Subspace method aided data-driven design of fault detection and isolation systems

被引：256

作者：

Ding, S. X. ^{[1
]}

Zhang, P. ^{[4
]}

Naik, A. ^{[1
]}

Ding, E. L. ^{[2
]}

Huang, B. ^{[3
]}

机构：

[1] Univ Duisburg Essen, Inst Automat Control & Complex Syst, D-47057 Duisburg, Germany

[2] Univ Appl Sci Gelsenkirchen, Dept Engn Phys, D-45877 Gelsenkirchen, Germany

[3] Univ Alberta, Dept Chem & Mat Engn, Edmonton, AB T6G 2M7, Canada

[4] BASF SE, Automat Technol, D-67056 Ludwigshafen, Germany

来源：

JOURNAL OF PROCESS CONTROL | 2009年 / 19卷 / 09期

关键词：

Fault detection and isolation; Parity space methods; Observer based FDI systems; Subspace methods; Tennessee Eastman challenge process; IDENTIFICATION; SPACE;

D O I：

10.1016/j.jprocont.2009.07.005

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This paper deals with data-driven design of fault detection and isolation (FDI) systems. The basic idea is to identify a primary form of residual generators, instead of the process model, directly from test data and, based on it, to design advanced FDI systems. The proposed method can be applied for the parity space and observer based detection and isolation of sensor and actuator faults as well as the construction of soft-sensors. The application of the proposed method is illustrated by a simulation study on the Tennessee Eastman process. (C) 2009 Elsevier Ltd. All rights reserved.

引用

页码：1496 / 1510

页数：15