Search Results (81)

Accurate temperature measurement is a key parameter that determines the quality of additive manufactured components in directed energy deposition processes. Optical pyrometers which are used to provide in-process temperature data require accurate emissivity data of the metal surface. Process-specific emissivity data for metals used in these processes is not readily available. This paper provides the emissivity of a variety of metals used in wire-arc directed energy deposition processes. For the first time, the test samples were fabricated using typical deposition processes and systems. The metals evaluated were titanium alloy (Ti-6Al-4V), Inconel 718, mild steel, aluminum alloy 2319, and nickel aluminum bronze. At ambient temperature, the measured normal emissivity was 0.26–0.28 for Ti-6Al-4V; for Inconel 718, it was 0.45–0.54; for mild steel, it was 0.4–0.72; for aluminum 2319, it was 0.14; and for nickel aluminum bronze, it was 0.35. The approximate emissivity values are also given over the temperature range 20–1400 °C. The effect of residual oxygen in the shield gas on emissivity is explored for the first time. The spectrophotometric technique was used to measure the metal thermo-optical properties. Full article

Machine learning and artificial intelligence have transformed fault detection and maintenance strategies for industrial machinery. This study applies well-established data-driven techniques to a rarely explored industrial application—the condition monitoring of high-precision paper cutting machines—enhancing condition-based maintenance to improve operational efficiency, safety, and cost-effectiveness. A key element of the proposed approach is the integration of an infrared pyrometer into vibration monitoring, utilizing accelerometer data to evaluate the state of health of machinery. Unlike traditional fault detection studies that focus on extreme degradation states, this work successfully identifies subtle deviations from optimal, which even expert technicians struggle to detect. Building on a feasibility study conducted with Tecnau SRL, a comprehensive diagnostic system suitable for industrial deployment is developed. Endurance tests pave the way for continuous monitoring under various operating conditions, enabling real-time industrial diagnostic applications. Multi-scale signal analysis highlights the significance of transient and steady-state phase detection, improving the effectiveness of real-time monitoring strategies. Despite the physical similarity of the classified states, simple time-series statistics combined with machine learning algorithms demonstrate high sensitivity to early-stage deviations, confirming the reliability of the approach. Additionally, a systematic analysis to downgrade acquisition system specifications identifies cost-effective sensor configurations, ensuring the feasibility of industrial implementation. Full article

This study investigates the use of YOLOv8 deep learning models to segment and classify thermal images acquired from the rear of the weld pool during the Gas Tungsten Arc Welding (GTAW) process. Thermal data were acquired using a two-color pyrometer under three welding current levels (160 A, 180 A, and 200 A). Models of sizes from nano to extra-large were trained on 66 annotated frames and evaluated with and without data augmentation. The results demonstrate that the YOLOv8m model achieved the best classification performance, with a precision of 83.25% and an inference time of 21.4 ms per frame by using GPU, offering the optimal balance between accuracy and speed. Segmentation accuracy also remained high across all current levels. The YOLOv8n model was the fastest (15.9 ms/frame) but less accurate (75.33%). Classification was most reliable at 160 A, where the thermal field was more stable. The arc reflection class was consistently identified with near-perfect precision, demonstrating the model’s robustness against non-relevant thermal artifacts. These findings confirm the feasibility of using lightweight, dual-task neural networks for reliable weld pool analysis, even with limited training data. Full article

The phase fraction plays a critical role in determining the solidification characteristics of metallic alloys. In this study, we propose a novel method (f_s = (t − t_l)/(t_s − t_l)) for estimating the phase fraction based on the solidification time in cooling curves. This method was validated through an experimental analysis of Al-18 wt%Cu and Fe₄₂Ni₄₂B₁₆ alloys, where the phase fractions derived from cooling curves were compared with quantitative microstructure evaluations using computer-aided image analysis and the box-counting method. Then, a comparison between the analysis using the present novel method and Newtonian thermal analysis demonstrates good agreement between the results. The present method is easier to operate, since it does not need derivative and integral operations as in Newtonian thermal analysis. In addition, based on the characteristics of the cooling curve, we also found two other relationships—V/R_c = D/ΔT_c and RΔt = constant, where V is the solidification rate, R_c is the recalescence rate, D is the diameter of the focal area of the pyrometer, ΔT_c is the recalescence height, R is the cooling rate, and Δt is the solidification plateau time. These findings establish an operational framework for quantifying phase fractions and solidification rates in rapid solidification. Full article

High-temperature thermal images enable monitoring and controlling processes in metal, semiconductors, and ceramic manufacturing but also monitor activities of volcanoes or contrasting wildfires. Infrared thermal cameras require knowledge of the emissivity coefficient, while multispectral pyrometers provide fast and accurate temperature measurements with limited spatial resolution. Bayer-pattern cameras offer a compromise by capturing multiple spectral bands with high spatial resolution. However, temperature estimation from color remains challenging due to spectral overlaps among the color filters in the Bayer pattern, and a widely accepted calibration method is still missing. In this paper, the quantum efficiency of an imaging system including the camera sensor, lens, and filters is inferred from a sequence of images acquired by looking at a black body source between 700 °C and 1100 °C. The physical model of the camera, based on the Planck law and the optimized quantum efficiency, allows the calculation of the Planckian locus in the color space of the camera. A regression neural network, trained on a synthetic dataset representing the Planckian locus, predicts temperature pixel by pixel in the 700 °C to 3500 °C range from live images. Experiments done with a color camera, a multispectral camera, and a furnace for heat treatment of metals as ground truth show that our calibration procedure leads to temperature prediction with accuracy and precision of a few tens of Celsius degrees in the calibration temperature range. Tests on a temperature-calibrated halogen bulb prove good generalization capability to a wider temperature range while being robust to noise. Full article

Low-Energy High-Current Electron Beam (LEHCEB) is an innovative vacuum technology employed for the surface modification of conductive materials. Surface treatments by means of LEHCEB allow the melting and rapid solidification of a thin layer (up to ~10 μm) of material. The short duration of each pulse (2.5 μs) allows for the generation of high thermal rates, up to 10⁹ K/s. Due to the peculiar features of LEHCEB source, in situ temperature monitoring inside the vacuum chamber is unfeasible, even with the most rapid IR pyrometers available on the market. Therefore, multiphysics simulations serve as a tool for predicting and assessing the thermal effects induced by electron beam irradiation. COMSOL Multiphysics was employed to study the thermal behaviour of metals and alloys at the sub-microsecond time scale by implementing both experimental power time profiles and semi-empirical electron penetration functions. Three case studies were considered: (a) 17-4 PH steel produced by Binder Jetting, (b) biphasic Al-Si13 alloy, and (c) Magnetron Sputtering Nb films on Ti substrate. The influence on the thermal effects of electron accelerating voltage and number of pulses was investigated, as well as the role of the physicochemical properties of the materials. Full article

Laser annealing plays a significant role in the fabrication of scaled-down semiconductor devices by activating dopant ions and rearranging silicon atoms in ion-implanted silicon wafers, thereby improving material properties. Precise temperature control is crucial in wafer annealing, particularly for repeated processes where repeatability affects uniformity. In this study, we employ a three-dimensional time-dependent thermal simulation model to numerically analyze the multiple static laser annealing processes based on a CO₂ laser with a center wavelength of 9.3 μm and a pulse repetition rate of 10 kHz. The heat transfer equation is solved using a multiphysics coupling approach to accurately simulate the effects of different numbers of CO₂ laser pulses on wafer temperature rise and repeatability. Additionally, a pyrometer is used to collect and convert the surface temperature of the wafer. Radiation intensity is converted to temperature via Planck’s law for real-time monitoring. Post-processing is performed to fit the measured temperature and the actual temperature into a linear relationship, aiding in obtaining the actual temperature under small beam spots. According to the simulation conditions, a wafer annealing device using a CO₂ laser as the light source was independently built for verification, and a stable and uniform annealing effect was realized. Full article

In this study, the integration of microwave-assisted technology into fixed-bed configuration processes is explored aiming to characterize and address its challenges with a customized multimodal microwave cavity. This research focuses on evaluating the uncertainty in contactless temperature measurement methods as spectral thermographic cameras and infrared pyrometers, microwave heating performance, and the thermal homogeneity within fixed beds containing microwave–susceptor materials, including the temperature-dependent dielectric characterization of such materials, having different geometry and size (from 120 to 5000 microns). The thermal inhomogeneities along different bed configurations were quantified, assessing the most appropriate fixed-bed arrangement and size limitation at the employed irradiation frequency (2.45 GHz) to tackle microwave-assisted gas–solid chemical conversions. An increased temperature heterogeneity along the axial profile was found for finer susceptor particles, while the higher microwave susceptibility of coarser grades led to increased temperature gradients, ΔT > 300 °C. Moreover, results evidenced that the temperature measurement on the fixed-bed quartz reactor surface by a punctual infrared pyrometer entails a major error regarding the real temperature on the microwave susceptor surface within the tubular quartz reactor (up to 230% deviation). The experimental findings pave the way to assess the characteristics that microwave susceptors and fixed beds must perform to minimize thermal inhomogeneities and optimize the microwave-assisted coupling with solid–gas-phase reactor design and process upscaling using such multimode cavities. Full article

Hot cracking is a frequent and severe defect that occurs during laser additive manufacturing of superalloys. In this work, a pulsed-wave (PW) laser modulation process was employed to control the solidification microstructure and reduce the hot cracking susceptibility of laser additive manufactured cobalt-based superalloy. The effects of continuous-wave (CW) and PW laser processing modes on the dendrite morphology, element segregation, eutectic phase, and hot cracking of fabricated Co-based superalloys were investigated. Optical microscopy, scanning electron microscopy, and energy-dispersive X-ray spectroscopy were used to characterize the microstructural characteristics of samples. A two-color pyrometer was used to measure the molten pool temperature variation under different laser processing modes. The results show that coarse columnar dendrites, chain-like eutectic carbides, and hot cracks were observed in the CW sample. In contrast, the fine equiaxed crystals, discrete eutectic carbides, and low-level residual stresses were obtained to avoid hot cracks, owing to the high cooling rate and the periodic melting and solidification of the molten pool under the PW laser processing mode. This work provides a new method for controlling solidification structure and hot cracking of laser additive manufactured Co-based superalloy. Full article

During the powder bed fusion of metals using a laser beam (PBF-LB/M), an inert atmosphere is maintained in the build chamber to avoid reactions of the liquid metal with ambient air leading to the creation of oxides or nitrides, which alter the mechanical properties of the processed part. A continuous gas flow is guided over the process zone to remove spatters and fumes. This flow induces a convective heat transfer from the molten metal to the gas, which, depending on the level of the heat flow, may alter the melt pool dimensions by influencing the cooling rate. The present work investigated these phenomena with single-line trials, both experimentally and numerically. For this reason, a smoothed-particle hydrodynamics model was utilized to investigate the temperatures of the melt pool, cooling rates, and the integral heat balance with various gas atmospheres. In parallel, an on-axis pyrometer was set up on an experimental PBF-LB/M machine to capture the surface emissions of the melt pool. The atmosphere in the simulations and experiments was varied between argon, helium, and two mixtures thereof. The results showed a slight increase in the cooling rates with an increasing fraction of helium in the process gas. Consistently, a slight decrease in the melt pool temperatures and dimensions was found. Full article

New systems and methods to access the temperature of the melt pool in welding processes have been developed to study phenomena, monitor behaviours, and even be used in closed-loop control strategies. Concerning arc welding processes, the arc radiation might impose a challenge to measure the temperature. However, heat input is the key point for welding quality. This work aims to evaluate the feasibility and detect potentialities of accessing the thermal field from the rear weld pool in the GTAW process by using in-house developed equipment. The original system was conceptualized based on a previous bichromatic method. Experiments were carried out with and without the wire feed addition, and welding parameters were varied to explore its impacts on the temperature measurement. A strategy to select the regions of interest (ROIs) within the weld pool was created, and the mean temperature was calculated and correlated to the weld bead features. This strategy was able to overcome the challenges imposed by the electrode/nozzle reflection and the arc radiation during the welding. The rear weld pool thermal field was shown to be an important source of data to provide hints of the weld bead features. The mean temperature can indicate geometrical changes in the weld bead. Furthermore, the technique has the potential to be used as a promising real-time process monitoring tool. Full article

The long-term use of steel strip in various industries makes it an important semi-finished product, which makes it necessary to improve its chemical composition and mechanical properties, reduce its thickness and weight, expand the range of new types of steel strip and increase its production. This entails a large number of technological operations dependent on precise temperature measurement and control. In some industrial plants, the steel strip is in continuous motion, which makes the use of contact measuring devices impossible. When using non-contact measuring devices such as pyrometers or thermal imaging cameras, the emissivity of the materials being measured is a problematic parameter, as setting an incorrect emissivity value to the measuring device results in inaccurate temperature readings. The essence of this research was to establish a measurement method and to perform experimental measurements of the emissivity of a polished steel strip used in a continuous annealing line, the subsequent processing of the data from these measurements and their evaluation. The emissivity measurements were carried out for 5 types of steel strip of different parameters, while the measurement itself was carried out in the long wavelength range of 7.5–14 µm and at strip temperatures of 100–300 °C. Depending on the type of steel strip, the mean emissivity values ranged from 0.0835– to 0.1143. The emissivity of the steel strip increased with increasing strip temperature, and it was not a linear dependence. The emissivity values determined in this research could be applied to measuring equipment in actual production, which could improve the accuracy of temperature measurement in the heat treatment of polished steel strip. Thermal camera measurements in the long wavelength range, taking thermal images and their processing and determining the emissivity value of polished steel strips are the parts of this research that make it different from other already published research. Full article

The infrared (IR) satellite remote sensing of sea surface skin temperature (SST_skin) is challenging in the northern high-latitude region, especially in the Arctic because of its extreme environmental conditions, and thus the accuracy of SST_skin retrievals is questionable. Several Saildrone uncrewed surface vehicles were deployed at the Pacific side of the Arctic in 2019, and two of them, SD-1036 and SD-1037, were equipped with a pair of IR pyrometers on the deck, whose measurements have been shown to be useful in the derivation of SST_skin with sufficient accuracy for scientific applications, providing an opportunity to validate satellite SST_skin retrievals. This study aims to assess the accuracy of MODIS-retrieved SST_skin from both Aqua and Terra satellites by comparisons with collocated Saildrone-derived SST_skin data. The mean difference in SST_skin from the SD-1036 and SD-1037 measurements is ~0.4 K, largely resulting from differences in the atmospheric conditions experienced by the two Saildrones. The performance of MODIS on Aqua and Terra in retrieving SST_skin is comparable. Negative brightness temperature (BT) differences between 11 μm and 12 μm channels are identified as being physically based, but are removed from the analyses as they present anomalous conditions for which the atmospheric correction algorithm is not suited. Overall, the MODIS SST_skin retrievals show negative mean biases, −0.234 K for Aqua and −0.295 K for Terra. The variations in the retrieval inaccuracies show an association with diurnal warming events in the upper ocean from long periods of sunlight in the Arctic. Also contributing to inaccuracies in the retrieval is the surface emissivity effect in BT differences characterized by the Emissivity-introduced BT difference (EΔBT) index. This study demonstrates the characteristics of MODIS-retrieved SST_skin in the Arctic, at least at the Pacific side, and underscores that more in situ SST_skin data at high latitudes are needed for further error identification and algorithm development of IR SST_skin. Full article

Machining nickel-based super alloys such as Inconel 718 generates a high thermal load induced via friction and plastic deformation, causing these alloys to be among most difficult-to-cut materials. Localized heat generation occurring in machining induces high temperature gradients. Experimental techniques for determining cutting tool temperature are challenging due to the small dimensions of the heat source and the chips produced, making it difficult to observe the tool–chip interface. Therefore, theoretical analysis of cutting temperatures is crucial for understanding heat generation and temperature distribution during cutting operations. Periodic heating and cooling occurring during cutting and interruption, respectively, are modeled using a hybrid analytical and finite element (FE) transient thermal model. In addition to identifying a transition distance associated with initial period of chip formation (IPCF) from apparent coefficient of friction results using a sigmoid function, the transition temperature is also identified using the thermal model. The model is validated experimentally by measuring the tool–chip interface temperature using a two-color pyrometer at a specific cutting distance. Due to the cyclic behavior in interrupted cutting, where a steady-state condition may or may not be achieved, transient thermal modeling is required in this case. Input parameters required to identify the heat flux for the transient thermal model are obtained experimentally and the definitions of heat-flux-reducing factors along the cutting path are associated with interruptions and the repeating IPCF. The thermal model consists of two main parts: one is related to identifying the heat flux, and the other part involves the determination of the temperature field within the tool using a partial differential equation (PDE) solved numerically via a 2D finite element method. Full article

Having garnered significant attention in the scientific community over the past decade, wire-arc directed energy deposition (arc-DED) technology is at the heart of this investigation into additive manufacturing parameters. Singularly focused on Invar as the selected material, the primary objective revolves around devising a virtual sensor for the indirect size measurement of the bead. This innovative methodology involves the seamless integration of internal signals and sensors, enabling the derivation of crucial measurements sans the requirement for direct physical interaction or conventional measurement methodologies. The internal signals recorded, the comprising voltage, the current, the energy from the welding heat source generator, the wire feed speed from the feeding system, the traverse speed from the machine axes, and the temperature from a pyrometer located in the head were all captured through the control of the machine specially dedicated to the arc-DED process during a phase of optimizing and modeling the bead geometry. Finally, a feedforward neural network (FNN), also known as a multi-layer perceptron (MLP), is designed, with the internal signals serving as the input and the height and width of the bead constituting the output. Remarkably cost-effective, this solution circumvents the need for intricate measurements and significantly contributes to the proper layer-by-layer growth process. Furthermore, a neural network model is implemented with a test loss of 0.144 and a test accuracy of 1.0 in order to predict weld bead geometry based on process parameters, thus offering a promising approach for real-time monitoring and defect detection. Full article