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design and Optimization of an Intelligent Monitoring System for Overhead Lines Based on Common information Model

ieee ACCESS 2024年 12卷 31386-31398页

作者： Wang, Yamin Sai, Pengfei Huanghe Jiaotong Univ Basic Teaching Dept Jiaozuo 454950 Henan Peoples R China

Overhead lines act as the basic media for electricity transmission, and their stable operation remains really important to the whole power systems. As a result, real-time monitoring towards the operation status and fast discovery towards the device fault are in urgent demand. To deal with such issue, this work presents design and optimization of an intelligent monitoring system for overhead lines based on common information model (CIM). Firstly, tree format data structure is established using CIM, and analysis of CIM-XML data files are completed based on CIM. Then, the necessary relational tables without affecting database performance are established, in order to ensure that the mapped relational database can fully express all kinds of relationships in CIM. Finally, the abnormal temperature rise at the connection of overhead lines in traction power supply systems is selected as the object. And some simulation is conducted to evaluate performance of the designed prototype system. The results show that the system can accurately detect the voltage value from normal working state to the limit state of human safety voltage, with relatively small errors (about 3%-6%). Compared with inductive high-voltage detection technology, this system has higher detection capability. The intelligent monitoring of overhead lines based on the Common information Model (CIM) optimizes the combined contact force characteristic values of pantographs and dynamic schemes of overhead lines, reducing the average risk loss.

关键词： Monitoring Real-time systems Data models Databases Object oriented modeling Rail transportation Standards Intelligent systems design engineering Power transmission lines Common information Model (electricity) Intelligent monitoring database development optimal design common information model

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Agriculture Impact on Climate Change and Climate Change Impact on Agriculture - Low Power design

Agriculture Impact on Climate Change and Climate Change Impa...

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ieee International symposium on Circuits and systems (ISCAS)

作者： Grimblatt, Victor Synopsys Chile Santiago Chile

ISBN: (纸本)9798350330991;9798350331004

The world is going into a disaster if no actions are taken soon to stop the global warming and the corresponding climate change. The agribusiness sector is responsible for almost a third of the greenhouse gas emissions (GHG). On the other hand, this sector is one of the most affected by climate change. Technology, IoT, machine learning, low power design, and artificial intelligence should play an important and essential role as it provides ways to measure and analyze data that will show GHG emissions and the main sources. From collected data, through a deep analysis, information can be sent to the farmers and some actions can be taken. In this paper we will analyze how climate change is affecting agribusiness, how agribussines is affecting climate change and how technology could help to mitigate the impact of climate change. Different options for low power design are also presented.

关键词： IoT climate change smart agriculture food security GHG emissions low power design SoC

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Fuzzy-Model-Based Finite Frequency Fault Detection Filtering design for Two-Dimensional Nonlinear systems

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ieee/CAA Journal of Automatica Sinica 2024年第10期11卷 2099-2110页

作者： Meng Wang Huaicheng Yan Jianbin Qiu Wenqiang Ji Key Laboratory of Smart Manufacturing in Energy Chemical Process Ministry of EducationSchool of Information Science and EngineeringEast China University of Science and TechnologyShanghai 200237China Research Institute of Intelligent Control and Systems School of AstronauticsHarbin Institute of TechnologyHarbin 150080China School of Artificial Intelligence Hebei University of TechnologyTianjin 300401China IEEE

This article studies the fault detection filtering design problem for Roesser type two-dimensional(2-D)nonlinear systems described by uncertain 2-D Takagi-Sugeno(T-S)fuzzy ***,fuzzy Lyapunov functions are constructed and the 2-D Fourier transform is exploited,based on which a finite frequency fault detection filtering design method is proposed such that a residual signal is generated with robustness to external disturbances and sensitivity to *** has been shown that the utilization of available frequency spectrum information of faults and disturbances makes the proposed filtering design method more general and less conservative compared with a conventional nonfrequency based filtering design ***,with the proposed evaluation function and its threshold,a novel mixed finite frequency H_(∞)/H_(-)fault detection algorithm is developed,based on which the fault can be immediately detected once the evaluation function exceeds the ***,it is verified with simulation studies that the proposed method is effective and less conservative than conventional non-frequency and/or common Lyapunov function based filtering design methods.

关键词： Fault diagnosis finite frequency specifications mixed H_(∞)/H_(-)performance two-dimensional nonlinear systems

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Optimizing Hysteresis-Based Reinforcement Learning to Improve Collision Avoidance for Self-Driving Vehicles

Optimizing Hysteresis-Based Reinforcement Learning to Improv...

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2024 systems and information engineering design symposium, SIEDS 2024

作者： Wunderlich, Erwin J. Korman, E. George Washington University Department of Electrical and Computer Engineering WashingtonDC20052 United States

ISBN: (纸本)9798350385144

This paper considers an optimization for fully automated driving systems. We analyze and optimize the performance of two different types of hysteresis-based feedback mechanisms based on noisy sensor inputs. We show how hysteresis can be used in conjunction with Reinforcement Learning (RL) algorithms to make them more resilient to noise. Our results show that by using hysteresis-based RL, we reduce the likelihood of collisions by over 50% in comparison to non-hysteresis-based RL. © 2024 ieee.

关键词： Hysteresis

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Ramulator 2.0: A Modern, Modular, and Extensible DRAM Simulator

IEEE COMPUTER ARCHITECTURE LETTERS

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ieee COMPUTER ARCHITECTURE LETTERS 2024年第1期23卷 112-116页

作者： Luo, Haocong Tugrul, Yahya Can Bostanci, F. Nisa Olgun, Ataberk Yaglikci, A. Giray Mutlu, Onur Swiss Fed Inst Technol CH-8092 Zurich Switzerland

We present Ramulator 2.0, a highly modular and extensible DRAM simulator that enables rapid and agile implementation and evaluation of design changes in the memory controller and DRAM to meet the increasing research effort in improving the performance, security, and reliability of memory systems. Ramulator 2.0 abstracts and models key components in a DRAM-based memory system and their interactions into shared interfaces and independent implementations. Doing so enables easy modification and extension of the modeled functions of the memory controller and DRAM in Ramulator 2.0. The DRAM specification syntax of Ramulator 2.0 is concise and human-readable, facilitating easy modifications and extensions. Ramulator 2.0 implements a library of reusable templated lambda functions to model the functionalities of DRAM commands to simplify the implementation of new DRAM standards, including DDR5, LPDDR5, HBM3, and GDDR6. We showcase Ramulator 2.0's modularity and extensibility by implementing and evaluating a wide variety of RowHammer mitigation techniques that require different memory controller design changes. These techniques are added modularly as separate implementations without changing any code in the baseline memory controller implementation. Ramulator 2.0 is rigorously validated and maintains a fast simulation speed compared to existing cycle-accurate DRAM simulators.

关键词： Computer architecture computer simulation systems engineering and theory computers and information processing DRAM systems engineering and theory memory architecture computers and information processing memory management computers and information processing memory modeling random access memory scalability simulation system analysis and design system simulation systems engineering and theory

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High-Level Reconfigurable Embedded System design Based on Heterogeneous Models of Computation

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ieee ACCESS 2025年 13卷 63918-63934页

作者： Duarte, Gabriel C. Loubach, Denis S. Sander, Ingo Aeronaut Inst Technol ITA Dept Comp Syst Comp Sci Div BR-12228900 Sao Jose Dos Campos Brazil KTH Royal Inst Technol Sch Elect Engn & Comp Sci S-10044 Stockholm Sweden

One of the main challenges of embedded system design lies in the natural heterogeneity of these systems. We can say that embedded systems are electronic systems designed and programmed to tackle a specific application. Each application has its requirements, although embedded systems often combine many domain-specific subsystems. Considering this context, the design of embedded systems can be extremely challenging, including system modeling, simulation, formal verification, and the synthesis to a correct implementation. To manage the complexity of such systems, the design should start at higher levels of abstraction, based on formal models, without considering the low-level characteristics of the underlying software or hardware. These high-level formal meta-models, named models of computation (MoC), define a set of rules that dictate how computation should be performed and how they should communicate with each other, along with other information such as the notion of time. In this paper, we present as the main contribution a set of rules and interfaces that enable the proper mixing of different MoC domains in a framework for complex embedded system design, thus allowing a heterogeneous system composition at a high abstraction level, including the synchronous reactive, synchronous dataflow, and scenario-aware dataflow MoCs. We model both part of an avionic system and a reconfigurable RISC-V processor using these MoCs and the proposed interfaces as a case study showing the applicability brought by our proposal.

关键词： Embedded systems heterogeneous modeling heterogeneous modeling heterogeneous systems heterogeneous systems models of computation models of computation reconfigurable systems reconfigurable systems RISC-V RISC-V

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Fault-Simulation-Based Flip-Flop Classification for Reverse engineering 27

Fault-Simulation-Based Flip-Flop Classification for Reverse ...

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27th International symposium on design & Diagnostics of Electronic Circuits & systems (DDECS)

作者： Mildner, Michael Brunner, Michaela Gruber, Michael Baehr, Johanna Sigl, Georg Tech Univ Munich TUM Sch Computat Informat & Technol Secur Informat Technol Munich Germany Fraunhofer Inst Appl & Integrated Secur AISEC Garching Germany

ISBN: (纸本)9798350359343

This work outlines a crucial step in gate-level netlist reverse engineering: classifying control and data flip-flops (FFs) to discern control logic and data paths. Existing methods rely mainly on structural characteristics, which can have disavantages. Our work introduces a novel approach that classifies FFs based on observed characteristics after fault insertion and propagation. We develop three new classification methods for block cipher implementations, emphasizing their significance in system security. However, we also explore the approach's applicability to other design types. We apply the approach on AES implementations using an automatic fault simulation framework, which shows perfect results for most classifications.

关键词： Flip-Flop Classification Fault Simulation Block Cipher Hardware Reverse engineering

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Ontology Versioning for Managing Inconsistencies in engineering Models Arising From Model Changes in the design of Intralogistics systems

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ieee TRANSACTIONS ON AUTOMATION SCIENCE AND engineering 2024年 22卷 1249-1261页

作者： Ji, Fan Vogel-Heuser, Birgit Schypula, Rafael Wuennenberg, Maximilian Goedicke, Michael Fottner, Johannes Tech Univ Munich Inst Automat & Informat Syst D-85748 Garching Germany Univ Duisburg Essen Ruhr Inst Software Technol D-45127 Essen Germany Tech Univ Munich Chair Mat Handling Mat Flow Logist D-85748 Garching Germany

The interdisciplinary design of intralogistics systems (ILS) involves engineers from various disciplines, resulting in the generation of discipline-specific model files with overlapping information. For instance, a conveyor system can be represented from various perspectives, such as 3D-CAD models that capture its geometric information and discrete-event simulation models that depict the system's dynamic material flow performance. The growing demands for flexible reconfigurability and adaptability in intralogistics systems necessitate frequent updates to engineering models. However, these updates often result in potential model inconsistencies due to insufficient stakeholder communication. Detecting the impact of model changes and related inconsistencies is challenging in practice due to data heterogeneity and complex inter-model relations. To address these challenges, we propose an ontology-versioning approach that automates the identification of inconsistencies resulting from model changes. Our approach facilitates the integration of heterogeneous model data, enables database versioning, detects inconsistencies caused by model updates, and provides traceability for identified issues. The concept is evaluated utilizing models from a prototypical implementation on a lab-sized demonstrator. Note to Practitioners-In the industry, the current development of intralogistics systems often lacks automated synchronization of overlapping model information and consistent model interfaces, frequently leading to contradictions among the models. This has been identified as a significant source of errors in the design of both industrial and academic intralogistics systems, as revealed by a study involving intralogistics experts from different technical disciplines. Effectively managing model inconsistencies is crucial for project success, particularly when frequent model changes occur. A promising approach to tackle this issue is to systematically link model data from different d

关键词： Intralogistics inconsistency management model change management

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Asymmetric Neural Image Compression with High-Preserving information

Asymmetric Neural Image Compression with High-Preserving Inf...

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ieee International symposium on Circuits and systems (ISCAS)

作者： Hui, Kai Liu, Yu Xu, Fang Liu, Renhe Wang, Han Song, Shenghui Tianjin Univ Sch Microelect Tianjin Peoples R China Southwest Univ Chongqing Peoples R China Hong Kong Univ Sci & Technol Hong Kong Peoples R China

ISBN: (纸本)9798350330991;9798350331004

Recently, neural image compression has made significant progress in reducing rate-distortion and has received widespread attention. However, existing methods focus more on perfecting entropy models yet overlook the ability of their encoder networks to extract non-linear features of images, which can promote compression performance. In this paper, we design a learning-based asymmetric image compression network to enhance the feature representation capability for improved compression quality. Firstly, we propose a high-preserving information block (HPIB) consisting of a high-frequency filtering module (HFM) and a feature modulation module (FMM) to fully utilize the different frequency information in images. Secondly, we progressively use the HPIB layer to design a high-performance encoder network for high-fidelity feature extraction. Results from extensive experiments demonstrate that our network performs superior to the prior art in terms of both PSNR and MS-SSIM metrics and achieves 3.91% and 8.88 % BD-rate over VVC on the Kodak and CLIC datasets, respectively.

关键词： Neural Image Compression Encoder Networks High-preserving information Block

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design of Dual Polarized FMCW Radar System with Coupler Integrated Lens Antenna for Automotive SAR Application

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ieee Transactions on Vehicular Technology 2025年第5期74卷 6991-7004页

作者： Lee, Chanhee Cho, Hyunyoung Ahn, ByungKuon Lee, Woo-Kyung Yu, Jong-Won Kim, Jeong-Wook School of Electrical Engineering Daejeon34141 Korea Republic of Soongsil University Department of Intelligent Semiconductors School of Electronic Engineering Seoul06978 Korea Republic of Korea Aerospace University School of electronic and information engineering Goyang Korea Republic of Ajou University Department of Electrical and Computer Engineering Suwon16499 Korea Republic of

This paper presents the design of a dual-polarized frequency-modulated continuous wave (FMCW) radar system with a coupler-integrated lens antenna for automotive synthetic aperture radar (SAR) applications. High-resolution radar imaging is imperative for automotive use, with dual-polarized SAR imaging providing robust support in achieving this objective. However, exploration of the system design for dual-polarized FMCW SAR systems has been limited. The paper outlines the design of the aforementioned radar system, emphasizing its suitability for automotive SAR applications. It details the requisite parameters for dual-polarized automotive SAR systems and the design considerations for the dual-polarized lens antenna. Additionally, it proposes a radar signal monitoring method employing a coupler-integrated antenna to detect the radiated radar signal. Furthermore, a dual-polarization synthesis method is introduced to enhance SAR image quality. Experimental validation of the implemented dual-polarized FMCW radar with a coupler-integrated lens antenna confirms the effectiveness of the proposed system design. © 1967-2012 ieee.

关键词： Lens antennas

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