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

被引：0
|
作者：
Cai, Zhong-jian [1 ]
Lu, Sheng [1 ]
Zhang, Fengchuan [2 ]
机构：
[1] Chongqing Technol & Business Univ, Sch Comp Sci & Informat Engn, Chongqing, Peoples R China
[2] Inspect Inst, Guangxi Special Equipment Supervision, Nanning, Peoples R China
来源：
2009 2ND IEEE INTERNATIONAL CONFERENCE ON COMPUTER SCIENCE AND INFORMATION TECHNOLOGY, VOL 1 | 2009年
关键词：
D O I：
10.1109/ICCSIT.2009.5234891
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
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.
引用
收藏
页码：532 / +
页数：2
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