We proposed a novel detection method for identifying joint defects in the brazing process between copper tubes and stainless steel using a convolutional neural network (CNN) model. The brazing joints were created using high-frequency induction heating equipment, and infrared thermal imaging cameras were employed to capture the thermal data generated during the jointing process. The experiments involved 15.88 mm diameter copper tubes commonly used in plate heat exchangers, stainless-steel tubes, and filler metal containing 20% Ag. The thermal data were obtained with a resolution of 80 × 80 pixels per frame, resulting in 4796 normal joint data and 5437 defective joint data collected over 100 high-frequency induction-heating brazing experiments. A total of 10,233 thermal imaging data were categorized into 6548 training data, 1638 validation data, and 2047 test data for the development of the predictive model. We designed CNN models with varying hyperparameters, specifically the number of kernel filters and nodes, to evaluate their impact on detection performance. A comparative analysis revealed that a CNN model structure, exhibiting 98.53% accuracy and 99.82% recall on test data, was the most effective. The selected CNN-based defect prediction model demonstrated the potential of using CNN models to discern joint defects in tube configurations that are challenging to identify visually. This study opens avenues for applying CNN-based models for detecting imperfections in complex tube structures.

Aluminum hulls, which are preferred in the marine industry due to their durability, corrosion resistance, and lightweight properties, face serious challenges due to thermal deformation during welding. This study aims to predict and minimize transverse deformations due to welding sequences for a transverse model in the lower part of an aluminum hull. To predict deformations, heat source dimensions obtained from actual weld beads were used as simulation conditions, and various welding sequence conditions were simulated through the developed finite element method (FEM). The simulation results were compared with actual deformation measurements to verify their reliability, and the optimal welding sequence which minimized deformation was derived. The simulation results show that by changing the welding sequence conditions, the maximum displacement can be reduced from a maximum of 52.1% to a minimum of 39.1%, and the effective plastic strain can be reduced from a maximum of 19.6% to a minimum of 4.8%. These results show that adjusting the welding sequence conditions can significantly improve structural integrity by minimizing deformation. The results of this study suggest that the control of the welding sequence can be used to reduce the deformation of aluminum hulls and promote a more sustainable marine industry with improved quality.

High-density polyethylene (HDPE) has emerged as a promising alternative to fiber-reinforced plastic (FRP) for small vessel manufacturing due to its durability, chemical resistance, lightweight properties, and recyclability. However, while thermoplastic polymers like HDPE have been extensively used in gas and water pipelines, their application in large, complex marine structures remains underexplored, particularly in terms of joining methods. Existing techniques, such as ultrasonic welding, laser welding, and friction stir welding, are unsuitable for large-scale HDPE components, where extrusion welding is more viable. This study focuses on evaluating the impact of key process parameters, such as the preheating temperature, hot air movement speed, and nozzle distance, on the welding performance of HDPE. By analyzing the influence of these variables on heat distribution during the extrusion welding process, we aim to conduct basic research to derive optimal conditions for achieving strong and reliable joints. The results highlight the critical importance of a uniform temperature distribution in preventing defects such as excessive melting or thermal degradation, which could compromise weld integrity. This research provides valuable insights into improving HDPE joining techniques, contributing to its broader adoption in the marine and manufacturing industries.

To effectively use aluminum, which is inherently weak under heat, as a material for hull construction, it is crucial to precisely predict the thermal deformation in the weld zone. Most studies employing finite element (FE) methods to predict thermal deformation due to welding typically use estimated heat source conditions based on the results of the weld. However, these estimated values can differ significantly from the actual welding conditions. In this study, we investigated whether using the actual shape of the heat source, rather than an estimated value, can serve as a reliable condition for analysis in predicting thermal deformation. This prediction is essential for minimizing deformation in the fillet welds of an aluminum hull. To compare deformation outcomes, Al 5083, commonly used in hull construction, was selected as the base material. The thermal deformation of aluminum hull fillet welds, welded using the Cold Metal Transfer (CMT) welding method, which reduces heat input, was measured. The simulation results demonstrated similar deformation trends, with discrepancies ranging from a minimum of 0.02 mm to a maximum of 1.4 mm when using actual welding conditions and heat source shapes. The results of this study confirm that the actual heat source shape can be utilized as a reliable condition for predicting thermal deformation in aluminum hull welds. The aim is to contribute to the improvement of aluminum hull manufacturing quality by providing essential data for establishing welding conditions and minimizing deformation.

Polymers are increasingly used as structural materials in medical devices due to their lightweight, chemical resistance, and electrical insulation properties. High-density polyethylene (HDPE) is widely applied; however, the fabrication of large or thick components often requires extrusion welding. Since joint performance directly affects structural reliability, controlling welding quality is essential. In this study, the effects of preheating conditions on the mechanical performance of HDPE extrusion-welded joints were systematically investigated. Preheating temperature and hot-air movement speed were selected as key variables, and their influence on tensile, flexural, and elongation properties was evaluated experimentally. The results provide insight into the role of preheating in weld quality and offer guidance for process optimization in medical device applications.