Passive Infrared Thermography Research Articles

Passive infrared thermography for subsurface delamination detection in concrete infrastructure: Capabilities

Passive infrared thermography (IRT) has been introduced as a faster, safer, and contactless alternative for the nondestructive inspection of subsurface delamination in concrete infrastructure. However, some uncertainties remain, such as the absence of an inspection protocol to inspect multiple concrete components and the dependence of the technique’s performance on environmental conditions and solar energy. This study presents a proof of concept about the capabilities of passive IRT in detecting subsurface damages in multiple concrete components under variate solar exposure. The passive IRT capabilities are explored by analyzing the thermal sequences obtained from samples of artificially damaged concrete structures inspected over 24 h in various environmental conditions over three seasons. As a result, damages with a size-to-depth (S/D) ratio between 1.0 and 2.7 were detected using the thermal contrast method. Furthermore, the implementation of signal processing techniques yielded an improvement in capabilities ranging from 15% to 52%. Finally, a procedure for acquiring data while inspecting multiple concrete components using passive IRT is proposed.

A novel application of deep learning approach over IRT images for the automated detection of rising damp on historical masonries

Nowadays, the fusion of Artificial Intelligence (AI) comprises a widespread approach for resolving various types of problems in many scientific domains including Protection of Monuments. Non-Destructive Testing (NDT) approaches and Infra-Red Thermography (IRT) specifically, plays a key role for the diagnosis and the assessment of the monuments’ preservation state. Additionally, IRT comprises a powerful tool for continuous monitoring especially when it concerns the physical and/or chemical processes that take place within or on the material and affect the irradiation of the historical surfaces. This study explores the application of Deep Learning (DL) to IRT images of passive approach, focusing on the automated detection of rising damp in historical masonries. The IRT data were acquired from two monuments, the Holy Aedicule of the Holy Sepulchre and the Historical Building "Msma’a". Exploiting the capabilities of AI for enhancing the non-intrusive nature of passive IRT, this research seeks to provide a cost-effective and non-destructive approach for the early identification of rising damp, contributing significantly to the long-term preservation, conservation, and protection of the cultural heritage. To achieve this, the study takes advantage of a combination of the PSPNet image segmentation model with the ResNet-50 backbone, the PSP_R50 model. The mmsegment framework, renowned for its versatility and effectiveness, serves as the ideal platform for training, evaluating, and fine-tuning the proposed segmentation model. Despite having a relatively small dataset, a highly effective segmentation model (0.93 accuracy, 0.89 IoU), has been successfully developed.

Applications of Passive Infrared Thermal Imaging for Detecting Delaminated Areas of Ancient Rock-cut Tunnel

Delaminations are generally developed in construction works due to numerous factors, including cyclic loading, water flow, and weather conditions. A conventional non-destructive method, such as tapping or chain dragging, is commonly used to predict subsurface delaminations. However, tapping tests may require more precision, especially for minor subsurface defects. Passive Infrared Thermal Imaging or Passive Infrared Thermography (PIRT) effectively detects sizable delaminated areas of a structure quickly. However, the inspected structural components are recommended to be exposed to direct sunlight. In this study, PIRT was used to investigate an operating ancient rock-cut tunnel and to detect potentially dangerous locations where delamination and spalling have occurred. The results prove that PIRT can effectively detect delaminated areas, even when there is only a 1-2°C atmospheric temperature difference nine hours before testing.

Detect submerged piping in river embankment by passive infrared thermography

Piping is one of the most harmful driving factors causing river embankment failures. Unmanned aerial vehicle (UAV) carried passive infrared thermography (IRT) is introduced herein for detecting submerged piping in river embankments. To verify the feasibility of this detection strategy and accumulate detection experience, an outdoor piping simulation platform was built. On the basis of exploring the time varying regulations of water temperature, night and afternoon are identified as the better time for piping detection. Passive IRT-based piping experiments of 9 submerging depths and 8 piping flow rates were carried out during nights and afternoons, and the heat distribution characteristics of the piping outlet in the thermal image under different submerging depths and flow rates were studied in detail. The effectiveness of passive IRT detecting piping in rainy weather was also explored. Finally, applicability and limitations of UAV carried passive IRT detecting piping were studied in an actual river embankment.

Spatio-temporal characterization of microbial heat production on undisturbed soil samples combining infrared thermography and zymography

Passive infrared thermography (IRT) has already been applied in several approaches for high-resolution and non-contact imaging of microbial hot spots and hot moments on soil sample surfaces. The technique has only been used on homogenized disturbed samples to characterize the in-situ heterogeneity of heat development. In this study, undisturbed top- and subsoils samples from two forest sites were used in a substrate-induced approach to capture surface heat production using passive IRT with homogeneously applied glucose and water. The soil sample surface temperature was measured at 10-minute intervals and a spatial resolution of 0.17 mm per pixel. The soil samples were incubated for five days during passive IRT measurements under controlled ambient conditions with a relative air humidity >95% and constant ambient air temperature of 20 °C. Soil sample surface characterization was done by using active IRT for soil moisture approximation and surface structure, digital photography to estimate soil organic carbon (SOC) contents from soil color parameters, and zymography to get an indicator of initial microbial activity. In a first step, surface temperature dynamics were characterized using mathematical and geostatistical methods concerning microbial hot spots and hot moments. The characterization of hot moments was performed using a Gaussian curve fit. The spatial information of the hot spots was described using geostatistical semivariance. In a second step, a stepwise forward regression using sample surface properties was performed to find explanatory variables for surface heat production. Finally, a hierarchical k-means clustering was applied to the sequential thermal images and transferred to the other spatial datasets for deeper insights into small-scale variations in heat production and to also consider the temporal perspective. With an ANOVA combined with Tukey’s HSD post hoc test, significant differences between the cluster groups were calculated. This study showed that the temperature difference between averaged glucose- and water-treated sample surface temperature increased up to 0.2 K with a maximum hot moment duration of nearly 46 h. The variance in the samples could not be mapped, since the maximum spatial variability of the sample surface temperature could not be represented in the sample sections. The regression analysis revealed significant influences by soil moisture content, approximated SOC content, as well as initial β-glucosidase activity in the subsoil, which could be confirmed by the k-means cluster analysis. There was an indication that soil brightness (SOC contents) was influencing heat production due to the varying soil-borne substrate availability. The initial β-glucosidase activity showed that the initial biotic state of the soil contributed to the temperature increase concerning the provision of energy for microbial activity. In conclusion, passive IRT is a helpful mapping tool for the spatio-temporal characterization of hot spots and hot moments. In this context, additional mapping techniques such as zymography help to gain insights into the process level of heat generation by microbial activity.

Long-Term Numerical Analysis of Subsurface Delamination Detection in Concrete Slabs via Infrared Thermography

One of the concerns about the use of passive Infrared Thermography (IRT) for structural health monitoring (SHM) is the determination of a favorable period to conduct the inspections. This paper investigates the use of numerical simulations to find appropriate periods for IRT-based detection of subsurface damages in concrete bridge slabs under passive heating along a 1 year of time span. A model was built using the Finite Element Method (FEM) and calibrated using the results of a set of thermographic field inspections on a concrete slab sample. The results showed that the numerical simulation properly reproduced the experimental thermographic measurements of the concrete structure under passive heating, allowing the analysis to be extended for a longer testing period. The long-term FEM results demonstrated that the months of spring and summer are the most suitable for passive IRT inspections in this study, with around 17% more detections compared to the autumn and winter periods in Brazil. By enhancing the possibility of using FEM beyond the design stage, we demonstrate that this computation tool can provide support to long-term SHM.

A novel method using infrared thermography for hot fluid leakage detection on surfaces with uneven emissivities

Uneven surface emissivity will cause illusory temperature variation in infrared surface temperature mapping. For this reason, most of the detailed reviews on the use of infrared thermography (IRT) for leakage detection have mainly focused on surfaces with homogeneous emissivity or the recognition of negative temperature gradients, while reports on sensing hot fluid leakage for uneven surface emissivity are very rare. In this study, a hypothesis is put forward and a new leakage detection method is proposed that uses a transient heating-cooling-heating process in association with a subtraction method of infrared images to eliminate the disturbance of inhomogeneous valve surface emissivities. A theoretical analysis is established that is experimentally tested as a case study. The results shows that the hypothesis is clear and the effect of the uneven emissivity is suppressed for the recognition of positive temperature gradients (hot fluid leakage) on a metal valve sample. The current work provides new insights on the modification of the surface emissivity under certain conditions, which has been a major limitation of passive IRT in the past.

IRT and GPR Techniques for Moisture Detection and Characterisation in Buildings.

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.

Detection of Delamination with Various Width-to-depth Ratios in Concrete Bridge Deck Using Passive IRT: Limits and Applicability.

In bridge structures, concrete decks have a higher risk of damage than other components owing to the direct impact of traffic. This study aims to develop a comprehensive system for bridge inspection using passive infrared thermography (IRT). Experiments were conducted on a concrete specimen (assumed as the surface of the bridge deck) embedded artificial delaminations with different width-to-depth ratios (WTDRs). Both professional handheld IR camera (H-IRC) and a UAV mounted with an IR camera (UAV-IRC) were employed simultaneously to capture the surface temperature of the structure. The present work indicates that the passive IRT technique with an H-IRC can be used to detect delaminations located at depths of 4 cm or less from the structure surface if the WTDRs are not lesser than 1.9 for daytime and 2.5 for nighttime when testing on a sunny day. In addition, the larger the WTDR, the higher the temperature difference can be produced, thus delaminations could be observed more clearly. Furthermore, our study suggests that the concrete bridge deck inspection using passive IRT can produce appropriate results if the inspection is performed from 10:00 to 15:00 or from 19:30 to approximately 2:00 on a sunny day. Good agreement between the results obtained from tests using H-IRC and UAV-IRC was observed, which validates the application of UAV-IRC in real structure inspection.

IR Thermography from UAVs to Monitor Thermal Anomalies in the Envelopes of Traditional Wine Cellars: Field Test

Infrared thermography (IRT) techniques for building inspection are currently becoming increasingly popular as non-destructive methods that provide valuable information about surface temperature (ST) and ST contrast (delta-T). With the advent of unmanned aerial vehicle (UAV)-mounted thermal cameras, IRT technology is now endowed with improved flexibility from an aerial perspective for the study of building envelopes. A case study cellar in Northwest (NW) Spain is used to assess the capability and reliability of low-altitude passive IRT in evaluating a typical semi-buried building. The study comparatively assesses the use of a pole-mounted FLIR B335 camera and a drone-mounted FLIR Vue Pro R camera for this purpose. Both tested IRT systems demonstrate good effectiveness in detecting thermal anomalies (e.g., thermal bridges, air leakages, constructive singularities, and moisture in the walls of the cellar) but pose some difficulties in performing accurate ST measurements under real operating conditions. Working with UAVs gives great flexibility for the inspection, but the angle of view strongly influences the radiometric data captured and must be taken into account to avoid disturbances due to specular reflections.

Imaging and condition diagnosis of underground sewer liners via active and passive infrared thermography: A case study in Singapore

This paper presents a case study of customizing an in-house built In-pipe Infrared Thermographic System (IPITS), which makes use of thermo-images for imaging and diagnosis of pipe crown condition in underground sewer pipelines. Active and passive infrared thermography (IRT) were attempted in two gravity sewer pipes in Singapore in July 2017. The results show that images captured with active IRT (with heating) can image and reveal invisible lining defects not readily revealed by traditional visual inspection using CCTV. These defects include bubbles, wrinkling and delamination, or construction details (like anchor knobs in HDPE material), for which sizes were estimated using an image processing algorithm customized in an in-house program. While images captured by passive IRT (without heating) can be used to identify suspected water seeping points, this paper also reports the design of instrumentation and appropriate parameter settings. The results of this case study are believed to pave the way for parallel inspections using a combination of CCTV and infrared cameras.

The potential of active and passive infrared thermography for identifying dynamics of soil moisture and microbial activity at high spatial and temporal resolution

Spatio-temporal analyses of soil properties are important for more profound insights into soil processes. Up to now, non-invasive approaches analyzing physical and biological soil properties and dynamics at the microscale are not available due to methodological, instrumental, and analytical challenges. In this study, we evaluate the use of active and passive infrared thermography (IRT), a non-invasive and non-contact technique, for the detection of surface temperature-based parameters on soil surfaces. The potential and possibilities of IRT were analyzed with a focus on the detection and calibration of soil moisture using active IRT and the determination of microbial activity using passive IRT. A pool of 51 soil samples was used to cover a wide range of chemical, physical, and biological soil properties. The samples were rewetted to 16 different moisture contents, filled into vessels, and placed in an air-proof glove box with an adjusted relative humidity of about 92% to reduce soil drying. Immediately after rewetting, the soil surface temperature was determined using active and passive IRT procedures at a high temporal resolution (1 min for passive IRT, hourly for active IRT) and a spatial resolution of 0.283 mm. Soil material was also sterilized by γ-irradiation in order to obtain sterile samples for validating the passive IRT procedure. Active IRT measurements were qualified for the detection of soil surface moisture due to changing specific heat capacity at varying water contents. The mean volumetric water contents explained up to 88% of active IRT values, which were a good approximation for relative differences in the spatial and temporal distribution of moisture contents. Passive IRT measurements are useful for the detection of microbial activity on soil sample surfaces since temperature increases by up to 0.5 K were detected on the surfaces of all non-sterile samples immediately after rewetting. In sterile samples, rewetting did not result in heat production. With regard to the commonly observed “Birch”-CO2-pulse, these results strongly suggested that the heat evolution on the surface of the non-sterile soils was associated with the rapidly increasing microbial activity from consuming dead and easily available soil biomass. In conclusion, IRT is a promising mapping tool of soil surface processes especially for undisturbed soil samples, since IRT techniques allow studying moisture and microbial activity of intact soil structures.