CN114486962A - Quantitative identification method, system and equipment for light element-containing minerals of complex component samples - Google Patents
Quantitative identification method, system and equipment for light element-containing minerals of complex component samples Download PDFInfo
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Abstract
The invention belongs to the field of material analysis, and particularly relates to a method, a system and equipment for quantitatively identifying light element-containing minerals of a complex component sample, aiming at solving the problem of misdetection of the light element-containing minerals by the existing method for analyzing the components of the minerals by using a scanning electron microscope. The invention includes: carrying out back scattering image and co-view field X-ray energy spectrum acquisition on the sample; obtaining primary classification mineral components and area ratio data according to an X-ray energy spectrum; uniformly marking minerals which cannot be distinguished by utilizing an X-ray energy spectrum and only differ from light elements in element types as a series A to obtain a primary classification mineral distribution image; superposing the primary classification mineral distribution image on a back scattering electronic signal diagram, and extracting light element-containing and light element-free mineral distribution images according to gray level difference; and calculating the area ratio of each mineral, and further obtaining the weight ratio and distribution of each mineral. The invention can utilize the mineral analysis technology of the scanning electron microscope to accurately and quantitatively characterize the surface distribution and the content of the mineral containing the light element in the complex component sample.
Description
Technical Field
The invention belongs to the field of material analysis, and particularly relates to a quantitative identification method, a system and equipment for light element-containing minerals of a complex component sample.
Background
The mineral analysis technology of the scanning electron microscope is a mainstream technology for acquiring mineral composition, content and distribution information at present, and mainly obtains a test result by acquiring X characteristic ray spectrogram information of minerals and comparing the X characteristic ray spectrogram information with an existing database. And the element species and concentration are the basic information for determining the mineral species. Due to the low characteristic X-ray yield and low energy of light elements (here, specifically B and the elements before B), these elements cannot be detected by an energy spectrometer, or the detected spectral peaks are low and irregular in shape. This has led to the fact that if the sample composition is complex and it is known to contain two minerals differing only in their elemental species by light elements, the identification and quantification of these two minerals cannot be carried out using sem mineral analysis techniques.
Disclosure of Invention
In order to solve the above problems in the prior art, that is, the problem that the existing scanning electron microscope mineral analysis technology cannot distinguish and quantitatively identify two minerals, which are known to be contained in a complex component sample and only differ from each other in element type by a light element, the present invention provides a quantitative identification method for a complex component sample light element-containing mineral, the method comprising:
step S100, acquiring a mineral sample to be identified, and carrying out back scattering electronic signal image acquisition after argon ion polishing to obtain a back scattering electronic signal image; the backscattered electron signal comprises a plurality of gray scale regions;
step S200, acquiring a back scattering electronic signal image view field based on the mineral sample to be identified, and carrying out X-ray energy spectrum acquisition on the back scattering electronic signal image view field to obtain an X-ray energy spectrogram;
step S300, comparing the X-ray energy spectrogram with a mineral spectrogram library to obtain primary classification mineral components and primary classification area percentage data;
step S400, based on the primary classification mineral component data, assigning colors to gray areas according to mineral types in a back scattering electron signal image, uniformly marking two minerals which cannot be distinguished by an X-ray energy spectrum and only have light element differences on element types as a series A, assigning a designated color to the gray area of the series A, marking all minerals which do not belong to the series A as a series B, and assigning another designated color to all gray areas of the series B to obtain a primary classification mineral distribution image;
step S500, adjusting the resolution of the primary classified mineral distribution image to be consistent with that of the back scattering electronic signal image, adjusting the transparency of the primary classified mineral distribution image, superposing the primary classified mineral distribution image on the back scattering electronic signal image, extracting a series A mineral overall distribution map, and extracting a distribution image containing light element minerals and a distribution image not containing light element minerals respectively;
step S600, based on the distribution map of the minerals containing the light elements and the distribution image of the minerals not containing the light elements, obtaining the number of pixels containing the minerals containing the light elements and the number of pixels not containing the minerals containing the light elements through image processing software, and further calculating the area ratio of the minerals containing the light elements and the area ratio of the minerals not containing the light elements, so as to obtain area percentage data of all the minerals;
and step S700, calculating the weight ratio of all the minerals by combining the density of the minerals based on the area percentage data of all the minerals, and further obtaining the weight ratio of the minerals containing light elements and the weight ratio of the minerals not containing light elements.
In some preferred embodiments, the mineral sample to be identified is any one of sandstone, shale, carbonate, metamorphic rock, volcanic rock and meteorite;
the mineral sample is a block sample or a powder sample with the micron-scale to centimeter-scale;
the powdery sample is embedded by resin.
In some preferred embodiments, after the mineral sample to be identified is obtained, the coating treatment or the coating treatment with the conductive glue solution can be selected;
the coating treatment adopts a carbon film or a gold film, and the coating thickness is 5-15 nm;
and (3) coating the conductive glue solution, specifically coating the conductive glue solution on the side surface of the sample.
In some preferred embodiments, the primary classified mineral distribution image is adjusted in transparency and then superimposed on the backscattered electron signal map, specifically, the primary classified mineral distribution image and the superimposed portion of the backscattered electron signal map are superimposed, the non-overlapping viewing zones are cut off, only the overlapping viewing zones are reserved, so as to obtain a superimposed image, and then the distribution image containing the light element minerals and the distribution image not containing the light element minerals are extracted based on the superimposed image.
In some preferred embodiments, the distribution image of the light element-containing mineral and the distribution image of the light element-free mineral are extracted, the light element-containing mineral and the light element-free mineral are distinguished from each other based on the gradation information of the superimposed images, and the distribution image of the light element-containing mineral and the distribution image of the light element-free mineral are extracted.
In some preferred embodiments, the S400 marks the series a as white and the series B as black.
In some preferred embodiments, the adjusted transparency is set at 50%.
In another aspect of the present invention, a quantitative identification system for a complex component sample light element-containing mineral is provided, which includes: the device comprises a back scattering electronic signal acquisition module, an X-ray energy spectrum acquisition module, a mineral component acquisition module, a mineral distribution image acquisition module, a light element-containing mineral area ratio calculation module and a light element-containing mineral weight ratio calculation module;
the back scattering electronic signal acquisition module is configured to acquire a mineral sample to be identified, and acquire a back scattering electronic signal image after argon ion polishing to acquire the back scattering electronic signal image, wherein the back scattering electronic signal comprises a plurality of gray scale areas;
the X-ray energy spectrum acquisition module is configured to acquire a back scattering electron signal image view field based on the mineral sample to be identified, and acquire an X-ray energy spectrum in the back scattering electron signal image view field to acquire an X-ray energy spectrum;
the mineral component acquisition module is configured to compare the X-ray energy spectrogram with a mineral spectrogram library to obtain primary classification mineral components and primary classification area percentage data;
the mineral distribution image acquisition module is configured to assign colors to gray regions according to mineral types in a back scattering electron signal image based on the primary classification mineral component data, uniformly mark two minerals which cannot be distinguished by an X-ray energy spectrum and only differ in light elements on element types as a series A, assign a specified color to the gray region of the series A, mark all minerals which do not belong to the series A as a series B, and assign another specified color to all gray regions of the series B to obtain a primary classification mineral distribution image;
the light element-containing mineral distribution image acquisition module is configured to adjust the resolution of the primary classified mineral distribution image to be consistent with that of the back scattering electronic signal image, adjust the transparency of the primary classified mineral distribution image, and then superimpose the primary classified mineral distribution image on the back scattering electronic signal image to extract a series A mineral overall distribution map, and then respectively extract a distribution image of light element-containing minerals and a distribution image of light element-free minerals;
the light element-containing mineral area ratio calculation module is configured to obtain the number of pixels containing light element minerals and the number of pixels containing no light element minerals through image processing software based on the distribution image containing light element minerals and the distribution image containing no light element minerals, and further calculate the area ratio containing light element minerals and the area ratio containing no light element minerals, so as to obtain area percentage data of all minerals;
the light element-containing mineral weight proportion calculation module is configured to calculate the weight proportion of all minerals by combining the density of the minerals based on the area percentage data of all minerals, and further obtain the weight proportion of the light element-containing mineral and the weight proportion of the light element-free mineral;
in a third aspect of the present invention, an electronic device is provided, including: at least one processor; and a memory communicatively coupled to at least one of the processors; wherein the memory stores instructions executable by the processor, and the instructions are used for being executed by the processor to realize the quantitative identification method of the light element-containing mineral in the complex component sample.
In a fourth aspect of the present invention, a computer-readable storage medium is provided, in which computer instructions are stored, and the computer instructions are used for being executed by the computer to implement a method for quantitatively identifying a light element-containing mineral in a complex component sample.
The invention has the beneficial effects that:
according to the invention, the scanning electron microscope and the EDS technology are combined to perform surface distribution characterization and quantitative identification on the light element-containing mineral in the complex sample, so that the distribution and the proportion of the light element-containing mineral can be accurately obtained, the defect that the surface distribution and the content of the light element-containing mineral in the complex component sample cannot be characterized by the existing scanning electron microscope mineral analysis technology is overcome, and the method has important significance for exploration and development of the light element-containing mineral resources.
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Other features, objects and advantages of the present application will become more apparent upon reading of the following detailed description of non-limiting embodiments thereof, made with reference to the accompanying drawings in which:
FIG. 1 is a schematic flow chart of the method for quantitatively identifying light element-containing minerals in a complex component sample according to the present invention;
FIG. 2 is a schematic representation of the mineral analysis principle of the scanning electron microscope of the present invention;
FIG. 3 is a backscattered electron signal image of a shale sample in an embodiment of the present invention;
FIG. 4 is a schematic illustration of an image of mineral distribution in an embodiment of the invention;
FIG. 5 is a schematic illustration of an overlay image in an embodiment of the invention;
FIG. 6 is a graph of the overall distribution of analcime and albite in an example of the present invention;
FIG. 7 is a graph of the analcime profile in an example of the present invention;
fig. 8 is a albite distribution diagram in the example of the present invention.
Detailed Description
The present application will be described in further detail with reference to the following drawings and examples. It is to be understood that the specific embodiments described herein are merely illustrative of the relevant invention and not restrictive of the invention. It should be noted that, for convenience of description, only the portions related to the related invention are shown in the drawings.
It should be noted that the embodiments and features of the embodiments in the present application may be combined with each other without conflict. The present application will be described in detail below with reference to the embodiments with reference to the attached drawings.
The invention provides a quantitative identification method of light element-containing minerals of a complex component sample, which comprises the following steps of S100-S700:
step S100, acquiring a mineral sample to be identified, and carrying out back scattering electronic signal image acquisition after argon ion polishing to obtain a back scattering electronic signal image; the backscattered electron signal comprises a plurality of gray scale regions;
step S200, acquiring a back scattering electronic signal image view field based on the mineral sample to be identified, and carrying out X-ray energy spectrum acquisition on the back scattering electronic signal image view field to obtain an X-ray energy spectrogram;
step S300, comparing the X-ray energy spectrogram with a mineral spectrogram library to obtain primary classification mineral components and primary classification area percentage data;
step S400, based on the primary classification mineral component data, assigning colors to gray areas according to mineral types in a back scattering electron signal image, uniformly marking two minerals which cannot be distinguished by an X-ray energy spectrum and only have light element differences on element types as a series A, assigning a designated color to the gray areas of the series A, marking all minerals which do not belong to the series A as a series B, and assigning another designated color to all the gray areas of the series B to obtain a primary classification mineral distribution image;
step S500, adjusting the resolution of the primary classified mineral distribution image to be consistent with that of the back scattering electronic signal image, adjusting the transparency of the primary classified mineral distribution image, superposing the primary classified mineral distribution image on the back scattering electronic signal image, extracting a series A mineral overall distribution map, and extracting a distribution image containing light element minerals and a distribution image not containing light element minerals respectively;
step S600, based on the distribution image containing the light element minerals and the distribution image not containing the light element minerals, obtaining the number of pixels containing the light element minerals and the number of pixels not containing the light element minerals through image processing software, and further calculating the area ratio of the light element minerals and the area ratio of the light element minerals, so as to obtain area percentage data of all minerals;
and step S700, calculating the weight ratio of all the minerals by combining the density of the minerals based on the area percentage data of all the minerals, and further obtaining the weight ratio of the minerals containing light elements and the weight ratio of the minerals not containing light elements.
In the embodiment, the content and the distribution of the light element-containing minerals in the complex component sample are determined by utilizing a scanning electron microscope mineral analysis technology. Various minerals containing light elements cannot be accurately identified in a complex component sample only through gray scale information, if two minerals (such as analcime and albite) only differ in whether the two minerals contain the light elements, the two minerals cannot be distinguished through an X-ray spectrogram, and therefore the two minerals are used as a series for primary classification; and because the light element is contained, the gray values of the two minerals after primary classification are different, so that the two minerals can be distinguished by utilizing the gray values.
The invention can not only accurately obtain the component content information of all minerals in the sample by utilizing the mineral analysis technology of the scanning electron microscope, but also obtain the surface distribution information of various minerals, and can conjecture the diagenetic evolution and calculate the mechanical properties of the rock according to the surface distribution information.
The method can accurately obtain the surface distribution and the proportion of the mineral containing the light element, overcomes the defect that the prior scanning electron microscope mineral analysis technology cannot represent the surface distribution and the content of the mineral containing the light element in a complex component sample, and has important significance for the investigation and the development of mineral resources containing the light element.
In order to more clearly illustrate the method for quantitatively identifying the light element-containing minerals in the complex component sample, the steps in the embodiment of the present invention are described in detail below with reference to fig. 1.
The method for quantitatively identifying the light element-containing minerals in the complex component sample comprises the following steps S100-S700, and the steps are described in detail as follows:
in this embodiment, the light element refers to an element before boron in the periodic table.
Step S100, acquiring a mineral sample to be identified, and carrying out back scattering electronic signal image acquisition after argon ion polishing to obtain a back scattering electronic signal image; the back scattering electronic signal image comprises component gray scale information of a sample and comprises a plurality of gray scale areas; argon ion polishing is to ensure the flatness of the sample surface.
In this embodiment, the mineral sample to be identified is any one of sandstone, shale, carbonate, metamorphic rock, volcanic rock and meteorite;
the mineral sample is a block sample or a powder sample with the micron-scale to centimeter-scale;
the powdery sample is embedded and embedded by resin;
in the embodiment, after the mineral sample to be identified is obtained, coating treatment or coating treatment with conductive glue solution can be selected; whether film coating treatment is carried out or not can be selected according to the surface conductivity of the sample and the voltage and beam intensity adopted by the test;
the coating treatment adopts a carbon film or a gold film, and the coating thickness is 5-15 nm;
coating the conductive glue solution, namely coating the conductive glue solution on the side surface of the sample;
in the embodiment, the shale sample is randomly obtained as an example, and a back scattering electron image is shown in fig. 3; in fig. 3, the resolution is 195nm, the size is 200 × 150 μm, the surface of the sample is subjected to film coating treatment, the film thickness is 5nm, and meanwhile, the side surface of the sample is coated with conductive glue solution to enhance the conductivity of the side surface of the sample. Since the backscattered electron signals may reflect compositional information, images of the backscattered electron signals are selected for acquisition when observing the mineral composition of the sample. The image size is not limited to this size, and an image of an arbitrary size may be selected to be acquired.
Step S200, acquiring a back scattering electronic signal image view field based on the mineral sample to be identified, and carrying out X-ray energy spectrum acquisition on the back scattering electronic signal image view field to obtain an X-ray energy spectrogram;
step S300, comparing the X-ray energy spectrogram with a mineral spectrogram library to obtain primary classification mineral components and primary classification area percentage data; the mineral spectrum library can be self-contained by software or built by a tester; the primary classification mineral composition and area percentage data are shown in table 1:
TABLE 1 Primary classification of mineral composition and area percent data
Step S400, based on the primary classification mineral component data, assigning colors to gray areas according to mineral types in a back scattering electron signal image, uniformly marking two minerals which cannot be distinguished by an X-ray energy spectrum and only have light element differences on element types as a series A, assigning a designated color to the gray area of the series A, marking all minerals which do not belong to the series A as a series B, and assigning another designated color to all gray areas of the series B to obtain a primary classification mineral distribution image; in this embodiment, the gray scale regions of the series B may be colored according to the mineral types that can be distinguished by the X-ray energy spectrum, so as to obtain more types of primary classification mineral distribution images.
The principle of mineral analysis by a scanning electron microscope is shown in fig. 2, and a back scattering diagram in fig. 2 is to acquire an image of a sample after argon ion polishing; the back scattering image comprises a plurality of gray scale regions, and different colors are given to adjacent regions with different gray scales to obtain a phase decomposition image in the image 2; collecting X-ray energy spectrum at the geometric center of each color block on the phase-resolved image, wherein the position of a collecting point is shown as an X-ray dot diagram in figure 2; different minerals are identified by using the X-ray energy spectrum diagram, different colors are respectively given to all gray scale areas of the different minerals in the back scattering diagram, and a mineral distribution diagram as shown in figure 2 is obtained.
The method specifically comprises the following steps: the image in the view field is divided into a plurality of fine gray scale regions, the geometric center of each region is subjected to X-ray energy spectrum acquisition, and the numerous fine gray scale regions represented by the X-ray energy spectrum with the same characteristics are endowed with the same color. That is, the same color represents the same X-ray energy spectrum information which can represent the same mineral or two minerals with only light element difference in element type; different colors represent different X-ray energy spectrum information and different minerals. Different individual minerals or series of minerals may be given different colours as required.
In this embodiment, the series a is marked white and the series B is marked black. Namely, analcime and albite are classified into one class, and other minerals are classified into one class, the analcime and albite are labeled to be white, the other minerals are labeled to be black, and finally, the distribution image of the primary classification minerals of the vision field is obtained and is shown in fig. 4;
step S500, adjusting the resolution of the primary classification mineral distribution image to be consistent with that of the back scattering electronic signal image, adjusting the transparency of the mineral distribution image, superposing the mineral distribution image on the back scattering electronic signal image, extracting a series A mineral overall distribution diagram as shown in a superposed image in a figure 5, and extracting a distribution image containing light element minerals and a distribution image not containing light element minerals respectively;
in this embodiment, the transparency is preferably adjusted to 50%, and the analcime and albite in the image are extracted by using the gray information of the superimposed image (gray values: albite and analcime > the rest of minerals), and the overall distribution diagram of analcime and albite is obtained as shown in fig. 6.
And adjusting the transparency of the primary classification mineral distribution image and then superposing the primary classification mineral distribution image on a back scattering electron signal diagram, specifically, superposing the superposed part of the mineral distribution image and the back scattering electron signal diagram, cutting off non-superposed vision fields, only reserving the superposed vision fields to obtain a superposed image, and further extracting a distribution image containing light element minerals and a distribution image containing no light element minerals based on the superposed image.
In this embodiment, the distribution image of the minerals containing light elements and the distribution image of the minerals not containing light elements can be extracted by distinguishing the minerals containing light elements from the minerals not containing light elements based on the gradation information of the superimposed image. For example, by using the gray scale difference between analcime and albite (in this embodiment, the gray scale value of analcime is 90-100, and the gray scale value of albite is 110-130), the analcime distribution diagram and the albite distribution diagram are respectively obtained as shown in fig. 7 and fig. 8.
Step S600, based on the distribution image containing the light element minerals and the distribution image not containing the light element minerals, obtaining the number of pixels containing the light element minerals and the number of pixels not containing the light element minerals through image processing software, and further calculating the area ratio of the light element minerals and the area ratio of the light element minerals, so as to obtain area percentage data of all minerals;
step S700, calculating the weight ratio of all minerals by combining the density of the minerals based on the area percentage data of all the minerals, and further obtaining the weight ratio of the minerals containing light elements and the weight ratio of the minerals not containing light elements;
and carrying out pixel number statistics on the superimposed image, the analcime distribution diagram and the albite distribution diagram, and calculating to obtain the area percentages of analcime and albite so as to obtain the area percentage data of all minerals in the embodiment. And combining the densities of the minerals in the visual field as shown in table 2, calculating the weight ratio of all the minerals, and further obtaining the weight percentages of analcime and albite as shown in table 3:
TABLE 2 mineral Density Meter
Table 3 area and weight percent of minerals table
The system for quantitatively identifying a light element-containing mineral in a complex component sample according to a second embodiment of the present invention includes: the device comprises a back scattering electronic signal acquisition module, an X-ray energy spectrum acquisition module, a mineral component acquisition module, a mineral distribution image acquisition module, a light element-containing mineral area ratio calculation module and a light element-containing mineral weight ratio calculation module;
the back scattering electronic signal acquisition module is configured to acquire a mineral sample to be identified, and after argon ion polishing, back scattering electronic signal image acquisition is carried out to acquire a back scattering electronic signal image; the backscattered electron signal comprises a plurality of gray scale regions;
the X-ray energy spectrum acquisition module is configured to acquire a back scattering electron signal image view field based on the mineral sample to be identified, and acquire an X-ray energy spectrum in the back scattering electron signal image view field to acquire an X-ray energy spectrum;
the mineral component acquisition module is configured to compare the X-ray energy spectrogram with a mineral spectrogram library to obtain primary classification mineral components and primary classification area percentage data;
the mineral distribution image acquisition module is configured to assign colors to gray regions according to mineral types in a back scattering electron signal image based on the primary classification mineral component data, uniformly mark two minerals which cannot be distinguished by an X-ray energy spectrum and only differ in light elements on element types as a series A, assign a specified color to the gray region of the series A, mark all minerals which do not belong to the series A as a series B, and assign another specified color to all gray regions of the series B to obtain a primary classification mineral distribution image;
the light element-containing mineral distribution image acquisition module is configured to adjust the resolution of the mineral distribution image to be consistent with that of the back scattering electronic signal image, adjust the transparency of the mineral distribution image, and then superimpose the mineral distribution image on the back scattering electronic signal image to extract a series A mineral overall distribution diagram, and then respectively extract the distribution image of the light element-containing mineral and the distribution image of the light element-free mineral;
the light element-containing mineral area ratio calculation module is configured to obtain the number of pixels containing light element minerals and the number of pixels containing no light element minerals through image processing software based on the distribution image containing light element minerals and the distribution image containing no light element minerals, and further calculate the area ratio containing light element minerals and the area ratio containing no light element minerals, so as to obtain area percentage data of all minerals;
the weight proportion calculation module of the minerals containing the light elements is configured to calculate the weight proportion of all the minerals by combining the density of the minerals based on the area percentage data of all the minerals, and further obtain the weight proportion of the minerals containing the light elements and the weight proportion of the minerals without the light elements.
It can be clearly understood by those skilled in the art that, for convenience and brevity of description, the specific working process and related description of the system described above may refer to the corresponding process in the foregoing method embodiments, and will not be described herein again.
It should be noted that, the quantitative identification system for a complex component sample containing a light element mineral provided in the above embodiment is only illustrated by the division of the above functional modules, and in practical applications, the above functions may be allocated to different functional modules according to needs, that is, the modules or steps in the embodiment of the present invention are further decomposed or combined, for example, the modules in the above embodiment may be combined into one module, or may be further split into multiple sub-modules, so as to complete all or part of the above described functions. The names of the modules and steps involved in the embodiments of the present invention are only for distinguishing the modules or steps, and are not to be construed as unduly limiting the present invention.
An electronic apparatus according to a third embodiment of the present invention includes: at least one processor; and a memory communicatively coupled to at least one of the processors; wherein the memory stores instructions executable by the processor, and the instructions are used for being executed by the processor to realize the quantitative identification method of the light element-containing mineral in the complex component sample.
A computer-readable storage medium of a fourth embodiment of the present invention stores computer instructions for execution by the computer to implement a method for quantitative identification of a light-element-containing mineral of a complex-component sample.
It can be clearly understood by those skilled in the art that, for convenience and brevity of description, the specific working processes and related descriptions of the storage device and the processing device described above may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present application. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The terms "first," "second," and the like are used for distinguishing between similar elements and not necessarily for describing or implying a particular order or sequence.
The terms "comprises," "comprising," or any other similar term are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus.
So far, the technical solutions of the present invention have been described in connection with the preferred embodiments shown in the drawings, but it is easily understood by those skilled in the art that the scope of the present invention is obviously not limited to these specific embodiments. Equivalent changes or substitutions of related technical features can be made by those skilled in the art without departing from the principle of the invention, and the technical scheme after the changes or substitutions can fall into the protection scope of the invention.
Claims (10)
1. A quantitative identification method for a light element-containing mineral of a complex component sample is characterized by comprising the following steps:
step S100, acquiring a mineral sample to be identified, and performing back scattering electronic signal image acquisition after argon ion polishing to obtain a back scattering electronic signal image; the backscattered electron signal comprises a plurality of gray scale regions;
step S200, acquiring a back scattering electronic signal image view field based on the mineral sample to be identified, and carrying out X-ray energy spectrum acquisition on the back scattering electronic signal image view field to obtain an X-ray energy spectrogram;
step S300, comparing the X-ray energy spectrogram with a mineral spectrogram library to obtain primary classification mineral components and primary classification area percentage data;
step S400, based on the primary classification mineral component data, assigning colors to gray areas according to mineral types in a back scattering electron signal image, uniformly marking two minerals which cannot be distinguished by an X-ray energy spectrum and only have light element differences on element types as a series A, assigning a designated color to the gray area of the series A, marking all minerals which do not belong to the series A as a series B, and assigning another designated color to all gray areas of the series B to obtain a primary classification mineral distribution image;
step S500, adjusting the resolution of the primary classification mineral distribution image to be consistent with that of the back scattering electronic signal image, adjusting the transparency of the primary classification mineral distribution image, superposing the primary classification mineral distribution image on the back scattering electronic signal image, extracting a series A mineral overall distribution graph, and extracting a distribution image containing light element minerals and a distribution image not containing light element minerals respectively;
step S600, based on the distribution image containing the light element minerals and the distribution image not containing the light element minerals, obtaining the number of pixels containing the light element minerals and the number of pixels not containing the light element minerals through image processing software, and further calculating the area ratio of the light element minerals and the area ratio of the light element minerals, so as to obtain area percentage data of all minerals;
and step S700, calculating the weight ratio of all the minerals by combining the density of the minerals based on the area percentage data of all the minerals, and further obtaining the weight ratio of the minerals containing light elements and the weight ratio of the minerals not containing light elements.
2. The method for quantitatively identifying the light element-containing minerals in the complex component samples according to claim 1, wherein the mineral samples to be identified are any one of sandstone, shale, carbonate, metamorphic rock, volcanic rock and meteorite;
the mineral sample is a block sample or a powder sample with the micron to centimeter grade;
the powdery sample is embedded by resin.
3. The method for quantitatively identifying the light-element-containing minerals in the complex-component samples according to claim 1, wherein after the mineral samples to be identified are obtained, coating treatment or coating treatment with conductive glue solution can be selected;
the coating treatment adopts a carbon film or a gold film, and the coating thickness is 5-15 nm;
and (3) coating the conductive glue solution, specifically coating the conductive glue solution on the side surface of the sample.
4. The method according to claim 1, wherein the distribution image of the primarily classified minerals is adjusted in transparency and superimposed on the backscattered electron signal map, and specifically, the superimposed portion of the distribution image of the primarily classified minerals and the backscattered electron signal map is superimposed, the non-overlapping viewing area is cut off, only the overlapping viewing area is reserved, and a superimposed image is obtained, and the distribution image of the minerals containing light elements and the distribution image of the minerals not containing light elements are extracted based on the superimposed image.
5. The method of claim 4, wherein the light-element-containing mineral and the light-element-free mineral are distinguished based on the gray scale information of the superimposed image, and the distribution image of the light-element-containing mineral and the distribution image of the light-element-free mineral are extracted.
6. The method for quantitatively identifying a complex constituent sample light element-containing mineral according to claim 1, wherein S400 marks a series a as white and a series B as black.
7. The method for quantitatively identifying a light-element-containing mineral in a complex-component sample according to claim 1, wherein the adjusted transparency is set to 50%.
8. A system for quantitatively identifying a light element-containing mineral in a complex component sample, the system comprising: the device comprises a back scattering electronic signal acquisition module, an X-ray energy spectrum acquisition module, a mineral component acquisition module, a mineral distribution image acquisition module, a light element-containing mineral area ratio calculation module and a light element-containing mineral weight ratio calculation module;
the back scattering electronic signal acquisition module is configured to acquire a mineral sample to be identified, and after argon ion polishing, back scattering electronic signal image acquisition is carried out to acquire a back scattering electronic signal image; the backscattered electron signal comprises a plurality of gray scale regions;
the X-ray energy spectrum acquisition module is configured to acquire a back scattering electron signal image view field based on the mineral sample to be identified, and acquire an X-ray energy spectrum in the back scattering electron signal image view field to acquire an X-ray energy spectrum;
the mineral component acquisition module is configured to compare the X-ray energy spectrogram with a mineral spectrogram library to obtain primary classification mineral components and primary classification area percentage data;
the mineral distribution image acquisition module is configured to assign colors to gray regions according to mineral types in a back scattering electron signal image based on the primary classification mineral component data, uniformly mark two minerals which cannot be distinguished by an X-ray energy spectrum and only differ in light elements on element types as a series A, assign a specified color to the gray region of the series A, mark all minerals which do not belong to the series A as a series B, and assign another specified color to all gray regions of the series B to obtain a primary classification mineral distribution image;
the light element-containing mineral distribution image acquisition module is configured to adjust the resolution of the primary classified mineral distribution image to be consistent with that of the back scattering electronic signal image, adjust the transparency of the primary classified mineral distribution image, and then superimpose the primary classified mineral distribution image on the back scattering electronic signal image to extract a series A mineral overall distribution map, and then respectively extract a distribution image of light element-containing minerals and a distribution image of light element-free minerals;
the light element-containing mineral area ratio calculation module is configured to obtain the number of pixels containing light element minerals and the number of pixels containing no light element minerals through image processing software based on the distribution image containing light element minerals and the distribution image containing no light element minerals, and further calculate the area ratio containing light element minerals and the area ratio containing no light element minerals, so as to obtain area percentage data of all minerals;
and the light element-containing mineral weight ratio calculation module is configured to calculate the weight ratio of all minerals by combining the density of the minerals based on the area percentage data of all minerals, and further obtain the weight ratio of the light element-containing mineral and the weight ratio of the light element-free mineral.
9. An electronic device, comprising: at least one processor; and a memory communicatively coupled to at least one of the processors; wherein the memory stores instructions executable by the processor for performing the method of quantitative identification of light element-containing minerals in a complex composition sample as defined in any one of claims 1 to 7.
10. A computer-readable storage medium storing computer instructions for execution by the computer to implement the method for quantitative identification of a light element-containing mineral of a complex composition sample according to any one of claims 1 to 7.
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