Full- and reduced-order fault detection filter design with application in flow transmission lines

Saeed Salavati, Karolos Grigoriadis, Matthew Franchek, Reza Tafreshi

Research output: Contribution to journalArticle

Abstract

The full- and reduced-order fault detection filter design is examined for fault diagnosis in linear time-invariant (LTI) systems in the presence of noise and disturbances. The fault detection filter design problem is formulated as an H problem using a linear fractional transformation (LFT) framework and the solution is based on the bounded real lemma (BRL). Necessary and sufficient conditions for the existence of the fault detection filter are presented in the form of linear matrix inequalities (LMIs) resulting in a convex problem for the full-order filter design and a rank-constrained nonconvex problem for the reduced-order filter design. By minimizing the sensitivity of the filter residuals to noise and disturbances, the fault detection objective is fulfilled. A reference model can be incorporated in the design in order to shape the desired performance of the fault detection filter. The proposed fault detection and isolation (FDI) framework is applied to detect instrumentation and sensor faults in fluid transmission and pipeline systems. To this end, a lumped parameter framework for modeling infinite-dimensional fluid transient systems is utilized and a low-order model is obtained to pursue the instrumentation fault diagnosis objective. Full- and reduced-order filters are designed for sensor FDI. Simulations are conducted to assess the effectiveness of the proposed fault detection approach.

LanguageEnglish
Article number021010
JournalJournal of Dynamic Systems, Measurement and Control, Transactions of the ASME
Volume141
Issue number2
DOIs
Publication statusPublished - 1 Feb 2019

Fingerprint

fault detection
Fault detection
transmission lines
Electric lines
filters
reduced order filters
Failure analysis
transmission fluids
isolation
disturbances
linear transformations
Fluids
sensors
Sensors
Linear matrix inequalities
theorems
Pipelines
fluids
sensitivity

Keywords

  • fault detection
  • linear matrix inequalities
  • nonconvex and rank constraints
  • pipeline lumped model
  • robust H filtering
  • transmission lines

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Information Systems
  • Instrumentation
  • Mechanical Engineering
  • Computer Science Applications

Cite this

Full- and reduced-order fault detection filter design with application in flow transmission lines. / Salavati, Saeed; Grigoriadis, Karolos; Franchek, Matthew; Tafreshi, Reza.

In: Journal of Dynamic Systems, Measurement and Control, Transactions of the ASME, Vol. 141, No. 2, 021010, 01.02.2019.

Research output: Contribution to journalArticle

@article{2738c2fed5234177860597d26789afde,
title = "Full- and reduced-order fault detection filter design with application in flow transmission lines",
abstract = "The full- and reduced-order fault detection filter design is examined for fault diagnosis in linear time-invariant (LTI) systems in the presence of noise and disturbances. The fault detection filter design problem is formulated as an H∞ problem using a linear fractional transformation (LFT) framework and the solution is based on the bounded real lemma (BRL). Necessary and sufficient conditions for the existence of the fault detection filter are presented in the form of linear matrix inequalities (LMIs) resulting in a convex problem for the full-order filter design and a rank-constrained nonconvex problem for the reduced-order filter design. By minimizing the sensitivity of the filter residuals to noise and disturbances, the fault detection objective is fulfilled. A reference model can be incorporated in the design in order to shape the desired performance of the fault detection filter. The proposed fault detection and isolation (FDI) framework is applied to detect instrumentation and sensor faults in fluid transmission and pipeline systems. To this end, a lumped parameter framework for modeling infinite-dimensional fluid transient systems is utilized and a low-order model is obtained to pursue the instrumentation fault diagnosis objective. Full- and reduced-order filters are designed for sensor FDI. Simulations are conducted to assess the effectiveness of the proposed fault detection approach.",
keywords = "fault detection, linear matrix inequalities, nonconvex and rank constraints, pipeline lumped model, robust H filtering, transmission lines",
author = "Saeed Salavati and Karolos Grigoriadis and Matthew Franchek and Reza Tafreshi",
year = "2019",
month = "2",
day = "1",
doi = "10.1115/1.4041383",
language = "English",
volume = "141",
journal = "Journal of Dynamic Systems, Measurement and Control, Transactions of the ASME",
issn = "0022-0434",
publisher = "American Society of Mechanical Engineers(ASME)",
number = "2",

}

TY - JOUR

T1 - Full- and reduced-order fault detection filter design with application in flow transmission lines

AU - Salavati, Saeed

AU - Grigoriadis, Karolos

AU - Franchek, Matthew

AU - Tafreshi, Reza

PY - 2019/2/1

Y1 - 2019/2/1

N2 - The full- and reduced-order fault detection filter design is examined for fault diagnosis in linear time-invariant (LTI) systems in the presence of noise and disturbances. The fault detection filter design problem is formulated as an H∞ problem using a linear fractional transformation (LFT) framework and the solution is based on the bounded real lemma (BRL). Necessary and sufficient conditions for the existence of the fault detection filter are presented in the form of linear matrix inequalities (LMIs) resulting in a convex problem for the full-order filter design and a rank-constrained nonconvex problem for the reduced-order filter design. By minimizing the sensitivity of the filter residuals to noise and disturbances, the fault detection objective is fulfilled. A reference model can be incorporated in the design in order to shape the desired performance of the fault detection filter. The proposed fault detection and isolation (FDI) framework is applied to detect instrumentation and sensor faults in fluid transmission and pipeline systems. To this end, a lumped parameter framework for modeling infinite-dimensional fluid transient systems is utilized and a low-order model is obtained to pursue the instrumentation fault diagnosis objective. Full- and reduced-order filters are designed for sensor FDI. Simulations are conducted to assess the effectiveness of the proposed fault detection approach.

AB - The full- and reduced-order fault detection filter design is examined for fault diagnosis in linear time-invariant (LTI) systems in the presence of noise and disturbances. The fault detection filter design problem is formulated as an H∞ problem using a linear fractional transformation (LFT) framework and the solution is based on the bounded real lemma (BRL). Necessary and sufficient conditions for the existence of the fault detection filter are presented in the form of linear matrix inequalities (LMIs) resulting in a convex problem for the full-order filter design and a rank-constrained nonconvex problem for the reduced-order filter design. By minimizing the sensitivity of the filter residuals to noise and disturbances, the fault detection objective is fulfilled. A reference model can be incorporated in the design in order to shape the desired performance of the fault detection filter. The proposed fault detection and isolation (FDI) framework is applied to detect instrumentation and sensor faults in fluid transmission and pipeline systems. To this end, a lumped parameter framework for modeling infinite-dimensional fluid transient systems is utilized and a low-order model is obtained to pursue the instrumentation fault diagnosis objective. Full- and reduced-order filters are designed for sensor FDI. Simulations are conducted to assess the effectiveness of the proposed fault detection approach.

KW - fault detection

KW - linear matrix inequalities

KW - nonconvex and rank constraints

KW - pipeline lumped model

KW - robust H filtering

KW - transmission lines

UR - http://www.scopus.com/inward/record.url?scp=85054979026&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85054979026&partnerID=8YFLogxK

U2 - 10.1115/1.4041383

DO - 10.1115/1.4041383

M3 - Article

VL - 141

JO - Journal of Dynamic Systems, Measurement and Control, Transactions of the ASME

T2 - Journal of Dynamic Systems, Measurement and Control, Transactions of the ASME

JF - Journal of Dynamic Systems, Measurement and Control, Transactions of the ASME

SN - 0022-0434

IS - 2

M1 - 021010

ER -