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Leakages in District Heating Networks-Model-Based Data Set Quality Assessment and Localization.
Vahldiek, Kai; Rüger, Bernd; Klawonn, Frank.
Afiliación
  • Vahldiek K; Institute for Information Engineering, Ostfalia University of Applied Sciences, Salzdahlumer Str. 46/48, 38302 Wolfenbuttel, Germany.
  • Rüger B; SWM Services GmbH, Emmy-Noether-Str. 2, 80992 Munchen, Germany.
  • Klawonn F; Institute for Information Engineering, Ostfalia University of Applied Sciences, Salzdahlumer Str. 46/48, 38302 Wolfenbuttel, Germany.
Sensors (Basel) ; 22(14)2022 Jul 15.
Article en En | MEDLINE | ID: mdl-35890979
Large spontaneous leakages in district heating networks (DHNs) require a separation of the affected network part, as interruption of the heat supply is imminent. Measurement data of 22 real events was analyzed for localization, but suitable results were not always achieved. In this paper, the reasons are investigated and a model for data evaluation (MoFoDatEv) is developed for further insights. This contains prior knowledge and a simplified physical model for the reaction of the DHN in the case of a large spontaneous leakage. A model like this does not exist so far. It determines the time point and the duration of the pressure drop of the pressure wave which is caused by such leakages. Both parameters and the evaluation time frame are optimized for each event separately. The quality assessment leads to a categorization of the events based on several parameters, and correlations between the pressure and the refill mass flow are found. A minimum leakage size is deduced for successful evaluation. Furthermore, MoFoDatEv can also be used for leakage localization directly, combining two steps from previous publications. Therefore, more data contribute to the result. The application is conducted with artificial data to prove the model concept, and also with real measurement data.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Calor / Calefacción Idioma: En Revista: Sensors (Basel) Año: 2022 Tipo del documento: Article País de afiliación: Alemania Pais de publicación: Suiza

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Calor / Calefacción Idioma: En Revista: Sensors (Basel) Año: 2022 Tipo del documento: Article País de afiliación: Alemania Pais de publicación: Suiza