Review of Quality-related Fault Detection and Diagnosis Techniques for Complex Industrial Processes

被引：0
|
作者：
Peng K.-X. [1 ,2 ]
Ma L. [1 ,2 ]
Zhang K. [1 ,2 ]
机构：
[1] School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing
[2] Key Laboratory for Advanced Control of Iron and Steel Process of Ministry of Education, Beijing
来源：
Zidonghua Xuebao/Acta Automatica Sinica | 2017年 / 43卷 / 03期
基金：
中国国家自然科学基金;
关键词：
Contribution plot; Fault detection; Fault diagnosis; Partial least squares (PLS); Quality-related;
D O I：
10.16383/j.aas.2017.c160427
中图分类号：
学科分类号：
摘要：
Quality-related fault detection and diagnosis techniques have been extensively applied to the process control field to guarantee production safety and product quality, which, thus, have recently become an active area of research both in academia and industry. Firstly, the basic idea and improvements of typical methods for quality-related fault detection techniques are introduced in this paper. Then, quality-related fault diagnosis techniques are revisited, with special case study attention on the contribution plot based methods and their improved methods, in which on a hot strip mill process (HSMP) is used to show their different performances. Finally, the state-of-the-art research of quality-related fault detection and diagnosis methods for main characteristics of complex industrial process operation data are reviewed, and open problems, challenges and perspectives for future research are presented as well. Copyright © 2017 Acta Automatica Sinica. All rights reserved.
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页码：349 / 365
页数：16
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