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    Comparison of AMI and SCADA Systems for Leak Detection and Localization in Water Distribution Networks

    Source: Journal of Water Resources Planning and Management:;2023:;Volume ( 149 ):;issue: 011::page 04023061-1
    Author:
    Sanghoon Jun
    ,
    Kevin E. Lansey
    DOI: 10.1061/JWRMD5.WRENG-5953
    Publisher: ASCE
    Abstract: Various water distribution leak detection and localization methods have been proposed for supervisory control and data acquisition (SCADA) data collection systems. However, because their available numbers of measurements are limited, the SCADA systems are often insufficient to identify realistic sized leaks. A clear next step is to develop detection and localization methods for smart systems that collect advanced metering infrastructure (AMI) data (i.e., AMI systems); however, only the authors have proposed tools for the AMI data collection systems. To encourage the usage of AMI data, this study tested five types of data collection systems for leak detection and localization that measure (1) only source flows, (2) source flows and a few nodal pressures, (3) source flows and AMI demands, (4) AMI demands and a few nodal pressures, and (5) AMI pressures and AMI demands. An appropriate leak detection and localization tool for each data collection system is applied and tested for two water distribution networks: one located in Austin, TX, and the other in Tucson, AZ. Each system’s performance was evaluated using metrics of detection probability, false alarm rate, time to detect, and localization pipe distance. Overall, based on the obtained results, the SCADA systems were poor in detecting realistic-sized leaks, while the AMI systems successfully identified those small failures. Thus, the AMI systems were required to improve detection, and a pressure-supplemented AMI system was necessary to obtain high localization performance, particularly for a large network, such as Austin, Texas.
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      Comparison of AMI and SCADA Systems for Leak Detection and Localization in Water Distribution Networks

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    contributor authorSanghoon Jun
    contributor authorKevin E. Lansey
    date accessioned2024-04-27T20:56:42Z
    date available2024-04-27T20:56:42Z
    date issued2023/11/01
    identifier other10.1061-JWRMD5.WRENG-5953.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4296302
    description abstractVarious water distribution leak detection and localization methods have been proposed for supervisory control and data acquisition (SCADA) data collection systems. However, because their available numbers of measurements are limited, the SCADA systems are often insufficient to identify realistic sized leaks. A clear next step is to develop detection and localization methods for smart systems that collect advanced metering infrastructure (AMI) data (i.e., AMI systems); however, only the authors have proposed tools for the AMI data collection systems. To encourage the usage of AMI data, this study tested five types of data collection systems for leak detection and localization that measure (1) only source flows, (2) source flows and a few nodal pressures, (3) source flows and AMI demands, (4) AMI demands and a few nodal pressures, and (5) AMI pressures and AMI demands. An appropriate leak detection and localization tool for each data collection system is applied and tested for two water distribution networks: one located in Austin, TX, and the other in Tucson, AZ. Each system’s performance was evaluated using metrics of detection probability, false alarm rate, time to detect, and localization pipe distance. Overall, based on the obtained results, the SCADA systems were poor in detecting realistic-sized leaks, while the AMI systems successfully identified those small failures. Thus, the AMI systems were required to improve detection, and a pressure-supplemented AMI system was necessary to obtain high localization performance, particularly for a large network, such as Austin, Texas.
    publisherASCE
    titleComparison of AMI and SCADA Systems for Leak Detection and Localization in Water Distribution Networks
    typeJournal Article
    journal volume149
    journal issue11
    journal titleJournal of Water Resources Planning and Management
    identifier doi10.1061/JWRMD5.WRENG-5953
    journal fristpage04023061-1
    journal lastpage04023061-11
    page11
    treeJournal of Water Resources Planning and Management:;2023:;Volume ( 149 ):;issue: 011
    contenttypeFulltext
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