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Resistance spot welding (RSW) faces critical monitoring challenges in industrial applications due to nonlinear coupling characteristics and production line disturbances. This study developed a Zigbee-enabled real-time monitoring system to address the precision limitations of conventional methods in tracking RSW parameters. Using DP780/DP590 dual-phase steel specimens with thickness variations, we implemented a dedicated data acquisition system capturing welding current, voltage, and barometric pressure dynamics. The experimental results demonstrated measurement accuracies within ±0.49% for current, ±0.25% for voltage, and 3.72% average relative error for barometric pressure with stable operational deviations (0.017–0.024 MPa).

Stainless steel welding plays a critical role in industrial manufacturing due to its superior corrosion resistance and structural reliability. The keyhole tungsten inert gas (K-TIG) welding, renowned for its high efficiency, high precision, and cost-effectiveness, demonstrates particular advantages in medium-to-thick plate joining. In order to synergistically leverage the properties of 2205 duplex stainless steel (DSS) and 316L austenitic stainless steel (ASS), we have implemented K-TIG welding with a single variable under control: a constant current and voltage travelling speeds spanning 280–360 mm/min. Defect-free dissimilar joints were consistently achieved within the 280–320 mm/min speed window. The effects of welding speed on microstructural characteristics, mechanical properties, and corrosion behavior of the weld seams were systematically investigated. The percentage of austenite in the weld zone decreases from 84.7% to 59.9% as the welding speed increases. At a welding speed of 280 mm/min, the microstructural features in the regions near the weld seam and fusion zone were investigated. All obtained joints exhibited excellent tensile properties, with their tensile strengths surpassing those of the 316L base metal. The optimal impact toughness of 142 J was achieved at a welding speed of 320 mm/min. The obtained joints exceeded the hardness of TIG joints by 19%. Notably, the grain refinement in the weld zone not only enhanced the hardness of the welded joint but also improved its corrosion resistance. This study provides valuable process references in dissimilar stainless steel K-TIG welding applications.

Lane detection is a key technology in automatic driving environment perception, and its accuracy directly affects vehicle positioning, path planning, and driving safety. In this study, an enhanced real-time model for lane detection based on an improved DeepLabV3+ architecture is proposed to address the challenges posed by complex dynamic backgrounds and blurred road boundaries in suburban road scenarios. To address the lack of feature correlation in the traditional Atrous Spatial Pyramid Pooling (ASPP) module of the DeepLabV3+ model, we propose an improved LC-DenseASPP module. First, inspired by DenseASPP, the number of dilated convolution layers is reduced from six to three by adopting a dense connection to enhance feature reuse, significantly reducing computational complexity. Second, the convolutional block attention module (CBAM) attention mechanism is embedded after the LC-DenseASPP dilated convolution operation. This effectively improves the model’s ability to focus on key features through the adaptive refinement of channel and spatial attention features. Finally, an image-pooling operation is introduced in the last layer of the LC-DenseASPP to further enhance the ability to capture global context information. DySample is introduced to replace bilinear upsampling in the decoder, ensuring model performance while reducing computational resource consumption. The experimental results show that the model achieves a good balance between segmentation accuracy and computational efficiency, with a mean intersection over union (mIoU) of 95.48% and an inference speed of 128 frames per second (FPS). Additionally, a new lane-detection dataset, SubLane, is constructed to fill the gap in the research field of lane detection in suburban road scenarios.

Mandatory lane-changing in complex driving scenarios poses significant challenges for autonomous driving systems due to complex vehicle interactions and strict safety requirements. Existing methods often rely on handcrafted rules or extensive expert demonstrations, which increase data collection costs and provide limited safety guarantees during learning. To address these issues, this paper proposes a rule-guided reinforcement learning framework for lane-changing policy optimization. A lightweight rule-based controller is employed to generate initial experience, guiding the training of an improved Distributional Soft Actor–Critic with Three Refinements (DSAC-T), while a safety-aware constraint controller filters high-risk actions to ensure stable and safe learning. The proposed method is evaluated in Regular Lane Change and Lane Merging scenarios under mixed traffic composed of aggressive and conservative vehicles within a simulation environment. Simulation results show that although lane-changing success rates decrease as traffic aggressiveness increases, the proposed method consistently outperforms SAC and TD3. Notably, under highly aggressive traffic conditions with an aggressiveness ratio of 0.7, the proposed approach improves the success rate by 17.13% compared to SAC and by 10.49% compared to TD3, demonstrating superior robustness and safety in complex, high-conflict lane-changing scenarios. The present study is conducted solely in simulation and requires further validation before application to real-world traffic environments.

In this paper, metal inert gas (MIG) welding of 6082-T6 aluminum alloy with a thickness of 4 mm was simulated using a double ellipsoidal heat source. Based on the simulation results, the evolution of the microstructure, the strengthening mechanism of mechanical properties, and the corrosion characteristics of the welded joint were studied further. The thermal cycle curve of the welded joint was obtained through numerical simulation. When the heat input was 2.34–2.75 KJ/mm, the temperature of the welded joint reached the melting point of the material. With the increase in welding heat input, the weld metal (WM) organization changed from the dendrite to the cellular crystal transformation and presented a uniform distribution. The precipitation of the strengthened phase was inhibited at 2.75 KJ/mm. When the heat input changed from small to large, the tensile strength and toughness first increased and then weakened. Dimple distribution of tensile fractures was observed with a scanning electron microscope. When the welding heat input was 2.57 KJ/mm, the mechanical properties of the joint were the best. The tensile strength can reach 76.62% of the base material, and the elongation after breaking can reach 59.38% of the base material. However, it was concluded through studying electrochemical corrosion that the corrosion resistance of welded joints under this parameter was the worst. This may be caused by the presence of Cu, Fe, Si, Mg, and other compounds, and was proven to be Mg2Si through EDS analysis.

Research on trajectory tracking control for climbing welding robots holds significant importance in the field of automated welding. However, existing trajectory tracking methods suffer from issues such as jitter and slow speed. In this paper, an improved sliding mode control strategy is proposed based on the self-designed wall-climbing welding mobile manipulator. Firstly, a new adaptive sliding mode control strategy is proposed for the mobile platform based on the kinematic model. By introducing a new approach law, the controller is designed when the distance between the center of mass is unknown. Secondly, regarding the manipulator, we analyze simplified dynamic equations, extract uncertain components, and utilize a CNN for compensation. This compensation strategy is integrated into the sliding mode control law, achieving precise control over the manipulator and effectively resolving issues like slow tracking speeds, large errors, and chattering. The stability of the robot control system is proved by the Lyapunov function. Through simulation analysis and experimental validation, the proposed control method is confirmed to be feasible and superior.

In this paper, 8 mm thickness 2205 duplex stainless steel (DSS) plates were successfully welded using keyhole tungsten inert gas welding (K-TIG) welding, and numerical simulations were performed applying the finite element method. Three models of combined heat source were adopted to verify accuracy of experiment. The welding process under different welding speeds were simulated, and the temperature field, molten pool shape, and thermal cycle curve were calculated. The welding simulation results show that a combined model consisting of the ellipsoid heat source and the conical heat source is more suitable for K-TIG welding. The results of the microstructure analysis of the welded joint showed that when the welding speed was increased from 280 mm/min to 340 mm/min, the austenite content and the ferrite and austenite grain size decreased. The evolution laws of welded joint morphologies, microstructure and grain sizes under different welding speed conditions were consistent with the analysis results of simulated molten pool morphologies, temperature field distributions and thermal cycle curves. It is proved that this kind of simulation method can effectively simulate the K-TIG welding process and ensure the welding quality, which is a guide for industrial applications.

The manufacture, maintenance and inspection of a ship involve a series of works on the ship shell plate, which were always seen as harmful for human operators and time-consuming work. The shipping industry is looking to replace manual work with automation equipment. A magnetic climbing robot that can omnidirectionally move on ship shell plate was presented in this paper. This article summarized the mechanical structure, control system, kinematic model, and autonomy of robot. The mechanical structure of the robot was inspired by bionics and adopted a wheel-leg hybrid locomotion system. In the control system of this robot, industrial control computer (IPC) was adopted as the core controller and brushless direct current servomotor was chosen as the actuating station. Finally, the motion analysis of the designed robot was performed. The results of the analysis show that the magnetic climbing robot adapted to the ship curved shell plate and crossed obstacles.

With the improvement and development of micro-mechanical manufacturing technology, people can produce an increasing variety of micro-electromechanical systems in recent years, such as micro-satellite thrusters, micro-sensors, micro-aircrafts, micro-medical devices, micro-pumps, and micro-motors. At present, these micro-mechatronic systems are driven by traditional energy power systems, but these traditional energy power systems have such disadvantages as short endurance time, large size, and low energy density. Therefore, efforts were made to study micro-energy dynamical systems with small size, light gravity, high density and energy, and long duration so as to provide continuous and reliable power for these systems. In general, the micro-thermal photoelectric system not only has a simple structure, but also no moving parts. The micro-thermal photoelectric system is a micro-energy power system with good application prospects at present. However, as one of the most important structural components of micro-thermal photoelectric systems, the microburner, is the key to realize the conversion of fuel chemical energy to electric energy in micro-thermal photoelectric system. The studies of how to improve the flame stability and combustion efficiency are very necessary and interesting. Thus, some methods to improve the performance of micro-burners were introduced and summarized systematically, hoping to bring some convenience to researchers in the field.

In this study all-position automatic tungsten inert gas (TIG) welding was exploited to enhance quality and efficiency in the welding of copper-nickel alloy pipes. The mathematical models of all-position automatic TIG weld bead shapes were conducted by the response surface method (RSM) on the foundation of central composition design (CCD). The statistical models were verified for their significance and adequacy by analysis of variance (ANOVA). In addition, the influences of welding peak current, welding velocity, welding duty ratio, and welding position on weld bead geometry were investigated. Finally, optimal welding parameters at the welding positions of 0° to 180° were determined by using RSM.