Gas Pipelines LPV Modelling and Identification for Leakage Detection

Jose A. Ramos; Paulo Lopes dos Santos; Teresa Paula Azevedo Perdicoulis; Gerhard Jank; Jorge L. Martins de Carvalho; J. Milhinhos

doi:10.1109/acc.2010.5531022

Gas Pipelines LPV Modelling and Identification for Leakage Detection

Jose A. Ramos
, Paulo Lopes dos Santos
, Teresa Paula Azevedo Perdicoulis
, Gerhard Jank
, Jorge L. Martins de Carvalho
, J. Milhinhos

Research output: Contribution to conference › Paper › peer-review

4 Scopus citations

Abstract

A new approach to gas leakage detection in high pressure distribution networks is proposed, where the pipeline is modelled as a Linear Parameter Varying (LPV) System driven by the source node mass flow with the pressure as the scheduling parameter, and the system output as the mass flow at the offtake. Using a recently proposed successive approximations LPV system subspace identification algorithm, the pipeline is thus identified from operational data. The leak is detected using a Kalman filter where the fault is treated as an augmented state. The effectiveness of this method is illustrated with an example with a mixture of real and simulated data.

Original language	American English
Pages	1211-1216
Number of pages	6
DOIs	https://doi.org/10.1109/acc.2010.5531022
State	Published - Jun 1 2010
Event	Proceedings of the 2010 American Control Conference - Baltimore, United States Duration: Jun 30 2010 → Jul 2 2010 https://ieeexplore.ieee.org/xpl/conhome/5512481/proceeding

Conference

Conference	Proceedings of the 2010 American Control Conference
Country/Territory	United States
City	Baltimore
Period	6/30/10 → 7/2/10
Internet address	https://ieeexplore.ieee.org/xpl/conhome/5512481/proceeding

ASJC Scopus Subject Areas

Control and Systems Engineering

Disciplines

Computer Sciences

Access to Document

10.1109/acc.2010.5531022

Cite this

@conference{05ca20042c914b378c702884332aa497,

title = "Gas Pipelines LPV Modelling and Identification for Leakage Detection",

abstract = " A new approach to gas leakage detection in high pressure distribution networks is proposed, where the pipeline is modelled as a Linear Parameter Varying (LPV) System driven by the source node mass flow with the pressure as the scheduling parameter, and the system output as the mass flow at the offtake. Using a recently proposed successive approximations LPV system subspace identification algorithm, the pipeline is thus identified from operational data. The leak is detected using a Kalman filter where the fault is treated as an augmented state. The effectiveness of this method is illustrated with an example with a mixture of real and simulated data.",

author = "Ramos, \{Jose A.\} and \{Lopes dos Santos\}, Paulo and \{Azevedo Perdicoulis\}, \{Teresa Paula\} and Gerhard Jank and \{Martins de Carvalho\}, \{Jorge L.\} and J. Milhinhos",

year = "2010",

month = jun,

day = "1",

doi = "10.1109/acc.2010.5531022",

language = "American English",

pages = "1211--1216",

note = "Proceedings of the 2010 American Control Conference ; Conference date: 30-06-2010 Through 02-07-2010",

url = "https://ieeexplore.ieee.org/xpl/conhome/5512481/proceeding",

}

TY - CONF

T1 - Gas Pipelines LPV Modelling and Identification for Leakage Detection

AU - Ramos, Jose A.

AU - Lopes dos Santos, Paulo

AU - Azevedo Perdicoulis, Teresa Paula

AU - Jank, Gerhard

AU - Martins de Carvalho, Jorge L.

AU - Milhinhos, J.

PY - 2010/6/1

Y1 - 2010/6/1

N2 - A new approach to gas leakage detection in high pressure distribution networks is proposed, where the pipeline is modelled as a Linear Parameter Varying (LPV) System driven by the source node mass flow with the pressure as the scheduling parameter, and the system output as the mass flow at the offtake. Using a recently proposed successive approximations LPV system subspace identification algorithm, the pipeline is thus identified from operational data. The leak is detected using a Kalman filter where the fault is treated as an augmented state. The effectiveness of this method is illustrated with an example with a mixture of real and simulated data.

AB - A new approach to gas leakage detection in high pressure distribution networks is proposed, where the pipeline is modelled as a Linear Parameter Varying (LPV) System driven by the source node mass flow with the pressure as the scheduling parameter, and the system output as the mass flow at the offtake. Using a recently proposed successive approximations LPV system subspace identification algorithm, the pipeline is thus identified from operational data. The leak is detected using a Kalman filter where the fault is treated as an augmented state. The effectiveness of this method is illustrated with an example with a mixture of real and simulated data.

UR - https://nsuworks.nova.edu/gscis_facarticles/401

U2 - 10.1109/acc.2010.5531022

DO - 10.1109/acc.2010.5531022

M3 - Paper

SP - 1211

EP - 1216

T2 - Proceedings of the 2010 American Control Conference

Y2 - 30 June 2010 through 2 July 2010

ER -

Gas Pipelines LPV Modelling and Identification for Leakage Detection

Abstract

Conference

ASJC Scopus Subject Areas

Disciplines

Access to Document

Other files and links

Fingerprint

Cite this