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检索条件"丛书名=Lecture Notes in Mechanical Engineering"

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Settings of Radial Corrections of the Gyroscopic Stabilizer 15th

Settings of Radial Corrections of the Gyroscopic Stabilizer

引用

15th International Conference on Vibration Problems (ICoVP)

作者： Skoda, Jan Sivcak, Michal Tech Univ Liberec Studentska 2 Liberec 46117 Czech Republic

ISBN: (纸本)9789819959211;9789819959228

The gyroscopic stabilizer is a device that protects a transported cargo from the undesirable effects of vehicle tilting. The characteristic parameters of such a system are the angular momentum of its gyroscopes and the magnitude of the feedback of the correction and compensation systems, or the so-called radial corrections, which are integral parts of the gyroscopic stabilizer. Radial corrections represent non-conservative forces of positional coordinates and positive feedback. Thus, they could cause instability in the system. Therefore, and in view of the purpose of the gyroscopic stabilizer, parameters of radial corrections must be chosen carefully. In this paper, we will present an approach to the tuning radial corrections of the two-axis gyroscopic stabilizer intended to improve the vibration-isolation of the lying human body during roadway transport in an ambulance car. Our approach starts with roadway design standards, vehicle homologation standards and uses experimentally-obtained real traffic data.

关键词： Two-axis gyroscopic stabilizer Radial corrections Cargo protection Vibration isolation

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Numerical Analysis of Roughened Target Surface for Enhancing Jet Impingement Cooling 14th

Numerical Analysis of Roughened Target Surface for Enhancing...

引用

14th International Conference on Computational Heat and Mass Transfer (ICCHMT)

作者： Yalcinkaya, Orhan Durmaz, Ufuk Tepe, Ahmet Umit Benim, Ali Cemal Uysal, Unal Sakarya Univ Mech Engn Dept TR-54050 Serdivan Sakarya Turkiye Tarsus Univ Dept Elect & Energy TR-33100 Mersin Turkiye Dusseldorf Univ Appl Sci Munsterstr 156 D-40476 Dusseldorf Germany

ISBN: (纸本)9783031672408;9783031672415

Roughening on a surface is crucial in heat transfer, primarily enhanced by the increased interaction between the fluid and the surface. Considering this, a thorough study was conducted to explore impinging jet array cooling (IJAC) applied to a semicircular curved surface, enhanced with aerofoil-shaped fins. Analyses were conducted under different Reynolds numbers (Re), fin arrangements, and nozzle-to-target surface spacings (S/d). Extensive analyses were conducted for both roughened and smooth target surfaces. The roughened surface and extending the nozzles to the surface increased the Nu numbers relative to the conventional IJAC scheme. The obtained heat transfer improvement was about 52.81%. In addition, the heat transfer distribution on the surface has become more homogeneous. The results of the study showed that a roughened target surface with elongated jets has significant potential for internal cooling.

关键词： Roughened Surfaces Aerofoil Shaped Pins Heat Transfer Uniformity Concave Surface

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AI-Based Structural Feature Recognition for Robotic Grasping of Additive Manufacturing Parts 1

引用

33rd International Conference on Flexible Automation and Intelligent Manufacturing

作者： Xu, Tongqing Gao, Yuer Cai, Yi Hong Kong Univ Sci & Technol Guangzhou Smart Mfg Thrust Guangzhou 511453 Peoples R China Hong Kong Univ Sci & Technol Hong Kong Peoples R China

ISBN: (数字)9783031744853

ISBN: (纸本)9783031744846;9783031744853

Additive manufacturing factories have emerged in recent years to provide printing services to a wide range of individuals and businesses. Although 3D printing itself is primarily automatic, many other operations in such production factories are still manual, hindering the overall operational efficiency. Therefore, this article aims to improve the automation level of additive manufacturing factories by developing a mobile robot system that integrates a vision system and a two-finger flexible manipulator to automatically complete the model removal work after 3D printing. The system uses a camera to scan and identify the best grasping point of the print through an improved multi-layer convolutional neural network (CNN), while using image segmentation technology to accurately locate the target grasping position. The optimal grasping angle is determined through multi-view analysis to achieve efficient and precise grasping operations. The performance of the system was verified through CNN training on a self-built data set and successful crawling on unknown models, demonstrating its potential in intelligent operation and maintenance of 3D printing equipment.

关键词： Additive manufacturing Convolutional neural network Robotic grasping

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Mixed Reality as a Perspective Education Tool in Industry 5.0 8th

Mixed Reality as a Perspective Education Tool in Industry 5....

引用

8th International Scientific-Technical Conference (MANUFACTURING)

作者： Husar, Jozef Hrehova, Stella Knapcikova, Lucia Trojanowski, Piotr Tech Univ Kosice Presov Slovakia West Pomeranian Univ Technol Szczecin Szczecin Poland

ISBN: (纸本)9783031564468;9783031564444

In this paper, we evaluate several aspects of mixed reality (MR) and its use in Industry 5.0. In the introduction, we define the term Industry 5.0 and its connectionwith mixed reality as a key educational tool. Next, wedevoted ourselves to the scientific interpretation of the terms Industry 5.0 and mixed reality. We then moved on to software and hardware tools in the field of MR and summarized the methods and materials in dealing with the topic of mixed reality in Industry 5.0. We assess the importance of MR in Industry 5.0 education, emphasizing its ability to provide authentic and immersive learning experiences for university students. Finally, we discuss ways to evaluate the results of MR implementation in education, including quantitative and qualitative methods. With this article, we cover a wide range of topics related tomixed reality and its applications in Industry 5.0 and education. By implementing the proposed methodology, we will provide students with a competitive advantage in their application in the smart factories of the future.

关键词： mixed reality education methodology Industry 5.0

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Handling Digital Thread Information to Bridge the Gap Between Design and Manufacturing 33rd

Handling Digital Thread Information to Bridge the Gap Betwee...

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33rd International Conference on Flexible Automation and Intelligent Manufacturing

作者： Burow, Kay Klein, Patrick Hribernik, Karl Thoben, Klaus-Dieter BIBA Bremer Inst Prod & Logist GmbH Hsch Ring 20 D-28359 Bremen Germany Univ Bremen Inst Integrated Prod Dev Badgasteiner Str 1 D-28359 Bremen Germany

ISBN: (纸本)9783031744815;9783031744822

Industry 4.0 is a common term nowadays, but in reality, there are still sectors where Industry 4.0 is still in the beginning, such as manufacturing large-scale components or one-of-a-kind production. Here, many complex parts and components are still fabricated and checked manually by workers. This paper focuses on a digitalised mapping for large-scale components, particularly on a use case in the shipyard environment - on an application on how to handle digital thread information and implement this knowledge to digitalise the manufacturing processes. In the context of joining two standardised ship segments, occurring piping gaps must be closed using fitting pipes. Both endings of the piping have to be measured and checked, and an individual fitting pipe is fabricated and inserted - work which is still done manually and thus time intensive. The vision is to develop an application to map the digital thread to adopt and automate the fitting pipe design within AutomationML for further usage.

关键词： Digital Thread AutomationML Large-scale Components

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A Hybrid Model for Solder Joint Height Prediction Based on Physical Knowledge and Machine Learning 33rd

A Hybrid Model for Solder Joint Height Prediction Based on P...

引用

33rd International Conference on Flexible Automation and Intelligent Manufacturing

作者： Cao, Nieqing Farrag, Abdelrahman Kim, Jaewoo Won, Daehan Yoon, Sang Won SUNY Binghamton Binghamton NY 13902 USA

ISBN: (纸本)9783031744815;9783031744822

This study presents a hybrid model for solder joint profile calculation before formation, merging physics-based insights with machine learning techniques. As the electronics industry shifts towards miniaturization and functionality, solder joint quality emerges as a vital factor for ensuring the electrical and mechanical integrity of electronic assemblies. The ability to predict solder joint height prior to the reflow process is key for real-time quality control. This study develops a numerical simulation model to predict the cross-sectional height of solder joints based on how molten solder wets the surfaces of pads and chip terminations during reflow. To align theoretical models with actual outcomes, machine learning is employed to refine prediction results by establishing correlations between chip placement and the cross-sectional area of solder joints. This method not only offers accurate predictions of solder joint height quickly and simply but also provides model interpretability, thus improving decision-making in the manufacturing process.

关键词： Solder joint height Numerical simulation Machine learning Physical knowledge

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Concrete Fault Detection Using Deep Learning: Towards Waste Reduction in Bridge Inspection 33rd

Concrete Fault Detection Using Deep Learning: Towards Waste ...

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33rd International Conference on Flexible Automation and Intelligent Manufacturing

作者： Shahin, Mohammad Chen, F. Frank Maghanaki, Mazdak Hosseinzadeh, Ali Firouzranjbar, Shadi Koodiani, Hamid Khodadadi Univ Texas San Antonio Dept Mech Engn San Antonio TX 78249 USA Univ Texas San Antonio Dept Civil Engn San Antonio TX 78249 USA

ISBN: (纸本)9783031744815;9783031744822

Bridge inspections across the United States represent a significant commitment of resources, given their biannual mandate for many structures. With a notable number of aging bridges, there's an imperative need to enhance the efficiency of these inspections. This study harnessed the power of computer vision, integrating it with the principles of waste reduction from Lean manufacturing, to streamline the inspection process. We examined the efficacy of 15 distinct deep learning Convolutional Neural Network (CNN) models, including well-known architectures like Inception, VGG16, Xception, LeNet, and a tailor-made CNN. These models were applied to a data set of 40,000 high-quality images from the Concrete Images for Classification dataset. With their heavy reliance on time and resources, traditional fault detection methods often fall short. In contrast, the deployed models, with accuracy rates reaching up to 99%, showcase a significant potential in promptly identifying concrete anomalies, enhancing safety, conserving resources, and potentially saving lives. VggNet proved the fastest (3.5 h), and LeNet the slowest (100.10 h. Considering their similar performance in other metrics, VggNet stands out as the preferred model for concrete inspection. The custom CNN model also performed well in comparison.

关键词： Deep Learning bridge inspection Convolutional Neural Network Lean manufacturing waste reduction

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Stability Issues in Adaptive Cruise Control Systems and Traffic Implication 16th

Stability Issues in Adaptive Cruise Control Systems and Traf...

引用

16th International Symposium on Advanced Vehicle Control

作者： Dona, Riccardo Mattas, Konstantinos Albano, Giovanni Vass, Sandor Ciuffo, Biagio European Commiss Joint Res Ctr I-21027 Ispra VA Italy Piksel Italia Milan Italy

ISBN: (纸本)9783031703942;9783031703928;9783031703911

Adaptive Cruise Control (ACC) systems under short headway configurations have been found to have a potentially detrimental impact on the transport network due to the string instability effect. Such phenomenon results in traffic perturbations amplification downstream causing increasing fuel consumption and posing safety threats. However, recent findings summarized in this paper show how even the simpler platoon stability might not be attained with current ACC-equipped vehicles raising additional concerns regarding their unregulated operation. In fact, as part of a recent campaign involving state-of-the-art assisted vehicles, an ACC displayed a low-frequency oscillatory behavior around the equilibrium speed. This work, by leveraging a mixed simulation/empirical approach, uncovers the harmful influences of such behavior. Ultimately, we found that despite the poor stability phenomenon might not be impactful for one vehicle, the overall repercussions on the transportation network can be dramatically detrimental raising the need for a regulatory framework for lower-level automation.

关键词： Adaptive Cruise Control Asymptotic/String Stability

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The Influence of Injection Parameters on the Thermomechanical Properties of a Polyamide Product 8th

The Influence of Injection Parameters on the Thermomechanica...

引用

8th International Scientific-Technical Conference (MANUFACTURING)

作者： Olszewski, Tomasz Matykiewicz, Danuta Poznan Univ Tech Fac Mech Engn Poznan Poland

ISBN: (纸本)9783031564659;9783031564635

The aim of this work was to assess the influence of injection process parameters on the thermal and thermo-mechanical properties of polyamide products. The thermal properties were assessed by means of differential scanning calorimetry (DSC) as well as Vicat softening temperatures (VST) were evaluated. In addition, the dimensional stability and weight of the finished products were assessed. The injection process was carried out at variable mold temperatures of 35 degrees C, 60 degrees C and 80 degrees C, respectively and variable packing pressures. In addition, the products were conditioned in water and in a conditioning chamber. In this work, it was shown that mold temperature as well as packing pressure influence the level of crystallinity. Additionally, it was confirmed that the conditioning of parts changes their overall dimensions.

关键词： polyamide injection parameters thermal and thermomechanical properties

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Modeling of Viscoelasticity of Thermoplastic Polymers Employed in the Hot Embossing Process 14th

Modeling of Viscoelasticity of Thermoplastic Polymers Employ...

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14th International Conference on Numerical Methods in Industrial Forming Processes (NUMIFORM)

作者： Rabhi, F. Cheng, G. Barriere, T. Univ Franche Comte CNRS Inst FEMTO ST F-25000 Besancon France Univ Orleans Univ Tours INSA CVL LaMe 3 Rue La ChocolaterieCS 23410 F-23410 Blois France

ISBN: (纸本)9783031580086;9783031580062;9783031580055

The manufacturing of micro-scale components requires mastery of shaping processes ranging from micromechanics to electronic microfabrication. The hot embossing (HE) process is widely developed in various fields, since it allows to emboss complex structures at themicro/nanoscale such as optical sensors, diffractive lenses, microfluidic channels, and so on. The development of micro-structured parts via this process requires an in-depth analysis of the surface quality obtained and the mold filling rate. It is essential to analyze the influence of polymer properties to optimize the final mold filling to reduce cycle time and obtain defect-free replicated components. In this research, compression tests were carried out with poly(methyl methacrylate) (PMMA) and polycarbonate (PC), at different forming temperatures to determine their behavior law properties. Numerical simulation of the polymer forming processing was carried out by using Abaqus finite element software, taking into account the mechanical properties of both polymers and the characteristics of microchannels. The aim was to analyze the effect of the elastic-viscoplastic properties of the materials on the mold filling rate at different temperatures. Numerical simulation of the HE process with PMMA shows that the mold cavity is completely filled with elastic-viscoplastic behaviors, and the filling rate increases as a function of mold displacement. On the other hand, for PC, the embossed temperature has an influence on the filling ratio of the mold.

关键词： Hot embossing Viscoplastic model Numerical simulation

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