Fortifying Smart Grids: A Holistic Assessment Strategy against Cyber Attacks and Physical Threats for Intelligent Electronic Devices

Intelligent electronic devices(IEDs)are interconnected via communication networks and play pivotal roles in transmitting grid-related operational data and executing control instructions.In the context of the heightened security challenges within smart grids,IEDs pose significant risks due to inherent hardware and software vulner-abilities,as well as the openness and vulnerability of communication protocols.Smart grid security,distinct from traditional internet security,mainly relies on monitoring network security events at the platform layer,lacking an effective assessment mechanism for IEDs.Hence,we incorporate considerations for both cyber-attacks and physical faults,presenting security assessment indicators and methods specifically tailored for IEDs.Initially,we outline the security monitoring technology for IEDs,considering the necessary data sources for their security assessment.Subsequently,we classify IEDs and establish a comprehensive security monitoring index system,incorporating factors such as running states,network traffic,and abnormal behaviors.This index system contains 18 indicators in 3 categories.Additionally,we elucidate quantitative methods for various indicators and propose a hybrid security assessment method known as GRCW-hybrid,combining grey relational analysis(GRA),analytic hierarchy process(AHP),and entropy weight method(EWM).According to the proposed assessment method,the security risk level of IEDs can be graded into 6 levels,namely 0,1,2,3,4,and 5.The higher the level,the greater the security risk.Finally,we assess and simulate 15 scenarios in 3 categories,which are based on monitoring indicators and real-world situations encountered by IEDs.The results show that calculated security risk level based on the proposed assessment method are consistent with actual simulation.Thus,the reasonableness and effectiveness of the proposed index system and assessment method are validated.

Recent Advances in Artificial Sensory Neurons:Biological Fundamentals,Devices,Applications,and Challenges

Spike-based neural networks,which use spikes or action potentialsto represent information,have gained a lot of attention because of their high energyefficiency and low power consumption.To fully leverage its advantages,convertingthe external analog signals to spikes is an essential prerequisite.Conventionalapproaches including analog-to-digital converters or ring oscillators,and sensorssuffer from high power and area costs.Recent efforts are devoted to constructingartificial sensory neurons based on emerging devices inspired by the biologicalsensory system.They can simultaneously perform sensing and spike conversion,overcoming the deficiencies of traditional sensory systems.This review summarizesand benchmarks the recent progress of artificial sensory neurons.It starts with thepresentation of various mechanisms of biological signal transduction,followed bythe systematic introduction of the emerging devices employed for artificial sensoryneurons.Furthermore,the implementations with different perceptual capabilitiesare briefly outlined and the key metrics and potential applications are also provided.Finally,we highlight the challenges and perspectives for the future development of artificial sensory neurons.

In-plane micro-sized energy storage devices:From device fabrication to integration and intelligent designs

The rapid development of micro-electronics raises the demand of their power sources to be simplified,miniaturized and highly integratable with other electronics on a chip.In-plane Micro-sized energy storage devices(MESDs),which are composed of interdigitated electrodes on a single chip,have aroused particular attentions since they could be easily integrated with other miniaturized electronics,reducing the complexity of overall chip design via removing complex interconnections with bulky power sources.This review highlights the achievements in the device fabrication of in-plane MESDs,as well as their integration and intelligent designs.We also discussed the current challenges and future perspectives for the development of in-plane MESDs.

Research on urban intelligent fashion advertising service model based on wearable devices

We are developing a novel wearable devices called the urban intelligent fashion advertising.Such system is mobile information devices capable of supporting remote communication and intelligent interaction between terminals.In this paper,we explore the possible functions of such a wearable devices and will present the service-based architecture combing the hardware and the software.This architecture involves two major parts.The first part is hardware design,which includes microcontroller,display part,communication module,and positioning system module.The second part is software design,which is a real-time interactive system that includes signal reception,position detection,and user workload assessment.Then,we use the interactive concept and interactive technology to construct the urban fashion advertising service model,and elaborate on its business model.Finally,we present sustainability development recommendations for the proposed service model.

Application of Machine Learning in Electronic Device Fault Diagnosis

As electronic devices become increasingly complex, traditional fault diagnosis methods face significant challenges. Machine learning technologies offer new opportunities and solutions for electronic device fault diagnosis. This paper explores the application of machine learning in electronic device fault diagnosis, focusing on common machine learning algorithms, data preprocessing techniques, and diagnostic model construction methods. Case study analysis elucidates the advantages of machine learning in improving diagnostic accuracy, reducing diagnosis time, and implementing predictive maintenance. Research indicates that machine learning techniques can effectively enhance the efficiency and precision of electronic device fault diagnosis, providing robust support for device reliability and maintenance strategy optimization. In the future, as artificial intelligence technology further develops, machine learning will play an increasingly important role in the field of electronic device fault diagnosis.

基于DeviceNet总线的智能照明控制器设计

Devicenet总线在智能照明控制方面有着明显优势。本文设计了一个基于Device Net现场总线的智能照明控制器。以协议规范为蓝本,介绍了智能照明控制器的Device Net接口硬件实现方案,系统软件在分析了对象模型的基础上由Keil u Vision4编写,最终实现调节灯光照度的效果。

Design of the Control System of Adaptive Balancing Device Based on PLC

Due to the well condition and the un-expected imbalance movement of the pumping unit in use, the energy consumes a lot. The existing balancing equipment cannot adjust and monitor the pumping units in real time. Therefore this paper introduces the new adaptive balancing equipment—fan-shaped adaptive balancing intelligent device, projects a design of such control system based on PLC, and determines the principle of the control system, the execution software and the design flow. Site commissioning effect on Daqing Oilfield shows this fan-shaped adaptive balancing intelligent device can effectively adjust and monitor the pumping unit in real time, the balance even adjusts from 0.787 to 0.901, and integrated energy saving rate is 14.2%. It is approved that this control device is professionally designed, with strong compatibility, and high reliability.

Research on intelligent ultrasonic thickness measurement system applied to large area of hull

For a ship in service,seawater corrosion is unavoidable. In order to ensure navigation safety and master the steel plate thickness in service ship,thickness of the ship steel plate must be tested periodically by a scientific method. After consideration of an actual situation of thickness measurement,the bearing mechanism of ultrasonic thickness meter probe has been designed on the basis of wall-climbing robot,and preliminary experiments have been carried out. The device is mainly used for thickness measurement of a large area of ship hull plate when the docking ship has been sandblasted. Efficiency and safety can be improved to finish thickness measurement by using the device.

Application of Mobile Intelligent Inspection System in Substation Equipment Management

Intelligent inspection is more and more widely applied in all walks of life. This paper introduces the application of the intelligent inspection system in substation equipment management based on mobile phone terminal. It can make the power supply enterprise have more effective means to ensure the safe operation of equipment, improve equipment management level, and improve the economic benefits of power supply.

The Research of Intelligent Substation Time Synchronization System and the Influence of Its Fault to Relay Protection

The intelligent substation realizes the digitization of information in the whole substation and thus time synchronization system becomes more and more important. This paper introduces time synchronization technology of intelligent substation and puts forward the principles for designing intelligent substation time synchronization system. According to some relay protection malfunction examples caused by time synchronization system fault, analyze the influence of time synchronization system fault to relay protection and correspondingly put forward some improving measures.

Edge Device Fault Probability Based Intelligent Calculations for Fault Probability of Smart Systems

In a smart system, the faults of edge devices directly impact the system’s overall fault. Further, complexity arises when different edge devices provide varying fault data. To study the Smart System Fault Evolution Process (SSFEP) under different fault data conditions, an intelligent method for determining the Smart System Fault Probability (SSFP) is proposed. The data types provided by edge devices include the following: (1) only known edge device fault probability;(2) known Edge Device Fault Probability Distribution (EDFPD);(3) known edge device fault number and EDFPD;(4) known factor state of the edge device fault and EDFPD. Moreover, decision methods are proposed for each data case. Transfer Probability (TP) is divided into Continuity Transfer Probability (CTP) and Filterability Transfer Probability (FTP). CTP asserts that a Cause Event (CE) must lead to a Result Event (RE), while FTP requires CF probability to exceed a threshold before RF occurs. These probabilities are used to calculate SSFP. This paper introduces a decision method using the information diffusion principle for low-data SSFP determination, along with an improved method. The method is based on space fault network theory, abstracting SSFEP into a System Fault Evolution Process (SFEP) for research purposes.

The accuracy of arrhythmia detection and its clinical significance of intelligent wearable electrocardiogram monitoring devices in asymptomatic myocardial ischemia patients during daily activities.

This study focuses on the accuracy of arrhythmia detection by intelligent wearable electrocardiogram(ECG)monitoring devices in asymptomatic myocardial ischemia patients during daily activities.It elaborates on the technical principles,features,and working modes of such devices and makes a comparison with traditional ECG monitoring methods.Through a well-designed experimental approach involving data collection and analysis using specific evaluation metrics and standards,the accuracy of arrhythmia detection is evaluated.The relationship between arrhythmia and myocardial ischemia is explored,along with its impact on diagnosis,prognosis,and treatment strategy development.The application of these devices in daily activities,including feasibility,compliance,and analysis during different activity states and long-term trends,is also examined.Despite the potential benefits,technical limitations and barriers to clinical acceptance are identified,and future research directions are proposed.The findings contribute to a better understanding of the role and value of intelligent wearable ECG monitoring devices in the management of asymptomatic myocardial ischemia patients.

Impact of Artificial Intelligence on Corporate Leadership

Artificial Intelligence (AI) is transforming organizational dynamics, and revolutionizing corporate leadership practices. This research paper delves into the question of how AI influences corporate leadership, examining both its advantages and disadvantages. Positive impacts of AI are evident in communication, feedback systems, tracking mechanisms, and decision-making processes within organizations. AI-powered communication tools, as exemplified by Slack, facilitate seamless collaboration, transcending geographical barriers. Feedback systems, like Adobe’s Performance Management System, employ AI algorithms to provide personalized development opportunities, enhancing employee growth. AI-based tracking systems optimize resource allocation, as exemplified by studies like “AI-Based Tracking Systems: Enhancing Efficiency and Accountability.” Additionally, AI-powered decision support, demonstrated during the COVID-19 pandemic, showcases the capability to navigate complex challenges and maintain resilience. However, AI adoption poses challenges in human resources, potentially leading to job displacement and necessitating upskilling efforts. Managing AI errors becomes crucial, as illustrated by instances like Amazon’s biased recruiting tool. Data privacy concerns also arise, emphasizing the need for robust security measures. The proposed solution suggests leveraging Local Machine Learning Models (LLMs) to address data privacy issues. Approaches such as federated learning, on-device learning, differential privacy, and homomorphic encryption offer promising strategies. By exploring the evolving dynamics of AI and leadership, this research advocates for responsible AI adoption and proposes LLMs as a potential solution, fostering a balanced integration of AI benefits while mitigating associated risks in corporate settings.

人工智能器件宇航应用面临的挑战与应对措施

人工智能器件是提供实现系统功能的微小型化器件,是实现空间环境感知、自主判断、自主任务规划等的硬件载体和基础。此类新型元器件在宇航应用前,仍然面临成熟度、可靠性、抗辐射能力、宇航适用性等诸多挑战。本文从分析人工智能器件国内外发展现状出发,分析人工智能器件宇航应用面临的挑战与应对措施,给出典型人工智能器件质量保证案例,并归纳和总结后续人工智能器件宇航应用的相关建议。

基于《国际功能、残疾和健康分类》评价中国智能化辅盲设备的补偿功能

背景:辅盲设备及技术的应用是当今视力障碍人群常用的干预手段,可提高日常生活活动的参与及工作学习能力,帮助其回归家庭、回归社会。数字信息和智能化时代下辅盲设备的形式、技术和功能各有不同,其分类目前暂未能得到有效统一的讨论和评价。目的:基于《国际功能、残疾和健康分类》评价国内视力障碍人群智能化辅盲设备的补偿功能。方法:通过计算机检索中国知网、维普和万方数据库2013-01-01/2023-12-31收录的相关文献。基于《国际功能、残疾和健康分类》理论模式和框架结构,应用术语结构和编码程序归纳相关视力障碍评估类目,整理与分析国内视力障碍的智能化辅盲设备补偿功能研究与分类。结果与结论:①共纳入197篇文献:其中身体功能1篇,包含b2(b210);身体结构1篇,包含s2(s220);活动与参与共119篇,包含d1(10篇,d110、d115、d120、d140、d166),d3(4篇,d315、d325、d345、d360),d4(102篇,d465、d470),d8(3篇,d820、d825);环境因素共76篇,包含e1(72篇,e115、e120、e125、e130、e140、e150、e155、e160),e2(4篇,e210、e240);②基于《国际功能、残疾和健康分类》的视力障碍智能化辅盲设备补偿功能研究分类包含4个部分、8个分类、25个类目,领域涉及身体补偿类、生活用品类、教育学习类、出行导盲类、布局规划类。

高铁预制箱梁桁架式收面装置快速施工技术研究

随着国内工程施工水平的不断发展,高速铁路箱梁预制施工技术及施工组织已基本成熟,宜兴铁路夷陵制梁场通过对制梁工序进行深入研究分析,研究了桁架式收面装置预制箱梁快速施工技术。该技术满足预制箱梁收面要求,所需人工少,与传统收面工艺相比,本收面装置设备轻便,智能化程度高,能实现减员、提高功效、降低劳动强度和施工成本最节约的目的。从施工技术上进行了创新,在宜兴铁路夷陵制梁场得到了推广应用,也给其它类似大中型制梁场提供了有力的技术支持和借鉴。

一种提高船闸运行效率的信号装置系统

针对当前船闸信号装置缺乏倒计时显示和人工操作可能导致信号跳转不及时的问题,本文提出了一种提高船闸运行效率的信号装置系统。该系统采用红绿信号灯和倒计时器组成信号装置,通过监控摄像头和激光雷达等感知设备实时采集过闸船舶数据,并利用人工智能和图像处理技术进行处理和分析。系统能够根据闸室内船舶的进出情况,实现红绿信号的自动跳转和倒计时显示功能,从而提高船闸的运行效率,减少过闸时间损耗,提升船舶过闸的安全性和顺畅性。

电气试验设备柜智能防凝露调控系统设计

电气试验设备柜内凝露现象会对设备的正常运作产生显著的负面影响,并可能对操作人员的安全构成威胁。基于分析凝露现象在设备柜内发展进程及防凝露控制原理,提出智能防凝露调控系统总体结构。该系统由可编程逻辑控制器(PLC)和人机界面(HMI)构成的中央控制单元、温度湿度控制装置以及外围执行机构组成。综合评估温度和湿度因素对设备凝露现象的影响并设计一套全面控制策略。该系统具备多项保护功能,包括设备疲劳防护、低温防护、快速冷却保护以及高温预警信号处理,从而增强了设备的运行安全与稳定性。人机交互HMI实现系统监视,测试了电气试验设备柜内不同相对湿度,不同相对高度,不同除湿装置的布置方式对壁面水蒸气冷凝速率的影响。测试结果表明相对湿度越大,冷凝速率衰减至0的时间越长,冷凝速率的变化主要发生在柜体的上半部分,在柜体的上部区域安装智能防凝露装置,效果将更为显著。

基于A^(2)/O技术的煤矿生活污水处理系统

古城煤矿近年来一直致力于节能减排增效等技术的研究、试验和推广应用。文章结合古城煤矿生活污水的特点,对比当前国内煤矿生活污水处理典型技术,设计了一套基于A^(2)/O技术,辅以智慧化曝气装置的生活污水处理系统,为提高古城煤矿未来生活污水处理能效,促进节能减排提供有益参考。

Intelligent algorithms: new avenues for designing nanophotonic devices [Invited]

The research on nanophotonic devices has made great progress during the past decades. It is the unremitting pursuit of researchers that realize various device functions to meet practical applications. However, most of the traditional methods rely on human experience and physical inspiration for structural design and parameter optimization, which usually require a lot of resources, and the performance of the designed device is limited. Intelligent algorithms, which are composed of rich optimized algorithms, show a vigorous development trend in the field of nanophotonic devices in recent years. The design of nanophotonic devices by intelligent algorithms can break the restrictions of traditional methods and predict novel configurations, which is universal and efficient for different materials, different structures, different modes, different wavelengths, etc. In this review, intelligent algorithms for designing nanophotonic devices are introduced from their concepts to their applications, including deep learning methods, the gradient-based inverse design method, swarm intelligence algorithms, individual inspired algorithms, and some other algorithms. The design principle based on intelligent algorithms and the design of typical new nanophotonic devices are reviewed. Intelligent algorithms can play an important role in designing complex functions and improving the performances of nanophotonic devices, which provide new avenues for the realization of photonic chips.