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10th IEEE World Forum on Internet of Things, WF-IoT 2024

作者： Correa, Juan David Arias Pinto, Alex Sandro Roschildt Montez, Carlos Post-graduate Program of Automation Systems Engineering Florianópolis Brazil Dept. of Informatics and Statistic Dept. of Automation and Systems Engineering Florianópolis Brazil Dept. of Automation and Systems Engineering Florianópolis Brazil

ISBN: (纸本)9798350373011

The communication system is essential for the devices used in IoT. Nevertheless, the consumption caused by transmitting and receiving data is a concern in many scenarios. That is due to these devices commonly having limited energy and computational capacities. Transmission of redundant or irrelevant samples frequently wastes the device's resources. Furthermore, Storing a large amount of redundant data could consume storage space and not offer any benefit. Data Compression (DC) methods are a potential solution. DC could reduce communication usage and storage demand. This research proposes the Training Swing Door Trending (TSDT) for being implemented in IoT Devices. TSDT is a new algorithm that improves the classic Swing Door Trending (STD). They represent the data by trend lines and have a constant computational complexity. TSDT has a training step for the automatic configuration of its parameters. This article additionally presents the Compression Factor (C-Score), a new quality metric to analyze the compression results in lossy DC methods. C-Score takes as a basis the F-Score, a measure of predictive performance. The C-Score uses the Compression and Error metrics to evaluate the compression performance in Lossy Algorithms. © 2024 IEEE.

关键词： Data compression ratio

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L2 Input-to-State Stability and Stabilization of Coupled Linear ODE-Hyperbolic PDE Systems∗ 63

L2 Input-to-State Stability and Stabilization of Coupled Lin...

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63rd IEEE Conference on Decision and Control, CDC 2024

作者： Coutinho, Daniel Andrade, Gustavo Artur De Carvalho, Franthiescolly Vieira De Federal University of Santa Catarina Department of Automation and Systems Engineering Florianópolis88040-370 Brazil Federal University of Santa Catarina Post-graduate Program in Automation and Systems Engineering Florianópolis88040-370 Brazil

ISBN: (纸本)9798350316339

This paper addresses the problem of input-to-state stability (ISS) and stabilization of linear ordinary differential equations (ODEs) coupled with a system of homogeneous linear hyperbolic partial differential equations (PDEs) through the boundaries. First, a Lyapunov result characterizing the ISS property for finite-dimensional systems is extended to deal with coupled ODE and PDE systems. The proposed ISS condition is then applied to derive stability and stabilization conditions in terms of linear matrix inequality constraints assuming magnitude bounded disturbances at the boundaries. Two convex optimization problems are also proposed in order to obtain either an optimized reachable set estimate or a boundary controller that minimizes the disturbance effects on the L2 × R-norm of the system states. Numerical examples illustrate the potential of the proposed approach. © 2024 IEEE.

关键词： Convex optimization

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Exploring Bess Services for Transformer Energization on Offshore Oil and Gas Platforms

Exploring Bess Services for Transformer Energization on Offs...

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2024 IEEE Petroleum and Chemical Industry Conference Brasil, PCIC Brasil 2024

作者： Banda, Joseph K. Araujo, Lucas S. Brandao, Danilo I. Marafao, Fernando P. Tedeschi, Elisabetta Department of Electric Power Engineering Trondheim Norway Graduate Program in Electrical Engineering Belo Horizonte Brazil Department of Control and Automation Engineering Sorocaba Brazil University of Trento Department of Industrial Engineering Trento Italy

ISBN: (纸本)9798350368154

The electrification of offshore oil and gas platforms (OOGPs), using offshore wind turbines, is now a reality, aimed at minimizing carbon emissions. In this scenario, the utilization of battery energy storage systems (BESS) improves both efficiency and power quality. As this integration comes with a high CAPEX, industries demand exploring BESS for multiple ancillary services on OOGPs. Thus, this paper proposes an alternative approach to energizing a power transformer (PT) using the BESS power conversion system (PCS) on the platform, aiming to minimize inrush currents. This avoids the necessity for additional bulky devices, converters, or dc voltage sources specifically designated for this purpose. The strategy consists of manipulating residual core flux using BESS PCS followed by a controlled switching, which reduces inrush currents during PT energization. The results show effective reduction of the inrush current from 2.31 pu to 0.16 pu for the presented case study. © 2024 IEEE.

关键词： Power transformers

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Evaluating cooling tube effects on defect formation and distribution in Czochralski crystal growth

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Journal of Materials Science: Materials in Electronics 2024年第19期35卷 1315页

作者： Huang, Yi-Jen Dezfoli, Amir Reza Ansari Department of Chemical and Materials Engineering National Chin-Yi University of Technology Taichung41170 Taiwan Department of Intelligent Automation Engineering National Chin-Yi University of Technology Taichung Taiwan Ph.D. Program at Graduate Institute of Precision Manufacturing National Chin-Yi University of Technology Taichung Taiwan

The quality of silicon ingots is paramount in semiconductor manufacturing as defects profoundly influence the crystal integrity and device performance. This study investigates the impact of cooling-tube configurations on defect formation during the Czochralski process. Comprehensive modeling and simulation elucidated the intricate relationship between the presence of a cooling tube and the evaluation of point defects within silicon ingots. The results show that cooling tubes augment the axial temperature gradient and shift the point-defect behavior from vacancy-rich to interstitial-dominated regions with an increase in the axial temperature gradient of up to 1.6 times. Additionally, cooling tubes impede the formation of agglomerated defects by reducing point-defect mobility and propagation time, resulting in a reduction of the agglomerated defect count by up to 30% compared to processes without cooling tubes. Experiments validated the simulation findings, demonstrating a notable decrease in agglomerated defect counts. These insights underscore the potential of optimized cooling-tube designs for enhancing semiconductor device performance and manufacturing yield, thereby driving progress in electronics and beyond. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

关键词： Agglomeration

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DigitalLLaVA: Incorporating Digital Cognition Capability for Physical World Comprehension in Multimodal LLMs 39

DigitalLLaVA: Incorporating Digital Cognition Capability for...

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39th Annual AAAI Conference on Artificial Intelligence, AAAI 2025

作者： Li, Shiyu Wei, Pengxu Qiao, Pengchong Liu, Chang Chen, Jie School of Electronic and Computer Engineering Peking University Shenzhen China Pengcheng Laboratory Shenzhen China Sun Yat-Sen University Guangzhou China -Preferred Program Peking University Shenzhen Graduate School China Department of Automation and BNRist Tsinghua University Beijing China

ISBN: (纸本)157735897X

Multimodal Large Language Models (MLLMs) have shown remarkable cognitive capabilities in various cross-modal tasks. However, existing MLLMs struggle with tasks that require physical digital cognition, such as accurately reading an electric meter or pressure gauge. This limitation significantly reduces their effectiveness in practical applications like industrial monitoring and home energy management, where digital sensors are not feasible. For humans, physical digits are artificially defined quantities presented on specific carriers, which require training to recognize. As existing MLLMs are only pre-trained in the manner of object recognition, they fail to comprehend the relationship between digital carriers and their reading. To this end, referring to human behavior, we propose a novel DigitalLLaVA method to explicitly inject digital cognitive abilities into MLLMs in a two-step manner. In the first step, to improve the MLLM’s understanding of physical digit carriers, we propose a digit carrier mapping method. This step utilizes object-level text-image pairs to enhance the model’s comprehension of objects containing physical digits. For the second step, unlike previous methods that rely on sequential digital prediction or digit regression, we propose a 32 bit floating point simulation approach that treats digit prediction as a whole. Using digit-level text-image pairs, we train three float heads to predict 32-bit floating-point numbers using 0/1 binary classification. This step significantly reduces the search space, making the prediction process more robust and straightforward. Being simple but effective, our method can identify very precise metrics (i.e., accurate to ±0.001) and provide floating-point results, showing its applicability in digital carrier domains. © 2025, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

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Mapping the Optimal Sites for Offshore Wind Power Plants and Green Hydrogen Production: South and Southeast Brazilian Case Study 32

Mapping the Optimal Sites for Offshore Wind Power Plants and...

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32nd IEEE International Symposium on Industrial Electronics, ISIE 2023

作者： Paula, Karen De Pumalloclla, Hayro Pourakbari-Kasmaei, Mahdi Melo, Joel D. Falcao, Djalma Federal University of ABC Graduate Program in Energy Santo André Brazil Aalto University Dept. Electrical Engineering and Automation Espoo Finland Alberto Luiz Coimbra Institute for Graduate Studies and Engineering Research Federal University of Rio de Janeiro Rio de Janeiro Brazil

ISBN: (纸本)9798350399714

The demand for renewable energy solutions has become a global trend due to the current climate change scenario and the increased demand for electricity. Hence, in several countries, the share of renewable sources in the electric matrix has grown with the insertion of new energy sources, such as offshore wind. Brazil presents optimal conditions for the construction of offshore wind farms. The Brazilian 10-year Energy Expansion Plan 2029, in addition to placing this source as an expansion for the coming years, intensely focuses on hydrogen. For this reason, this study aims to assist planners and agents interested in running new construction projects of offshore wind farms with green hydrogen production. Such a study case seeks better use of the available wind resources in the high energy consumption regions of Brazil's South and Southeast, assessing the wind resource considering technical, environmental, social, and economic restrictions to identify the best locations for installing wind farms. As such, it processes the data within a geographic information system, and then a fuzzy logic-based model is used for the joint evaluation of constraints. Results show that Rio de Janeiro and Espírito Santo are the most favorable places. © 2023 IEEE.

关键词： Offshore wind farms

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A Multi Soft-sensor Approach for the Development of Emergencies Detection Units on the Edge 6

A Multi Soft-sensor Approach for the Development of Emergenc...

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6th IEEE International Workshop on Metrology for Industry 4.0 and IoT, MetroInd4.0 and IoT 2023

作者： Oliveira, Franklin Costa, Daniel G. Assis, Flavio Silva, Ivanovitch Federal University of Bahia Graduate Program in Mechatronics Salvador Brazil University of Porto INEGI Faculty of Engineering Porto Portugal Federal University of Rio Grande Do Norte Department of Computer Engineering and Automation Natal Brazil

ISBN: (纸本)9798350396577

The adoption of multi-sensor hardware units to detect different types of emergencies in complex scenarios such as Industry 4.0 and Smart Cities is a recent development trend, which have demanded research efforts to optimize the way these units are assembled, configured, and deployed. However, although their expected advantages, usual multi-sensors emergency-oriented approaches may be constrained by the tight association between physical sensor devices and the emergency detection process. Therefore, this paper proposes an innovative approach to concurrently detect multiple emergencies exploiting the concept of soft-sensor modules, which are implemented on Emergency Detection Units (EDUs) as concurrent tasks along with a high-priority emergency alerting task. The soft-sensor concept defines physical sensors as ordinary input data streams, which will be processed according to the defined algorithms by each particular soft-sensor, allowing detection decisions to be performed on the edge. In order to support the practical exploitation of this concept, a formal specification based on Petri Nets is defined, modeling the concurrent operation of the tasks within an EDU. A proof of concept is also designed based on the affordable Raspberry Pi Pico microcontroller, demonstrating how the proposed approach would behave when two soft-sensors are implemented in a typical detection unit. © 2023 IEEE.

关键词： Industry 4.0

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Capacitance Estimation Algorithm for Condition Monitoring of Electrolytic DC-Link Capacitors Using Artificial Neural Network in Front-End Diode Rectifier Three-Phase Motor Drive Systems

Capacitance Estimation Algorithm for Condition Monitoring of...

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IEEE Annual Southern Power Electronics Conference (SPEC)

作者： Mateus Abreu de Andrade Rodolfo César Costa Flesch Graduate Program in Automation and Systems Engineering Universidade Federal de Santa Catarina Florianópolis Brazil

A factor that must be taken into account in the modern design of power electronics converters is the reliability of dc-link capacitors, but traditional condition monitoring methods require extra hardware that increase the overall cost. This work proposes and experimentally evaluates a condition monitoring method for electrolytic dc-link capacitors in three-phase front-end diode rectifier motor drives which does not require hardware modifications. The presented method uses an artificial neural network (ANN) to predict the capacitance value of the dc-link capacitor bank. Based on time-domain parameters, the ANN is trained and evaluated using an error analysis to determine the effectiveness of the proposed method with a printed circuit board capacitor jig and aged samples. The proposed method is evaluated in several operating conditions and the results show that the prediction errors are less than 2.4% and that the method is able to monitor the degradation level of the dc-link capacitor bank.

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L2 Input-to-State Stability and Stabilization of Coupled Linear ODE-Hyperbolic PDE Systems*

L2 Input-to-State Stability and Stabilization of Coupled Lin...

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IEEE Conference on Decision and Control

作者： Daniel Coutinho Gustavo Artur de Andrade Franthiescolly Vieira de Carvalho Department of Automation and Systems Engineering Federal University of Santa Catarina Florianópolis Brazil Post-graduate Program in Automation and Systems Engineering Federal University of Santa Catarina Florianópolis Brazil

ISBN: (数字)9798350316339

ISBN: (纸本)9798350316346

This paper addresses the problem of input-to-state stability (ISS) and stabilization of linear ordinary differential equations (ODEs) coupled with a system of homogeneous linear hyperbolic partial differential equations (PDEs) through the boundaries. First, a Lyapunov result characterizing the ISS property for finite-dimensional systems is extended to deal with coupled ODE and PDE systems. The proposed ISS condition is then applied to derive stability and stabilization conditions in terms of linear matrix inequality constraints assuming magnitude bounded disturbances at the boundaries. Two convex optimization problems are also proposed in order to obtain either an optimized reachable set estimate or a boundary controller that minimizes the disturbance effects on the ${\mathcal{L}}_{2} \times \mathbb{R}$-norm of the system states. Numerical examples illustrate the potential of the proposed approach.

关键词： Partial differential equations Ordinary differential equations Convex functions Linear matrix inequalities Numerical stability

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Real-Time Hand Gesture Recognition for Humanoid Robot Control Using Python CVZone 7th

Real-Time Hand Gesture Recognition for Humanoid Robot Contro...

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7th International Conference on Smart City Applications, SCA 2022

作者： Baihaqi, Muhammad Yeza Vincent Simatupang, Joni Welman Graduate Institute of Automation and Control College of Engineering National Taiwan University of Science and Technology Taipei Taiwan School of Electrical Engineering and Informatics Institut Teknologi Bandung Bandung Indonesia Study Program of Electrical Engineering President University Bekasi Indonesia

ISBN: (纸本)9783031268519

Humanoid robot is able to mimic repetitive activities done by human. By having them, humans can focus on tasks that require extra focus, while leaving the simple one to be done by humanoid robot. To extend the functionality of the 3D-printed upper-body humanoid robot, a camera along with a machine learning algorithm is implemented. In this case, their responses can be categorized based on the gesture it sees. In this paper, the authors evaluate the performance of an upper-body humanoid robot that implements CVZone. The method of evaluation is conducted under three different distances, and each distance has three different brightness levels. It is found that the success rate is highest at the shortest distance which is 50 cm, and under medium-lighted environment. As the distance increases, the hand gesture gets harder to differentiate. At the same time, low or high brightness environment makes the image that contain hand gesture hard to interpret, thus lowering the success rate. Finally, hand gesture that involves third and little finger has the lowest success rate of 75%, while the movement that involves three fingers simultaneously has the second lowest success rate of 80.9%. Meanwhile, simple hand gesture such as clenched-fist or lifting a thumb has 100% success rate under all condition. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Anthropomorphic robots

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