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Methods for Large-Scale Monitoring of District Heating Systems Using Airborne Thermography
Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology. Swedish Defence Research Agency, Linköping, Sweden.
Swedish Defence Research Agency, Linköping, Sweden.
Linköping University, Department of Electrical Engineering, Information Coding. Linköping University, The Institute of Technology. Termisk Systemteknik AB, Linköping, Sweden.ORCID iD: 0000-0002-6763-5487
Termisk Systemteknik AB, Linköping, Sweden.
2014 (English)In: IEEE Transactions on Geoscience and Remote Sensing, ISSN 0196-2892, E-ISSN 1558-0644, Vol. 52, no 8, 5175-5182 p.Article in journal (Refereed) Published
Abstract [en]

District heating is a common way of providing heat to buildings in urban areas. The heat is carried by hot water or steam and distributed in a network of pipes from a central powerplant. It is of great interest to minimize energy losses due to bad pipe insulation or leakages in such district heating networks. As the pipes generally are placed underground, it may be difficult to establish the presence and location of losses and leakages. Toward this end, this work presents methods for large-scale monitoring and detection of leakages by means of remote sensing using thermal cameras, so-called airborne thermography. The methods rely on the fact that underground losses in district heating systems lead to increased surface temperatures. The main contribution of this work is methods for automatic analysis of aerial thermal images to localize leaking district heating pipes. Results and experiences from large-scale leakage detection in several cities in Sweden and Norway are presented.

Place, publisher, year, edition, pages
IEEE , 2014. Vol. 52, no 8, 5175-5182 p.
Keyword [en]
image processing, remote sensing, thermal sensors
National Category
Signal Processing Remote Sensing
Identifiers
URN: urn:nbn:se:liu:diva-105285DOI: 10.1109/TGRS.2013.2287238ISI: 000332598500055OAI: oai:DiVA.org:liu-105285DiVA: diva2:705324
Available from: 2014-03-15 Created: 2014-03-15 Last updated: 2017-12-05Bibliographically approved

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