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IEEE/IAS International Conference on Industry Applications (INDUSCON)

作者： Teylor M. Guaitolini Ernani B. Nascimento Rafaela P. Breder Renan E. Gobbi Danilo P. e Silva Flavio B. B. Silva Renner S. Camargo Espaço Energia Laboratory Federal Institute of Espirito Santo Serra Brazil Graduate Department of Applied Computing Federal Institute of Espirito Santo Serra Brazil Electrical Engineering Department Federal Institute of Espirito Santo Vitoria Brazil Automation Engineering Dept. Federal Institute of Espirito Santo Serra Brazil

This study presents a comprehensive case study centered around the modeling of a load curve for a public education institution in Brazil that harnesses energy from distributed sources, specifically photovoltaic panels. Actual demand data, sourced from an energy analyzer, and weather data collected through an automated weather station, were integrated into the photovoltaic generation model. The model's efficacy was meticulously assessed, juxtaposing the actual and simulated photovoltaic generation data, which showcased a remarkable alignment with a percentage error of merely 6.88%. Furthermore, the study delved into weekly load curve simulations spanning the spring and summer seasons. These simulations yielded a compelling percentage error of 8.01%. These outcomes underscore the potential of the proposed load curve model, not only in strategic solar energy production planning but also in the strategic optimization of energy costs. This work not only underscores the feasibility of accurate load curve prediction but also illuminates the capacity to explore solar energy production potential, thereby opening avenues for future research in revenue generation and energy credit evaluation.

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Communication Encryption Scheme of 5G Power Trading Private Network Based on Dynamic Key

Communication Encryption Scheme of 5G Power Trading Private ...

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Electrical, Power and Computer engineering (EPCE), Asia Conference on

作者： Rui Zhou Yiyang Song Ying Xu Electrical Engineering and Automation School Harbin Institute of Technology Harbin China Information Data Department Guangdong Power Exchange Center Guangzhou China Key Laboratory of Trustworthy Distributed Computing and Service Beijing University of Posts and Telecommunications Beijing China

Security has been the primary concern for the 5G power trading private network, which involves a large amount of power trading information. The communication must be encrypted to prevent the leakage of important information. The communication encryption scheme for 5G power trading private network should meet the characteristics of small communication overhead, low storage space requirement and strong resistance to attack. Based on these characteristics, the dynamic key-based encryption scheme is designed. To ensure the security and reduce the computation overhead, the optimized symmetric encryption algorithm is used to update the shared key. And the dynamic key generation method is improved by adding random numbers to solve the problem that the correct transmission of the data link does not have true randomness. The encryption mode used can generate dynamic keys directly and synchronously at both ends of the communication, reducing the overhead of key exchange and eliminating the need for trusted third parties. The algorithm is also analyzed for security and efficiency and compared with other algorithms. The experimental results show that the improved algorithm enhances security with guaranteed efficiency.

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Data-Filtered Prediction with Decomposition and Amplitude-Aware Permutation Entropy for Workload and Resource Utilization in Cloud Data Centers

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IEEE Internet of Things Journal 2025年

作者： Yuan, Haitao Hu, Qinglong Wang, Meijia Wang, Shen Bi, Jing Buyya, Rajkumar Shi, Shuyuan Yang, Jinhong Zhang, Jia Zhou, MengChu Beihang University School of Automation Science and Electrical Engineering Beijing100191 China City University of Hong Kong Department of Computer Science Hong Kong999077 Hong Kong Beijing University of Technology School of Software Engineering The Faculty of Information Technology Beijing100124 China Lab School of Computing and Information Systems MelbourneVIC3010 Australia Beihang University School of Integrated Circuit Science and Engineering Beijing China CSSC Systems Engineering Research Institute Beijing China Southern Methodist University Department of Computer Science The Lyle School of Engineering DallasTX75205 United States New Jersey Institute of Technology Department of Electrical and Computer Engineering NewarkNJ07102 United States

In recent years, cloud computing has witnessed widespread applications across numerous organizations. Predicting workload and computing resource data can facilitate proactive service operation management, leading to substantial improvements in quality of service and cost efficiency. However, these data often exhibit non-linearity, high volatility, and interdependencies across different categories, presenting challenges for accurate forecasting. Consequently, there is a critical need to develop a method that thoroughly and comprehensively analyzes all available data to forecast future trends effectively. This work proposes a novel integrated data-enhanced prediction model named SVAPI for achieving high-accuracy workload prediction in cloud computing systems. SVAPI employs the Savitzky-Golay filter, Variational mode decomposition, and the mode selection based on Amplitude-aware Permutation entropy for feature processing, whose features are subsequently utilized by Informer for multivariate joint analysis of the enhanced data, achieving high-precision prediction. Ablation and comparative experiments with advanced prediction models are conducted on the Google cluster trace and other typical datasets. Realistic data-driven results indicate that SVAPI improves the prediction accuracy by 37.7% compared to the original Informer, with each module contributing to the performance enhancement. Furthermore, compared with Autoformer, SVAPI enhances the prediction accuracy of workload, CPU, and memory by 65.6%, 66.9%, and 70.8%, respectively, demonstrating that SVAPI owns strong abilities in noise filtering, feature processing, and multivariate joint analysis for achieving higher prediction accuracy. © 2014 IEEE.

关键词： Quality of service

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Surface Extraction and Boundary Detection Based on DBSCAN Clustering in 3D Point Clouds

Surface Extraction and Boundary Detection Based on DBSCAN Cl...

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International Conference on Electronic Measurement and Instruments, ICEMI

作者： Hui Chen Tingting Xie Muhammad Llyas Menhas Bilal Ahmad Heping Huang Qilin Li College of Automation Engineering Shanghai University of Electric Power Shanghai China Department of Electrical Engineering Mirpur University of Science and Technology Mirpur Pakistan College of Electrical Engineering University of Poonch Rawalakot Mirpur Pakistan Zhengtai Instrument Co. Ltd Hangzhou China School of Electrical Engineering Computing and Mathematical Sciences Curtin University Perth Australia

Surface extraction from point clouds has many applications in product design, reverse engineering, industrial manufacturing and more. One of the key challenges is the detection and segmentation of overlapping areas of different surfaces. Existing methods are mainly on local judgment of similarity features, which can lead to either over- or under-segmentation. The proposed method in this paper utilizes DBSCAN for 3D point clouds surface extraction and boundary detection. Prior to extraction, the normal vector at sharp features is estimated based on a voting method. The surface extraction process is comprises two stages. First, the local quadric surface is determined based on the candidate sample points, and the points belonging to the same local surface are clustered. Second, in the merging stage, where the local surfaces are combined into a single smooth surface using three merging conditions. To demonstrate its effectiveness, the proposed approach is accessed on synthetic and real datasets, showing that the method can address the problem of insufficient and excessive segmentation of curved point clouds, and achieve high extraction accuracy.

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Terms Development of Additive Manufacturing 2

Terms Development of Additive Manufacturing

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2nd IEEE International Conference on Digital Twins and Parallel Intelligence, DTPI 2022

作者： Tamir, Tariku Sinshaw Xiong, Gang Jiang, Jingchao Shen, Zhen Lodhi, Ehtisham Ali, Hub Wan, Li Beijing Engineering Research Center of Intelligent Systems and Technology Institute of Automation Chinese Academy of Sciences Beijing100190 China School of Artificial Intelligence University of Chinese Academy of Sciences Beijing100049 China The Chinese University of Hong Kong Department of Mechanical and Automation Engineering Shatin Hong Kong Guangdong Engineering Research Center of 3D Printing and Intelligent Manufacturing Cloud Computing Center Chinese Academy of Sciences Dongguan523808 China Intelligent Manufacturing Center Qingdao Academy of Intelligent Industries Qingdao266000 China Technology Co. Ltd Foshan528225 China

ISBN: (纸本)9781665492270

Nowadays, additive manufacturing has been increasingly developed and applied in many fields. As a rapid development of additive manufacturing, similar terms are appeared, such as 3D printing, freeform fabrication, rapid tooling, rapid manufacturing, direct digital manufacturing, layer manufacturing, additive process, 4D printing, 3D bioprinting, and 3D biofabrication. This paper reports and analyze the development of these terms. Moreover, it tries to give the readers a comprehensive understanding of these terms and their development. © 2022 IEEE.

关键词： 3D printers

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Chinese automation Congress (CAC)

作者： Yumin Lang Jiande Wu Xun Lang Wanke Yu Chuanyan Yang Hongye Su Department of Electronic Engineering Information School Yunnan University Kunming China Yunnan Key Laboratory of Intelligent Systems and Computing Yunnan University Kunming China School of Automation China University of Geosciences Wuhan China State Key Laboratory of Industrial Control Technology Zhejiang University Hangzhou China

ISBN: (数字)9798350368604

ISBN: (纸本)9798350368611

Oscillation is a significant indication of the deterioration of control system performance and needs to be carefully monitored to ensure safe and stable process operations. However, industrial processes are often prone to noisy artifacts and nonstationary trends, resulting in low signal-to-noise ratios. In order to tackle this problem, this study introduces a novel framework for enhanced trend removal and noise reduction, which is featured by the following steps:(i) The circulant singular spectrum analysis (CiSSA) is used to decompose oscillation data into several reconstructed components (RCs). (ii) The estimated power spectral density (PSD) of these RCs is then smoothed using the Savitzky-Golay filter (SGF) to eliminate noise and identify the RCs corresponding to oscillatory components. (iii) These identified RCs are subsequently reconstructed to produce purified oscillatory data. The effectiveness of the suggested approach is validated using simulations and real-world industrial case studies. The findings indicate that the method notably enhances the quality of oscillatory data.

关键词： Power filters Noise reduction Process control Market research Information filters Noise measurement Oscillators Spectral analysis Monitoring Signal to noise ratio

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Influence of Rotor Slot Number on Magnetic Noise in a Squirrel-cage Induction Motor for Traction Applications 35

Influence of Rotor Slot Number on Magnetic Noise in a Squirr...

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35th International Conference on Power Electronics and Electrical Drives, EDPE 2021

作者： Milažar, Ivan Žarko, Damir KONČAR - Generators and Motors Inc. Zagreb Croatia University of Zagreb Faculty of Electrical Engineering and Computing Department of Electrical Machines Drives and Automation Zagreb Croatia

In this paper, the influence of rotor slot number on the magnetic noise of a squirrel cage motor for traction applications is analyzed. The introductory part explains the importance of noise analysis and measurement and gives an overview of the types of noise that occur in this type of motor. The dominance of a particular type of noise depending on the design of the induction motor (number of poles, type of cooling) and the operating range of the motor is also commented. The cause and occurrence of magnetic noise are explained by analytical expressions. Methods are listed that can be used to effectively influence the magnetic noise level at the design stage. The difference between sound pressure level and sound power level is explained as noise level is expressed in both forms. The dominant stress components due to the radial forces acting on the stator teeth and the resulting sound power maxima are calculated for three combinations of stator and rotor slot numbers using the software package MANATEE. ©2021 IEEE.

关键词： Induction motor Magnetic noise Simulation Slot number

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Quantification of Valve Stiction in Control Loops Using Adaptive Differential Evolution Algorithm

Quantification of Valve Stiction in Control Loops Using Adap...

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Chinese automation Congress (CAC)

作者： Dong Yang Xun Lang Jiande Wu Wanke Yu Songhua Liu Lei Xie Department of Electronic Engineering Information School Yunnan University Kunming China Yunnan Key Laboratory of Intelligent Systems and Computing Yunnan University Kunming China School of Automation China University of Geosciences Wuhan China State Key Laboratory of Industrial Control Technology Zhejiang University Hangzhou China

ISBN: (数字)9798350368604

ISBN: (纸本)9798350368611

Accurately and promptly quantifying stiction is crucial for valve maintenance in industrial settings and ensuring the stability of control loop performance. However, current Hammerstein-based stiction quantification methods overlook valve dynamics, potentially leading to inaccurate quantification. Therefore, this paper proposes a novel stiction quantification method based on an adaptive differential evolution algorithm. In addition to considering the impact of valve dynamics on stiction, the proposed method demonstrates a certain level of robustness against the interference of unknown noise. Finally, the effectiveness of the proposed method is demonstrated through a series of simulations and industrial case studies.

关键词： Adaptation models Heuristic algorithms Noise Interference Valves Stability analysis Robustness Data models Maintenance Classification algorithms

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An Energy Sharing Mechanism Considering Network Constraints and Market Power Limitation

arXiv

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arXiv 2022年

作者： Chen, Yue Zhao, Changhong Low, Steven H. Wierman, Adam The Department of Mechanical and Automation Engineering The Chinese University of Hong Kong Hong Kong The Department of Information Engineering The Chinese University of Hong Kong Hong Kong The Computing + Mathematical Sciences Department California Institute of Technology PasadenaCA91125 United States

As the number of prosumers with distributed energy resources (DERs) grows, the conventional centralized operation scheme may suffer from conflicting interests, privacy concerns, and incentive inadequacy. In this paper, we propose an energy sharing mechanism to address the above challenges. It takes into account network constraints and fairness among prosumers. In the proposed energy sharing market, all prosumers play a generalized Nash game. The market equilibrium is proved to have nice features in a large market or when it is a variational equilibrium. To deal with the possible market failure, inefficiency, or instability in general cases, we introduce a price regulation policy to avoid market power exploitation. The improved energy sharing mechanism with price regulation can guarantee existence and uniqueness of a socially near-optimal market equilibrium. Some advantageous properties are proved, such as prosumer’s individual rationality, a sharing price structure similar to the locational marginal price, and the tendency towards social optimum with an increasing number of prosumers. For implementation, a practical bidding algorithm is developed with convergence condition. Experimental results validate the theoretical outcomes and show the practicability of our model and method. © 2022, CC BY-NC-ND.

关键词： Energy resources

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Research on experimental method of high-speed railway perimeter intrusion monitoring technology based on multi-sensor fusion 24

Research on experimental method of high-speed railway perime...

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Proceedings of the 2024 4th International Conference on Big Data, Artificial Intelligence and Risk Management

作者： Xue Yang Bo Zhang Tao Yu Ye Liang Wanpeng Zhang Wentao Li Institute of Computing Technologies China Academy of Railway Sciences Corporation Limited Beijing China School of Automation and Software Engineering Shanxi University Taiyuan Shanxi China China Railway Nanchang Group Co. Ltd. Nanchang Jiangxi China Graduate Department China Academy of Railway Sciences Beijing China

ISBN: (纸本)9798400709753

In recent years, China's high-speed railway has achieved rapid development, and has become the largest and fastest high-speed railway country in the world. By the end of 2023, the operating mileage has reached 159,000 km, including 45,000 km of high-speed railway. With the continuous expansion of high-speed railway development scale, the country also attaches more and more importance to railway operation safety. The report of the 20th National Congress of the Communist Party of China pointed out that we should accelerate the construction of a modern infrastructure system, transportation equipment system, transportation service system, and transportation governance system, promote the safe, intelligent, green and open development of transportation, and find a new road of transportation modernization with Chinese characteristics. Many scholars have successively proposed high-speed railway perimeter monitoring technology schemes based on various sensor devices. However, due to the diversity of monitoring equipment, uneven data interfaces and unified data standards, centralized testing of high-speed railway perimeter intrusion monitoring technology based on different types and models of sensing equipment has been unable to be carried out, and synchronous testing cannot be conducted in a unified test environment. In order to solve the above problems, this paper carried out research on device interface, data standardization, sample library construction methods and test methods, and compared various high-speed railway perimeter intrusion monitoring technology schemes based on multi-sensor fusion to verify the functional performance and environmental adaptability of various monitoring devices in actual operation scenarios.

关键词： Data standard

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