期，不代表论文的发表时间）