Classification and temporal analysis of district heating leakages in thermal images
2014 (English)In: Proceedings of The 14th International Symposium on District Heating and Cooling, 2014Conference paper (Other academic)
District heating pipes are known to degenerate with time and in some cities the pipes have been used for several decades. Due to bad insulation or cracks, energy or media leakages might appear. This paper presents a complete system for large-scale monitoring of district heating networks, including methods for detection, classification and temporal characterization of (potential) leakages. The system analyses thermal infrared images acquired by an aircraft-mounted camera, detecting the areas for which the pixel intensity is higher than normal. Unfortunately, the system also finds many false detections, i.e., warm areas that are not caused by media or energy leakages. Thus, in order to reduce the number of false detections we describe a machine learning method to classify the detections. The results, based on data from three district heating networks show that we can remove more than half of the false detections. Moreover, we also propose a method to characterize leakages over time, that is, repeating the image acquisition one or a few years later and indicate areas that suffer from an increased energy loss.
Place, publisher, year, edition, pages
IdentifiersURN: urn:nbn:se:liu:diva-112980OAI: oai:DiVA.org:liu-112980DiVA: diva2:776415
The 14th International Symposium on District Heating and Cooling, Stockholm, Sweden, 7-9 September 20141
FunderSwedish Research Council, D0570301