Model based statistical process control for continuous systems

被引：1
|
作者：
Linstrom, PJ [1 ]
Asbjornsen, OA [1 ]
机构：
[1] UNIV TRONDHEIM,NORWEGIAN INST TECHNOL,DEPT MECH ENGN,DIV THERMAL ENERGY & HYDROPOWER,N-7034 TRONDHEIM,NORWAY
来源：
JOURNAL OF DYNAMIC SYSTEMS MEASUREMENT AND CONTROL-TRANSACTIONS OF THE ASME | 1996年 / 118卷 / 02期
关键词：
D O I：
10.1115/1.2802316
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Statistical process control (SPC) is a set of methodologies for signaling the presence of undesired sources of variation in manufacturing processes. SPC methods for continuous processes may be developed by using stochastic models which do not assume that successive observations are independent. A method for applying SPC to continuous processes is presented. This method incorporates a computationally efficient procedure for the on-dine identification and estimation of autoregressive with exogenous inputs (ARX) models. Two examples illustrating the method for SPC monitoring are presented.
引用
收藏
页码：283 / 289
页数：7
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