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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101-110 订阅

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Measurement of Contact Travel of High Voltage Circuit Breaker Based on GMR Sensor 3

Measurement of Contact Travel of High Voltage Circuit Breake...

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3rd international conference on Electrical engineering and Control Science, IC2ECS 2023

作者： Wang, Congge Chen, Keming Kong, Xiuting School of Electronics and Information Engineering Hangzhou Dianzi University Hangzhou China

ISBN: (纸本)9798350382426

To address the issue of contact travel measurement in high-voltage circuit breaker, a non-contact off-axis angle measurement scheme based on the giant magnetostrictive effect is proposed. By studying the structural principles of high-voltage circuit breakers and comparing existing sensor schemes, a non-contact measurement method is selected to avoid the loss and instability issues caused by severe vibration in traditional contact-based methods. Corresponding installation structures are designed to reduce errors resulting from improper installation. By using sensors to monitor the real-time rotation angle of the contact shaft, precise angle information is obtained, and the angle values are converted into contact travel data using conversion formulas for different actuating mechanisms. experimental results show that the accuracy of this scheme can be up to 0.03°, which is able to meet the requirements for measuring contact travel in high-voltage circuit breaker. Therefore, this scheme holds significant application value in power system maintenance and fault diagnosis, providing an effective means to ensure the safe operation of power equipment. © 2023 IEEE.

关键词： Angle measurement Giant magnetoresistive sensor High-voltage circuit breaker mechanical characteristics Non-contact

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RESEARCH AND APPLICATION OF COMPONENT-BASED SOFTWARE TECHNOLOGY FOR DIGITAL FLIGHT ACCOMPANIMENT SYSTEM 3

RESEARCH AND APPLICATION OF COMPONENT-BASED SOFTWARE TECHNOL...

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3rd international conference on mechanical, Aerospace and Automotive engineering, CMAAE 2023

作者： Hu, Binxing Feng, Kai Li, Lei Aerospace Systems Engineering Shanghai Shanghai China

ISBN: (纸本)9781839539954

Due to the complexity of the electrical system composition and flight missions of new-generation launch vehicles, advanced digital technology has been adopted to ensure the successful completion of rocket flight missions and the safe and stable flight during the subsequent maintenance period. This study focuses on the construction and application of a digital twin and copilot system based on digital twin technology. By constructing a digital model of the rocket, the virtual-to-real mapping is achieved through semi-physical data-driven or telemetry data-driven approaches. This provides simulation and computational support for pre-mission simulation prediction, in-flight digital copilot, and post-mission status evaluation, which is very important in ensuring flight stability and supporting the integration of experimental *** by the emerging needs of the next generation of reusable space vehicles, an autonomous integrated guidance and control system is developed that provides a safe approach to the highly constrained and nonlinear reentry problem. © The Institution of engineering & Technology 2023.

关键词： Flight simulators

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Prediction of Gas-Liquid Flow Parameters in Pipes Based on Physics-Informed Neural Network 1

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3rd international conference on Autonomous Unmanned Systems, ICAUS 2023

作者： Ding, Nanxi Lou, Wenzhong Xuan, Weikun Zhao, Fei Zhang, Zihao School of Mechanical Engineering Beijing Institute of Technology Beijing China Beijing Institute of Technology Chongqing Innovation Center Chongqing401120 China

ISBN: (数字)9789819710874

ISBN: (纸本)9789819710867

Gas-liquid two-phase flow is a prevalent phenomenon in unmanned industrial settings, and understanding the vortex behavior in pipes is crucial for its analysis and prediction. The occurrence of vortex is intricately linked to fluid velocity, pressure distribution, and pipe geometry. Accordingly, the presence of vortex induces friction and vibration on the pipe wall, thereby impacting the mechanical properties of the pipe. Presently, many investigations on gas-liquid two-phase flow vortex in pipes rely on conventional computational fluid dynamics (CFD) methods, which suffer from lengthy computational cycles. Conversely, some studies employ deep learning techniques for flow field prediction, albeit requiring extensive data. To address these challenges, this paper simplifies the model to a homogeneous flow, exploits the physical information neural network for spatial and temporal prediction of parameters distribution in gas-liquid two-phase flow within pipes, as well as proposes the utilization of the weak-constrain 4DVar approach to refine the data. This framework resolves the computational inefficiency and data-intensive nature of CFD and NN method. Moreover, the impact of different neural network structures on prediction accuracy is investigated. By comparing with the validation data, it is observed that the method proposed in this study achieves an accuracy with an error less than 2%, which has a SOTA performance, and the prediction time is shortened to less than twenty minutes compared with the dozens of hours required by traditional CFD. © Beijing HIWING Scientific and Technological Information Institute 2024.

关键词： Vortex flow

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Data-driven surrogate model with a novel active learning strategy for failure probability estimation 23

Data-driven surrogate model with a novel active learning str...

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3rd international conference on Bioinformatics and Intelligent Computing, BIC 2023

作者： Shang, Zheyu School of Mechanical Engineering Taiyuan Institute of Technology Taiyuan China

ISBN: (纸本)9798400700200

Failure probability estimation is still a challenge due to the requirement of intensive computation resources to obtain an accurate response to the structure. This study outlines an efficient failure probability estimation approach through a data-driven surrogate model. Firstly, a coarse Kriging model is built on the design of the experiment (DoE). Then, the surrogate model is refined by a novel active learning strategy which transforms the active learning process into solving a constrained optimization problem. This study introduces a new metaheuristic algorithm called group teaching optimization (GTO) to assist in selecting the most promising samples in the proximity of the limit state surface and iteratively updating the surrogate model. The validation results reveal that the proposed Kriging-GTO method is competitive with classic reliability methods regarding computational accuracy and efficiency. © 2023 ACM.

关键词： Kriging

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Research on the Correlation of Building mechanical and Electrical Installation Material Names based on HMM-NF 3

Research on the Correlation of Building Mechanical and Elect...

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3rd international conference on High Performance Computing and Communication engineering, HPCCE 2023

作者： Ling, Rui Shanghai Installation Engineering Group Co. Ltd. Shanghai200080 China

ISBN: (数字)9781510674653

ISBN: (纸本)9781510674646

The continuous development of the construction industry has spurred the growth of mechanical and electrical (M&E) installation engineering, in which material management is a crucial component. The classification of material names in M&E installation has become increasingly prominent, with traditional manual classification not only being labor-intensive and costly but also inefficient. To address this issue, this paper introduces a Hidden Markov Model based on Named Entity Features (HMM-NF) for the study of the correlation between names of materials used in M&E installation. This model applies the Hidden Markov Model (HMM) and named entity recognition technology to classify and recognize the names of construction M&E installation materials and to establish the correlation between them. experimental results show that the model can accurately identify and match material names, specifications, units, and other data, scoring the matches in a manner that well describes the correctness of the established correlations. Furthermore, this paper compares the HMM-NF model with the traditional HMM and the Maximum Probability Segmentation Model, demonstrating that the HMM-NF model exhibits higher accuracy and efficiency during both training and segmentation, making it a reasonable and effective model. This research provides new insights and methods for material management in construction M&E installation engineering, helping to enhance the efficiency and precision of material management and thereby optimizing the management of the entire M&E installation process. Additionally, this study offers a new application and reference for the use of Hidden Markov Models in the field of construction. © 2024 SPIE.

关键词： Hidden Markov models

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Lightweight human pose estimation based on high-resolution network 3

Lightweight human pose estimation based on high-resolution n...

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3rd international conference on Machine Learning and Computer Application, ICMLCA 2022

作者： Yang, Zhiwen Yang, Ruan Yang, Yunong College of Computer and Information Science Chongqing Normal University Chongqing China College of Education Science Chongqing Normal University Chongqing China Digital Education Engineering Center for Technology and Applied Research Chongqing Normal University Chongqing China

ISBN: (纸本)9781510664814

Most of the existing methods of human pose estimation methods focus on improving the accuracy of prediction results, but due to network parameters and high computational complexity, a great deal of computing resources are needed. In this paper, a lightweight human pose estimation method based on high-resolution network is proposed. The bottleneck module and the basic module in the high-resolution network are redesigned by using the depth separable convolution instead of the ordinary convolution and integrating attention mechanism, which ensures the accuracy of the network and greatly reduces the number of parameters and computational complexity of the model. experimental results on the COCO VAL2017 dataset show an 84.5% reduction in the number of model parameters, a 73.9%% reduction in computational complexity, and 0.2% increase in the accuracy of human keypoint detection compared to the high-resolution network. © 2023 SPIE.

关键词： Convolution

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computational methods for Analysing Biometric Systems 3

Computational Methods for Analysing Biometric Systems

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

作者： Multani, Fahim Bijlwan, Sheela Upadhyay, Viyat Varun Goyal, Bhawna Dogra, Ayush Lepcha, Dawa Chyophel Ies College of Technology Bhopal Department of Computer Science Engineering Madhya Pradesh India Uttaranchal School of Computing Sciences Uttaranchal Institute of Technology Uttaranchal University Dehradun248007 India Gla University Department of Mechanical Engineering Mathura Mathura India University Center for Research and Development Chandigarh University Punjab Mohali India Chitkara University Institute of Engineering and Technology Chitkara University Punjab India Chandigarh University Department Electronics and Communication Engineering Punjab Mohali India

ISBN: (纸本)9798350342338

The use of biometric data, such as various anatomical and behavioural attributes in automatic identification and authentication systems for access control, surveillance, computer security, and law enforcement are increasing. Several nations are already or will soon begin to use biometric technology. In this paper, there is a in detail analysis of innovative biometric systems and also the research study of how the computational techniques used intelligent data system in order to analyse biometric system, The efficacy of biometric technologies will depend on how well they work. Biometric system evaluation examines how well biometric systems adapt to particular characteristics. Planning and carrying out biometric tests are frequently handled by an impartial third party. A measure of confidence in the validity of the claim might be one of the options the algorithm offers. Applications that validate a user's address or confirm their identity at the point of sale are examples of verification applications. © 2023 IEEE.

关键词： Attributes Biometric data computational techniques Innovative Research Technology

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experimental Study of Waste Plastic Oil - Pertamax (RON 92) Blend on Spark Ignition Engine Performance at High-Speed Rotation 3rd

Experimental Study of Waste Plastic Oil - Pertamax (RON 92) ...

引用

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

作者： Siregar, Muhammad Rikhwan Khairil Sofyan, Sarwo Edhy Department of Mechanical Engineering Universitas Syiah Kuala Jl. Tgk. Syech Abdurrauf No. 7 Darussalam Banda Aceh23111 Indonesia

ISBN: (纸本)9789811936289

Pyrolysis of plastic waste is an attempt to convert waste into alternative fuels. Besides being able to solve the problem of the energy crisis currently faced, it is also a solution in overcoming plastic pollution, especially HDPE, LDPE and PET. This study aims to investigate the effect of pyrolysis waste plastic oil (WPO) of HDPE;LDPE;PET as a mixture of pertamax (RON 92) fuel on the performance of a spark ignition (SI) engine at high speed rotation. The mixture of WPO-pertamax is varied in percentage namely 10:90, 20:80 and 30:70, respectively. Based on the experimental results, the engine performance including the engine power, specific fuel consumption, and thermal efficiency, is then analysed. It was found that the test results on each plastic waste oil mixture obtained that PET-10 at 2500 rpm rotation where the power and specific fuel consumption it produces are 2.98 HP and 0.32 kg/Kwh. Thermal efficiency of 18.95%. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Pyrolysis

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experimental Evaluation of Independent Component Analysis Design with Enhanced Performance Metrics using ALJM 3

Experimental Evaluation of Independent Component Analysis De...

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3rd IEEE international conference on Intelligent Technologies, CONIT 2023

作者： Saranya, C. Sridhar, V. Sriram Sundhar, K. Praveen, R. K.S.Rangasamy Collage of Technology Eletronics and Communication Engineering Thiruchengode India

ISBN: (纸本)9798350338607

The goal of Independent Component Analysis (ICA) is to use statistical and computational methods to determine the underlying structure of a data collection consisting of independent variables, metrics or signals. The analyzed data with multiple variables is usually provided as a massive collection of instances and Independent Component Analysis creates a generative framework for this information. Several interesting hardware architectures for implementing Fast Independent Component Analysis are available, such as: Application Specific Integrated-Circuit (ASIC), Field-Programmable Gate Array (FPGA) and so on. In order to carry out the Eigen-Value-Deconstruction (EVD) necessary for the execution of Fast-ICA, a novel approach called the ALgebraic Jacobi Method (ALJM), is proposed. This ALJM simplify the calculation of the Jacobi rotations by making use of an approximate polynomial estimate and the Newton Raphson technique. The complexity of computation and energy usage of Fast-ICA are reduced without sacrificing its calculation speed by reusing hardware throughout both the Eigen-Value-Deconstruction phase and the Weight-Vector Estimation (WVE) phase. By applying Blind-Source-Separation (BSS) to linear combinations of predictable and unpredictable signals, the performance of the Fast-ICA assisted ALgebraic Jacobi Method is assessed and compare the findings to those of existing approaches. A Scalable-Systolic-Processing-Array (SPA) is proposed for the Fast ICA assisted ALJM and build it on Spartan6 FPGA after ensuring its performance and statistical consistency. The ALJM-based Fast ICA is concluded as one of the best and most effective methodologies for creating and distributing an ongoing deployable solution incorporating Fast-ICA by comparing it to current Fast-ICA implementations in terms of runtime, memory footprint, and power consumption. The envisioned symmetric computational array is designed in verilog-HDL, modeled with ModelSim-6.4C and synthesized with Xilinx S

关键词： Blind source separation

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Comparison and Selection of Modeling methods for Material Removal Power in Cylindrical Turning 3rd

Comparison and Selection of Modeling Methods for Material Re...

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3rd international conference on Smart Manufacturing, Industrial and Logistics engineering, SMILE 2023 and the 7th Asian conference of Management Science and Applications, ACMSA 2023

作者： Jia, Shun Wang, Shang Li, Anbang Yang, Yang Shandong University of Science and Technology Qingdao266590 China

ISBN: (纸本)9789819701933

Cylindrical turning, as one of the most common machining methods in mechanical processing, accurately evaluating the power during the material removal process in cylindrical turning is a prerequisite and foundation for achieving energy optimization in mechanical machining processes. Currently, there are three main modeling methods for the material removal power in cylindrical turning: First, calculating the material removal power through the specific energy of cutting per unit volume (Method I);Second, calculating the material removal power through cutting forces (Method II);Third, calculating the material removal power through power measurement combined with statistical analysis (Method III). However, there is currently no general agreement on the effectiveness and applicability of these three modeling methods. Therefore, the purpose of this study is to compare and evaluate these three modeling methods through cylindrical turning experiments. The experimental results indicate that Method II has the smallest prediction error, with an average error of 4.91%. Method III follows with prediction errors all below 8.57%. Method I has the largest prediction error, with the maximum error reaching 31.09%. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Cutting

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