Typical Welding Research Articles

DETERMINATION OF OPTIMAL CONDITIONS FOR HERMETIC WELDING OF THIN FOILS WHEN USED IN MEMBRANE-TYPE STRUCTURES

Purpose. Development of optimal technology for welding thin-walled shells mode of 12Х18Н10Т steel (δ=0.15 mm), working at alternating loads. Research methods. Research methods. For welding automatic argon-arc welding (AAAW) equipment was used for of orbital welding, which includes a MW 2600 current source (FRONIUS) with software control unit and welding head of closed type MW40. Research warks showed that this type of welding is not enough for such small thicknesses concentration of the welding arc, which does not allow stable forming of the bath and obtaining solid uniform seam. A special robotic complex was used for microplasma welding STARWELD 190H, which includes: a power source for the regular arc INV 50; source main arc power supply INV 190; SIEMENS Simatic S 7-300 control unit; robot CR3-535M (MITSUBISHI); manipulator and HPH 80 plasmatron. Welding quality control was carried out by visual inspection and metallographic examination. Taking into account the conditions of operation of the parts, according to the technical conditions of the drawing, it was also provided pneumohydraulic control method. Obtained results. Visual inspection the outer surface of the welds showed the absence of defects in the form of pores, cracks, shells, no fusions, undercuts, etc. The geometric dimensions of the weld met the requirements of the standard documentation valid at the enterprise. Metallographic studies of the boxes membranes, welded by microplasma welding, gave a positive result. Defects of metallurgical character were not found in the welds. Practical value. The optimal method of welding that can be applied is determined for the manufacture of thin-walled membrane structures, from the point of view of manufacturability and economy expediency It has been established that microplasma welding allows obtaining a hermetically tight seam, when the thickness of parts to be welded is about 0.15 mm. The performance of welded membrane boxes is confirmed in the barostatic valve of an aircraft engine. It is established that micro plasma welding can be used in the manufacture of thin-walled shells made of 12X18H10T steel (δ=0.15 mm), which work at variable loads. The technological process of welding is introduced into the series production.

Analysis Welding Types Pipe Fabrication Process in Missile Fast Attack Boat Construction

The equipment in the piping system consists of pipes, valves, flanges, filters, fittings, pumps, and others. The installation schedule for this piping system begins after the connection between blocks. Pipes as part of a ship's system have several steps in their installation procedure, one of which is welding. Welding on pipes is carried out by professional welders who have met more complex competency requirements than welders in general, such as flat position welders, vertical welders, or overhead welders. The purpose of this study was to determine the welding process and types of welding in pipe fabrication for the construction of the Missile Fast Attack Boat. Result comparison between the diameters of the welded pipes, the greater the value of the welding volume formed. The largest volume is 426 mm3, with a pipe length for the fabrication process of 4,3 m. On the other hand, the shortest fabrication is for welding pipes with a diameter of 2,5 m, which has a volume of 127 mm3. While the welding process using GTAW / Gas Tungsten Arc Welding (TIG) is very appropriate for welding in small areas and thin pipes. The TIG welding process has an average volume of below 150 mm3.

A Case Study on the Possibility of Extending the Service Life of the Demining Machine Belt.

The operational practice of the design of the Bozena 5 demining machine has shown that its belts are the critical component that fundamentally affects the functionality of the entire machine. This article is a practical continuation and extension of the previous research results from the point of view of materials (research of the uniaxial fatigue life in bending and torsion), calculation (creation of the necessary mathematical, analytical and numerical models for the research) and construction (i.e., patented design of the belt tensioning of this machine). All these actions are aimed at a single objective-to achieve a condition that guarantees a sufficient service life without malfunctions, since repairing these machines in the field is often impossible. Therefore, this study examined the fatigue life of welded joints (uniaxial bending and torsion) of S960 QL and S500MC steels welded by MAG technology. Subsequently, the data were compared with previous results (electron and laser welds) and the influence of each type of weld on the fatigue life relative to the base material was discussed. It was found that conventional MAG technology had a more significant negative impact on the fatigue life of the base material than non-conventional technologies. This trend was particularly true for the bending stress. At the same time, the bending stress was identified by the FEM analysis as the dominant load on the belt. The maximum stress in the belt link under the considered boundary conditions was approximately 240 MPa (in bending). This stress corresponded to the continuous fatigue life (more than 107 cycles) for both base materials tested (S960QL, S500MC). In the whole studied spectrum of controlled deformation amplitudes (Manson-Coffin), the life of MAG welds was lower in comparison with the base material and with welds made by unconventional technologies. All the activities carried out so far (research on microstructure, hardness, strength, residual stresses, tribological properties and fatigue life) have shown that the original belt design (S500MC) using MAG technology has significant deficiencies in the state of optimal life. It is expected that the proposed material change (use of S960QL instead of S500MC) and work with advanced technologies will bring this state significantly closer.

Research on a Feature Point Detection Algorithm for Weld Images Based on Deep Learning

Laser vision seam tracking enhances robotic welding by enabling external information acquisition, thus improving the overall intelligence of the welding process. However, camera images captured during welding often suffer from distortion due to strong noises, including arcs, splashes, and smoke, which adversely affect the accuracy and robustness of feature point detection. To mitigate these issues, we propose a feature point extraction algorithm tailored for weld images, utilizing an improved Deeplabv3+ semantic segmentation network combined with EfficientDet. By replacing Deeplabv3+’s backbone with MobileNetV2, we enhance prediction efficiency. The DenseASPP structure and attention mechanism are implemented to focus on laser stripe edge extraction, resulting in cleaner laser stripe images and minimizing noise interference. Subsequently, EfficientDet extracts feature point positions from these cleaned images. Experimental results demonstrate that, across four typical weld types, the average feature point extraction error is maintained below 1 pixel, with over 99% of errors falling below 3 pixels, indicating both high detection accuracy and reliability.

Predictive modeling for coiled tubing fatigue using advanced machine learning techniques

Coiled tubing CT plays Pivotal role in oil and gas well intervention operations due to its advantages such as flexibility, fast mobilization, safe, low cost and wide range of applications, including: well intervention, cleaning, stimulation, fluid displacement, cementing, and drilling. However, CT is subject of fatigue and mechanical damage caused by repeated bending cycles, internal pressure and environmental factors which can lead to a premature failure, high operational cost and production downtime. With the development of CT proprieties and application traditional fatigue life prediction methods based on analytical models integrated in tracking process showed in some cases an underestimate or overestimate of the actual fatigue life of CT particularly when complex factor like welding type, corrosive environment, and high-pressure variation are involved. This study addresses this limitation by introducing a comprehensive machine learning-based approach to improve the accuracy of CT fatigue life prediction, using a data set derived from over 350 tests both lab scale and full-scale fatigue test. The study has incorporated the impact of different parameters such as CT, grades, wall, thickness, CT diameter, internal pressure and welding types. By using advanced machine learning techniques such as artificial network (ANN), Gradient boosting regressor we got a more precise estimation of the number of cycles to failure than traditional models. The results of this study shown the importance of integration of machine learning for CT fatigue life analysis and demonstrating its capacity to enhance the prediction accuracy and reduce the uncertainty. A detailed machine Learning models is presented, emphasizing their capability to handle complex data and improve prediction under diverse operational conditions. This study contributes to more reliable, CT management and safer more cost-efficient well intervention operations.

Laser powder bed fusion of pure copper using ring-shaped beam profiles

Additive manufacturing of copper using laser powder bed fusion (PBF-LB/M) enables the production of highly complex components. However, processing of copper by means of near-infrared laser radiation is challenging due to its absorptivity of only 5%–20%. Using a keyhole welding process with a Gaussian intensity distribution increases the absorptivity up to 53% due to multireflection. This enables the production of components with a density larger than 99.5% and electrical conductivity larger than 90% of the International Annealed Copper Standard (IACS), but this type of welding leads to keyhole porosity due to keyhole instabilities. One way of counteracting is the use of a heat conduction welding process. However, due to the Gaussian intensity distribution, it is not possible to supply sufficient energy to eliminate lack-of-fusion porosity and concurrently avoid the formation of a keyhole. Ring-shaped beam profiles have proven their advantages in stabilizing the PBF-LB/M process with a tendency toward higher laser power, but pure copper has not yet been processed in this way. Therefore, this study investigates the potential of three ring-shaped beam profiles to produce specimens with a density of more than 99.5% and their respective electrical conductivity using a laser power of up to 1300 W. In order to understand the underlying welding process, the weld geometry of single-tracks is analyzed. Specimens with a density of up to 99.77% and an electrical conductivity of up to 101.62% IACS are produced, whereby the material properties and welding regime depend on the selected ring-shaped beam profile.

Awareness of ocular hazards among welders in Bindura, Zimbabwe

Occupational health issues are the highest among workers in developing nations. This study aimed to assess the awareness of ocular hazards among welders in Bindura. An observational cross-sectional design with a validated structured self-administered questionnaire was used to assess the awareness of ocular hazards among 400 welders. Among the 400 welders, 397(99.3%) were males and their ages ranged from 19 – 56 with a mean age of 36 ± 8 years. Most (35%) of them, 140 had been involved in welding for 6-10 years. The most common type of welding among the participants was arc welding (87.8%). Majority (99.3%) of the welders were aware that welding without the use of protective equipment is a potential source of ocular hazards. Many welders had access to protective face shields and used them all the time (84.5%). The most common condition was ocular foreign bodies (17.7%), followed by Arc eye (4.8%). Awareness about welding as a source of ocular hazard depends on the type of welding used (p < 0.05). The awareness of ocular hazards among welders in Bindura is high. Although, protective devices are provided, regular utilization needs to be encouraged and enforced.

ASTM International Subcommittee E07.02 on Reference Radiological Images: A brief history and update of recent work

Radiographic interpretation is a combination of art and science. The radiograph interpreter must be well versed in x-ray physics, conditions of the exposure, characteristics of the source and image detector, the design of the part, its specifications, and potential flaws. But there is also an art to interpretation that is gained over years of looking at many radiographs taken in many different conditions. As an aid to interpretation, reference radiographs have been developed and well accepted as means of identifying different types of indications and grading those indications for accept/reject decisions. Industrial radiography began in 1922 under the direction of HH Lester at the US Army Watertown Arsenal. The first radiography standards and reference radiographs appeared in the 1930s. ASTM International Committee E07 on Nondestructive Testing was formed out of Committee E04 on Metallography X-ray Methods subcommittee in 1938 when ASTM was the American Society for Testing Materials. An ASTM Subcommittee on Reference Radiographs was formed in 1950 and immediately adopted some of these first reference films as consensus standards. Since those first reference radiograph standards ASTM has developed both film and digital radiograph standards for 11 types of castings and 3 types of welds, several radiographic parameter demonstration films, a standard film for measuring film digitization performance, and films for evaluating visual acuity of radiograph interpreters. This paper discusses the history of reference films and the recent development of digital reference images, film digitizer performance film, and the visual acuity standard. The just-approved ASTM E3168 Standard Practice for Determining Low-Contrast Visual Acuity of Radiographic Interpreters is the first standard containing actual radiographic images of varying sharpness, contrast, and noise that can be used to evaluate interpreters and/or interpretation environments. This paper documents the initial statistical study performed on the visual acuity standard films.

Evaluation decision on green degree combination of typical welding processes for large-diameter thick plates

Abstract Aiming at the environmental impact of large-diameter thick plate manufacturing scenarios in the welding process, a comprehensive evaluation method combining AHP and TOPSIS is proposed to analyze and make decisions on the green welding process suitable for large-diameter thick plates. The optimal green welding process evaluation and decision-making index system for large-diameter thick plates is constructed. The system can be flexibly applied to different large-diameter plate welding scenarios by focusing on different optimization objectives, providing welders with a more suitable green welding process. The constructed model is applied to the seashore factory welding scenarios and general welding scenarios for comparative decision-making, and the effectiveness and feasibility of the proposed comprehensive decision-making evaluation method are verified by the actual data calculation results.

A wall climbing robot based on machine vision for automatic welding seam inspection

With the ongoing progress of industrial technology such as shipbuilding, the importance of weld quality in industrial production is becoming increasingly prominent. Intelligent and automated welding seam inspection robots are more efficient than traditional manual inspection and can avoid dangerous accidents. This article describes the design of a welding seam inspection robot suitable for high-altitude ship operation. The robot uses machine vision and object segmentation models to automatically detect the position of welding seams, and uses a cubic polynomial to fit the welding seam path. The upper and lower computers of the robot communicate through WIFI transmission and TCP protocol, which can realize remote real-time detection of weld surface defects. In addition, this article designs a permanent magnet adsorption structure for robot high-altitude wall climbing, which has been verified through simulation and experimental verification. To verify the intelligence of the robot, this paper conducted performance analysis experiments on weld line recognition and tracking models and surface defect models. The experimental results showed that the average detection accuracy of the weld line recognition and tracking algorithm was 96.8%, and the average detection accuracy of surface defects in the three types of welds was 94.2%. The method proposed in this article combines two algorithms and a special robot structure, providing a new approach for the automated inspection of welds in large industrial products such as ships.

EfficientNet-ECA: A lightweight network based on efficient channel attention for class-imbalanced welding defects classification

Welding defects recognition is crucial for ensuring weldment quality in robot arc welding. Nevertheless, due to unbalanced data distributions, limited computing resources in factory, as well as intraclass variability and interclass similarity among different welding defects, it is difficult to extract the most discriminative defect features from welding molten pool images on site, resulting in weak class-imbalanced defect recognition performance. To address the above issue, a novel lightweight network named EfficientNet-ECA is proposed for recognizing and classifying welding defects according to molten pool images of robot arc welding. Firstly, the EfficientNet-ECA network based on Efficient Channel Attention (ECA) is designed to extract the most discriminative features of different defects from molten pool images, where ECA is employed to enhance cross-channel information interactions. Secondly, a dynamic equalized focal loss function is proposed to both rebalance the loss contribution of class-imbalanced data of different defects and improve defects recognition accuracy. Subsequently, a class-imbalanced dataset containing eight typical welding defects is constructed to evaluate the EfficientNet-ECA model. Finally, the proposed model is comprehensively analyzed through ablation studies and compared with the existing state-of-the-art lightweight models, and results show that the proposed method exhibits better effectiveness and generalizability in classifying class-imbalanced defects across different welding scenarios, achieving the highest accuracy of 95.84% on a self-constructed AL5083 dataset and 96.50% on a publicly available SS304 dataset. Moreover, with fewer parameters and less complexity, the proposed method is more suitable for online welding quality monitoring in factory.

The Effect of Chamfer Angle Variations on the Quality of Friction Welding Results of AZ-31B Magnesium

Friction welding is one of the solid-state welding types. Friction welding is a joining process whose application melts the material itself by using the heat generated between the surfaces through a combination of rotational motion and the application of compressive loads. The use of magnesium alloys is widely used in various industrial fields, examples of magnesium alloy applications include coating materials from iron and steel as a means of protecting against corrosion. The use of AZ-31B series magnesium alloys has a high specific strength compared to other series such as AM. The purpose of this final project research is to determine the effect of the addition of chamfer angle on the tensile strength value and microstructure of AZ-31B magnesium friction welding results. From this research, the results obtained in tensile testing are that the addition of the chamfer angle to the surface of the weld specimen will increase the tensile strength value. The highest maximum stress value was obtained in the chamfer angle variation of 300 with an average of 228.525 MPa and the lowest maximum stress value was in the material that did not use the chamfer angle variation with an average of 105.722 MPa. Based on microstructure testing, it shows differences in ?- Mg and ?-Mg phase grains17 Al12 in each region, this is influenced by heat and also the melting generated from welding so that it changes its microstructure.

Investigating the effectiveness of concentric welded anchor rods in column base plate connections: A numerical and experimental study

This study presents a new strategy for column base plate connections, which involves the utilization of welded anchor rods positioned concentrically beneath the base plate, in alignment with the connected column. The objective was to remove the eccentricity between the anchor rods and the column, thereby excluding the base plate from the load-transferring chain. A numerical study was performed to compare the cyclic behavior and uplift response of the proposed connection with conventional column base connections. Additionally, different weld types were investigated to connect the anchor rods to the base plate, and their efficiency was evaluated based on a comprehensive dataset of nine tests on equivalent base-plate T-stub connections with different base-plate thicknesses, anchor-rod strengths, and anchor-rod diameters. The numerical results showed that using welded anchor rods could remove the pinching from the hysteresis loops, as the anchor rods can effectively resist cyclic loads in both compression and tension. Furthermore, removing the eccentricity between the anchor rods and the column enhanced the uplift stiffness by approximately 31 %. The experimental results indicated that the failure mode was the fracture of anchor rods for all specimens, while the other components remained elastic. The specimens with high-strength anchor rods showed a brittle failure accompanied by a sudden drop in load, which coincided with the fracture of anchor rod in the softened heat-affected zone. All developed weld types successfully withstood the ultimate tensile strength of anchor rods upon fracturing.

Ultrasonic weldability of thick and heavier nonwoven fabrics

AbstractNonwovens have wide application areas due to their advantageous properties like low cost, high production efficiency, and tuneable properties. They are mostly used for disposable products. Combining bicomponent fiber spinning with hydroentanglement method is one of the innovative methods to obtain nonwovens for durable applications. On the other hand, ultrasonic welding is an alternative assembling method for disposable products made of low weight nonwovens. In this study, the ultrasonic weldability of relatively heavier weight and thicker nonwoven fabrics made of polyester: polyamide bicomponent microfilaments were examined in order to combine the advantages of nonwovens and ultrasonic welding. Relatively higher thickness and weight, and also fiber composition of the nonwoven fabrics were compelling effects of the study that drove the motivation. Overall 60 samples were produced using five nonwoven fabrics with varying unit masses and 12 selected ultrasonic welding types. Seam strength and strain assessments were supported with stereomicroscope and visual inspections in evaluating the welds. Results showed that despite having thick seam lines up to 1.6 mm, successful welded seams could be obtained. Depending on the welding parameters, seam lines of some samples exhibited waviness, color changes, and deformations but these situations did not drastically affect the seam strength of samples.

Studying an improved recursive rough method for three-dimensional visual examination of steel plate butt welding surface quality

An improved recursive rough algorithm is proposed to extract feature points in order to address the slow speed and poor accuracy of feature point extraction in 3D visual inspection, as well as the difficulty in meeting the requirements of efficient and quantitative analysis of welded surface quality detection. The preprocessed point cloud is sliced by section. The feature points are obtained according to the improved recursive rough algorithm. The defect evaluation is carried out to obtain the inspection conclusion of the weld appearance defect. Finally, according to the formulated weld defect evaluation process and standards, the typical weld template is selected for weld width, weld misedge and weld straightness test. Weld detection accuracy can reach 3 decimal places, the speed is 4 times the current manual detection speed. The detection results show that the system has the characteristics of high accuracy and fast speed which can replace manual detection. It also has a good application prospect.

Modification of electro gas weld metal microstructure reflecting mechanical property specifications in cruise vessel shipbuilding

AbstractTo identify the microstructural factors effecting the electro gas welding (EGW) weld metal properties, this study investigated the influence of different prototype welding consumables and shielding gases on the microstructural composition and mechanical-technological properties. The aim was to adjust the weld metal properties as a trade-off between strength, ductility, and impact toughness to fulfill typical weld metal material specifications in cruise vessel shipbuilding under consideration of the manufacturing conditions at European shipyards. The microstructure is analyzed by quantitative metallography of the ferritic matrix, martensite-retained austenite (M/A) constituents, and non-metallic inclusions (NMI). The influence of the Ni content, the deoxidation concept by variation of Si and Ti contents, and different shielding gas activity by variation of the Ar proportions is discussed. The interaction of ferritic matrix with high acicular ferrite content of about 70 ± 10%, the existence of larger grain boundary ferrite formations, and the M/A morphology plus distribution are considered as the determining factors for the material properties.

AF-FTTSnet: An end-to-end two-stream convolutional neural network for online quality monitoring of robotic welding

Online welding quality monitoring (WQM) is crucial for intelligent welding, and deep learning approaches considering spatiotemporal features for WQM tasks show great potential. However, one of the important challenges for existing approaches is to balance the spatiotemporal representation learning capability and computational efficiency, which makes it challenging to adapt welding processes with complex and drastic molten pool dynamic behavior. This paper proposes a novel approach for WQM using molten pool visual sensing and deep learning considering spatiotemporal features, the proposed deep learning network called attention fusion based frame-temporality two-stream network (AF-FTTSnet). Firstly, a passive vision sensor is used to acquire continuous dynamic molten pool images. Meanwhile, temporal difference images are computed to provide novel features and temporal representations. Then, a two-stream feature extraction module is designed to concurrently extract rich spatiotemporal features from molten pool images and temporal difference images. Finally, an attention fusion module with the ability to automatically identify and weight the most relevant features is designed to achieve optimal fusion of the two-stream features. The shop welding experimental results indicate that the proposed AF-FTTSnet model can effectively and robustly recognize five typical welding states during helium arc welding, with an accuracy of 99.26%. This model has been demonstrated to exhibit significant performance improvements compared to mainstream temporal sequence models. Available: https://github.com/Just199806/TSCNN/tree/master.

Preliminary study on terahertz non-destructive testing for defect detection in hot melt joints of polyethylene pipes

With the rapid development of the economy and society, non-metallic pipelines are more and more widely used in oil and gas fields, water supply projects, urban gas systems, and so on. Among the conventional nondestructive testing (NDT) methods, only ultrasonic, radiographic, and penetration testing tools are applicable to non-metallic pipe examination from a theoretical perspective, while their actual efficiency is quite low. In this work, terahertz (THz) non-destructive detection of typical welding defects in polyethylene-pipe hot melt joints is carried out. The characteristic THz wave signal is obtained, and the relationship between the THz wave and the defect type is established. Finally, a THz signal processing model for defect detection in polyethylene-pipe hot melt joints is established. Thus, this research lays a foundation for the application of the THz non-destructive testing technology to polyethylene pipeline engineering.

Effect of Tool Profile on Mechanical Properties, Temperature, and RPM Using Micro Friction Stir Spot Welding (mFSSW) on Aluminum Alloy AA1100

Micro friction stir spot welding (mFSSW) is a type of solid-state spot welding of nonconsumable tools using friction and force to join material of thickness less than 1 mm. This research aimed to investigate the shape of the tools for best welding results among the proposed tool’s profile. The material specimen was aluminum alloy AA1100, with a thickness of 0.42 mm. This study aims to measure the temperature and RPM of the welding process with thermocouples and tachometers. And then investigate the mechanical properties using the tensile shear test, microhardness, and macrostructural observation to find the welding zone and hook profile. Four tools’ profiles are named tool 1, tool 2, tool 3, and tool 4. The result of this study was that tool 3 (Shoulder 450μm) had the highest temperature, around 428˚ C, and the shear tensile test was 450 N (the highest). The macrostructural observation used to define the zone on the welding result there are stir zone (SZ), thermos-mechanically affected zone (TMAZ), and heat affected zone (HAZ).

A fast simulation method for thermal management in wire arc additive manufacturing repair of a thin-walled structure

Ensuring first-time-right on-site repair of critical structures is a key challenge for additive manufacturing (AM)–based repair solutions. Fast thermal simulations are thus needed to plan efficient and error-free AM processes. This paper addresses a fast thermal simulation method for a novel subsea wire arc additive manufacturing (SWAAM) repair procedure. Current commercial finite element (FE) codes for typical welding and AM are computationally expensive and slow. The presented 2D finite difference approach can be used to simulate SWAAM on a damaged plate with around 70 times acceleration compared to real welding times, without the use of parallelization. Although not being able to accurately represent the temperature in close vicinity of the welding torch, the approach shows excellent correspondence with FE simulations and experiments in regions of the plate where the temperature has assumed a distribution that is largely two-dimensional. Compared with FE simulations, the approach is experimentally verified to be accurate to 10 °C within 7 s after the welding torch has passed a point on the plate. Thus, the approach can provide a measure of the global temperature field in a thin-walled structure during repair. The thermal simulation is preceded by a welding path planner, which generates appropriate paths based on slicing of a 3D surface scan of the damage that is to be repaired. Damages to equipment or non-ideal welding conditions are prevented by automatically pausing the welding if the calculated temperature in the path ahead of the welding torch exceeds a predefined interpass temperature limit.