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Cross-machine predictions of the quality of injection-molded parts by combining machine learning, quality indices, and a transfer model

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International Journal of Advanced Manufacturing technology 2024年第9-10期133卷 4981-4998页

作者： Chang, Chia Hao Ke, Kun-Cheng Huang, Ming-Shyan Department of Mechatronics Engineering National Kaohsiung University of Science and Technology Dept. of Mechatronics Engineering National Taiwan Normal University

The achievement of consistent molding quality, which is critical in injection molding, is heavily reliant on the reasonable control of processing materials, molds, machines, process parameters, and environmental conditions. Notably, new molds usually require a trial molding process before being delivered to relevant machines for online production. However, performance differences between machines make it challenging to maintain consistent molding quality, and suitable adjustments must be made to machine parameters to compensate for these differences. Therefore, cross-machine product quality prediction is critical for accurately forecasting product quality across different machines in a manufacturing process and thus for ensuring consistent quality, few defects, and optimized production. To avoid the considerable time and high cost required for quality inspection and to improve production efficiency, this study developed a multilayer perceptron (MLP) model combined with quality indices to predict molding quality. This paper describes how the developed model predicts product quality for the same mold in different machines. The procedure of the proposed MLP model involves four steps. First, data are prepared, features are extracted (extraction of quality indices), and the model is trained on an actual injection molding machine (machine A). Second, the developed MLP model establishes the relationships between the process parameters, quality indices, and product quality for machine A. Third, Moldex3D Studio, which is a software program for simulating injection molding, is employed to generate production data for a virtual injection molding machine (machine B). Finally, a transfer model is used to fit the quality indices of machines A and B so that the MLP model can directly predict the product quality (in terms of weight and geometric dimensions) for machine B on the basis of the quality indices generated using the process parameters of machine B. Experimental results in

关键词： Injection molding Machine learning Multilayer perceptron (MLP) Quality index Quality prediction Trial molding process

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Research on the Camouflage Characteristics of a Microfluidic Vision Camouflage System Based on the Image Inpainting Algorithm

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Journal of Bionic engineering 2025年第1期22卷 370-382页

作者： Jian Cao Huanhuan Li Songjing Li Jiyan He Zhifan Li School of Mechatronics Engineering Harbin Institute of TechnologyHarbin150001China Tianjin Institute of Aerospace Mechanical and Electrical Equipment Tianjin300301China

Combining deep-learning image inpainting algorithms with the microfluidic technology,the paper proposes a method to achieve dynamic stealth and camouflage by using a microfluidic vision camouflage system simulating the chameleon *** basic principle is to perceive color changes in the external environment and collect ambient image information,and then utilize the image inpainting algorithm to adjust the control signals of the microfluidic system in real *** detailed working principle of the microfluidic vision camouflage system is presented,and the mechanism of generating control signals for the system through deep-learning image inpainting algorithms and image-processing techniques is *** camouflage effect of the chameleon skin is analyzed and evaluated using color *** indicate that the camouflaged images are consistent with the background environment,thereby improving the target’s stealth and maneuvering *** camouflage technology developed in the paper based on the microfluidic vision camouflage system can be applied to several situations,such as military camouflage uniforms,robot skins,and weapon equipment.

关键词： Chameleon skin Bionic skin Microfluidic technology Self-adaptive system Camouflage film

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Analysis of anomalous behaviour in network systems using deep reinforcement learning with convolutional neural network architecture

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CAAI Transactions on Intelligence technology 2024年第6期9卷 1467-1484页

作者： Mohammad Hossein Modirrousta Parisa Forghani Arani Reza Kazemi Mahdi Aliyari-Shoorehdeli Faculty of Electrical Engineering K.N.Toosi University of TechnologyTehranIran Faculty of Mechatronics Engineering K.N.Toosi University of TechnologyTehranIran

To gain access to networks,various intrusion attack types have been developed and *** increasing importance of computer networks in daily life is a result of our growing dependence on *** this,it is glaringly obvious that algorithmic tools with strong detection performance and dependability are required for a variety of attack *** objective is to develop a system for intrusion detection based on deep reinforcement *** the basis of the Markov decision procedure,the developed system can construct patterns appropriate for classification purposes based on extensive amounts of informative *** Q-Learning(DQL),Soft DQL,Double DQL,and Soft double DQL are examined from two *** evaluation of the authors’methods using UNSW-NB15 data demonstrates their superiority regarding accuracy,precision,recall,and F1 *** validity of the model trained on the UNSW-NB15 dataset was also checked using the BoT-IoT and ToN-IoT datasets,yielding competitive results.

关键词： deep reinforcement learning intrusion detection Q-Learning transferability

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Computational and experimental investigations of a microfluidic mixer for efficient iodine extraction using carbon tetrachloride enhanced with gas bubbles

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Chinese Physics B 2023年第11期32卷 518-526页

作者： Siddique Muhammad Kashif 孙林李松晶 Department of Fluid Control and Automation School of Mechatronics EngineeringHarbin Institute of TechnologyHarbin 150001China

Numerous studies have been conducted on microfluidic mixers in various microanalysis systems, which elucidated the manipulation and control of small fluid volumes within microfluidic chips. These studies have demonstrated the ability to control fluids and samples precisely at the microscale. Microfluidic mixers provide high sensitivity for biochemical analysis due to their small volumes and high surface-to-volume ratios. A promising approach in drug delivery is the rapid microfluidic mixer-based extraction of elemental iodine at the micro level, demonstrating the versatility and the potential to enhance diagnostic imaging and accuracy in targeted drug delivery. Micro-mixing inside microfluidic chips plays a key role in biochemical analysis. The experimental study describes a microfluidic mixer for extraction of elemental iodine using carbon tetrachloride with a gas bubble mixing process. Gas bubbles are generated inside the microcavity to create turbulence and micro-vortices resulting in uniform mixing of samples. The bubble mixing of biochemical samples is analyzed at various pressure levels to validate the simulated results in computational fluid dynamics(CFD). The experimental setup includes a high-resolution camera and an air pump to observe the mixing process and volume at different pressure levels with time. The bubble formation is controlled by adjusting the inert gas flow inside the microfluidic chip. Microfluidic chip-based gas bubble mixing effects have been elaborated at various supplied pressures.

关键词： microfluidic mixer iodine extraction CFD simulation micro-mixing properties

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Hybrid Robotic Arm for Autonomous Aerial Refueling

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Chinese Journal of Mechanical engineering 2024年第6期37卷 429-440页

作者： Kaixuan Li Gangfeng Liu Yongsheng Gao Jie Zhao State Key Laboratory of Robotics and Systems Harbin Institute of TechnologyHarbin 150080China School of Mechatronics Engineering Harbin 150080China

Autonomous aerial refueling technology is gaining increasing attention to enhance aircraft combat *** research on autonomous refueling focuses mainly on flight control laws,with little attention to the automation of refueling *** leads to high demands on control law performance and navigation accuracy,making it difficult to ensure *** address this,we propose a robotic arm system capable of automatic docking during the flexible aerial refueling *** system uses a conical kinematic space configuration,offering enhanced stability and impact *** frame-type structure achieves a lightweight ***,we establish a single-objective optimization model for the connecting rod dimensions and apply a genetic algorithm(GA)for their *** also propose a trajectory-fitting calibration theory based on the robotic arm's special configuration and complete its movement accuracy calibration using a laser *** calibration method reduces the robotic arm's motion error by 71%,achieving an absolute positioning accuracy better than 3.5 mm,which meets the requirements for autonomous aerial *** summary,this research presents a hybrid robotic arm that meets automatic docking requirements,offering a new approach to autonomous aerial refueling.

关键词： Autonomous aerial refueling Conical kinematic space configuration Optimization of structural design Calibration method

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A Singularly Perturbed Model of 3rd Order Discrete-time Linear Systems With Two-rate Samplings and Its Stability Analysis

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Journal of Institute of Control, Robotics and Systems 2024年第7期30卷 663-667页

作者： Kim, Hongkeun ARC-MEE Future Convergence Engineering School of Mechatronics Engineering Korea University of Technology and Education Korea Republic of

In this paper, we propose a singularly perturbed model of 3rd order discrete-time linear systems. A unique feature of this model is that the 3rd order system is composed of two subsystems, each of which has its own sampling rate. The first and second subsystems are 2nd and 1st order, respectively, and the sampling rate of the latter subsystem is higher than that of the former. For this model, we present a sufficient condition for the stability of the original 3rd order system that interprets as follows: If the reduced system and the boundary layer system are stable and if the sampling rate of the second subsystem is sufficiently higher than that of the first subsystem, then the original 3rd order system is asymptotically stable. A Lyapunov function to prove the stability of the 3rd order linear system is also proposed. Finally, a computer simulation is conducted to confirm the result. © ICROS 2024.

关键词： Lyapunov functions

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Mechanism of material removal and chip formation of alumina dispersion strengthened copper in micro-milling

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Frontiers of Mechanical engineering 2025年第1期20卷 27-43页

作者： Chang LIU Chunya WU Xiguang LI Bo HOU Jiahao WU Ruijiang SUN Mingjun CHEN School of Mechatronics Engineering Harbin Institute of TechnologyHarbin 150001China State Key Laboratory of Robotics and System Harbin Institute of TechnologyHarbin 150001China

Alumina dispersion-strengthened copper (ADSC), as a representative particle-reinforced metal matrix composite (PRMMC), exhibits superior wear resistance and high strength. However, challenges arise in their processability because of the non-uniform material properties of biphasic materials. In particular, limited research has been conducted on the reinforcement mechanism and behavior of particles during material cutting deformation of PRMMC with nanoscale particles. In this study, a cutting simulation model for ADSC was established, separating the nanoscale reinforcement particles from the matrix. This model was utilized to analyze the interactions among particles, matrix, and tool during the cutting process, providing insights into chip formation and fracture. Particles with high strength and hardness are more prone to storing stress concentrations, anchoring themselves at grain boundaries to resist grain fibration, thereby influencing the stress distribution in the cutting deformation zone. Stress concentration around the particles leads to the formation of discontinuous chips, indicating that ADSC with high-volume fractions of particle (VFP) exhibits low cutting continuity, which is consistent with the results of cutting experiments. The tool tip that is in contact with particles experiences stress concentration, thereby accelerating tool wear. Cutting ADSC with 1.1% VFP results in tool blunting, which increases the radius of cutting edge from 0.5 to 1.9 μm, accompanied with remarkable coating delamination and wear. Simulation results indicate that the minimum uncut chip thickness increases from 0.04 to 0.07 μm as VFP increases from 0.3% to 1.1%. In conjunction with scratch experiments, MUCT increases with the augmentation of VFP. Computational analysis of the specific cutting force indicates that particles contribute to the material’s size effect. The results of this study provide theoretical guidance for practical engineering machining of ADSC, indicating its g

关键词： alumina dispersion-strengthened copper particle-reinforced metal matrix composites material removal mechanism micro-milling chip formation minimum uncut chip thickness

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The roles of microstructural anisotropy in tribo-corrosion performance of one certain laser cladding Fe-based alloy

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Friction 2023年第9期11卷 1673-1689页

作者： Weitao SUN Xuehong HUANG Jian ZHANG Bin WANG Xiaoliang LIU College of Mechatronics Engineering Binzhou UniversityBinzhou 256600China Key Laboratory of Solidification Control and Digital Preparation Technology(Liaoning Province) Dalian University of TechnologyDalian 116085China College of Mechatronics Engineering Binzhou PolytechnicBinzhou 256600China

Because of the microstructural anisotropy for laser cladding materials,the tribo-corrosion performance can vary significantly with different *** this study,one certain Fe-based coating was fabricated by laser *** study the effects of anisotropy,three working surfaces(0°,45°,and 90°to the building direction)were machined from the laser cladding samples;as-cast samples with an approximately homogeneous structure were prepared as *** tribo-corrosion tests were conducted in a 3.5 wt%NaCl solution with varying normal loads(5,10,and 15 N).The results demonstrated that the 45°surface has superior friction stability,corrosion resistance,and wear *** was directly related to the crystal orientation and grain boundary *** addition,a refined microstructure may enhance tribo-corrosion properties by increasing deformation resistance and decreasing surface activity.

关键词： laser cladding anisotropy Fe-based tribo-corrosion performance

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Vehicle Height Control of Active Hydropneumatic Suspension Considering Ride Comfort

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IAENG International Journal of Applied Mathematics 2025年第4期55卷 861-867页

作者： Duan, Yizhuang Dong, Zhenle Bai, Dongjie Zhou, Zhigang Li, Geqiang Wang, Shuai School of Vehicle and Transportation Engineering Henan University of Science and Technology Luoyang471000 China School of Mechatronics Engineering Henan University of Science and Technology Luoyang471000 China

Active hydro-pneumatic suspension has been widely used in heavy vehicles for its extraordinary merits, such as non-linear stiffness and damping, adjustable body height, etc. This paper proposes a vehicle height control method for active hydro-pneumatic suspension considering ride-comfort, a mathematical model of the hydro-pneumatic suspension integrating the dynamics of gas spring (accumulator) and valve-controlled hydraulic system is established, and the control strategy containing model compensation and robust feedback is designed based on backstepping, and the stability of the system is proved via Lyapunov analysis, which shows that the proposed control strategy can theoretically realize the accurate control of vehicle height and limit the acceleration amplitude of the frame. The MATLAB/Simulink platform is used for simulation. The simulation results under the two working conditions show that compared with PID control, the proposed control strategy can achieve higher vehicle height adjustment accuracy and improve vehicle ride comfort. © 2025 IAENG International Journal of Applied Mathematics

关键词： Backstepping

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The effect of instance mask-guided attention for discriminative learning of vehicular collision image classification

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Multimedia Tools and Applications 2025年第7期84卷 3929-3945页

作者： Madhumitha, G. Senthilnathan, R. Department of Mechatronics Engineering SRM Institute of Science and Technology Tamil Nadu Chengalpattu District Kattankulathur603203 India

A vehicular collision is an unfortunate event and a great challenge to be addressed for autonomous vehicles’ navigation. In this paper, an instance mask-guided attention (IMGA) method is presented for vehicular collision image classification. The major challenge in developing deep learning solutions to understand vehicular collision lies in the dataset, which is typically developed from unintentionally captured dashboard camera videos that have wide variations in acquisition conditions. In the proposed IMGA method, the instance masks of vehicles undergoing collision in an image supervise the learning of an attention-based image classification model. The proposed method consists of a pre-trained instance segmentation branch that generates colliding vehicles instance masks that are used as ground truth for learning the attention map of the classifier. This helps achieve a discriminative learning strategy that concentrates only on the significant regions in the image from its background increasing its robustness and accuracy. Experimentation proved the effectiveness of the proposed IMGA method with a result of 97.94% accuracy in the presented vehicular collision image classification dataset which is much higher compared to state-of-the-art image classification models. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

关键词： Image classification

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