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Smart Mechatronics (ICSMech), IEEE International Conference on

作者： Muhammad Rizalul Wahid Endra Joelianto Bentang Arief Budiman Manida Tongroon Mulia Pratama Mahmudah Salwa Gianti Muhammad Fauzan Hernadi Mechatronics and Artificial Intelligence Universitas Pendidikan Indonesia Bandung Indonesia Instrumentation Control and Automation Research Group Institut Teknologi Bandung Bandung Indonesia Faculty of Mechanical and Aerospace Engineering Institut Teknologi Bandung Bandung Indonesia Department of Mechanical Engineering ATAE Research Unit Kasetsart University Sriracha Thailand Pusat Riset Mekatronika Cerdas Organisasi Riset Elektronika dan Informatika-BRIN Bandung Indonesia

ISBN: (数字)9798350368918

ISBN: (纸本)9798350368925

Optimizing regenerative braking systems in electric vehicles presents a complex challenge requiring precise and adaptable control. This research proposes employing K-Means Clustering to the Interval Type-2 Fuzzy Logic (IT2FL) membership functions, thereby improving overall regenerative braking efficiency and enhancing driving range. This research demonstrates that implementing a K-Means in the IT2FL control system in electric vehicles effectively recovers 35.84% of energy. By incorporating a K-means-based approach, the IT2FL controller further enhances vehicle range by 43 kilometers, achieving a total range of 108 kilometers. In comparison, an IT2FL system without K-means recovered only 26.67% of energy and achieved a total range of 93 kilometers. Notably, the IT2FL controller with K-means enabled the electric vehicle to attain an energy efficiency of 22 kilometers per kilowatt-hour. These findings underscore the significant improvement in maximum range offered by the IT2FL controller with K-means compared to alternative methods.

关键词： Fuzzy logic Energy consumption Electric potential Mechatronics Electric vehicles control systems Energy efficiency Optimization

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Development of a Flow Simulator for Evaluation of Hemodynamics Computational Simulation

Development of a Flow Simulator for Evaluation of Hemodynami...

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International Conference on instrumentation control and Automation (ICA)

作者： Fara Azzahra Dinata Muhammad Salman Al Farisi Muhammad Iqbal Narendra Kurnia Putra Engineering Physics Department Faculty of Industrial Technology Institut Teknologi Bandung Bandung Indonesia Department of Biomedical Information Sciences Hiroshima City University Hiroshima Japan Advance Functional Material Research Group Faculty of Industrial Technology Institut Teknologi Bandung Bandung Indonesia Instrumentation and Control Research Group Faculty of Industrial Technology Institut Teknologi Bandung Bandung Indonesia

Cardiovascular disease is the leading cause of death globally. It is responsible for most deaths caused by heart attacks and strokes, which may occur due to stenosis or aneurysm in blood vessels. Intravascular therapy is a minimally invasive medical treatment that is carried out directly into the affected blood vessel without the need for open surgery. There is significant ongoing research into intravascular therapy for the treatment of cardiovascular disease, particularly in the fields of computational fluid dynamics (CFD) simulations. CFD simulation in the development of intravascular treatment has been widely used for treatment planning, hemodynamics analysis, medical device development and design optimization. However, to ensure the accuracy and reliability of these simulations, it is necessary to validate the results using specific models and evaluation devices. Validation testing is crucial in CFD simulations as a result of the use of various parameters, such as assumptions, numerical methods, and boundary conditions. Furthermore, due to the challenges of directly observing and measuring within vessels, it is crucial to have an evaluation device that can effectively represent their hemodynamic *** meet this need, it is necessary to carry out vascular modeling related to flow conditions in vessels that can be used to evaluate the results of computational simulations and modeling more broadly. This research focus on developing an evaluation that modeling a flow circuit device to represent the hemodynamic conditions with a measurement platform using a micro-pumping system equipped with a flow rate sensor to monitor instantaneous conditions in the vessel model. Specifically, the model used is an extradural internal carotid artery (ICA) aneurysm patient-specific case and was fabricated using additive manufacturing made of flexible resin. A steady state conditions from the peristaltic pumps were used in this experimental study to provide the analysis of fl

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Analysis and Comparison of Characteristics for Offline PD Measurements in Turbo-Generators at Different Test Time Intervals

Analysis and Comparison of Characteristics for Offline PD Me...

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2022 9th International Conference on Condition Monitoring and Diagnosis (CMD)

作者： K. Dorkmai P. Pannil K. Tattiwong S. Maneerot D. Suksawat N. Pattanadech Department of Electrical Engineering School of Engineering King Mongkut's Institute of Technology Ladkrabang Bangkok Thailand Department of Instrumentation and Control Engineering School of Engineering King Mongkut's Institute of Technology Ladkrabang Bangkok Thailand Faculty of Engineering Rajamangala University of Technology Krungthep Bangkok Thailand TESLA Power Co. Ltd. Samut Sakhon Thailand

ISBN: (数字)9784886864314

ISBN: (纸本)9781665470155

Partial discharge (PD) measurement is widely used for the condition assessment of high voltage equipments. It is a tool to detect the localized discharges occurring in the weakness point sites, which causes deterioration that can lead to failure. Hence, it is essential to diagnose the PD behavior to prevent the consequent failure which maybe takes place. This paper presents an analysis of the offline PD measurements performed on the stator winding insulation system of three turbo-generators which consist of a hydrogen-cooled generator rate of 211.75 MVA, 15.75 kV, and two air-to-water heat-cooled generators which the same rate of 50.8 MVA, 11.5 kV, which were located in the power plant. Firstly, the offline PD measurements of these generators have been energized to the star point side and the high voltage coupling capacitor is installed on the high voltage terminal side, according to IEC 60034-27-1. Additionally, the test voltages were applied to the test object with a step voltage profile. To analyze the PD behaviors of the stator winding insulation, the PD characteristics such as the PD pulses, PD magnitude, and phase-resolved PD (PRPD) patterns were monitored and recorded. Besides, the effect of applied test voltage-time, i.e., 1, 3, and 5 minutes, on such characteristics were reported and compared. Finally, the PD behavior of the stator winding insulation of these generators showed clearly different results for PD measured at different recording times. The highly fluctuating PD magnitude and PD pulse shape at the initial duration of the measurement, and then gradually decreases to convergence to a stable charge magnitude as the test-time increases.

关键词： Insulation Power measurement Voltage measurement Stator windings High-voltage techniques Generators Time measurement

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Seismic Interpolation Transformer for Consecutively Missing Data: A Case Study in DAS-VSP Data

arXiv

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arXiv 2024年

作者： Cheng, Ming Lin, Jun Dong, Xintong Lu, Shaoping Zhong, Tie College of Instrumentation and Electrical Engineering Jilin University Jilin Changchun130026 China School of Earth Sciences and Engineering Sun Yat-Sen University Guangdong Guangzhou510275 China Guangdong Zhuhai519000 China Guangdong Provincial Key Lab of Geodynamics and Geohazards Sun Yat-sen University Guangdong Guangzhou510275 China Key Laboratory of Modern Power System Simulation and Control and Renewable Energy Technology Ministry of Education Jilin132012 China Department of Communication Engineering College of Electric Engineering Northeast Electric Power University Jilin132012 China

Distributed optical fiber acoustic sensing (DAS) is a rapidly-developed seismic acquisition technology with advantages of low cost, high resolution, high sensitivity, and small interval, etc. Nonetheless, consecutively missing cases often appear in real seismic data acquired by DAS system due to some factors, including optical fiber damage and inferior coupling between cable and well. Recently, some deep-learning seismic interpolation methods based on convolutional neural network (CNN) have shown impressive performance in regular and random missing cases but still remain the consecutively missing case as a challenging task. The main reason is that the weight sharing makes it difficult for CNN to capture enough comprehensive features. In this paper, we propose a transformer-based interpolation method, called seismic interpolation transformer (SIT), to deal with the consecutively missing case. This proposed SIT is an encoder-decoder structure connected by some U-shaped swin-transformer blocks. In encoder and decoder part, the multi-head self-attention (MSA) mechanism is used to capture global features which is essential for the reconstruction of consecutively missing traces. The U-shaped swin-transformer blocks are utilized to perform feature extraction operations on feature maps with different resolutions. Moreover, we combine the loss based on structural similarity index (SSIM) and L1 norm to propose a novel loss function for SIT. In experiments, this proposed SIT outperforms U-Net and swin-transformer. Moreover, ablation studies also demonstrate the advantages of new network architecture and loss function. Copyright © 2024, The Authors. All rights reserved.

关键词： Optical fibers

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Efficient Photocatalytic Degradation Towards Tetracycline Triggered by Z-Scheme Znsno3/Agi Composites: The Synergistic Effect of Oxygen Vacancies, Lewis Acid Sites, and Interfacial Chemical Bonds

SSRN

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SSRN 2024年

作者： Sun, Jing Chang, Ting Liu, Qian Wang, Zhuoyue Huo, Xiaoqi Li, Meifeng Wang, Yafeng Zhao, Zhilei Zhao, Xin Wang, TingXin Liu, Jue National&Local Joint Engineering Research Center of Metrology Instrument and System College of Quality and Technical Supervision Hebei University Baoding071002 China Department of Chemical and Materials Engineering University of Alberta EdmontonT6G2R3 Canada Yunnan Provincial Key Laboratory of Soil Carbon Sequestration and Pollution Control Faculty of Environmental Science & Engineering Kunming University of Science &Technology Kunming650500 China

Chemically bonded Z-scheme ZnSnO3/AgI composites rich in oxygen vacancies (OVs) and Lewis acid sites were prepared successfully and showed excellent photocatalytic activities. Especially, ZnAg-2 degraded 96.1% tetracycline under visible light irradiation for 15 min. OVs contributed to Lewis acid sites production and interfacial chemical bonds formation through weakening the metal-O bonding. Lewis acid sites favored the adsorption of electron-rich tetracycline. Interfacial chemical bonds together with Z-scheme structure accelerated electron transfer and retained the high redox ability of ZnSnO3 and AgI. OVs contributed to singlet oxygen (1O2) production through facilitating the energy transfer from triplet exciton to O2. ZnSnO3/AgI composites realized efficient removal towards tetracycline after five consecutive cycles utilization as well as in different environmental conditions and water matrices, showing practical application potential. Based on ROSs generation and photoreduction experiment, the photocatalytic mechanism of the ZnAg composites was proposed. Possible degradation pathway was deduced according to the detected main degradation intermediates. The biological toxicity in solution was reduced after tetracycline degradation. This work highlights the significant roles of OVs, Lewis acid sites, and chemical bonding in improving the photocatalytic activity of Z-scheme composites and provides new insight into designing high efficient photocatalysts for visible light induced organic pollutants removal. © 2024, The Authors. All rights reserved.

关键词： Zinc compounds

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Data poisoning: issues, challenges, and needs

Data poisoning: issues, challenges, and needs

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7th IET Smart Cities Symposium (SCS 2023)

作者： Mohammad Aljanabi Alaa Hamza Omran Maad M Mijwil Mostafa Abotaleb El-Sayed M. El-kenawy Sahar Yousif Mohammed Abdelhameed Ibrahim Department of computer College of Education Aliarqai university Baghdad Iraq University of information technology and communications Baghdad Iraq Computer Techniques Engineering Department Baghdad College of Economic Sciences University Baghdad Iraq Department of System Programming South Ural State University Chelyabinsk Russia Department of Communications and Electronics Delta Higher Institute of Engineering and Technology Egypt Computer Science Department Computer Science & Information Technology College Anbar University Anbar Iraq Computer Engineering and Control Systems Department Faculty of Engineering Mansoura University Mansoura Egypt

Data poisoning attacks, where adversaries manipulate training data to degrade model performance, are an emerging threat as machine learning becomes widely deployed in sensitive applications. This paper provides a comprehensive overview of data poisoning including attack techniques, adversary incentives, impacts on security and reliability, detection methods, defenses, and key research gaps. We examine label flipping, instance injection, backdoors, and other attack categories that enable malicious outcomes ranging from IP theft to accidents in autonomous systems. Promising detection approaches include statistical tests, robust learning, and forensics. However, significant challenges remain in translating academic defenses like adversarial training and sanitization into practical tools ready for operational use. With safety and trustworthiness at stake, more research on benchmarking evaluations, adaptive attacks, fundamental tradeoffs, and real-world deployment of defenses is urgently needed. Understanding vulnerabilities and developing resilient machine learning pipelines will only grow in importance as data integrity is fundamental to developing safe artificial intelligence.

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Experimental validation of a novel hybrid Equilibrium Slime Mould Optimization for solar photovoltaic system

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Heliyon 2024年第20期10卷 e38943页

作者： Zabia, Djallal Eddine Afghoul, Hamza Kraa, Okba Himeur, Yassine Ramadan, Haitham S. Genc, Istemihan Idriss, Abdoulkader I. Miniaoui, Sami Atalla, Shadi Mansoor, Wathiq Laboratory of Identification Command Control and Communication (LI3CUB) University of Biskra Algeria LAS Laboratory Faculty of Technology Ferhat Abbas Setif-1 University Algeria Laboratory of Energy System Modeling Electrical Engineering (LMSE) Algeria College of Engineering and Information Technology University of Dubai Dubai United Arab Emirates Electrical Power and Machines Department Faculty of Engineering Zagazig University Egypt ISTHY Institut International sur le Stockage de l'Hydrogene Meroux-Moval 90400 France Department of Electrical Engineering Istanbul Technical University Istanbul 34469 Turkey Electrical and Energy Department Faculty of Engineering University of Djibouti Street Djanaleh 1904 Djibouti

Maximizing Power Point Tracking (MPPT) is an essential technique in photovoltaic (PV) systems that guarantees the highest potential conversion of sunlight energy under any irradiance changes. Efficient and reliable MPPT technique is a challenge faced by researchers due to factors such as fluctuations in irradiance and the presence of partial shading. This paper introduced a novel hybrid Equilibrium Slime Mould Optimization (ESMO) MPPT-based algorithm combining the advantages of two recent algorithms, Slime Mould Optimization (SMO) and Equilibrium Optimizer (EO). The ESMO algorithm is compared with highly efficient MPPT-based techniques such as SMO, EO, Particle Swarm Optimization (PSO), Grey Wolf Optimization (GWO), and Whale Optimization Algorithm (WOA), both under a Simulink environment and a real-time experimental laboratory setup using a Dspace1104 controller and PV emulator. The comparison focuses on performance under several irradiance cases, including instant irradiance change, partial shading, complex partial shading, and dynamic partial shading. The key advantage of ESMO is the fact that it has a single tunable parameter, which makes implementation much easier and, at the same time, reduces the computational resources that are required by the control system. Extensive testing proves the superiority of ESMO over all other techniques, the average efficiency of which is 99.98% under all conditions. Additionally, ESMO provides fast average tracking times of 244 ms under simulation experiments and 200 ms for real-time experiments. These results show that ESMO can be very important for future implementation in large-scale solar PV systems. © 2024

关键词： Complex partial shading condition Equilibrium Slime Mould optimization algorithm Maximum power point tracking Photovoltaic system Renewable energy

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MAE-GAN: A Novel Strategy for Simultaneous Super-resolution Reconstruction and Denoising of Post-stack Seismic Profile

arXiv

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arXiv 2024年

作者： Yu, Wenshuo Dong, Shiqi Lu, Shaoping Dong, Xintong The College of Instrumentation and Electrical Engineering Jilin University Jilin Changchun130026 China The Key Laboratory of Modern Power System Simulation and the Control and Renewable Energy Technology Ministry of Education Jilin Jilin City132012 China Department of Communication Engineering College of Electric Engineering Northeast Electric Power University Jilin Jilin City132012 China School of Earth Sciences and Engineering Sun Yat-Sen University Guangdong Guangzhou510275 China Guangdong Zhuhai519000 China Guangdong Provincial Key Lab of Geodynamics and Geohazards Sun Yat-Sen University Guangdong Guangzhou510275 China

Post-stack seismic profiles are images reflecting containing geological structures which provides a critical foundation for understanding the distribution of oil and gas resources. However, due to the limitations of seismic acquisition equipment and data collecting geometry, the post-stack profiles suffer from low resolution and strong noise issues, which severely affects subsequent seismic interpretation. To better enhance the spatial resolution and signal-to-noise ratio of post-seismic profiles, a multi-scale attention encoder-decoder network based on generative adversarial network (MAE-GAN) is proposed. This method improves the resolution of post-stack profiles, and effectively suppresses noises and recovers weak signals as well. A multi-scale residual module is proposed to extract geological features under different receptive fields. At the same time, an attention module is designed to further guide the network to focus on important feature information. Additionally, to better recover the global and local information of post-stack profiles, an adversarial network based on a Markov discriminator is proposed. Finally, by introducing an edge information preservation loss function, the conventional loss function of the Generative Adversarial Network is improved, which enables better recovery of the edge information of the original post-stack profiles. Experimental results on simulated and field post-stack profiles demonstrate that the proposed MAE-GAN method outperforms two advanced convolutional neural network-based methods in noise suppression and weak signal recovery. Furthermore, the profiles reconstructed by the MAE-GAN method preserve more geological structures. Copyright © 2024, The Authors. All rights reserved.

关键词： Generative adversarial networks

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A new force profile signal for a convex solution of muscle force estimation from electromyographic signals*

A new force profile signal for a convex solution of muscle f...

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Annual International Conference of the IEEE engineering in Medicine and Biology Society (EMBC)

作者： Mehdi Shirzadi Arezoo Mirshamsi Alp Eşrefoğlu Monica Rojas-Martínez Hamid Reza Marateb Miquel Angel Mañanas Taian Vieira Department of Automatic Control (ESAII) Biomedical Engineering Research Centre (CREB) Universitat Politèncicna de Catalunya (UPC) Barcelona Spain Biomedical Engineering Department Engineering Faculty University of Isfahan Isfahan Iran Laboratory of Applied Biology & Research Unit in Applied Neurophysiology (LABNeuro) – Université Libre de Bruxelles Brussels Belgium CIBER of Bioengineering Biomaterilas and Nanomedicine (CIBER-BBN) Madrid Spain Department of Electronics and Telecommunication Laboratory for Engineering of the Neuromuscular System (LISiN) PolitoBIOMed Lab – Politecnico di Torino Turin Italy

High-Density Surface Electromyography (HD-sEMG) is a non-invasive technique for measuring the electrical activity of a muscle with multiple, closely spaced electrodes. Estimation of muscle force is one of the applications of HD-sEMG. Usually, validating different EMG-Force models entails simple movements limited to laboratory settings. The validity of these models in more ecological conditions, requesting force production over a wide frequency band, remains unknown. In this study, we, therefore, compare the results of force prediction using four different types of input force profiles that can be representative of daily life activities, and we investigate whether the crest factor of these different input signals affects force prediction. For predicting the force from sEMG signals, we used our real-time and convex methods. HD-sEMG signals were recorded with 144 channels from the biceps brachii, brachioradialis, and triceps (long, lateral, and medial head) muscles of 24 healthy subjects during random signal, random phase, Schroeder phase, and minimum crest factor (crestmin) signal. The correlation and coefficient of determination (R 2 ) between measured and predicted forces were calculated for the different force feedback profiles. The crestmin signal showed significantly better results based on statistical tests (P-value < 0.05), with correlation and R 2 equal to 0.92±0.03 and 0.86±0.05, respectively. The results demonstrate that the crest factor of input signals is a crucial parameter that can impact the performance of EMG-Force models and must be considered during *** Relevance— This study demonstrates that lower crest factor multisine force profiles result in improved fitness for force prediction and can be used as an alternative to random signals.

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基于自解耦三明治结构的横向运动栅场效应晶体管MEMS微力传感器

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engineering 2023年第2期21卷 61-74,M0004页

作者：高文迪乔智霞韩香广王小章 Adnan Shakoor 刘存朗卢德江杨萍赵立波王永录王久洪蒋庄德孙东 State Key Laboratory for Manufacturing Systems Engineering International Joint Laboratory for Micro/Nano Manufacturing and Measurement TechnologiesOverseas Expertise Introduction Center for Micro/Nano Manufacturing and Nano Measurement Technologies Discipline InnovationXi’an Jiaotong University(Yantai)Research Institute for Intelligent Sensing Technology and SystemSchool of Mechanical EngineeringXi’an Jiaotong UniversityXi’an 710049China Shandong Laboratory of Yantai Advanced Materials and Green Manufacturing Yantai 265503China Beijing Advanced Innovation Center for Intelligent Robots and Systems Beijing Institute of TechnologyBeijing 100081China State Key Laboratory of Robotics and Systems Harbin Institute of TechnologyHarbin 150006China Eleventh Research Institute Sixth Academy of China Aerospace Science and Technology Co.Xi’an 710100China Department of Control and Instrumentation Engineering King Fahd University of Petroleum and MineralsDhahran 31261Saudi Arabia Department of Biomedical Engineering City University of Hong KongHong Kong 999077China

本文介绍了一种基于横向可移动栅极场效应晶体管(LMGFET)的新型微型力传感器的开发。提出了一种精确的电气模型,用于小型LMGFET器件的性能评估,与以前的模型相比,其精度有所提高。采用了一种新型三明治结构,该结构由一个金交叉解耦栅阵... 详细信息

本文介绍了一种基于横向可移动栅极场效应晶体管(LMGFET)的新型微型力传感器的开发。提出了一种精确的电气模型,用于小型LMGFET器件的性能评估,与以前的模型相比,其精度有所提高。采用了一种新型三明治结构,该结构由一个金交叉解耦栅阵列层和两个软光阻层SU-8组成。通过所提出的双差分传感结构,LMGFET横向工作在垂直干扰下的输出电流被大大消除,所提出传感器的相对输出误差从4.53%(传统差分结构)降低到0.01%。提出了一种实用的传感器制造工艺,并对其进行了模拟。基于LMGFET的力传感器的灵敏度为4.65μA·nN^(-1),可与垂直可移动栅极场效应晶体管(VMGFET)器件相媲美,但非线性度提高了0.78%,测量范围扩大了±5.10μN。这些分析为LMGFET器件的电气和结构参数提供了全面的设计优化,并证明了所提出的传感器在生物医学显微操作应用中具有良好的力传感潜力。

关键词：力传感器场效应晶体管横向运动三明治结构电气模型显微操作非线性度双差分

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