Title:
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Flow meter data validation and reconstruction using neural networks: Application to the Barcelona water network
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Author:
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Rodríguez, Héctor; Puig Cayuela, Vicenç; Flores, Juan; López, Rodrigo
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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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Abstract:
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The use of false or erroneous data can lead to wrong decisions when operating a system. In case of a water distribution network, the use of incorrect data could lead to errors in the billing system, waste of energy, incorrect management of control elements, etc. This paper is focused on detecting Flow meters reading abnormalities by exploiting the temporal redundancy of the demand time series by means of artificial neural networks (ANN). Communication problems with the sensor generate missing data and bad maintenanceservice in the flow meters produce false data. In this work, a methodology to detect the false data (validate) and replace the missing or false data (reconstruct) is proposed. As a core methodology, ANNs are used to model the time series generated from the water demand flow meters, and use the confidence intervals to validate the information. To illustrate the proposed methodology, the application to flow meters in the water distribution network of Barcelona is used. |
Abstract:
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Subject(s):
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-Àrees temàtiques de la UPC::Informàtica -Failure analysis (Engineering) -Computational methods -Fault detection and identification -Neural networks -Errors de sistemes (Enginyeria) |
Rights:
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http://creativecommons.org/licenses/by-nc-nd/3.0/es/ |
Document type:
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Conference Object |
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