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SICE International Symposium on Control Systems (ISCS)

作者： Toshihiro Wada Shoichi Kobayashi Shusaku Takamoto Ayumi Nishikawa Yuki Sumiyoshi Wataru Tsujita Addvanced Technology R&D Center Mitsubishi Electroc Corporation Hyogo Japan Automotive Electronics Development Center Mitsubishi Electroc Corporation Hyogo Japan Sanda works Mitsubishi Electroc Corporation Hyogo Japan

In this paper, we propose a method for estimating vehicle pitch angle from a triaxial accelerometer, a wheel speed sensor and an altimeter. In our method, a static pitch angle, that is the stationary point of suspension under the condition of neither acceleration nor gradient, is estimated by an adaptive filter, then the pitch angle is feedforwardly estimated using the model of suspension. We verify our algorithm by a simulation, and we also illustrate the performance of our algorithm by an experimental result of an actual driving test.

关键词： Accelerometers Suspensions (mechanical systems) Adaptation models Wheels Estimation Adaptive filters Control systems

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research on defect Identification Algorithm of Power Network Telesignaling and Telemetry data Based on dynamic programming

Research on Defect Identification Algorithm of Power Network...

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Energy, Power and Electrical Engineering (EPEE), International Conference on

作者： di Huang Chaoyue Zhu Junliang Qiu Xixing Hu Weiyan Zheng Shaojie Luo R&D Department Hangzhou Science and Technology Development Branch Zhejiang Dayou Industrial Co. Ltd. Hangzhou China Marketing Department Zhejiang Dayou Co. Ltd Hangzhou China

distribution networks manage numerous devices, however, their level of automation is relatively low, often resulting in false signals and relatively low data quality. Therefore, it has become extremely challenging to directly use telecontrol and telemeasurement data for defect identification. To address this issue, this paper proposes a defect identification algorithm for power grid telecontrol and telemeasurement data based on dynamic programming. Firstly, we employ data cleansing techniques to filter out erroneous data. Then, we introduce a dynamic density clustering-based method for detecting anomalies in power quality data, which can extract feature indicators of abnormal data and identify the defects in telecontrol and telemeasurement data. Next, we utilize the GrU-LightGBM network to identify defects in the telecontrol and telemeasurement data of the power grid. Finally, we compare this method with existing classification methods for defect identification in telecontrol and telemeasurement data through experiments. The experimental results demonstrate that our proposed method not only improves classification accuracy but also enhances generalization ability.

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Enhancement of Security in IoT using Secure Hash Cryptography Algorithm with double Encryption (SHCA-dE) 9

Enhancement of Security in IoT using Secure Hash Cryptograph...

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9th International Conference on Communication and Electronics Systems, ICCES 2024

作者： Uganya, G. rajalakshmi, d. Vangapandu, ramarao dinesh, M. Giri, Jayant Odeh, Mahmoud Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology Department of Ece Chennai India Srm Institute of Science and Technology Department of Data Science and Business Systems Kattankulathur Chennai India Vignan's Institute of Engineering for Women Department of Computer Science and Engineering Vishakhapatnam India Saveetha University Department of Vlsi Microelectronics Saveetha School of Engineering Chennai India Yeshwantrao Chavan College of Engineering Department of Mechanical Engineering Nagpur India Lovely Professional University Division of Research and Development Phagwara India Zarqa University Faculty of Information Technology Department of Cyber Security Zarqa Jordan University of Business and Technology Jeddah Saudi Arabia

ISBN: (纸本)9798350377972

The 'Internet of things' is the developing technology to transfer the world into smart innovation. 'IoT' security is the most problematic issue in recent applications due to its properties including 'centralized architecture', 'limited capacity devices', and 'ambiguity'. So, blockchain with 'IoT' applications provides secure data communication compared to traditional 'IoT' applications. Blockchain is a recent growing technology that has features including 'decentralized structure', 'transparency', 'immutable records', 'increased capacity', and 'quick backtracks'. The 'cryptography hash algorithm' is very important to provide secure data transmission. It converted the different size input to fixed-size unalterable output to enhance the security. But still, it needs efficient algorithm to secure data transmission with safeguard of private key. The objective of this paper is to propose a secure hash cryptography algorithm with double encryption (SHCA-dE) to protect the private key message. Then, this proposed algorithm has been analyzed with Md5, SHA-256, and SHA3-512. From this analysis, the SHA3-512 performs well with proposed algorithm. © 2024 IEEE.

关键词： Encryption algorithms

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Investigating the Failure Mechanism of Wet eMachines in the Presence of Transmission Oils

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Journal of Tribology 2025年第5期147卷 051111页

作者： Nyman, Pär Björklund, Peter Yaghini, Negin Lu, Li Hopper, Elizabeth r. Hunt, Gregory https://***/03g4sde39Scania (Sweden) Propulsion Development Scania CV AB R&D Building 117-12 Södertälje 151 87 Sweden https://***/03g4sde39Scania (Sweden) Materials Technology Scania CV AB R&D Building 101-2 Södertälje 151 87 Sweden Materials Technology Scania CV AB R&D Building 101-2 Södertälje 151 87 Sweden https://***/01ee9ar58University of Nottingham School of Pharmacy The University of Nottingham University Park Campus Nottingham NG7 2RD UK Lubrizol Ltd. The Knowle Nether Lane Hazelwood Derbyshire DE56 4AN UK

This paper investigates the failure mechanisms in electric machines used in heavy trucks and buses exposed to transmission oil. Five machines from field operations were examined. Subsystem tests—copper corrosion testing, conductive deposit tests, material compatibility tests, and oil analysis—were conducted. Copper sulfide, known for its conductive properties, was found in failed machines and during subsystem tests with lubricants containing reactive sulfur components in contact with exposed copper. Two prerequisites for the chemical reaction—the presence of reagents and sufficient activation energy—were met at normal operating temperatures. Analysis revealed the sulfur presence in damaged machines and identified cracks in the polymer coating on copper wires, allowing corrosive substances to reach the copper surface. The proposed failure mechanism involves active sulfur reacting with copper to form copper sulfide. These layers can create contact bridges between phases in the eMachine, leading to short circuits, sharp temperature increases, electrical arcing, and total machine failure. Coating aging experiments showed that fluids can form conductive films on the polymer layer. Oil conductivity measurements showed minor changes within the static dissipative regime, and contamination by transmission and axle oil elements was found in failed eMachines but not in functional ones. Activation energy experiments demonstrated that copper sulfide forms at normal operating temperatures, with damage likely within 10–100 days depending on conditions. These findings highlight the risks associated with certain oils in eMachines and the need for further research to develop strategies to mitigate these risks and ensure long-term reliability.

关键词： lubricant additives soft materials Coating processes Coatings Copper Polymers electrical contacts polymeric additives lubricants corrosion Corrosion coatings Wire Petroleum Fluids surface properties and characterization Sulfur Oils

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The Impact of the Heat Leakage on Thermoelectric Generator Applied in Engine Waste Heat recovery

SSRN

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SSrN 2024年

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 GlasgowG12 8QQ United Kingdom

Efforts to enhance the performance of thermoelectric generators (TEGs) in engine waste heat recovery have primarily focused on increasing heat extraction and energy conversion. However, the impact of heat leakage has been consistently overlooked in both modeling and optimization endeavors. To address this gap, this study establishes and validates a computational fluid dynamic (CFd) - finite element (FE) coupled model based on a TEG prototype and its engine test bench. Unlike other models, the approach employed here captures the intricate dynamics of heat propagation from the TEG via air gaps, encompassing conduction, convection, and radiation. Through comprehensive analysis, it is revealed that heat leakage accounts for approximately 11% of TEG power output loss. Key areas of heat leakage are identified and numerical factors influencing this phenomenon are explored. Vertical TEG placement and a 15 mm spacing between thermoelectric modules emerge as optimal strategies for mitigating heat leakage's impact on power output. Leveraging these insights, strategic thermoelectric module placement, vertical TEG orientation and the application of thermal insulation materials for the heat exchanger are proposed as effective measures to enhance TEG power output by 5% approximately. 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. All rights reserved.

关键词： Waste heat utilization

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A Way of Making Smart Health Through Collaborating Machine Learning with the Bibliometrics 4

A Way of Making Smart Health Through Collaborating Machine L...

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4th IEEE International Conference on Advance Computing and Innovative Technologies in Engineering, ICACITE 2024

作者： Vignesh, T. Sruthi, P.S. Mohanraj, T. Kumar, Gaurav Varkale, Akshay Sheela, M.Sahaya Prince Shri Venkateshwara Padmavathy Engineering College Department of Computer Science and Engineering TN India Nehru Institute of Technology Department of Computer Science and Business System Tamil Nadu T.M. Palayam India Karpagam Academy of Higher Education Department of Computer Science Engineering India Chitkara University Chitkara Centre for Research and Development Himachal Pradesh India M.P Bhopal India Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology Department of Electronics and Communication Engineering Tamil Nadu Chennai India

ISBN: (纸本)9798350360165

It datasets are widely utilized, shared, and repurposed without providing enough context for understanding the decision-making processes that led to their creation. It is necessary to modify system creation and use procedures to handle the concrete effects of how knowledge for model building is envisioned and used in real-world applications as AI systems assume more and more important roles. documents are created at every phase of the data generation lifecycle to improve communication, aid in decision-making, and highlight the need of careful data work. By putting out this paradigm, we want to shed light on the choices and duties that are often disregarded while creating datasets, which is a crucial first step in bridging the duty of care gap in AI. This framework provides an essential and important resource for guaranteeing ethical AI activities, and it is in line with current developments in auditing procedures. © 2024 IEEE.

关键词： Adversarial machine learning

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Micro-Nano Polymer Microspheres as a Plugging Agent in Oil-Based drilling Fluid

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SSrN 2023年

作者： Zhao, Zhen Sun, Jinsheng Liu, Fan Cheng, rongchao Bai, Yingrui Wang, ren Wang, Jintang Geng, Yuan Jin, Yeliang Ma, Zhihu CNPC Engineering Technology R&D Company Limited Beijing102206 China Research Institute of Petroleum Exploration &Development Beijing100083 China China Department of Petroleum Engineering China University of Petroleum Beijing China

The wellbore instability of shale formations with micro fractures was mainly ascribed to drilling fluid invasion and pressure transmission during drilling using oil-based drilling fluids (OBdF). Nano-plugging agents or micro-plugging agents at present only match a narrow size range of nanopores or microcracks. Plugging agents with good suitability to multidimensional fractures used in OBdF are lacking. This paper synthesized micro-nano polymer microsphere dispersion (PMd) with a solid content of 30% through inverse emulsion polymerization. PMs had good wettability for water in the oil environment. The filtration of the emulsion with 4% PMd dropped the filtration through 0.1~3 μm filters to within 14 mL while the emulsion with 1% CaCO3 only plugged the filter with a pore size of 3 μm. Hydrophilic PMs with a wide size distribution have excellent suitability with multi-scale pores or cracks. PMs could reduce the filtration of OBdF after aging at 120 and 150℃ without significantly influencing their rheology and electrical stability. Based on darcy’s law, the HTHP mud cake permeability calculated decreased by half with the addition of PMd at 120 and 150℃. Moreover, the addition of PMd could decline the disc HTHP filtration by 100~50% when the disc diameter was 5~120 μm respectively. Compared with CaCO3, the PMd showed superior plugging performance and self-suitability when plugging 5~120 μm discs. Micro-nano PMs could interact with organic clays through hydrogen bonds to form thinner and denser mud cakes. They could also form hydrogen bonds with the formation surface. PMs could enter, aggregate and arrange tightly at multi-scale pores or cracks owing to their wide size distribution. In addition, they formed a dense plugging layer and prevent the filtration from invading the formation. The PMd with good compatibility, suitability and plugging performance has a promising application prospect in shale oil and gas exploration. © 2023, The Authors. All rights reserved.

关键词： Emulsification

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research on Off-design Performance Prediction Method of diagonal Compressor With Adjustable Guide Vane

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Kung Cheng Je Wu Li Hsueh Pao/Journal of Engineering Thermophysics 2025年第3期46卷 777-789页

作者： Zhang, Yuxin Zuo, Zhitao Guo, Wenbin Li, Jingxin Chen, Haisheng Qin, Wei Institute of Engineering Thermophysics Chinese Academy of Science Beijing100190 China University of Chinese Academy of Science Beijing100049 China National Energy Large-scale Physical Energy Storage Technology R&D Center of Bijie High-Tech Industrial Development Zone Bijie551712 China Nanjing Institute of Future Energy System Institute of Engineering Thermophysics Chinese Academy of Science Nanjing211135 China

The diagonal compressor is one of the important types of combined compressors for large-scale compressed air energy storage system (CAES). The off-design performance prediction is crucial in the research and development of the diagonal compressor. It can not only quickly evaluate the initial design parameters, but also select the overall optimal parameters according to the characteristics of the off-design operation of the compressor in CAES. The accuracy of the performance prediction model is essential. In this paper, a one dimensional performance prediction program for the diagonal compressor of the developing large-scale CAES is established by programming, and the optimal selection result of the loss model combination of the program is given through the design point parameters. Then, the off-design loss model is modified by using the flow coefficient, and the results are verified by CFd. The results show that this method can effectively predict the off-design performance of the diagonal compressor under different guide vane openings. © 2025 Science Press. All rights reserved.

关键词： Compressed air energy storage

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Intelligent distribution Grid reliability Simplification Algorithm and Online Computing Implementation

Intelligent Distribution Grid Reliability Simplification Alg...

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New Energy and Power Engineering (ICNEPE), International Conference on

作者： Hongjun Wen Bowei Chen Zuxin Li Jiqiao Chen Zhi Nie Qian Wu Power Grid Development Department State Grid Zhejiang Electric Power Co. Ltd. Lishui Company Lishui China R&D Center T&D Power Research (Beijing) Technology Co. Ltd Beijing China

At present, reliability calculation is mostly focused on the calculation of current years, and the calculation of planned years is often carried out using fuzzy estimation. The calculation methods are complex and diverse, which is not conducive to the modular implementation of software. This article deeply analyzes the essence of reliability calculation based on the topology simplification model of power flow, and summarizes the parts related to the grid structure in its classic calculation formula as the grid coefficient. The parts related to the equipment are collected as the equipment coefficient, and the calculation is simplified based on practical applications. Then, based on the power grid resource business center and data center, a centralized (microservices/micro applications) + collaborative computing framework construction model is adopted, integrating basic data such as reliability facility ledger, topology, and graph model, and obtaining important parameters such as fault rate and average recovery time of distribution grid equipment components. Based on simplified calculation formulas, a power supply reliability online calculation micro application module is developed, The calculation results can provide convenient data support for reliability management and decision-making of distribution grids. This article also provides the specific implementation of software architecture design and interface display effects.

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Estimating Ground Conditions for Efficient Operation of robotic Lawn Mowers

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Journal of Japan Institute of Electronics Packaging 2022年第3期25卷 240-249页

作者： Zushida, Kazuki Zhang, Haohao Kojima, Masaki Motegi, Kazuhiro Shiraishi, Yoichi Shimamura, Hideaki Yamada, So Department of Mechanical Science and Technology Graduate School of Science and Technology Gunma University 29-1 Honcho Gunma Ota-shi373-0057 Japan Research and Development Division Nippon Mobility Inc. Maebashi Center Building15th floor C 2-13-11 Honcho Maebashi-shi Gunma371-0023 Japan Life Creation Center Honda R&D Co. Ltd. 3-15-1 Senzui Asaka-shi Saitama351-0024 Japan

The objective of this research is to estimate the length of the grass and the condition of the ground when a robotic lawn mower runs using the random Forest and Neural Network, and to change the running control according to the ground conditions for efficient lawn mowing. The main robotic lawn mowers currently on the market cannot recognize the length of the grass or the condition of the ground other than the lawn, such as bare soil. Therefore, the robotic lawn mower always rotates its blade at the maximum speed while running randomly over the specified area. In order to mow the lawn efficiently, we propose to estimate the length of the grass and the ground condition using sensors and machine learning, and to control the mower appropriately. In this study, we experimentally show that the system achieves a correct answer rate of more than 90% in estimating the ground conditions. Copyright© The Japan Institute of Electronics Packaging.

关键词： Lawn mowers

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