Signal grouping algorithm for an improved on-line calibration monitoring system

被引：0
|
作者：
Hoffmann, Mario [1 ]
机构：
[1] OECD Halden Reactor Project, NO-1751 Halden, Norway
来源：
Applied Artificial Intelligence | 2006年
关键词：
D O I：
10.1142/9789812774118_0135
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
On-Line Monitoring evaluates instrument channel performance by assessing its consistency with other process indications. In nuclear power plants the elimination or reduction of unnecessary field calibrations can reduce associated labor costs, reduce personnel radiation exposure, and reduce the potential for calibration errors. A signal validation system based on fuzzy-neural networks, called PEANO [1], has been developed to assist in on-line calibration monitoring. Currently the system can be applied to a limited set of channels. In this paper we will explore different grouping algorithms to make the system scalable and applicable in large applications.
引用
收藏
页码：970 / 976
页数：7
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