CN113406130A - Method for measuring mineral content of massive rock sample - Google Patents

Method for measuring mineral content of massive rock sample Download PDF

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CN113406130A
CN113406130A CN202010179456.4A CN202010179456A CN113406130A CN 113406130 A CN113406130 A CN 113406130A CN 202010179456 A CN202010179456 A CN 202010179456A CN 113406130 A CN113406130 A CN 113406130A
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mineral
sample
value
image
rock
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张彩霞
张耀南
王肖波
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Northwest Institute of Eco Environment and Resources of CAS
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Cold and Arid Regions Environmental and Engineering Research Institute of CAS
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N23/00—Investigating or analysing materials by the use of wave or particle radiation, e.g. X-rays or neutrons, not covered by groups G01N3/00 – G01N17/00, G01N21/00 or G01N22/00
    • G01N23/20—Investigating or analysing materials by the use of wave or particle radiation, e.g. X-rays or neutrons, not covered by groups G01N3/00 – G01N17/00, G01N21/00 or G01N22/00 by using diffraction of the radiation by the materials, e.g. for investigating crystal structure; by using scattering of the radiation by the materials, e.g. for investigating non-crystalline materials; by using reflection of the radiation by the materials
    • G01N23/203—Measuring back scattering
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N2223/00—Investigating materials by wave or particle radiation
    • G01N2223/10—Different kinds of radiation or particles
    • G01N2223/102—Different kinds of radiation or particles beta or electrons
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N2223/00—Investigating materials by wave or particle radiation
    • G01N2223/40—Imaging
    • G01N2223/401—Imaging image processing

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Abstract

The invention discloses a method for measuring mineral content of a massive rock sample, which comprises the steps of scanning the surface of the sample, obtaining a back scattering image after scanning, and measuring mineral particles on the surface of the massive rock sample, namely mineral A and mineral B according to the gray value of the back scattering image of the sample. And after the respective measurement is finished, performing statistical integration on the obtained test results to obtain mineral content data of the whole rock. The method solves the problem that the traditional automatic mineral parameter analysis system with the model number of MLA650, which is produced by FEI company, cannot be applied to block rock mineral analysis, and makes the analysis of block rock samples by the automatic mineral parameter analysis system possible. The whole process of measuring the mineral content of the massive rock sample is simple and quick, safe and economical, and the defects of long time consumption, complex operation and the like of mineral identification under the traditional microscope are overcome. The mineral detection efficiency is effectively improved, and the method has the characteristics of accuracy of test results and timeliness of data feedback.

Description

Method for measuring mineral content of massive rock sample
Technical Field
The invention belongs to the technical field of analysis and detection, and particularly relates to a method for determining the content of minerals in a massive rock sample by using an automatic mineral parameter analysis system.
Background
The automatic analysis system for mineral parameters, model number MLA650, produced by FEI is a high-speed automated automatic quantitative analysis system for mineral parameters. The method is mainly used in the fields of mining industry, metallurgy, geology and the like. The method can automatically and quantitatively analyze important parameters such as mineral substance composition, component quantification, mineral embedding characteristics, mineral size distribution, mineral dissociation degree and the like of the sample. The working principle of the automatic quantitative analysis system for mineral analysis parameters is that after a mineral sample is scanned, background removal is carried out based on a back scattering image, then mineral phase separation is carried out after the mineral is granulated, and then information of mineral content is obtained through a statistical method. This method has significant advantages for granulation of significant samples, such as soil and sand content, but has significant limitations for monolithic rock samples. This is because the minerals in the whole rock are tightly connected together to form a glued state, and the background without impurities can be removed in the analysis process, which also results in that the mineral parameter automatic analysis system cannot detect and analyze the content information of the whole minerals.
Disclosure of Invention
In view of the above, the present invention aims to provide a method for determining the mineral content in a bulk rock sample using an automated mineral parameter analysis system. The method can be used for detecting and analyzing the whole mineral content, and adds a new function for the automatic mineral parameter analysis system to determine the blocky rock.
The purpose of the invention is realized by the following technical scheme:
a method of mineral content measurement of a rock block sample, comprising the steps of:
step one, processing a massive rock sample into a cylindrical structure with the diameter of 30mm and the thickness of 2mm, and putting the cylindrical structure into a sample tray for vacuumizing;
starting an electron beam of an automatic analysis system to scan the surface of the vacuumized cylindrical sample, and obtaining a back scattering image after scanning;
thirdly, background subtraction is carried out based on the gray scale distribution characteristics of the back scattering image, minerals are divided into A and B to be used as research objects through the setting of the gray scale value range, namely, in the first step, the image with the gray scale value of the minerals A being 0-X is selected to be used as the research object, the 255-X image part is used as the background value to be subtracted, and the background value is used as a sample to be measured and analyzed; secondly, selecting an image with a mineral B gray value of 255-X as a research object, deducting the image with the gray value of 0-X as a background value, and performing test analysis by taking the image as a sample; wherein: x represents a selected gray segmentation value, and the value range of the selected gray segmentation value is 0-255;
step four: and after the mineral contents of the A part and the B part are respectively measured, summarizing the data of the mineral contents of the A part and the B part. Area statistics for A and B minerals can be obtained based on the following equation (1)
Cm=(A+B)/(Atotal+Btotal)×100% (1)
Calculating the area percentage content of different minerals in the whole block sample to obtain the mineral content data of the whole rock;
(1) in the formula, CmRefers to the area percentage content of a certain mineral in the whole block sample, and A and B are the total area of single mineral particles measured by two samples with different gray scale ranges respectively. A. thetotalAnd BtotalThe total area of all mineral particles measured for two different grey scale range samples respectively.
The advantages and the beneficial effects of the invention are as follows:
the method fills the defects of an automatic mineral parameter analysis system, and makes it possible to measure the mineral content of the massive rock sample based on the automatic quantitative mineral parameter analysis system. The whole process of measuring the mineral content of the massive rock sample is simple and quick, safe and economical, and the defects of long time consumption, complex operation and the like of mineral identification under the traditional microscope are overcome. The detection efficiency is effectively improved, and the method has the characteristics of accuracy of test results and timeliness of data feedback.
Drawings
Fig. 1 is a back-scattered electron image of a bulk sample.
FIG. 2 is a mineral profile plot of a portion of a block sample having gray scale values of 0-125.
FIG. 3 is a mineral distribution graph of a portion of a block sample with gray scale values of 125-255.
Detailed Description
The invention is explained in detail below with reference to the figures and examples:
example (b): bulk sandstone sample mineralogical composition analysis
A method of mineral content measurement of a rock block sample, comprising the steps of:
step one, processing a massive rock sample into a cylindrical structure with the diameter of 30mm and the thickness of 2mm, putting the cylindrical structure into a sample disc, and vacuumizing to 5 Mpa;
starting an electron beam of an automatic analysis system to scan the surface of the vacuumized cylindrical sample, and obtaining a back scattering image (see figure 1) after scanning;
thirdly, based on the fact that the mineral particles on the surface of the rock are in a connected state, performing background subtraction on the gray scale distribution characteristics of the scanned back scattering image, namely performing background subtraction on minerals A and B, namely selecting an image with a gray scale value of 0-X of the mineral A as a research object, subtracting an image part with a gray scale value of 255-X as a background value, and performing measurement analysis on the image part serving as a sample; secondly, selecting an image with a B gray value of 255-X as a research object, deducting the image with 0-X as a background value, and performing test analysis by using the image as a sample; wherein: and X represents a selected gray segmentation value, the value range of the selected gray segmentation value is 0-255 (the selected gray segmentation value of the mineral is reasonably selected according to the distribution characteristics of the gray values of the specific sample), and the value of X suitable for the sandstone sample is selected to be 125 after the comparison of the X value taking effects. FIGS. 2 and 3 show the results of the background subtraction mineral measurement, in which the white part is the background subtracted in several times;
step four: after the mineral contents of the mineral A and the mineral B are respectively measured, the data of the mineral contents of the mineral A and the mineral B are summarized, so that the area statistical data of the mineral A and the mineral B can be obtained, and the area statistical data are based on the following formula:
Cm=(A+B)/(Atotal+Btotal)×100%
calculating the area percentage content of different minerals in the whole block sample to obtain the mineral content data of the whole rock;
wherein, CmRefers to the area percentage content of a certain mineral in the whole block sample, and A and B are the total area of single mineral particles measured by two samples with different gray scale ranges respectively. A. thetotalAnd BtotalThe total area of all mineral particles measured for two different grey scale range samples respectively.
In the following, table 1 and table 2 respectively list the mineral contents of quartz, muscovite, plagioclase, waintianite, jade, chlorite and potash feldspar with gray values between 0 and 125 and gray values between 125 and 255.
TABLE 1 mineral content (. mu.m) of part A (between grey values 0-125)2）
Mineral name Mineral Area
Quartz Quartz 387420.84
White mica Muscovite 103416.46
Plagioclase feldspar Plagioclase 167985.10
Calcium antimonite Romeite 5435.28
Jadeite Jadeite 20429.53
Chlorite (chlorite) Chamosite 5230.55
Potassium feldspar K-feldspar 17104.47
Background Background 31050.36
Total of Total 738072.58
Table 2 mineral content (. mu.m) of section B (gray scale values between 125 and 255)2）
Mineral name Mineral Area
Quartz Quartz 1383158.31
White mica Muscovite 635661.74
Plagioclase feldspar Plagioclase 167985.10
Calcium antimonite Romeite 179429.33
Jadeite Jadeite 169260.68
Chlorite (chlorite) Chamosite 362190.45
Potassium feldspar K-feldspar 367225.28
Calcite Calcite 62336.94
Iron dolomite Ankerite 41990.66
Aluminum cerium apatite Aluminium britholite 3241.82
Albite Albite 484605.63
Background Background 42571.07
Total of Total 3899656.99
Table 3 shows the percentage by area of the monolithic quartz, muscovite, plagioclase, wainite, emerald, chlorite, and potash feldspar minerals.
TABLE 3 mineral area percentage content (%)
Figure 682339DEST_PATH_IMAGE001
Table 1, table 2 and table 3 can give: according to the method, the background of the minerals A and the background of the minerals B are deducted, the image with the gray value of 0-X of the minerals A is used as a research object, the image part of 255-X is deducted as a background value, the images with the gray value of 255-X of the minerals B are used as a research object, and the image with the gray value of 0-X is deducted as a background value, so that the total area of single mineral particles measured by two samples with different gray ranges is obtained respectively.
And the data of the mineral contents of the minerals A and B are summarized to obtain the data of the mineral content of the whole rock after the mineral contents of the minerals A and B are respectively measured in the table 3.

Claims (1)

1. A method of mineral content measurement of a rock block sample, comprising the steps of: :
step one, processing a massive rock sample into a cylindrical structure with the diameter of 30mm and the thickness of 2mm, and putting the cylindrical structure into a sample tray for vacuumizing;
starting an electron beam of an automatic analysis system to scan the surface of the vacuumized cylindrical sample, and obtaining a back scattering image after scanning;
thirdly, background subtraction is carried out based on gray scale distribution characteristics of the scanned back scattering image, minerals are divided into A and B as research objects through setting of a gray scale value range, namely, in the first step, an image with a gray scale value of 0-X of the minerals A is selected as a research object, a 255-X image part is subtracted as a background value, and the background value is used as a sample for measurement and analysis; secondly, selecting an image with a B gray value of 255-X as a research object, deducting the image with 0-X as a background value, and performing test analysis by using the image as a sample; wherein: x represents a selected gray segmentation value, and the value range of the selected gray segmentation value is 0-255;
step four: respectively measuring the mineral contents of the A part and the B part, and summarizing data of the mineral contents of the A part and the B part; area statistics for a and B minerals can be obtained based on the following equation (1):
Cm=(A+B)/(Atotal+Btotal)×100% (1)
calculating the area percentage content of different minerals in the whole block sample to obtain the mineral content data of the whole rock;
(1) in the formula, CmThe area percentage content of a certain mineral in the whole block sample is indicated, and A and B are the total area of single mineral particles measured by two samples with different gray scale ranges respectively; a. thetotalAnd BtotalThe total area of all mineral particles measured for two different grey scale range samples respectively.
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Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113866197A (en) * 2021-12-06 2021-12-31 中国科学院地质与地球物理研究所 Method for determining main quantity elements of sample with non-uniform mineral composition
CN116165054A (en) * 2023-04-21 2023-05-26 煤炭科学研究总院有限公司 Rock mechanical parameter acquisition method and device and electronic equipment

Citations (3)

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Publication number Priority date Publication date Assignee Title
CN104122283A (en) * 2014-08-01 2014-10-29 桂林理工大学 Total-rock component testing method based on in-situ electronic probe analysis
CN109270105A (en) * 2018-08-21 2019-01-25 中国科学院地质与地球物理研究所 The method for quickly identifying and positioning target mineral particle in the big ken
CN110873722A (en) * 2018-09-03 2020-03-10 中国石油化工股份有限公司 Rock core mineral component identification method

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Publication number Priority date Publication date Assignee Title
CN104122283A (en) * 2014-08-01 2014-10-29 桂林理工大学 Total-rock component testing method based on in-situ electronic probe analysis
CN109270105A (en) * 2018-08-21 2019-01-25 中国科学院地质与地球物理研究所 The method for quickly identifying and positioning target mineral particle in the big ken
CN110873722A (en) * 2018-09-03 2020-03-10 中国石油化工股份有限公司 Rock core mineral component identification method

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Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113866197A (en) * 2021-12-06 2021-12-31 中国科学院地质与地球物理研究所 Method for determining main quantity elements of sample with non-uniform mineral composition
CN116165054A (en) * 2023-04-21 2023-05-26 煤炭科学研究总院有限公司 Rock mechanical parameter acquisition method and device and electronic equipment

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