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检索条件"任意字段=3rd International Conference on Computational and Experimental Methods in Mechanical Engineering"

共 1766 条记录，以下是151-160 订阅

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A Numerical Method for a Problem Occurring in Conduction of Heat Through a Solid and Other Applications 3rd

A Numerical Method for a Problem Occurring in Conduction of ...

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3rd international conference on computational and experimental methods in mechanical engineering, ICCEMME 2021

作者： Gupta, Shradha Sharma, Sanjeev Department of Applied Sciences GL Bajaj Institute of Technology and Management Greater Noida Uttar Pradesh India

ISBN: (纸本)9789811628566

A singular boundary value problem arises in the conduction of heat through a solid and having other important applications is solved using a novel spline method. The removal of the singularity is done before applying a cubic B-spline and then a B-spline with a free parameter. The numerical examples show that the results have a very close agreement with exact solutions. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Numerical methods

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Study of Thermal Uniformity and Heat Displacement Characteristics in Multi-stage Drying Equipment 3rd

Study of Thermal Uniformity and Heat Displacement Characteri...

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3rd international conference on experimental and computational Mechanics in engineering, ICECME 2021

作者： Fikri, Thaharul Syuhada, Ahmad Thaib, Razali of Mechanical Engineering Program Department of Mechanical and Industrial Engineering Faculty of Engineering Universitas Syiah Kuala Banda Aceh Indonesia

ISBN: (纸本)9789811936289

Traditional drying still lacks one of the lengths of the curing process that takes 2–4 days depending on the condition of the sun, unlike the modern way of using dryer equipment. Previous research had created a multistoried dryer, but there was still a considerable temperature difference between the shelves. The study aims to reexamine the distribution of temperatures that occur in high-rise dryer equipment. Prior research has designed dryer appliances with a leveling 9 levels of hot gas line and a sharp turning fins, 45-degree bend on the left and right sides of the instruments. Still, they do not achieve the same temperature consistency in the dryer room. Achieving the right temperature in each dryer requires reshaping the fins of a hot gas line. From the long changes to the hot gas line, an efficient fin variation, a size of 35 mm in the gas duct, followed by a 5 mm increase in the last fin at the first deposit of 60 mm, but at the other end of the hot gas line at 7, 8, 9, was shut, with the experiment producing an evenly matched temperature between 1–2 ºC. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Dryers (equipment)

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experimental Validation of Damage Detection in Concrete Beams Under Impact Load Using Piezo Sensors 1

引用

3rd international conference on Recent Advances in Materials, Manufacturing and Thermal engineering, RAMMTE 2022

作者： Sajith, Arya Pal, Shilpa Delhi Technological University Shahabad Daulatpur Main Bawana Road Delhi India

ISBN: (数字)9789811985171

ISBN: (纸本)9789811985164

Over the past few years, damage detection and structural health monitoring have gained a lot of interest in the civil engineering field. Smart materials such as lead zirconate titanate (PZT) is being widely used to detect damages in a structure with the help of electro-mechanical impedance (EMI) technique. The EMI technique uses both the direct and converse piezoelectric effect which allows the PZT sensor to act as both the actuator and the sensor. The PZT patches uses high-frequency responses to detect damage. Changes in admittance signature indicates the damage, and this is quantified by using root mean square deviation index (RMSD). In this study, experimental investigation of a plain concrete beam with embedded PZT sensors under impact load is used to find the extent of damage detection properties of PZT sensors. From the study, it can be concluded that the RMSD percentage value and peak value of admittance signature are increasing with each impact which indicates the increase in extent of damage with each impact. It can be concluded that EMI technique has proven to be one of the effective methods for structural health monitoring. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Damage detection

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Improved Personnel Statistics Algorithm for Construction Main Working Face Based on YOLOv5 3

Improved Personnel Statistics Algorithm for Construction Mai...

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3rd international conference on Intelligent Communications and Computing, ICC 2023

作者： Zhang, Xulin Chen, Binjin Liu, Peng Gong, Hao Su, Yawu Qi, Ligang Yunhan Times Digital Technology Co. Ltd China Construction Eighth Engineering Division. Corp. Ltd. Shanghai China The Second Construction Company China Construction Eighth Engineering Division. Corp. Ltd. Shanghai China

ISBN: (纸本)9798350308327

The statistics of the number of personnel on the construction main working face is one of the important indicators for identifying construction progress, and is of great significance for the refined management and resource allocation of construction projects. The deep learning object detection algorithm can effectively replace the existing manual statistics method, reduce mechanical and time-consuming statistical work, and improve statistical accuracy. However, existing object detection algorithms have technical shortcomings such as information loss, insufficient features, and scale imbalance in detecting such small-sized entities. Therefore, this study improves the YOLOv5 object detection algorithm through methods such as image enhancement, multi-scale samples, data enhancement, and model improvement. The experimental results show that our improved algorithm achieves a mean average precision of 83.3%, significantly improving accuracy and robustness, and effectively solving the problem of detecting small and medium-sized personnel in the captured images of the construction main working face. © 2023 IEEE.

关键词： Object detection

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Image Classification Model Based on Self-supervised Deep Learning 3

Image Classification Model Based on Self-supervised Deep Lea...

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3rd international conference on Advanced Algorithms and Neural Networks, AANN 2023

作者： Xiao, Jiankun School of Mechanical Engineering Dalian University of Technology China

ISBN: (纸本)9781510668355

Image classification methods are extremely devised to dispose the predictions of images labels through extracting the features. Existing methods mainly utilize unsupervised deep learning method, which will cause numerous computation costs and require human to label the images data set. Therefore, we propose a novel self-supervised deep learning method to solve the image classification issue. Initially, we extract the feature vectors of input data through utilizing a residual network. Subsequently, the self-supervised framework is established with a loss function to optimize the training results. At last, we simulate our proposed method on CIFAR-10 and MNIST classification tasks data set to evaluate the performance and compare our method with existing unsupervised learning methods. From our continuous experimental results and comparison simulations, we can conclude that our devised method can achieve the classification tasks for various input images with reasonable computation costs. © 2023 SPIE.

关键词： Image classification

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The Role of AI in Biochips for Early Disease Detection 3

The Role of AI in Biochips for Early Disease Detection

引用

3rd international conference on Technological Advancements in computational Sciences, ICTACS 2023

作者： Sukumaran, C. Indhumathi, K. Balamurugan, P. Ambilwade, R.P. Sunthari, P. Mohana Natrayan, L. Government Law College Tamilnadu Thiruchirappalli620023 India Saveetha Engineering College India Vel Tech Multi Tech Dr. Rangarajan Dr. Sakunthala Engineering College Department of Mathematics Chennai India National Defence Academy Pune Department of Computer Science India K S R Institute for Engineering and Technology India Saveetha School of Engineering Simats Department of Mechanical Engineering Tamil Nadu Chennai602105 India

ISBN: (纸本)9798350342338

Improvements in illness diagnosis made possible by combining AI with biochip technology. It highlights the use of AI to improve the sensitivity and efficiency of biochips, allowing for faster and more precise illness diagnosis. Current healthcare uses of biochips are discussed, as well as artificial intelligence methods that may be used to the processing of biochip data. Through a variety of case studies, it shows how AI may be used for real-world tasks including early detection of cancer and other diseases through its capacity to analyze complicated data and perform predictive analysis. Data privacy, ethical considerations, and the need for extensive datasets to train AI are all discussed in the study as well as other obstacles to integrating AI with biochips. Furthermore, the legal implications of implementing new healthcare technology are covered. Future research options are suggested, with an emphasis on the importance of multidisciplinary cooperation and the possible effect of AI in biochip design. © 2023 IEEE.

关键词： Artificial Intelligence (AI) Biochips Data Privacy Healthcare Technology Predictive Analysis

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Designing a Predictive Maintenance-Based Algorithm for DC Motor Fault Detection and Classification 3

Designing a Predictive Maintenance-Based Algorithm for DC Mo...

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3rd international conference on Technological Advancements in computational Sciences, ICTACS 2023

作者： Satria, Habib Dhabliya, Dharmesh Srisainath, R. Edwin Prabhakar, P.B. Sivakamasundari, S. Universitas Medan Area Faculty of Engineering Medan Indonesia Viit Department of It Maharashtra Pune India Psvp Engineering College Chennai India New Prince Shri Bhavani College Chennai India Npsb College Chennai India

ISBN: (纸本)9798350342338

DC motors, integral to numerous sectors, transform electrical energy into mechanical action. Their critical role necessitates reliable operation, but inherent vulnerabilities can cause unplanned breakdowns, resulting in operational and financial implications. Traditional maintenance methods often overlook early malfunction signs, leading to production halts or unwarranted repairs. In contrast, predictive maintenance offers a forward-looking approach by leveraging sensor data and modern analytics to monitor equipment health proactively. This study introduces an advanced predictive maintenance algorithm for DC motors, combining data-driven strategies such as machine learning with sensory data assimilation. This comprehensive algorithm not only aims to boost operational efficiency but also to enhance fault detection accuracy. As DC motors remain vital in industrial operations, the pressing need for precise fault detection and categorization using cutting-edge techniques becomes increasingly evident. © 2023 IEEE.

关键词： classification DC motor fault detection Machine learning predictive maintenance

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Stress Analysis on the Lower Arm and Coil Spring of an Automotive Due to Dynamic Loadings 3rd

Stress Analysis on the Lower Arm and Coil Spring of an Autom...

引用

3rd international conference on experimental and computational Mechanics in engineering, ICECME 2021

作者： Marjuni, Teuku Husaini Edisah Putra, Teuku Department of Mechanical Engineering Universitas Syiah Kuala Banda Aceh Indonesia

ISBN: (纸本)9789811936289

This study aims to analyze the stresses that occur in the lower arm and coil spring of an automotive subjected to dynamic loads. The strain signals produced from the lower arm and coil spring of a car were used as the loads in these dynamic analyses. Based on the simulation results, the stress that occurs in the lower arm was 244,612 kPa or only 54.35% of the yield strength of the SAE 1513 carbon steel. Meanwhile, the stress on the coil spring was 542,893 kPa or only 36.5% of the yield strength of the SAE 5160 carbon steel. In conclusion, the risk of failure of the lower arm is greater than the coil spring. Although the stresses that occurred were relatively small compared to the yield strength of the material, these stresses can still cause failure because the component receives loads continuously. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Yield stress

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Statistical Shape Modelling as a Tool for Medical Reverse engineering 3rd

Statistical Shape Modelling as a Tool for Medical Reverse En...

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3rd international conference on Design Tools and methods in Industrial engineering, ADM 2023

作者： Sciortino, Vincenza Ingrassia, Tommaso Cerniglia, Donatella Pasta, Salvatore University of Palermo Palermo90128 Italy Department of Research IRCCS-ISMETT Palermo90100 Italy

ISBN: (纸本)9783031520747

Manipulating patient data acquired by Computer tomography (CT), e.g., anatomical shape and geometry, as well as studying the biomedical devices used in patient care, is certainly of remarkable importance. Here, Medical Re- verse engineering (MRE) and Rapid Prototyping (RP) play a key role in the 3D models reconstruction of patient anatomy, that can be exploit to make patient- specific, custom-made devices. The inherent variability of the human anatomy can be a problem, which is why the concept of custom-made devices is men- tioned. In this field, MRE exploits the computational tools provided by Statistical Shape Modelling (SSM) and Principal Component Analysis (PCA) to achieve computer modelling of 3D data from real models. The PCA is a statistical tool for reducing the number of variables in a population, while the SSM enables the development of an infinite digital population of a given anatomy. This paper aims to show the potential of SSM in the field of the MRE. The study will focus on the pathological lumbar spine. Here, SSM provides new pathological geometries of the lumbar spine, which can be extrapolated and used to produce customized biomedical devices for that given pathological deformation, as well as to perform Finite Element (FE) simulations. Therefore, utilising SSM can bring an addi- tional edge to MRE, due to the infinite population of CAD models of patient anatomy, which can be useful in the medical industry, as already pointed out. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Principal component analysis

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Degradation and Fatigue Life methods for Ceramic Matrix Composite and Nickel Superalloy Materials in Gas Turbine Combustor Liner 33rd

Degradation and Fatigue Life Methods for Ceramic Matrix Comp...

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33rd international conference on Flexible Automation and Intelligent Manufacturing

作者： Karadimas, Georgios Pagone, Emanuele Georgarakis, Konstantinos Salonitis, Konstantinos Cranfield Univ Sustainable Mfg Syst Ctr Sch Aerosp Transport & Mfg Cranfield MK43 0AL Beds England

ISBN: (纸本)9783031744815;9783031744822

This paper investigates the durability of Ceramic Matrix Composite (CMC) and Nickel Superalloy materials in gas turbine combustor liners across different flight conditions. Thermo-mechanical and physical properties of CMCs are assessed and compared with selected superalloys (i.e., Inconel 625, Hastelloy X, SiC/SiC, Al2O3/B4C, and Al2O3/SiO2) using Finite Element Analysis (FEA). An integrated methodology employing computational Fluid Dynamics (CFD) and FEA is introduced to analyze thermal stresses and fatigue life, establishing a direct connection between combustion dynamics and structural responses. The study addresses a research gap by thoroughly evaluating CMC materials in gas turbine combustor liners, offering valuable insights for material selection and design strategies in aerospace engineering. The findings enhance understanding of CMC behavior, showcasing their reliability and durability for gas turbine components and their usage for advancements in aerospace applications.

关键词： Ceramic Matrix Composites (CMCs) Nickel Superalloys Aerospace applications Durability assessment

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