Current Issue : October-December Volume : 2025 Issue Number : 4 Articles : 5 Articles
We developed an automatic optical inspection (AOI) system for detecting defects in finished workpieces and determining the parameters for CNC machining. The system addresses quality control issues in CNC machining using image processing, machine learning, and G-code analysis techniques. The accuracy and efficiency of CNC machining were improved by reducing manual inspection tasks, minimizing production downtime, and achieving higher precision in defect detection and correction. Experiments were conducted in a pre-planned CNC machining environment to validate the effectiveness of the proposed AOI system. The system was tested on metals and composites and CNC lathes and milling machines. The AOI system significantly improved defect detection accuracy, exceeding 95% across different defect types. The proposed machining parameters enabled a reduction in the recurrence rate of defects by approximately 80%, demonstrating the potential to enhance overall machining quality. By developing AOI recognition and optimizing CNC machining parameters, an automated and intelligent defect detection and correction solution was realized. The reliability and accuracy of CNC processes were improved, and data-driven automated manufacturing and process optimization were achieved, meeting the goals of intelligent manufacturing and Industry 4.0....
In large welding structures, maintaining a uniform assembly condition and machined dimension in the pre-welding groove is challenging. The assembly condition and machined dimension of the pre-welding groove significantly impact the selection of the welding parameters. In this study, laser–arc hybrid welding is used to perform butt welding on 6 mm Q345 steel in various assembly conditions, and we propose an adaptive model of the BP neural network optimized by a genetic algorithm (GA) for laser–arc welding. By employing the GA algorithm to optimize the parameters of the neural network, the relationship between the pre-welding groove parameters and welding parameters is established. The mean square error (MSE) of the GA-BP neural network is 0.75%. It is verified via experiments that the neural network can predict the welding parameters required to process a specific welding morphology under different pre-welding grooves. This model provides technical support for the development of intelligent welding systems for large and complex components....
The mismatch between the engine noise and the vehicle speed of hybrid vehicles in the state of battery depletion constitutes one of the main noise sources of the vehicles. A noise testing method for the hybrid engine was proposed with the aid of the rotating hub test bench. The data of the in-vehicle engine noise under various operating powers were parsed, and simultaneously, the background noise data within the vehicle during the uniform-speed driving in the pure electric driving mode of the vehicle were collected. Based on the acoustic masking effect, a subjective evaluation method has been developed to assess the masking impact of background noise on engine noise within vehicles. Analysis of the subjective evaluation results revealed that a fundamental condition for effective masking of engine noise by background noise is that the latter must sufficiently envelop the characteristic spectrum of the engine noise. Ultimately, the vehicle calibration strategy was refined based on the outcomes of subjective evaluations. This adjustment not only enhanced the vehicle’s NVH performance but also introduced an innovative approach to engine noise control in hybrid vehicles operating in series mode....
Combined cooling, heating, and power systems (CCHP) could increase the efficiency of conventional energy supply systems and mitigate carbon emissions. In this paper, a novel arrangement of a combined cooling, heating, and power (CCHP) system is presented with prime movers of internal combustion and Stirling engines, which are numerically simulated by Range-Kutta method and optimized with the genetic algorithm technique. The influence of some key parameters such as Stirling engine speed, phase angle, length and porosity of Stirling engine’s regenerator, and also speed and spark timing of the internal combustion engine, on the capacity, efficiency, primary energy saving and the investment payback period of the CCHP system has been discussed. The results illustrated that using the CCHP system with hybrid prime movers, due to the appropriate efficiency of the combustion engine, allows the Stirling engine to be started at high speeds. In this condition, the overall efficiency of the hybrid system is increased by 12 % compared to using the CCHP system with only the Stirling engine. Additionally, the payback period of the CCHP system with combined prime movers at 3500 rpm for the two engines is approximately 4.4 years, which is about 1.6 years shorter than the payback period of the CCHP system based solely on the internal combustion engine. This work provides valuable insights into the design and optimization of hybrid CCHP systems with two different combustion-based prime movers....
The aerodynamic performance of an aircraft can be enhanced by incorporating wingtip devices, or winglets, which primarily reduce lift-induced drag created by wingtip vortices. This study outlines an optimization procedure for implementing winglets on a Class I fixed-wing mini-UAV to maximize aerodynamic efficiency and performance. After the Conceptual and Preliminary design phases, a baseline UAV was developed without winglets, adhering to specific layout constraints (e.g., wingspan, length). Various winglet designs—plate and blended types with differing heights, cant angles, and sweep angles—were then created and assessed. A Computational Fluid Dynamics (CFD) analysis was conducted to evaluate the flow around both the winglet-free UAV and configurations with each winglet design. The simulations employed Reynolds-Averaged Navier-Stokes (RANS) equations coupled with the Spalart-Allmaras turbulence model, targeting the optimal winglet configuration for enhanced aerodynamic characteristics during cruise. Charts of lift, drag, pitching moment coefficients, and lift-to-drag ratios are presented, alongside flow contours illustrating vortex characteristics for both baseline and optimized configurations. Additionally, dynamic stability analyses examined how winglets impact the UAV’s stability and control. The results demonstrated a significant improvement in aerodynamic coefficients (CLmax, L/Dmax, CLa, Cma), leading to an increase in both range and endurance....
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