IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v134y2014icp499-505.html
   My bibliography  Save this article

Quantitative infrared thermography imaging of the density of heat flow rate through a building element surface

Author

Listed:
  • Ohlsson, K.E.A.
  • Olofsson, T.

Abstract

Infrared thermography is often used to record an image of the building envelope surface temperature, and thereby acquire qualitative information on its thermal insulation performance. Recently, a thermography method has evolved, which enables quantitative measurement of the 2-dimensional pattern of the density of heat flow rate (q) across the building element surface. However, based on previous estimates of its measurement uncertainty, the capacity of the thermography method to yield accurate results has been questioned. We present here an improved procedure for measurement of q, with an evaluation of measurement errors. The main improvement consists of the simultaneous measurement of surface temperature, surrounding radiative temperature, and air temperature, based on information included in one single thermal camera image. This arrangement allows for accurate measurements of small temperatures differences, and thereby reduced uncertainty in the measurement of q. The measurement bias was evaluated experimentally by a comparison of thermography results against a reference method. Under natural convective conditions, there was a 2.6Wm−2 constant difference between the two methods. The measurement uncertainty u(q) was estimated as a function of q. Based on this, the lower limit of the measurement working range was determined to be 6Wm−2, which corresponds to less than 10% relative uncertainty. In the case of forced convection, the thermography method yielded less reliable results. The reason for this was the sensitivity of the results to the choice of model for the convective heat transfer coefficient, and the difficulty to select the position for measurement of the wind speed, which is appropriate for this model.

Suggested Citation

  • Ohlsson, K.E.A. & Olofsson, T., 2014. "Quantitative infrared thermography imaging of the density of heat flow rate through a building element surface," Applied Energy, Elsevier, vol. 134(C), pages 499-505.
  • Handle: RePEc:eee:appene:v:134:y:2014:i:c:p:499-505
    DOI: 10.1016/j.apenergy.2014.08.058
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261914008691
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.apenergy.2014.08.058?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Fokaides, Paris A. & Kalogirou, Soteris A., 2011. "Application of infrared thermography for the determination of the overall heat transfer coefficient (U-Value) in building envelopes," Applied Energy, Elsevier, vol. 88(12), pages 4358-4365.
    2. Asdrubali, Francesco & Baldinelli, Giorgio & Bianchi, Francesco, 2012. "A quantitative methodology to evaluate thermal bridges in buildings," Applied Energy, Elsevier, vol. 97(C), pages 365-373.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Luca Evangelisti & Leone Barbaro & Claudia Guattari & Edoardo De Cristo & Roberto De Lieto Vollaro & Francesco Asdrubali, 2024. "Comparison between Direct and Indirect Heat Flux Measurement Techniques: Preliminary Laboratory Tests," Energies, MDPI, vol. 17(12), pages 1-16, June.
    2. Bienvenido-Huertas, David & Moyano, Juan & Rodríguez-Jiménez, Carlos E. & Marín, David, 2019. "Applying an artificial neural network to assess thermal transmittance in walls by means of the thermometric method," Applied Energy, Elsevier, vol. 233, pages 1-14.
    3. Lucchi, Elena, 2018. "Applications of the infrared thermography in the energy audit of buildings: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 82(P3), pages 3077-3090.
    4. Lee, Junghun & Kim, Jeonggook & Song, Doosam & Kim, Jonghun & Jang, Cheolyong, 2017. "Impact of external insulation and internal thermal density upon energy consumption of buildings in a temperate climate with four distinct seasons," Renewable and Sustainable Energy Reviews, Elsevier, vol. 75(C), pages 1081-1088.
    5. Baldinelli, Giorgio & Bianchi, Francesco & Rotili, Antonella & Costarelli, Danilo & Seracini, Marco & Vinti, Gianluca & Asdrubali, Francesco & Evangelisti, Luca, 2018. "A model for the improvement of thermal bridges quantitative assessment by infrared thermography," Applied Energy, Elsevier, vol. 211(C), pages 854-864.
    6. Bienvenido-Huertas, David & Moyano, Juan & Marín, David & Fresco-Contreras, Rafael, 2019. "Review of in situ methods for assessing the thermal transmittance of walls," Renewable and Sustainable Energy Reviews, Elsevier, vol. 102(C), pages 356-371.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Kylili, Angeliki & Fokaides, Paris A. & Christou, Petros & Kalogirou, Soteris A., 2014. "Infrared thermography (IRT) applications for building diagnostics: A review," Applied Energy, Elsevier, vol. 134(C), pages 531-549.
    2. Blanca Tejedor & Eva Barreira & Vasco Peixoto de Freitas & Tomasz Kisilewicz & Katarzyna Nowak-Dzieszko & Umberto Berardi, 2020. "Impact of Stationary and Dynamic Conditions on the U-Value Measurements of Heavy-Multi Leaf Walls by Quantitative IRT," Energies, MDPI, vol. 13(24), pages 1-19, December.
    3. Yu Hou & Rebekka Volk & Lucio Soibelman, 2021. "A Novel Building Temperature Simulation Approach Driven by Expanding Semantic Segmentation Training Datasets with Synthetic Aerial Thermal Images," Energies, MDPI, vol. 14(2), pages 1-16, January.
    4. Carlos Morón & Pablo Saiz & Daniel Ferrández & Rubén Felices, 2018. "Comparative Analysis of Infrared Thermography and CFD Modelling for Assessing the Thermal Performance of Buildings," Energies, MDPI, vol. 11(3), pages 1-19, March.
    5. Baldinelli, Giorgio & Bianchi, Francesco & Rotili, Antonella & Costarelli, Danilo & Seracini, Marco & Vinti, Gianluca & Asdrubali, Francesco & Evangelisti, Luca, 2018. "A model for the improvement of thermal bridges quantitative assessment by infrared thermography," Applied Energy, Elsevier, vol. 211(C), pages 854-864.
    6. Aïssani, A. & Chateauneuf, A. & Fontaine, J.-P. & Audebert, Ph., 2016. "Quantification of workmanship insulation defects and their impact on the thermal performance of building facades," Applied Energy, Elsevier, vol. 165(C), pages 272-284.
    7. Fokaides, Paris A. & Jurelionis, Andrius & Gagyte, Laura & Kalogirou, Soteris A., 2016. "Mock target IR thermography for indoor air temperature measurement," Applied Energy, Elsevier, vol. 164(C), pages 676-685.
    8. O'Grady, Małgorzata & Lechowska, Agnieszka A. & Harte, Annette M., 2017. "Quantification of heat losses through building envelope thermal bridges influenced by wind velocity using the outdoor infrared thermography technique," Applied Energy, Elsevier, vol. 208(C), pages 1038-1052.
    9. Shabunko, Veronika & Badrinarayanan, Samyuktha & Pillai, Dhanup S., 2021. "Evaluation of in-situ thermal transmittance of innovative building integrated photovoltaic modules: Application to thermal performance assessment for green mark certification in the tropics," Energy, Elsevier, vol. 235(C).
    10. Martin, Miguel & Chong, Adrian & Biljecki, Filip & Miller, Clayton, 2022. "Infrared thermography in the built environment: A multi-scale review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 165(C).
    11. Albatici, Rossano & Tonelli, Arnaldo M. & Chiogna, Michela, 2015. "A comprehensive experimental approach for the validation of quantitative infrared thermography in the evaluation of building thermal transmittance," Applied Energy, Elsevier, vol. 141(C), pages 218-228.
    12. Flores Larsen, Silvana & Hongn, Marcos, 2014. "Determining the infrared reflectance of specular surfaces by using thermographic analysis," Renewable Energy, Elsevier, vol. 64(C), pages 306-313.
    13. Sanhudo, Luís & Ramos, Nuno M.M. & Poças Martins, João & Almeida, Ricardo M.S.F. & Barreira, Eva & Simões, M. Lurdes & Cardoso, Vítor, 2018. "Building information modeling for energy retrofitting – A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 89(C), pages 249-260.
    14. Bienvenido-Huertas, David & Moyano, Juan & Marín, David & Fresco-Contreras, Rafael, 2019. "Review of in situ methods for assessing the thermal transmittance of walls," Renewable and Sustainable Energy Reviews, Elsevier, vol. 102(C), pages 356-371.
    15. Lucchi, Elena, 2018. "Applications of the infrared thermography in the energy audit of buildings: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 82(P3), pages 3077-3090.
    16. Lehmann, B. & Ghazi Wakili, K. & Frank, Th. & Vera Collado, B. & Tanner, Ch., 2013. "Effects of individual climatic parameters on the infrared thermography of buildings," Applied Energy, Elsevier, vol. 110(C), pages 29-43.
    17. Luca Evangelisti & Leone Barbaro & Claudia Guattari & Edoardo De Cristo & Roberto De Lieto Vollaro & Francesco Asdrubali, 2024. "Comparison between Direct and Indirect Heat Flux Measurement Techniques: Preliminary Laboratory Tests," Energies, MDPI, vol. 17(12), pages 1-16, June.
    18. Bienvenido-Huertas, David & Moyano, Juan & Rodríguez-Jiménez, Carlos E. & Marín, David, 2019. "Applying an artificial neural network to assess thermal transmittance in walls by means of the thermometric method," Applied Energy, Elsevier, vol. 233, pages 1-14.
    19. David Bienvenido-Huertas & Juan Antonio Fernández Quiñones & Juan Moyano & Carlos E. Rodríguez-Jiménez, 2018. "Patents Analysis of Thermal Bridges in Slab Fronts and Their Effect on Energy Demand," Energies, MDPI, vol. 11(9), pages 1-18, August.
    20. Asdrubali, Francesco & Baldinelli, Giorgio & Bianchi, Francesco & Costarelli, Danilo & Rotili, Antonella & Seracini, Marco & Vinti, Gianluca, 2018. "Detection of thermal bridges from thermographic images by means of image processing approximation algorithms," Applied Mathematics and Computation, Elsevier, vol. 317(C), pages 160-171.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:appene:v:134:y:2014:i:c:p:499-505. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/405891/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.