Fault Diagnosis of Pump Based on a Hybrid HMM/SVM Model

摘要：

A hybrid support vector machine (SVM) and hidden Markov model (HMM) model was introduced into the fault diagnosis of pump. This model had double layers: the first layer used HMM to classify preliminarily in order to get the coverage of possible faults; the second layer utilized this information to activate the corresponding SVMs for improving the recognition accuracy. The structure of this hybrid model was clear and feasible. Especially the model had the potential of large-scale multiclass application in fault diagnosis because of its good scalability. The recognition experiments of 26 statuses on the ZLH600-2 pump showed that the recognition capability of this model was sound in multiclass problems. The recognition rate of one bearing eccentricity increased from SVM’s 84.42％ to 89.61％ while the average recognition rate of hybrid model reached 95.05％. Although some goals while model constructed did not be fully realized, this model was still very good in practical applications.

关键词： Fault diagnosis Pump HMM SVM Hybrid model

作者: X. Yue C.L. Zhang J. Li H.Y. Zhu

作者单位: School of Mechanical and Automotive Engineering, South China University of Technology,Guangzhou, Chi School of Mechanical and Electric Engineer, Guangzhou University, Guangzhou, China School of Mechanical Engineering, University of South China, Hengyang, China

会议类型: 国际会议

会议名称: The 4th International Conference on High Speed Machining(第四届高速加工国际会议 ICHSM2010)

会议地点: 武汉

会议语种:英文

页码: 629-635

在线出版日期: 2011-05-28（万方平台首次上网日期，不代表论文的发表时间）