A fuzzy diagnosis method in process systems with feedback control loops

Chuei-Tin Chang, Sheng Yung Chang

Research output: Contribution to journalConference article

Abstract

By considering the fault propagation behaviors in process systems with control loops, a fuzzy-logic based fault diagnosis strategy has been developed in the present work. The proposed fault diagnosis methods can be implemented in two stages. In the off-line preparation stage, the potential causes of a system hazard are identified by deterrnining the minimal cut sets of a fault tree. The occurrence order of observable fault symptoms is derived frorn the system digraph and then encoded into a set of IF-THEN rules. In the next on-line diagnosis stage, the occurrence indices of the top event and also the fault origins are computed in a fuzzy inference system based on real-time measurement data. Simulation studies have been carried out to demonstrate the feasibility of the proposed approach.

Original languageEnglish
Pages (from-to)267-272
Number of pages6
JournalIFAC Proceedings Volumes (IFAC-PapersOnline)
Volume36
Issue number12
DOIs
Publication statusPublished - 2003 Jan 1
Event5th IFAC International Symposium on Intelligent Components and Instruments for Control Applications, SICICA 2003 - Aveiro, Portugal
Duration: 2003 Jul 92003 Jul 11

Fingerprint

Feedback control
Failure analysis
Fuzzy inference
Time measurement
Fuzzy logic
Hazards

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering

Cite this

@article{199260e36a114259baae2447ae489ede,
title = "A fuzzy diagnosis method in process systems with feedback control loops",
abstract = "By considering the fault propagation behaviors in process systems with control loops, a fuzzy-logic based fault diagnosis strategy has been developed in the present work. The proposed fault diagnosis methods can be implemented in two stages. In the off-line preparation stage, the potential causes of a system hazard are identified by deterrnining the minimal cut sets of a fault tree. The occurrence order of observable fault symptoms is derived frorn the system digraph and then encoded into a set of IF-THEN rules. In the next on-line diagnosis stage, the occurrence indices of the top event and also the fault origins are computed in a fuzzy inference system based on real-time measurement data. Simulation studies have been carried out to demonstrate the feasibility of the proposed approach.",
author = "Chuei-Tin Chang and Chang, {Sheng Yung}",
year = "2003",
month = "1",
day = "1",
doi = "10.1016/S1474-6670(17)32545-4",
language = "English",
volume = "36",
pages = "267--272",
journal = "IFAC-PapersOnLine",
issn = "2405-8963",
publisher = "IFAC Secretariat",
number = "12",

}

A fuzzy diagnosis method in process systems with feedback control loops. / Chang, Chuei-Tin; Chang, Sheng Yung.

In: IFAC Proceedings Volumes (IFAC-PapersOnline), Vol. 36, No. 12, 01.01.2003, p. 267-272.

Research output: Contribution to journalConference article

TY - JOUR

T1 - A fuzzy diagnosis method in process systems with feedback control loops

AU - Chang, Chuei-Tin

AU - Chang, Sheng Yung

PY - 2003/1/1

Y1 - 2003/1/1

N2 - By considering the fault propagation behaviors in process systems with control loops, a fuzzy-logic based fault diagnosis strategy has been developed in the present work. The proposed fault diagnosis methods can be implemented in two stages. In the off-line preparation stage, the potential causes of a system hazard are identified by deterrnining the minimal cut sets of a fault tree. The occurrence order of observable fault symptoms is derived frorn the system digraph and then encoded into a set of IF-THEN rules. In the next on-line diagnosis stage, the occurrence indices of the top event and also the fault origins are computed in a fuzzy inference system based on real-time measurement data. Simulation studies have been carried out to demonstrate the feasibility of the proposed approach.

AB - By considering the fault propagation behaviors in process systems with control loops, a fuzzy-logic based fault diagnosis strategy has been developed in the present work. The proposed fault diagnosis methods can be implemented in two stages. In the off-line preparation stage, the potential causes of a system hazard are identified by deterrnining the minimal cut sets of a fault tree. The occurrence order of observable fault symptoms is derived frorn the system digraph and then encoded into a set of IF-THEN rules. In the next on-line diagnosis stage, the occurrence indices of the top event and also the fault origins are computed in a fuzzy inference system based on real-time measurement data. Simulation studies have been carried out to demonstrate the feasibility of the proposed approach.

UR - http://www.scopus.com/inward/record.url?scp=85064488532&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85064488532&partnerID=8YFLogxK

U2 - 10.1016/S1474-6670(17)32545-4

DO - 10.1016/S1474-6670(17)32545-4

M3 - Conference article

AN - SCOPUS:85064488532

VL - 36

SP - 267

EP - 272

JO - IFAC-PapersOnLine

JF - IFAC-PapersOnLine

SN - 2405-8963

IS - 12

ER -