文献类型：会议论文

英文题名：The fault diagnosis system with self-repair function for screw oil pump based on support vector machine

作者：Tian, Jingwen[1,2];Gao, Meijuan[1,2];Liu, Yanxia[1];Zhou, Hao[2];Li, Kai[2]

第一作者：Tian, Jingwen

通讯作者：Tian, JW[1]

机构：[1]Beijing Union Univ, Dept Automat Control, Beijing, Peoples R China;[2]Beijing Univ Chem Technol, Sch Informat Sci, Beijing, Peoples R China

第一机构：北京联合大学城市轨道交通与物流学院

通讯机构：[1]corresponding author), Beijing Union Univ, Dept Automat Control, Beijing, Peoples R China.|[1141751]北京联合大学城市轨道交通与物流学院;[11417]北京联合大学;

会议论文集：IEEE International Conference on Robotics and Biomimetics (ROBIO 2007)

会议日期：DEC 15-18, 2007

会议地点：Sanya, PEOPLES R CHINA

语种：英文

外文关键词：fault diagnosis; self-repair function; support vector machine; screw oil pump

摘要：Considering the issues that the relationship between the fault of screw oil pump existent and fault information is a complicated and nonlinear system, and it is very difficult to found the process model to describe it. The support vector machine (SVM) has the ability of strong nonlinear function approach and the ability of strong generalization and also has the feature of global optimization. In this paper, a fault diagnosis system with self-repair function for screw on pump based on SVM is presented. Moreover, the genetic algorithm (GA) was used to optimize SVM parameters. With the ability of strong self-learning and well generalization of SVM, the diagnosis system can truly diagnose the fault of screw off pump by learning the fault information. The real diagnosis results show that this system is feasible and effective.