Estimation of the daily global solar radiation; Nepal experience

This work focuses on estimation of global solar radiation and, in particular, it explores the effect of precipitation and temperature on solar radiation profile of Kathmandu (Nepal). An accurate knowledge of solar radiation distribution in each particular geographical location is crucial for the promotion of solar energy technology. The best way of knowing the amount of global solar radiation is to install quality instruments at many locations in the given region. This requires their day to day maintenance, recording and calibration, which is very costly in developing countries like Nepal. Thus, the alternative approach is to correlate meteorological measurements with appropriate models and investigate the key parameters. For the research activities the RadEst program has been used. It includes, for evaluating the daily global solar radiation values at a given latitudes, four models which estimate the atmospheric transmissivity by measurements of daily temperature range and precipitations. The model parameters are fitted in 2 years data by iterative procedures. The values obtained by these models are, then, compared with measured radiation data. The paper reports graphical and statistical evaluations suggesting that among the four models, the Modular DCBB is the best model for Kathmandu area. This result is useful for designing solar panels able to maximize the harvesting of solar energy and to reduce the chronic shortage of hydrocarbon fuel that Nepal imports in a significant amount each year.     

基于LS-SVM的一次风机振动在线监测及故障预警研究

针对火电厂一次风机运行工况复杂和多状态变量强耦合特性而难以构建设备精确模型问题,将智能数据挖掘方法应用于风机设备故障预警和诊断中。通过对风机典型运行特性进行分析,提出了一种基于最小二乘支持向量机(LS-SVM)的一次风机振动状态估计和故障预警方法。结合山西河曲发电厂1号机组的1#一次风机历史运行数据,应用Matlab对所提出的方法进行了验证和分析。研究结果表明,该预测方法有较高的估计精度,能够及时辨别一次风机在运行中的振动异常,适用于火电厂辅机设备的故障诊断,具有一定的工程应用价值。     

非线性控制系统的支持向量机辨识建模研究

针对非线性控制系统辨识建模难的问题,系统研究了基于支持向量机的非线性控制系统的辨识建模理论和方法,然后利用回归支持向量机(Support Vector Regression,SVR)设计了一个非线性控制系统的辨识建模系统.仿真试验结果表明,SVR具有很高的建模精度和较强的泛化能力,从而验证了该辨识方法的有效性和先进性.     

基于大气透过率比例校正的目标辐射测量

大气透过率是影响目标辐射测量精度的重要因素,而常规通过MODTRAN等模式计算软件,由大气参数计算大气透过率的误差一般在15％以上,极大地限制了目标辐射测量精度.为此,本文提出利用某一距离的实测大气透过率和模式计算大气透过率之比得到大气过率校正系数来对其它距离的模式计算大气透过率进行比例校正.实验显示,校正后大气透过率的精度优于8.1％,大大提高了目标辐射测量精度.利用中波红外相机和面源黑体开展了目标辐射特性测量实验,结果表明,采用MODTRAN计算大气透过率的辐射测量方法得到的目标辐射反演精度约为20％,而采用本文方法对大气透过率校正后可将反演精度提高到10％以内.     

基于支持向量回归的小尺寸零件精密测量

为提高小尺寸零件测量精度和速度,提出了基于支持向量回归(SVR)的小尺寸零件精密测量方法。系统以齿形链板为研究对象,对其主要参数进行测量。系统采用透射照明方式,使用A102FCCD数字摄像头采集齿形链板的图像,经过IEEE1394数字接口卡传输到计算机。对含有噪声的原始数字图像实施中值滤波降噪、二值化,轮廓提取及图像旋转等处理,使图像转变成易于检测的单像素宽边缘信息。然后根据齿形链板长度与宽度比例确定待检测区域,以待检测区域内的边缘轮廓上的各像素点构成对应线段的训练集,进行支持向量回归,获得具有亚像素表示的各检测线段的回归函数,并据此对齿形链板的主要参数进行测量。最后,对测量误差进行了分析。测量结果满足零件的公差要求,测量精度可达2 μm。理论分析及实验结果表明,该方法测量速度快,测量精度高,同时对图像平面内旋转、尺度变化、噪声等具有较强的鲁棒性。     

A least squares support vector machine model for prediction of the next day solar insolation for effective use of PV systems

Accurate prediction of daily solar insolation has been one of the most important issues of solar engineering. The amount of solar insolation on a given location is a vital data for photovoltaic plants. Systems efficiency is easily affected by the changes in solar radiation so, this study is aimed to develop a Least Squares Support Vector Machine (LS-SVM) based intelligent model to predict the next day’s solar insolation for taking measures. Daily temperature and insolation data measured by Turkish State Meteorological Service for three years (2000–2002) were used as training data and the values of 2003 used as testing data. Numbers of the days from 1st January, daily mean temperature, daily maximum temperature, sunshine duration and the solar insolation of the day before parameters have been used as inputs to predict the daily solar insolation. The simulations were carried out with SVM Toolbox of MATLAB software. As a conclusion the results show that LS-SVM is a good method in estimating the amount of solar insolation of a given location with 99.294% accuracy.     

面向IP模式测控系统的PLSR-SBR双层压缩

针对以太网测控网络存在数据冲突导致系统实时性、可靠性降低问题,提出了基于偏最小二乘回归(PLSR)SBR的双层压缩方法。第一层建立主参量与所有辅助参量的确定模型,利用压缩有效性指标确定主成分,完成主参量的信息压缩。第二层基于改进的SBR,通过选取辅助参量中的基础序列,建立基础信号;在满足拟合误差条件下,逐步将每一个辅助参量序列映射到基础信号上,完成对辅助参量的数据压缩。该方法重点解决辅助参量和主参量中的解释潜变量和反映潜变量相关程度最大、基础信号由最少基础序列组成、辅助参量实现最小变长分解个数及基础信号独立更新原则等关键问题。最后将该方法应用于IP模式乙醇浓度测控系统。实验结果表明,在IP模式测控系统同时具有主参量和辅助参量,且不同参量间存在相关性时,该方法可在允许拟合相对误差为5%的情况下,使压缩率达到68%以上,从而有效地降低以太网测控网络数据冲突程度。     

基于力矩的尺寸实时测量方法的研究

采用视觉检测技术,利用工件图像轮廓上各像素点相对质心力矩的大小,基于力学原理提出了一种区域质心算法,可以对孔类工件的内径实现精确的在线检测.     

基于光辐射压力的激光功率测量技术

随着激光应用领域的快速拓展,超高峰值功率、超窄脉宽逐渐成为未来激光行业的重点研究方向之一,这种激光的超高电场能量给高精度的激光功率测量提出了挑战。传统的激光功率测量方法,如光电法、热释电法、量热法等逐渐显露出不适用于上述激光功率测量的缺点,此外上述方法都难以实现实时、在线测量。为了克服以上困难,需要一种新型激光功率测量原理与方法。以美国国家标准与技术研究院为代表的机构提出了一种光辐射压力测量法,该方法使激光作用在高反射率的反射镜上,激光动量形成了光辐射压力,这个力可以采用多种力学传感方式进行计量。该方法不但能实现激光功率快速、准确测量,而且不影响激光能量传输,可以实现实时、在线的激光功率测量。系统回顾了国内外通过光辐射压力测量激光功率的基本原理和系统组成,光辐射压力测量激光功率的研究现状,并对该方法的发展方向进行了展望。     

基于卡尔曼预测的差动共焦轮廓跟踪测量方法

针对轴向扫描式差动共焦测量法(ASDCM)测量轮廓效率低下问题,提出一种基于卡尔曼预测的差动共焦轮廓跟踪测量方法。该方法使用激光差动共焦轴向响应曲线数百纳米量程的线性区间实现了表面连续轮廓高精度线性传感测量,提高了测量效率;同时引入基于卡尔曼预测器的轮廓跟踪原理利用已测轮廓点数据对未测表面预测并跟踪,扩展了线性传感轮廓测量法测量范围。实验结果表明,该方法相对于ASDCM法测量效率提升了8倍,且实现了轮廓PV值大于线性传感测量范围的标准椭圆柱高精度跟踪测量,激光聚变靶丸内轮廓圆度重复测量标准差达3 nm。为精密元器件表面连续轮廓的高精度、快速、无损测量提供了一种高质量方法。     

基于波长积分双色法的小视场快速温度场测量

激光退火技术有热预算低、瞬间温度高的特点,其温度场特性是材料电学性能的重要表征参数.准确实时测量瞬态小温度场对整体退火工艺过程的把控具有重要的参考价值.辐射测温法通过收集样品辐射光谱中特定波段的能量来实现温度的非接触在线测量,具有响应快、测温范围宽等特点.提出了一种基于InGaAs红外光电二极管的双色辐射测温系统设计方...     

Innovation based two-interval overlap test for failure prediction in measurement systems

An approach to predict failure in the measurement system is developed. Proposed approach uses confidence and tolerance intervals for the innovation of Kalman filter and it is based on the criterion of overlapping these intervals whereby it allows the detection of potential failures in the system. The proposed failure prediction method is well suited to realize detection of constant shifting and slowly varied failures, such as distortion in measuring instruments and gyroscope axes shifting in navigation systems. The method is simple and permits to solve the problem of failure prediction in the measurement system under the conditions of its practical operation.     

基于粒子群算法优化支持向量机的数控机床状态预测

数控机床状态预测对于及时发觉数控机床健康状况有着非常重要的作用.为了实现数控机床状态的准确预测,提出采用粒子群算法优化支持向量机(PSO-SVM)进行数控机床状态预测方法,其中粒子群算法用于确定支持向量机(SVM)中的训练参数,以得到优化的SVM 预测模型.试验结果表明,用PSO-SVM对数控机床状态进行预测,不仅所需样本少,而且具有很好的预测精度.     

基于大气实时修正的飞机辐射特性测量

研究了飞机飞行时的动态辐射特性测量方法。针对利用软件计算大气透过率进行目标辐射修正精度较低的问题,提出了通过机上标校黑体进行实时大气修正的新辐射测量方法。该方法通过目标飞机上挂载的标校黑体实现大气透过率的实时测量,并利用实测大气透过率对目标飞机辐射进行大气修正来提高修正精度。借助中波和长波红外相机、两个标准面源黑体及一块硒化锌平板,开展了飞机目标辐射特性测量的地面模拟实验。利用MODTRAN和CART计算以及实测大气透过率分别对黑体目标红外测量值进行辐射反演。与MODTRAN和CART计算大气透过率的传统方法相比,文中提出的实测大气透过率方法可将目标辐射反演精度提高一倍以上。     

A regression model for prediction of pipe conveyor belt contact forces on idler rolls

The paper presents design and verification of regression models for prediction of pipe conveyor belt contact forces on idler rolls. Their advantage is in the fact that they have been created according to the real experimental measurement. The obtained models correspond with real operational conditions. The concept of the experimental rig at the Technical University of Košice is designed so that it represents 8 m long section of pipe conveyor. The conveyor belt is an object with action of tension force and at the same time it takes the initiative in the contact force formation. Several criteria have been used to verify the presented regression models. The tensioning force 9000, 12,000 and 15,000 N have MPE of prediction error less than 5%. About 120,000 measured values have been processed during the evaluations which correspond to approximately 15,000 results from experimental measurements.     

A new design approach for solar concentrating parabolic dish based on optimized flexible petals

Large parabolic dish concentrator mirrors are an important component of many solar energy systems. They need to be relatively precise and are expensive to fabricate and to transport. Here, a new concept for designing and fabricating large parabolic dish mirrors is presented. The dish mirror is formed from several optimal-shaped thin flat metal petals with highly reflective surfaces. Attached to the rear surface of the mirror petals are several thin layers whose shapes are optimized to have reflective petals form into a parabola when their ends are pulled toward each other by cables or rods. An analytical model to optimize the shape and thickness of the petals is presented. The validity of the concept is demonstrated using Finite Element Analysis and laboratory experiments. The concept would permit flat mirror elements to be easily fabricated and efficiently packaged for shipping to field sites where they can be assembled into the parabolic dish concentrators. The concept has the potential to provide precision solar parabolic solar collectors at a substantially lower cost than conventional methods.     

An integrated method for measurement of diamond tools based on AFM

The measurement and evaluation technology of high precision diamond tools is critically important for supporting the ultra-precision machining. In practical cutting process, the edge profile quality of the diamond tool, including sharpness, micro defects, roughness and tip arc waviness, greatly affects the cutting quality. It is very difficult to measure and evaluate the diamond tool edge profile due to the high precision of tool edge profile and complexity of various measurement parameters. In this paper, an integrated method for measurement and characterization of diamond tools is proposed, which is based on an Atomic Force Microscope (AFM) module. Multiple technical indexes of diamond tools are obtained and validated based on the presented research and cutting experiments, and the evaluation model for each technical index is also proposed. The integrated measurement equipment, including an AFM, precision adjustment device and aerostatic bearings, has been established based on the accuracy requirement of measurement parameters. The edge sharpness, micro defects, surface roughness and tip arc waviness have been obtained based on the evaluation model and experimental data. The experimental results show that the measurement accuracy meets the requirements of the comprehensive evaluation of the diamond tool edge profile. The research work will also contribute to the development of ultra-precision machine.     

一种基于振动信号处理的颤振预报方案研究

针对切削过程中产生的颤振现象,通过对机床的在线监测,将采样出的振动加速度信号进行数据处理,提出一种以方差和互相关系数作为综合判据的方法来判别颤振是否发生,并在MATLAB环境下仿真证明该方法的可行性。     

High accurate squareness measurement squareness method for ultra-precision machine based on error separation

Traditional measurement methods of squareness for ultra-precision motion stage have many limitations, especially the errors caused by the inaccuracy of standard specimens. On the basis of error separation, this paper presents a novel method to measure squareness with an optical square brick. The angles between the guideways and the four lines of brick section are measured based on the fact that sum of interior angle of a quadrilateral is 2π, and the squareness is obtained. A squareness measurement experiment was performed on a profilometer with a modified optical square brick. Experimental results show that the squareness accuracy between X and Y axes is not influenced by the accuracy of brick, and the measurement repeatability reaches 0.22 arcsec. Finally, a verification experiment to the proposed method was carried out with a high accurate standard specimen, and the error between the two methods is 1.06 arcsec. According to the error results and simulation analysis of the measurement system, the measurement error based on error separation is 0.06 arcsec. The proposed method is able to achieve a very high accurate squareness measurement with auxiliary components of normal accuracy, and can be applied to measure the accuracy class of sub-arcsec squareness.     

基于子空间域对抗判别网络的不同型号滚动轴承剩余寿命预测

针对不同型号滚动轴承因结构尺寸、运行工况等差异导致轴承退化数据分布和特征尺度不一致,引起剩余寿命预测精 度下降的问题,提出基于子空间域对抗判别网络的不同型号滚动轴承剩余寿命预测方法。 首先,通过高效通道注意力机制提升 特征提取器各通道中重要特征的权重,自适应获取不同型号滚动轴承的深层性能退化特征,并以此预训练标签预测器;然后,在 对抗判别网络框架上将域判别器与特征提取器对抗训练,最小化源域和目标域在表征子空间上的正交基距离,利用表征子空间 正交基不受特征缩放影响的性质克服特征尺度变化过大引起的回归性能下降问题,实现不同型号滚动轴承间的域自适应;最 后,利用训练好的特征提取器提取待预测轴承退化特征,输入标签预测器得到剩余寿命。 在 PRONOSTIA、XJTU-SY 和自测数据 集上进行了验证,实验结果表明所提方法能充分学习源域特征分布信息,有效克服不同型号下的特征尺度差异,相比其他域自 适应方法效果提升 20% 至 40% 。