Detection and identification of bias faults in nonlinear system

Youmin Zhang; X. Rong Li; Xuedong Yang; Hongcai Zhang

Detection and identification of bias faults in nonlinear system

Youmin Zhang
, X. Rong Li
, Xuedong Yang
, Hongcai Zhang

University of New Orleans

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

Abstract

Although fault detection and identification (FDI) methods for linear systems have been developed extensively, FDI for nonlinear systems still deserves much attention. In order to detect bias type faults, a bias χ² FDI method is proposed here on the basis of the pseudo separated-bias estimation (PSBE) algorithm. Estimates of biases obtained by PSBE are used to construct a statistical variable which obeys χ² distribution in normal operational conditions. As a result, by testing if the constructed variable is χ² distributed at every estimation step, one can detect input-output bias faults quickly. In order to identify where a bias fault occurs, a bias component χ² detection scheme is proposed further. Simulation results of a paper machine illustrate the effectiveness of the method for real-time application.

Original language	English
Title of host publication	Proceedings of the IEEE Conference on Decision and Control
Editors	Anon
State	Published - 1996
Externally published	Yes
Event	Proceedings of the 1996 35th IEEE Conference on Decision and Control. Part 3 (of 4) - Kobe, Jpn Duration: 11 Dec 1996 → 13 Dec 1996

Publication series

Name	Proceedings of the IEEE Conference on Decision and Control
Volume	1
ISSN (Print)	0191-2216

Conference

Conference	Proceedings of the 1996 35th IEEE Conference on Decision and Control. Part 3 (of 4)
City	Kobe, Jpn
Period	11/12/96 → 13/12/96

Cite this

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title = "Detection and identification of bias faults in nonlinear system",

abstract = "Although fault detection and identification (FDI) methods for linear systems have been developed extensively, FDI for nonlinear systems still deserves much attention. In order to detect bias type faults, a bias χ2 FDI method is proposed here on the basis of the pseudo separated-bias estimation (PSBE) algorithm. Estimates of biases obtained by PSBE are used to construct a statistical variable which obeys χ2 distribution in normal operational conditions. As a result, by testing if the constructed variable is χ2 distributed at every estimation step, one can detect input-output bias faults quickly. In order to identify where a bias fault occurs, a bias component χ2 detection scheme is proposed further. Simulation results of a paper machine illustrate the effectiveness of the method for real-time application.",

author = "Youmin Zhang and Li, \{X. Rong\} and Xuedong Yang and Hongcai Zhang",

year = "1996",

language = "英语",

series = "Proceedings of the IEEE Conference on Decision and Control",

editor = "Anon",

booktitle = "Proceedings of the IEEE Conference on Decision and Control",

note = "Proceedings of the 1996 35th IEEE Conference on Decision and Control. Part 3 (of 4) ; Conference date: 11-12-1996 Through 13-12-1996",

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TY - CHAP

T1 - Detection and identification of bias faults in nonlinear system

AU - Zhang, Youmin

AU - Li, X. Rong

AU - Yang, Xuedong

AU - Zhang, Hongcai

PY - 1996

Y1 - 1996

N2 - Although fault detection and identification (FDI) methods for linear systems have been developed extensively, FDI for nonlinear systems still deserves much attention. In order to detect bias type faults, a bias χ2 FDI method is proposed here on the basis of the pseudo separated-bias estimation (PSBE) algorithm. Estimates of biases obtained by PSBE are used to construct a statistical variable which obeys χ2 distribution in normal operational conditions. As a result, by testing if the constructed variable is χ2 distributed at every estimation step, one can detect input-output bias faults quickly. In order to identify where a bias fault occurs, a bias component χ2 detection scheme is proposed further. Simulation results of a paper machine illustrate the effectiveness of the method for real-time application.

AB - Although fault detection and identification (FDI) methods for linear systems have been developed extensively, FDI for nonlinear systems still deserves much attention. In order to detect bias type faults, a bias χ2 FDI method is proposed here on the basis of the pseudo separated-bias estimation (PSBE) algorithm. Estimates of biases obtained by PSBE are used to construct a statistical variable which obeys χ2 distribution in normal operational conditions. As a result, by testing if the constructed variable is χ2 distributed at every estimation step, one can detect input-output bias faults quickly. In order to identify where a bias fault occurs, a bias component χ2 detection scheme is proposed further. Simulation results of a paper machine illustrate the effectiveness of the method for real-time application.

UR - https://www.scopus.com/pages/publications/0030406145

M3 - 章节

AN - SCOPUS:0030406145

T3 - Proceedings of the IEEE Conference on Decision and Control

BT - Proceedings of the IEEE Conference on Decision and Control

A2 - Anon, null

T2 - Proceedings of the 1996 35th IEEE Conference on Decision and Control. Part 3 (of 4)

Y2 - 11 December 1996 through 13 December 1996

ER -

Detection and identification of bias faults in nonlinear system

Abstract

Publication series

Conference

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