Rolling Bearing Faults Diagnosis Method Based on SVM-HMM

摘要：

This paper presents a new scheme of bearing fault diagnosis based on SVM and HMM. Combining the classification ability of SVM and the ability of HMM to distinguish dynamic time series, by means of the sigmoid function and Gaussian model, we translate the information output of SVM into the form of posterior probability, and then introduce it into the observation probability estimation of hidden states in HMM model. Feature vectors used in diagnosis are established by AR parameters. The scheme was tested with experimental data extracted from the high frequency resonant vibration signal of bearing by wawelet analysis.

关键词： SVM-HMM model fault diagnosis bearing

作者: Bin Wu Shanping Yu Yuegang Luo Changjian Feng

作者单位: College of Electromechanical and Information Engineering, Dalian Nationalities University, Dalian, 1 College of Electromechanical and Information Engineering, Dalian Nationalities University, Dalian, 1

会议类型: 国际会议

会议名称: 2010 International Conference on Measuring Technology and Mechatronics Automation(ICMTMA 2010)(2010年检测技术与机电自动化国际会议)

会议地点: 长沙

会议语种:英文

页码: 2549-2552

在线出版日期: 2010-03-13（万方平台首次上网日期，不代表论文的发表时间）