Thermal-based analysis for the automatic detection and characterization of thermal bridges in buildings

Garrido, Iván; Lagüela, S.; Arias, Pedro; Balado, Jesús

doi:10.1016/j.enbuild.2017.11.031

Cited by 62 publications

(44 citation statements)

References 28 publications

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“…However, there is still work to be done, and one of the fields that should be studied, with regard to future IRT research, is the automation of the interpretation for infrastructure inspections, as in [37,39,40], in order to minimize the risk of missing or misinterpreting thermal pathologies present in the infrastructure under study.…”

Section: Discussionmentioning

confidence: 99%

“…The main reason of this increase is that the building sector is responsible for consuming up to 40% of the total energy in developed countries [39], being a very important sector to be analysed in order to obtain more and more energy efficiency and savings. For this reason, there are IRT studies that range from the thermal characterization of building materials to the detection and thermal characterization of building pathologies.…”

Section: Buildingsmentioning

confidence: 99%

“…There are several IRT studies related to the analysis of thermal bridges, due to their severity in buildings. Garrido et al [39] propose a method for the automatic detection of thermal bridges in different building façades and the automatic computation of their linear thermal transmittance with an image processing approach and in passive mode. Another important pathology is moisture, for which Edis et al [46] test a quasi-quantitative approach in order to identify rising damp in an adhered ceramic façade, comparing three different thermal data processing techniques, including PCA, and in passive mode.…”

mentioning

confidence: 99%

“…To avoid misinterpretation, the automation of thermal images interpretation is performed in recent IRT researches as a solution [37,39,40].…”

mentioning

confidence: 99%

See 3 more Smart Citations

Infrared Thermography’s Application to Infrastructure Inspections

2018

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Health monitoring and prediction in different types of structures is essential in order to maintain optimal conditions. Some of the pathologies that affect their structural stability are characterized by distinct thermal properties compared to unaltered areas. Infrared thermography (IRT) is a technique based on the acquisition of the thermal radiation of the bodies using thermal sensors of infrared (IR) cameras, which produce an image of the thermal infrared radiation captured through the conversion of the radiation values to temperature values. Therefore, this technique can be used in different studies to analyse structures with one or more pathologies based on their anomalous thermal behaviour with regard to the unaltered surroundings. As a consequence, this review presents various IRT applications to infrastructure inspections, showing the utility of the technique.

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Section: Discussionmentioning

confidence: 99%

Section: Buildingsmentioning

confidence: 99%

mentioning

confidence: 99%

“…To avoid misinterpretation, the automation of thermal images interpretation is performed in recent IRT researches as a solution [37,39,40].…”

mentioning

confidence: 99%

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Infrared Thermography’s Application to Infrastructure Inspections

2018

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“…Thermal infrared (TIR) images enable us to visualize different thermal faults such as air infiltrations or moisture areas and to detect damages to the building structure; for example, cracks, delamination, or loose tiling. Depending on the final aim of energy auditing, thermal data can be collected in an indoor environment [1,2] or by outdoor measurements including airborne platforms [3] and close-range techniques [4]. A broad review of various infrared thermography applications for building diagnostics is presented in Kylili et al [5].…”

Section: Introductionmentioning

confidence: 99%

Supervised Detection of Façade Openings in 3D Point Clouds with Thermal Attributes

2020

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Targeted energy management and control is becoming an increasing concern in the building sector. Automatic analyses of thermal data, which minimize the subjectivity of the assessment and allow for large-scale inspections, are therefore of high interest. In this study, we propose an approach for a supervised extraction of façade openings (windows and doors) from photogrammetric 3D point clouds attributed to RGB and thermal infrared (TIR) information. The novelty of the proposed approach is in the combination of thermal information with other available characteristics of data for a classification performed directly in 3D space. Images acquired in visible and thermal infrared spectra serve as input data for the camera pose estimation and the reconstruction of 3D scene geometry. To investigate the relevance of different information types to the classification performance, a Random Forest algorithm is applied to various sets of computed features. The best feature combination is then used as an input for a Conditional Random Field that enables us to incorporate contextual information and consider the interaction between the points. The evaluation executed on a per-point level shows that the fusion of all available information types together with context consideration allows us to extract objects with 90% completeness and 95% correctness. A respective assessment executed on a per-object level shows 97% completeness and 88% accuracy.

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