Search Results (136)

AISI 316 is a stainless steel known for its exceptional corrosion resistance and excellent mechanical properties. It is used in the chemical and pharmaceutical industries, food processing equipment, and medical devices. This alloy’s wide range of applications underscores its importance in industries requiring materials that can withstand extreme conditions while maintaining structural integrity and performance. Additionally, the excellent weldability and formability of AISI 316 allow for versatile design and production processes, ensuring durable and reliable performance in marine environments. This work aims to examine the behavior of AISI 316L and its welded joints under high-cycle fatigue loadings using infrared thermography (IR). Two kinds of experimental tests are performed on specimens with the same geometry: static tests and stepwise succession tests. The results of the static tests are in accordance with the stepwise succession test results in predicting the fatigue properties. Full article

Hydrogen leakage in Proton Exchange Membrane (PEM) fuel cells poses critical safety, efficiency, and operational reliability risks. This study introduces an innovative infrared (IR) thermography-based methodology for detecting and quantifying hydrogen leaks towards the outside of PEM fuel cells. The proposed method leverages the catalytic properties of a membrane electrode assembly (MEA) as an active thermal tracer, facilitating real-time visualisation and assessment of hydrogen leaks. Experimental tests were conducted on a single-cell PEM fuel cell equipped with intact and defective gaskets to evaluate the method’s effectiveness. Results indicate that the active tracer generates distinct thermal signatures proportional to the leakage rate, overcoming the limitations of hydrogen’s low IR emissivity. Comparative analysis with passive tracers and baseline configurations highlights the active tracer-based approach’s superior positional accuracy and sensitivity. Additionally, the method aligns detected thermal anomalies with defect locations, validated through pressure distribution maps. This novel, non-invasive technique offers precise, reliable, and scalable solutions for hydrogen leak detection, making it suitable for dynamic operational environments and industrial applications. The findings significantly advance hydrogen’s safety diagnostics, supporting the broader adoption of hydrogen-based energy systems. Full article

The state of the art in IR thermal imaging methods for applications in medical diagnostics is discussed. A review of advances in IR thermal imaging technology in the years 1960–2024 is presented. Recently used artificial intelligence (AI) methods in the analysis of thermal images are the main interest. IR thermography is discussed in view of novel applications of machine learning methods for improved diagnostic analysis and medical treatment. The AI approach aims to improve image quality by denoising thermal images, using applications of AI super-resolution algorithms, removing artifacts, object detection, face and characteristic features localization, complex matching of diagnostic symptoms, etc. Full article

Infrared (IR) magneto-optical (MO) bi-imaging is an innovative method for detecting weld defects, and it is important to process both IR thermography and MO imaging characteristics of weld defects. IR thermography and MO imaging can not only run simultaneously but can also run separately in special welding processes. This paper studies the sensing processing of eddy current IR thermography and MO imaging for detecting weld defects of laser spot welding and butt joint laser welding, respectively. To address the issues of high-level noise and low contrast in eddy current IR detection thermal images interfering with defect detection and recognition, a method based on least squares and Gaussian-adaptive bilateral filtering is proposed for denoising eddy current IR detection thermal images of laser spot welding cracks and improving the quality of eddy current IR detection thermal images. Meanwhile, the image gradient is processed by Gaussian-adaptive bilateral filtering, and then the filter is embedded in the least squares model to smooth and denoise the image while preserving defect information. Additionally, MO imaging for butt joint laser welding defects is researched. For the acquired MO images of welding cracks, pits, incomplete fusions, burn-outs, and weld bumps, the MO image processing method that includes median filtering, histogram equalization, and Wiener filtering was used, which could eliminate the noise in an image, enhance its contrast, and highlight the weld defect features. The experimental results show that the proposed image processing method can eliminate most of the noise while retaining the weld defect features, and the contrast between the welding defect area and the normal area is greatly improved. The denoising effect using the Natural Image Quality Evaluator (NIQE) and the Blind Image Quality Index (BIQI) has been evaluated, further demonstrating the effectiveness of the proposed method. The differences among weld defects could be obtained by analyzing the gray values of the weld defect MO images, which reflect the weld defect information. The MO imaging method can be used to investigate the magnetic distribution characteristics of welding defects, and its effectiveness has been verified by detecting various butt joint laser welding weldments. Full article

In this paper, the thermal insulation performance of a wooden house was evaluated with infrared thermographies which were captured by a non-contact and non-destructive method. Heat transmissions were determined by the difference between surface temperature of outdoor and indoor sides of the walls, which were measured with an IR ray signal, and indoor and outdoor air temperatures. The heat transmission coefficient, which was determined by IR thermography, was compared to the coefficient calculated with thermal conductivities of wall component materials. The heat transmission coefficient calculated through wall components was 0.24 W/m²·K, while the coefficients determined with IR thermography ranged from 0.27 to 4.61 W/m²·K. The invisible thermal insulation defects in the wall, such as heat losses from the premature deterioration of thermal insulation material and air leakage through windows, were observed by IR thermography. It is expected that the results of this study could be used effectively not only for improving thermal insulation performance but also for suppressing decay occurrence in wooden building materials. Full article

Breast cancer remains one of the most prevalent and deadly cancers affecting women worldwide. Early detection is crucial, particularly for younger women, as traditional screening methods like mammography often struggle with accuracy in cases of dense breast tissue. Infrared thermography offers a non-invasive imaging alternative that enhances early detection by capturing subtle thermal variations indicative of breast abnormalities. This study investigates and compares the performance of various deep learning and machine learning models in analyzing thermographic data to classify breast tissue as healthy, benign, or malignant. To maximize detection accuracy, data preprocessing, feature extraction, and dimensionality reduction were implemented to isolate distinguishing characteristics across tissue types. Leveraging advanced feature extraction and visualization techniques inspired by geospatial data methodologies, we evaluated several deep learning architectures and classical classifiers using the DRM-IR and Breast Thermography Mendeley thermal datasets. Among the tested models, the ResNet152 architecture combined with a Support Vector Machine (SVM) classifier delivered the highest performance, achieving 97.62% accuracy, 95.79% precision, 98.53% recall, 94.52% specificity, an F1 score of 97.16%, an area under the curve (AUC) of 99%, a latency of 0.06 s, and CPU utilization of 88.66%. These findings underscore the potential of integrating infrared thermography with advanced deep learning and machine learning approaches to significantly improve the accuracy and efficiency of breast cancer detection, supporting its role as a valuable tool for early diagnosis. Full article

The knee is one of the joints most vulnerable to disease and injury, particularly in athletes and older adults. Surface temperature monitoring provides insights into the health of the analysed area, supporting early diagnosis and monitoring of conditions such as osteoarthritis and tendon injuries. This study presents an innovative approach that combines infrared thermography techniques with a Resnet 152 (DeepLabCut based) to detect and monitor temperature variations across specific knee regions during repeated sit-to-stand exercises. Thermal profiles are then analysed in relation to weight distribution data collected using a Wii Balance Board during the exercise. DeepLabCut was used to automate the selection of the region of interest (ROI) for temperature assessments, improving data accuracy compared to traditional time-consuming semi-automatic methods. This integrative approach enables precise and marker-free measurements, offering clinically relevant data that can aid in the diagnosis of knee pathologies, evaluation of the rehabilitation progress, and assessment of treatment effectiveness. The results emphasize the potential of combining thermography with DeepLabCut-driven data analysis to develop accessible, non-invasive tools for joint health monitoring or preventive diagnostics of pathologies. Full article

This article presents the application of infrared thermography as a nondestructive testing method (NDT) for detecting osmotic damage in glass-fiber-reinforced polymer (GFRP) and glass-reinforced polymer (GRP) boat hull structures. The aim of the conducted experiments is to explore the possibilities of applying active infrared thermography to real structures and to establish a procedure capable of filtering out anomalies caused by various thermal influences, such as thermal reflections from surrounding objects, geometry effects, and heat flow variations on the observed object. The methods used for post-processing IR signals include lock-in thermography (LT), pulse thermography (PT), pulse phase thermography (PPT), and gradient pulse phase thermography (GT). The practical application and advantages and disadvantages of infrared thermography in identifying osmotic damage in GFRP and GRP boat hulls will be illustrated through three case studies. Each case study is based on specific conditions and characteristics of different types of osmotic damage, enabling a thorough analysis of the effectiveness of the method in detecting and assessing the severity of the damage. The post-processed thermal images enable a clearer distinction between damaged and undamaged zones, improving the robustness of detection under realistic field conditions. Full article

Firefighters need personal protection equipment and protective clothing to be safe and protected when responding to fire incidents. At present, firefighters’ suits are developed by using inherently thermal-resistant fibers but pose serious problems related to comfort. In the present research, multilayered fire-fighting fabrics were developed with different fiber blends. Multilayer fire retardant (FR) fabrics with phase change materials (PCMs) inserts were developed and compared with reference multilayer fabrics without PCM. In this context, four fabric samples were chosen to fabricate the multilayer FR fabrics. Properties of multilayer fabrics were investigated, which include physical, thermo–physiological comfort, and flame-resistant performance. The heating process of the clothing was examined using infrared (IR) thermography, differential scanning calorimetry (DSC), thermal protective testing (TPP), and steady-state (Convective and Radiant) heat resistance tests. Areal density and thickness were measured as physical parameters, and air permeability (AP), overall moisture management capacity (OMMC), and thermal conductivity were measured as thermo–physiological comfort characteristics. The inclusion of PCM improved the thermal protection as well as flame resistance significantly. Sample S1 (Nomex + PTFE + Nomex with PCM) demonstrated superior fire resistance, air permeability, and thermal protection, with a 37.3% increase in air permeability as compared to the control sample (SC) by maintaining comfort while offering high thermal resilience. The inclusion of PCM enhanced its thermal regulation, moderating heat transfer. Flame resistance tests confirmed its excellent performance, while thermo–physiological assessments highlighted a well-balanced combination of thermal conductivity and air permeability. This study will help to improve the performance of firefighter protective fabrics and provide guidelines in terms of balancing comfort and performance while designing firefighter protective clothing for different climatic conditions. Full article

Recently, the dairy sector has been ever more affected by global warming. This study aimed to test a novel conductive cooling system for cattle that was successfully implemented and evaluated under summer thermally challenging weather conditions in Poland. The system consists mainly of the chiller, tank, and chilled water-driven mattress, designed to prioritize animal well-being. The experimental evaluation was carried out on three Friesian dry cows, housed on different types of bedding—commercial water mattress, straw, and cooling water mattress—and supplied with water at 10 °C (day) and 16 °C (night). The cooling water mattress’ surface temperature was twice as low as that of the commercial water mattress. The animal’s thermal comfort was assessed with physiological and behavioral reactions. The cooling effect on animals’ bodies was demonstrated with a lower reticulorumen temperature of the cooled cow (p < 0.05) than the reference ones. The local effect of cooling was proved with an 8 °C-lower skin temperature after the cow’s resting period. The presented study opens a new research direction toward dairy cattle’s welfare, sustainability, and the food–energy–water nexus, based on potential energy and water savings. Full article

This paper deals with the experimental procedures of lock-in thermography (LIT) for polyetheretherketone (PEEK), which is used as a lightweight material in various industrial fields. The LIT has limitations due to non-uniform heating by external optic sources and the non-uniformity correction (NUC) of the infrared (IR) camera. It is generating unintended contrast in the IR image in thermal imaging inspection, reducing detection performance. In this study, the non-uniformity effect was primarily improved by producing an equivalent array halogen lamp. Then, we presented absolute temperature compensation (ATC) and temperature ratio compensation (TRC) techniques, which can equalize the thermal contrast of the test samples by compensating for them using reference samples. By applying compensation techniques to data acquired from the test samples, defect detectability improvement was quantitatively presented. In addition, binarization was performed and detection performance was verified by evaluating the roundness of the detected defects. As a result, the contrast of the IR image was greatly improved by applying the compensation technique. In particular, raw data were enhanced by up to 54% using the ATC compensation technique. Additionally, due to improved contrast, the signal-to-noise ratio (SNR) was improved by 7.93%, and the R² value of the linear trend equation exceeded 0.99, demonstrating improved proportionality between the defect condition and SNR. Full article

A new class of biologics is obtained using the technologically processed of antibodies (TPA), which are used as the initial substance, and their dilution at each stage is accompanied by a controlled external vibrational (mechanical) treatment. This article focuses on the development and validation of a novel technique that can be applied for assessing the identity of TPA-based drugs. It has previously been found that after such treatment, the resulting solution either acquired new properties that were not present in the initial substance or a quantitative change in properties compared to the initial substance was observed. The use of mechanical treatment during the manufacture of the TPA-based drugs can cause the formation of new bonds between the solvent and antibody molecules. These changes manifest themselves in altered adsorption at the surface of the test solutions, which results in the formation of a near-surface film. One of the indicators of such events is the change in the surface temperature of the solution, which can be analyzed using high-resolution thermography. Unlike other methods, the high-resolution thermography allows the near-surface layer of a heterogeneous aqueous solution to be clearly visualized and quantified. A number of experiments were performed: seven replicates of sample preparations were tested; the influence of factors “day” or “operator” was investigated during 12 days of testing by two operators. The method also allowed us to distinguish between technologically processed antibodies and samples containing technologically processed buffer. The thermographic analysis has proven to be a simple, specific, and reproducible technique that can be used to analyze the identity of TPA-based drugs, regardless of the dosage form tested. Full article

In the manufacture of ancient books, it was quite common to insert written scraps belonging to earlier library material into bookbindings. For scholars like codicologists and paleographers, it is extremely important to have the possibility of reading the text lying on such scraps without dismantling the book. In this regard, in this paper, we report on the detection of these texts by means of infrared (IR) pulsed thermography (PT), which, in recent years, has been specifically proven to be an effective tool for the investigation of Cultural Heritage. In particular, we present a quantitative analysis based, for the first time, on PT images obtained from books of historical relevance preserved at the Biblioteca Angelica in Rome. The analysis has been carried out by means of a theoretical model for the PT signal, which makes use of two image parameters, namely, the distortion and the contrast, related to the IR readability of the buried texts. As shown in this paper, the good agreement between the experimental data obtained in the historical books and the theoretical analysis proved that the capability of the adopted PT method could be fruitfully applied, in real case studies, to the detection of buried texts and to the quantitative characterization of the parameters affecting their thermal readability. Full article

The detection of impact and depth defects in Glass Fiber Reinforced Polymer (GFRP) composites has been extensively studied to develop effective, reliable, and cost-efficient assessment methods through various Non-Destructive Testing (NDT) techniques. Challenges in detecting these defects arise from varying responses based on the geometrical shape, thickness, and defect types. Long Pulse Thermography (LPT), utilizing an uncooled microbolometer and a low-resolution infrared (IR) camera, presents a promising solution for detecting both depth and impact defects in GFRP materials with a single setup and minimal tools at an economical cost. Despite its potential, the application of LPT has been limited due to susceptibility to noise from environmental radiation and reflections, leading to blurry images. This study focuses on optimizing LPT parameters to achieve accurate defect detection. Specifically, we investigated 11 flat-bottom hole (FBH) depth defects and impact defects ranging from 8 J to 15 J in GFRP materials. The key parameters examined include the environmental temperature, background reflection, background color reflection, and surface emissivity. Additionally, we employed image processing techniques to classify composite defects and automatically highlight defective areas. The Tanimoto Criterion (TC) was used to evaluate the accuracy of LPT both for raw images and post-processed images. The results demonstrate that through parameter optimization, the depth defects in GFRP materials were successfully detected. The TC success rate reached 0.91 for detecting FBH depth defects in raw images, which improved significantly after post-processing using Canny edge detection and Hough circle detection algorithms. This study underscores the potential of optimized LPT as a cost-effective and reliable method for detecting defects in GFRP composites. Full article

This paper focuses on an integrated approach to study the materials and the degradation issues in the urban mural painting Ama Il Tuo Sogno, painted by the famous street artist Jorit Agoch in Matera (Italy). The study was conducted in the framework of a conservation project, aiming to contrast a progressive decay affecting the artifact that started a few months after its creation. Multi-analytical techniques were used to investigate the stratigraphy and chemical composition of the pictorial film within a low-impact analytical protocol for sustainable diagnostics. They included polarized light microscopy in UV and VIS reflected light, FTIR spectroscopy, Py-GC-HRAMS, and SEM-EDS. The mineralogical–petrographic composition of the mortar employed in the pictorial support was also studied with optical microscopy of thin sections and X-ray diffractometry. To know the mechanism underlying the degradation, IR thermography was performed in situ to establish the waterways and the distribution of the humidity in the mural painting. In addition, ion chromatography and X-ray diffractometry were used to identify and quantify the soluble salts and to understand their sources. The overall results allowed us to determine the chemical composition of the binder and pigments within the pictorial layers, the mineralogical–petrographic characteristics of the mortar of the support, and the execution technique of the painting. They also highlighted a correlation between the presence of humidity in the painted mural and the salt damage. The mineralogical phases were detected in the mural materials by XRD, and the results of ion chromatographic analyses suggested a supply of soluble salts mainly from the mortar of the support. Finally, the study provided basic knowledge for planning appropriate sustainable conservation measures. Full article