碳酸钠浸取-紫外荧光光谱法测定地质样品中痕量铀     

刘金巍  王彦丽  杨金荣  罗治定  刘庆学 《岩矿测试》2007,26(2):160-162

地质样品经HF—HNO3-HCl-HClO4溶解后，用50g／L碳酸钠溶液浸取分离，采用紫外荧光光谱法直接测定上清液的铀含量。浸取时间选择30min，Fe、Zn、Ca、Co、Ni、Cu和Mn等元素留在残渣中不产生干扰。方法精密度（RSD，n=12）为3．37％～7．06％，检出限为0．009μg／g（进样量100μL）。方法参加区域地球化学考核样品的测试，合格率100％，适用于土壤、水系沉积物、岩石及Fe、Zn、Ca、Co、M、Cu和Mn含量较高的样品中痕量铀的测定。  相似文献   

大陆深钻超高压变质岩中可溶有机质的提取研究   总被引：5，自引：0，他引：5  

饶竹 杨柳罗立强  詹秀春方家虎 《岩石矿物学杂志》2006,25(3):257-260

目前可溶有机质的研究大多集中在沉积岩中。研究超高压变质岩中有机质有助于探索和研究超高压这种极端地质条件下有机质的来源、分布、保存和演化等一系列问题。由于大陆深钻超高压变质岩中可溶有机质含量非常低，为防止泥浆、钻井液及碎样、提取、分析等过程带来污染，尽可能获取岩心样品原始的有机质信息，提高样品可溶有机质的提取效率，本文采用超声-试剂、超声-有机试剂等清洗手段消除可能污染，利用索氏抽提、超声抽提等连续抽提的方法提高抽提效率，并与可能存在的污染物类型进行对比研究，确保岩心抽提有机物为样品原始有机物，为进一步研究超高压变质岩中可溶有机质的赋存状态提供前提保证。  相似文献   

泡沫塑料富集-石墨炉原子吸收光谱法测定地质样品中微量铊   总被引：2，自引：0，他引：2  

林光西周泳德  周康明 《岩矿测试》2006,25(4):377-380

采用HF-HClO4-HNO3-HCl溶解样品，泡沫塑料富集-石墨炉原子吸收光谱法测定岩石、土壤、水系沉积物等地质样品中微量铊。以抗坏血酸为基体改进剂，Fe^3＋加入量选择100mg，灰化温度为600℃，原子化温度为1600℃。方法用于测定国家一级标准物质，结果与标准值基本一致。方法精密度（RSD，n=8）为2．88％～6．27％，回收率为95．24％～101．3％，检出限可达0．058μg/g。  相似文献   

磁参数测量装置的设计原理及操作     

MA Shu-yan WANG Xi-chen YU Hui-min College of GeoExploration Science  Technology  Jilin University  Changchun  China 《吉林大学学报(地球科学版)》2006,(Z2)

利用高精度磁测仪器,采用高斯第一位置测定磁性标本。使标本架上倾斜板面垂直于地磁场T_0的磁力线,使标本的中心与探头中心等高,根据标本磁性的强弱,可调节标本与探头的距离(不小于15 cm)。根据上述原理设计并制造了磁参数测量装置.与MP—4高精度磁力仪配套使用,大大提高了磁性参数的准确度。  相似文献   

Elicited Data and Incorporation of Expert Opinion for Statistical Inference in Spatial Studies     

Subhash R. Lele  Abhik Das 《Mathematical Geology》2000,32(4):465-487

Spatial data are often sparse by nature. However, in many instances, information may exist in the form of soft data, such as expert opinion. Scientists in the field often have a good understanding of the phenomenon under study and may be able to provide valuable information on its likely behavior. It is thus useful to have a sensible mechanism that incorporates expert opinion in inference. The Bayesian paradigm suffers from an inherent subjectivity that is unacceptable to many scientists. Aside from this philosophical problem, elicitation of prior distributions is a difficult task. Moreover, an intentionally misleading expert can have substantial influence on Bayesian inference. In our experience, eliciting data is much more natural to the experts than eliciting prior distributions on the parameters of a probability model that is a purely statistical construct. In this paper we elicit data, i.e., guess values for the realization of the process, from the experts. Utilizing a hierarchical modeling framework, we combine elicited data and actual observed data for inferential purposes. A distinguishing feature of this approach is that even an intentionally misleading expert proves to be useful. Theoretical results and simulations illustrate that incorporating expert opinion via elicited data substantially improves the estimation, prediction, and design aspects of statistical inference for spatial data.  相似文献   

大地电磁法数据的采集及质量分析   总被引：2，自引：0，他引：2  

赵理芳  吴健生 《矿产与地质》2004,18(4):393-396

由于大地电磁测深法勘探的轻便和有效，其作为深层构造研究的重要手段越来越受到重视。以V5-2000大地电磁测深仪为例，阐述了大地电磁数据的野外采集过程和影响MT数据质量的一些因素以及提高数据丰富质量的措施。  相似文献   

原子荧光光谱法测定地质样品中的痕量锗   总被引：7，自引：1，他引：7  

肖灵张培新  胡月华 《岩矿测试》2004,23(3):231-234

分析了溶矿过程中HNO3、H2SO4、HClO4、H3PO4等对Ge的影响，采用AgNO3滤气装置消除气相干扰，测定了地质样品中的痕量锗，方法检出限为0．06μg／g，用土壤国家一级标准物质GBW 07401～GBW 07408验证方法，结果与标准值相符，其相对标准偏差(RSD，n=12)为3．66％～6．11％。  相似文献   

应用于静力触探中串行控制的数据采集系统     

张洋  张晓培  盛俭 《吉林大学学报(地球科学版)》2004,(Z1)

设计了应用于静力触探中的数据采集系统,给出了系统电路原理图并主要介绍了MAX132芯片及它的软件算法。该系统以AT89C2051单片机为控制核心,主要采用可编程的±18位串行A/D转换器MAX132进行数据采集并转换,通过RS232串行通信接口与上位机进行异步串行通信。  相似文献   

Comparative performance of convolutional neural network,weighted and conventional support vector machine and random forest for classifying tree species using hyperspectral and photogrammetric data     

C. Sothe  C. M. De Almeida  M. B. Schimalski  L. E. C. La Rosa  J. D. B. Castro  R. Q. Feitosa 《地理信息系统科学与遥感》2020,57(3):369-394

ABSTRACT

The classification of tree species can significantly benefit from high spatial and spectral information acquired by unmanned aerial vehicles (UAVs) associated with advanced classification methods. This study investigated the following topics concerning the classification of 16 tree species in two subtropical forest fragments of Southern Brazil: i) the potential integration of UAV-borne hyperspectral images with 3D information derived from their photogrammetric point cloud (PPC); ii) the performance of two machine learning methods (support vector machine – SVM and random forest – RF) when employing different datasets at a pixel and individual tree crown (ITC) levels; iii) the potential of two methods for dealing with the imbalanced sample set problem: a new weighted SVM (wSVM) approach, which attributes different weights to each sample and class, and a deep learning classifier (convolutional neural network – CNN), associated with a previous step to balance the sample set; and finally, iv) the potential of this last classifier for tree species classification as compared to the above mentioned machine learning methods. Results showed that the inclusion of the PPC features to the hyperspectral data provided a great accuracy increase in tree species classification results when conventional machine learning methods were applied, between 13 and 17% depending on the classifier and the study area characteristics. When using the PPC features and the canopy height model (CHM), associated with the majority vote (MV) rule, the SVM, wSVM and RF classifiers reached accuracies similar to the CNN, which outperformed these classifiers for both areas when considering the pixel-based classifications (overall accuracy of 84.4% in Area 1, and 74.95% in Area 2). The CNN was between 22% and 26% more accurate than the SVM and RF when only the hyperspectral bands were employed. The wSVM provided a slight increase in accuracy not only for some lesser represented classes, but also some major classes in Area 2. While conventional machine learning methods are faster, they demonstrated to be less stable to changes in datasets, depending on prior segmentation and hand-engineered features to reach similar accuracies to those attained by the CNN. To date, CNNs have been barely explored for the classification of tree species, and CNN-based classifications in the literature have not dealt with hyperspectral data specifically focusing on tropical environments. This paper thus presents innovative strategies for classifying tree species in subtropical forest areas at a refined legend level, integrating UAV-borne 2D hyperspectral and 3D photogrammetric data and relying on both deep and conventional machine learning approaches.  相似文献   

悬浮液进样石墨炉原子吸收光谱法测定地质样品中痕量镓和铊   总被引：5，自引：7，他引：5  

张佩瑜  彭红卫 《岩矿测试》1994,13(2):96-100

对固体悬浮液直接进样及石墨炉原子吸收光谱法测定Ｇａ和Ｔｌ进行了研究，拟定了以琼脂为悬浮剂，Ｎｉ（对Ｇａ）和Ｖ（对Ｔｌ）为基体改进剂，标准溶液进行校准的、灵敏、快速、准确测定Ｇａ和Ｔｌ的方法。在选定条件下，测得Ｇａ和Ｔｌ的特征量（１％吸收）分别为２．８×１０￣（－１１）ｇ和４．４×１０￣（－１１）ｇ，检出限（３σ）分别为２４ｐｇ和２８ｐｇ，相对标准偏差分别为６．３％（含Ｇａ６．４ｇ／ｇ，ｎ＝１１）和４．８％（含Ｔｌ１．０ｇ／ｇ，ｎ＝１３）。方法适用于地质样品中低至０．１ｇ／ｇＧａ和Ｔｌ的测定。  相似文献