Research and application of a hierarchical fault diagnosis system based on support vector machine

被引：0

作者：

Liu, Ailun ^{[1
]}

Yuan, Xiaoyan ^{[1
]}

Yu, Jinshou ^{[1
]}

机构：

[1] E China Univ Sci & Technol, Res Inst Automat, Shanghai 200237, Peoples R China

来源：

ICNC 2007: THIRD INTERNATIONAL CONFERENCE ON NATURAL COMPUTATION, VOL 2, PROCEEDINGS | 2007年

关键词：

support Vector Machine (SVM); fault diagnosis; pattern recognition;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Support Vector Machine (SVM) is a kind of machine learning method based on the statistical learning theory, it has been applied in the fault diagnosis field. After analyzing SVM pattern classification theory, a hierarchical structure Fault Detection and Identification (FDI) system is presented in this paper, and simulation results show that this method can effectively handle the complex process characteristic and improve FDI model performance.

引用

页码：59 / +

页数：2

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