Search Results (152)

To capture the complex metallic spatter and melt pool behavior during the rapid interaction between the laser and metal material, high-speed cameras are applied to record the laser powder bed fusion process and generate a large volume of image data. In this study, four deep learning algorithms are applied: YOLOv5, Fast R-CNN, RetinaNet, and EfficientDet. They are trained by the recorded videos to learn and extract information on spatter and melt pool behavior during the laser powder bed fusion process. The well-trained models achieved high accuracy and low loss, demonstrating strong capability in accurately detecting and tracking spatter and melt pool dynamics. A stability index is proposed and calculated based on the melt pool length change rate. Greater index value reflects a more stable melt pool. We found that more spatters were detected for the unstable melt pool, while fewer spatters were found for the stable melt pool. The spatter’s size can affect its initial ejection speed, and large spatters are ejected slowly while small spatters are ejected rapidly. In addition, more than 58% of detected spatters have their initial ejection angle in the range of 60–120$°$. These findings provide a better understanding of spatter and melt pool dynamics and behavior, uncover the influence of melt pool stability on spatter formation, and demonstrate the correlation between the spatter size and its initial ejection speed. This work will contribute to the extraction of important information from high-speed recorded videos for additive manufacturing to reduce waste, lower cost, enhance part quality, and increase process reliability. Full article

Real-time quality monitoring using molten pool images is a critical focus in researching high-quality, intelligent automated welding. To address interference problems in molten pool images under complex welding scenarios (e.g., reflected laser spots from spatter misclassified as porosity defects) and the limited interpretability of deep learning models, this paper proposes a multi-granularity spatiotemporal representation learning algorithm based on the hybrid enhancement of handcrafted and deep learning features. A MobileNetV2 backbone network integrated with a Temporal Shift Module (TSM) is designed to progressively capture the short-term dynamic features of the molten pool and integrate temporal information across both low-level and high-level features. A multi-granularity attention-based feature aggregation module is developed to select key interference-free frames using cross-frame attention, generate multi-granularity features via grouped pooling, and apply the Convolutional Block Attention Module (CBAM) at each granularity level. Finally, these multi-granularity spatiotemporal features are adaptively fused. Meanwhile, an independent branch utilizes the Histogram of Oriented Gradient (HOG) and Scale-Invariant Feature Transform (SIFT) features to extract long-term spatial structural information from historical edge images, enhancing the model’s interpretability. The proposed method achieves an accuracy of 99.187% on a self-constructed dataset. Additionally, it attains a real-time inference speed of 20.983 ms per sample on a hardware platform equipped with an Intel i9-12900H CPU and an RTX 3060 GPU, thus effectively balancing accuracy, speed, and interpretability. Full article

Multi-laser processing is increasingly adopted in laser powder bed fusion (L-PBF) to improve productivity and enable the fabrication of larger components, but its impact on part quality and performance remains a critical concern. This study investigates the microstructure, tensile properties, and fatigue performance of components fabricated by L-PBF using single- and multiple-laser configurations. Both strategies were evaluated under varying layer thicknesses and gas flow conditions with optimized process parameters. Microstructural analysis revealed defects such as lack-of-fusion, porosity and microcracks in multiple-laser builds with reduced gas flow. However, the density and microhardness results showed negligible differences between single and multiple-laser builds. Tensile testing indicated that single-laser builds exhibited superior strength and ductility, whereas multiple-laser builds demonstrated reduced performance due to localized defects such as lack-of-fusion and microcracks. Low-cycle fatigue testing results showed that optimized multiple-laser strategies could achieve performance comparable to that of single-laser builds while improving productivity. The results also revealed that the gas flow becomes more pronounced with multiple-laser processing, where more spatter is generated due to the interactions of the lasers in a small scan area, and that reduced gas flow leads to fatigue degradation due to increased defect density. The results from this study clearly highlight the importance of gas flow, laser overlap, border optimization, and defect mitigation strategies in producing multiple-laser produced components with mechanical properties and fatigue performance comparable to those of single-laser produced L-PBF components. Full article

In the present study, the coaxial waterjet-assisted nanosecond laser drilling of micro-holes in C_f/SiC composites, coupled with nanosecond laser drilling in air for fabricating micro-holes with high aspect ratios, were investigated. The surface morphology, reaction products, and micro-hole shapes were thoroughly examined. The results reveal that, for the coaxial waterjet-assisted nanosecond laser drilling of micro-holes in the C_f/SiC composite, the increasing of waterjet velocity enhances the material removal rate and micro-hole depth, but reduces the micro-hole diameter and taper angle. The coaxial waterjet isolates the laser-ablated region and cools down the corresponding region rapidly, leading to the formation of a mixture of SiC, SiO₂, and Si on the surface. As the coaxial waterjet velocity increases, the morphology of residual surface products changes from a net-like structure to individual spheres. Coaxial waterjet-assisted nanosecond laser drilling, with a waterjet velocity of 9.61 m/s, achieves micro-holes with a good balance between efficiency and quality. For the fabrication of micro-holes with a high aspect ratio in C_f/SiC composites, micro-holes fabricated by nanosecond laser drilling in air exhibit obvious taper features, which should be ascribed to the combined effects of spattering slag, plasma, and energy dissipation. The application of coaxial waterjet-assisted nanosecond laser drilling on micro-holes fabricated by laser drilling in air effectively expands the hole diameter. The fabricated micro-holes have very small taper angles, with clean wall surfaces and almost no reaction products. This approach, combining nanosecond laser drilling in air followed by coaxial waterjet-assisted nanosecond laser drilling, offers a promising technique for fabricating high-quality micro-holes with high aspect ratios in C_f/SiC composites. Full article

Arc stud welding differs from conventional arc welding techniques and is widely used for joining structural steel, stainless steel, aluminum, and copper alloys in various configurations. Achieving a reliable stud weld requires appropriate welding parameters and a suitable process selection, considering factors such as stud diameter, base material, and surface condition. This study experimentally compares three arc stud welding techniques—arc welding with a ceramic ferrule (ARC CF), arc welding with shielding gas (ARC SG), and arc welding assisted by a radially symmetric magnetic field (ARC SRM)—applied to structural steel (1.0038) and stainless steel (1.4301). Macrostructural analysis, Vickers hardness testing (HV10), visual inspection, non-destructive testing, and bend tests were performed to evaluate weld quality. Results show that ARC CF achieved the highest penetration and hardness but produced more spatter. ARC SG provided moderate penetration but was more prone to cold welds, while ARC SRM resulted in the cleanest collars with minimal spatter but shallower penetration. All welds met ISO 5817:2014 Quality Level C, confirming acceptable structural integrity. These findings support informed selection and optimization of stud welding techniques for diverse engineering applications. Full article

A copper-10 wt.% graphite composite was paired with QCr0.5 to investigate the effects of normal load on current-carrying friction behavior. Arc discharges were monitored using a high-speed camera and photodiodes. The results indicate that, under the given experimental conditions, normal load predominantly influences the tribological performance of the material. As the c normal load increases, the wear rate decreases rapidly at first and then increases gradually. The optimal normal load was found to be 70 N, at which the wear rate reached a minimum of 0.46 mg/m. Material degradation was found to consist of mechanical damage—mainly plowing and plastic deformation—as well as arc-induced erosion characterized by melting and spattering. With increasing normal load, arc erosion decreased progressively, and the overall damage was minimized at 70 N. Arc erosion contributed to surface wear non-uniformity. Moreover, particular attention should be paid to high-current, long-duration arcs, which can pose serious localized threats to material integrity. Full article

Laser-Directed Energy Deposition (LDED) has recently been widely used for 3D-printing metal components and repairing high-value parts. One key performance indicator of the LDED process is represented by melt pool stability and spatter behavior. In this research study, an off-axis vision monitoring system is employed to characterize spatter formation based on different anomalies in the process. This study utilizes a 1 kW fiber laser-based LDED system equipped with a monochrome high-dynamic-range (HDR) vision camera and an SP700 Near-IR/UV Block visible bandpass filter positioned at various locations. To extract meaningful features from the original images, a novel image processing algorithm is developed to quantify spatter counts, orientation, area, and distance from the melt pool under harsh conditions. Additionally, this study analyzes the average number of spatters for different laser power settings, revealing a strong positive correlation. Validation experiments confirm over 93% detection accuracy, underscoring the robustness of the image processing pipeline. Furthermore, spatter detection is employed to assess the impact of spatter formation on deposition continuity. This research study provides a method for detecting spatters, correlating them with LDED process parameters, and predicting deposit quality. Full article

This study investigates the spatter suppression mechanism in aluminum alloy welding using a hybrid fiber–semiconductor laser system. By integrating high-speed photography and three-dimensional thermal-fluid coupling numerical simulations, the spatter formation process and its suppression mechanisms were systematically analyzed. The results indicate that spatter formation is primarily governed by surface tension and recoil pressure. In single fiber laser welding, concentrated laser energy induces a steep temperature gradient on the molten pool surface, triggering a strong Marangoni effect and subsequent spatter generation. In contrast, the hybrid laser system optimizes energy distribution, reducing the temperature gradient and weakening the Marangoni effect, thereby suppressing spatter. Additionally, the hybrid laser stabilizes molten pool flow through uniform recoil pressure distribution, further inhibiting spatter formation. Experimental results demonstrate that the hybrid fiber–semiconductor laser system significantly reduces spatter, improving welding quality and stability. This study provides theoretical and technical support for optimizing aluminum alloy laser welding. Full article

Parts fabricated by laser powder bed fusion (LPBF) contain oxide inclusions, which can be detrimental to fatigue resistance. Under typical LPBF conditions, the atmosphere contains enough oxygen to oxidize reactive elements such as aluminum and titanium, forming oxides in the parts. In this work, mechanisms of oxide formation and oxide alteration were studied by laser-remelting the surfaces of bulk specimens of IN718 and AlSi10Mg, without the addition of metal powder. Calculations based on the mass transfer of oxygen to the melt pool surface indicated that direct oxidation of the melt pool did not play a major role. Rather, both the oxidation of hot spatter and reworking of the pre-existing oxide affected the concentration and morphology of oxides on the metal surface. Full article

Laser vision sensors for weld seam extraction face critical challenges due to arc light and spatter interference in welding environments. This paper presents a real-time weld seam extraction method. The proposed framework enhances robustness through the sequential processing of historical frame data. First, an initial noise-free laser stripe image of the weld seam is acquired prior to arc ignition, from which the laser stripe region and slope characteristics are extracted. Subsequently, during welding, a dynamic region of interest (ROI) is generated for the current frame based on the preceding frame, effectively suppressing spatter and arc interference. Within the ROI, adaptive Otsu thresholding segmentation and morphological filtering are applied to isolate the laser stripe. An optimized RANSAC algorithm, incorporating slope constraints derived from historical frames, is then employed to achieve robust laser stripe fitting. The geometric center coordinates of the weld seam are derived through the rigorous analysis of the optimized laser stripe profile. Experimental results from various types of weld seam extraction validated the accuracy and real-time performance of the proposed method. Full article

Conditions in dental offices are conducive to Legionella pneumophila infections. This is mainly related to the use of a dental unit in the daily clinical work, which is the basic equipment of the office. Water discharged from the dental unit waterlines (DUWLs) and the working tips of the dental unit generates splatter/spatter and bioaerosol, constituting the main sources of potential infection and posing a health threat to both patients and professional dental staff. This article presents a narrative review on the presence and risk associated with Legionella spp., particularly the species L. pneumophila, in the dental office. This paper summarizes current knowledge and offers readers practical references, especially useful in everyday clinical dental practice. Full article

Spatters in the powder-based metal additive manufacturing processes influence deposition quality, part surface quality, and internal defects. We developed a novel video analysis method to monitor and count the melted spatter particles of biomedical-grade Co-Cr-Mo-4Ti powder particles in depositing layers using a micro-plasma transferred arc additive manufacturing (M-PTAAM) process. We captured the spatters using a weld-monitoring camera and building datasets of videos and monitored different combinations of M-PTAAM process parameters. We captured videos of the melted spatter particles and counted the melted spatter particles in real time using a Kalman filter. The weld-monitoring camera captured the melted spatter particles and the fumes generated by the evaporated spatter particles. The video processing algorithm was developed in this study to accurately capture melted spatter particles. In images without fumes, nearly all melted spatter particles were successfully detected. Even in images with the presence of fumes, the algorithm maintained a detection accuracy of 90%. The real-time melted spatter count particle exhibited a powder feed rate changing from 30 to 35 g/min and then to 50 g/min. The melted spatter particle count was lowest at a powder feed rate of 30 g/min and increased with the increasing powder feed rate. Full article

In this study, through RH water model simulation experiments, the effects of precipitation bubbles on the two-phase flow pattern, liquid steel flow behavior, and flow characteristics in an RH reactor during the whole decarburization process were comparatively investigated and analyzed by using quasi-counts that reflected the similarity of the precipitation bubble phenomenon. The experimental results show that an increase in precipitation bubbles is positively related to an increase in circulating flow rate, a reduction in mixing time, and an increase in gas content and negatively related to the residence time of liquid steel in the vacuum chamber. The two-phase flow pattern of the rising tube under the influence of precipitation bubbles includes bubble flow, slug flow, mixing flow, and churn flow. Under the influence of precipitation bubbles, the liquid surface spattering inside the vacuum chamber is reduced, the fluctuation amplitude is reduced, the efficiency of liquid steel processing is improved, it is not easy for cold steel to form, and the fluctuation frequency is increased, which is conducive to increasing the surface area of the vacuum chamber; the bubbles’ rising, aggregating, and crushing behavior increases the stirring effect inside the vacuum chamber, which is conducive to improving the decarburization and mass transfer rate. Under the influence of the precipitated bubbles, the concentration gradient between the ladle and the vacuum chamber is increased, which accelerates the mixing speed of the liquid steel in the ladle, and the volume of the dead zone is reduced by 50%. The lifting gas flow rate can be appropriately reduced in the plant. Full article

Real-time detection of welding defects in resistance spot welding is a complex challenge. Dynamic resistance (DR) reflects nugget growth and varies with defect types, serving as a key indicator. This study presents an online quality evaluation and defect classification method for Q235 low-carbon steel welding. Welding current and voltage were collected in real-time, and DR signals were processed employing a second-order Butterworth low-pass filter featuring zero-phase processing to enhance accuracy. Empirical mode decomposition (EMD) decomposed these signals into intrinsic mode functions (IMFs) and residuals, which were classified by a support vector machine (SVM). Experiments showed the EMD-SVM method outperforms traditional approaches, including backpropagation (BP) neural networks, SVM, wavelet packet decomposition (WPD)-BP, WPD-SVM, and EMD-BP, in identifying four welding states: normal, spatter, false, and edge welding. This method provides an efficient, robust solution for online defect detection in resistance spot welding. Full article

Rainfall infiltration and groundwater fluctuations induced by cyclonic rainfall are the main causes of slope failure. Slope stability monitoring is key to preventing and controlling rock slope failure. Aiming at the monitoring theory and technical problems of dam slope failure under a cyclonic rainfall environment, this study carried out a physical model test and numerical simulation on the stability monitoring of the weathering transition zone in rock slopes. The results show that: (1) Under cyclonic rainfall, the increased permeability, the expansion of the rock fracture network, and the decrease of effective stress are the main causes of increased lateral deformation of the slope. (2) Physical model test results showed that rain spatter erosion and runoff erosion could lead to rapid loss of anchor bolt preload. In the hydraulic fluctuation stage, the anchor bolt axial force decreased first, then increased, and finally tended to be stable. The unloading response of the Intelligent Terminal Structure was significant during rock block sliding. In the numerical simulation, the anchor bolt axial force increased continuously with the increase of lateral displacement of slope. (3) By analyzing the evolution of anchor bolt axial force and pore water pressure in the weathering transition zone, a monitoring criterion for the stability of the weathering transition zone of rock slopes based on the Logistic function was proposed. Full article