CN115791757A - A uranium content detection method based on plasma parameter correction of uranium signal intensity - Google Patents
A uranium content detection method based on plasma parameter correction of uranium signal intensity Download PDFInfo
- Publication number
- CN115791757A CN115791757A CN202211505485.0A CN202211505485A CN115791757A CN 115791757 A CN115791757 A CN 115791757A CN 202211505485 A CN202211505485 A CN 202211505485A CN 115791757 A CN115791757 A CN 115791757A
- Authority
- CN
- China
- Prior art keywords
- uranium
- signal intensity
- characteristic
- plasma
- spectrum
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 229910052770 Uranium Inorganic materials 0.000 title claims abstract description 154
- JFALSRSLKYAFGM-UHFFFAOYSA-N uranium(0) Chemical compound [U] JFALSRSLKYAFGM-UHFFFAOYSA-N 0.000 title claims abstract description 154
- 238000001514 detection method Methods 0.000 title claims abstract description 26
- 238000001228 spectrum Methods 0.000 claims abstract description 58
- 239000012141 concentrate Substances 0.000 claims abstract description 29
- 238000000034 method Methods 0.000 claims abstract description 26
- 238000002536 laser-induced breakdown spectroscopy Methods 0.000 claims abstract description 13
- 230000003595 spectral effect Effects 0.000 claims description 12
- 239000013307 optical fiber Substances 0.000 claims description 5
- 230000005284 excitation Effects 0.000 claims description 4
- 230000001681 protective effect Effects 0.000 claims description 4
- 230000003287 optical effect Effects 0.000 claims description 2
- 239000000284 extract Substances 0.000 abstract description 3
- 238000005516 engineering process Methods 0.000 description 10
- 238000004458 analytical method Methods 0.000 description 5
- 238000005259 measurement Methods 0.000 description 4
- 238000004448 titration Methods 0.000 description 4
- ZAASRHQPRFFWCS-UHFFFAOYSA-P diazanium;oxygen(2-);uranium Chemical compound [NH4+].[NH4+].[O-2].[O-2].[O-2].[O-2].[O-2].[O-2].[O-2].[U].[U] ZAASRHQPRFFWCS-UHFFFAOYSA-P 0.000 description 3
- 230000005855 radiation Effects 0.000 description 3
- 230000015556 catabolic process Effects 0.000 description 2
- 238000010586 diagram Methods 0.000 description 2
- 230000000694 effects Effects 0.000 description 2
- 238000000295 emission spectrum Methods 0.000 description 2
- 238000000605 extraction Methods 0.000 description 2
- 230000005251 gamma ray Effects 0.000 description 2
- 150000002500 ions Chemical class 0.000 description 2
- 238000005457 optimization Methods 0.000 description 2
- KMUONIBRACKNSN-UHFFFAOYSA-N potassium dichromate Chemical compound [K+].[K+].[O-][Cr](=O)(=O)O[Cr]([O-])(=O)=O KMUONIBRACKNSN-UHFFFAOYSA-N 0.000 description 2
- 230000035945 sensitivity Effects 0.000 description 2
- 238000004876 x-ray fluorescence Methods 0.000 description 2
- 238000001636 atomic emission spectroscopy Methods 0.000 description 1
- 238000001816 cooling Methods 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 235000003891 ferrous sulphate Nutrition 0.000 description 1
- 239000011790 ferrous sulphate Substances 0.000 description 1
- 238000009854 hydrometallurgy Methods 0.000 description 1
- BAUYGSIQEAFULO-UHFFFAOYSA-L iron(2+) sulfate (anhydrous) Chemical compound [Fe+2].[O-]S([O-])(=O)=O BAUYGSIQEAFULO-UHFFFAOYSA-L 0.000 description 1
- 229910000359 iron(II) sulfate Inorganic materials 0.000 description 1
- 238000004519 manufacturing process Methods 0.000 description 1
- 239000011159 matrix material Substances 0.000 description 1
- 230000003647 oxidation Effects 0.000 description 1
- 238000007254 oxidation reaction Methods 0.000 description 1
- 238000005293 physical law Methods 0.000 description 1
- 238000011002 quantification Methods 0.000 description 1
- 230000002285 radioactive effect Effects 0.000 description 1
- 239000002994 raw material Substances 0.000 description 1
- DGXTZMPQSMIFEC-UHFFFAOYSA-M sodium;4-anilinobenzenesulfonate Chemical compound [Na+].C1=CC(S(=O)(=O)[O-])=CC=C1NC1=CC=CC=C1 DGXTZMPQSMIFEC-UHFFFAOYSA-M 0.000 description 1
- 239000000126 substance Substances 0.000 description 1
- 230000007704 transition Effects 0.000 description 1
Images
Landscapes
- Investigating, Analyzing Materials By Fluorescence Or Luminescence (AREA)
Abstract
Description
技术领域technical field
本发明属于原子发射光谱测量领域的激光诱导击穿光谱检测技术领域,具体涉及一种基于等离子体参数修正铀信号强度的铀含量检测方法。The invention belongs to the technical field of laser-induced breakdown spectrum detection in the field of atomic emission spectrometry, and in particular relates to a method for detecting uranium content based on plasma parameter correction of uranium signal intensity.
背景技术Background technique
铀浓缩物(主要为重铀酸盐、八氧化三铀等)为我国最主要的铀水冶产品,是核工业中重要的原材料,对其铀含量进行快速准确测定,在产品交易及生产工艺控制中均具有十分重要的意义。目前,铀浓缩物中铀的测定主要采用硫酸亚铁还原/重铬酸钾氧化滴定法,该方法以二苯胺磺酸钠做指示剂滴定,操作过程复杂,自动化程度较低,分析时间长,并且滴定终点的判断受人为主观影响较大,结果的准确性不足。Uranium concentrates (mainly diuranate, U3O8, etc.) are the most important uranium hydrometallurgy products in my country and important raw materials in the nuclear industry. The rapid and accurate determination of uranium content in the product transaction and production process are very important in control. At present, the determination of uranium in uranium concentrates mainly adopts ferrous sulfate reduction/potassium dichromate oxidation titration method, which uses sodium diphenylamine sulfonate as indicator titration, the operation process is complicated, the degree of automation is low, and the analysis time is long. Moreover, the judgment of the titration end point is greatly influenced by human subjectivity, and the accuracy of the result is insufficient.
目前铀在线检测中使用的技术为X射线荧光技术、中子感生瞬发γ射线分析技术。其中,X射线荧光技术测量精度和灵敏度不高,还可能有辐射风险;中子感生瞬发γ射线分析技术存在投资大、辐射危害和放射源半衰期短的缺点。由于这些技术本身的缺点,所以并没有得到广泛的应用。因此需要一种精度高、并能实现快速检测的铀浓缩物中的铀含量检测技术。At present, the technologies used in online detection of uranium are X-ray fluorescence technology and neutron-induced prompt gamma-ray analysis technology. Among them, X-ray fluorescence technology has low measurement accuracy and sensitivity, and may also have radiation risks; neutron-induced prompt gamma-ray analysis technology has the disadvantages of large investment, radiation hazards, and short half-life of radioactive sources. Due to the shortcomings of these technologies, they have not been widely used. Therefore, there is a need for a detection technology for uranium content in uranium concentrates that has high precision and can realize rapid detection.
近年来,激光诱导击穿光谱技术(简称LIBS)由于具有高灵敏度、样品预处理简单、检测速度快和可实现多元素测量等优点,成为一种新的激光分析技术,在铀浓缩物中铀含量快速准确检测上有很大的应用潜力。但由于该技术受基体效应影响比较明显,目前的定标模型准确性不足。准确的定量测量是LIBS系统在铀浓缩物快速检测中发挥作用的前提和基础,而准确的提取铀峰信号强度是铀元素定量化的基础。在LIBS发射光谱中,由于铀元素属于重核元素,电子能级分布密集,跃迁特征谱线超过30万条,具有丰富的发射光谱,在铀含量较高的铀浓缩物中,极易出现谱峰重叠的情况,重叠的铀谱峰与背景噪声信号糅杂在一起,对铀光谱信号的准确提取带来了极大的困难。因此需要一种方法准确剔除铀光谱信号中的背景噪声,得到准确的铀信号强度,从而为提高LIBS技术检测铀浓缩物中铀含量的准确性奠定基础。In recent years, laser-induced breakdown spectroscopy (LIBS for short) has become a new laser analysis technology due to its advantages of high sensitivity, simple sample pretreatment, fast detection speed and multi-element measurement. It has great application potential for rapid and accurate detection of content. However, because the technology is significantly affected by the matrix effect, the current calibration model is not accurate enough. Accurate quantitative measurement is the premise and basis for the LIBS system to play a role in the rapid detection of uranium concentrates, and the accurate extraction of uranium peak signal intensity is the basis for the quantification of uranium elements. In the LIBS emission spectrum, because uranium is a heavy nuclear element, the electronic energy levels are densely distributed, and there are more than 300,000 transition characteristic lines, which have rich emission spectra. In the case of overlapping peaks, the overlapping uranium spectral peaks are mixed with background noise signals, which brings great difficulties to the accurate extraction of uranium spectral signals. Therefore, there is a need for a method to accurately remove the background noise in the uranium spectral signal to obtain an accurate uranium signal intensity, thereby laying a foundation for improving the accuracy of LIBS technology in detecting uranium content in uranium concentrates.
发明内容Contents of the invention
本发明针对目前LIBS对铀浓缩物中铀含量进行检测时,光谱中重叠铀峰与背景噪声融合在一起无法分开的缺点,提供了一种基于等离子体参数修正铀信号强度的铀含量检测方法,可在使用激光诱导等离子光谱系统上运用,解决了铀浓缩物中铀含量快速检测的问题。本发明基于等离子体光谱信号的物理规律,通过等离子体特征参数与光谱信号强度之间的内在关系,通过求解等离子体参数来提取信号强度。本发明方法综合利用了激光诱导等离子光谱的信息,而且便于在计算机快速实现,既可以进行快速分析,又可以提高测量精度。The present invention aims at the defect that overlapping uranium peaks and background noise in the spectrum cannot be separated when the current LIBS detects the uranium content in the uranium concentrate, and provides a uranium content detection method based on plasma parameters to correct the uranium signal intensity, It can be applied to a laser-induced plasma spectroscopic system, and solves the problem of rapid detection of uranium content in uranium concentrates. The invention is based on the physical law of the plasma spectrum signal, and extracts the signal intensity by solving the plasma parameter through the internal relationship between the plasma characteristic parameter and the spectrum signal intensity. The method of the invention comprehensively utilizes the information of the laser-induced plasma spectrum, and is convenient for rapid realization on a computer, which can not only perform rapid analysis, but also improve measurement accuracy.
本发明的技术方案如下:Technical scheme of the present invention is as follows:
一种基于等离子体参数修正铀信号强度的铀含量检测方法,包括以下步骤:A uranium content detection method for correcting uranium signal intensity based on plasma parameters, comprising the following steps:
步骤1:利用激光诱导击穿光谱系统对铀浓缩物标准样品进行光谱采集,得到铀浓缩物标准样品的激光诱导等离子体特征光谱;Step 1: Using the laser-induced breakdown spectroscopy system to collect the spectrum of the uranium concentrate standard sample to obtain the laser-induced plasma characteristic spectrum of the uranium concentrate standard sample;
步骤2:从特征光谱中得到铀元素的特征谱峰强度;Step 2: Obtain the characteristic spectrum peak intensity of uranium element from characteristic spectrum;
步骤3:基于等离子体特征光谱修正铀特征谱峰强度;Step 3: Correcting the peak intensity of the uranium characteristic spectrum based on the plasma characteristic spectrum;
步骤4:建立铀浓缩物标准样品中铀元素含量与铀特征峰信号强度的定标模型;Step 4: Establish a calibration model for the content of uranium element in the standard sample of uranium concentrate and the signal intensity of the characteristic peak of uranium;
步骤5:对未知浓度的待测样品重复步骤1~步骤3操作,然后利用步骤4中定标模型反算出待测样品中铀元素含量。Step 5: Repeat
步骤2中,首先通过光谱仪采集铀特征谱峰信号强度I1,然后采集背景的信号强度IB。In
步骤2中,铀特征谱峰信号强度I1是采集的原始光谱扣除暗电流背景后的信号强度,背景的信号强度IB是所选取的铀特征谱峰对应波段范围内连续光谱的强度。In
步骤2中,铀特征谱峰信号和背景信号选取相同的信号长度。In
步骤3中,以I=I1-k IB得到修正后的铀特征峰信号强度I。In
步骤3中,k值确定方式为:In
筛选铀的多条特征谱线,在玻尔兹曼平面法公式中,修正后的铀特征峰信号强度I与相应能级Ek具有线性关系,由于I1与IB已知,因此通过不断优化k值,直至I与相应能级Ek相关性最优,即拟合线性R2最大;确定k值后,即得到修正后的铀特征峰信号强度I;Multiple characteristic spectral lines of uranium are screened. In the Boltzmann plane method formula, the corrected signal intensity I of the characteristic peak of uranium has a linear relationship with the corresponding energy level E k . Since I 1 and I B are known, so through continuous Optimize the k value until the correlation between I and the corresponding energy level E k is optimal, that is, the fitting linearity R2 is the largest; after determining the k value, the corrected signal intensity I of the characteristic peak of uranium is obtained;
能级Ek可从《原子数据库》中查阅。The energy level E k can be consulted from the "atomic database".
所述的k最大取值为1,最小取值为0。The maximum value of said k is 1, and the minimum value is 0.
步骤3中,选取九条铀一阶离子线用于玻尔兹曼平面法确定k值,其波长分别为409.013纳米、414.122纳米、415.541纳米、417.159纳米、424.166纳米、424.437纳米、434.169纳米、447.233纳米、454.362纳米。In
步骤4中,用修正后的铀特征峰信号强度I与铀浓缩物标准样品中已知铀元素含量建立标准曲线定标模型。In
步骤1中,以脉冲激光器为激发光源,从脉冲激光器出射的激光经过聚焦透镜聚焦后作用于定标样品表面,在聚焦点产生等离子体,等离子体在保护气体的氛围中进行冷却,产生的辐射光信号通过采集透镜进入光纤,并经过光谱仪处理后转化成电信号被计算机采集,得到铀浓缩物标准样品的激光诱导等离子体特征光谱。In
本发明的显著效果在于:Remarkable effect of the present invention is:
(1)相较于传统的化学滴定铀含量检测方法,本发明方法可以快速检测铀浓缩物样品中的铀含量。(1) Compared with the traditional method for detecting uranium content by chemical titration, the method of the present invention can quickly detect the uranium content in uranium concentrate samples.
(2)本发明方法能够准确剔除铀光谱信号中的背景噪声,提取到准确的铀特征光谱强度,解决了目前铀浓缩物样品中LIBS光谱中重叠铀峰与背景噪声融合在一起无法分开的问题,极大地提高了检测准确度。(2) The method of the present invention can accurately remove the background noise in the uranium spectral signal, extract the accurate characteristic spectral intensity of uranium, and solve the problem that the overlapping uranium peaks in the LIBS spectrum in the current uranium concentrate sample cannot be separated from the background noise. , greatly improving the detection accuracy.
附图说明Description of drawings
图1为实施例中铀浓缩物激光诱导击穿光谱检测示意图;Fig. 1 is the schematic diagram of laser-induced breakdown spectrum detection of uranium concentrate in the embodiment;
图2为实施例中波尔兹曼平面法k值优化对相关性系数R2的影响;Fig. 2 is the impact of Boltzmann plane method k value optimization on correlation coefficient R in the embodiment;
图中:1脉冲激光器;2聚焦透镜;3样品;4采集透镜;5光纤;6光谱仪;7计算机。In the figure: 1 pulse laser; 2 focusing lens; 3 sample; 4 collecting lens; 5 optical fiber; 6 spectrometer; 7 computer.
具体实施方式Detailed ways
下面结合附图及具体实施例对本发明作进一步详细说明。The present invention will be described in further detail below in conjunction with the accompanying drawings and specific embodiments.
一种基于等离子体参数修正铀信号强度的铀含量检测方法,包括以下步骤:A uranium content detection method for correcting uranium signal intensity based on plasma parameters, comprising the following steps:
步骤1:利用激光诱导击穿光谱系统对铀浓缩物标准样品进行光谱采集Step 1: Spectral collection of standard samples of uranium concentrate by laser-induced breakdown spectroscopy
以脉冲激光器为激发光源,从脉冲激光器出射的激光经过聚焦透镜聚焦后作用于定标样品表面,在聚焦点产生等离子体,等离子体在保护气体的氛围中进行冷却,产生的辐射光信号通过采集透镜进入光纤,并经过光谱仪处理后转化成电信号被计算机采集,得到铀浓缩物标准样品的激光诱导等离子体特征光谱;The pulsed laser is used as the excitation light source. The laser emitted from the pulsed laser is focused by the focusing lens and then acts on the surface of the calibration sample. The plasma is generated at the focal point, and the plasma is cooled in the atmosphere of the protective gas. The lens enters the optical fiber, and after being processed by a spectrometer, it is converted into an electrical signal and collected by a computer to obtain the laser-induced plasma characteristic spectrum of the standard sample of uranium concentrate;
步骤2:从特征光谱中得到铀元素的特征谱峰强度Step 2: Obtain the characteristic spectrum peak intensity of uranium element from the characteristic spectrum
从光谱仪中首先采集铀特征谱峰信号强度I1,然后采集背景的信号强度IB;From the spectrometer, first collect the signal intensity I 1 of the uranium characteristic spectrum peak, and then collect the signal intensity I B of the background;
其中,铀特征谱峰信号强度I1是采集的原始光谱扣除暗电流背景后的信号强度,背景的信号强度IB是指所选取的铀特征谱峰对应波段范围内连续光谱的强度,两个信号选取相同的信号长度;Among them, the signal intensity I of the uranium characteristic spectrum peak is the signal intensity after deducting the dark current background from the original spectrum collected, and the background signal intensity I B refers to the intensity of the continuous spectrum in the corresponding band range of the selected uranium characteristic spectrum peak, two The signal selects the same signal length;
步骤3:基于等离子体特征光谱修正铀特征谱峰强度Step 3: Correct the uranium signature peak intensity based on the plasma signature spectrum
以I=I1-k IB得到修正后的铀特征峰信号强度I,其中k值确定方式为:The corrected signal intensity I of the characteristic peak of uranium is obtained by I=I 1 -k I B , where the value of k is determined as follows:
筛选铀的多条特征谱线,在玻尔兹曼平面法公式中,修正后的铀特征峰信号强度I与相应能级Ek具有线性关系,由于I1与IB已知,因此通过不断优化k值,直至I与相应能级Ek相关性最优,即拟合线性R2最大;确定k值后,即得到修正后的铀特征峰信号强度I,准确剔除了铀光谱信号中的背景噪声;Multiple characteristic spectral lines of uranium are screened. In the Boltzmann plane method formula, the corrected signal intensity I of the characteristic peak of uranium has a linear relationship with the corresponding energy level E k . Since I 1 and I B are known, so through continuous Optimize the k value until the correlation between I and the corresponding energy level E k is optimal, that is, the fitting linearity R2 is the largest; after determining the k value, the corrected uranium characteristic peak signal intensity I is obtained, and the uranium spectral signal is accurately eliminated. background noise;
能级Ek可从《原子数据库》中查阅;The energy level E k can be checked from the "atomic database";
所述的k最大取值为1,最小取值为0;The maximum value of said k is 1, and the minimum value is 0;
步骤4:建立定标模型Step 4: Build a Calibration Model
用修正后的铀特征峰信号强度I建立铀浓缩物标准样品中已知铀元素含量与铀特征峰信号强度I的标准曲线定标模型;Using the corrected uranium characteristic peak signal intensity I to establish a standard curve calibration model between the known uranium element content in the uranium concentrate standard sample and the uranium characteristic peak signal intensity I;
步骤5:检测铀浓缩物样品中铀元素含量Step 5: Detection of uranium content in uranium concentrate samples
对未知浓度的待测样品重复步骤1~步骤3操作,得出修正后的特征峰信号强度,然后利用步骤4中定标模型反算出待测样品中铀元素含量。Repeat steps 1 to 3 for the sample to be tested with an unknown concentration to obtain the corrected characteristic peak signal intensity, and then use the calibration model in
实施例:对重铀酸铵样品进行检测Example: detection of ammonium diuranate sample
步骤1:利用激光诱导击穿光谱系统对铀浓缩物标准样品进行光谱采集Step 1: Spectral collection of standard samples of uranium concentrate by laser-induced breakdown spectroscopy
如图1所示,以脉冲激光器(1)为激发光源,从激光器出射的激光经过聚焦透镜(2)聚焦后作用于定标标准样品(3)表面,在聚焦点产生等离子体,等离子体在保护气体的氛围中进行冷却,产生的辐射光信号通过采集透镜(4)进入光纤(5),并经过光谱仪(6)处理后转化成电信号被计算机(7)采集,得到重铀酸铵样品的激光诱导等离子体特征光谱;As shown in Figure 1, the pulsed laser (1) is used as the excitation light source, and the laser light emitted from the laser is focused by the focusing lens (2) and then acts on the surface of the calibration standard sample (3), generating plasma at the focal point. Cooling in an atmosphere of protective gas, the generated radiated light signal enters the optical fiber (5) through the collection lens (4), and after being processed by the spectrometer (6), it is converted into an electrical signal and collected by the computer (7) to obtain a sample of ammonium diuranate The characteristic spectrum of laser-induced plasma;
步骤2:从特征光谱中得到铀元素的特征谱线强度Step 2: Obtain the characteristic line intensity of uranium element from the characteristic spectrum
首先,计算铀特征谱峰信号强度I1,然后计算背景的信号强度IB;First, calculate the signal intensity I 1 of the uranium characteristic spectrum peak, and then calculate the signal intensity I B of the background;
其中,铀特征谱峰信号强度I1是指采集的原始光谱扣除暗电流背景后的信号强度,背景的信号强度IB是指所选取的铀特征谱峰对应波段范围内连续光谱的强度,两个信号选取相同长度的信号长度;Among them, the signal intensity I of the uranium characteristic spectrum peak refers to the signal intensity after deducting the dark current background from the original spectrum collected, and the background signal intensity I B refers to the intensity of the continuous spectrum in the corresponding band range of the selected uranium characteristic spectrum peak. Select the signal length of the same length for each signal;
步骤3:基于等离子体特征光谱修正铀特征谱峰强度Step 3: Correct the uranium signature peak intensity based on the plasma signature spectrum
选取九条铀一阶离子线建立玻尔兹曼平面法公式,其波长分别为409.013纳米、414.122纳米、415.541纳米、417.159纳米、424.166纳米、424.437纳米、434.169纳米、447.233纳米、454.362纳米;Select nine uranium first-order ion lines to establish the Boltzmann plane method formula, and their wavelengths are 409.013 nm, 414.122 nm, 415.541 nm, 417.159 nm, 424.166 nm, 424.437 nm, 434.169 nm, 447.233 nm, and 454.362 nm;
基于玻尔兹曼平面法建立各波长下的铀特征峰信号强度I与能级Ek的拟合方程,其中I以I=I1-k IB进行修正;不断调整k值,使拟合线性达到最佳(即相关性系数R2最大),从而确定k值,此时的铀特征峰信号强度I即为修正后的铀特征峰信号强度;图2展示其中一个铀样品优化结果图,该样品中当k=0.9时取得最优结果,则该样品中修正后的信号强度应为I=I1-0.9IB;Based on the Boltzmann plane method, the fitting equation of the uranium characteristic peak signal intensity I and the energy level Ek under each wavelength is established, wherein I is corrected with I=I 1 -k I B ; the value of k is constantly adjusted to make the fitting The linearity reaches the best (that is, the correlation coefficient R2 is the largest), so as to determine the k value, and the signal intensity I of the characteristic peak of uranium at this time is the signal intensity of the characteristic peak of uranium after correction; Fig. 2 shows the optimization result diagram of one of the uranium samples, The optimum result is obtained when k=0.9 in this sample, then the corrected signal intensity in this sample should be I=I 1 -0.9I B ;
步骤4:建立定标模型Step 4: Build a Calibration Model
选择光强度最大、与铀含量相关性系数最好的特征谱线,即用修正后的波长为409.013纳米的铀一阶离子线强度建立重铀酸铵标准样品中铀元素含量与铀特征峰信号强度的定标模型;Select the characteristic spectral line with the largest light intensity and the best correlation coefficient with the uranium content, that is, use the corrected wavelength of 409.013 nanometers to establish the uranium element content and uranium characteristic peak signal in the ammonium diuranate standard sample Intensity calibration model;
步骤5:检测铀浓缩物样品中铀元素含量Step 5: Detection of uranium content in uranium concentrate samples
对未知含量的重铀酸盐样品进行检测时,通过上述步骤1~3确定修正后的铀特征峰信号强度,然后代入步骤4的定标模型中,反算出样品中的铀含量。When detecting diuranate samples with unknown content, the corrected uranium characteristic peak signal intensity is determined through the
上表给出了采用本发明方法测得的铀元素含量实验数据,可见本发明方法铀元素含量检测平均相对误差低于2%。The above table shows the experimental data of the uranium element content measured by the method of the present invention. It can be seen that the average relative error of the uranium element content detection by the method of the present invention is less than 2%.
以上显示和描述了本发明的基本原理、主要特征和本发明的优点,对于本领域技术人员而言,显然本发明不限于上述示范性实施例的细节,而且在不背离本发明的精神或基本特征的情况下,能够以其他的具体形式实现本发明。因此,无论从哪一点来看,均应将实施例看作是示范性的,而且是非限制性的,本发明的范围由所附权利要求而不是上述说明限定,因此旨在将落在权利要求的等同要件的含义和范围内的所有变化囊括在本发明内。不应将权利要求中的任何附图标记视为限制所涉及的权利要求。The basic principles, main features and advantages of the present invention have been shown and described above. For those skilled in the art, it is obvious that the present invention is not limited to the details of the above-mentioned exemplary embodiments, and without departing from the spirit or fundamentals of the present invention. The present invention can be implemented in other specific forms without any specific features. Accordingly, the embodiments should be regarded in all points of view as exemplary and not restrictive, the scope of the invention being defined by the appended claims rather than the foregoing description, and it is therefore intended that the scope of the invention be defined by the appended claims rather than by the foregoing description. All changes within the meaning and range of equivalents of the elements are embraced in the present invention. Any reference sign in a claim should not be construed as limiting the claim concerned.
Claims (10)
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN202211505485.0A CN115791757A (en) | 2022-11-28 | 2022-11-28 | A uranium content detection method based on plasma parameter correction of uranium signal intensity |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN202211505485.0A CN115791757A (en) | 2022-11-28 | 2022-11-28 | A uranium content detection method based on plasma parameter correction of uranium signal intensity |
Publications (1)
Publication Number | Publication Date |
---|---|
CN115791757A true CN115791757A (en) | 2023-03-14 |
Family
ID=85442568
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN202211505485.0A Pending CN115791757A (en) | 2022-11-28 | 2022-11-28 | A uranium content detection method based on plasma parameter correction of uranium signal intensity |
Country Status (1)
Country | Link |
---|---|
CN (1) | CN115791757A (en) |
Cited By (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN118641528A (en) * | 2024-08-13 | 2024-09-13 | 机数仪器(浙江)有限公司 | A method and system for detecting ore grade and elements |
CN119310066A (en) * | 2024-12-06 | 2025-01-14 | 核工业北京地质研究院 | Method for determining uranium content in ore |
Citations (6)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20030231306A1 (en) * | 2002-04-11 | 2003-12-18 | Gornushkin Igor B. | Automatic correction for continuum background in laser induced breakdown and Raman spectroscopy |
CN102410992A (en) * | 2011-08-01 | 2012-04-11 | 清华大学 | Simplified element measurement method through laser-induced plasma spectral standardization |
CN105445239A (en) * | 2015-12-18 | 2016-03-30 | 北京农业智能装备技术研究中心 | Background deduction-based element detection method and system |
CN109781711A (en) * | 2019-02-21 | 2019-05-21 | 华中科技大学 | A Quantitative Analysis Method of Laser-Induced Breakdown Spectroscopy Based on Single-Standard Calibration |
CN113063770A (en) * | 2021-03-11 | 2021-07-02 | 中国原子能科学研究院 | A method for quantitative analysis of uranium content |
CN113075201A (en) * | 2021-03-30 | 2021-07-06 | 华中科技大学 | Concentration detection method and system for complex matrix sample |
-
2022
- 2022-11-28 CN CN202211505485.0A patent/CN115791757A/en active Pending
Patent Citations (6)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20030231306A1 (en) * | 2002-04-11 | 2003-12-18 | Gornushkin Igor B. | Automatic correction for continuum background in laser induced breakdown and Raman spectroscopy |
CN102410992A (en) * | 2011-08-01 | 2012-04-11 | 清华大学 | Simplified element measurement method through laser-induced plasma spectral standardization |
CN105445239A (en) * | 2015-12-18 | 2016-03-30 | 北京农业智能装备技术研究中心 | Background deduction-based element detection method and system |
CN109781711A (en) * | 2019-02-21 | 2019-05-21 | 华中科技大学 | A Quantitative Analysis Method of Laser-Induced Breakdown Spectroscopy Based on Single-Standard Calibration |
CN113063770A (en) * | 2021-03-11 | 2021-07-02 | 中国原子能科学研究院 | A method for quantitative analysis of uranium content |
CN113075201A (en) * | 2021-03-30 | 2021-07-06 | 华中科技大学 | Concentration detection method and system for complex matrix sample |
Non-Patent Citations (1)
Title |
---|
王静鸽;李新忠;李贺贺;王辉;张利平;尹传磊;唐苗苗;: "背景扣除和强度校正对激光诱导等离子体光谱参数的影响", 光谱学与光谱分析, no. 01, 15 January 2018 (2018-01-15) * |
Cited By (4)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN118641528A (en) * | 2024-08-13 | 2024-09-13 | 机数仪器(浙江)有限公司 | A method and system for detecting ore grade and elements |
CN118641528B (en) * | 2024-08-13 | 2024-12-24 | 机数仪器(浙江)有限公司 | Ore grade and element detection method and system |
CN119310066A (en) * | 2024-12-06 | 2025-01-14 | 核工业北京地质研究院 | Method for determining uranium content in ore |
CN119310066B (en) * | 2024-12-06 | 2025-02-14 | 核工业北京地质研究院 | Methods for determining uranium content in ores |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
CN104251846B (en) | Discriminant analysis combined laser-induced breakdown spectroscopy quantitative analysis method | |
CN101509872B (en) | Coal quality on-line detecting analytical method based on regression analysis | |
CN102053083B (en) | An online measurement method of coal quality characteristics based on partial least square method | |
CN102004097B (en) | Coal quality on-line detecting method based on dominating factor and combined with partial least squares method | |
CN102262076B (en) | Laser-Induced Breakdown Spectroscopy Element Concentration Measurement Method Based on Line Combination | |
CN101949852B (en) | Spectral standardization-based coal quality on-line detection method | |
CN101509873B (en) | Coal quality detecting method based on active marker method | |
CN115791757A (en) | A uranium content detection method based on plasma parameter correction of uranium signal intensity | |
CN102004088B (en) | Method for measuring coal property on line based on neural network | |
CN103808695B (en) | A method for detecting total iron in iron ore based on laser-induced breakdown spectroscopy | |
CN103234944A (en) | Coal quality characteristic analysis method based on combination of dominant factors and partial least square method | |
CN106814061A (en) | A kind of method for improving LIBS overlap peak accuracy of quantitative analysis | |
CN102313731A (en) | Method for detecting content of component in unknown object on line | |
CN102410993A (en) | Elemental Measurement Method Based on Standardization of Laser-Induced Plasma Emission Spectra | |
CN112504983A (en) | Nitrate concentration prediction method based on turbidity chromaticity compensation | |
CN103792215A (en) | Method for rapidly measuring content of carbon element in steel | |
CN106248653B (en) | A method of improving laser induced breakdown spectroscopy quantitative analysis long-time stability | |
CN106290263B (en) | A kind of LIBS calibration and quantitative analysis methods based on genetic algorithm | |
CN104730043A (en) | Method for measuring heavy metals in ink based on partial least squares | |
CN105277531B (en) | A kind of coal characteristic measuring method based on stepping | |
CN103792214A (en) | Method for improving carbon content measuring accuracy in steel | |
CN114636687B (en) | Small sample coal quality characteristics analysis system and method based on deep transfer learning | |
CN104316510B (en) | A kind of uranic Raman spectrum analysis method | |
CN109030467B (en) | Self-absorption effect correction method for laser breakdown spectroscopy | |
Hao et al. | Long-term repeatability improvement of quantitative LIBS using a two-point standardization method |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
PB01 | Publication | ||
PB01 | Publication | ||
SE01 | Entry into force of request for substantive examination | ||
SE01 | Entry into force of request for substantive examination |