Spatter Characteristics Research Articles

A novel multi-loss dynamic fusion-enhanced image segmentation model for welding spatter measurement

Quantitative detection of welding spatter is not only critical for evaluating and optimizing welding energy consumption, but also significant for improving welding quality. Inspired by the welder's visual estimation of the amount of spatter, a novel welding spatter measurement method based on image segmentation is proposed. Considering the challenges of welding spatter such as small object, aggregation, and unclear boundary, four loss functions, namely, Focal loss, Dice loss, Boundary loss, and Count loss, are designed to achieve global optimization for complex welding spatter. Furthermore, for the different spatter characteristics with different optimization difficulties, a multi-loss dynamic fusion method with differential optimization capability is designed. Finally, a welding spatter segmentation dataset is established and a comprehensive ablation and comparison test of the proposed methodology is carried out. The results indicate that the proposed method has an average F1-score metric of 83.52 % and a mean intersection over union metric of 75.11 %. These findings suggest the potential for vision-based quantitative estimation of welding spatter.

Real-time tracking method for motion spatter in high-power laser welding of stainless steel plate based on a lightweight deep learning model

The high-power laser welding of stainless steel is prone to spatter defects. The dynamic behavior of motion spatter is closely related to the welding state, but the relevant features are difficult to obtain. This paper extensively describes a motion spatter tracking method based on a lightweight deep learning model and a multi-target tracking algorithm. Firstly, an in-situ observation platform with a high-speed camera-based high spatiotemporal resolution for motion spatters is established. This platform can record the generation and motion process of different spatters during welding. To reduce the interferences and highlight the spatter characteristics, a linear point operation-based image low-brightness metal vapor plume removal method is also proposed. Then, a deep learning-based lightweight spatter detection model is established, and an automatic spatter label generation method is proposed to quickly obtain a sufficient amount of highly discriminative training data to train the established model comprehensively. Compared with the basic model, the validation results show that the lightweight spatter detection model runs 5.11 times faster, with a spatter detection accuracy of 96.71%. Finally, a motion spatter tracking method based on the DeepSORT algorithm is proposed to distinguish different spatters and associate the same spatters. The spatter size, velocity, quantity, and other features are also able to be accurately extracted via this method, achieving spatter defect monitoring. In summary, this study describes a novel and robust method for motion spatter real-time tracking during laser welding and this method can provide reliable data support for accurate and fast process condition monitoring as well as weld quality assessment.

Quantitative analysis of spatter formation in Laser Powder Bed Fusion: unraveling the impact of beam shaping and multi-beam processing

In the realm of laser-based powder bed fusion processes with metals (PBF-LB/M), spatter formation serves as a crucial stability criterion. However, existing analyses often adopt a qualitative approach, hindering meaningful comparisons between processes. The quantitative investigation of the advantages of beams with non-Gaussian intensity distribution as well as multi-beam processing strategies with regard to spatter formation is still largely unexplored. To address this gap, we present an experimental setup utilizing high-speed videography and individual particle tracking to measure spatter characteristics, count size, ejection angle, and velocity, within the PBF-LB/M process conditions. The investigation deals with focused and defocused Gaussian beams, a beam with ring-shaped intensity as well as processing with two coupled Gaussian beams for the PBF-LB/M of nickel-base alloy 625.

Laser powder bed fusion spatters of Zr-Cu-Al-Nb metallic glass

Understanding the morphology, composition and structural changes experienced by metallic glass powder particles upon laser powder bed fusion (LPBF) is the first step towards evaluating the impact of spatter generation on part quality and on feedstock degradation. This study presents the characterization of Zr-Cu-Al-Nb spatter particles by means of scanning and transmission electron microscopy with automated crystallographic orientation mapping and energy dispersive spectroscopy, and X-ray photoelectron spectroscopy. The powder exposed to the LPBF environment exhibits an average surface composition similar to the original feedstock, but with a rougher morphology. The typical spatter encountered in the remaining lack-of-fusion is a vapour-entrained particle, which probably underwent partial melting leading to the formation of α-Zr(O) dendrites, and “big-cube” Cu2Zr4O nanocrystals in its heat affected zone. In the present work, spatter characteristics are discussed considering glass properties and their connection to lack-of-fusion defects is addressed.

Influence of ring-shaped beam profiles on spatter characteristics in laser-based powder bed fusion of metals

Despite the maturity of laser-based powder bed fusion of metals (PBF-LB/M), some barriers prevent the manufacturing process from fully being established in the industry. One drawback is spatter formation, which is disadvantageous to PBF-LB/M for three main reasons. First, adhering spatter can initiate coater collision, resulting in process failure. Second, large adhering spatter may cause lack-of-fusion defects as they require more energy to remelt sufficiently compared to unprocessed powder. Furthermore, big nonadhering spatter cannot be recycled as powder. The recycling of small spatter particles potentially results in degraded material properties. Ring-shaped beam profiles have been established for deep penetration welding to reduce spatter formation. Investigations on ring-shaped beam profiles in PBF-LB/M focus on improving productivity and process robustness. Qualitative spatter reduction in PBF-LB/M using ring-shaped beam profiles has also been reported. This publication quantitatively examines the influence of ring-shaped beam profiles on spatter formation in PBF-LB/M. Image processing algorithms of on-axis high-speed images are utilized for spatter detection and tracking. A self-developed spatter segmentation is used to determine the spatter size. A Laplacian of Gaussian filter is combined with a Kalman tracker to count and track the spatter. The results show that spatter formation is highly influenced by the beam profile and the chosen process parameters. Considering the melt track width, ring-shaped beam profiles could reduce the number of spatter per fused area. High numbers of spatter are generated when parameter sets result in balling. Moreover, spatter velocity is primarily dependent on the introduced dimensionless enthalpy.

Effect of layer thickness on spatter properties during laser powder bed fusion of Ti–6Al–4V

ABSTRACT High layer thicknesses for laser powder bed fusion are promising for productivity increase. However, these are associated with increased process instability, spatter generation and powder degradation, crucial for alloys sensitive to oxygen. The effect of increasing layer thickness from 30 to 60 µm is studied focusing on Ti-6Al-4V spatter formation during LPBF and its characterisation, with scanning and transmission electron microscopy, combustion analysis and X-ray photoelectron spectroscopy. Results indicate that spatters are covered with a uniform Ti-Al-based oxide layer and Al-rich oxide particulates, the thickness of which is about twice that present on virgin powder. The oxygen content was about 60% higher in spatters compared to the virgin powder. The study highlights that increasing the layer thickness to 60 µm permits to reduce the total generation of spatters by ∼40%, while maintaining similar spatter characteristics and static tensile properties. Hence, this allows to increase build rate without compromising process robustness. Highlights Increased layer thickness from 30 to 60 µm resulted in ∼40% lower amount of spatter generated per build Increased layer thickness from 30 to 60 µm resulted in ∼17% higher amount of generated spatter per scanned layer Increase in bulk oxygen content by >60% was registered for spatter compared to the virgin powder in both cases The oxide layer is about twice thicker on the spatter particles compared to virgin powder

Tracking and quantifying spatter characteristics in a laser directed energy deposition process using Kalman filter

Laser-based directed energy deposition (L-DED) has emerged as one of the most promising additive manufacturing (AM) technologies in the past decade. This is particularly due to its ability to print functionally graded materials and achieve a higher deposition rate compared to its counterparts. For L-DED, the flow dynamics of the powder particles and laser-material interactions are the chief determinants of the build quality. In particular, we are interested in the characterization of spatter, which is the ejection of the molten material from the deposition zone that includes the melt pool and the area where the laser interacts with the incident powder particles. Spatters are detrimental to the overall build quality as they can increase porosity and lead to irregular surface morphology. While recent studies have investigated the spatter formation, very little attention has been given to its quantitative in situ characterization. To this end, we develop a high-speed imaging capability integrated with an L-DED process to record the trajectory of the spatter particles as they eject out from the deposition zone. We use a Kalman filter to track the trajectory of the individual spatter particles in real-time. By using the trajectory information and apriori knowledge of the material properties, we estimate the percentage of the material lost as spatter. Our results indicate that at a laser power of 300 W and a feed rate of 7.41 mm/sec, only an estimated 11% of the powder material (released from the nozzles) interacts with the laser beam. Out of this, approximately 12% of the material is ejected out as spatter. This shows that a significant portion of the material is wasted during the L-DED process.

Investigation of Spatter Characteristics in Selective Laser Melting Based on Maximum Entropy Threshold Segmentation Algorithm

Investigation of Spatter Characteristics in Selective Laser Melting Based on Maximum Entropy Threshold Segmentation Algorithm

Deep Learning Based Monitoring of Spatter Behavior by the Acoustic Signal in Selective Laser Melting.

As one of the most promising metal additive manufacturing (AM) technologies, the selective laser melting (SLM) process has high expectations ofr its use in aerospace, medical, and other fields. However, various defects such as spatter, crack, and porosity seriously hinder the applications of the SLM process. In situ monitoring is a vital technique to detect the defects in advance, which is expected to reduce the defects. This work proposed a method that combined acoustic signals with a deep learning algorithm to monitor the spatter behaviors. The acoustic signals were recorded by a microphone and the spatter information was collected by a coaxial high-speed camera simultaneously. The signals were divided into two types according to the number and intensity of spatter during the SLM process with different combinations of processing parameters. Deep learning models, one-dimensional Convolutional Neural Network (1D-CNN), two-dimensional Convolutional Neural Network (2D-CNN), Recurrent Neural Network (RNN), Long Short Term Memory (LSTM), and Gated Recurrent Unit (GRU) were trained to establish the relationships between the acoustic signals and characteristics of spatter. After K-fold verification, the highest classification confidence of models is 85.08%. This work demonstrates that it is feasible to use acoustic signals in monitoring the spatter defect during the SLM process. It is possible to use cheap and simple microphones instead of expensive and complicated high-speed cameras for monitoring spatter behaviors.

Spatter Characteristics of High-Power Fibre Laser Deep Penetration Welding and Effect of Defocus on Spatter

Spatter Characteristics of High-Power Fibre Laser Deep Penetration Welding and Effect of Defocus on Spatter

In-situ monitoring and detection of spatter agglomeration and delamination during laser-based powder bed fusion of Invar 36

Invar 36 (FeNi36) is a weldable nickel alloy, known for its low thermal expansion properties, that contains 36% of nickel and 64% iron. The laser-based powder bed fusion process is often associated with defects and flaws that should be controlled for production quality. Spatter formation and delamination are two phenomena that could be observed in thermal images taken during the laser melting process. This paper presents an in-situ monitoring setup for detecting spatters and delamination of Invar 36. The size, shape, count, and cooling rate of spatter particles are evaluated using a combination of infrared pyrometer and high-speed infrared thermography. Thermograms of Invar 36 are processed to determine the spatter characteristics. The influence of processing conditions on the spatter count, spatter size, and size of melt track is discussed. The effect of spatters on the surface morphology of Invar 36 parts is also investigated. The processing conditions that cause melt pool instabilities, excessive spattering, and delamination are presented. This paper concludes recommendations for avoiding delamination and excessive spatter formation during the laser-based powder bed fusion of Invar 36.

Characteristics of Spatter in Micro-Drilling of Metal Sheet by Pulsed Nd:YAG Laser

In laser cutting and drilling process, molten material was scattered as spatter, which deteriorates the surface integrity of a workpiece because of the thermal damage. It is expected that the control of assist gas flow can reduce the adhesion of spatter. In order to investigate the improvement method of thermal damage due to the adhesion of spatter, it is required to clarify characteristics of spatter. Therefore, a method was developed to collect and analyze spatter based on the use of high-speed video cameras in the laser micro-drilling process, and the characteristics of spatter movement were numerically investigated by CFD analysis. The scattering velocity and angle of the spatter were investigated by recognizing and tracking spatter with the high-speed video observation. The movement of spatter was observed by using two high-speed video cameras, and analyzed by using a two-direction tracking method, in which the 3D tracking lines of spatter particles were reconstructed in the forward and backward frames, and the actual trajectory of individual spatter particle was obtained by averaging those tracking lines. These measurements revealed that the initial velocity of spatter was mainly distributed from 52 m/s to 200 m/s with an average velocity of 129 m/s. The initial angle of spatter was mainly distributed between 0 and 30 degrees from the workpiece surface in the upward direction. There was little correlation between the initial velocity and angle of spatter. The diameter of spatter was mainly distributed from 1μm to 4μm with an average diameter of 3.7μm. It is important to use the processing conditions achieving the smaller spatter diameter in order to reduce the thermal damage caused by spatter. Although coaxial assist gas flow has an influence on the spatter behavior, that time period is very short. Therefore, it is important to control the spatter behavior outside of the coaxial assist gas flow by using an additional gas flow to prevent the thermal damage to the workpiece surface.

Elucidation of Metallic Plume and Spatter Characteristics Based on SVM During High-Power Disk Laser Welding

During deep penetration laser welding, there exist plume (weak plasma) and spatters, which are the results of weld material ejection due to strong laser heating. The characteristics of plume and spatters are related to welding stability and quality. Characteristics of metallic plume and spatters were investigated during high-power disk laser bead-on-plate welding of Type 304 austenitic stainless steel plates at a continuous wave laser power of 10 kW. An ultraviolet and visible sensitive high-speed camera was used to capture the metallic plume and spatter images. Plume area, laser beam path through the plume, swing angle, distance between laser beam focus and plume image centroid, abscissa of plume centroid and spatter numbers are defined as eigenvalues, and the weld bead width was used as a characteristic parameter that reflected welding stability. Welding status was distinguished by SVM (support vector machine) after data normalization and characteristic analysis. Also, PCA (principal components analysis) feature extraction was used to reduce the dimensions of feature space, and PSO (particle swarm optimization) was used to optimize the parameters of SVM. Finally a classification model based on SVM was established to estimate the weld bead width and welding stability. Experimental results show that the established algorithm based on SVM could effectively distinguish the variation of weld bead width, thus providing an experimental example of monitoring high-power disk laser welding quality.

Analysis of high-power disk laser welding stability based on classification of plume and spatter characteristics

Classification of plume and spatter images was studied to evaluate the welding stability. A high-speed camera was used to capture the instantaneous images of plume and spatters during high power disk laser welding. Characteristic parameters such as the area and number of spatters, the average grayscale of a spatter image, the entropy of a spatter grayscale image, the coordinate ratio of the plume centroid and the welding point, the polar coordinates of the plume centroid were defined and extracted. Karhunen-Loeve transform method was used to change the seven characteristics into three primary characteristics to reduce the dimensions. Also, K-nearest neighbor method was used to classify the plume and spatter images into two categories such as good and poor welding quality. The results show that plume and spatter have a close relationship with the welding stability, and two categories could be recognized effectively using K-nearest neighbor method based on Karhunen-Loeve transform.

Study on Metal Transfer and Welding Spatter Characteristics of Basic Flux Cored Wire

The metal transfer behaviors of basic flux cored wire at different arc voltage and welding current and the resultant welding spatter were investigated by using a high speed camera. Two modes of metal transfer are found: globular repelled transfer (lower welding parameters) and small droplet transfer (higher welding parameters). The former is accompanied by large granular spatter, large droplet itself explosion spatter and electric explosive spatter of short-circuit, and spatter in the latter is reduced obviously. But if the slag column is found in the two models, spatter could be dropped evidently owing to its significant guiding role for metal transfer. Therefore the slag column is the key factor of reducing welding spatter.

A010 Fundamental Characteristics of Spatter in Micro-drilling of Metal Sheet by Pulsed Nd:YAG Laser

A010 Fundamental Characteristics of Spatter in Micro-drilling of Metal Sheet by Pulsed Nd:YAG Laser

Spatter Formation in Laser Welding with Beam Oscillation

The investigation presented in this paper aims on a quantitative analysis of spatter formation in laser beam welding with superposed beam oscillation. After a discussion of design space limitations, which result from the scanner dynamics and theoretical considerations on the welding process itself, an optimal experimental design is created. By the use of high speed camera imaging, spatters were captured during statistically designed welding experiments and correlations between the number of spatters and the welding parameters have been derived. To evaluate the spatter characteristics in the high speed videos, a state space approach was applied, which is based on automated image data processing.

Analysis of characteristics of spatters during high-power disk laser welding

Real-time monitoring and control of welding process is important for laser welding quality. Therefore, the variation rule of sensing characteristics of welding process and their relations to weld quality should be known. Spatter is one of the most important phenomena in high-power laser welding process. The characteristics of spatters are related to the quality and stability of welding and the utilization of the laser power. An approach to analyze the characteristics of spatters is investigated during high-power disk laser bead-on-plate welding of Type 304 austenitic stainless steel plates at a continuous wave laser power of 10 kW. An ultraviolet and visible sensitive high-speed video camera is used to capture the dynamic images of the laser welding spatters. The number, area, and ejecting distance of spatters and the centroid height of spatter images are calculated as the characteristic parameters of spatters by using the image processing technology. The weld bead width is considered as a parameter reflecting the quality and stability of welding process. The linear and the higher order polynomial curve fitting for the data of the characteristic parameters are used to study the variation rule of the characteristic parameters of spatters. In comparison of the fluctuation of the weld bead width, the correlation between the spatter characteristics and the quality and stability of welding is studied. The experimental results of actual laser welding show that the quality and stability of a high-power disk laser welding of Type 304 austenitic stainless steel plates could be monitored and estimated by analyzing the characteristic parameters of spatters, which is the foundation for monitoring and control of welding quality in real time.

Study on metal transfer modes and welding spatter characteristics of self-shielded flux cored wire

The metal transfer behaviour of self-shielded flux cored wire and the resultant welding spatter were investigated by using a high speed camera. Three modes of metal transfer were found, i.e. bridging transfer without arc interruption in explosive form or by surface tension, globular repelled transfer and droplet transfer, while the former two modes played a key role in the weld metal transfer. Correspondingly, the bridge explosion, discontinuous globular repelled process and the misalignment of droplets transfer were the main factors causing the welding spatter.

The influence of assist gas on the mechanism of material ejection and removal during laser percussion drilling

This paper elucidates the effects of different gases on the dominant mechanisms of the material ejection and removal and the cooling rate during laser percussion drilling. In particular, work was conducted for the reactive O2 and inert Ar assist gases, in terms of their effects on (a) the behaviour and characteristics of spatter, (b) the recast layer characteristics and (c) the material ejection spark distribution for the drilling of Nimonic 263 alloy sheets using a Nd-doped yttrium aluminium garnet laser. It was shown that using O2 assist gas, the material ejection was characterized with increased liquid particle ejection, coupled with volatile burning, possibly similar to that of nucleation-induced explosions, while the employment of Ar assist gas influenced the material ejection to be dominated by bulk radial liquid ejection.