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Leakages in District Heating Networks—Model-Based Data Set Quality Assessment and Localization
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 reason...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9321529/ https://www.ncbi.nlm.nih.gov/pubmed/35890979 http://dx.doi.org/10.3390/s22145300 |
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author | Vahldiek, Kai Rüger, Bernd Klawonn, Frank |
author_facet | Vahldiek, Kai Rüger, Bernd Klawonn, Frank |
author_sort | Vahldiek, Kai |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-9321529 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-93215292022-07-27 Leakages in District Heating Networks—Model-Based Data Set Quality Assessment and Localization Vahldiek, Kai Rüger, Bernd Klawonn, Frank Sensors (Basel) Article 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. MDPI 2022-07-15 /pmc/articles/PMC9321529/ /pubmed/35890979 http://dx.doi.org/10.3390/s22145300 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Vahldiek, Kai Rüger, Bernd Klawonn, Frank Leakages in District Heating Networks—Model-Based Data Set Quality Assessment and Localization |
title | Leakages in District Heating Networks—Model-Based Data Set Quality Assessment and Localization |
title_full | Leakages in District Heating Networks—Model-Based Data Set Quality Assessment and Localization |
title_fullStr | Leakages in District Heating Networks—Model-Based Data Set Quality Assessment and Localization |
title_full_unstemmed | Leakages in District Heating Networks—Model-Based Data Set Quality Assessment and Localization |
title_short | Leakages in District Heating Networks—Model-Based Data Set Quality Assessment and Localization |
title_sort | leakages in district heating networks—model-based data set quality assessment and localization |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9321529/ https://www.ncbi.nlm.nih.gov/pubmed/35890979 http://dx.doi.org/10.3390/s22145300 |
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