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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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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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Hardware Implementation of a Sliding Detection Algorithm for Robotic Hands Using Force Sensors

Hardware Implementation of a Sliding Detection Algorithm for...

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Symposium on Integrated Circuits and Systems Design (SBCCI)

作者： Jose Mendoza-Peñaloza Daniel M. Muñoz Department of Mechanical Engineering Mechatronics Systems Graduate Program Automation and Control Group/GRACO Faculty of Gama Electronics Engineering Undergraduate Program University of Brasilia Brasilia DF Brazil

In this work, a sliding detection algorithm was proposed for a previously developed robotic hand through the utilization of force sensors. Previous works have designed several hardware architectures to filter sensor data, implement dynamic control, and machine learning models for controlling the robotic fingers using a single Field programmable Gate Arrays (FPGA) chip. In this regard, the slip detection algorithm was developed to comprise three stages, each with a low computational cost, including a moving average filter, a first-order derivative, and a peak detection algorithm. A reference model was constructed and validated through an experimental protocol employing daily use objects to create a database. Subsequently, the slip detection algorithm was mapped onto hardware utilizing previously developed floating-point arithmetic IP cores and implemented using a Zynq 7020 device. The FPGA implementation was characterized in terms of resource occupation, power consumption, execution time, and numerical error with the reference model.

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A preliminary discussion of digital transformation and semantic interoperability to support the information exchange in the business process 28

A preliminary discussion of digital transformation and seman...

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28th ISTE International Conference on Transdisciplinary engineering, TE 2021

作者： Nakano, Lucas Yoshio Bertoldi, Pedro Henrique Szejka, Anderson Luis Canciglieri Junior, Osiris Industrial and Systems Engineering Graduate Program Pontifical Catholic University of Parana Curitiba Brazil Automation and Control Engineering Program Pontifical Catholic University of Parana Curitiba Brazil

ISBN: (纸本)9781643682082

The development of interoperability is more and more an essential task for all kinds of organizations. It needs to be measured, verified, and continuously improved. With the advent of the Internet of Things, Industry 4.0, Digital Transformation, as well as all technologies it brings, such as big data, cloud computing, and mobile applications, this subject become quite ordinary and necessary, not only in a manufacturing scenario but also in a business process. As crucial benefits, it can bring possible gains for developers and users, also reduce the efforts to communicate multiple and different platforms. Like all new implementations, there are significant challenges that have to be overcome to allow satisfactory results. In this paper, after a systematic literature review to better understand the technologies and this new situation, we conduct a study involving a case in a business process, presenting some actions that can be executed and technologies that can be implemented to reach a well interoperable environment. For instance, to analyze the interoperability maturity level and to adopt ontologies as an alternative to integrate heterogeneous systems. Finally, in the last part of the paper, we give conclusions and perspectives for futures works. © 2021 The authors and IOS Press.

关键词： Interoperability

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Comparison Performance on SOTA Deep Learning Models for Coffee Beans Grading Inspection

Comparison Performance on SOTA Deep Learning Models for Coff...

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Asian control Conference

作者： Achmad Norman Firdaus Amalia Rakhmawati Vebi Nadhira Suprijanto Endang Juliastuti Gema Nuran Utomo Ayu Gareta Risangtuni Master Program on Instrumentation and Control Faculty of Industrial Technology Bandung Institute of Technology Bandung Indonesia Graduate Program on Engineering Physics Faculty of Industrial Technology Bandung Institute of Technology Bandung Indonesia Instrumentation Control and Automation Research Group Faculty of Industrial Technology Bandung Institute of Technology Bandung Indonesia

ISBN: (数字)9789887581598

ISBN: (纸本)9798331540845

Several coffee producers rely on manual inspection for quality control, which is prone to inconsistencies and time consumption. Recent studies have proposed Comparison performance on State-of-The-Art (SOTA). Deep learning models were investigated as part of the proposed intelligent computer vision for faster and more reliable coffee bean grading. Performance Deep learning models, i.e., MobileNetV3Small, ResNet50, EfficientNetV2L, and DenseNet201, were evaluated to grade the quality of coffee beans that followed a grading procedure based on Indonesian National Standard (SNI) 01-2907-2008. A specific tray was designed to position coffee beans evenly without overlap for sample preparation, which consist of about 500–600 coffee beans. The process of capturing images is conducted systematically, focusing on each type of coffee bean defect individually. For comparison of SOTA models, five classes of coffee bean defects, With 1053 beans per class, the total dataset comprises 5265 beans. This dataset was divided into 10% for testing and 90% for training. Within the training data, 12% was reserved for validation. The result from this paper shows that MobileNetV3Small achieves the highest accuracy (99.43%) with minimal memory and parameters. Its efficient design allows for robust feature extraction, crucial for distinguishing subtle defect features. While larger models like ResNet50 and EfficientNetV2L also perform well, they exhibit higher memory and parameters.

关键词： Deep learning Training Accuracy Computational modeling Training data Inspection Feature extraction

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Tuning of FP-PID controller based on PSO Algorithm Applied to a Human Gait

Tuning of FP-PID Controller based on PSO Algorithm Applied t...

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IEEE Latin American Robotics Symposium, LARS

作者： Rodrigo B. de Medeiros Daniel M. Muñoz Department of Mechanical Engineering Mechatronics Graduate Program Automation and Control Group/GRACO University of Brasilia Brasilia DF Brazil

ISBN: (数字)9781665462808

ISBN: (纸本)9781665462815

Robotic manipulators are multi-input multi-output (MIMO) systems with nonlinear points affected by numerous uncertainties and disturbances. PID controllers are widely used in industry for kinematic and dynamic control. However, when applied to MIMO systems, they are not easy to tune and require performance improvements. In this work, a PID controller is proposed with a fuzzy precompensator (FP-PID), both tuned by the bioinspired particle swarm optimization (PSO) algorithm to a two-degree of freedom (2-DOF) robotic manipulator representing a human leg. To validate the system, two real datasets of human gait were used: normal walking and stair climbing to estimate the error trajectory of the manipulator. The statistical analysis of the PSO algorithm with 16 experiments was satisfactory, and the addition of the fuzzy precompensator to the conventional PID resulted in a reduction of the mean square error of one of the manipulator links by up to 73 percent.

关键词： Legged locomotion Uncertainty Statistical analysis Service robots Stairs Trajectory Robots

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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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IEEE Petroleum and Chemical Industry Conference - Brasil (PCIC Brasil)

作者： Joseph K. Banda Lucas S. Araujo Danilo I. Brandao Fernando P. Marafão Elisabetta Tedeschi Department of Electric Power Engineering Norwegian University of Science and Technology (NTNU) Trondheim Norway Graduate Program in Electrical Engineering Universidade Federal de Minas Gerais (UFMG) Belo Horizonte Brazil Department of Control and Automation Engineering Universidade Estadual Paulista (Unesp) Sorocaba Brazil Department of Industrial Engineering University of Trento Trento Italy

ISBN: (数字)9798350368154

ISBN: (纸本)9798350368161

关键词： Offshore installations Battery energy storage system Oils Voltage Switches Oil insulation Transformer cores

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Data-Driven control and Behavior-Based control Applied to a SISO Mobile Robot

Data-Driven Control and Behavior-Based Control Applied to a ...

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IEEE Latin American Robotics Symposium, LARS

作者： M. A. Pastrana Karine R. Santos Alceu B. C. de Farias Daniel M. Muñoz Department of Mechanical Engineering Mechatronics Graduate Program Automation and Control Group/GRACO University of Brasilia Brasilia DF Brazil Faculty of Gama Biomedical Engineering Graduate Program University of Brasilia Brasilia DF Brazil Faculty of Gama Electronics Engineering Undergraduate Program University of Brasilia Brasilia DF Brazil

ISBN: (数字)9781665462808

ISBN: (纸本)9781665462815

With the advancement of technology, systems in many different areas of application have become more complex, and obtaining reliable mathematical models is a task that is increasingly becoming more difficult as well. To overcome these issues, new methodologies have emerged, such as the one known as Data-Driven-control (DDC), which uses the input and output data of the system to design a controller, and Behavior-Based-control (BBC), which provides the controller based on the desired behavior of a system. In this work, these two methodologies were applied to obtain the transfer function of a Single-Input Single-Output mobile robotic platform that moves parallel to a wall. A Proportional Integral Derivative controller was used to control the left wheel, while the right wheel was set to a constant speed, allowing the mobile robot to maintain a constant distance from the wall. The controller was tuned utilizing root locus methodology with an overshot of 16.7%, settling time of 6.45 seconds, and a static error of 2.1%. Additionally, disturbances were added to test the robustness of the mobile robot model and the PID controller.

关键词： Analytical models Biological system modeling Wheels Transfer functions Robot sensing systems control systems Mathematical models

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AGV Detection in Industrial Environments through Computer Vision

AGV Detection in Industrial Environments through Computer Vi...

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IEEE Latin American Robotics Symposium, LARS

作者： Wilson Eduardo Barioni Igor Pardal Latini André Lazzaretti Marco Teixeira Flavio Neves Lucia Valeria Ramos De Arruda Automation and Advanced Control System Laboratory (LASCA) Graduate Program in Electrical and Computer Engineering (CPGEI) Universidade Tecnologica Federal do Parana (UTFPR) Curitiba Parana Brazil

ISBN: (数字)9781665462808

ISBN: (纸本)9781665462815

Automated Guided Vehicles (AGVs) are usual in industrial settings, with an increasing economic impact on processes. They move through numerous environments inside factories, commonly navigating long distances, while performing several activities. The constant detection of such vehicles, especially in cases of maintenance and safety, is a main issue in an industry setting. Usually, this information could be provided by a supervisory system, but many applications are not so large as to make such a system viable. Thus, a solution via machine learning and computer vision is developed in this work, by using simple cameras, such as the factories' security cameras. As the industrial environment is a scenario with a lot of variation and noise, the Transfer Learning technique is used to improve the training step of the developed AGV detection system. Finally, a database with 1067 images is used to build and validate the model, achieving a result greater than 80% of F1-score for various confidence values.

关键词： Training Computer vision Remotely guided vehicles Computational modeling Transfer learning Cameras Production facilities

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Comparison between Line-Followers and Free Movement Robots in Tasks Execution in a Simulated Environment

Comparison between Line-Followers and Free Movement Robots i...

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IEEE Latin American Robotics Symposium, LARS

作者： Igor Pardal Latini Wilson Eduardo Barioni Marco Teixeira Flavio Neves-Jr Lucia Valeria Ramos de Arruda Universidade Tecnológica Federal do Paraná (UTFPR) Curitiba Parana Brazil Automation and Advanced Control System Laboratory (LASCA) Graduate Program in Electrical and Computer Engineering (CPGEI)

ISBN: (数字)9781665462808

ISBN: (纸本)9781665462815

In Industry 4.0, there is a constant pursuit for efficiency and productivity, and, searching to achieve this, the usage of multiple robots to attend to several tasks simultaneously is usual. Nowadays, there is plenty of robotic architectures, having their navigation system based on numerous different sensors. This work compares the line-follower robots, having a determined path, with the free-moving robots that navigate based on odometry, for load collecting and delivery tasks in specific locations. For this, four simulated experiments are run in two scenes, with two and four tasks, respectively. The comparison is based on a difference in robot quantity, with more line-followers than free-moving ones, aiming to collect values such as idle time, task wait time, and the number of tasks done for each machine. The results show advantages in using less but more intelligent robots with free movement. Such robots are not bound to one unique task and can use their idle time to roam and complete other processes. However, the task wait time is a concerning issue, as too few robots for overcharged situations can increase execution delays.

关键词： Service robots Navigation Robot sensing systems Time measurement Sensor systems Sensors Delays

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