基于近红外光谱技术定量分析导热油的研究

导热油在设备热传递领域应用广泛,但目前市场上导热油的品质良莠不齐,优质导热油掺杂劣质导热油会导致一系列安全问题。常用的导热油鉴定手段耗时长,检测复杂。本实验借助近红外光谱技术结合偏最小二乘回归法(Partial Least Squares Regression,PLSR)用于鉴定导热油品质。结果表明:鉴定导热油品质的模型,经标准正态变量(standard normal variate,SNV)预处理后的定量分析模型的拟合程度最佳,预测相关系数(regression coefficient of prediction,Rp)达到0.9999,预测均方根误差(the root mean square error of prediction,RMSEP)小于0.02。因此,近红外光谱技术结合PLSR可为导热油的品质鉴定提供一种快速、便捷的方法。     

导热油在太阳能中高温热利用中的研究现状

介绍了导热油的分类、性质和选择导热油的要求,其中导热油的换热性能对系统的设计和安全运行有着重要影响,并对导热油的强化换热研究进行了介绍。综述了复合抛物面聚光器(CPC)、抛物面槽式集热器(PTC)、菲涅尔聚光器(LFR)三种中高温太阳能集热器的研究进展,并对导热油系统及应用进行了综合分析,展望了导热油在太阳能中高温热利用中的研究方向。     

基于NIR的茶叶成分检测仪的设计与实现

本文提出了基于近红外光谱的荼叶成份检测仪的设计与实现.该检测仪采用干涉滤光片作为分光器件,其旋转样品池内嵌了漫反射标准白板,以实现快速交替检测样品及白板漫反射信号,使样品与白板的检测同步完成,简化仪器机械结构,提高了光谱稳定性和样品检测速度与精度.光电信号检测系统采用了InGaAs光电探测器,利用仪表放大器和24位A/D转换器分别完成信号调理和数据采集,以USB 2.0实现仪器与计算机的数据传输,再由计算机化学计量学软件完成吸光度计算及茶叶样品的成分分析.实验结果表明,本样机实测茶叶成份值与理化检验值的相对误差小于5%.     

主成分分析法在多元质量控制中的应用

提出以多元统计方法中的主成分分析法解决大型企业中的多元质量控制问题。阐明了主成分分析法的原理，在观测变量为正态分布的假设下，论述了Q—Q图、主成分质量椭圆图以及T^2控制图的原理及构造方法。通过化妆品公司的实例说明了主成分分析法的两个作用：一是发现异常值，二是进行质量稳定性控制。     

导热油在工业换热过程中的应用

在工业换热过程中．除非采用热源(冷源)直接对工艺介质进行加热(冷却)的换热方式，一般均采用中间传热介质在热源(冷源)和工艺介质之间作为媒介进行换热。这种通过中间介质进行换热的方式称为间接换热．间接换热的最大优点是可在换热过程中对被加热的工艺介质进行精确的温控。有利于实现工艺过程的有效控制和产品及其质量的精细化。而实现间接换热方式最大优点的关键是在热源(冷源)的工作方式和工艺需求之间找到一种适合的中间传热介质。     

近红外光谱技术在土壤成分检测中的研究进展

近红外光谱技术(NIRS)是一种快速的例行分析方法,在土壤科学领域内具有广阔的应用前景。本文评述了近红外光谱分析技术在土壤成分检测中的应用,并指出了其在土壤领域内的发展方向。     

导热油代替间接蒸汽加热的研究与应用

在清香花生油生产实践中,介绍了作者针对蒸炒锅间接蒸汽加热存在弊端及原因分析,通过精心设计、科学论证,将蒸炒锅改为导热油代替间接蒸汽加热,经过使用并不断完善,节能降耗效果显著,节约燃煤35％,提高炒料温度,提升油品香味和品质,为企业增加经济效益和社会效益。     

主成分分析法在清水河健康评估体系指标筛选中的应用

1．引言河湖水系是地表水资源的主要载体,是维系生态系统健康的重要因子,也是哺育人类历史文明的摇篮。在大规模经济开发和全球气候变化双重作用下,一些河流、湖泊出现不同程度地恶化,形态、结构、水文条件变化,生境退化及重要或敏感水生生物消失等问题l。主成分分析也称主分量分析法,旨在利用降维的思想,把多指标转化为少数几个综合指标,是系统工程处理定性与定量相结合的简单易行且行之有效的一种系统分析方法。通过对现有指标的统计分析,提取出可以最大程度上代表和说明主体状况的指标,从而达到通过用较少指标得到全面结果的目的。     

基于样本选择的光谱重构研究

目的为了提高使用主成分分析法重构光谱反射率的重构精度。方法利用Matlab进行仿真实验,选择3种不同色卡作为训练样本,使用主成分分析法探究主成分个数和样本间隔对重构结果的影响。结果主成分个数为4时,贡献率均超过99%;样本间隔为10 nm时,RC24色卡重构效果最好,其平均色差2.37ΔE_(ab)~*平均均方根误差为0.0185。结论训练样本的选择会影响光谱重构精度,RC24色卡具有数据量小、重建精度较高的特点,在颜色复制领域可以优先选择。     

类加权主成分分析在企业物流绩效评价中的应用

以企业物流绩效为研究对象,建立了一种较全面的二层次指标体系,综合考虑了财务、客户、市场、业务以及学习等各方面的绩效指标,并将上层指标看作是下层指标的指标类.利用层次分析法确定全体指标和每个指标类的权重系数,并对指标进行主成分分析,求得主成分;对标准化指标进行加权处理,同时考虑指标类的权重,建立了类加权主成分评价模型.通过一个示例对企业物流绩效进行评价,并将评价结果分别与主成分分析和加权主成分分析进行了比较.该模型将层次分析法的主观分析与主成分分析法的客观分析相结合,不仅考虑了全体指标的重要程度,而且考虑了物流绩效指标类的重要度差异,更加符合客观实际.     

近红外光谱法快速预测烟梗中常规化学成分的研究

采用近红外光谱法对烟梗中常规化学成分进行快速预测,其相对误差较小,预测能力和稳定性较好,具备推广价值。     

Wavelet neural network (WNN) approach for calibration model building based on gasoline near infrared (NIR) spectra

In this paper we have compared the abilities of two types of artificial neural networks (ANN): multilayer perceptron (MLP) and wavelet neural network (WNN) — for prediction of three gasoline properties (density, benzene content and ethanol content). Three sets of near infrared (NIR) spectra (285, 285 and 375 gasoline spectra) were used for calibration models building. Cross-validation errors and structures of optimized MLP and WNN were compared for each sample set. Four different transfer functions (Morlet wavelet and Gaussian derivative – for WNN; logistic and hyperbolic tangent – for MLP) were also compared. Wavelet neural network was found to be more effective and robust than multilayer perceptron.     

The application of direct orthogonal signal correction for linear and non-linear multivariate calibration

Traditionally, the direct orthogonal signal correction (DOSC) is always used together with a latent variable method such as partial least square (PLS) or principal component regression (PCR), to build a linear calibration model. In this study, PLS and least square support vector machine (LSSVM) were used to develop the linear and non-linear relation between spectra and components, respectively. DOSC was used to preprocess the input data, and the effect of DOSC pretreatment on linear and non-linear calibration model was investigated. The experiment was performed with three data sets. The first one was the acousto-optic tunable filter near infrared (AOTF-NIR) spectra of apples, the second one was the temperature-induced spectra of a ternary mixture of ethanol, water and 2-propanol, and the third one was the NIR spectra of corn. For all of the applications, the relation between spectra and components can be clearly observed in the spectra plot or the score plot after DOSC pretreatment. DOSC improved the predictive ability of PLS model. However, DOSC removed useful non-linear information that was related to components, thus, was not able to improve the performance of LSSVM model. DOSC pretreatment seems to be not suitable for non-linear calibration.     

近红外技术应用于成品卷烟的内在质量稳定性控制

以某品牌卷烟为例,采用傅立叶变换近红外光谱技术采集成品卷烟的近红外光谱,结合连续流动法测定样品中还原糖、烟碱、氯、钾含量的数据,采用偏最小二乘法(PLS)分别建立了预测品牌卷烟烟丝中还原糖、烟碱、氯、钾及糖碱比、钾氯比的近红外模型,模型的相关系数(除钾外)都在0.95以上。用建立的模型快速检测红狼卷烟的各化学成分,通过值的波动范围初步监控成品的质量稳定性。并采集它们的近红外光谱,应用连续小波变换(CWT)对原始光谱进行预处理,再对CWT系数进行主成分分析(PCA),在PCA分析的基础上引入马氏距离算法建立成品卷烟质量稳定性评价模型。通过研究光谱预处理对卷烟样品分类鉴别的影响,确定马氏距离阈值Dthro,结合近红外定量测定值与马氏距离阈值Dthro,对卷烟产品质量稳定性进行评价和控制。     

Degradation evaluation of ethylene-propylene-diene monomer (EPDM) rubber in artificial weathering environment by principal component analysis

Artificial weathering tests on ethylene-propylene-diene monomer (EPDM) containing 5-ethylidene-2-norbornene (ENB) as diene were conducted in a xenon lamp light exposure and weathering equipment for different time periods. Principal component analysis (PCA) was used to evaluate the 12 degradation parameters of EPDM including surface properties, crosslink density and mechanical properties. The results showed that the combined evaluating parameter Z of EPDM degradation increased quickly in the first 12 days of exposure and then leveled off. After 45 days, it began to increase rapidly again. Among the 12 degradation parameters, the crosslink density is strongly associated with tensile stress at 300% elongation and tear strength. The surface tension is also well correlated with the color aberration.     

Metal-doped (Ti, WC) diamond-like-carbon coatings: Reactions with extreme-pressure oil additives under tribological and static conditions

In contrast to non-doped diamond-like-carbon (DLC) coatings, reliable chemical evidence of the reactions between metal-doped DLC coatings and oil additives under tribological conditions using state-of-the-art surface-sensitive chemical analyses is still scarce. In this study we have investigated the reactivity of metal-doped (Ti, WC) DLC coatings with the extreme-pressure (EP) dialkyl dithiophosphate additive — without the presence of a steel counter body in the contact that befogs the actual coating reactions. Static “reactivity” experiments without any tribological or mechanical effects were also performed to provide a further insight into the lubrication mechanisms. The results confirmed the chemical reactions between the EP additive and all the DLC coatings, as well as their oxidation during the tribological contacts. We measured an about 10-times higher chemical activity (a 25-fold P/S ratio increase) for the Ti-doped DLC compared to the WC-doped or non-doped DLC, which also agrees with it having the lowest amount of wear in this study. We suggest that the Ti-DLC boundary lubrication is achieved via binding sites at the O vacancies present in the Ti-doped DLC coating. The data also clearly show, in contrast to most of literature reports, that even though small, some direct chemical activity between the W-DLC and the dialkyl dithiophosphate EP additive is also possible without any iron catalytic effect. However, the chemical changes were significantly smaller, also allowing coating graphitization, which might be one of the reasons for the 50% higher wear of the WC-doped compared to the Ti-doped DLC.     

基于RBF网络和NIRS的绿茶水分含量分析模型

基于径向基函数(RBF)和反向传播(BP)神经网络分别建立了绿茶水分含量的近红外光谱分析模型.结果表明:RBF网络预测模型的相关系数r(p)=0.933,预测标准误RMSEP=0.528%;BP网络预测模型的相关系数r(p)=0.914,预测标准误RMSEP=0.598%.RBF网络模型优于BP网络模型.     

A procedure to facilitate the choice of the number of factors in multi-way data analysis applied to the natural samples: Application to monitoring the thermal degradation of oils using front-face fluorescence spectroscopy

Multi-way data analysis techniques are becoming ever more widely used to extract information from data, such as 3D excitation-emission fluorescence spectra, that are structured in (hyper-) cubic arrays. Parallel Factor Analysis (PARAFAC) is very commonly applied to resolve 3D-fluorescence data and to recover the signals corresponding to the various fluorescent constituents of the sample. The choice of the appropriate number of factors to use in PARAFAC is one of the crucial steps in the analysis. When the signals in the data come from a relatively small number of easily distinguished constituents, the choice of the appropriate number of factors is usually easy and the mathematical diagnostic tools such as the Core Consistency, in general give good results. However, when the data is from a set of natural samples, the core consistency may not be a good indicator for the choice of the appropriate number of factors.In this work, Multi-way Principal Component Analysis (MPCA) and the Durbin-Watson criterion (DW) are utilized to choose the number of factors to use in PARAFAC decomposition. This is demonstrated in a case where 3D-front-face fluorescence spectroscopy is used to monitor of the evolution of naturally occurring and neo-formed fluorescent components in oils during thermal treatment.     

The formation of a SiOx interfacial layer on low-k SiOCH materials fabricated in ULSI application

The characterizations of SiOCH films using oxygen plasma treatment depends linearly on the O₂/CO flow rate ratio. According to the results of Fourier transform infrared spectroscopy (FTIR) and X-ray photoelectron spectroscopy (XPS) analyses, it was found that the carbon composition decreases with increasing O₂/CO flow rate ratio, because more carbon in the Si–O–C and Si–CH₃ bonds on the film surface would be converted by oxygen radicals. It was believed that the oxygen plasma could oxidize the SiOCH films and form a SiO_x interfacial capping layer without much porosity. Moreover, the result of FTIR analysis revealed that there was no water absorbed on the film. A SiO₂-like capping layer formed at the SiOCH film by the O₂/CO flow rate ratio of 0.75 had nearly the same dielectric properties from the result of capacitance–voltage (C–V) measurement in our research.     

基于PCA-SVMR快速测定复方氯丙那林和对乙酰氨基酚

基于主成分分析-支持向量机回归(PCA-SVMR)方法,利用近红外光谱技术研究了复方氯丙那林和复方对乙酰氨基酚两种模型制剂有效组分的快速同时测定,建立了它们的多元校正模型,并以传统的稳健方法偏最小二乘回归(PLSR)为基础考察了PCA-SVMR方法对于小样本药物体系的拟合能力、预测能力和模型稳定性。研究表明,PLSR的预测能力必须以强拟合能力为前提,PCA-SVMR则没有这样的要求,使前者对校正样本的依赖性远强于后者,从而在小样本药物体系中前者的稳定性大大弱于后者,该两种药物制剂的PCA-SVMR多元校正模型的测定准确度总体上优于PLSR。