The Measurement and Control of Diameter in Large-Scale Part Processing

Based on laser-scanned measuring technology, a met ho d of on-line dynamic non-contact measurement and feedback control of processin g dimension, i.e. the double edges laser-scanned large diameter on-line dynami c measurement and control system is presented, which can be used to measure diam eter in large-scale machine part processing. In this paper, the working princip le, overall structure and microcomputer real-time control and data processing s ystem of the system are discussed in detail, the method of double edges scanned large diameter dimension measurement and control is theoretically analyzed, its possibility has been verified by experiments of lathing large diameters machine parts by a vertical lathe. The system adopts the measuring scheme of double edge s laser-scanned combined with grating displacement measurement. The two edges c haracteristic information of the measured diameter is given by the double edges laser-scanned measuring system, the non-contact measurement of large diameter dimension is realized to combine with the grating displacement measuring systems . The main controller gives out feedback control signal by means of measured res ults, and controls advance and retreat of lathe tool by the servo-control syste m of a vertical lathe to realize on-line dynamic non-contact measurement and c ontrol in processing.

Robust iterative learning control for nonlinear systems with measurement disturbances

The iterative learning control （ILC） has been demon-strated to be capable of considerably improving the tracking perfor-mance of systems which are affected by the iteration-independent disturbance. However, the achievable performance is greatly degraded when iteration-dependent, stochastic disturbances are pre-sented. This paper considers the robustness of the ILC algorithm for the nonlinear system in presence of stochastic measurement disturbances. The robust convergence of the P-type ILC algorithm is firstly addressed, and then an improved ILC algorithm with a decreasing gain is proposed. Theoretical analyses show that the proposed algorithm can guarantee that the tracking error of the nonlinear system tends to zero in presence of measurement dis-turbances. The analysis is also supported by a numerical example.

A Trusted Attestation Mechanism for the Sensing Nodes of Internet of Things Based on Dynamic Trusted Measurement

Internet of things has been widely applied to industrial control, smart city and environmental protection, in these application scenarios, sensing node needs to make real-time response to the feedback control of the application layer. Therefore, it is necessary to monitor whether or not awareness nodes are trusted in real time, but the existing mechanisms for trusted certification lack the real-time measurement and tracking of the sensing node. To solve the above problems,this paper proposes a dynamic metric based authentication mechanism for sensing nodes of Internet of things. Firstly, the dynamic trustworthiness measure of the sensing nodes is carried out by introducing the computational function such as the trust function, the trustworthiness risk assessment function, the feedback control function and the active function of the sensing node. The dynamic trustworthiness measure of sensing nodes from multiple dimensions can effectively describe the change of trusted value of sensing nodes. Then, on the basis of this, a trusted attestation based on node trusted measure is realized by using the revocable group signature mechanism of local verifier. The mechanism has anonymity, unforgeability and traceability, which is proved the security in the standard model. Simulationexperiments show that the proposed trusted attestation mechanism is flexible, practical and efficient and has better attack resistance. It can effectively guarantee the reliable data transmission of nodes and realize the dynamic tracking of node reliability, which has a lower impact on system performance.

Dynamic Integrity Measurement Model Based on vTPM

With the development of cloud computing, virtualization technology has been widely used in our life. Meanwhile, it became one of the key targets for some attackers. The integrity measurement in virtual machine has become an urgent problem. Some of the existing virtualization platform integrity measurement mechanism introduces the trusted computing technology, according to a trusted chain that the Trusted Platform Module(TPM) established for trusted root to measure the integrity of process in static. But this single chain static measurement cannot ensure the dynamic credible in platform running. To solve the problem that the virtual trusted platform can not guarantee the dynamic credibility, this paper put forward Dynamic Integrity Measurement Model(DIMM) based on virtual Trusted Platform Module(v TPM) which had been implemented with typical virtual machine monitor Xen as an example. DIMM combined with virtual machine introspection and event capture technology to ensure the security of the entire user domain. Based on the framework, this paper put forward Self-modify dynamic measurement strategy which can effectively reduce the measurement frequency and improve the measurement performance. Finally, it is proved that the validity and feasibility of the proposed model with comparison experiments.

基于镜面和漫反射面标定板的系统参数标定

为获取同一像素点镜面反射和漫反射两种反射特性的相位信息和标定数据,实现兼具镜面和漫反射面的复合表面物体三维形貌的全场测量,进而扩大测量范围,提出一种基于镜面/漫反射面标定板的系统参数标定方法。设计并制作镜面/漫反射面标定板,该标定板呈棋盘格样式,其表面带有相邻距离已知的标识。基于镜面/漫反射面标定板的特殊构型,通过限位平移的方式,结合外参约束和样条插值算法以融合获取完整参考相位。在同一坐标系下,逐像素标定空间距离、系统参数、像素位置和横向坐标XY间的映射关系。最后,利用完整参考相位和逐像素标定数据重建复合表面物体的三维形貌。实验结果表明:与非全场测量相比,基于镜面和漫反射面标定板的参数标定方法的测量范围扩大了1.5~2倍。该方法在不牺牲精度的同时,实现了非连续复合表面物体三维形貌的全场测量,扩大了测量范围,对复合表面物体的三维形貌测量有实际应用价值。

A multi-paradigm decision modeling framework for combat system effectiveness measurement based on domain-specific modeling

Decision modeling is an essential part of the combat system effectiveness simulation (CoSES), which needs to cope with the cognitive quality, diversity, flexibility, and higher abstraction of decision making. In this paper, a multi-paradigm decision modeling framework is proposed to support decision modeling at three levels of abstraction based on domain-specific modeling (DSM). This framework designs a domain-specific modeling language (DSML) for decision modeling to raise the abstraction level of modeling, transforms the domain-specific models to formalism-based models to enable formal analysis and early verification and validation, and implements the semantics of the DSML based on a Python scripts framework which incorporates the decision model into the whole simulation system. The case study shows that the proposed approach incorporates domain expertise and facilitates domain modeler's participation in CoSES to formulate the problem using DSML in the problem domain, and enables formal analysis and automatic implementation of the decision model in the solution domain.

基于机器学习与大数据技术的入侵检测方法研究

电力系统中的异构数据严重影响了入侵检测结果,存在检准率低的问题,针对该问题,结合机器学习与大数据技术对电力系统进行入侵检测。构建入侵行为分析模型,使用大数据技术约减数据,将属性集转换为目标字符串。利用编辑距离计算两个字符串之间距离,以计算结果为判断依据,分析两个属性集之间的关联关系。将约减后的数据作为机器学习数据,分析入侵行为。引入异构值差度量距离函数,归一化预处理异构数据。经过多模式匹配生成待检测的报文,对报文逐条遍历,使用机器学习签名技术确定入侵行为数据位置,由此完成入侵行为检测。实验结果表明,该方法在不同攻击手段下的检准率均大于0.95,具有精准检测效果。

Junction temperature measurement of alternating current light-emitting-diode by threshold voltage method

Junction temperature of alternating current light-emitting-diode （AC-LED） has a significant effect on its stable light output and lifetime. The threshold voltage measurement is employed to characterize the junction temperature of AC-LED, due to its excellent merits in high efficiency and accuracy. The threshold voltage is measured when the driving current of an AC-LED rises to a reference on-set value from the zero-crossing node. Based on multiple measurements of threshold voltage at different temperatures, a linear relationship was uncovered between the threshold voltage and the junction temperature of AC- LED with the correlating factor of temperature sensitive parameter （TSP）. Thereby, we can calculate the junction temperature with the TSP and threshold voltage once the AC-LED stays at thermal equilibrium state. The accuracy of the proposed junction temperature measurement technique was found to be ＋3.2℃ for the reference current of 1 mA. It is concluded that the method of threshold voltage is accurate and simple to implement, making it highly suitable for measuring the junction temperature of AC-LED in industry.

航空发动机内流场数据平均方法研究综述

回顾了在航空发动机测试结果处理和数值仿真边界条件构建过程中发展而来的多种数据平均技术。归纳静压、总压、总温基于面积、体积流量、质量流量和熵通量等权重的加权平均法;介绍在假想混合面上与非均匀物理场满足相同物理特性的等效平均法及其扩展方法。梳理基于质量、动量、能量和熵等通量守恒规则发展出来的转静子交界面处的周向平均法;比较了不同加权平均方法之间各种等效平均方法之间的差别。最后总结各类平均方法的优势和缺陷,给出针对性应用场合中数据平均方法的选择建议。

二维超声剪切波弹性成像和血清学指标评分诊断慢性乙肝患者肝纤维化的价值

目的探讨二维超声剪切波弹性成像(2D-SWE)与血清学评分诊断慢性乙肝患者肝纤维化的价值。方法回顾2020年12月至2022年7月义乌市中心医院75例慢性乙肝患者的临床资料,根据经肝穿刺活检病理检查结果的Metavir分期分为纤维化组44例(F2~4期)和无纤维化组31例(F0~1期)。采用2D-SWE测量肝脏硬度(LSM),比较两组患者性别、年龄、病程、病毒载量、血生化指标、血清学指标评分,采用单因素和多因素logistic回归筛选肝纤维化的预测因素,绘制ROC曲线分析各项指标诊断肝纤维化的效能。结果与无纤维化组患者比较,纤维化组患者年龄较大,病程较长,病毒载量、ALT、AST、ALP、γ-谷氨酰转肽酶(γ-GT)、TBil、Ⅲ型前胶原、Ⅳ型胶原、透明质酸和LSM水平均明显较高,而球蛋白和PLT均明显较低(均P<0.05)。多因素logistic回归显示,LSM(OR=2.656,95%CI:2.103~3.562,P<0.01)和Ⅲ型前胶原(OR=1.546,95%CI:1.124~1.968,P<0.05)是发生肝纤维化的预测因素。ROC曲线分析得出LSM和Ⅲ型前胶原诊断肝纤维化的AUC分别为0.801和0.746,最佳截断值分别为12.6 kPa和7.7 ng/mL,即LSM≥12.6 kPa或者Ⅲ型前胶原≥7.7 ng/mL均提示肝纤维化。4个血清学评分包括AST-血小板比值指数(APRI)、King评分、Forns指数和基于4个因素的纤维化指数(FIB-4)诊断肝纤维化的AUC分别为0.772、0.703、0.685、0.621。选择性诊断(LSM≥12.6 kPa或者Ⅲ型前胶原≥7.7 ng/mL)和联合诊断(LSM≥12.6 kPa且Ⅲ型前胶原≥7.7 ng/mL)的AUC分别为0.874和0.778。logistic回归模型(0.124+1.021×LSM+0.741×Ⅲ型前胶原)的AUC为0.886,显著高于4个血清学指标评分(均P<0.05),与单一指标诊断和LSM诊断肝纤维化的效能相当(P>0.05)。结论2D-SWE定量检测慢性乙肝患者LSM可作为无创诊断肝纤维化的新型指标,结合血清Ⅲ型前胶原的选择性诊断或者logistic回归模型的诊断效能可能优于4个血清学评分。

恒温加热台温度偏差的测量不确定度评定

恒温加热台主要用于提供一个温度可调节、均匀稳定的平面温场,广泛用于半导体器件焊接加工,以及材料理化分析及生物工程等领域。随着相应的校准规范的发布与实施,规范恒温加热台的校准工作迫在眉睫,测量不确定度的评定更能更加体现校准工作的严谨性,本文依据相应的校准规范,简述恒温加热台的校准条件、校准项目及方法,对恒温加热台温度偏差的测量不确定度进行评定。

基于MDSplus分段技术的Web数据显示系统

先进托卡马克装置需要长脉冲放电实验运行,针对装置长脉冲放电实验的数据存储和交互技术是重要的研究内容之一。本工作设计了一种Web数据显示系统,系统采用ASP.NET架构和数据分段技术从MDSplus数据库读取分段数据,利用NI Measurement Studio控件库将数据显示在Web页面中。数据分段技术将长脉冲实验数据划分为多个较小的数据单元——数据段,用户可按需读取长脉冲实验数据中的部分数据段。同时系统制定了高效的分段读取策略,可准确、快速地显示用户所需的数据波形。Web数据显示系统在J-TEXT托卡马克上进行了测试,运行性能稳定,达到了系统的设计目标。

长空气间隙放电研究的挑战与进展

开展空气间隙放电的理论研究,是支撑我国特高压工程建设、提升电力系统雷击防护水平的现实需求。通过分析特高压下长空气间隙放电的工程需求,以及雷电绕击输电线路的先导发展模型、电气几何模型所面临的理论困境,归纳了当前长空气间隙研究所面临的主要挑战——物理模型的内在复杂性、测试手段的局限性及数值求解方法的不确定性。同时,基于过去30多年测量、计算方法的长足进步,指出目前我国开展长空气间隙放电研究的重大机遇。另外,还简要总结了国内外长空气间隙放电研究的发展历程及流注先导模型在不同历史时期的典型成果,详细介绍了清华大学在973项目的支持下,在长空气间隙放电的微观机理与宏观过程研究方面的最新进展,并对未来的研究方向与目标做了初步展望,包括:1)明晰不同尺度流注起始及发展的规律;2)更深入认识流注转化为先导的规律及机理;3)清晰描述先导的发展过程特征参数;4)建立更完备的长空气间隙击穿模型,能够更准确地预测长空气间隙的放电特性;5)建立更科学的雷击闪络先导发展模型及雷击闪络风险评估方法;6)提出工程实用的更优化的长空气间隙结构。

一维光电位置敏感器的应用研究

简要叙述了一维光电位置敏感器 (PSD)的工作原理 ,以及采用光学三角法测量构成的尺寸测量传感器 ,重点介绍光电位置敏感器、半导体激光器实现铁路钢轨磨耗自动检测的方法。

毛竹冬笋的笋体剖析及营养成分的测定

我国每年生产大量笋罐头出口，获得一定外汇，促进了笋加工业的发展。但外商对笋产品的要求非常严格，只要幼嫩的笋尖（占笋体重量的25％），还有75％的剩余物，造成了笋资源的严重浪费。本文着眼于当前笋罐头加工对原料利用的现状，将笋体分割成五部分（笋尖、笋中部、笋基部、嫩笋衣、老笋衣）。分别测定其营养成分。结果表明，笋体各部位均含有丰富的蛋白质、氨基酸和矿质元素，是很好的食物资源。为竹笋加工综合利用提供依据。

现场杆塔接地电阻和土壤电阻率测量存在问题及误差分析

介绍了杆塔接地电阻和土壤电阻率的测量原理和测量方法,针对安徽池州供电局的4条110kV输电线路杆塔接地电阻和土壤电阻率的测量误差,采用数据对比、理论计算的方法并配合电路模型,分析了杆塔接地电阻测量误差的产生原因。结果表明:杆塔接地电阻测量时,宜采用直线三级法;电流极的布线长度至少应达到接地网对角线的2倍;布线方向应尽量和塔体基座垂直;测量时应在晴朗天气下进行。

脉冲激光测距机性能综合测试技术

提出利用室外消光法与室内时序增益系数比检测相结合的方法进行激光测距机最大测程测试,利用精密光电延时与激光回波模拟技术相结合的方法实现对测距机测程范围、测距精度、选通范围及精度、距离分辨力等主要性能参数的室内模拟测试。对测试原理进行了论述,并对激光测距机的实验数据进行了分析。实验结果表明:利用所提出的综合测试技术可实现对脉冲激光测距机多个主要性能参数的准确测试,为客观评价激光测距机的性能提供了可靠的测量数据。

新型汽车悬架检测台建模与仿真

针对目前国际上普遍采用的谐振式汽车检测设备 ,建立了汽车不解体时悬架综合性能检测系统理论模型 ,并开发了系统仿真软件 .通过模拟检测分析 ,表明只需检测汽车作用于检测台的压力信号 ,就可以对汽车悬架性能进行有效检测 .

MIMO雷达比幅单脉冲测角精度分析

和差比幅单脉冲测角方法由于实现简单且测角精度高,在雷达系统中得到广泛应用。研究多输入多输出(multiple-input multiple-output,MIMO)雷达的比幅单脉冲测角技术及其精度问题,采用全微分方法详细推导了MIMO雷达和传统相控阵雷达的单脉冲测角精度,得到了准确的测角误差函数表达式。通过计算机仿真,验证了理论分析的正确性,并在相同信噪比条件下,对两种模式下的测角精度进行了比较。

基于SEA法的反导预警系统作战效能评估

对反导预警系统进行作战效能评估可以为预警装备体系的发展和作战运用提供基础,在对反导预警作战流程分析的基础上,选取了对反导预警系统作战效能影响较大的因素,给出了系统效能性能量度,分析了系统映射和使命映射,并运用SEA方法建立了效能评估的数学模型,结合仿真试验对反导预警系统保障反导拦截任务的作战效能进行了评估。