Burst detection in water distribution system using the extended Kalman filter

D. Jung; K. Lansey

doi:10.1016/j.proeng.2014.02.100

Burst detection in water distribution system using the extended Kalman filter

D. Jung
, K. Lansey

Research output: Contribution to journal › Conference article › peer-review

11 Scopus citations

Abstract

A water distribution system burst from a pipe rupture results in water loss and disruptions of customer service. Numerous methods, including Statistical Process Control, time series modeling, and pattern recognition, have been applied to detect bursts. However, system changes its boundary conditions such as the set of operating pumps and valve closures greatly complicating the detection problem. Thus, to date applications have been limited to the network supplied by gravity or under constant boundary conditions. This study seeks to overcome these limitation using the Kalman filter method to estimate the system state and detect bursts.

Original language	English (US)
Pages (from-to)	902-906
Number of pages	5
Journal	Procedia Engineering
Volume	70
DOIs	https://doi.org/10.1016/j.proeng.2014.02.100
State	Published - 2014
Event	12th International Conference on Computing and Control for the Water Industry, CCWI 2013 - Perugia, Italy Duration: Sep 2 2013 → Sep 4 2013

Keywords

Burst detection
Extended Kalam filter (EKF)
Innovation sequence

ASJC Scopus subject areas

General Engineering

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10.1016/j.proeng.2014.02.100

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title = "Burst detection in water distribution system using the extended Kalman filter",

abstract = "A water distribution system burst from a pipe rupture results in water loss and disruptions of customer service. Numerous methods, including Statistical Process Control, time series modeling, and pattern recognition, have been applied to detect bursts. However, system changes its boundary conditions such as the set of operating pumps and valve closures greatly complicating the detection problem. Thus, to date applications have been limited to the network supplied by gravity or under constant boundary conditions. This study seeks to overcome these limitation using the Kalman filter method to estimate the system state and detect bursts.",

keywords = "Burst detection, Extended Kalam filter (EKF), Innovation sequence",

author = "D. Jung and K. Lansey",

note = "Funding Information: This material is based in part upon work supported by the National Science Foundation under Grant No. 083590. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.; 12th International Conference on Computing and Control for the Water Industry, CCWI 2013 ; Conference date: 02-09-2013 Through 04-09-2013",

year = "2014",

doi = "10.1016/j.proeng.2014.02.100",

language = "English (US)",

volume = "70",

pages = "902--906",

journal = "Procedia Engineering",

issn = "1877-7058",

publisher = "Elsevier Limited",

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TY - JOUR

T1 - Burst detection in water distribution system using the extended Kalman filter

AU - Jung, D.

AU - Lansey, K.

N1 - Funding Information: This material is based in part upon work supported by the National Science Foundation under Grant No. 083590. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.

PY - 2014

Y1 - 2014

N2 - A water distribution system burst from a pipe rupture results in water loss and disruptions of customer service. Numerous methods, including Statistical Process Control, time series modeling, and pattern recognition, have been applied to detect bursts. However, system changes its boundary conditions such as the set of operating pumps and valve closures greatly complicating the detection problem. Thus, to date applications have been limited to the network supplied by gravity or under constant boundary conditions. This study seeks to overcome these limitation using the Kalman filter method to estimate the system state and detect bursts.

AB - A water distribution system burst from a pipe rupture results in water loss and disruptions of customer service. Numerous methods, including Statistical Process Control, time series modeling, and pattern recognition, have been applied to detect bursts. However, system changes its boundary conditions such as the set of operating pumps and valve closures greatly complicating the detection problem. Thus, to date applications have been limited to the network supplied by gravity or under constant boundary conditions. This study seeks to overcome these limitation using the Kalman filter method to estimate the system state and detect bursts.

KW - Burst detection

KW - Extended Kalam filter (EKF)

KW - Innovation sequence

UR - https://www.scopus.com/pages/publications/84899677193

UR - https://www.scopus.com/pages/publications/84899677193#tab=citedBy

U2 - 10.1016/j.proeng.2014.02.100

DO - 10.1016/j.proeng.2014.02.100

M3 - Conference article

AN - SCOPUS:84899677193

SN - 1877-7058

VL - 70

SP - 902

EP - 906

JO - Procedia Engineering

JF - Procedia Engineering

T2 - 12th International Conference on Computing and Control for the Water Industry, CCWI 2013

Y2 - 2 September 2013 through 4 September 2013

ER -

Burst detection in water distribution system using the extended Kalman filter

Abstract

Keywords

ASJC Scopus subject areas

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