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2022 IEEE International Conference on electrical, computer, and Energy Technologies, ICECET 2022

作者： Jelacic, Zlata Dedic, Remzo University of Sarajevo Facilty of Mechanical Engineering Department of Mechanics Sarajevo Bosnia and Herzegovina University of Mostar Faculty of Mechanical Eng. Computer Science and Electrical Engineering Mostar Bosnia and Herzegovina

ISBN: (数字)9781665470872

ISBN: (纸本)9781665470872

Development of an actuated prosthetic device for transfemoral amputees is a complex task. Largest number of amputees make use of the passive prostheses which are not powered in any way and cannot give any additional output of energy to its user. Such prosthetic devices usually use elastic or some other potential energy which is stored during one sequence of gait, and then released in another. However, in order to perform tasks which require high power, such as stair ascent, this presents a problem. Lack of muscles makes it impossible to produce the required forces. Hence, the prosthetic devices must be powered, primarily in its main joints - knee and ankle. In this paper, element topology optimization of smart above knee prosthesis whose functionality is based on virtual intelligence is carried out. Lower leg model with topological optimized structure is created according to the stress analysis results obtained by usage of Ansys mechanical Software. The two conceptual solutions based on above mentioned model are created by using SolidWorks Software. Numerical stress analysis of conceptual solutions, discussion and conclusion are performed in the final part of paper. © 2022 IEEE.

关键词： 3D printers

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Implementation of Block Chain, IoT and Role-basis Data Access Control (RBAC) for Intelligent Manufacturing 7

Implementation of Block Chain, IoT and Role-basis Data Acces...

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7th International Conference on Inventive Computation Technologies, ICICT 2024

作者： Kaushal, Rajanish Kumar Kumar, S. M. Ravi Chellaiah, Pandeeswaran Pundir, Sumit Maranan, Ramya Krishnaiah, Nallam Chandigarh University Department of Electrical Engineering Mohali Punjab Gharuan India G. Pullaiah College of Engineering And Technology Department of Mechanical Engineering Andhra Pradesh Kurnool518452 India St. Joseph's College of Engineering Department of Computer Science And Engineering Tamil Nandu Chennai600119 India Graphic Era Deemed To Be University Department of Computer Science & Engineering Uttarakhand Dehradun248002 India Saveetha School of Engineering SIMATS Department of Research And Innovation Tamil Nadu Chennai India St.Martin's Engineering Department of Information Technology Telangana Secunderabad500100 India

ISBN: (纸本)9798350359299

Various recommendations for predicting the dependability and quality of equipment contribute to the success of intelligent manufacturing systems. Numerous Role basis access control (RBAC) techniques are being investigated for this purpose. Data security and administration is another industry concern that is regarded as crucial. To surmount the challenges, The proposed work integrates block chain and Role basis access control (RBAC) to secure system transactions and manage a dataset to combat the forgery dataset. Big data techniques were used to manage and examine the collected dataset. Based on the hybrid prediction technique, the aspect of defect diagnosis prediction was evaluated on-linear Role basis access control (RBAC) techniques which are mainly used for estimating the system's complex background and figuring out its true positive rate. This was done to evaluate the proposed system's quality control. © 2024 IEEE.

关键词： Access control

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Mitigating Voltage Fluctuations in Grid-Tied PV Systems: Power Quality Enhancement 3

Mitigating Voltage Fluctuations in Grid-Tied PV Systems: Pow...

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3rd International Conference on Computational Modelling, Simulation and Optimization, ICCMSO 2024

作者： Khan, Sheena Tahira Joshi, Vilas Ramrao Bhardwaj, Deepak Sharma, Surender Kumar Waheed, Shaikh Abdul Sharma, Deepak K. Poornima University Department of Electrical Engineering Jaipur India ISBM College of Engineering Department of Computer Engineering Maharashtra Pune India Dr. Akhilesh Das Gupta Institute of Professional Studies Department of Mechanical Engineering New Delhi India GH Raisoni College of Engineering and Management Pune India Savitribai Phule Pune University Department of Artificial Intelligence and Data Science Maharashtra Pune India

ISBN: (纸本)9798350361391

This paper investigates voltage fluctuations in grid-tied Photovoltaic (PV) systems, employing advanced methodologies within a 10 kW experimental setup that incorporates SunTech STP330-24/Vfw panels, an Advanced Power Electronics Inverter, and real-time monitoring, supported by MAT-LAB/Simulink simulations. Robust data collection utilizes real-time monitoring, data loggers, and a power quality analyzer, with calibration against simulated outputs. The integration of smart inverters, advanced control algorithms, real-time monitoring, energy storage, grid-interactive power electronics, and Hardware in the Loop simulation showcases substantial enhancements in power quality, stability, and response times. Key findings include minimal voltage fluctuations (0.25 V), a power quality index of 0.92, and rapid response times (12 ms). Comparative analyses validate proposed methodologies, emphasizing implications for heightened reliability, potential widespread adoption of advanced PV technologies, and informed policymaking for cleaner energy. This study makes a significant contribution to renewable energy goals, with suggested avenues for future research focusing on adaptability, buffering enhancement, iterative testing, and economic feasibility assessments, ensuring the continuous evolution of resilient and eco-friendly energy solutions. © 2024 IEEE.

关键词： Hardware-in-the-loop simulation

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Single-input single-output multi-touch soft sensor systems using band-pass filters

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npj Flexible Electronics 2022年第1期6卷 681-690页

作者： Junhyung Kim Suhan Kim Yong-Lae Park Department of Mechanical Engineering Institute of Advanced Machines and DesignInstitute of Engineering ResearchSeoul National UniversitySeoul 08826Republic of Korea Department of Electrical Engineering and Computer Science Research Laboratory of ElectronicsMassachusetts Institute of Technology77 Massachusetts AvenueCambridgeMA 02139USA

In many soft sensor systems,external wires for connecting the sensors to control circuits have posed practical problems,in terms of compact form factors and physical *** study proposes a design of soft sensor arrays that can operate with a drastically reduced number of wires without degrading the original *** proposed concept is an array of soft sensing modules,each of which consists of an inductor and a capacitor embedded next to the resistive sensing module,constructing a resistorinductor-capacitor band-pass *** adjusting the values of the capacitance and the inductance,unique frequency band is assigned to each sensing module,enabling the distinctive detection using only two external wires regardless of the number of *** multi-touch sensing functionality of the system is analytically modeled and experimentally *** advantage of the design,a fingertip tactile sensor and an insole foot pressure sensor are demonstrated as practical applications.

关键词： connecting constructing touch

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SODIUM-ION BATTERY CYCLE LIFE PREDICTION USING MACHINE LEARNING

SODIUM-ION BATTERY CYCLE LIFE PREDICTION USING MACHINE LEARN...

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International Conference on Green Energy, Computing and Intelligent Technology 2024, GEn-CITy 2024

作者： Liu, Linfeng Juwono, Filbert H. Wong, W.K. Purwanto, Erick Jin, Tingyan Zhen, Yuyang Sustainable Energy Technology Program Xi'an Jiaotong-Liverpool University Suzhou China Department of Electrical and Electronic Engineering Xi'an Jiaotong-Liverpool University Suzhou China Department of Electrical and Computer Engineering Curtin University Malaysia Miri Malaysia Department of Computing Xi'an Jiaotong-Liverpool University Suzhou China School of Mechanical and Electrical Engineering Beijing Information Science and Technology University Beijing China School of Instrument Science and Technology Beijing University of Technology Beijing China

ISBN: (纸本)9781837242689

In this study, we explore the classification and prediction capabilities of three models-Genetic Programming (GP), Logistic Regression (LR), and the Kolmogorov-Arnold Network (KAN)-on the task of sodium-ion battery life prediction. By leveraging a dataset composed of multiple battery characteristics, we aim to determine the remaining power of sodium-ion batteries using these machine learning models. The KAN model, being a novel approach, demonstrates superior performance across various metrics, including accuracy, precision, recall, and F1 score, when compared to the other two models. This highlights the potential of KAN as a robust model for complex classification tasks in the field of battery life prediction. © The Institution of engineering & Technology 2024.

关键词： Genetic programming

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SINCHDrone Technology Demonstration UAV Hybrid Incorporating Power Regeneration Technologies & Weight Minimization

SINCHDrone Technology Demonstration UAV Hybrid Incorporating...

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2023 IEEE Conference on Technologies for Sustainability, SusTech 2023

作者： Kudebeh, Kyrie Baez, Jeff Austin, Liam Yu, Zhen Lo, Alton Dobbs, Steven K. Rico, Joseph California State Polytechnic University Pomona Electrical and Computer Engineering Department PomonaCA United States California State Polytechnic University Pomona Aerospace Engineering Department PomonaCA United States California State Polytechnic University Pomona Mechanical Engineering Department PomonaCA United States

ISBN: (纸本)9798350345483

In this paper, an in-flight power regeneration and structural battery integration approach were employed to increase the endurance, range, and therefore mission capability of a VTOL (Vertical Takeoff and Landing) fixed-wing UAV (Unmanned Aerial Vehicle) by a multidisciplinary student team in California State Polytechnic University, Pomona. The average flight time for a UAV drone has a maximum flight time of 30 minutes, limiting the number of applications that can be used. Although military drones have flight time measured in hours, their cost, size, and complexity eliminate them from commercial use even after they may be retired from military use. Project BANSHEE's overarching goal is to increase the range and endurance of a UAV in a compact and economical manner. This is to be achieved by the integration of power generation and storage equipment into the load-bearing structure of the airframe. Doing so will decrease the parasitic weight from external components and extend the battery life of the craft, allowing for longer flight time. Modifications to currently available drones such as the Storm4 are being made in order to perform autonomous flight plans and in the future: return to home base when battery is low, exchange depleted battery with new one while maintaining power through induction charging. © 2023 IEEE.

关键词： Drones

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Data-driven modeling of dislocation mobility from atomistics using physicsinformed machine learning

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npj Computational Materials 2024年第1期10卷 937-948页

作者： Yifeng Tian Soumendu Bagchi Liam Myhill GiacomoPo Enrique Martinez Yen Ting Lin Nithin Mathew Danny Perez Information Sciences Group ComputerComputational and Statistical Sciences Division(CCS-3)Los Alamos National LaboratoryLos Alamos87545 NMUSA Physics and Chemistry of Materials Theoretical Division(T-1)Los Alamos National LaboratoryLos Alamos87545 NMUSA Center for Nanophase Materials Sciences Oak Ridge National LaboratoryOak RidgeUSA Department of Materials Science and Engineering Clemson UniversityClemson29623 SCUSA Department of Mechanical and Aerospace Engineering University of MiamiMiami33146 FLUSA

Dislocationmobility,which dictates the response of dislocations to an applied stress,is a fundamental property of crystalline materials that governs the evolution of plastic *** approaches for deriving mobility laws rely on phenomenological models of the underlying physics,whose free parameters are in turn fitted to a small number of intuition-driven atomic scale simulations under varying conditions of temperature and *** tedious and time-consuming approach becomes particularly cumbersome for materials with complex dependencies on stress,temperature,and local environment,such as body-centered cubic crystals(BCC)metals and *** this paper,we present a novel,uncertainty quantification-driven active learning paradigm for learning dislocation mobility laws from automated high-throughput large-scale molecular dynamics simulations,using Graph Neural Networks(GNN)with a physics-informed *** demonstrate that this Physics-informed Graph Neural Network(PI-GNN)framework captures the underlying physics more accurately compared to existing phenomenological mobility laws in BCC metals.

关键词： stress dislocation consuming

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Citrus objects recognition in orchard scene using HSV methods

Citrus objects recognition in orchard scene using HSV method...

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2024 International Conference on Image Processing and Artificial Intelligence, ICIPAl 2024

作者： Hua, Yanzhi Wu, Shuqin Liang, Liling Jiang, Minghui Fan, Yong Xie, Wu School of Mechanical and Electrical Engineering Guilin University of Electronic Technology Guilin541004 China School of Architecture and Transportation Engineering Guilin University of Electronic Technology Guilin541004 China School of Computer Science and Information Security Guilin University of Electronic Technology Guilin541004 China

ISBN: (纸本)9781510681514

There is a problem that it is always difficult for picking and spraying robots to identify the objects for such factors such as leaf occlusion, similar color and others. In this paper, based on the citrus image data set collected from the actual orchard scene, image features are extracted and a mathematical model is constructed to identify and count the number of citruses in each image, and the distribution of apples in the whole data set is displayed. A model is constructed to be used to identify and count citrus via these images with diversity of citrus colors and the complexity of the background. Firstly, the yellow mature citruses are focused on using the HSV (Hue, Saturation, Value) method for the data sets. Secondly, the empirical HSV range for two citrus fruits, cyan and yellow, was defined, and contour processing is introduced to optimize the recognition model to process more citrus image datasets. Finally, such three types of objects as immature citrus, leaves with similar colors, and citrus covered by leaves are distinguish. The research results indicate that we adopt more detailed color threshold settings and morphological operations with the eccentricity of the contour is less than 0.85, and can distinguish citrus and leaves through image segmentation,and the recognition effect on citrus objects is improved. © 2024 SPIE.

关键词： Morphology

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A Variable Gain Discrete Time Sliding Mode Observer for MMC Capacitor Voltage Estimation

A Variable Gain Discrete Time Sliding Mode Observer for MMC ...

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China International electrical and Energy Conference (CIEEC)

作者： Yao Lei Li Tianhao Zhou Xinyu Dong Xuanang Zhang Yufei College of mechanical engineering University of Shanghai for Science and Technology School of Optical-Electrical and Computer Engineering University of Shanghai for Science and Technology College of Information and Electrical Engineering China Agricultural University

ISBN: (数字)9798350359558

ISBN: (纸本)9798350359565

Modular Multilevel Converter (MMC) is one of the main development directions in the future medium and low voltage DC transmission and distribution field. In engineering, capacitive voltage sensors are usually configured for all submodules to ensure high reliability measurement, but this makes the hardware structure more complex. This paper proposes a control algorithm for online adjustment of observer gain based on discrete-time sliding mode observer (DTSMO). A weighted error judgment energy function is defined and three modes are distinguished. A transition mode is introduced between the approaching mode and sliding mode, and the gain within each mode is adjusted online according to the size of each component error function. This algorithm suppresses the chattering of traditional DTSMO during parameter changes and reduces the voltage error of each observed SM, this observer can eliminate all capacitive voltage sensors within a single bridge arm, and is designed based on the consideration of uncertain parameters outside of MMC. Its stability and convergence have been mathematically proven. Finally, simulation and experimental results of hardware prototypes has verified that the proposed VDTSMO observer has good steady-state and transient performance.

关键词： Phase modulation Capacitors Bridge circuits Observers Hardware Capacitive sensors Steady-state

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Dynamic Environment-Aware Lifetime Prediction of SiC MOSFET Modules Through LSTM 14

Dynamic Environment-Aware Lifetime Prediction of SiC MOSFET ...

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14th Annual IEEE Applied Power Electronics Conference and Exposition, APEC 2025

作者： Hasan, Md Zakir Choi, Seungdeog Aider, Youssef Singh, Prashant Liu, Chun-Hung Mississippi State University Department of Electrical and Computer Engineering Starkville United States University of Tennessee Department of Mechanical Aerospace & Biomedical Engineering Knoxville United States

ISBN: (纸本)9798331516116

The state-of-the-art determines the remaining useful lifetime (RUL) through a steady-state, fixed power cycling tests (PCT) without considering the impact of dynamically changing environmental conditions. It has resulted in considerable RUL prediction errors in the real world. However, the dynamic changing conditions (e.g., large temperature swings) may affect the degradation evolution of SiC MOSFET, which could eventually result in RUL changes. Thus, it must be integrated to make accurate predictions. To precisely understand the RUL variation complexity, the junction temperature (Tj) has been measured with a Negative Thermal Coefficient (NTC) thermistor, Temperature Sensitive electrical Parameter (TSEP), and these profiles have been modeled through the thermal model RC foster network using Extended Kalman Filter (EKF). Then, the on-state resistance (Rds,on) variations and Degradation Acceleration Factor (DAF) under the dynamic environment conditions are integrated into a lifetime prediction model to accurately predict the RUL through the Long Short-Term Memory (LSTM) machine learning algorithm. © 2025 IEEE.

关键词： Silicon carbide

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