Search Results (142)

This work investigates the feasibility of using thermographic techniques to identify the three possible states of a silicon-based coating on a carbon–silicon matrix (ISiComp). Experimental tests were therefore carried out on specimens prepared in three different conditions: uncoated, coated, and coated then oxidized. The study compares lock-in thermography and pulsed thermography using both a cooled mid-wave infrared (MWIR) camera and an uncooled long-wave infrared (LWIR) microbolometric camera. The main objective is to distinguish coated from uncoated conditions and oxidized from non-oxidized conditions, while recognizing that the coated and oxidized states cannot coexist simultaneously on the same specimen. The results show that thermographic techniques, when supported by appropriate post-processing, are promising for this purpose. In particular, the uncooled LWIR camera provided better results than the cooled MWIR camera, whereas the current approach did not allow a robust distinction between the pristine-coated and oxidized-coated states. At the same time, the study highlights limitations related to specimen size and to the additional treatments applied to reproduce the different surface states. Future work will address larger specimens and real components, together with the implementation of advanced AI-based classification algorithms to overcome the current limitations of the proposed approach. Full article

Combined pulse laser systems combining continuous-wave (CW) lasers and nanosecond pulsed lasers have shown clear advantages in metal ablation and surface modification. However, the plasma shielding effect induced by nanosecond pulses and the associated shock-wave phenomena in hybrid laser systems remain insufficiently investigated, particularly regarding their influence on CW laser energy coupling. In this study, the ablation behavior of metal targets under the combined irradiation of a 500 W CW laser and nanosecond pulsed lasers with pulse energies ranging from 0.4 J to 1.0 J was investigated. High-speed plasma imaging was employed to analyze laser–material interaction characteristics, including absorption behavior and molten material ejection, while high-speed infrared thermography was used to monitor transient temperature evolution during combined pulse laser processing. Macroscopic and microscopic analyses were conducted to characterize damage morphology, and a three-dimensional surface profilometer was used to quantitatively evaluate ablation efficiency. The results show that, under combined pulse laser irradiation, the removed volume increased from 0.05 mm³ to 0.618 mm³ and the ablation depth increased from 0.136 mm to 0.776 mm. Compared with CW laser processing alone, the ablation efficiency was markedly enhanced. This improvement is attributed to the combined effects of optimized energy deposition, thermal distribution, and material response. In addition, the plasma shielding effect was observed to vary with nanosecond pulse energy, indicating that precise energy control is critical for performance enhancement. This study demonstrates the potential of combined pulse laser technology for high-efficiency and high-precision metal surface processing and micro–nano fabrication. Full article

Background: The analysis of gunshot residue (GSR) is crucial for gaining information on how a crime occurred. This study presents an innovative proof of concept for measuring shooting distances by performing Flash-Pulse active Thermography (FPT). Compared to conventional chemical methods, FPT offers a significant advantage by digitalizing the residue pattern in a non-destructive manner. Methods: Thermal images of cotton canvases, both white and colored, were analyzed to quantify the distribution of gunshot residues after shooting from several distances, specifically focusing on smoke and semi-burnt powders. The proposed approach uses contrast and radial intensity profiles to extract exponential coefficients, which are dependent on the shooting distance. Results: Employing a sigmoid model to fit the coefficients over distance and to derive a characteristic feature used as a classification metric, firing distances can be classified into short, medium, and long range and can be predicted with an uncertainty of less than 5 cm for distances between 18 and 38 cm under the tested conditions. Considerations regarding the influence of different weapons and ammunition are reported, suggesting the potential for a general approach. Conclusions: The methodology has been validated on several samples, demonstrating its feasibility for specific forensic applications. Its most robust use is as a weapon- and ammunition-specific calibration tool, supporting case-specific distance estimation analysis. Full article

This study addresses the detection of gunshot residue (GSR) around a bullet hole, which is one of the key forensic procedures for estimating the firing distance. GSR was inspected using flash-pulse thermography (FPT) with Kurtosis statistical processing. The result of such an inspection is a pattern composed of numerous small indications distributed around the hole, attributed to gunshot residue particles. The number and spatial distribution of these indications depend on the firing distance. Analyzing such results based on individual indications is impractical, as the pattern must be evaluated as a whole. Therefore, quantifying the overall result can significantly improve the analysis of the firing distance estimation. This study presents a quantification procedure based on threshold-based mass-marking of indications and evaluation of several statistical characteristics. The correlation between these characteristics and firing distance is then analyzed. A strong but distinctly nonlinear correlation was found between the firing distance and some simple quantitative characteristics, such as the total number of indications. However, the study shows that some derived characteristics, such as the contrast between marked areas and background, exhibit a near-linear correlation. These parameters are, therefore, promising for firing distance analysis based on FPT inspection of GSR on through-shot targets. Full article

In nondestructive evaluation (NDE), pulsed phase thermography (PPT) is a commonly used technique which relies on phase contrast to detect defects. This study presents a methodology to investigate how changes in signal processing and geometrical parameters affect phase contrast. Analytically simulated thermal signals are used to evaluate the phase contrast for varying sample thicknesses and defect sizes, relative to a fixed defect depth. To address the issue of spectral leakage, phase contrasts are recorded using both rectangular and Hamming windows before transformation into the frequency domain. A Gaussian process regression (GPR) modelling scheme is used to observe the relationship between phase contrast and geometrical parameters. The results suggest that both the choice of windowing function and geometrical factors can influence defect detection, offering insights to improve the reliability of PPT-based inspections. Full article

This work presents a non-destructive methodology to estimate the residual porosity and mechanical properties of titanium foams produced via Hot Isostatic Pressing (HIP) followed by solid-state foaming (SSF). Pulsed laser-spot thermography was employed to measure thermal diffusivity in compact and foamed Ti6Al4V-ELI samples derived from powders of different granulometries. A power-law correlation between thermal diffusivity and porosity was used to estimate post-foaming porosity, which was then used to predict elastic modulus, yield strength, and ultimate tensile strength. Results highlight the potential of thermal diffusivity as a reliable indicator of structural performance, offering a rapid and fully non-destructive route for evaluating metallic foams in biomedical and aerospace applications. Full article

This study investigates the effect of paint-related properties on the accuracy of delamination detection in lined oil paintings using pulsed phase thermography (PPT). Mock-ups of lined oil paintings were examined by PPT under both normal and angled illumination to induce apparently localized heating. Spectral characteristics in the excitation and detection wavelength ranges were analyzed and related to phase contrast variations in the resulting images. While paint-dependent energy absorption under localized heating may blur phase contrast and lead to misidentification of delamination, emissivity properties appear to contribute to stabilizing phase signals. These findings underscore the importance of accounting for paint properties in conservation diagnostics. Full article

In the weld bonding used in automobiles, inspecting the adhesive areas is important to achieve the desired increase in rigidity. Active infrared thermography using flash lamp heating was applied to a weld-bonded specimen. Temperature differences were observed on the measurement surface depending on the presence or absence of adhesive, enabling the detection of the bonded areas. Furthermore, singular value decomposition (SVD) was applied to obtain time-series temperature variation data. SVD emphasizes the boundaries of the adhesive areas, improving the accuracy of inspections of the adhesive application areas. Full article

The application of thermal barrier coatings (TBCs) for protecting mechanical components is widespread, particularly in high-temperature environments, such as gas turbines and aero-engines. Ensuring the integrity of these coatings throughout their service life is essential, as their degradation can lead to delamination, ultimately compromising the underlying component. It has been demonstrated that monitoring the thermal diffusivity value over time allows the monitoring of degradation of the coatings. Common thermographic techniques like pulsed and lock-in thermography have been used so far. However, to enhance both the signal-to-noise ratio (SNR) and the accuracy of thermal property measurements, new active thermography techniques have been developed. These methods rely on optimized excitation schemes combined with advanced signal processing strategies. In this work, we first introduce the pulse-compression thermography approach, which employs pseudo-noise modulated excitation to monitor and estimate the thermal diffusivity of the coating layers. Full article

The article presents a mathematical description of the thermal phenomena occurring both inside and on the surfaces of a homogeneous plate subjected to an external heat flux on one side. Analytical formulae for thermal excitation, with a given duration and constant power, are derived, enabling the determination of temperature increases on both the heated and unheated surfaces of the plate under specific heat transfer conditions to the surroundings. Convective heat transfer, with individual heat transfer coefficients on both sides of the slab, is considered; however, radiative heat loss can also be included. The solution of the problem obtained using two methods is presented: the method of separation of variables (MSV) and the Laplace transform (LT). The advantages and disadvantages of both analytical formulae, as well as the impact of various factors on the accuracy of the solution, are discussed. Among others, the MSV solution works well for a sufficiently long time, whereas the LT solution is better for a sufficiently short time. The theoretical considerations are illustrated with diagrams for several configurations, each representing various heat transfer conditions on both sides of the plate. The presented solution can serve as a starting point for further analysis of more complex geometries or multilayered structures, e.g., in non-destructive testing using active thermography. The developed theoretical model is verified for a determination of the thermal diffusivity of a reference material. The model can be useful for analyzing the method’s sensitivity to various factors occurring during the measurement process, or the method can be adapted to a pulse of known duration and constant power, which is much easier to implement technically than a very short impulse (Dirac) with high energy. Full article

This paper reviews recent advances in machine learning (ML) algorithms to improve the postprocessing and interpretation of thermographic data in non-destructive testing (NDT). While traditional NDT methods (e.g., visual inspection, ultrasonic testing) each have their own advantages and limitations, thermographic techniques (e.g., pulsed thermography, laser thermography) have become valuable complementary tools, particularly in inspecting advanced materials such as carbon fiber-reinforced polymers (CFRPs) and superalloys. These techniques generate large volumes of thermal data, which can be challenging to analyze efficiently and accurately. This review focuses on how ML can accelerate defect detection and automated classification in thermographic NDT. We summarize currently popular algorithms and analyze the limitations of existing workflows. Furthermore, this structured analysis provides an in-depth understanding of how artificial intelligence can assist in processing NDT data, with the potential to enable more accurate defect detection and characterization in industrial applications. Full article

This paper presents a comparative analysis of ten state-of-the-art robotic de-mining systems, grouped into (i) sensor-centric platforms for high-precision detection and (ii) rapid mechanical-contact vehicles for clearance. Building on these findings, we propose a lightweight tracked platform (~1.9 T) equipped with a four-channel sensing suite-RGB/IR camera, 32-layer LiDAR, pulsed-induction metal detector, and 2.45 GHz microwave thermography—integrated in an adaptive Bayesian “detect → confirm → neutralize” loop. The modular end-effector permits either pinpoint mechanical intervention or deployment of a linear charge. Modelling indicates an expected detection sensitivity ≥ 95% with a false-positive rate ≤ 5% in humanitarian demining mode and a clearance throughput above 1.5 ha·h⁻¹ in breaching mode. Ongoing work includes CFD analysis of the thermal front, fabrication of a prototype, and performance testing in accordance with IMAS 10.20. Full article

Rolling contact fatigue (RCF)-induced cracks in steel rails exhibit a fish-scale-shaped cluster distribution, and generally form in a layered, overlapping manner. Eddy-current-pulsed thermography (ECPT) has been applied in RCF detection by taking advantage of electromagnetic–thermal execution; however, one still faces challenges in identifying and quantifying such layered, overlapping defects. This paper proposes a swept-frequency eddy-current-pulsed thermal tomography (ECPTT) detection method to quantitatively characterize multilayer crack depth and inclination angle in an artificial rail sample. In particular, stimulating frequency modulation is used to guide the induced eddy current and heat to varying depths, and this is combined with principal component analysis (PCA) to identify multilayer defects. Moreover, a thermal signal reconstruction (TSR) algorithm is introduced. TSR features are extracted for analyzing the burial depth and inclination angle of multilayer defects. The results demonstrate that the third principal component (PC3), extracted via PCA, enables layer-count discrimination in multilayer defects. Integrated with gradient magnitude analysis of the second principal component (PC2) under swept-frequency excitation, defect contour localization error can be controlled within 0.5 mm. Building on layer discrimination, multi-frequency thermal response analysis further reveals variations in PC1’s variance contribution, differentiating inclination angles of 10° and 20°, whereas comparative heating- and cooling-rate magnitudes distinguish burial depths of 0.5 mm and 1.0 mm. The research verifies that the ECPTT system can accurately detect the layer number, inclination angle, and depth of buried RCF defects, substantially enhancing the accuracy of defect contour reconstruction. Full article

The Karnak Temples are considered one of Egypt’s most significant archaeological sites, dating back to the Middle Kingdom (c. 2000–1700 BC) and were continuously expanded until the Ptolemaic period (305–30 BC). As the second most visited UNESCO World Heritage archaeological site in Egypt after the Giza Pyramids, Karnak faces severe deterioration processes due to prolonged exposure to environmental impacts, mechanical damage, and historical interventions. This study employs a multidisciplinary approach integrating non-destructive testing (NDT) methods to assess the physical and mechanical condition and degradation mechanisms of scattered sandstone blocks at the site. Advanced documentation techniques, including Reflectance Transformation Imaging (RTI), photogrammetry, and Infrared Thermography (IRT), were used to analyze surface morphology, thermal stress effects, and weathering patterns. Ultrasonic Pulse Velocity (UPV) testing provided internal structural assessments, while spectral and gloss analysis quantified chromatic alterations and surface roughness. Additionally, the Karsten Tube test determined the water absorption behavior of the sandstone, highlighting variations in porosity and susceptibility to salt crystallization. In this sense, the results indicate that climatic factors such as extreme temperature fluctuations, wind erosion, and groundwater infiltration contributed to sandstone deterioration. Thermal cycling leads to microcracking and granular disintegration, while high capillary water absorption accelerates chemical weathering processes. UPV analyses showed substantial internal decay, with low-velocity zones correlating with fractures and differential cementation loss. Finally, an interventive conservation plan was proposed. Full article

This study investigates the thermal performance of induction motors powered by multilevel H-bridge inverters using a novel pulse-width phase shift triangle modulation (PSTM-PWM) technique. Conventional PWM methods introduce significant harmonic distortion, increasing copper and iron losses and causing overheating and reduced motor lifespan. Through experimental testing and comparison with standard PWM techniques (LS-PWM and PS-PWM), the proposed PSTM-PWM reduces harmonic distortion by up to 64% compared to the worst one and internal motor losses by up to 5.5%. A first-order thermal model is used to predict motor temperature, validated with direct thermocouple measurements and infrared thermography. The results also indicate that the PSTM-PWM technique improves thermal performance, particularly at a triangular waveform peak value of 3.5 V, reducing temperature by around 6% and offering a practical and simple solution for industrial motor drive applications. The modulation order was set to M = 7 to reduce both the losses in the power inverter and to prevent the generation of very high voltage pulses (high dV/dt), which can deteriorate the insulation of the induction motor windings over time. Full article