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Innovative dust detection and efficient cleaning of PV Panels: A CNN‑RF approach using I–V curve data transformed into RGB mosaics

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Energy Conversion and Management: X 2025年

作者： Safia Babikir Bashir Mena Maurice Farag Abdul-Kadir Hamid Ali A. Adam Ramesh C. Bansal Nsilulu T Mbungu A. Elnady Ahmed G. Abo-Khalil Mousa Hussein Smart Grid Research Group Sustainable Energy and Power Systems Research Center Research Institute of Sciences and Engineering (RISE) Department of Electrical Engineering University of Sharjah Sharjah 27272 United Arab Emirates Smart Automation and Communication Technologies Research Center (SACT) University of Sharjah 27272 Sharjah United Arab Emirates Department of Electrical Electronic and Computer Engineering University of Pretoria Pretoria South Africa Department of Electrical and Communication Engineering United Arab Emirates University Al Ain United Arab Emirates

Photovoltaic (PV) panels are vital for renewable energy generation, yet their efficiency is critically hindered by environmental challenges such as dust accumulation, especially in arid regions like the UAE. Dust buildup can reduce efficiency by up to 30% within a month, threatening the sustainability of solar power, which is projected to supply 10% of global energy by 2030. Existing cleaning methods are unsustainable, consuming an estimated 10 billion gallons of water annually, enough to meet the drinking needs of 2 million people, necessitating the development of a cost-effective, resource-efficient alternative. This research presents a novel machine learning-based system to automate dust detection and optimize cleaning, significantly reducing water consumption while improving power generation efficiency. The methodology transforms I-V curve electrical parameters into RGB mosaic images, enabling precise classification of operational states such as normal operation, dust accumulation, shading, and faults without relying on external imaging devices. The system is built on a hybrid model combining Convolutional Neural Networks (CNN) and Random Forest (RF) classifiers (CNN-RF), where the CNN extracts high-level features from RGB mosaic images, and the RF classifier accurately categorizes operational states. Upon detecting dust accumulation, a secondary CNN-RF model classifies the severity into low, moderate, or heavy, guiding an optimized cleaning process that minimizes water usage while maintaining cleaning effectiveness. The primary CNN-RF model achieved 100% accuracy in classifying operational states using RGB mosaic images, surpassing the 97% accuracy achieved by I–V curve-based methods. Furthermore, the secondary CNN-RF model for dust severity classification attained an accuracy of 98% using RGB mosaic images, compared to only 68% when using traditional I–V curves, highlighting the superior performance of RGB mosaic images in detecting fine-grained dust levels. T

关键词： Automated Cleaning Convolutional Neural Networks Dust Detection Machine Learning Photovoltaics

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Reducing the Modeling Error by Observer Based PID Regulators for a Class of Factorable Nonlinear Plants

Reducing the Modeling Error by Observer Based PID Regulators...

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作者： Keviczky, L. Bányász, Cs. Institute of Computer Science and Automation MTA-BME Control Engineering Research Group Hungarian Academy of Sciences H-1111 Budapest Kende u 13-17 Hungary

A PID regulator tuning method is introduced for HAMMERSTEIN and WIENER type block-oriented cascade factorable nonlinear models. Then the YOULA-parameterization approach is discussed which allows to develop an observer... 详细信息

关键词： Proportional control systems

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Steady-state Voltage Security-constrained Optimal Frequency control for Weak HVDC Sending-end AC Power Systems

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Journal of Modern Power Systems and Clean Energy 2024年第2期12卷 658-669页

作者： Qiangqiang Wang Liangzhong Yao Jian Xu Yuping Zheng Wei Li Wei Wang School of Electrical Engineering and Automation Wuhan UniversityWuhan 430072China Hubei Engineering and Technology Research Center for AC/DC Intelligent Distribution Network(Wuhan University) Wuhan 430072China State Key Laboratory of Smart Grid Protection and Control NARI Group Corporation(State Grid Electric Power Research Institute)Nanjing 211106China

Due to the fact that a high share of renewable energy sources(RESs)are connected to high-voltage direct current(HVDC)sending-end AC power systems,the voltage and frequency regulation capabilities of HVDC sending-end AC power systems have *** has resulted in potential system operating problems such as overvoltage and overfrequency,which occur simultaneously when block faults exist in the HVDC *** this study,a steady-state voltage security-constrained optimal frequency control method for weak HVDC sending-end AC power systems is *** integrated virtual inertia control of RESs is employed for system frequency *** dynamic reactive power compensation devices are utilized to control the voltage of all nodes meet voltage security ***,an optimization model that simultaneously considers the frequency and steady-state voltage security constraints for weak HVDC sending-end AC power systems is *** optimal control scheme with the minimum total cost of generation tripping and additional dynamic reactive power compensation required is obtained through the optimization *** are conducted on a modified IEEE 9-bus test system and practical Qing-Yu line commutated converter based HVDC(LCC-HVDC)sending-end AC power system to verify the effectiveness of the proposed method.

关键词： Renewable energy source(RES) high-voltage direct current(HVDC) AC power system optimal frequency control steady-state voltage security dynamic reactive power compensation

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Knowledge-based diagnosis of process systems using procedure HAZID information

Knowledge-based diagnosis of process systems using procedure...

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Lecture Notes in computer Science

作者： Werner-Stark, Ágnes Németh, Erzsébet Hangos, Katalin M. Department of Electrical Engineering and Information Systems University of Pannonia Veszprém Hungary School of Chemical Engineering University of Queensland Brisbane QLD Australia Process Control Research Group Systems and Control Laboratory Computer and Automation Research Institute Budapest Hungary

ISBN: (纸本)9783642238536

Earlier investigations show that the results of hazard identification (HAZID) and analysis (e.g. HAZOP or FMEA) can effectively be used for knowledge-based diagnosis of complex process systems in their steady-state operation. In order to extend this approach for transient operating conditions controlled by operating procedures, the notion of nominal input-output event sequences of qualitative signals has been introduced, and the deviations used in the procedure HAZID analysis have been defined therefrom. The diagnosis can then be performed algorithmically by matching the deviation sequences of the observed input-output event sequences and the nominal ones generated by qualitative dynamic models. The concepts and methods are illustrated using a simple case study consisting of a simple tank, controlled by an operating procedure. © 2011 Springer-Verlag.

关键词： Hazards

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An algorithm for recognizing palm polygons

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The Visual computer 1994年第8期10卷 443-451页

作者： Ghosh, Subir Kumar Maheshwari, Anil Pal, Sudebkumar Prasant Madhavan, C.E.Veni Computer Science Group Tata Institute of Fundamental Research Bombay 400005 India Computer Systems and Communications Group Tata Institute of Fundamental Research Bombay 400005 India Department of Computer Science and Engineering Indian Institute of Technology Kharagpur 721302 India Department of Computer Science and Automation Indian Institute of Science Bangalore 560012 India

A polygon P is said to be a palm polygon if there exists a point x∈P such that the Euclidean shortest path from x to any point y∈P makes only left turns or only right turns. The set of all such points x is called the palm kernel. In this paper we propose an O(E) time algorithm for recognizing a palm polygon P, where E is the size of the visibility graph of P. The algorithm recognizes the given polygon P as a palm polygon by computing the palm kernel of P. If the palm kernel is not empty, P is a palm polygon. © 1994 Springer-Verlag.

关键词： Computational geometry Kernel Palm polygon Visibility graph Weak visibility polygon

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Roadmap on Neuromorphic Photonics

arXiv

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arXiv 2025年

作者： Brunner, Daniel Shastri, Bhavin J. Al-Qadasi, Mohammed A. Ballani, H. Barbay, Sylvain Biasi, Stefano Bienstman, Peter Bilodeau, Simon Bogaerts, Wim Böhm, Fabian Brennan, G. Buckley, Sonia Cai, Xinlun Strinati, Marcello Calvanese Canakci, B. Charbonnier, Benoit Chemnitz, Mario Chen, Yitong Cheung, Stanley Chiles, Jeff Choi, Suyeon Christodoulides, Demetrios N. Chrostowski, Lukas Chu, J. Clegg, J.H. Cletheroe, D. Conti, Claudio Dai, Qionghai Di Lauro, Luigi Diamantopoulos, Nikolaos-Panteleimon Dinc, Niyazi Ulas Ewaniuk, Jacob Fan, Shanhui Fang, Lu Franchi, Riccardo Freire, Pedro Gentilini, Silvia Gigan, Sylvain Giorgi, Gian Luca Gkantsidis, C. Gladrow, J. Goi, Elena Goldmann, M. Grabulosa, A. Gu, Min Guo, Xianxin Hejda, Matěj Horst, F. Hsieh, Jih-Liang Hu, Jianqi Hu, Juejun Huang, Chaoran Hurtado, Antonio Jaurigue, Lina Kalinin, K.P. Kamalian-Kopae, Morteza Kelly, D.J. Khajavikhan, Mercedeh Kremer, H. Laydevant, Jeremie Lederman, Joshua C. Lee, Jongheon Lenstra, Daan Li, Gordon H.Y. Li, Mo Li, Yuhang Lin, Xing Lin, Zhongjin Lis, Mieszko Lüdge, Kathy Lugnan, Alessio Lupo, Alessandro Lvovsky, A.I. Manuylovich, Egor Marandi, Alireza Marchesin, Federico Massar, Serge McCaughan, Adam N. McMahon, Peter L. Moralis-Pegios, Miltiadis Morandotti, Roberto Moser, Christophe Moss, David J. Mukherjee, Avilash Nikdast, Mahdi Offrein, B.J. Oguz, Ilker Oripov, Bakhrom O'Shea, G. Ozcan, Aydogan Parmigiani, F. Pasricha, Sudeep Pavanello, Fabio Pavesi, Lorenzo Peserico, Nicola Pickup, L. Pierangeli, Davide Pleros, Nikos Porte, Xavier Primavera, Bryce A. Prucnal, Paul Psaltis, Demetri Puts, Lukas Qiao, Fei Rahmani, B. Raineri, Fabrice Ríos Ocampo, Carlos A. Robertson, Joshua Romeira, Bruno Roques-Carmes, Charles Rotenberg, Nir Rowstron, A. Schoenhardt, Steffen Schwartz, Russell L.T. Shainline, Jeffrey M. Shekhar, Sudip Skalli, A. Sohoni, Mandar M. Sorger, Volker J. Soriano, Miguel C. Spall, James Stabile, Ripalta Stiller, Birgit Sunada, Satoshi Tefas, Anastasios Tossoun, Bassem Tsakyridis, Apostolos Turitsyn, Sergei K. Van der Sande, G Université Marie et Louis Pasteur CNRS UMR 6174 Institut FEMTO-ST Besançon25000 France Centre for Nanophotonics Department of Physics Engineering Physics & Astronomy Queen's University Canada Department of Electrical and Computer Engineering The University of British Columbia Vancouver Canada Microsoft Research Cambridge United Kingdom Université Paris-Saclay CNRS Centre de Nanosciences et de Nanotechnologies France Nanoscience Laboratory Department of Physics University of Trento Italy Photonics Research Group Department of Information Technology Ghent University imec Belgium Princeton University NJ United States Hewlett Packard Labs Hewlett Packard Enterprise Böblingen Germany National Institute of Standards and Technology BoulderCO United States State Key Laboratory of Optoelectronic Materials and Technologies School of Electronics and Information Technology Sun Yat-sen University China Enrico Fermi Research Center Rome Italy Université Grenoble-Alpes CEA Leti Grenoble France Leibniz-Institute of Photonic Technology Jena Germany Institute of Applied Optics and Biophysics Jena Germany Department of Automation Tsinghua University Beijing China Department of Electrical and Computer Engineering North Carolina State University NC United States Department of Electrical Engineering Stanford University CA United States University of Southern California Los AngelesCA United States Department of Physics Sapienza University Rome Italy Institute for Complex Systems National Research Council Rome Italy Varennes Canada NTT Device Technology Labs NTT Corporation Kanagawa Atsugi Japan Institute of Electrical and Microengineering School of Engineering École Polytechnique Fédérale de Lausanne Switzerland Edward L. Ginzton Laboratory Stanford University StanfordCA United States Department of Electronic Engineering Tsinghua University China Beijing National Research Center for Information Science and Technology Tsinghua University China Aston Univ

Neuromorphic photonics are processors inspired by the human brain and enabled by light (photons) instead of traditional electronics. Neuromorphic photonics and its associated concepts are experiencing a significant resurgence, building on foundational research from the 1980s and 1990s. This renewed momentum is driven by breakthroughs in photonic integration, nonlinear optics, and advanced materials, alongside the growing necessity of neuro-inspired computing in numerous applications of economic and societal relevance. The increasing demand for energy-efficient artificial intelligence (AI) solutions underscores the need for innovation and a cohesive vision to address key challenges, including scalability, energy efficiency, precision, and standardized performance benchmarks. Together, these efforts present an opportunity to establish a unique photonic advantage with practical, real-world applications. This roadmap consolidates recent advances while exploring emerging applications, reflecting the remarkable diversity of hardware platforms, neuromorphic concepts, and implementation philosophies reported in the field. It emphasizes the critical role of cross-disciplinary collaboration in this rapidly evolving field. The roadmap introduces various approaches to embedding the high-complexity transformations central to neuromorphic computing, focusing on frequency, delay, and spectral embeddings. This is followed by a discussion of architectures of photonic neural networks (PNNs) and an in-depth analysis of methods for implementing these architectures in photonic hardware. Dedicated sections delve into integrated photonic hardware, the realization of photonic weights and memories, and the optimization of training processes for photonic neuromorphic architectures. The roadmap concludes by exploring numerous potential applications, highlighting the challenges and advances necessary to transition neuromorphic photonic computing from a primarily academic pursuit to a technolog

关键词： Philosophical aspects

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Dynamic modeling and model analysis of a large industrial synchronous generator

Dynamic modeling and model analysis of a large industrial sy...

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作者： Fodor, Attila Magyar, Attila Hangos, Katalin M. Department of Electrical Engineering and Information Systems University of Pannonia 8200 Veszprém Hungary Process Control Research Group Computer and Automation Research Institute HAS Budapest Hungary

ISBN: (纸本)9788070438657

A simple dynamic model of an industrial size synchronous generator operating in a nuclear power plant is developed in this paper based on first engineering principles. The constructed state-space model consists of a nonlinear state equation and a bi-linear output equation. It has been shown that the model is locally asymptotically stable with parameters obtained from the literature for a similar generator. The effect of load disturbances on the partially controlled generator has been analyzed by simulation using a traditional PI controller. It has been found that the controlled system is stable and can follow the set-point changes in the effective power well. The disturbance rejection of the controller is also satisfactory.

关键词： Disturbance rejection

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Rice Variety Classification Based on Optimized Near-Infrared Spectral Classification Model

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Rice science 2024年第1期31卷 6-9,I0009-I0012页

作者： YANG Sen WANG Zhenmin ZHANG Houqing SONG Wenlong College of Computer and Control Engineering Northeast Forestry UniversityHarbin 150040China The 49th Research Institute of China Electronics Technology Group Corporation Harbin 150000China

Accurate classification of rice variety is essential to ensure the brand value of high-quality rice *** the impact of sample state on modeling optimization algorithms,rice samples after grinding and sealing were *** enhance the accuracy of rice variety classification,we introduced a spectral characteristic wavelength selection method based on adaptive sliding window permutation entropy(ASW-PE).

关键词： sealing Infrared grinding

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Multi-view people detection on arbitrary ground in real-time

Multi-view people detection on arbitrary ground in real-time

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8th International Conference on computer Vision Theory and Applications, VISAPP 2013

作者： Kiss, Ákos Szirányi, Tamás Distributed Events Analysis Research Group Computer and Automation Research Institute Hungarian Academy of Sciences Budapest Hungary Dept. of Control Engineering and Information Technology Budapest University of Technology and Economics Budapest Hungary

ISBN: (纸本)9789898565471

We show a method to detect accurate 3D position of people from multiple views, regardless of the geometry of the ground. In our new method we search for intersections of 3D primitives (cones) to find positions of feet. The cones are computed by back-projecting ellipses covering feet in input images. Instead of computing complex intersection body, we use approximation to speed up intersection computing. We found that feet positions are determined accurately, and the height map of the ground can be reconstructed with small error. We compared our method to other multiview-detectors - using somewhat different test methodology -, and achieved comparable results, with the benefit of handling arbitrary ground. We also present accurately reconstructed height map of non-planar ground. Our algorithm is fast and most of steps are parallelizable, making it possibly available for smart camera systems.

关键词： computer vision

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Cost-optimal model predictive scheduling of home appliances

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IFAC-PapersOnLine 2017年第1期50卷 3344-3349页

作者： Bálint R. Magyar A. Hangos K.M. Department of Electrical Engineering and Information Systems Faculty of Information Technology University of Pannonia Veszprém Hungary Process Control Research Group HAS Research Institute for Computer Science and Control Budapest Hungary

A novel heuristic model-based optimal scheduling algorithm is proposed in this paper to operate heating and cooling type home appliances connected to smart grids where the price of the electrical energy is known in advance and temperature constraints are present. The properties and the use of the proposed algorithm are shown using a simple refrigerator model. The accuracy and the computational properties of the proposed method are compared to the schedule generated by the MPT toolbox. The algorithm works well with a relatively short prediction horizon using a fraction of the computing time needed for the MPT-based method. The robustness of the algorithm is also investigated with respect to the load of the refrigerator. It is shown that the designed schedule with an empty refrigerator is always suitable, yet not optimal, for any loaded case. © 2017

关键词： Demand side management Heuristics Model predictive control Scheduling algorithms Smart grids

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