Causal model based supervising and training

被引：0
|
作者：
Evsukoff', A [1 ]
Montmain, J [1 ]
Gentil, S [1 ]
机构：
[1] Univ Grenoble 1, INPG, CNRS, Lab Automat Grenoble, F-38402 St Martin Dheres, France
来源：
ON-LINE FAULT DETECTION AND SUPERVISION IN THE CHEMICAL PROCESS INDUSTRIES 1998 | 1998年
关键词：
fault detection and isolation; knowledge-based systems; fuzzy logic; supervision system; computer aided training;
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：
In this work, causal models are proposed as a basis for knowledge representation of complex process dynamics. A prototype system has been implemented for a specific application in a nuclear fuel reprocessing plant. In this system, a causal model, built from expert knowledge, is used for operator support in process supervision and training. A fuzzy logic decision analysis provides a continuous transition from quantitative data into qualitative information and avoids threshold effects. An evaluation of the prototype system has been carried out by students of a technical school and its results are discussed in this paper. Copyright (C) 1998 IFAC.
引用
收藏
页码：237 / 242
页数：6
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