Thermographic methodologies used in infrastructure inspection: A review—Post-processing procedures

Garrido, Iván; Lagüela, S.; Otero, Roi; Arias, Pedro

doi:10.1016/j.apenergy.2020.114857

Cited by 56 publications

(26 citation statements)

References 74 publications

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“…The façade should not be exposed to wetting, frosting, or direct solar radiation in the acquisition phase. In addition, this technique is significantly dependent on the expertise of the operator [71]. However, this technique could be an upgrade for damage detection in visual inspection with a capability of mapping moisture stains, detachment, loss of adhesion, and cracks, particularly when there is no access to the facade.…”

Section: Infrared Thermography (Irt)mentioning

confidence: 99%

Critical Analysis about Emerging Technologies for Building’s Façade Inspection

2021

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The diagnosis of the building’s façades pathology is extremely important to support rational and technically informed decisions regarding maintenance and rehabilitation actions. With a reliable diagnosis, the probable causes of the anomalies can be correctly identified, and the correction measures adopted can be more compatible with the existing elements, promoting the durability of the façades. Visual inspection is the most common approach to identify anomalies in a building’s façade and, in many cases, this technique is sufficient to support the decision to intervene. However, the pathological phenomenon is complex, and the anomalies observed may indicate the presence of other defects, or some anomalies may not be visible in a simple visual observation. This study intends to discuss the application of emerging technologies on the diagnosis and anamneses of building’s façade, in order to automatise the collection of reliable on-site data and, thus, reduce the uncertainty of the diagnosis. The use of these techniques can help existing inspection methodologies, already tested, based mainly on the visual assessment of the buildings’ elements degradation condition.

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Section: Infrared Thermography (Irt)mentioning

confidence: 99%

Critical Analysis about Emerging Technologies for Building’s Façade Inspection

2021

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“…Compared to alternative intrusive investigations, GPR and IRT require less time and costs, and they produce less disruption to the users of the buildings [ 18 , 34 ]…”

Section: Figurementioning

confidence: 99%

“…Under ambient conditions, and without any thermal excitation applied by artificial sources to the object under study, TIR is the appropriate band for the measurement of temperatures through the thermal radiation. Regarding the distribution, the sensors are usually placed in a matrix shape and this matrix is typically installed inside a camera, known as InfraRed (IR) camera [ 18 ]. Then, the spatial distribution of the temperature values of the object under study is obtained by the Stefan–Boltzmann law using the measured radiation as input [ 17 ], resulting in a thermal image, or several thermal images in case of monitoring.…”

Section: Introductionmentioning

confidence: 99%

“…Then, the spatial distribution of the temperature values of the object under study is obtained by the Stefan–Boltzmann law using the measured radiation as input [ 17 ], resulting in a thermal image, or several thermal images in case of monitoring. It should be noted that the following correction factors must be applied if accurate temperature values are required [ 18 ]: (i) emissivity, (ii) reflected temperature, and (iii) atmospheric attenuation.…”

Section: Introductionmentioning

confidence: 99%

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IRT and GPR Techniques for Moisture Detection and Characterisation in Buildings

Garrido

Solla

Lagüela

et al. 2020

Sensors

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The integrity, comfort, and energy demand of a building can be negatively affected by the presence of moisture in its walls. Therefore, it is essential to identify and characterise this building pathology with the most appropriate technologies to perform the required prevention and maintenance tasks. This paper proposes the joint application of InfraRed Thermography (IRT) and Ground-Penetrating Radar (GPR) for the detection and classification of moisture in interior walls of a building according to its severity level. The IRT method is based on the study of the temperature distribution of the thermal images acquired without an application of artificial thermal excitation for the detection of superficial moisture (less than 15 mm deep in plaster with passive IRT). Additionally, in order to characterise the level of moisture severity, the Evaporative Thermal Index (ETI) was obtained for each of the moisture areas. As for GPR, with measuring capacity from 10 mm up to 30 cm depth with a 2300 MHz antenna, several algorithms were developed based on the amplitude and spectrum of the received signals for the detection and classification of moisture through the inner layers of the wall. In this work, the complementarity of both methods has proven to be an effective approach to investigate both superficial and internal moisture and their severity. Specifically, IRT allowed estimating superficial water movement, whereas GPR allowed detecting points of internal water accumulation. Thus, through the combination of both techniques, it was possible to provide an interpretation of the water displacement from the exterior surface to the interior surface of the wall, and to give a relative depth of water inside the wall. Therefore, it was concluded that more information and greater reliability can be gained by using complementary IRT-GPR, showing the benefits of combining both techniques in the building sector.

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“…In cultural heritage, the emitted radiation is measured by an array of sensors installed inside a camera (called IR camera). These sensors are sensitive to either: (i) The Long-Wave InfraRed sub-band (LWIR, with a wavelength range from 7 µm to 14 µm), or (ii) the Medium-Wave InfraRed sub-band (MWIR, with a wavelength range from 3 µm to 5 µm) [ 10 , 11 ]. Then, the radiation measured by each sensor is converted into temperature as output data of the IR camera: Radiation is related to temperature through the Stefan-Boltzmann law [ 12 ].…”

Section: Introductionmentioning

confidence: 99%

Introduction of Deep Learning in Thermographic Monitoring of Cultural Heritage and Improvement by Automatic Thermogram Pre-Processing Algorithms

Garrido

Erazo-Aux

Lagüela

et al. 2021

Sensors

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The monitoring of heritage objects is necessary due to their continuous deterioration over time. Therefore, the joint use of the most up-to-date inspection techniques with the most innovative data processing algorithms plays an important role to apply the required prevention and conservation tasks in each case study. InfraRed Thermography (IRT) is one of the most used Non-Destructive Testing (NDT) techniques in the cultural heritage field due to its advantages in the analysis of delicate objects (i.e., undisturbed, non-contact and fast inspection of large surfaces) and its continuous evolution in both the acquisition and the processing of the data acquired. Despite the good qualitative and quantitative results obtained so far, the lack of automation in the IRT data interpretation predominates, with few automatic analyses that are limited to specific conditions and the technology of the thermographic camera. Deep Learning (DL) is a data processor with a versatile solution for highly automated analysis. Then, this paper introduces the latest state-of-the-art DL model for instance segmentation, Mask Region-Convolution Neural Network (Mask R-CNN), for the automatic detection and segmentation of the position and area of different surface and subsurface defects, respectively, in two different artistic objects belonging to the same family: Marquetry. For that, active IRT experiments are applied to each marquetry. The thermal image sequences acquired are used as input dataset in the Mask R-CNN learning process. Previously, two automatic thermal image pre-processing algorithms based on thermal fundamentals are applied to the acquired data in order to improve the contrast between defective and sound areas. Good detection and segmentation results are obtained regarding state-of-the-art IRT data processing algorithms, which experience difficulty in identifying the deepest defects in the tests. In addition, the performance of the Mask R-CNN is improved by the prior application of the proposed pre-processing algorithms.

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Thermographic methodologies used in infrastructure inspection: A review—Post-processing procedures

Cited by 56 publications

References 74 publications

Critical Analysis about Emerging Technologies for Building’s Façade Inspection

Critical Analysis about Emerging Technologies for Building’s Façade Inspection

IRT and GPR Techniques for Moisture Detection and Characterisation in Buildings

Introduction of Deep Learning in Thermographic Monitoring of Cultural Heritage and Improvement by Automatic Thermogram Pre-Processing Algorithms

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