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Fault detection in Solar Power System with Internet of Things using Multi resolution Sinusoidal Neural Network - Snow Geese Optimization Approach 4

Fault Detection in Solar Power System with Internet of Thing...

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4th International Conference on Sustainable Expert Systems, ICSES 2024

作者： Kumar, Pramod Purushothaman, K.E. Arunmozhi, r.V. Jayachitra, S. rani, d. Leela Kaliappan, S. Ganga Institute of Technology and Management Department of Computer Science and Engineering Haryana Kablana124001 India Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology Department of Electronics and Communication Engineering Avadi Tamil Nadu Chennai600062 India Karpagam Academy of Higher Education Department of Electrical and Electronic Engineering Tamil Nadu Coimbatore641021 India S.A. Engineering College Department of Chemistry Tamil Nadu Chennai600077 India Department of Electronics and Communication Engineering Andhra Pradesh Tirupati517102 India Lovely Professional University Division of Research and Development Delhi Punjab Jalandhar144411 India

ISBN: (纸本)9798331540364

Fault detection in power systems, including Photovoltaic (PV) systems, using Internet of Things (IoT) involves deploying sensors to monitor key parameters and analyzing the data identify anomalies. The accuracy of these systems can be compromised by issues such as noisy or low-quality sensor data, which may lead to false positives or missed faults. Additionally, the complexity of managing large volumes of data from numerous IoT devices can strain the system, further affecting detection accuracy. To overcome these drawbacks, this paper proposes an efficient approach for fault uncovering in solar power system grounded on IoT. The data are collected from solar power generation dataset. Subsequently, the data are nourished to preprocessing. In preprocessing segment removes the absent values in the data utilizing reverse Lognormal Kalman Filter (rLKF). The consequence after the preprocessing data is transported to the Multiresolution Sinusoidal Neural Network (MSNN). The line-line faults, ground faults, line-ground faults and partial shading are successfully predicted and classified by using MSNN. The Snow Geese Optimization (SGO) is rummage-sale to optimize the weight structure of MSNN. The projected MSNN-SGO is utilized within the MATLAB platform. Performance metrics counting precision, accuracy, root Mean Squared Error (rMSE), F1-score, and Mean Squared Error (MSE) were examined in order to determine the proposed method. The proposed dAGCN-COA technique yields 14.89%, 16.89%, and 18.23% higher precision, 16.65%, 18.85%, and 17.89% higher accuracy, 22.36%, 15.42% and 28.27% lower rMSE when analysed the existing methods. The proposed MSNN-SGO technique is associated with the existing methods for instance spatial-temporal recurrent graph neural network (STrGNN), convolutional neural network (CNN), and long short-term memory network (LSTMN), respectively. © 2024 IEEE.

关键词： Mean square error

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Electricity generation from co-pyrolysis gas of fresh palm fruit bunches and medical waste plastic bottles for sustainable energy applications

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Case Studies in Chemical and Environmental Engineering 2025年 12卷

作者： Wiriyasart, Songkran Unsomsri, Nathawat Asadamongkon, Pichai Tawkaew, Sittinun Jansri, Surachai Narrat Kaewluan, Sommas Thermal Solution and Energy Technology Research and Development Laboratory (TSET R&D) Department of Mechanical Engineering Faculty of Engineering Srinakharinwirot University 63 Rangsit-Nakhonnayok Rd. Nakhon-nayok Ongkharak 26120 Thailand Biofuel and Bioenergy Technology Research and Development Laboratory (BBT R&D) Department of Mechanical Engineering Faculty of Engineering Srinakharinwirot University 63 Rangsit- Nakhonnayok Rd. Nakhon-nayok Ongkharak 26120 Thailand Department of Chemical Engineering Faculty of Engineering Srinakharinwirot University Rangsit-Nakhonnayok Rd. Nakhon-nayok Ongkharak 26120 Thailand Asian Development College for Community Economy and Technology (adiCET) Chiang Mai Rajabhat University Khilek Mae Rim Chiang Mai 50180 Thailand

Co-pyrolysis gas produced from the co-pyrolysis of fresh palm fruit bunches and medical waste plastic bottles using a batch pyrolyzer integrated with a downdraft gasifier was evaluated for sustainable electricity generation. Increasing the plastic fraction enhanced the gas heating value (41.43–55.53 MJ/Nm³) but decreased gas yield from 22.7 % to 9.0 %. Electrical efficiency was calculated based on the ratio of output power to syngas energy content, achieving 8.96–9.01 %. Engine tests showed a reduction in CO emissions (30,149–17,419 ppm) and comparable NO_x levels to gasoline combustion. These results demonstrate the co-pyrolysis gas's potential as a renewable fuel for decentralized power. © 2025 The Authors

关键词： Co-pyrolysis gas Electricity generation Fresh palm fruit bunches Heating value Medical waste plastic

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research on Business Center Monitoring System Based on Business Emergency System of Power Grid Company

Research on Business Center Monitoring System Based on Busin...

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System reliability and Safety Engineering (SrSE), International Conference on

作者： Kai Kang Yi Yi Liu Li Shou Zhang Qing Bi Li Kui He Yuan Yuan Zhang Information Construction and Operation Center State Grid Shanghai Electric Power Company Information and Communication Company Shanghai China R&D Center Shanghai Xinneng Information Technology Development Company Shanghai China Business Analysis Department Shanghai Zimu Information Technology Company Shanghai China

The purpose of this paper is to introduce the research related to the business center monitoring system based on the emergency response system of the business center of the power grid company. The business monitoring of the business center determines to a certain extent the basis of the stable and continuous operation of the business center. Through the research on the business indicator monitoring system of the business platform emergency system, it can provide sufficient support for the business development of the power grid company. It can also provide assistance for the operation of various businesses and play a certain role in guiding. In this paper, through the overall architecture design and key technology research on the corresponding business indicator monitoring system of the business center, a complete set of business indicator monitoring system specifications based on the emergency system of the business center of the grid company is obtained. It will provide the basis and guidance for the actual construction of the subsequent system, reduce the system construction cycle and the uncertainty of the construction, as well as help the business center flexibly and quickly adapt to the changes of the business development. Meanwhile, it will also help the business center adapt flexibly and quickly to business development changes.

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room-Temperature Highly-Tunable Coercivity and Highly-Efficient Nonvolatile Multi-States Magnetization Switching by Small Current in Single 2d Ferromagnet Fe$_3$GaTe$_2$

arXiv

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arXiv 2023年

作者： Zhang, Gaojie Wu, Hao Yang, Li Jin, Wen Xiao, Bichen Zhang, Wenfeng Chang, Haixin State Key Laboratory of Material Processing and Die & Mold Technology School of Materials Science and Engineering Huazhong University of Science and Technology Wuhan430074 China Wuhan National High Magnetic Field Center Institute for Quantum Science and Engineering Huazhong University of Science and Technology Wuhan430074 China Shenzhen R&D Center of Huazhong University of Science and Technology Shenzhen518000 China

room-temperature electrically-tuned coercivity and nonvolatile multi-states magnetization switching is crucial for next-generation low-power 2d spintronics. However, most methods have limited ability to adjust the coercivity of ferromagnetic systems, and room-temperature electrically-driven magnetization switching shows high critical current density and high power dissipation. Here, highly-tunable coercivity and highly-efficient nonvolatile multi-states magnetization switching are achieved at room temperature in single-material based devices by 2d van der Waals itinerant ferromagnet Fe3GaTe2. The coercivity can be readily tuned up to ~98.06% at 300 K by a tiny in-plane electric field that is 2-5 orders of magnitude smaller than that of other ferromagnetic systems. Moreover, the critical current density and power dissipation for room-temperature magnetization switching in 2d Fe3GaTe2 are down to ~1.7×105 A·cm-2 and ~4×1012 W·m-3, respectively. Such switching power dissipation is 2-6 orders of magnitude lower than that of other 2d ferromagnetic systems. Meanwhile, multi-states magnetization switching are presented by continuously controlling the current, which can dramatically enhance the information storage capacity and develop new computing methodology. This work opens the avenue for room-temperature electrical control of ferromagnetism and potential applications for vdW-integrated 2d spintronics. © 2023, CC BY-NC-Nd.

关键词： room temperature

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Basic Study of Communication System in Seawater Using Magnetic Field Coupler and Wavelet OFdM

Basic Study of Communication System in Seawater Using Magnet...

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Asia-Pacific Conference on Microwave

作者： ryosuke Hasaba Kazuhiro Eguchi Toshiyuki Wakisaka Hiroshi Sato Jiro Hirokawa Miyuki Hirose Tohlu Matsushima Yuki Fukumoto Department of Electrical and Electronic Engineering Tokyo Institute of Technology Tokyo Japan R&D Division Panasonic Connect Co. Ltd. Tokyo Japan Department of Electrical and Electronic Engineering Kyushu Institute of Technology Tokyo Japan Development Center Panasonic System Networks R&D Lab. Co. Tokyo Japan

ISBN: (数字)9784902339567

ISBN: (纸本)9781665451086

Since seawater has high attenuation of electromagnetic waves, the transmitting and receiving antennas are magnetically coupled using a coil with a diameter of 80 cm. The antenna is submerged in saltwater, and insertion loss is measured using a VNA. The communication speeds experiment of the UdP and TCP protocols is conducted when the distance between the transmitter and receiver antenna is changed.

关键词： Antenna measurements Microwave measurement Magnetic field measurement Protocols OFdM Transmitting antennas receiving antennas

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Seed-mediated growth of flexible Ag NFs with high activity and their application for SErS detection of thiram in tomato juice

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Colloids and Surfaces A: Physicochemical and Engineering Aspects 2025年 721卷

作者： Sun, Li Ye, Zheng Zhi, Yuan Zhang, Hua dou, Binlin Shan, Yuejin Chen, Jian School of Energy and Power Engineering University of Shanghai for Science and Technology Jun Gong Road 516 Shanghai200093 China R&D Department Shanghai Minrula Biotechnology Co. Ltd Building 15 Haji Sixth Road 218 Shanghai201306 China Department of Material and Environmental Chemistry Research Division of Functional Materials Design Utsunomiya University Yoto 7-1-2 Utsunomiya321-8585 Japan

In this study, a prospective strategy on seed-mediated growth in vacuum is provided and used to prepare flexible silver nanofilms (AC0–3 NFs) with high purity, crystallinity and SErS performance. Noteworthy, AC2 NFs surface is uniformly covered with silver nanoparticles (Ag NPs), following the appearance of numerous nano-gaps between Ag NPs. Through the finite-difference time-domain (FdTd) simulation, it is found that the ultra-small nano-gaps less than 5 nm can generate abundant "hot spots" to amplify the raman signal. Therefore, the above AC2 NFs as SErS substrates exhibit superior activity for the SErS detection of thiram in tomato juice, with the limit of detection (LOd) of 10−15 M and the enhancement factor (EF) of 3.7 × 1011. Meanwhile, AC2 NFs show outstanding reproducibility and stability during the SErS detection. Additionally, the calibration curve is established, by which the thiram (10−7 to 10−15 M) can be quantitatively detected. Clearly, the as-prepared flexible AC2 NFs have great potential in the SErS detection and analysis. © 2025 Elsevier B.V.

关键词： Fruit juices

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The impact of the heat leakage through air gap on thermoelectric generator applied in engine waste heat recovery

Green Energy and Resources

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Green Energy and resources 2024年第3期2卷

作者： Zhang, Ning Wang, Jiawei Li, Yuhuai Lan, Jianglin Lan, Song Powertrain Technology R&D Center Guangzhou Automobile Group Research and Development Center 510000 China School of Automotive and Transportation Engineering Hefei University of Technology 230009 China James Watt School of Engineering University of Glasgow Glasgow G12 8QQ United Kingdom

Efforts to enhance the performance of thermoelectric generators (TEGs) in engine waste heat recovery have primarily focused on directly increasing energy conversion efficiency. Heat leakage can occur in many parts of a TEG. It is needed to develop a model to help researchers study this phenomenon and propose measures to reduce heat leakage. To address this gap, this study establishes and validates a computational fluid dynamic (CFd) and finite element (FE) coupled model based on a TEG prototype and its engine test bench. Unlike other models, this approach captures the intricate dynamics of heat propagation from the TEG via air gaps, encompassing conduction, convection, and radiation. Comprehensive analysis reveals that heat leakage accounts for approximately 11% of TEG power output loss. Ignoring the impact of heat leakage can lead to an overestimation of TEG power output. Key areas of heat leakage are identified, and numerical factors influencing this phenomenon are explored. Vertical TEG placement and optimal spacing between thermoelectric modules emerge as effective strategies for mitigating the impact of heat leakage on power output. Leveraging these insights, strategic thermoelectric module placement, vertical TEG orientation, and the application of thermal insulation materials to the heat exchanger are proposed as measures to enhance TEG power output by approximately 5%. The experimental and numerical results underscore the feasibility of optimizing TEGs from the perspective of heat leakage, a crucial aspect previously overlooked. These findings provide valuable insights for future TEG optimization endeavors, highlighting the importance of addressing heat leakage to maximize TEG performance. © 2024 The Authors

关键词： Engine waste heat recovery Heat leakage Optimization Thermoelectric generator

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Image-Based Condition Monitoring of Air-Spinning Machines with deep Neural Networks

Image-Based Condition Monitoring of Air-Spinning Machines wi...

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IEEE Sensors Applications Symposium, SAS

作者： Kai Jansen Irida Shallari Safer Mourad Patrick Werheit Sebastian Bader Department of Computer and Electrical Engineering Mid Sweden University Sundsvall Sweden Saurer Machine Data Analytics Saurer Spinning Solutions GmbH & Co. KG Übach-Palenberg Germany Saurer Business Development Office & R&D Sensor BU SPIN Saurer Intelligent Technology AG Arbon Switzerland

ISBN: (数字)9798350369250

ISBN: (纸本)9798350369267

Industrial condition monitoring has benefited significantly from developments in machine learning and deep learning. However, textile machines, to a large extent, still use simple sensor systems, requiring additional manual quality inspections. This paper focuses on applying deep neural networks (dNNs) in image-based condition monitoring of air-spinning machines. It specifically focuses on the spinning pressure parameter, which is strongly related to the quality of the produced yarn. The study aims to develop a method to detect structural defects in yarns and assign them to specific machine conditions. dNNs are used to analyze images of yarns generated at different spinning pressures within the spinning box to create a rich dataset for training deep learning models. The study then evaluates the effectiveness of the dNN-based approach in detecting and classifying structural defects in yarns and determining the corresponding machine conditions. The results demonstrate that the developed model can distinguish good yarn from bad yarn, which is used to analyze the proportion of good yarn segments in a longer yarn section. A decreasing proportion with decreasing spinning pressure can thus be used to identify trends in degrading machine conditions. The outcomes of the presented research could potentially help textile enterprises improve the quality and efficiency of their yarn manufacturing processes.

关键词： Condition monitoring deep learning Training Analytical models Artificial neural networks Sensor systems Spinning

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Ag Ink-Jet Printed CPW with Micro-Surface Cavities: Effects of Cavity removal on rF Characteristics

Ag Ink-Jet Printed CPW with Micro-Surface Cavities: Effects ...

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SBMO/IEEE MTT-S International Conference on Microwave and Optoelectronics (IMOC)

作者： Sung-Min Sim Jun-Ho Yu Jung-Mu Kim Sang-Ho Lee RF&MS development DBHitek Eumseong-gun Republic of Korea Digital transformation R&D department Korea Institute of Industrial Technology Ansan-si Republic of Korea Department of Electronic Engineering Jeonbuk National University Jeonju-si Republic of Korea

This paper presents a study on the rF characteristics of CPW transmission lines with micro-surface cavities generated by Ag ink-jet printing. The cavities were formed by printing Ag ink on a substrate and then drying the ink. The size and number of cavities changed depending on the drying temperature. The rF characteristics of the transmission lines were measured using a vector network analyzer. The insertion loss at 3 GHz was measured to be 0.046 dB/mm at 30°C, 0.043 dB/mm at 65°C, and 0.039 dB/mm at 100°C. The results show that the presence of the cavities degrades the rF characteristics of the transmission lines, particularly at high frequencies.

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High-voltage converter with 2 kV SiC MOSFETs for electric fast charging stations

High-voltage converter with 2 kV SiC MOSFETs for electric fa...

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European Conference on Power Electronics and Applications

作者： david derix Christian Blaum Wolfram Kruschel daniel Heer Andreas Hensel Jonas Pfeiffer Ainhoa Puyadena Mier Juan Mena Carrillo Jürgen Thoma Christoph drexler Michael Schmidhuber Peter Friedrichs Power Electronics and Grid Integration Fraunhofer Institute for Solar Energy Systems Freiburg Germany Advance R&D SUMIDA Components & Modules GmbH Germany Power Module Development Infineon Technologies AG Warstein Germany Technical Marketing Infineon Technologies AG Warstein Germany Business Excellence Infineon Technologies AG Munich Germany Technology Development Infineon Technologies AG Erlangen Germany

ISBN: (数字)9798350364446

ISBN: (纸本)9798350364453

In this project, the power electronic system technology for future high-performance charging systems along highways or large inner-city electric charging stations with several MVA system sizes with reduced material demand is presented. The concept is based on a dC bus with 1.5 kV and corresponding high efficient power electronics to connect the vehicles to the dC grid. This approach leads to a cost-efficient system. Key components are an electrically isolated dC converter based on 2 kV SiC power modules and an inductive transformer with switching frequencies up to 50 kHz and an output power of 175 kW.

关键词： road transportation MOSFET Silicon carbide Switching frequency Europe Multichip modules High-voltage techniques Transformers Power electronics Power generation

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