Title:
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Online leak diagnosis in pipelines using an EKF-based and steady-state mixed approach
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Author:
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Santos Ruiz, Ildeberto de los; Bermúdez, Josu R.; López Estrada, Francisco Ronay; Puig Cayuela, Vicenç
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Other authors:
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Universitat Politècnica de Catalunya. Departament d'Enginyeria de Sistemes, Automàtica i Informàtica Industrial; Universitat Politècnica de Catalunya. SAC - Sistemes Avançats de Control |
Abstract:
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This paper proposes a methodology for leak detection and isolation (LDI) in pipelines based on data fusion from two approaches: a steady-state estimation and an Extended Kalman Filter (EKF). The proposed method considers only pressure head and flow rate measurements at the pipeline ends, which contain intrinsic sensor and process noise. The LDI system is tested in real-time by using an USB data acquisition device that is implemented in MATLAB environment. The effectiveness of the method is analyzed by considering: online detection, location as well as quantification of non-concurrent leaks at different positions. The leak estimation error average is less than 1% of the flow rate and less than 3% in the leakage position. Furthermore, the incorporation of a steady-state estimation shows that the solution of the LDI problem has improved significantly with respect to the one that only considers the EKF estimation. An experimental analysis was also performed on the effectiveness of the proposed approach for different sampling rates and for different leakage positions |
Abstract:
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Peer Reviewed |
Subject(s):
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-Àrees temàtiques de la UPC::Informàtica::Automàtica i control -Predictive control -Detectors -Pipelines -Leak diagnosis -Extended Kalman Filter -Data fusion -Steady state -Real-time -Control predictiu -Detectors de fuites |
Rights:
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Attribution-NonCommercial-NoDerivs 3.0 Spain
http://creativecommons.org/licenses/by-nc-nd/3.0/es/ |
Document type:
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Article - Submitted version Article |
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