Development of a Model Driven ACSI Conformance Testing for IEC 61850-Based IED

Globally, traditional power systems are rapidly transforming towards the adoption of smart grid platforms. Substations which are at the center of the electric power transformation from the power plant are changing to IEC 61850 based digital substations. Therefore, within substation, there is a growing demand for the IEC 61850 based Intelligent Electronic Devices (IEDs). The operation of multiple manufacturers of IEDs in a single digital substation network increases the need for IEC 61850 communications specification conformance diagnosis to ensure interoperability for efficient data exchange between IEDs. The IEC 61850-10 presents test items for diagnosing communication specification conformance. There are many test tools available in the market today to test the compliance of the IEC 61850 communications specifications to the IED. In this paper, we propose a model-based diagnostic method for IED communication conformance testing. The proposed model-based software therefore uses the “drag and drop” technique to select the various IEC 61850 communication services (objects) required to design the test case in a user friendly Graphical User Interface (GUI). This makes the service conformance testing more flexible for test engineers and system integrators especially in situations that require test case modifications. Also, the proposed software tool makes it easy to understand the various IEC 61850 services using the friendly GUI.

The Impact of Social Media Networks Websites Usage on Students’ Academic Performance

Social Networks Sites (SNSs) are dominating all internet users’ generations, especially the students’ communities. Consequently, academic institutions are increasingly using SNSs which leads to emerge a crucial question regarding the impact of SNSs on students’ academic performance. This research investigates how and to what degree the use of SNSs affects the students’ academic performance. The current research’s data was conducted by using drop and collect surveys on a large population from the University of Jordan. 366 undergraduate students answered the survey from different faculties at the university. In order to study the impact of SNSs on student’s academic performance, the research hypotheses was tested by using descriptive analysis, T-test and ANOVA. Research results showed that there was a significant impact of SNS on the student’s academic performance. Also, there was a significant impact of SNS use per week on the student’s academic performance, whereas no differences found in the impact of use of SNSs on academic performance due to age, academic achievement, and use per day to most used sites. The findings of this research can be used to suggest future strategies in enhancing student’s awareness in efficient time management and better multitasking that can lead to improving study activities and academic achievements.

深度神经网络的测试输入选择与度量标准研究综述

随着深度神经网络在各个领域受到广泛应用,对其进行测试评估并确保其安全性显得尤为重要。测试输入选择方法可以帮助在测试数据集规模较大且标注成本较高的情况下,对测试样本进行选择与排序,以提高测试效率和测试覆盖率。为了深入了解深度神经网络测试输入选择领域的研究进展,对近5年来91篇相关领域的学术论文进行了系统梳理。介绍了深度神经网络测试的基本概念和流程,包括深度学习系统的构建、测试输入的选择和测试结果的评估;概括分析了各种度量标准和测试输入选择方法的适用场景与不足之处,以及彼此之间的相互联系。最后,指出了当前深度神经网络测试输入选择与评估工作面临的挑战和机遇。

基于BP神经网络的刀片切割竹枝性能研究

为探究竹枝切割时的刀片切割性能影响因素,支持后续打枝装置的设计,开展竹枝切割刀片性能研究试验,通过单因素试验研究,利用切割阻力作为衡量标准,探究刀片切割性能与关键参数(刀片的滑动角、楔角和滑动速度)之间的相互关系。试验结果显示,随着刀片滑动角和楔角的减小,刀片切割性能呈现明显改善。同时,随着刀片滑动速度的增加,切割性能也呈现相应提升趋势。在多组实验中,采用不同的刀片滑切角度、楔角和滑切速度参数,对不同直径尺寸的竹枝进行切割,并收集了切割阻力的数据构成数据集,构建一个3层BP神经网络模型,研究了刀片切割性能与滑切角度、楔角以及滑切速度之间的关联,并应用相关模型进行了拟合和预测。在BP神经网络中,当隐含层节点数设定为9时,成功建立了刀片切割阻力模型,精准地预测了刀片切割过程中的阻力变化,对刀片切割竹枝性能研究具有一定参考价值。

信创CPU与Intel CPU在NUMA架构方面的调优实践

通过选取具有代表性的基准测试工具,文章对比了信创CPU和IntelCPU在多核性能方面的表现。同时,针对NUMA架构的特点进行了调优实验,并通过分析性能数据得出了调优前后的性能差异。结果表明,通过NUMA调优可以有效提高处理器的性能。

等保2.0标准下网络渗透测试研究

该文旨在探讨等保2.0标准下进行网络渗透测试的方法和技术。通过研究等保2.0标准对网络渗透测试的要求和影响,以及针对等保2.0标准下网络渗透测试的挑战和解决方案,旨在为实施等保2.0标准提供更有效的安全保障。在研究中,重点关注等保2.0标准下网络渗透测试的方法和流程,包括渗透测试目标的确定和规划、渗透测试工具的选择和使用、渗透测试的技术和策略,以及渗透测试结果的分析和报告等方面。

基于BP神经网络的目标识别算法和多源感知技术相融合的GIS性能检测方法

针对传统多源感知检测方法在气体绝缘全封闭组合电器(Gas Insulated Switchgear, GIS)作业中性能检测数据准确度不足的问题,设计了一种基于目标识别算法和多源感知技术相融合的GIS性能检测方法。在传统性能检测技术中引入以BP神经网络为核心的目标识别算法,通过BP多层神经网络,实现了高效地数据目标提取,大幅提高了数据检测的准确度。为解决单一传感器不能完整地捕捉复杂环境信息的问题,基于多源感知技术,采用多个传感器对多个数据源进行综合感知,扩展了环境视角与信息维度,实现了对周围环境的全方位监控,使检测系统获得了更为理想的数据检测能力。在实际GIS运行环境中进行实地检测,将所提出的改进多源感知方法与传统多源感知方法进行了实验对比。结果表明,所提方法能够将GIS性能检测的准确度提高至98%以上。

振动检测在配网开关性能检测中的应用

配网开关性能振动检测方法通过采集和分析配网开关的振动信号,实现对配网开关运行状态的检测和故障预警。首先,介绍了配网开关的基本概念及振动检测的意义;其次,阐述了振动检测技术在配网开关检测中的应用原理和优势;然后,详细描述了配网开关性能振动检测系统的设计和实现,包括硬件和软件2个部分;最后,分析了该技术在电力行业中的应用现状和发展趋势。

Pre-deformation for Assembly Performance of Machine Centers

The current research of machine center accuracy in workspace mainly focuses on the poor geometric error subjected to thermal and gravity load while in operation,however,there are little researches focusing on the effect of machine center elastic deformations on workspace volume.Therefore,a method called pre-deformation for assembly performance is presented.This method is technically based on the characteristics of machine tool assembly and collaborative computer-aided engineering(CAE)analysis.The research goal is to enhance assembly performance,including straightness,positioning,and angular errors,to realize the precision of the machine tool design.A vertical machine center is taken as an example to illustrate the proposed method.The concept of travel error is defined to obtain the law of the guide surface.The machine center assembly performance is analyzed under cold condition and thermal balance condition to establish the function of pre-deformation.Then,the guide surface in normal direction is processed with the pre-deformation function,and the machine tool assembly performance is measured using a laser interferometer.The measuring results show that the straightness deviation of the Z component in the Y-direction is 158.9%of the allowable value primarily because of the gravity of the spindle head,and the straightness of the X and Y components is minimal.When the machine tool is processed in pre-deformation,the straightness of the Z axis moving component is reduced to 91.2%.This research proposes a pre-deformation machine center assembly method which has sufficient capacity to improving assembly accuracy of machine centers.

Time Delay Characteristic of Industrial Wireless Networks Based on IEEE 802.15.4a

The IEEE 802.15.4a standard provides a framework for low-data-rate communication systems,typically sensor networks.In this paper,we established a realistic environment for the time delay characteristic of industrial network based on IEEE 802.15.4a.Several sets of practical experiments are conducted to study its various features,including the effects of 1) numeral wireless nodes,2) numeral data packets,3) data transmissions with different upper-layer protocols,4) physical distance between nodes,and 5) adding and reducing the number of the wireless nodes.The results show that IEEE 802.15.4a is suitable for some industrial applications that have more relaxed throughput requirements and time-delay.Some issues that could degrade the network performance are also discussed.

Characterization of machine tools and measurement system for micromilling

Technological progress has led to increased demand for small components with tiny features, which cannot be achieved through conventional machining. Industrial application of processes based on microcutting is limited by some issues concerning the geometrical scale. The process performance is significantly affected by milling machine, tool holder, tool, workpiece material microstructure, workpiece fixtures, and process parameters. At present, an ultimate micromachining assessment procedure is not available. This study aims to propose and conduct an experiment on a testing procedure for micromilling. The set up to be implemented and the output to be considered are defined and described. Three major stages are identified: estimation of the effective bandwidth of the load cell–tool holder system, the milling machine natural frequency measurement, and micromilling test execution. The entire procedure is performed, and its robustness is demonstrated.

Technology Provides Better Document Search Results on Slovak Legislation Webpage as Result of a Simulation of Webpage Performance Parameters

This article acquaints the public with the insights gained from conducting document searches in the Slovak public administration information system,when supported by knowledge of its management.Additionally,it discusses the advantages of simulating performance parameters and comparing the obtained results with the real parameters of the eZbierka(eCollection)legislation webpage.This comparison was based upon simulated results,obtained through the Gatling simulation tool,versus those obtained from measuring the properties of the public administration legislation webpage.Both sets of data(simulated and real),were generated via the the document search technologies in place on the eZbierka legislation webpage.The webpage provides users with binding laws and bylaws available in an electronically signed PDF file format.It is free open source.In order to simulate the accessing of documents on the webpage,the Gatling simulation tool was used.This tool simulated the activity,performed in the background of the information system,as a user attempted to read the data via the steps mentioned in the scenario.The settings of the simulated environment corresponded as much as possible to the hardware parameters and network infrastructure properties used for the operation of the respective information system.Based on this data,through load changing,we determined the number of users,the response time to queries,and their number;these parameters define the throughput of the server of the legislation webpage.The required parameter determination and performance of search technology operations are confirmed by a suitable hardware design and the webpage property parameter settings.We used the data from the eZbierka legislation webpage from its operational period of January 2016 to January 2019 for comparison,and analysed the relevant data to determine the parameter values of the legislation webpage of the slov-lex information system.The basic elements of the design solution include the technology used,the technology for searching the legislative documents with support of a searching tool,and a graphic database interface.By comparing the results,their dependencies,and proportionality,it is possible to ascertain the proper determination and appropriate applied search technology for selection of documents.Further,the graphic interface of the real web database was confirmed.

BP神经网络在大跨斜拉桥性能检测中的应用研究

大跨斜拉桥工程的迅速发展对给该类桥梁的工作性能评估提出了更高的要求。针对大跨度斜拉桥的复杂情况,以浙江省某大跨度斜拉桥为检测对象,利用MIDAS/CIVIL有限元建模预测和荷载试验相结合的方法对桥梁的实际工作性能进行评测。采用Python软件构建BP神经网络,利用MIDAS/CIVIL有限元模型提供的训练样本对算法进行训练,将荷载试验实测值作为算法输入,得到桥梁模型参数和桥梁挠度应变改良值。由结果对比可知:MIDAS/CIVIL模型参数取值和真实值相差较大,误差最大可达27%。BP神经网络算法优化后的桥梁应变预测值更接近实际,优化后理论值误差可减少10%~20%。研究结果表明BP神经网络算法在桥梁工作性能评估中具有实践意义,该研究为大跨斜拉桥工作性能评估提供了可靠的方法借鉴。

钻头破岩能量与岩石自适应匹配提速技术

针对深层、超深层和复杂地层等对钻井提速的要求,考虑深层岩体可钻性变化,提出了基于钻头破岩能量与岩石特征自适应匹配的钻井提速技术。在分析钻头破岩过程中扭矩特征的基础上,研制了自适应匹配工具,利用行星齿轮和扭簧结构进行能量存储与释放,钻进岩性均质地层过程中提前蓄能,钻遇砾石层或非均质地层时释放能量进行辅助破岩。通过静力学和动力学性能测试,验证了自适应匹配工具结构的可靠性和实现提速的可行性。自适应匹配工具在深层页岩气井进行了现场试验,结果表明:与使用常规方法的邻井相比,机械钻速提高了83%,验证了该工具提速的有效性和稳定钻头工作状态的效果。钻头破岩能量与岩石自适应匹配提速技术,为深层、超深层和复杂地层钻井提速提供了理论支撑和新的技术途径。

刀具表面椭圆开口偏置抛物线微织构参数优化

为充分发掘微织构刀具提高钛合金切削性能的潜力。以硬质合金刀具切削钛合金为研究对象,基于响应面试验方法研究了椭圆开口偏置类抛物线微织构(elliptic opening offset parabola micro texture, EOOPT)特征参数对刀具切削性能的影响规律;通过神经网络和遗传算法对其进行多目标参数优化;对相同切削条件下织构最优参数EOOPT刀具和原型刀具的相关切削性能进行了对比分析。结果表明:与原型刀具相比,最优参数EOOPT刀具的最高温度、最大应力和主切削力的平均值分别降低了11.24%、15.48%和10.81%,这对提高钛合金零件的加工质量、提高刀具寿命、降低生产成本具有积极作用。

涡轮旋转引鞋的研制与应用

针对目前国内完井管柱下入工具驱使套管下入水平段长度有限,难以到达预定深度,功率消耗过大,容易损坏套管引发事故等问题,研制了水力驱动涡轮旋转引鞋。通过建立涡轮定、转子的三维模型,并导入Workbench软件建立涡轮定、转子中液流流过的流道模型,在Fluent中对涡轮旋转引鞋定、转子的水力性能进行分析,完成结构设计、性能试验及现场试验。试验结果表明:该工具可通过液流循环实现引鞋头旋转,从而进行井壁的修整和井筒的冲洗,并帮助完井管柱顺利下入到预定位置;设计的涡轮旋转引鞋工具完成了50 h寿命试验,满足现场应用需求。所得结论可为水平井与大斜度井完井管柱下入工具的研制提供技术借鉴。

武器装备网络脆弱性试验方案设计

针对武器装备网络安全试验需求,阐述了网络脆弱性发现、分类、赋值和验证方法,提出了脆弱性试验的流程、方法和步骤;以某典型武器控制系统为例,设计了脆弱性验证试验方案,对系统内的设备进行分类识别,从物理环境、网络结构、系统软件、应用程序等方面进行赋值和描述,并提出了验证方法,为靶场开展网络安全专项试验提供支撑。

黑盒遗传算法下异构网络信息安全漏洞深度挖掘

为设计有效测试信息用例,深度、全面挖掘异构网络信息安全漏洞,提出黑盒遗传算法下异构网络信息安全漏洞深度挖掘方法.其核心基于威胁概率计算的异构网络态势感知方法,在分析异构网络环境后,计算目前网络攻击状态与历史攻击状态之间相关性,分析网络威胁概率判断网络态势;针对属于异常态势的网络,基于黑盒遗传算法的漏洞深度挖掘模型,使用驱动Fuzzing测试工具,设计有效测试信息用例,将测试信息用例从异构网络链路层,发送至目标服务器,根据目标服务器所接收数据包中测试信息用例的缺失状态,便可判断信息安全是否存在漏洞.经测试,所提方法在挖掘信息安全漏洞时,所设计的有效测试信息用例的比例明显增大,对多种漏洞信息均可准确挖掘,具备深度、全面挖掘异构网络信息安全漏洞能力.

基于multi-CNN的专用网络入侵检测模型设计与仿真

多尺度卷积神经网络模型在网络入侵检测中可获取更丰富的局部特征。针对浅层卷积核神经网络获取数据局部特征能力较差的不足,文中基于多尺度卷积神经网络,提出一种改进的列车通信专用网络入侵检测模型。该模型对Inception V3网络加以改进,并将模型部分大尺寸卷积核进行合理缩小并串联,以增强模型获取数据局部特征的能力;同时结合循环神经网络对时间序列的学习能力,利用Bi-GRU模型对局部特征进行学习,使模型训练后的数据也具有全局特征。实验测试结果表明:所设计模型在二分类测试中的准确度与Inception V3模型相比提升约1.3%,运行时间缩短近5.2 s;在五分类测试中,与其他对比算法相比准确度平均提升1.7%。该模型有良好的性能及效率,可有效且准确地对网络入侵进行检测。

基于高速数据处理平台的网络转发性能测试方法

鉴于目前国产化测试环境中对网络数据转发性能测试方法不足的问题,提出一种基于高速数据处理平台的软件测试方法。依托国产化平台,搭建一个高效的数据转发性能测试环境,通过对设备的单双向的吞吐量、响应时间等技术指标进行测试,发现设备的三层转发性能的极限。测试结果表明,该方法能高效快捷地得到性能测试结果,为国产化设备的转发性能的测试和环境部署提供了技术参考。