R-Factor Analysis of Data Based on Population Models Comprising R- and Q-Factors Leads to Biased Loading Estimates

Effects of performing an R-factor analysis of observed variables based on population models comprising R- and Q-factors were investigated. Although R-factor analysis of data based on a population model comprising R- and Q-factors is possible, this may lead to model error. Accordingly, loading estimates resulting from R-factor analysis of sample data drawn from a population based on a combination of R- and Q-factors will be biased. It was shown in a simulation study that a large amount of Q-factor variance induces an increase in the variation of R-factor loading estimates beyond the chance level. Tests of the multivariate kurtosis of observed variables are proposed as an indicator of possible Q-factor variance in observed variables as a prerequisite for R-factor analysis.

Overload problem research on aperiodic real-time tasks

In this paper, a novel scheduling mechanism is proposed to handle the real-time overload problem by maximizing the cumulative values of three types of tasks： the soft, the hard and the imprecise tasks. The simulation results show that the performance of our presented mechanism in this paper is greatly improved, much better than that of the other three mechanisms： earliest deadline first （EDF）, highest value first （HVF） and highest density first （HDF）, under the same conditions of all nominal loads and task type proportions.

Development of All-Weather and Real-Time Bottom-Mounted Monitor of Bed Load Quantity

Quantity of bed load is an important physical parameter in sediment transport research. Aiming at the difficulties in the bed load measurement, this paper develops a bottom-mounted monitor to measure the bed load transport rate by adopting the sedimentation pit method and resolving such key problems as weighing and desilting, which can achieve long-time, all-weather and real-time telemeasurement of the bed load transport rate of plain rivers, estuaries and coasts. Both laboratory and field tests show that this monitor is reasonable in design, stable in properties and convenient in measurement, and it can be used to monitor the bed load transport rate in practical projects.

Rapid quantification of semen hepatitis B virus DNA by real-time polymerase chain reaction

AIM： To examine the sensitivity and accuracy of real-time polymerase chain reaction （PCR） for the quantification of hepatitis B virus （HBV） DNA in semen. METHODS： Hepatitis B viral DNA was isolated from HBV carriers＇ semen and sera using phenol extraction method and QIAamp DNA blood mini kit （Qiagen, Germany）. HBV DNA was detected by conventional PCR and quantified by TaqMan technology-based real-time PCR （quantitative polymerase chain reaction （qPCR））. The detection threshold was 200 copies of HBV DNA for conventional PCR and 10 copies of HBV DNA for real time PCR per reaction. RESULTS： Both methods of phenol extraction and QIAamp DNA blood mini kit were suitable for isolating HBV DNA from semen. The value of the detection thresholds was 500 copies of HBV DNA per mL in the semen. The viral loads were 7.5×10^7 and 1.67×10^7 copies of HBV DNA per mL in two HBV infected patients＇ sera, while 2.14×10^5 and 3.02×10^5 copies of HBV DNA per mL in the semen. CONCLUSION： Real-time PCR is a more sensitive and accurate method to detect and quantify HBV DNA in the semen.

A STUDY ON THE ENSEMBLE FORECAST REAL-TIME CORRECTION METHOD

Using real-time correction technology for typhoons, this paper discusses real-time correction for forecasting the track of four typhoons during 2009 and 2010 in Japan, Beijing, Guangzhou, and Shanghai. It was determined that the short-time forecast effect was better than the original objective mode. By selecting four types of integration schemes after multiple mode path integration for those four objective modes, the forecast effect of the multi-mode path integration is better, on average, than any single model. Moreover, multi-mode ensemble forecasting has obvious advantages during the initial 36 h.

A Model Predictive Scheduling Algorithm inReal-Time Control Systems

Abstract-The ineffective utilization of power resources has attracted much attention in current years. This paper proposes a real-time distributed load scheduling algorithm considering constraints of power supply. Firstly, an objective function is designed based on the constraint, and a base load forecasting model is established when aggregating renewable generation and non-deferrable load into a power system, which aims to transform the problem of deferrable loads scheduling into a distributed optimal control problem. Then, to optimize the objective function, a real-time scheduling algorithm is presented to solve the proposed control problem. At every time step, the purpose is to minimize the variance of differences between power supply and aggregate load, which can thus ensure the effective utilization of power resources. Finally, simulation examples are provided to illustrate the effectiveness of the proposed algorithm.

Errors Prediction for Vector-to-Raster Conversion Based on Map Load and Cell Size

Vector-to-raster conversion is a process accompanied with errors.The errors are classified into predicted errors before rasterization and actual errors after that.Accurate prediction of the errors is beneficial to developing reasonable rasterization technical schemes and to making products of high quality.Analyzing and establishing a quantitative relationship between the error and its affecting factors is the key to error prediction.In this study,land cover data of China at a scale of 1:250 000 were taken as an example for analyzing the relationship between rasterization errors and the density of arc length(DA),the density of polygon(DP) and the size of grid cells(SG).Significant correlations were found between the errors and DA,DP and SG.The correlation coefficient(R2) of a model established based on samples collected in a small region(Beijing) reaches 0.95,and the value of R2 is equal to 0.91 while the model was validated with samples from the whole nation.On the other hand,the R2 of a model established based on nationwide samples reaches 0.96,and R2 is equal to 0.91 while it was validated with the samples in Beijing.These models depict well the relationships between rasterization errors and their affecting factors(DA,DP and SG).The analyzing method established in this study can be applied to effectively predicting rasterization errors in other cases as well.

Load-induced error identification of hydrostatic turntable and its influence on machining accuracy

In heavy duty machine tools, hydrostatic turntable is often used as a means for providing rotational motion and supporting workpiece, so the accuracy of turntable is crucial for part machining. In order to analyze the influence of load-indcued errors on machining accuracy, an identification model of load-induced errors based on the deformation caused by applied load of hydrostatic turntable of computerized numerical control(CNC) gantry milling heavy machine is proposed. Based on multi-body system theory and screw theory, the space machining accuracy model of heavy duty machine tool is established with consideration of identified load-induced errors. And then, the influence of load-induced errors on space machining accuracy and the roundness error of a milled hole is analyzed. The analysis results show that load-induced errors have a big influence on the roundness error of machined hole, especially when the center of the milled hole is far from that of hydrostatic turntable.

Day-Ahead Probabilistic Load Flow Analysis Considering Wind Power Forecast Error Correlation

Short-term power flow analysis has a significant influence on day-ahead generation schedule. This paper proposes a time series model and prediction error distribution model of wind power output. With the consideration of wind speed and wind power output forecast error’s correlation, the probabilistic distributions of transmission line flows during tomorrow’s 96 time intervals are obtained using cumulants combined Gram-Charlier expansion method. The probability density function and cumulative distribution function of transmission lines on each time interval could provide scheduling planners with more accurate and comprehensive information. Simulation in IEEE 39-bus system demonstrates effectiveness of the proposed model and algorithm.

Disintegration of uncertainties associated with real-time multi-satellite precipitation products in diverse topographic and climatic area in Pakistan

Satellite-based Precipitation Estimates(SPEs)have gained importance due to enhanced spatial and temporal resolution,particularly in Indus basin,where raingauge network has fewer observation stations and drainage area is laying in many countries.Formulation of SPEs is based on indirect mechanism,therefore,assessment and correction of associated uncertainties is required.In the present study,disintegration of uncertainties associated with four prominent real time SPEs,IMERG,TMPA,CMORPH and PERSIANN has been conducted at grid level,regional scale,and summarized in terms of regions as well as whole study area basis.The bias has been disintegrated into hit,missed,false biases,and Root Mean Square Error(RMSE)into systematic and random errors.A comparison among gauge-and satellite-based precipitation estimates at annual scale,showed promising result,encouraging use of real time SPEs in the study area.On grid basis,at daily scale,from box plots,the median values of total bias(-0.5 to 0.5 mm)of the used SPEs were also encouraging although some under/over estimations were noted in terms of hit bias(-0.15 to 0.05 mm/day).Relatively higher values of missed(0.3 to 0.5 mm/day)and false(0.5 to 0.7 mm/day)biases were observed.The detected average daily RMSE,systematic errors,and random errors were also comparatively higher.Regional-scale spatial distribution of uncertainties revealed lower values of uncertainties in plain areas,depicting the better performance of satellite-based products in these areas.However,in areas of high altitude(>4000 m),due to complex topography and climatic conditions(orographic precipitation and glaciated peaks)higher values of biases and errors were observed.Topographic barriers and point scale gauge data could also be a cause of poor performance of SPEs in these areas,where precipitation is more on ridges and less in valleys where gauge stations are usually located.Precipitation system’s size and intensity can also be a reason of higher biases,because Microwave Imager underestimate precipitation in small systems(<200 km^(2))and overestimate in large systems(>2000 km^(2)).At present,use of bias correction techniques at daily time scale is compulsory to utilize real time SPEs in estimation of floods in the study area.Inter comparison of satellite products indicated that IMERG gave better results than the others with the lowest values of systematic errors,missed and false biases.

Contact analysis and load distribution of double-envelop hourglass worm gearing affected by errors and load

An approach for the contact analysis and load distribution of double-envelop hourglass worm gearing is presented, which is based on a 3-D elastic contact finite element method (FEM) model that accommodates the influence of errors and load. As compared with existing tooth contact analysis model that assumes rigidity for the contacting surfaces, the proposed model provides a more realistic analysis on the contact patterns, the distribution of contact load and transmission errors. It is also capable of exploring the influence of different errors on meshing performances, the contact deformation, the shift of the contact zone and load share among the meshing tooth-pairs under different load.

Real-Time Operation of Microgrids

Microgrid (MG) systems effectively integrate a generation mix of solar, wind, and other renewable energy resources. The intermittent nature of renewable resources and the unpredictable weather conditions contribute largely to the unreliability of microgrid real-time operation. This paper investigates the behavior of microgrid for different intermittent scenarios of photovoltaic generation in real-time. Reactive power coordination control and load shedding mechanisms are used for reliable operation and are implemented using OPAL-RT simulator integrated with Matlab. In an islanded MG, load shedding can be an effective mechanism to maintain generation-load balance. The microgrid of the German Jordanian University (GJU) is used for illustration. The results show that reactive power coordination control not only stabilizes the MG operation in real-time but also reduces power losses on transmission lines. The results also show that the power losses at some substations are reduced by a range of 6% - 9.8%.

“数形结合”——测量及不确定度教学模式的改革与研究

理解测量的不确定度是大学物理实验课程一项重要的教学目标。在大学物理实验绪论课中,准备了两个版本的不确定性教学方式:即有无测量数据的图形化展示。课程结束后,对学生进行测试,研究数据的图形化展示是否能够提高学生对不确定度的理解。结果表明,有图形展示的班级学生比没有图形展示的班级学生得分更高。图形表示有助于数据的可视化,在进行测量数据分析时减少了学生的认知负荷,因此应该在教学中积极推广使用。

考虑加载历史的小半径曲线桥梁梁轨相互作用分析

目前,大部分考虑加载历史的梁轨相互作用研究都集中在直线桥梁上,针对曲线桥梁,尤其是小半径曲线桥梁,梁轨相互作用的研究相对较少。采用理想弹塑性滞回阻力模型模拟扣件纵向阻力,运用有限元软件,建立以城东特大桥为研究对象的钢轨-桥梁-墩台三维有限元空间力学计算模型,研究曲线半径对于梁轨相互作用的影响,探究了多荷载耦合作用、往复荷载作用以及循环荷载作用下考虑加载历史效应的曲线桥梁梁轨相互作用情况,并提出“拉力百分比”以及“压力百分比”的概念以便分析曲线半径对传统线性叠加法误差的影响。结果表明,曲线桥梁中梁轨纵、横向相互作用分别与曲线半径成正、反比,相关数据改变幅度与曲线半径成反比且当曲线半径超过800 m时基本收敛,此时可采用“以直代曲”的简化算法;曲线半径对于横向梁轨相互作用影响程度大于纵向,相较于挠曲、制动工况,伸缩工况受曲线半径影响更加显著;多荷载耦合作用下,采用传统线性叠加法相较于考虑加载历史更为保守且温度荷载起主要贡献;考虑加载历史时钢轨在往复荷载作用下会产生不可忽视的残余内力,且在循环荷载作用下将会产生收敛于第1次往复荷载下的残余内力,这是扣件纵向阻力的弹塑性滞回特性决定的;线性叠加法误差与曲线半径具有相关性,相较于挠曲、制动工况,伸缩工况下对其更为敏感。研究结果可为考虑加载历史下曲线桥梁结构设计提供参考。

基于误差幅空特性分析的空间负荷预测误差评价方法

对空间负荷预测误差进行有效评价是客观认识预测结果,指导预测结果合理应用的前提。然而,现有空间负荷预测误差评价的研究存在对误差的空间分布不考虑或考虑不充分导致评价不准确的问题。为此,提出一种基于误差幅空特性分析的空间负荷预测误差评价方法。首先,从空间负荷预测误差幅值大小和空间分布对电网规划影响的角度出发,对误差的幅空特性进行详细分析;其次,利用运输问题的数学模型来表征正负误差的幅空抵消特性,使用各空间邻近度–幅值误差值曲线与x轴围成面积之和来表征剩余未抵消误差的幅空叠加特性;然后,分别通过伏格尔法和各梯形面积累加公式来计算正负误差的幅空抵消影响值和剩余未抵消误差的幅空叠加影响值,并在此基础上构建空间负荷预测误差评价指标;最后,基于误差对电网规划的实际影响给出对误差评价指标性能的检验方法。算例分析表明,与传统方法相比,该文所提误差评价方法从幅值和空间两个维度实现了对空间负荷预测误差更为全面的评估,与误差对电网规划影响的实际情况贴近度更高。

齿轮传动误差峰峰值最小化的拓扑修形优化研究

为了满足齿轮传动系统低噪声、小振动和高传动精度等要求,提出了一种基于传动误差峰峰值最小化的齿轮拓扑修形优化方法。基于直线与抛物线的复合修形叠加曲线,在标准渐开线齿轮的齿廓和齿向方向对齿轮进行修形设计,提出一种拓扑修形齿面形成方法;以齿轮传动误差峰峰值最小为优化目标,基于遗传算法对提出的拓扑修形齿轮齿面进行参数优化,得出拓扑修形齿轮齿面的最佳修形参数;将拓扑修形齿轮和标准齿轮进行对比,分析修形前后齿轮的齿面受载情况和齿根应力分布情况,验证了提出的拓扑修形优化方法的有效性。

基于位错运动的弹簧应力松弛方程应用研究

评价弹簧的强压处理工艺、预测弹簧的贮存寿命和载荷损失具有重要的工程意义。本文对圆柱螺旋压缩弹簧进行应力松弛试验,利用基于位错运动的应力松弛方程对加速试验数据进行拟合分析,提出评价弹簧强压处理效果的方法,并对应力松弛方程进行线性化处理,导出弹簧寿命预测方程和载荷预测方程,给出计算载荷损失误差的方法,预测圆柱螺旋压缩弹簧的寿命和载荷损失,并对其进行试验验证。结果表明:本文提出的弹簧应力松弛方程效果较好,载荷损失预测误差在±2%以内。

机器视觉系统中光源位移误差分析与优化

为了采集多类型工况的图像,扩大神经网络的学习样本。改变光源的高度能显著影响图像的差异,为此对影响光源位移准确度的步进电机和驱动结构进行误差分析并提出对应的优化补偿方法。经由对四台步进电机所需负载分析研究,建立负载模型,优化负载驱动电路。针对传动结构中轴心定位误差以及丝杆应力的干扰分别设计优化方案并完成对整体方案的验证。实验表明优化方法能有效地减小装置误差,四组传动丝杆的定位精度分别提升了88.896%、98.336%、45.081%、31.479%,优化效果明显,为图像采集提供位移精度保证。

考虑齿形误差影响的摆线针轮承载特性分析

针对缺乏考虑齿形误差的承载分析软件,导致分析结果不符合实际工程状况的问题,提出了1种包含摆线轮齿形误差的摆线针轮副承载特性分析方法。利用三次非均匀B样条准确描述出包含齿形误差的摆线轮实际齿廓,构建并分析了摆线针轮误差齿廓接触分析模型(error tooth contact analysis,E-TCA),得到了初始啮合位置参数及啮合间隙。在此基础上,建立了齿形误差影响下的摆线针轮副负载接触分析模型,确定了零部件多体接触之间的力矩平衡和变形协调关系,利用能量最低原理获取了真实承载特性。通过有限元模型验证了RV-40E型号减速器的摆线针轮承载特性。结果表明:由于齿形误差的影响,啮合齿数减少了1对,啮合应力和传动误差增大了5.3%和5.7%。

基于现代试验设计的风洞天平校准方法

风洞天平的校准精度直接决定了风洞试验的气动载荷测量精度,为了提升天平校准的质量和效率,以BCS-100天平校准系统为研究对象,基于现代试验设计方法(modern design of experiments,MDOE)开展了风洞天平校准研究。针对单因子变量法(one factor at a time,OFAT)天平校准中存在系统误差与响应量耦合的问题,采用MDOE的随机、重复和分块策略控制校准的系统误差,并选定响应面理论的中心复合设计方法生成校准矩阵。校准矩阵共计86个样本点,包括64个分级因子点、12个轴向因子点和10个中心因子点,其中所有样本点的加载顺序做随机化处理,并作为一个样本块在短时间内集中完成加载,中心因子点则用于满足重复原则。最后开展了OFAT和MDOE的对比校准,拟合载荷的残差正态概率分布显示MDOE校准中横侧向分量的样本点独立性更强,样本点残差最高可降低84%;检验载荷显示MDOE和OFAT两种方法中天平所有分量的综合加载重复性持平,MDOE校准中横侧向分量的综合加载误差最高可降低54%。研究表明MDOE能够有效降低校准的系统误差,提升横侧向小量的预测能力。