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4th International Conference on Intelligent Power and Systems, ICIPS 2024

作者： Wu, Tongqi Zou, Bin Shanghai University Dept. Department of Control Science and Engineering Shanghai China

ISBN: (纸本)9798331532765

In recent years, the development of new energy sources has led to a reduction in the proportion of thermal power generation, which in turn has highlighted the issue of non-convexities in electricity markets. Convex hull pricing is a well-documented method for coping with the non-existence of uniform clearing prices in electricity markets with non-convex costs and constraints. This paper revisits the primal and dual approaches for calculating convex hull prices, discusses the Dantzig-Wolfe decomposition method, and highlights its limitations. Building on this, we propose a simplified approach to convex hull pricing. Additionally, we provide empirical evidence about the favorable performance of our algorithm on large test instances based on RTS system. © 2024 IEEE.

关键词： convex hull pricing level method simplified approach uniform clearing prices

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Non-Line-of-Sight Imaging Using AdaGrad-ADMM

Non-Line-of-Sight Imaging Using AdaGrad-ADMM

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2023 China Automation Congress, CAC 2023

作者： Shi, Di Shi, Ruolin Wang, Yong Li, Li Cheng, Shuming Tongji University Dept. Control Science and Engineering Shanghai China

ISBN: (纸本)9798350303759

Non-line-of-sight (NLOS) imaging aims to reconstruct the hidden scene using transients reflected from the relay wall. The reconstruct task can be formulated as an inverse problem and many methods have been proposed using convolutional kernels to solve this problem, which are either inefficient or inaccurate to complete the reconstruction. Here we use the convolutional approximation of the Gram operator of the transportation matrix to formulate the reconstruction as a computationally-efficient optimization problem. As the inherent features of sparsity and positivity are added as regularization to the above optimization problem, we employ the ADMM method to find the suitable regularization coefficients. We further use AdaGrad-Norm, an adaptive gradient descent algorithm, to efficiently solve the reformulated optimization objective. Finally, we test our method via both simulated and real scenes and demonstrate its advantages of reconstruct accuracy and efficiency in comparison to other commonly-used methods. © 2023 IEEE.

关键词： Inverse problems

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Innovative System of Cameras Allowing to Coordinate the Flight of a Swarm of UAVs 6

Innovative System of Cameras Allowing to Coordinate the Flig...

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6th International Conference on control and Robotics, ICCR 2024

作者： Muller, Jens Horn, Joachim Larkin, Kevin Schweim, Marie Schweim, Anne Helmut-Schmidt-University Dept. of Control Engineering Hamburg Germany Carnegie Mellon University Dept. of Materials Science and Engineering PittsburghPA United States

ISBN: (纸本)9798331518158

This paper aims to deliver insights into an innovative camera system called the Swarm Flight Unit (SFU). The SFU enables unmanned aerial vehicles (UAVs) to coordinate their movements as a swarm without any external help. Over the course of several years of development, conventional image processing algorithms were used to tackle the task of identifying and localizing drones in real time. This paper will describe applied methods, show the results of validation tests performed within a dedicated test bench, and prospect further actions regarding device integration. © 2024 IEEE.

关键词： Flight testing

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Detection of Electric Motor Damage Through Analysis of Sound Signals Using Bayesian Neural Networks 50

Detection of Electric Motor Damage Through Analysis of Sound...

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50th Annual Conference of the IEEE Industrial Electronics Society, IECON 2024

作者： Bauer, Waldemar Zagórowska, Marta Baranowski, Jerzy Dept. of Automatic Control & Robotics AGH University of Krakow Krakow Poland Dept. of Engineering Cybernetics Norwegian University of Science and Technology Trondheim Norway

ISBN: (纸本)9781665464543

Fault monitoring and diagnostics are important to ensure reliability of electric motors. Efficient algorithms for fault detection improve reliability, yet development of cost-effective and reliable classifiers for diagnostics of equipment is challenging, in particular due to unavailability of well-balanced datasets, with signals from properly functioning equipment and those from faulty equipment. Thus, we propose to use a Bayesian neural network to detect and classify faults in electric motors, given its efficacy with imbalanced training data. The performance of the proposed network is demonstrated on real life signals, and a robustness analysis of the proposed solution is provided. © 2024 IEEE.

关键词： Damage detection

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Enhancing Energy Efficiency and Renewable Integration in Industrial Plants through DC Microgrids: A Case Study for an Ethylene Plant 25

Enhancing Energy Efficiency and Renewable Integration in Ind...

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25th International Middle East Power System Conference, MEPCON 2024

作者： Gomaa, Abdallah. M. Abdelrahim, Ahmed Atteya, Inji. I. Ahmed Ashour, Hamdy Arab Academy for Science Technology and Maritime Transport Dept. of Electrical and Control Engineering Alexandria Egypt Arab Academy for Science Technology and Maritime Transport Dept. of Basic and Applied Science Alexandria Egypt

ISBN: (纸本)9798350379648

As industrial plants seek to improve energy efficiency and reduce carbon emissions in line with climate change mitigation strategies, the implementation of DC microgrids presents a promising solution. This study investigates the potential of DC microgrids to enhance energy efficiency and facilitate the integration of renewable energy resources, particularly solar photovoltaic (PV) systems, in industrial settings. The research focuses on the advantages of DC microgrids over traditional AC systems, specifically in reducing the number of conversion stages required for system design. A case study of an ethylene plant is presented to illustrate the benefits of implementing a DC microgrid in an industrial environment. The study employs ETAP and PVsyst software for analysis and simulations. Results demonstrate that the adoption of a DC microgrid leads to a significant reduction in conversion losses, resulting in enhancing the overall system efficiency by 9.5%. Furthermore, The DC microgrid enhanced the benefits of integrating the same PV capacity, reducing grid energy consumption and carbon emissions by 20.5% compared to the AC microgrid. The findings have important implications for industrial energy management and sustainable manufacturing practices in the context of global efforts to combat climate change. © 2024 IEEE.

关键词： carbon emissions DC microgrid energy efficiency Ethylene plants PV system uninterruptible power supply variable speed drives

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Evaluation of Simulated Training Results based on Deep Learning and Battlefield Situation Awareness 24

Evaluation of Simulated Training Results based on Deep Learn...

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24th International Carpathian control Conference, ICCC 2023

作者： Liu, ZhaoXiang Li, Yingshun Guo, ZhanNan Dalian University of Technology Dept. School of Control Science and Engineering Dalian China

ISBN: (纸本)9798350310221

Battlefield situation awareness is the basis of command decision in simulated battlefield combat training. The accuracy of battle commanders' judgements and decisions on the environment of the battlefield can be improved with the advancement of artificial intelligence technologies. In this paper, firstly, the calculation model of situation evolution speed is derived by simulating the self information of situation factors in battlefield training, and a case is analyzed with Markov chain;Then the cross entropy loss function of the deep learning model is derived from the evolution speed prediction model of the situation factors in the two-dimensional grid, which is equivalent to the evolution speed of the situation. Finally, the uncertainty of situation factors, the speed of situation evolution and the accuracy of training prediction are analyzed through the experimental results, and it is found that for the situation factors with randomness, the prediction accuracy has an extreme value. © 2023 IEEE.

关键词： Convolutional neural networks

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Challenges in AI-supported Process Analysis in the Italian Judicial System: what After Digitalization?

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Digital Government: Research and Practice 2024年第1期5卷 1-10页

作者： Bianchini, Devis Bono, Carlo Campi, Alessandro Cappiello, Cinzia Ceri, Stefano De Luzi, Francesca Mecella, Massimo Pernici, Barbara Plebani, Pierluigi Dept. of Computer Science University of Brescia Via Branze 38 Brescia25123 Italy Dept. of Electronics Information and Bioengineering Politecnico di Milano Piazza Leonardo da Vinci 32 Milan20133 Italy Dept. of Computer Control and Management Engineering Sapienza Universitá di Roma Via Ariosto 25 Roma00185 Italy

In this commentary article, we outline research challenges and possible directions for the potential applications of AI in the judicial domain by specifically considering process analysis in the Italian context. Applying AI to process analysis poses several challenges, including information extraction from legacy information systems and analysis of legal documents, process modeling with a particular emphasis on temporal analysis, real-time process monitoring, conformance and compliance checking, predictive techniques for accurate predictions, and analysis of judges' workload. Solutions to these challenges include methods and tools for data identification and collection, innovative approaches to process modeling, reactive techniques for real-time monitoring, conformance checking with explainability, language models adapted to specific domains, and the identification of suitable indicators for the analysis of case handling efficiency and case classification. Copyright © 2024 held by the owner/author(s).

关键词： Process monitoring

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Physics-Informed Neural Networks: A Step Towards Data-Driven Optimization of Additive Manufacturing 29

Physics-Informed Neural Networks: A Step Towards Data-Driven...

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29th IEEE International Conference on Emerging Technologies and Factory Automation, ETFA 2024

作者： Depaoli, Fabio Felicioni, Stefano Ponzio, Francesco Aliberti, Alessandro MacIi, Enrico Bondioli, Federica Padovano, Elisa Di Cataldo, Santa Dept. of Control and Computer Engineering Politecnico di Torino Italy Dept. of Applied Science and Technology Politecnico di Torino Italy Interuniv. Dept. of Reg. and Urban Studies and Planning Politecnico di Torino Italy

ISBN: (纸本)9798350361230

Laser powder bed fusion (L-PBF) is the most popular Additive Manufacturing (AM) process for metals. It builds a 3D object layer-by-layer, by spreading metal powder on top of the previous layer and selectively melting it with a laser. Despite its many advantages, large-scale production may be hampered by the large number of process parameters and the challenges associated with their optimization. We propose an automated parameter selection approach based on process signatures extracted from a parameterized simulation of the process. Specifically, we outline a rapid data-driven simulation method based on Physics-Informed Neural Network (PINN). This approach involves training a neural network to solve the partial differential equation describing the process at varying values of a parameter of interest (for example, the laser power), thus eliminating the need for repeated Finite Elements Method (FEM) simulations. Our preliminary experiments demonstrate the feasibility of our approach. © 2024 IEEE.

关键词： Smart manufacturing

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Aerogel defect detection using terahertz waves 11

Aerogel defect detection using terahertz waves

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Infrared, Millimeter-Wave, and Terahertz Technologies XI 2024

作者： Maa, Yehao Shen, Liran Cao, Yuqi Hou, Dibo Zhang, Guangxin State Key Laboratory of Industrial Control Technology Dept. of Control Science and Engineering Zhejiang University Hangzhou310027 China Robotics Institute Ningbo University of Technology Ningbo315211 China

ISBN: (数字)9781510682238

ISBN: (纸本)9781510682221

Aerogel is known as super insulation materials and has already been applied to manufacture thermal protection parts of aerospace equipment. Terahertz (THz) wave has good penetration to non-metallic and non-polar materials. To explore its potential in aerogel defect detection, the absorption coefficient and refractive index of aerogel were studied. As a result, the absorption spectrum of aerogel has not obvious absorption peak, and THz wave has great penetration for aerogel. Additionally, two aerogel samples with different sizes of defects were imaged with two time domain parameters (pulse peak and pulse valley) and two frequency domain parameters (absorption coefficient and refractive index). In contrast to other three parameters, the refractive index presents the greatest performance in defect detection, defects in the aerogel can be observed more clearly through the refractive index. The study is of key importance for THz wave in nondestructive testing for aerogel, offering a rapid and non-destructive detection method for aerogel defects. © 2024 SPIE.

关键词： Refractive index

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Optical Evanescent Field for Direct Observation of Sub-100nm Particle Motion on Glass Surface 1

Optical Evanescent Field for Direct Observation of Sub-100nm...

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1st International Conference on Robotics, engineering, science, and Technology, RESTCON 2024

作者： Khajornrungruang, Panart Permpatdechakul, Thitipat Suzuki, Keisuke Blattler, Aran Terayama, Yutaka Goto, Daiki Phaisalpanumas, Pipat Bun-Athuek, Natthaphon Phunopas, Amornphun Kyushu Institute of Technology Iizuka-Shi Mechanical Science and Technology Division Dept. of Intelligent and Control System Faculty of Computer Science and Systems Engineering Fukuoka Japan Kyushu Institute of Technology Iizuka-Shi Mechanical Information Science and Technology Division Dept. of Interdisciplinary Informatics Graduate School of Computer Science and Systems Engineering Fukuoka Japan King Mongkut's University of Technology North Bangkok Bangsue Faculty of Engineering Dept. of Production and Robotics Engineering Bangkok Thailand Kyushu Institute of Technology Iizuka-Shi Mechanical Science and Technology Course Dept. of Intelligent and Control System Graduate School of Computer Science and Systems Engineering Fukuoka Japan King Mongkut's University of Technology North Bangkok Bangsue Faculty of Engineering Dept. of Industiral Engineering Bangkok Thailand King Mongkut's University of Technology North Bangkok Bangsue College of Industrial Technology Dept. of Mechanical Engineering Technology Bangkok Thailand

ISBN: (纸本)9798350348842

To directly investigate the dynamic nanoscale phenomenon on the surface being processed in wet conditions such as precision polishing, and cleaning in semiconductor industrial, an optical method for visualization and observation of each sub-100 nm sized particle that is moving on an interface such as a silica glass surface by applying an evanescent field have been proposing. Subsequently, we developed an experimental apparatus equipped with an optical microscopy system for verifying the moving particle observation method in a laboratory scale. This article introduces some experimentally direct observation results of duplicated wet processes. © 2024 IEEE.

关键词： Visualization

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