适合近红外光谱数据特征的降维方法对比分析

因近红外光谱具有波长点多、谱带归属困难、光谱重叠严重及光谱分布结构未知等问题,在进行近红外光谱关键特征提取和数据特征空间映射时难以准确获知合适降维方法。为了解决该问题,本文对比分析了典型线性和非线性降维方法 ,并用烟叶近红外光谱数据从数据降维可视化和分类准确性识别率角度分别进行了实验验证。结果表明,线性降维算法,特别是PCA、LDA算法,比较适合应用于烟叶近红外光谱降维分析中,非线性降维算法因其泛化学习能力与推广能力差以及本征维数估计困难不适合应用于近红外光谱降维分析。     

二维相关红外光谱分析技术在"清开灵"注射剂热稳定性研究中的应用

运用傅里叶变换红外光谱法实时原位跟踪了中药复方“清开灵”注射剂的热稳定性，并采用二维相关分析技术编制程序进一步进行的谱图处理和分析。通过对一维光谱和二维相关光谱的比较研究表明：二维相关分析能提供更丰富的结构信息，提高了谱图的分辨率，并能捕捉到热力学过程中物质体系和分子结构的动态变化，为中药注射剂的质量控制提供了一种强有力的手段。     

基于近红外光谱的柴油凝点计算机软测量法

柴油是重要的石油化工产品,凝点是确定其品质的主要理化指标,但传统测定方法周期长、费用高,且易受人为的影响。本文提出一种用近红外光谱(NIRS)分析技术的柴油凝点软测量方法。先用多项式卷积为原始的柴油MR光谱数据作光谱平滑、基线校正和标准归一化;然后,利用主元分析(PCA)组合近红外光谱数据集的高维特征并向低维空间投影,降低输入维数,提高各维特征的敏感性;最后,用最小二乘支持向量机(LS-SVM)回归算法建立凝点的软测量模型。用一个含120个样本的401维柴油近红外全光谱数据集建模和检验,通过PCA后,全光谱数据集的特征降到了6维,并保留了99.6%的信息。进一步的实验表明,采用PCA提取特征做软测量建模的性能,要普遍优于直接作用在光谱波长域的方法。与BP、PCA BP及PCA SVM方法相比,所提方法建立的柴油凝点软测量模型测量精度更高,且与标准方法测量的结果更为接近,因此,又为柴油凝点的在线测定提供一种新方法。     

典型煤系岩石的可见-近红外光谱特征研究

为研究基于可见-近红外光谱技术的煤岩识别方法,从山西、山东4个煤矿收集了页岩、砂岩、灰岩三大类11种典型煤系岩石,测定了其可见-近红外波段(400～2 450nm)的反射光谱,分析了其矿物、元素组成对反射光谱特征的影响,获得了碳质物质含量对煤系页岩反射光谱曲线特征参数的影响规律。研究结果表明:①绝大多数煤系岩石的反射光谱曲线在可见光波段(400～780nm)和短波近红外波段(780～1 100nm)呈现出随波长增加的多重吸收谷。在长波近红外波段(1 100～2 450nm),明显的吸收谷主要集中在1 400,1 900,2 200,2 350nm波长,页岩、灰岩吸收谷的波长相对固定,而不同砂岩吸收谷的波长呈现出多种变化。②除碳质物质含量较高的碳质页岩外,同一煤矿各类煤系岩石与煤的可见-近红外波段反射光谱吸收特征差异明显。③当煤系页岩中碳质物质含量增大时,可见-近红外波段反射光谱曲线的光谱斜率和各明显吸收谷深度均呈先快速减小后趋于平缓的特点。     

FUDT在苹果近红外光谱分类中的应用

苹果的分类是苹果采收后商品化处理的重要环节。为了快速、无损和有效地实现苹果的分类,利用近红外光谱技术采集四种苹果的近红外反射光谱,用主成分分析对高维的近红外光谱进行降维处理,分别运行线性判别分析,二次判别分析,模糊非相关判别转换和Foley-Sammon判别分析提取鉴别信息,用k-近邻分类器进行分类。分类结果表明,模糊非相关判别转换能更好地提取苹果近红外光谱的品种鉴别信息,达到了最高的分类准确率。     

9个不同厂家的六味地黄丸红外光谱分析

采用一维红外光谱(FTIR)并结合二阶导数谱技术,对9个不同厂家的六味地黄丸进行了快速无损的鉴别研究。结果表明,它们在一维谱图上差别不显著,而在高分辨率的二阶导数谱中,它们之间具有明显的差异,可以达到类同制剂的鉴别和质量监控。结论:一维红外光谱和二阶导数谱相结合可快速有效地分析和鉴别不同厂家生产的六味地黄丸。六味地黄丸是否以熟地黄入药,将影响其药效与质量。若以生地黄入药,那么单糖含量少,在1020 cm~(-1)附近吸收峰弱,但氨基酸含量多,出现了3676 cm~(-1)吸收峰。此外,吸收峰777 cm~(-1)也可作为熟地黄含量的另1个重要指标。该方法快速、简便、直观、可靠,适用于药物的鉴定。     

NIRS结合PLS快速分析银黄颗粒中有效成分含量

研究旨在探讨利用银黄颗粒样品的近红外漫反射光谱(NIRS)信息,建立黄芩苷和绿原酸含量的校正模型,为银黄颗粒质量的快速评价提供1种新方法.以HPLC分析值为参照,采用近红外漫反射光谱技术采集100批银黄颗粒样品的近红外漫反射光谱,结合偏最小二乘法(PLS)建立了黄芩苷和绿原酸含量的校正模型.黄芩苷和绿原酸含量的校正模型相关系数(R2)分别为0.998和0.995,校正均方差(RMSEC)为0.578和0.123,内部交叉验证均方差(RMSECV)为2.356和0.412;经外部验证,预测相关系数(r)分别为0.995和0.984,预测均方差为(RMSEP)0.597和0.166.结果表明,该方法准确、简便、无污染,可实现大批量银黄颗粒样品的快速分析.     

基于近红外与高光谱技术的小麦种子多指标检测方法

采集47份小麦样本的高光谱图像,提取感兴趣区内的平均光谱,结合反映小麦品质的水分、蛋白质和湿面筋三个指标基础数据,通过OPUS软件搜寻最佳的光谱预处理和波段组合,分别建立了三个指标的偏最小二乘法(PLS)定量分析模型.同时与采用近红外(.NIR)光谱技术建立的三个指标的近红外模型进行比较,发现高光谱模型的各性能指标均明显优于近红外模型.结果表明:当被测样品为颗粒状且内部化学成分分布不均匀时,近红外模型的准确性和稳定性会受其测量条件的限制,而高光谱采样面积大,获取信息更全面,展现出强大的分析检测潜质,为小麦品质评价提供了新方法.     

谐波分析光谱角制图高光谱影像分类

目的 针对光谱角制图(SAM)分类算法对高光谱像元光谱曲线的局部特征和其辐射强度不敏感,而且易受噪声和维数灾难影响,致使分类效率低和精度较差等缺陷,将谐波分析(HA)技术引入到SAM高光谱影像分类中,提出一种基于谐波分析的光谱角制图(HA-SAM)高光谱影像分类算法.方法 利用HA技术将高光谱影像从光谱维变换到能量谱特征维空间,并提取低次谐波分量及特征系数(谐波余项、相位和振幅),用特征系数组成的向量代替光谱向量,对高光谱影像进行SAM分类.结果 将SAM和HA-SAM同时应用于EO-1卫星的Hyperion高光谱影像分类,通过对比和分析,验证了HA-SAM的优越性,再选择AVIRIS(airborne visible infrared imaging spectrometer)高光谱影像对HA-SAM进行验证,结果表明该算法具有较强的普适性.结论 HA-SAM提高了传统SAM高光谱影像分类的效率和精度,而且适用性较强具有良好的应用前景.     

基于混合卷积与三重注意力的高光谱图像分类网络

针对高光谱图像光谱维度高、现有网络无法提供深度级的多层次特征,从而影响分类精度和速度的问题。首先采用核主成分分析对高光谱图像进行降维,使降维后的数据具有最佳区分度,提出了一种基于混合卷积与三重注意力的卷积神经网络(hybrid convolutional neural network with triplet attention, HCTA-Net)模型,该模型设计了一种基于三维、二维和一维卷积的混合卷积神经网络,通过不同维度卷积神经网络的融合,提取高光谱图像精细的光谱–空间联合特征。在二维卷积中加入深度可分离卷积,减少了模型参数,同时引入三重注意力机制,使用三分支结构实现跨维度信息交互,抑制无用的特征信息。在Indian Pines、Salinas和Pavia University数据集上的实验结果表明,本文提出的模型优于其他对比方法,总体分类精度分别达到了99.16%、99.87%和99.76%。     

Heavy-baryon spectroscopy from lattice QCD

We use a four-dimensional lattice calculation of the full-QCD (quantum chromodynamics, the non-abelian gauge theory of the strong interactions of quarks and gluons) path integrals needed to determine the masses of the charmed and bottom baryons. In the charm sector, our results are in good agreement with experiment within our systematics, except for the spin-1/2 Ξcc, for which we found the isospin-averaged mass to be Ξcc to be . We predict the mass of the (isospin-averaged) spin-1/2 Ωcc to be . In the bottom sector, our results are also in agreement with experimental observations and other lattice calculations within our statistical and systematic errors. In particular, we find the mass of the Ωb to be consistent with the recent CDF measurement. We also predict the mass for the as yet unobserved to be 5955(27) MeV.     

Detection of gases by correlation spectroscopy

This paper describes the detection of various common gases by means of correlation spectroscopy, employing a complementary-source-modulation (CoSM) approach based on compact light-emitting diode (LED) sources. Theoretical results for the quantitative detection of O₂, CO, and CO₂ by this CoSM method are presented, using, as their basis, spectral absorption data from the Hitran database. In demonstrating the proposed detection principle, new experimental results for the detection of O₂ in air are presented, with the use of practical low-cost LED sources.     

Field spectroscopy of estuarine intertidal habitats

The recent introduction of portable, low‐cost hyperspectral radiometers for measuring the reflectance of marine intertidal habitats has considerable promise, first as a source of reference spectra for airborne and satellite remote sensing, and second as a survey technique in its own right. This paper reports on the results of an intercalibration exercise in which two designs of commercially available instruments were used to measure reflectance spectra across a diverse, intertidal site. The substrates sampled included seagrasses, macroalgae, and sediments which varied in wetness and grain size. Spectra were compared statistically using several measures of similarity, and the results showed a high degree of correlation between the measured reflectance spectra. There were no significant differences between instruments from different manufacturers in the shape of reflectance spectra, but the signal‐to‐noise ratio varied considerably between individual instruments. Spectra measured by operators with lesser experience in field spectrometry tended to be more variable than those of more experienced operators, indicating that training and adherence to set protocols are important when implementing this method in the field situation. Spatial plots derived from field spectra showed essentially the same trends in surface features as plots created using traditional sampling and remote sensing methods. Furthermore, the use of field spectrometry as a stand‐alone, low‐cost method for rapidly mapping the distribution of major habitat types was demonstrated by the results of a survey of a large intertidal sandbank.     

Review Article Principles of field spectroscopy

Abstract

Field spectroscopy involves the study of the interrelationships between the spectral characteristics of objects and their biophysical attributes in the field environment. It is a technique of fundamental importance in remote sensing, yet its full potential is rarely exploited. In this article the principles of the subject are explained and its historical development reviewed with reference to the instruments and methods adopted. Field spectroscopy has a role to play in at least three areas of remote sensing. Firstly, it acts as a ridge between laboratory measurements of spectral reflectance and the field situation and is thus useful in the calibration of airborne and satellite sensors. Secondly, it is useful in predicting the optimum spectral bands, viewing configuration and time to perform a particular remote sensing task. Thirdly, it provides a tool for the development, refinement and testing of models relating biophysical attributes to remotely-sensed data.     

一种集成式阻抗谱测量系统

针对传统阻抗测量仪器电路复杂、集成度低等问题,设计并实现了基于FPGA和AD5933的集成式阻抗谱测量系统.详细介绍了AD5933阻抗测量方法,FPGA系统架构及I2C IP Core工作机理.实验评估了系统的测量精度和信噪比等性能指标;通过对三元件生物阻抗模型的测量,进一步验证了系统测量的准确性.该系统具有体积小,功耗低,集成度高,抗干扰能力强,信噪比大于70 dB等特点,实现了阻抗谱测量系统的小型化.     

Mechanical stress measurements using micro-Raman spectroscopy

 The application of micro-Raman spectroscopy for measurements of mechanical stress in silicon microelectronics devices is discussed. The advantages and disadvantages of the technique are shown through different examples such as Si₃N₄ and metal lines, isolation structures and solder bumps.     

Machine vision system for automated spectroscopy

This paper describes a novel system based on the machine vision and machine learning techniques for fully automated, real-time identification of constituent elements in a sample specimen using laser-induced breakdown spectroscopy (LIBS) images. The proposed system is developed as a compact spectrum analyzer for rapid element detection using a commercially available video camera. We proposed a correlation-based pattern matching algorithm for analyzing single element spectra. However, the use of a high-speed laser and presence of numerous imperfections in the experimental setup require advanced techniques for analyzing multi-element spectra. We cast the element detection problem as a multi-label classification problem that uses support vector machines and artificial neural networks for multi-element classification. The proposed algorithms were evaluated using actual LIBS images. The machine learning approaches yielded correct identification of elements to an accuracy of 99%. Our system is useful in instances where a qualitative analysis is sufficient over a quantitative element analysis.     

工业混合酚的拉曼光谱分析

尝试以拉曼光谱直接对工业混合酚中甲酚及二甲酚定性定量分析。用乙腈在2251cm^-1的C≡N伸缩振动峰作为内标,间甲酚在732 cm^-1处、对甲酚在839 cm^-1处以及2,6-二甲酚在667 cm^-1处的苯环变形振动选用为以上各组分各自的特征峰。通过实验得到乙腈与间甲酚、对甲酚、2,6-二甲酚的背反射显微拉曼相对拉曼截面,分别是（■σ/■Ω）732cm^-1/（■σ/■Ω）2251cm^-1=1.8416、（■σ/■Ω）667cm^-1/（■σ/■Ω）2251cm^-1=0.8557。分别对实验室模拟样及工业混合酚进行拉曼定量分析得到的结果与其他分析方法一致。     

近红外光谱信号的优化处理

用实验室常规方法测定竹材样品的木质素含量,漫反射方式采集样品的近红外光谱信号,偏最小二乘法(PLS)和完全交互验证方式以建立毛竹木质素含量的定量分析模型。研究主成分数、建模谱区、求导和平滑预处理技术对定量分析模型的影响。结果表明,预处理技术压缩和恢复的近红外光谱信号效果良好,提高了模型的预测能力,优化近红外定量分析模型有重要参考价值。     

光声光谱法探测微量气体

介绍光声光谱气体传感器的发展及应用意义,根据气体光声效应讨论了光声气体传感器的工作原理,详细分析了多种不同结构传感器的原理及优缺点.重点讨论了常用一维管状光声腔体的光声理论,并给出了数学模拟模型.根据国内外的研究现状,分析了光声气体探测系统的重难点以及可能的解决方法,并讨论了光声传感向MEMS方向发展的原因及意义.