Distance Rejection in a Bayesian Network for Fault Diagnosis of Industrial Systems

被引：0

作者：

Verron, Sylvain ^{[1
]}

Tiplica, Teodor ^{[1
]}

Kobi, Abdessarnad ^{[1
]}

机构：

[1] Univ Angers, LASQUO ISTIA, F-49000 Angers, France

来源：

2008 MEDITERRANEAN CONFERENCE ON CONTROL AUTOMATION, VOLS 1-4 | 2008年

关键词：

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：

The purpose of this article is to present a method for industrial process diagnosis with bayesian network. The interest of the proposed method is to combine a discriminant analysis and a distance rejection in a bayesian network in order to detect new types of fault. The performances of this method are evaluated on the data of a benchmark example: the Tennessee Eastman Process. Three kinds of fault are taken into account on this complex process. The challenging objective is to obtain the minimal recognition error rate for these three faults and to obtain sufficient results in rejection of new types of fault.

引用

页码：496 / 501

页数：6

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