Fault Diagnosis and Knowledge Management of Turbo-generator based on Support Vector Machine

摘要：

Support vector machine (SVM) which overcomes the drawbacks of neural networks has been widely used for pattern recognition in recent years. In the study, the proposed SVM model is applied to fault diagnosis of turbo-generator, and the method of knowledge management in SVM diagnostic system of turbo-generator is presented. The real data sets are used to investigate its feasibility in fault diagnosis of turbo-generator. The experimental results show that SVM not only has high diagnostic accuracy, but also has excellent antinoise capability.

作者: Zhong-jian Cai Sheng Lu Fengchuan Zhang

作者单位: School of Computer Science and Information Engineering Chongqing Technology and Business University Guangxi Special Equipment Supervision and Inspection Institute Nanning ,China

会议类型: 国际会议

会议名称: 2009 2nd IEEE International Conference on Computer Science and Information Technology(第二届计算机科学与信息技术国际会议 ICCSIT2009)

会议地点: 北京

会议语种:英文

页码: 532-535

在线出版日期: 2009-08-08（万方平台首次上网日期，不代表论文的发表时间）