IR Thermal Imaging Research Articles

2D‐Pyroelectric Materials for Waste Thermal Energy Harvesting and Beyond

AbstractPolar 2D materials hold the emerging functionalities such as ferro‐, piezo‐, and pyro‐electric properties. On account of infrared‐active low bandgap and polar nature at reduced dimensionality, they served as an ideal choice of pyroelectric material. It can cover up a diverse range of applications, such as waste thermal energy harvesting, IR imaging, photodetector, temperature sensors, and several catalytic processes due to the abundance of dynamic thermal fluxes. Recently, 2D pyroelectric materials have manifested a substantial role in thermal energy harvesting. Consequently, it is realized that there are plenty of scopes available to diversify its applicability. Thus, the challenges are spotlighted in this perspective to envision the desired 2D pyroelectric materials to achieve the effective thermal energy harvesting, sensing, and catalytic efficacy. Particularly, the emphasis is given to elucidate the role of spontaneous polarization in 2D materials to ascertain the giant pyroelectricity.

Experimental and numerical studies of detailed heat transfer and flow characteristics in the rib turbulated annulus of a double pipe heat exchanger

An enhancement in the overall heat transfer between the fluids in a Double pipe heat exchanger (DPHE) can be achieved through various active or passive techniques. The present study focuses on the passive heat transfer enhancement in the annular region of a DPHE by incorporating circular ribs on the outer surface of the inner pipe. The primary objective is to investigate the influence of the ribs on the local distribution of heat transfer and fluid flow in the annulus of the heat exchanger. The local Nusselt number (Nu) distribution was determined experimentally using a test section specially designed with a provision to measure the wall temperature distribution of the inner pipe with an IR thermal imaging camera. The pressure drop across the channels with the ribs was also measured in the experimental studies. Numerical studies are employed to gain insights into the flow characteristics in the annular region in the presence of ribs. Studies comprise various rib diameters (e/Dh = 0.08, 0.14), rib-to-rib pitches (P/e = 6, 12, 18), and Reynolds number values (Re = 5000, 7500, and 10000). The heat transfer behaviour from the experimental study is discussed based on the flow mechanism observed using numerical techniques. The flow separation and reattachment due to the rib and the induced recirculation zone cause large variations in the Nusselt number distribution between the ribs. The peak Nusselt number value between adjacent ribs is observed at the location of reattachment of the flow to the ribbed wall. Acquired data also shows that the flow and heat transfer characteristics differ significantly with changes in the P/e ratio. The rib configuration with e/Dh = 0.14 and P/e = 12 is identified as optimal, achieving a balanced improvement in heat transfer while showing a relatively lower pressure drop.

A novel method for detecting polypropylene fibers in cotton yarns based on thermal properties and IR image processing

Contamination of cotton yarns with foreign materials, such as polypropylene (PP) fibres, presents challenges in textile manufacturing. Conventional methods for detecting foreign fibres are often ineffective, particularly when the fibres are colourless or lack distinct visual characteristics. In this study, we propose a novel approach to detect PP fibres in cotton yarns by leveraging their differential thermal properties and employing infrared (IR) image processing. The method involves analysing temperature differentials between cotton and PP fibres when subjected to a heating source, followed by IR image processing to identify and quantify PP fibres. Experimental results demonstrate the feasibility and effectiveness of the proposed method in detecting PP fibres in cotton yarns.

Prediction of internal welding penetration based on IR thermal image supported by machine vision and ANN-model during automatic robot welding process

Welding quality is a critical criterion for evaluating welding operations. Traditional evaluation methods suffer from drawbacks such as lack of objectivity, untimeliness, and high costs. Therefore, real-time monitoring and assessment of the weld pool have become the mainstream trend in welding technology. This study introduces a novel method for defining weld pool width boundaries. It utilizes an infrared (IR) camera to capture the weld pool temperature clusters and employs the Sobel operator for convolution to generate the gradient map of the weld pool temperature clusters. Through enhanced processing in the gradient map, the width boundaries of the weld pool are more effectively detected compared to previous methods. Previous studies defined weld pool width boundaries by identifying characteristic points with the most distinct temperature fluctuations, caused by the different radiative properties of the same material in different states. However, practical tests revealed susceptibility to interference from reflected arc light. The proposed method mitigates the impact of reflected arc light and is applicable to complex multilayer welding scenarios. To address the lag in quality monitoring, reduce welding costs, and achieve real-time monitoring of the weld pool process, we employed machine vision and an artificial neural network (ANN) model. This led to the development of a weld penetration assessment system based on infrared thermal images. The system successfully predicted the penetration depth for 4 mm carbon steel with an accuracy of 86.6 %. This validates the feasibility of estimating and predicting weld performance using the surface temperature characteristics of the weld pool. The newly proposed weld pool boundary definition method holds promise for real-time monitoring in more complex multilayer pipe welding scenarios. It lays the groundwork for predicting and fusing the weld depth in intricate multi-pass pipe welding.

Non-Contact Size Estimation of Pressure Ulcers Using IR Thermal Imaging

Non-Contact Size Estimation of Pressure Ulcers Using IR Thermal Imaging

Influence of inclined unconfined circular air jet impingement on local heat transfer characteristics of smooth flat plate

The influence of inclined unconfined circular air jet impingement on local heat transfer characteristics of smooth flat plate is studied experimentally. The experimental investigation was conducted with jet inclination angles of 45°, 60° and 75°, jet Reynolds number of 12000–28000 and nozzle to target surface distance of 1–6. The Nu characteristics is studied in different radial direction angles on flat plate ranging from θ = 0° to 180° in stagnation and wall jet area for different z/d, Re and jet inclination configurations. The Nu characteristics are obtained by using an IR thermal imaging and thin foil approach. The Nu characteristics of different jet inclination angles (φ = 75°, 60° and 45°) was compared with vertical jet (φ = 90°) for different z/d and Re. Asymmetric in Nu characteristics increases with decrease in jet inclination about the geometric impingement point. With jet inclination, the maximum Nu value shifts away from geometric impinging point towards the uphill area of target plate. The displacement of maximum Nu from geometric impinging point towards the uphill area is highly pronounced at lower z/d and higher Re for a given jet inclination configuration. The isothermal Nu ring is reported at r/d ∼2 from geometric point in wall jet area. Within isothermal ring, Nu increases with radial direction angles from 0° to 180° and reverse behavior is observed outside the isothermal Nu ring. Correlations of Nu are obtained at geometric point and maximum Nu point with maximum deviation of ±10 %. Moreover, correlation for average Nu is also presented with and accuracy of ±3.4 %.

A Breathable, Reliable, and Flexible Siloxene Incorporated Porous SEBS‐Based Triboelectric Nanogenerator for Human–Machine Interactions

AbstractThe breathability of wearable sensors is of utmost necessity as it facilitates heat dissipation and sweat evaporation from the skin–sensor interface for improving the user's comfort and minimizing the inflammation risk. In this work, a Siloxene/porous styrene–ethylene–butylene–styrene (SEBS)‐based breathable triboelectric sensor is newly designed and fabricated for increasing user comfort and reliability. The reliability of the fabricated sensor is evaluated by measuring the heat dissipation through the skin–sensor interface using a thermal IR imaging test. Similarly, the sensor's breathability is quantified through a water vapor transmission rate (WVTR) test, where the achieved breathability of 5.88 mg cm−2 h−1 is sufficient for sweat evaporation, as an average person loses 1.2–4.2 mg cm−2 h−1 of sweat. Furthermore, a porous, metal‐free, hybridized nanoporous carbon (H‐NPC)/laser‐induced graphene (LIG) is utilized as a charge‐collecting electrode, which is transferred and conformally attached to the Siloxene/SEBS substrate. This results in a reduction in the interfacial resistance and an improvement in bonding between the dielectric and electrode layers. With a pressure sensitivity of 0.75 VkPa−1, the fabricated sensor demonstrates successful application in gesture recognition. Thus, this research showcases the considerable potential for developing triboelectric naongenerators (TENGs) with breathable and reliable features and underscores their broad applicability in human–machine interfaces and soft robotics systems.

Rapid and nondestructive testing for simultaneous measurement of thermal conductivity and thermal diffusivity of flat materials based on thermography

This study presents a novel experimental method that simultaneously supplies the thermal conductivity and thermal diffusivity of flat materials, which solves the limitations of traditional methods that have strict demands for thermal excitation, boundary, and size of samples. In this method, IR thermal imaging is used to collect data from the material surface temperature field caused by a laser excitation, and the differential terms in the basic heat-conduction differential equation are estimated by curve fitting. The differential equation is so transformed in an algebraic equation, which allows to simultaneously determine the thermal conductivity and thermal diffusivity. The measurement experiment does not require a strict control of the boundary or initial conditions, or thermal excitation modalities. The hypothesis this method is based on is that the spatial derivative of temperature in the Z-direction is linear with the temperature difference between the material surface and environment. Using this constraint the optimal operation conditions can be identified. The influence of operation conditions, including the heat transfer distance, excitation duration, material thickness, and number of sampling points on the measured surface, together with the results, were analysed by numerical simulation. The optimal operation conditions when testing two 304 stainless steel samples were found from this simulation analysis. Results of 304 stainless steel samples 1 and 2 mm thick show a deviation between the reference and measured values of the two thermal properties within 4.2 %, and repeatability within 5.5 %. Therefore, this method can realise rapid, nondestructive, and simultaneous measurements of thermal conductivity and thermal diffusivity.

An empirical firebrand pile heat flux model

Firebrand exposure has been identified as a leading cause of structure losses during wildfires. However, only a limited number of studies have attempted to quantify the incident firebrand heat flux to a target substrate surface. In this study, a bench-scale wind tunnel retrofitted with an IR thermal imaging system was used to generate high-resolution temperature data for the back surface of a thin, non-combustible insulation board exposed to a glowing firebrand pile at 0.9–2.7 m s−1 air flow velocities and 0.06 and 0.16 g cm−2 firebrand coverage densities. An inverse heat flux modelling technique utilizing a solid-phase pyrolysis solver, ThermaKin, was employed to determine transient firebrand pile heat flux profiles underneath and directly in front of a glowing firebrand pile. The inverse modelling technique used both the experimental back surface temperature data and the insulation's thermophysical properties. Average incident firebrand pile heat flux values obtained for all testing conditions ranged between 28 and 80 kW m−2. For the first time, an empirical model capturing the firebrand pile incident heat flux dependence on time, air flow velocity and firebrand coverage density was developed.

Graphite-epoxy composite systems for Joule heating based de-icing

Ice accretion and build-up in low temperature environments are issues plaguing many different branches of the industry. Recently much work has been done into the development of active de-icing systems based on carbon materials and their composites. The following research presents an investigation into graphite/epoxy composite materials made by a simple casting method with cheap materials and scalability potential, intended for de-icing applications based on Joule heating. The examination has been carried out for samples with different amounts of carbon filler using IR thermal imaging to measure sample heating under the influence of electrical current under constant voltage. Measured electrical currents were then analyzed to examine changes in samples' electrical resistance dependent on temperature. Results provide a positive outlook for further experiments and development for this type of material toward its potential application.

Multi-objective optimization of multiple droplet impacts on a molten PCM using NSGA-II optimizer and artificial neural network

Embracing an interaction between the phase change material (PCM) and the droplets of a heat transfer fluid, the direct contact (DC) method suggests a cutting-edge solution for expediting the phase change rates of PCMs in thermal energy storage (TES) units. In the direct contact TES configuration, when impacting the molten PCM pool, droplets evaporate, provoking the formation of a solidified PCM area (A). Then, they reduce the created solid temperature, leading to a minimum temperature value (Tmin). As a novelty, this research intends to maximize A and minimize Tmin since augmenting A expedites the discharge rate, and by lowering Tmin, the generated solid is preserved longer, resulting in a higher storage efficacy. To take the influences of interaction between droplets into account, the simultaneous impingement of two ethanol droplets on a molten paraffin wax is surveyed. Impact parameters (Weber number, impact spacing, and the pool temperature) govern the objective functions (A and Tmin). Initially, through high-speed and IR thermal imaging, the experimental values of objective functions are achieved for a wide range of impact parameters. Afterward, exploiting an artificial neural network (ANN), two models are fitted to A and Tmin, respectively. Subsequently, the models are provided for the NSGA-II algorithm to implement multi-objective optimization (MOO). Eventually, utilizing two different final decision-making (FDM) approaches (LINMAP and TOPSIS), optimized impact parameters are attained from the Pareto front. Regarding the results, the optimum amount of Weber number, impact spacing, and pool temperature accomplished by LINMAP and TOPSIS procedures are 309.44, 2.84 mm, 66.89 °C, and 294.98, 2.78 mm, 66.89 °C, respectively. This is the first investigation delving into the optimization of multiple droplet impacts for TES applications.

An Integrated Intelligent System for Breast Cancer Detection at Early Stages Using IR Images and Machine Learning Methods with Explainability.

Breast cancer is the second most common cause of death among women. An early diagnosis is vital for reducing the fatality rate in the fight against breast cancer. Thermography could be suggested as a safe, non-invasive, non-contact supplementary method to diagnose breast cancer and can be the most promising method for breast self-examination as envisioned by the World Health Organization (WHO). Moreover, thermography could be combined with artificial intelligence and automated diagnostic methods towards a diagnosis with a negligible number of false positive or false negative results. In the current study, a novel intelligent integrated diagnosis system is proposed using IR thermal images with Convolutional Neural Networks and Bayesian Networks to achieve good diagnostic accuracy from a relatively small dataset of images and data. We demonstrate the juxtaposition of transfer learning models such as ResNet50 with the proposed combination of BNs with artificial neural network methods such as CNNs which provides a state-of-the-art expert system with explainability. The novelties of our methodology include: (i) the construction of a diagnostic tool with high accuracy from a small number of images for training; (ii) the features extracted from the images are found to be the appropriate ones leading to very good diagnosis; (iii) our expert model exhibits interpretability, i.e., one physician can understand which factors/features play critical roles for the diagnosis. The results of the study showed an accuracy that varies for the most successful models amongst four implemented approaches from approximately 91% to 93%, with a precision value of 91% to 95%, sensitivity from 91% to 92 %, and with specificity from 91% to 97%. In conclusion, we have achieved accurate diagnosis with understandability with the novel integrated approach.

3D Radiometric Mapping by Means of LiDAR SLAM and Thermal Camera Data Fusion.

The ability to produce 3D maps with infrared radiometric information is of great interest for many applications, such as rover navigation, industrial plant monitoring, and rescue robotics. In this paper, we present a system for large-scale thermal mapping based on IR thermal images and 3D LiDAR point cloud data fusion. The alignment between the point clouds and the thermal images is carried out using the extrinsic camera-to-LiDAR parameters, obtained by means of a dedicated calibration process. Rover's trajectory, which is necessary for point cloud registration, is obtained by means of a LiDAR Simultaneous Localization and Mapping (SLAM) algorithm. Finally, the registered and merged thermal point clouds are represented through an OcTree data structure, where each voxel is associated with the average temperature of the 3D points contained within. Furthermore, the paper presents in detail the method for determining extrinsic parameters, which is based on the identification of a hot cardboard box. Both methods were validated in a laboratory environment and outdoors. It is shown that the developed system is capable of locating a thermal object with an accuracy of up to 9 cm in a 45 m map size with a voxelization of 14 cm.

Enhanced thermal imaging to detect microvasculature during surgery: Real-time image acquisition

We are developing a new IR imaging technique, enhanced thermal imaging (ETI), that can delineate blood vessels embedded in water-rich tissue in real time. The technique is a combination of thermal IR imaging (8-10 μm) and selective heating of blood (∼0.5°C) relative to surrounding water-rich tissue using LED sources (530 nm) at low powers (irradiance <500 mW/cm2). Blood absorbs light strongly at these wavelengths, while absorption by soft tissues is lower. Illumination of tissue containing vessels with the LED heats the blood compared to surrounding tissue so that the vessels appear brighter in the thermal image. In previous work, we successfully highlighted vessels embedded in porcine heart tissue and the blood-rich vascular region that is routinely targeted for surgical excision around mammary tumor masses in a murine model. However, in this earlier work the IR images were recorded, and extensive post-acquisition processing was necessary to highlight the presence of the vascular structures. In this work, we describe recent progress in making ETI a real-time technique. A tissue model with simulated blood vessels and a porcine heart tissue model were both imaged with a FLIR thermal camera. Frame-to-frame temporal and spatial derivatives were calculated in real-time and then used to identify regions exhibiting rapid changes in temperature, thus highlighting the structure of blood-rich regions.

Особенности и результаты измерений ИК-поля от 4-щелевой диск-мишени и абсолютно черного тела в диапазоне спектра 7–14 мкм

Object and purpose of research. This paper discusses infrared signature measurements for test targets. The purpose of the study was to control and investigate infrared signature and its dynamics in different conditions of its generation by a simulator of an absolutely black body. Subject matter and methods. The measurement was performed with a set of automatically rotating 4-slot targets. From one side, these targets were subject to the radiation from an absolutely black body and a 7–14 μm IR thermal imager. On the other side, the targets had the instrumentation that recorded infrared signals. Main results. The study yielded infrared signature estimates for six different targets. It also yielded the expressions linking the parameters of the target field, the field around target slots and the initial field generated by the absolutely black body. It was also possible to obtain the parameters that determine the efficiency of IR imager in the detection of targets of different size. The study established the boundaries for 50 % loss of target structure detection and investigated the methods that maintain the applicability of this technique. Conclusion. The study yielded the data about acceptable resolution parameters of the IR imager, as well as the methods for maintaining its capabilities and further development paths for this control technology based on test targets.

Optimization of thermal characteristics of axisymmetric synthetic air jet impingement on flat surface

The local heat transfer of axisymmetric synthetic air jet impinging on flat surface is investigated experimentally. Acoustic speaker is used for generation of synthetic air jet with cavity of cylindrical shape.The experiments is conducted for actuator frequency ranging from 50Hz to 400Hz, orifice diameter 2mm to 10mm, orifice plate thickness 2mm to 10mm, cavity diameter 50mm to 75mm, cavity depth 30mm to 60mm, jet to plate distance 16mm to 112mm. A steady heat flow is maintained on the flat surface. Local heat transfer characteristics on flat surface is found by thermal images using IR thermal imaging and thin foil technique.The experimental results reveals that the heat transfer is highly effected by frequency, orifice diameter, orifice plate thickness, jet to plate distance. However, cavity depth and cavity diameter has small influence on thermal performance.The higher cavity volume show more influence on heat transfer characteristics. An optimization of synthetic jet performance parameters is studied for maximum thermal performance interms of heat transfer characteristics.

Influence of turbulator under the detached rib on heat transfer study of air jet impinging on a flat surface

Detached ribs are one of the surface roughners for heat transfer augmentation. The mounts provided under the detachable rib act as a turbulator and assist in additional heat transfer augmentation. The influence of number of mounts under the detachable rib on heat transfer augmentation is investigated experimentally by varying nozzle to surface distance (z/d = 0.5 to 6) for jet Reynolds number of 20000. The heat transfer characteristics is determined by IR thermal imaging and thin foil method. At stagnation region, detachable rib design resulted constant enhancement in heat transfer distribution in comparison to the results of smooth flat surface. At z/d = 0.5, the enhancements of around 43%, 53% and 58% in average Nusselt numbers are observed for fully detached rib, detached rib with 4 mounts and 6 mounts when compared with smooth flat surface. For lower value of nozzle to surface distance (z/d = 0.5), the augmentation in average Nusselt numbers are effective for detachable rib with 6 mounts due to higher turbulence intensity as a consequence of mixing caused by flow recirculation and counter spinning vortex formation behind the mounts.

Influence of ratio of nozzle length to diameter on local heat transfer study of an unconfined circular air jet impingement

The influence of ratio of nozzle length to diameter on local heat transfer characteristics of an unconfined circular air jet impingement on flat plate is studied experimentally. The ratio of nozzle length to diameter (L/D = 0.5 to 83), nozzle to plate surface (z/D = 0.2 to 2) and Reynolds number (Re = 12,000 to 28,000) is investigated. The local heat transfer characteristics are reported at stagnation and wall jet region by using IR thermal imager and thin foil technique. Peak Nu occurs at wall jet area for z/D = 0.2 rather than at stagnation point for all L/D ratios and is substantially dependent on z/D and Re. It is caused by flow acceleration due to venacontraction effect between the nozzle and target surfaces which results in higher Nu in wall jet area than in stagnation area. For all Reynolds number, long pipe nozzle gives higher stagnation Nu value at z/D < 0.75 due to fully developed flow at nozzle outlet and L/D = 0.5 gives higher stagnation Nu value at z/D > 0.75 due to higher turbulence motion at nozzle outlet. At z/D < 0.4, L/D = 0.5 has a lower Nu at all L/D ratios in wall jet area (R/D > 2) and it decreases as Re increases. The influence of L/D ratio in wall jet zone (R/D > 1.8) is nearly comparable at all Re for z/D > 0.75. The L/D ratios are least influenced at lower Re and higher z/D value. The correlation of stagnation Nu was obtained with maximum deviation of ±16% to the maximum heat transfer rate for optimum conditions.

Extrapolation method for reliable measurement of Seebeck coefficient of organic thin films

Measurement of the Seebeck coefficient of an organic thermoelectric (TE) thin film necessitates the accurate measurement of the temperature difference across the film. However, direct measurement of temperature difference is difficult for a small-gap organic TE device, which is favored for the high-resistance organic materials. Here, the effect of a nonlinear temperature distribution on the Seebeck coefficient measurement of organic TE films was systematically investigated to enable clear identification of the Seebeck coefficient for an organic TE film. The nonlinear temperature distribution across an organic TE device was analyzed by a finite-element analysis simulation and IR thermal imaging. The nonlinear temperature distribution resulted in a difference between the measured temperature difference and the actual temperature difference across the organic TE film. The conventional interpolation method significantly overestimated the Seebeck coefficient when the temperature distribution was nonlinear. To reduce the measurement error, the ideal Seebeck voltage was extrapolated from a series of Seebeck voltages measured at different position in the edge-contacted device configuration. The ideal Seebeck coefficients of various organic TE films with a wide range of electrical conductivities were determined successfully, and the Seebeck coefficient measured by extrapolation method was not affected by the geometry of the organic TE film. • Nonlinear temperature distribution during Seebeck coefficient measurement is systematically investigated. • An extrapolation method is used for evaluating an ideal Seebeck voltage that directly corresponded to the temperature difference across organic films. • Our method enables accurate measurement of the Seebeck coefficient of an organic thin film with a short-channel architecture and a high-resistance.

Automated Crater detection from Co-registered optical images, elevation maps and slope maps using deep learning

Craters are topographic structures resulting from impactors striking the surface of planetary bodies. This paper proposes a novel way of simultaneously utilizing optical images, digital elevation maps (DEMs), and slope maps for automatic crater detection on the lunar surface. The proposed system utilizes Mask R–CNN by tuning it for the crater detection task. Two catalogs, namely, Head-LROC and Robbins, are used for performance evaluation, and extensive analysis of detection results for the lunar surface is performed for both of these catalogs. A recall value of 93.94% is obtained for the Head-LROC catalog, which has relatively strict crater markings. For the Robbins catalog, an exhaustive crater catalog based on relatively liberal marking, F 1 -score of the proposed system ranges from 64.27% to 81.33%, for different crater size ranges. The proposed system's generalization capability for crater detection on different terrains with different input data types is also evaluated. Experimental results show that the proposed system trained on the lunar surface can also detect craters on the Martian surface. This model is trained by simultaneously using lunar surface's optical images and DEMs with their corresponding slope maps; however, it is tested on an entirely different input data type, thermal IR images from the Martian surface. • Crater detection by simultaneously using optical images, DEMs, and slope data. • Evaluation of crater detection and localization on conservative and liberal catalogs. • Proposed system either outperforms or matches the current state-of-the-art. • For the first time exploration of training deep learning system on Robbins catalog. • Generalization capability explored on Martian surface with different input data type.