A neural network approach to fault diagnosis in industry system

被引：0

作者：

Kau, SW ^{[1
]}

Fang, CH ^{[1
]}

机构：

[1] Natl Kaohsiung Inst Technol, Dept Elect Engn, Tai Wan, Peoples R China

来源：

ICEMI'99: FOURTH INTERNATIONAL CONFERENCE ON ELECTRONIC MEASUREMENT & INSTRUMENTS, VOLS 1 AND 2, CONFERENCE PROCEEDINGS | 1999年

关键词：

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

This paper provides a hybrid neural network approach to model-based fault diagnosis techniques in industry chemistry and incinerator system. The case study is almost 20 static elements (bus-bar couples, lines, and transformers) and about 19 dynamic elements (circuit breaks and switches that alter the configuration of grid when their state is updated). A comparison of CPN, surd hybrid ANN methods is given.

引用

页码：873 / 878

页数：6

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