Intelligent process monitoring by interfacing knowledge-based systems and multivariate spc tools

被引：0
|
作者：
Norvilas, A [1 ]
Negiz, A [1 ]
DeCicco, J [1 ]
Çinar, A [1 ]
机构：
[1] IIT, Dept Environm Chem & Engn, Chicago, IL 60616 USA
来源：
(SAFEPROCESS'97): FAULT DETECTION, SUPERVISION AND SAFETY FOR TECHNICAL PROCESSES 1997, VOLS 1-3 | 1998年
关键词：
knowledge-based system; multivariate statistical process monitoring; fault detection and diagnosis; canonical variate analysis; state space models;
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：
An intelligent process monitoring and fault diagnosis environment has been developed by interfacing multivariate statistical process monitoring (MSPM) techniques and knowledge-based systems (KBS) for monitoring multivariable process operation. In particular, the real-time KBS G2 and its Diagnostic Assistant (GDA) tool are used with multivariate SPM methods based oil canonical variate state space (CVSS) process models. Fault detection is based on T-2 charts of state variables, contribution plots in G2 are used for determining the process variables that have contributed to the out-of-control signal indicated by large T2 values, and GDA is used to diagnose the source cause of the abnormal process behavior, The MSPM modules developed ill Matlab are linked with G2 slid GDA. This setup extends the Statistical Process Control (GSPC) library of GDA significantly and permits the use of MSPM tools for autocorrelated data and multivariable processes. The presentation will focus oil the structure and performance of the integrated system. On-line SPM of multivariable processes will be illustrated Ly simulation studies. Copyright (C) 1998 IFAC.
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收藏
页码：43 / 48
页数：6
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