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Advanced fuzzy-based leak detection and size estimation for pipelines.

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Title: Advanced fuzzy-based leak detection and size estimation for pipelines.
Authors: Piltan, Farzin1 (AUTHOR), Kim, Jong-Myon2 (AUTHOR) jmkim07@ulsan.ac.kr, Kahraman, Cengiz (AUTHOR)
Source: Journal of Intelligent & Fuzzy Systems. 2020, Vol. 38 Issue 1, p947-961. 15p.
Subjects: Leak detection, Hyperbolic processes, Leakage, Pipelines, Hyperbolic differential equations, Gas leakage, Natural gas pipelines, Pressure sensors
Abstract: The design of an effective procedure for leak detection, estimation, and leak size classification is necessary to maintain the healthy and safe operations of pipelines for conveying fluids and gas from one place to another. The complexities of nonlinear and uncertain behavior inherent in a pipeline lead to difficulty of detection, estimation, and leak size estimation. Hence, a robust hybrid leak detection and size estimation method based on the back stepping hyperbolic Takagi-Sugeno (T-S) fuzzy sliding mode extended ARX-Laguerre Proportional Integral (PI) observer for pipelines is presented. Because of the effects of gases and fluids in pipelines, accurate physical modeling of a pipeline is difficult. Consequently, the ARX-Laguerre technique is used for pipeline modeling in this study. Early detection of leaks is important to avoid product loss and other severe damage. To address this issue, the extended ARX-Laguerre PI observer is utilized to detect and estimate a leak. In addition, a T-S fuzzy technique is applied to an extended ARX-Laguerre PI observer to improve leak estimation in the presence of uncertainties. Thus, the T-S fuzzy sliding mode extended ARX-Laguerre PI observer adaptively improves the reliability, robustness, and estimation accuracy of leak detection and estimation. To leak size classification in the presence of uncertainties, the hyperbolic differential equations are governed by the T-S fuzzy extended ARX-Laguerre PI observer to find the exact solution for the kernels of a backstepping-based leak boundary. The leak estimation convergence error shows that the leak size estimation can be calculated independent of the location of the leak, which is the main contribution of this research. It is assumed that pressure and flowmeter sensors are available at the inlet and outlet of the pipeline. The effectiveness of the proposed robust backstepping hyperbolic T-S fuzzy sliding mode extended ARX-Laguerre PI observer was tested over an experimental dataset. According to the results, the proposed technique improved the leak detection, estimation, and size estimation. [ABSTRACT FROM AUTHOR]
Copyright of Journal of Intelligent & Fuzzy Systems is the property of Sage Publications Inc. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: Advanced fuzzy-based leak detection and size estimation for pipelines.
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  Data: <searchLink fieldCode="DE" term="%22Leak+detection%22">Leak detection</searchLink><br /><searchLink fieldCode="DE" term="%22Hyperbolic+processes%22">Hyperbolic processes</searchLink><br /><searchLink fieldCode="DE" term="%22Leakage%22">Leakage</searchLink><br /><searchLink fieldCode="DE" term="%22Pipelines%22">Pipelines</searchLink><br /><searchLink fieldCode="DE" term="%22Hyperbolic+differential+equations%22">Hyperbolic differential equations</searchLink><br /><searchLink fieldCode="DE" term="%22Gas+leakage%22">Gas leakage</searchLink><br /><searchLink fieldCode="DE" term="%22Natural+gas+pipelines%22">Natural gas pipelines</searchLink><br /><searchLink fieldCode="DE" term="%22Pressure+sensors%22">Pressure sensors</searchLink>
– Name: Abstract
  Label: Abstract
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  Data: The design of an effective procedure for leak detection, estimation, and leak size classification is necessary to maintain the healthy and safe operations of pipelines for conveying fluids and gas from one place to another. The complexities of nonlinear and uncertain behavior inherent in a pipeline lead to difficulty of detection, estimation, and leak size estimation. Hence, a robust hybrid leak detection and size estimation method based on the back stepping hyperbolic Takagi-Sugeno (T-S) fuzzy sliding mode extended ARX-Laguerre Proportional Integral (PI) observer for pipelines is presented. Because of the effects of gases and fluids in pipelines, accurate physical modeling of a pipeline is difficult. Consequently, the ARX-Laguerre technique is used for pipeline modeling in this study. Early detection of leaks is important to avoid product loss and other severe damage. To address this issue, the extended ARX-Laguerre PI observer is utilized to detect and estimate a leak. In addition, a T-S fuzzy technique is applied to an extended ARX-Laguerre PI observer to improve leak estimation in the presence of uncertainties. Thus, the T-S fuzzy sliding mode extended ARX-Laguerre PI observer adaptively improves the reliability, robustness, and estimation accuracy of leak detection and estimation. To leak size classification in the presence of uncertainties, the hyperbolic differential equations are governed by the T-S fuzzy extended ARX-Laguerre PI observer to find the exact solution for the kernels of a backstepping-based leak boundary. The leak estimation convergence error shows that the leak size estimation can be calculated independent of the location of the leak, which is the main contribution of this research. It is assumed that pressure and flowmeter sensors are available at the inlet and outlet of the pipeline. The effectiveness of the proposed robust backstepping hyperbolic T-S fuzzy sliding mode extended ARX-Laguerre PI observer was tested over an experimental dataset. According to the results, the proposed technique improved the leak detection, estimation, and size estimation. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
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  Group: Ab
  Data: <i>Copyright of Journal of Intelligent & Fuzzy Systems is the property of Sage Publications Inc. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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RecordInfo BibRecord:
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      – Type: doi
        Value: 10.3233/JIFS-179461
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      – Code: eng
        Text: English
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      Pagination:
        PageCount: 15
        StartPage: 947
    Subjects:
      – SubjectFull: Leak detection
        Type: general
      – SubjectFull: Hyperbolic processes
        Type: general
      – SubjectFull: Leakage
        Type: general
      – SubjectFull: Pipelines
        Type: general
      – SubjectFull: Hyperbolic differential equations
        Type: general
      – SubjectFull: Gas leakage
        Type: general
      – SubjectFull: Natural gas pipelines
        Type: general
      – SubjectFull: Pressure sensors
        Type: general
    Titles:
      – TitleFull: Advanced fuzzy-based leak detection and size estimation for pipelines.
        Type: main
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            NameFull: Piltan, Farzin
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            NameFull: Kim, Jong-Myon
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            NameFull: Kahraman, Cengiz
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          Dates:
            – D: 01
              M: 01
              Text: 2020
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              Y: 2020
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              Value: 38
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            – TitleFull: Journal of Intelligent & Fuzzy Systems
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