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American control Conference (ACC)

作者： Glenn Andreasen Jakob Stoustrup Roozbeh Izadi-Zamanabadi Ángel Á. Pardiñas Armin Hafner Faculty of Electrical Engineering Automation and Control Aalborg University Aalborg Denmark Danfoss A/S Denmark Department of Energy and Process Engineering NTNU Trondheim Norway

This paper describes a data-driven method for system identification of a CO 2 refrigeration system. Traditionally, the interaction between the measured variables is not utilized as they are highly dependent on the refrigeration system. In this work a data-driven method, namely subspace identification, is investigated for deriving a control-oriented model such that the dynamic interaction in the refrigeration systems can be utilized for e.g. fault detection and diagnosis. The subspace identification is applied on laboratory data obtained from a test setup located at NTNU in Trondheim, Norway. The obtained results offer promising perspectives for performance improvement in fault detection and diagnosis methods as well as control strategies.

关键词： Compressors Valves Temperature measurement Heating systems Receivers Coolants

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Visual navigation in real-world Indoor environments using end-to-end deep reinforcement learning

arXiv

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arXiv 2020年

作者： Kulhánek, Jonáš Derner, Erik Babuška, Robert Czech Institute of Informatics Robotics and Cybernetics Czech Technical University in Prague Prague16636 Czech Republic Department of Control Engineering Faculty of Electrical Engineering Czech Technical University in Prague Prague16627 Czech Republic Cognitive Robotics Faculty of 3mE Delft University of Technology CD Delft2628 Netherlands Czech Institute of Informatics Robotics and Cybernetics Czech Technical University in Prague Prague16636 Czech Republic

Visual navigation is essential for many applications in robotics, from manipulation, through mobile robotics to automated driving. Deep reinforcement learning (DRL) provides an elegant map-free approach integrating image processing, localization, and planning in one module, which can be trained and therefore optimized for a given environment. However, to date, DRL-based visual navigation was validated exclusively in simulation, where the simulator provides information that is not available in the real world, e.g., the robot’s position or image segmentation masks. This precludes the use of the learned policy on a real robot. Therefore, we propose a novel approach that enables a direct deployment of the trained policy on real robots. We have designed visual auxiliary tasks, a tailored reward scheme, and a new powerful simulator to facilitate domain randomization. The policy is fine-tuned on images collected from real-world environments. We have evaluated the method on a mobile robot in a real office environment. Training took ~30 hours on a single GPU. In 30 navigation experiments, the robot reached a 0.3-meter neighborhood of the goal in more than 86.7 % of cases. This result makes the proposed method directly applicable to tasks like mobile manipulation. Copyright © 2020, The Authors. All rights reserved.

关键词： Deep learning

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control design considering magnetic flux characteristic uncertainty for magnetic levitation system with magnetic flux and current feedback

IEEJ Transactions on Electronics, Information and Systems

引用

IEEJ Transactions on Electronics, Information and Systems 2019年第10期139卷 1159-1166页

作者： Urasaki, Shinpachiro Kobayashi, Yoshimitsu Kami, Yasushi Mitani, Yuichiroh Nobuyama, Eitaku Department of Electronic Control Engineering National Institute of Technology Gifu College 2236-2. Kamimakuwa. Motosu. Gifu 501-0495 Japan Department of Electrical and Computer Engineering National Institute of Technology Akashi College 679-3. Nishioka. Uozumi Akashi. Hyogo674-8501 Japan Department of Mechanical Engineering National Institute of Technology Numazu College 3600. Ooka. Numazu Shizuoka410-8501 Japan Department of Systems Innovation and Informatics Faculty of Computer Science and System Engineering Kyushu Institute of Technology 680-4.Kawazu. Iizuka Fukuoka820-8502 Japan

This paper describes control design considering magnetic flux characteristic uncertainty for magnetic levitation system with magnetic flux and current feedback. The position of the levitated object is calculated from the hall voltage and current of the electromagnet. We show the uncertainty for magnetic flux characteristic and design the stabilizing controller by proportional feedback with the hall voltage and current. Moreover, we tried to design servo controller by two-degree-of-freedom control by using a finite number of frequency response (FNFR) model including the uncertainty and confirmed the validity of the proposed method by experiment results. © 2019 The Institute of Eleclrical Engineers of Japan.

关键词： Frequency response

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Continuous conveyor system evaluation based on the quality of conveyor belts 18

Continuous conveyor system evaluation based on the quality o...

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18th International Multidisciplinary Scientific Geoconference, SGEM 2018

作者： Marasová, Daniela Andrejiová, Miriam Grinčová, Anna Technical University of Košice Faculty of Mining Ecology Process Control and Geotechnologies Slovakia Technical University of Košice Faculty of Mechanical Engineering Slovakia Technical University of Košice Faculty of Electrical Engineering an Informatics Slovakia

ISBN: (纸本)9786197408355

Belt conveying belongs to high-performance, economically and energy efficient continuous system. Optimization of this conveying systems makes possible reducing the total operating costs up to 30%. For this reason is necessary to choice of the suitable structural elements. Conveyor belt is the most important element of this system and quality of its strength properties is a needful prerequisite for a smooth operation of belt conveyors. Insufficient quality of strength properties has a negative effect on the reliability of the entire continuous belt conveyor system;it causes downtimes and financial loss to a user. Moreover, conveyor belt rupture caused by insufficient strength represents an unacceptable risk in terms of belt conveyor system safety. The present article is focused on the evaluation of conveyor belt quality based on result of the tensile strength belt research and evaluation of experiment using the Design of experiment method. At the end of the article is applied the multi-criterion decision method by the selection of optimal quality of the fabric conveyor belts. The object of the research were 12 different types of fabric conveyor belts. Shapes, dimensions and conditioning of testing specimens were determined according to the international standards. A testing specimens were observed until to disturbance. The purpose of the article is to examine the relationship between the tensile strength, ductility, and elongation at the reference load in selected technical criteria of a conveyor belt. The selection of relevant criteria is a very important step. From the numbers of properties were selected tree main properties-nominal strength, carcass type, number of plies. By utilization method of AHP (Analytic Hierarchy process) was defined the weight of main criteria important for the selection of conveyor belt. The research output is the determination that the strongest impact on the conveyor belts quality had the nominal strength. © 2018, International Multidis

关键词： Operating costs

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Development of electrical Resistance Tomography Applying Vertical Metallic Column

引用

Journal of Physics: Conference Series 2021年第1期1874卷

作者： Suzanna binti Ridzuan Aw Ruzairi bin Hj Abd Rahim Yasmin binti Abdul Wahab Farah Hanan binti Azimi Lia Safiyah binti Syafie Raja Siti Nur Adiimah binti Raja Aris Faculty of Engineering Technology University College TATI (UC TATI) Telok Kalong 24000 Kemaman Terengganu Process Tomography and Instrumentation Engineering Research Group (PROTOM-i) INFOCOMM Research Alliance Faculty of Electrical Engineering Universiti Teknologi Malaysia 81310 UTM Skudai Johor Malaysia Department of Instrumentation & Control Engineering (ICE) Faculty of Electrical & Electronics Engineering Universiti Malaysia Pahang 26600 Pekan Pahang Malaysia

Majority of industrial pipelines and process vessels are constructed from conducting composites. This paper focusing on the hardware and software development of laboratory test electrical Resistance Tomography (ERT) measurement methods to obtain the cross-sectional image of the conductivity distribution of gas bubble phantom in a static vertical metallic column filled with water. The system with sixteen sensors implementation was investigated on a stainless steel vertical column of 100 mm inner diameter. The conducting boundary strategy was applied as the measurement strategy. Software for the current study was developed using Graphical User Interface (GUI) application program in MATLAB. The software contains many functions to ease user to get necessary information from the research done. The cross section image of the bubble phantom was reconstructed using Linear Back Projection (LBP) algorithm after the data collection process was completed. The system has been tested and can successfully generate the phantom under test.

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The application of improving proposals at technical universities and their impact on the quality of education 18

The application of improving proposals at technical universi...

引用

18th International Multidisciplinary Scientific Geoconference, SGEM 2018

作者： Teplická, Katarína Hurná, Soňa Matvija, Miloš Steingartner, William Technical university Faculty of Mining ecology process control and geotechnologies Slovakia Technical university Faculty of Aeronautics Slovakia Technical university Faculty of Materials Metallurgy and Recycling Slovakia Technical university Faculty of Electrical Engineering and Informatics Slovakia

ISBN: (纸本)9786197408355

The Kaizen concept represents a continuous improvement approach to exploiting the potential of human capital. Employees are the bearers and co-creators of values and their performance contributes to increasing efficiency and therefore education strategies need to be directed to the education of university students, potential workers in enterprises in the labor market. In education, there is scope for using the Kaizen concept as an incentive tool that increases the quality of human potential and the level of human factor education. Improving proposals bring the human factor the possibility of self-realization, personal development and career advancement. In the pedagogical process, it is possible to implement the Kaizen method in a questionnaire survey on the quality of education at higher education institutions in terms of the improvement of individual subjects. Improvements have resulted in an increase in the quality of education because, on the basis of the surveys, we have creatively prepared the study plan for field of study Management of earth resources. © 2018, International Multidisciplinary Scientific Geoconference. All rights reserved.

关键词： Human engineering

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Communication-Efficient Distributed Online Nonconvex Optimization with Time-Varying Constraints

arXiv

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arXiv 2025年

作者： Zhang, Kunpeng Xu, Lei Yi, Xinlei Wen, Guanghui Cao, Ming Johansson, Karl H. Chai, Tianyou Yang, Tao State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang110819 China Department of Mechanical Engineering University of Victoria VictoriaBCV8W 2Y2 Canada Shanghai Institute of Intelligent Science and Technology National Key Laboratory of Autonomous Intelligent Unmanned Systems Frontiers Science Center for Intelligent Autonomous Systems Ministry of Education Shanghai201210 China School of Automation Southeast University Nanjing210096 China Engineering and Technology Institute Groningen Faculty of Science and Engineering University of Groningen GroningenAG 9747 Netherlands Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm10044 Sweden

This paper considers distributed online nonconvex optimization with time-varying inequality constraints over a network of agents, where the nonconvex local loss and convex local constraint functions can vary arbitrarily across iterations, and the information of them is privately revealed to each agent at each iteration. For a uniformly jointly strongly connected time-varying directed graph, we propose two distributed bandit online primal–dual algorithm with compressed communication to efficiently utilize communication resources in the one-point and two-point bandit feedback settings, respectively. In nonconvex optimization, finding a globally optimal decision is often NP-hard. As a result, the standard regret metric used in online convex optimization becomes inapplicable. To measure the performance of the proposed algorithms, we use a network regret metric grounded in the first-order optimality condition associated with the variational inequality. We show that the compressed algorithm with one-point bandit feedback establishes an O(Tθ1) network regret bound and an O(T7/4−θ1) network cumulative constraint violation bound, where T is the number of iterations and θ1 ∈ (3/4,5/6] is a user-defined trade-off parameter. When Slater’s condition holds (i.e, there is a point that strictly satisfies the inequality constraints at all iterations), the network cumulative constraint violation bound is reduced to O(T5/2−2θ1). In addition, we show that the compressed algorithm with two-point bandit feedback establishes an O(Tmax{1−θ1,θ1}) network regret and an O(T1−θ1/2) network cumulative constraint violation bounds, where θ1 ∈ (0,1). Moreover, the network cumulative constraint violation bound is reduced to O(T1−θ1) under Slater’s condition. The bounds are comparable to the state-of-the-art results established by existing distributed online algorithms with perfect communication for distributed online convex optimization with inequality constraints. To the best of our knowledge, thi

关键词： Convex optimization

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Efficient MedSAMs: Segment Anything in Medical Images on Laptop

arXiv

引用

arXiv 2024年

作者： Ma, Jun Li, Feifei Kim, Sumin Asakereh, Reza Le, Bao-Hiep Nguyen-Vu, Dang-Khoa Pfefferle, Alexander Wei, Muxin Gao, Ruochen Lyu, Donghang Yang, Songxiao Purucker, Lennart Marinov, Zdravko Staring, Marius Lu, Haisheng Dao, Thuy Thanh Ye, Xincheng Li, Zhi Brugnara, Gianluca Vollmuth, Philipp Foltyn-Dumitru, Martha Cho, Jaeyoung Mahmutoglu, Mustafa Ahmed Bendszus, Martin Pflüger, Irada Rastogi, Aditya Ni, Dong Yang, Xin Zhou, Guang-Quan Wang, Kaini Heller, Nicholas Papanikolopoulos, Nikolaos Weight, Christopher Tong, Yubing Udupa, Jayaram K. Patrick, Cahill J. Wang, Yaqi Zhang, Yifan Contijoch, Francisco McVeigh, Elliot Ye, Xin He, Shucheng Haase, Robert Pinetz, Thomas Radbruch, Alexander Krause, Inga Kobler, Erich He, Jian Tang, Yucheng Yang, Haichun Huo, Yuankai Luo, Gongning Kushibar, Kaisar Amankulov, Jandos Toleshbayev, Dias Mukhamejan, Amangeldi Egger, Jan Pepe, Antonio Gsaxner, Christina Luijten, Gijs Fujita, Shohei Kikuchi, Tomohiro Wiestler, Benedikt Kirschke, Jan S. de la Rosa, Ezequiel Bolelli, Federico Lumetti, Luca Grana, Costantino Xie, Kunpeng Wu, Guomin Puladi, Behrus Martín-Isla, Carlos Lekadir, Karim Campello, Victor M. Shao, Wei Brisbane, Wayne Jiang, Hongxu Wei, Hao Yuan, Wu Li, Shuangle Zhou, Yuyin Wang, Bo AI Collaborative Centre University Health Network Department of Laboratory Medicine and Pathobiology University of Toronto Vector Institute Toronto Canada Peter Munk Cardiac Centre University Health Network Toronto Canada Toronto General Hospital Research Institute University Health Network Department of Computer Science University of Toronto University Health Network Vector Institute Toronto Canada University of Science Vietnam National University Ho Chi Minh City Viet Nam Institute of Computer Science University of Freiburg Freiburg Germany School of Medicine and Health Harbin Institute of Technology Harbin China Division of Image Processing Department of Radiology Leiden University Medical Center Leiden Netherlands Department of System and Control Engineering School of Engineering Institute of Science Tokyo Formerly Tokyo Institute of Technology Tokyo Japan Institute for Anthropomatics and Robotics Karlsruhe Institute of Technology Karlsruhe Germany School of Information and Communication Engineering University of Electronic Science and Technology of China Chengdu China School of Electrical Engineering and Computer Science University of Queensland Brisbane Australia School of Cyberspace Hangzhou Dianzi University Hangzhou China Division for Computational Radiology and Clinical AI The Department of Neuroradiology University Hospital Bonn Germany Division for Computational Radiology and Clinical AI The Department of Neuroradiology University Hospital Bonn Germany Department of Neuroradiology Heidelberg University Hospital Heidelberg Germany Division for Computational Radiology and Clinical AI Department of Neuroradiology University Hospital Bonn Germany School of Biomedical Engineering Shenzhen University Shenzhen China School of Biological Science and Medical Engineering Southeast University Nanjing China Department of Urology Cleveland Clinic Cleveland United States Department of Computer Science University of Minnesota Minneapolis United St

Promptable segmentation foundation models have emerged as a transformative approach to addressing the diverse needs in medical images, but most existing models require expensive computing, posing a big barrier to their adoption in clinical practice. In this work, we organized the first international competition dedicated to promptable medical image segmentation, featuring a large-scale dataset spanning nine common imaging modalities from over 20 different institutions. The top teams developed lightweight segmentation foundation models and implemented an efficient inference pipeline that substantially reduced computational requirements while maintaining state-of-the-art segmentation accuracy. Moreover, the post-challenge phase advanced the algorithms through the design of performance booster and reproducibility tasks, resulting in improved algorithms and validated reproducibility of the winning solution. Furthermore, the best-performing algorithms have been incorporated into the open-source software with a user-friendly interface to facilitate clinical adoption. The data and code are publicly available to foster the further development of medical image segmentation foundation models and pave the way for impactful real-world applications. © 2024, CC BY-NC-SA.

关键词： Open source software

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Optimisation of Sensor Electrode Size for in electrical Resistance Tomography Implementing Conducting Boundary Strategy

引用

Journal of Physics: Conference Series 2021年第1期1874卷

作者： Suzanna Ridzuan Aw Ruzairi Abdul Rahim Fazlul Rahman Mohd Yunus Mohd Hafiz Fazalul Rahiman Yasmin Abdul Wahab Farah Hanan Azimi Lia Safiyah Syafie Nurul Huda Mat Tahir Raja Siti Nur Adiimah Raja Aris Shahrulnizahani Mohammad Din Faculty of Engineering Technology University College TATI (UC TATI) Telok Kalong 24000 Kemaman Terengganu Process Tomography and Instrumentation Engineering Research Group (PROTOM-i) INFOCOMM Research Alliance Faculty of Electrical Engineering Universiti Teknologi Malaysia 81310 UTM Skudai Johor Malaysia Faculty of Electrical Engineering Universiti Malaysia Perlis Pauh Putra Campus 02600 Arau Perlis Malaysia Department of Instrumentation & Control Engineering (ICE) Faculty of Electrical & Electronics Engineering Universiti Malaysia Pahang 26600 Pekan Pahang Malaysia

electrical Resistance Tomography (ERT), due to its diverse advantages has become a promising technique for monitoring and analysing various industrial flows. In this research, an ERT system employing a conducting bubble column was studied because a majority of industrial processes use metal composites for their columns. This paper presents an approach to obtain the optimum size of electrodes in ERT to maximize the capability of an ERT system. A finite element model using COMSOL software was developed to investigate the effect of the electrode size in ERT on sensing field distribution. By adapting the conducting boundary strategies in COMSOL, wider and longer electrodes reduce the potential change near source, suggesting less current density near source. Besides that, wider and longer electrodes also reduce the potential drop and improve the signal strength in electrical Resistance Tomography. The optimum size of 12 mm x 100 mm electrode is sufficient for the proposed ERT system using conducting bubble column.

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Remote real-time wastewater surveillance by the optical sensor supported by machine learning

Sensors and Actuators Reports

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Sensors and Actuators Reports 2025年 10卷

作者： Małgorzata Szczerska Kacper Cierpiak Monika Kosowska Paweł Wityk Sebastián García-Galán Patryk Sokołowski Sylwia Fudala-Książek Michał T. Tomczak Bei Ye Aneta Łuczkiewicz Department of Metrology and Optoelectronics Faculty of Electronics Telecommunications and Informatics Gdańsk University of Technology 11/12 Narutowicza Street 80-233 Gdansk Poland Faculty of Telecommunications Computer Science and Electrical Engineering Bydgoszcz University of Science and Technology Al. Prof. S. Kaliskiego 7 85-796 Bydgoszcz Poland Department of Biotechnology and Microbiology Faculty of Chemistry Gdańsk University of Technology 11/12 Narutowicza Street 80-233 Gdansk Poland Department of Biopharmaceutics and Pharmacodynamics Medical University of Gdańsk Hallera 107 Pharmacy Faculty Gdańsk Poland Telecommunications Engineering Department Linares Higher Polytechnic School Jaén University Avenida de la Universidad S/N 23700 Linares Jaén Spain Department of Water and Wastewater Technology Faculty of Civil and Environmental Engineering Gdańsk University of Technology 11/12 Narutowicza Street 80-233 Gdańsk Poland Faculty of Management and Economics Gdańsk University of Technology 11/12 Narutowicza Street 80-233 Gdańsk Poland Shenzhen Key Laboratory of Ecological Remediation and Carbon Sequestration Environmental Protection Key Laboratory of Microorganism Application and Risk Control Institute of Environment and Ecology Shenzhen International Graduate School Tsinghua University Shenzhen 518055 PR China

In this study, a remote monitoring sewage system based on optical method is presented for the first time. The built-in wastewater surveillance system can perform autonomous monitoring with no requirement of sample collection and its transport to the laboratory. The measurement results can be obtained in real time, the work operation allows continuous or on-demand mode. The study includes design, development and application of a biofunctionalized fiber-optic sensor, as well as engaging machine learning algorithms for measured signals classification. The validated SARS-CoV-2 antibodies sensor has a measurement range of 10 −12 mg/mL to 10 −1 mg/mL. Known concentrations of Immunoglobulin G (IgG) from 10 −6 mg/mL to 10 −1 mg/mL were added to the tested wastewater samples and then detected by the prepared optical probe. The data obtained were then processed and classified by traditional method and selected machine learning algorithms; the results obtained for the KNeighbors algorithm are Balanced Accuracy of 92.97 % and F1-score of 94.19 %. This study is of significance to establish a system that can effectively monitor the outbreak of potential infections in society.

关键词： Remote wastewater surveillance Real-time monitoring SARS-CoV-2 Optical sensors Fiber optic sensor Machine learning

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