地基CE312热红外辐射计定标方法分析与评价

地基CE312热红外辐射计用于星载传感器的定标,其定标精度直接影响热红外传感器的场地定标精度。文章论述CE312-1b带宽辐亮度定标法和分谱辐亮度定标法的定标原理,利用实验室黑体对CE312-1b热红外辐射计进行定标,最后利用2010年8月青海湖的野外实测数据结合MODIS观测值,分析对比两种定标方法所得定标结果的准确性及误差来源。结果表明,带宽辐亮度定标法得到的CE312热红外辐射计定标系数相对分谱辐亮度定标法所得结果在准确性、适用性方面表现更好。     

嫦娥一号干涉成像光谱仪(IIM)2C级数据信息提取

通过分析Chang’E-1卫星所获取的高光谱数据的太阳高度角因素,选取了太阳高度角较高的IIM2C数据进行光谱定标。采用邻域平均法及邻域加权均值法对原始数据进行了杂点、条带修复。由于干涉成像光谱仪CCD阵列增益畸变以及它的自身问题使得干涉影像存在横向响应不均一性,提出采用基于子空间最大特征值法进行校正,结果影像亮度统计其强度表现均一,符合自然图像特征,并采用自编程序进行几何校正。运用国际上较为成熟的经验线性法对Chang’E-1IIM 2C数据进行绝对定标;与此同时,为了修正线性定标的偏置系数及降低数据噪声,首次采用自适应小波变换法对辐射定标后数据进行后处理,确定了IIM2C数据可用波段。通过对比国际标准定标点数据,制订了嫦娥IIM2C数据分析方案,完成了第一幅完整的Chang’E-1IIM 2C月球正面反射率影像。     

便携式近红外光谱仪的苹果糖度模型温度修正

样品温度对近红外光谱有很大影响,在近红外技术评价水果品质的实际应用时,需要修正温度变化对模型预测结果的影响。便携式近红外光谱仪采集不同温度下(0～30℃)苹果的漫透射光谱,采用二阶导数和卷积平滑进行预处理。选取20℃下代表性样本的光谱数据,建立基准PLS模型。斜率/偏差法分别计算苹果糖度PLS模型在0,10和30℃下的修正方程。分析结果表明:斜率/偏差法对0,10和30℃下外部样本预测结果进行修正,预测精度得到显著提高,其修正前后的Q值分别为0.525cv 0.810,0.680cv0.822,0.669cv 0.802。温度修正模型可以有效提高预测精度,也扩展了近红外仪器的适用性,为自主研发便携式近红外光谱仪提供参考。     

热流计校准装置自适应温度控制方法研究

以热流计校准装置为研究对象,建立了热板温度仿真模型。根据模糊控制原理和BP神经网络原理,分别设计了模糊PID控制器和BP神经网络PID控制器,并在Matlab的Simulink下进行了不同控制方法的仿真对比实验。仿真结果表明:模糊PID有更快的响应速度、更短的稳定时间,BP神经网络PID有更小的超调量。     

基于X射线衍射仪的X光晶体本征参量的标定

X光晶体本征参量的实验标定是准确鉴定X光晶体种类和品质,研制各种类型晶体谱仪,X光线谱定量测量和高分辨X光单能成像的基础.基于X射线衍射仪,通过制作平面晶体样品架,采取控制X射线管电源、滤波片选取和厚度控制等措施,极大地抑制了Cu-KJ3及韧致辐射,使X射线管光源Cu-Kα单能化,提出了用滤片作为光源单能化的判据.对X光线谱测量中常用的X光分光晶体季戊四醇[PET(002)]的晶格常量2d和Cu-Ka能点的积分衍射效率R.进行了标定方法研究,其标定值分别为(0.87425±0.00042)nm和(1.759±0.024)×10-4 Rad.基于X射线衍射仪的X光晶体本征参量的精密实验标定方法既快速高效,且十分方便和灵活.通过更换衍射仪的X射线管靶材,采取类似方法,可以标定其它能点的晶体积分衍射效率,可为X光晶体的本征参量库提供更多的标定数据.     

维生素B2片中维生素B2的测定及稳定性

以pH=7.0的水作为溶液,激发、发射波长分别为443、523nm,运用荧光光谱法测定了维生素B₂的荧光强度,以荧光强度与浓度的关系作图,得到了回归曲线,本实验条件下,在5×10^-8—6×10^-7g/mL范围内呈良好的线性关系,回收率在98.53%—103.59%之间,该方法具有灵敏度高、重现性和稳定性好的特点,但维生素B₂不稳定。     

The Calibration Problem in Statistics and Its Application to Chemistry

Abstract

Most linear regression problems involving prediction or estimation require determining the Y value corresponding to a given X. The calibration problem (or inverse estimation or discrimination) is the inverse of the above situation in that we have a given value of Y and we want to determine X. This paper will document the various statistical approaches to this problem and do a numerical example using the classical estimator.     

Determination of [13C-15N] Labeled Methylxanthines by Gas Chromatography-Atomic Emission Detection (GC-AED) and Compound-Independent Calibration

ABSTRACT

Compound independent calibration (CIC) can be used to measure stable isotopically labeled molecules and their metabolites. This study was designed to demonstrate that gas chromatography coupled to atomic emission detection and CIC are useful analytical tools for the specific and quantitative determination of ¹³C and ¹⁵N labeled caffeine and its metabolites. These labeled compounds can be measured by monitoring either ¹³C or ¹⁵N atomic emission lines and using only one calibration function from one of the analytes. This method can be helpful when it is difficult or impossible to obtain an authentic reference material, which is often the case in metabolic studies.     

Treatment of Model Error in Calibration by Robust and Fuzzy Procedures

Abstract

In every mathematical (e.g., statistical) procedure and theorem used in calibration, several conditions need to be fulfilled. What can analysts and chemometricians do, however, if the conditions are only nearly fulfilled? One can expect that small changes in the conditions yield only small changes in the results. This article shows how to treat two types of model error caused by assuming an incorrect error distribution or relationship (i.e., linear). The procedures applied are based on robust statistics and fuzzy theory, respectively.     

Subspace Regression Ensemble Method Based on Variable Clustering for Near-Infrared Spectroscopic Calibration

Abstract

An ensemble approach, based on the combination of multiple linear regressions in subspace and variable clustering and therefore named VCS-MLR, was proposed for near-infrared spectroscopy (NIRS) calibration. By an experiment involving the determination of five components in tobacco samples, it was shown that VCS-MLR improved the performance by 61.4, 23.3, 10.2, 20.5, and 18, respectively, with respect to partial least squares regression (PLSR). The results confirmed that VCS-MLR can result in a more accurate calibration model but without the increase of computational burden. Moreover, the superiority of VCS-MLR was highlighted for small sample problems.