A fault diagnosis method based on composite model and SVM for fermentation process

被引：0

作者：

Ma, Liling ^{[1
]}

Wang, Junzheng ^{[1
]}

Liu, Zhigang ^{[1
]}

机构：

[1] Beijing Inst Technol, Dept Automat Control, Beijing 100081, Peoples R China

来源：

2007 IEEE INTERNATIONAL CONFERENCE ON CONTROL AND AUTOMATION, VOLS 1-7 | 2007年

关键词：

fault diagnosis; composite model; support vector machine; fermentation process;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

A method of fault diagnosis based on composite model and support vector machines for fermentation process is proposed to overcome its difficulty in direct measurement of state parameters. In order to obtain the process state, composite model is presented by combining mass equations of bioreactors with RBF neural network that serve as estimators of unmeasured process kinetic parameters. Then Support vector machines are used to analyze and recognize fault patterns, making use of estimated state variables on line. The proposed method is applied to glutamic acid fermentation process, and the simulation results show its feasibility and effectiveness.

引用

页码：1227 / 1230

页数：4

共 8 条

[1]

DEABHINANDAN, 2002, IEEE T POWER DELIVER, V17, P489

[2] Fusion of multi-class support vector machines for fault diagnosis [J].

Hu, ZH ;

Cai, YZ ;

He, X ;

Xu, XM .

ACC: PROCEEDINGS OF THE 2005 AMERICAN CONTROL CONFERENCE, VOLS 1-7, 2005, :1941-1945

[3]

Li Y, 2005, PROCEEDINGS OF 2005 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND CYBERNETICS, VOLS 1-9, P3309

[4]

LUO ZY, 2006, 1 INT S SYST CONTR A, P1026

[5]

SANG HF, 2006, P 6 WORLD INT CONTR, P4837

[6] RBF NN based marine diesel engine generator modeling [J].

Shi, WF ;

Yang, JM ;

Tang, TH .

ACC: Proceedings of the 2005 American Control Conference, Vols 1-7, 2005, :2745-2749

[7]

Vapnik V., 1998, STAT LEARNING THEORY, V1, P2

[8]

ZHAO Z, 1999, 14 TRIENN WORLD C IF, P145

← 1 →