CN116087249A - Method, system and electronic equipment for identifying mineral distribution and content - Google Patents
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Abstract
The invention belongs to the field of material analysis, in particular relates to a method, a system and electronic equipment for identifying mineral distribution and content, and aims to solve the problem that the existing detection method cannot accurately obtain mineral components, distribution and content. The method comprises the following steps: carrying out flatness treatment and conductivity enhancement treatment on a mineral sample to be identified, and carrying out back scattering electronic signal image acquisition; collecting element plane distribution information, extracting element concentration dividing lines, overlapping the element concentration dividing lines on a back scattering electronic signal image, and dividing the back scattering electronic signal image into a plurality of first-stage dividing regions; carrying out pixel gray scale identification on each first-level boundary region, and dividing the first-level boundary region into a second-level boundary region, namely a two-factor boundary control region; and (3) carrying out X-ray energy spectrum acquisition on the double-factor edge control region, and comparing the obtained product with a mineral spectrum gallery to obtain the mineral type, distribution and content information of the mineral sample. The invention can accurately identify different minerals with approximate gray scale and adjacent growth in the sample, thereby obtaining accurate mineral distribution and content information.
Description
Technical Field
The invention belongs to the field of material analysis, and particularly relates to a method, a system and electronic equipment for identifying mineral distribution and content.
Background
The automatic mineral analysis technology of the scanning electron microscope is a mainstream technology for acquiring mineral composition, content and distribution information at present, mainly utilizes pixel gray information of a back scattering electronic signal image to divide different areas, acquires mineral X-characteristic ray spectrogram information of the different areas, and compares the mineral X-characteristic ray spectrogram information with an existing database to obtain a test result. The pixel gray information of minerals in the back-scattered electronic signal image is a threshold value, and gray threshold values of different minerals are crossed and even consistent. This results in that if the gray thresholds are crossed or the multiple minerals are distributed adjacently in a consistent manner, the gray information alone cannot be accurately distinguished, and thus the information of the mineral composition, distribution and content cannot be accurately obtained.
Disclosure of Invention
In order to solve the above-mentioned problems in the prior art, that is, in order to solve the problem that the existing detection method cannot accurately obtain the mineral composition, distribution and content, the present invention provides a method for identifying the mineral distribution and content, the method comprising:
step S100, obtaining a mineral sample to be identified; performing flatness treatment and conductivity enhancement treatment on the mineral sample to be identified to obtain a treated mineral sample, and performing back scattering electronic signal image acquisition on the treated mineral sample to obtain a back scattering electronic signal image;
step S200, acquiring element surface distribution information of the processed mineral sample in a set vision field to obtain an element surface distribution map; extracting element concentration boundaries in the element plane distribution map, and superposing the element concentration boundaries on the back-scattered electronic signal image, wherein the element concentration boundaries divide the back-scattered electronic signal image into a plurality of first-stage boundary regions; the first-stage boundary region is an element phase;
step S300, pixel gray scale identification is carried out on each level of demarcation zone one by one, so as to obtain pixel gray scale information; dividing each first-level boundary region according to the pixel gray information to obtain a second-level boundary region; the secondary boundary region is a two-factor edge control region, namely an element-gray phase;
and S400, collecting an X-ray energy spectrum of the double-factor edge control region to obtain an X-ray energy spectrum and element content information, and comparing the X-ray energy spectrum and the element content information with energy spectrum data stored in a mineral spectrum gallery to obtain the type, distribution and content information of minerals of the mineral sample to be identified in the set view.
In some preferred embodiments, the mineral sample to be identified is any one of sedimentary, metamorphic, volcanic and merle; the mineral sample to be identified is a block sample or a granular sample from micron level to centimeter level; the granular sample is a sample embedded by resin.
In some preferred embodiments, the mineral sample to be identified is subjected to a flatness treatment by the method of: and polishing the mineral sample to be identified.
In some preferred embodiments, the mineral sample to be identified is subjected to a conductivity enhancing treatment by: coating a film on the mineral sample to be identified and/or smearing conductive glue;
wherein, a carbon film or a gold film is adopted for coating, and the thickness of the coating is 5-15 nm;
and when conducting glue solution smearing treatment is carried out, conducting glue solution is smeared on the side face of the mineral sample to be identified.
In some preferred embodiments, when collecting the information of the distribution of the treated mineral sample on the element surface of the set view, the collected element types comprise a single element or a plurality of elements; each element corresponds to an element face profile.
In some preferred embodiments, when the processed mineral sample is subjected to back-scattering electronic signal image acquisition, the acceleration voltage is 5-20 kV, and the beam current is 1-5 nA; the acceleration voltage and the beam current are used to excite X-ray signals.
In a second aspect of the invention, a system for identifying mineral distribution and content is presented, the system comprising: the system comprises a back scattering electronic signal acquisition module, an image superposition module, a region division module and an X-ray energy spectrum acquisition module;
the back scattering electronic signal acquisition module is configured to acquire a mineral sample to be identified; performing flatness treatment and conductivity enhancement treatment on the mineral sample to be identified to obtain a treated mineral sample, and performing back scattering electronic signal image acquisition on the treated mineral sample to obtain a back scattering electronic signal image;
the image superposition module is configured to acquire element surface distribution information of the processed mineral sample in a set vision field to obtain an element surface distribution map; extracting element concentration boundaries in the element plane distribution map, and superposing the element concentration boundaries on the back-scattered electronic signal image, wherein the element concentration boundaries divide the back-scattered electronic signal image into a plurality of first-stage boundary regions; the first-stage boundary region is an element phase;
the region dividing module is configured to recognize pixel gray scales of each level of demarcation region one by one to obtain pixel gray scale information; dividing each first-level boundary region according to the pixel gray information to obtain a second-level boundary region; the secondary boundary region is a two-factor edge control region, namely an element-gray phase;
the X-ray energy spectrum acquisition module is configured to acquire an X-ray energy spectrum of the double-factor edge control area to obtain an X-ray energy spectrum and element content information, and compare the X-ray energy spectrum and the element content information with energy spectrum data stored in a mineral spectrum gallery to obtain the type, distribution and content information of minerals of the mineral sample to be identified in the set view.
In a third aspect of the present specification, an electronic device, at least one processor is presented; and a memory communicatively coupled to at least one of the processors, wherein the memory stores instructions executable by the processor for execution by the processor to implement a method for identifying mineral distribution and content as described above.
In a fourth aspect of the present description, a computer-readable storage medium is presented, the computer-readable storage medium storing computer instructions for execution by the computer to implement a method for identifying mineral distribution and content as described above.
The invention has the beneficial effects that:
the existing automatic mineral analysis technology of the scanning electron microscope utilizes gray level information to conduct partition identification, when different minerals growing adjacently and with similar gray level are encountered, the partition is inaccurate, one partition possibly contains multiple minerals, and at the moment, the acquisition of the X-ray energy spectrum of the partition can lead to misjudgment of the multiple minerals as one mineral. Thus, accurate zoning is the basis for accurate identification of minerals. According to the invention, the element distribution characteristics and the image gray level characteristics are combined, the double-factor control partition is used for accurately identifying different minerals which are similar in gray level and adjacently grown in a sample, so that accurate mineral distribution and content information is obtained, the technical defect that the existing automatic mineral analysis technology of the scanning electron microscope only utilizes gray level for mineral identification is overcome, and the method has important significance for accurate representation of mineral distribution and content.
Drawings
Other features, objects and advantages of the present application will become more apparent upon reading of the detailed description of non-limiting embodiments, made with reference to the following drawings, in which:
FIG. 1 is a schematic flow diagram of a method for identifying mineral distribution and content in accordance with an embodiment of the present invention;
FIG. 2 is a sample backscattered electron signal image of a method for identifying mineral distribution and content according to one embodiment of the invention;
FIG. 3 is a plot of the Na element surface of the same field of view for a method for identifying mineral distribution and content in accordance with an embodiment of the present invention;
FIG. 4 is a schematic illustration of the same field of view Na element concentration demarcation for a method of identifying mineral distribution and content according to one embodiment of the invention;
FIG. 5 is a superimposed image of the same field of view Na element concentration demarcation and the backscattered electron signal image of a method for identifying mineral distribution and content according to one embodiment of the invention;
FIG. 6 is a two-factor edge-controlled area image of a method for identifying mineral distribution and content in accordance with one embodiment of the present invention;
FIG. 7 is a two-factor controlled mineral profile of a method for identifying mineral distribution and content in accordance with one embodiment of the present invention;
FIG. 8 is a gray factor-only controlled mineral profile of a method for identifying mineral distribution and content in accordance with one embodiment of the present invention;
FIG. 9 is a schematic diagram of a system for identifying mineral distribution and content in accordance with the present invention;
FIG. 10 is a schematic diagram of a computer system suitable for use in implementing the electronic device of an embodiment of the present invention.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present invention more apparent, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention, and it is apparent that the described embodiments are some embodiments of the present invention, but not all embodiments of the present invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
The present application is described in further detail below with reference to the drawings and examples. It is to be understood that the specific embodiments described herein are merely illustrative of the invention and are not limiting of the invention. It should be noted that, for convenience of description, only the portions related to the present invention are shown in the drawings.
It should be noted that, in the case of no conflict, the embodiments and features in the embodiments may be combined with each other. The present application will be described in detail below with reference to the accompanying drawings in conjunction with embodiments.
A method for identifying mineral distribution and content according to a first embodiment of the invention, the method comprising:
step S100, obtaining a mineral sample to be identified; performing flatness treatment and conductivity enhancement treatment on the mineral sample to be identified to obtain a treated mineral sample, and performing back scattering electronic signal image acquisition on the treated mineral sample to obtain a back scattering electronic signal image;
step S200, acquiring element surface distribution information of the processed mineral sample in a set vision field to obtain an element surface distribution map; extracting element concentration boundaries in the element plane distribution map, and superposing the element concentration boundaries on the back-scattered electronic signal image, wherein the element concentration boundaries divide the back-scattered electronic signal image into a plurality of first-stage boundary regions; the first-stage boundary region is an element phase;
step S300, pixel gray scale identification is carried out on each level of demarcation zone one by one, so as to obtain pixel gray scale information; dividing each first-level boundary region according to the pixel gray information to obtain a second-level boundary region; the secondary boundary region is a two-factor edge control region, namely an element-gray phase;
and S400, collecting an X-ray energy spectrum of the double-factor edge control region to obtain an X-ray energy spectrum and element content information, and comparing the X-ray energy spectrum and the element content information with energy spectrum data stored in a mineral spectrum gallery to obtain the type, distribution and content information of minerals of the mineral sample to be identified in the set view.
In order to more clearly illustrate the method for identifying mineral distribution and content according to the invention, the steps of the method embodiment according to the invention are described in detail below with reference to the accompanying drawings.
A method for identifying mineral distribution and content, as shown in figure 1, the method comprising:
step S100, obtaining a mineral sample to be identified; performing flatness treatment and conductivity enhancement treatment on the mineral sample to be identified to obtain a treated mineral sample, and performing back scattering electronic signal image acquisition on the treated mineral sample to obtain a back scattering electronic signal image;
in this embodiment, the invention preferably uses argon ion polishing, since the surface of the mineral sample to be identified cannot be a fresh fracture surface, but must be a polished surface. Therefore, after the mineral sample (such as a sandstone sample) to be identified is obtained, the sandstone sample is subjected to polishing treatment, so that the flatness of the surface of the sample is ensured. Depending on the conductivity of the sample surface and the voltage and beam intensity used for the test, it may be selected whether or not to perform the plating treatment. When the conductivity of the sample is not strong or high voltage and large beam current are adopted in the test, the sample needs to be coated. Coating the sandstone sample (adopting a carbon film or a gold film for coating, wherein the carbon film is preferably coated), and the film thickness is 5-5 nm, and the carbon film is preferably 5nm; meanwhile, conductive glue solution is smeared on the side face of the sandstone sample so as to form a good lateral conductive channel. The backscattered electron signals may reflect gray scale information, so that the acquisition of the image of the backscattered electron signals is selected when observing the mineral composition of the sandstone sample. Randomly acquiring a back scattering electronic signal image of a sandstone sample, wherein the image size is preferably 235 x 176 mu m as shown in fig. 2; the image size is not limited to this size, and an image of an arbitrary size may be selected to be acquired. The accelerating voltage is 5-20 kV, the beam current is preferably 1-5 nA, the accelerating voltage is preferably 20kV, and the beam current is preferably 3nA in the present invention, wherein the accelerating voltage and the beam current are determined by the element with the largest atomic number in all the elements to be identified, and must be larger than the characteristic X-ray energy of the element (i.e. the element with the largest atomic number).
Step S200, acquiring element surface distribution information of the processed mineral sample in a set vision field to obtain an element surface distribution map; extracting element concentration boundaries in the element plane distribution map, and superposing the element concentration boundaries on the back-scattered electronic signal image, wherein the element concentration boundaries divide the back-scattered electronic signal image into a plurality of first-stage boundary regions; the first-stage boundary region is an element phase;
in this example, the minerals produced in the sandstone sample in close proximity and adjacent to each other were quartz and albite, wherein the quartz contains Si and O and the albite contains O, na, al, si, ca. The element surface distribution diagram of Na element is collected in the embodiment, as shown in FIG. 3; in the element face distribution map, the brighter the color is indicative of the higher the element concentration, the darker the color is indicative of the lower the element concentration, and the black is indicative of the region without the element distribution; the Na element concentration dividing line was extracted by using the color difference as shown in fig. 4.
And superposing the extracted Na element concentration boundary on the back-scattered electronic signal image of the same view to obtain a superposition image of the Na element concentration boundary and the back-scattered electronic signal image, as shown in fig. 5. The Na element concentration dividing line divides the field of view of the gray approximation in the backscattered electron signal image into a plurality of regions, which are referred to as a first-order boundary region, i.e. the element phase.
Step S300, pixel gray scale identification is carried out on each level of demarcation zone one by one, so as to obtain pixel gray scale information; dividing each first-level boundary region according to the pixel gray information to obtain a second-level boundary region; the secondary boundary region is a two-factor edge control region, namely an element-gray phase;
in this embodiment, pixel gray scale recognition is sequentially performed on each first-stage boundary region, and the pixel gray scale difference in some first-stage boundary regions is larger, so that a plurality of regions with different gray scales can be divided; some of the first-stage boundary regions have small pixel gray scale differences and cannot be further divided. After the pixel gray scales of all the first-stage boundary regions are identified and divided, a second-stage boundary region is obtained, which is a two-factor edge control region, namely, an element-gray scale phase (namely, gray scales represent a series of values from 0 to 255, and the difference value between two adjacent gray scales can be set to be larger than a certain value (namely, a difference value is set, and the difference value is set according to actual needs in other embodiments) in the actual processing process), and the boundary region is divided, as shown in fig. 6. The dual-factor edge control area is obtained by combining two factors of element concentration difference and pixel gray level difference, and the partitioning result is reliable.
And S400, collecting an X-ray energy spectrum of the double-factor edge control region to obtain an X-ray energy spectrum and element content information, and comparing the X-ray energy spectrum and the element content information with energy spectrum data stored in a mineral spectrum gallery to obtain the type, distribution and content information of minerals of the mineral sample to be identified in the set view.
In this embodiment, the dual-factor edge control region is subjected to X-ray energy spectrum acquisition to obtain X-ray energy spectrum and element content information, and the X-ray energy spectrum and element content information are compared with energy spectrum data stored in a mineral spectrum library (specifically, the acquired data comprise the X-ray energy spectrum and element content information, a range value is set by comparing the peak value of each element with the content of each element in the X-ray energy spectrum, and when the peak value and the content of each element are in a certain range, the energy spectrum data comprise the X-ray energy spectrum and the element content information of a mineral), and automatic mineral component analysis is performed to obtain an element-gray scale dual-factor control mineral distribution map (shown in fig. 7) and element-gray scale dual-factor control mineral component and content data (table 1) in a visual field. The mineral profile library may be self-contained in the software or built by the tester. The visual field contains quartz, albite, calcite and chlorite, wherein the area percentages are 44.56%, 34.63%, 19.73% and 1.07%, and the weight percentages are 44.16%, 34.32%, 20.22% and 1.30%, respectively.
TABLE 1
| Mineral name | Quartz | Albite feldspar | Calcite | Chlorite stone |
| Area percent | 44.56 | 34.63 | 19.73 | 1.07 |
| Weight percent | 44.16 | 34.32 | 20.22 | 1.30 |
The same view field only utilizes pixel gray information to divide the collected back scattering electronic signal image, and collects X-ray energy spectrogram and element content information; the acquired X-ray energy spectrum and element content information were compared with the energy spectrum data in the database for automatic mineral composition analysis to obtain gray factor-controlled mineral distribution maps alone (as shown in fig. 8) and gray factor-controlled mineral composition and content data alone (table 2) within the view. The visual field contains quartz, albite, calcite and chlorite, and the area percentages are respectively 48.03%, 31.47%, 19.44% and 1.06%, and the weight percentages are respectively 47.60%, 31.19%, 19.92% and 1.28%.
TABLE 2
| Mineral name | Quartz | Albite feldspar | Calcite | Chlorite stone |
| Area percent | 48.03 | 31.47 | 19.44 | 1.06 |
| Weight percent | 47.60 | 31.19 | 19.92 | 1.28 |
It can be seen that the mineral distribution and content information obtained by the two-factor control (element-gray scale) is greatly different from the mineral distribution and content information obtained by the one-factor control (gray scale), especially the distribution and content information of the quartz and albite grown adjacently and having similar gray scale. The distribution and content of minerals are related to the research of the rock causes and have important significance for the formulation of later mining development schemes. The mineral distribution can be accurately identified under the control of double factors, and accurate content information is obtained.
A system for identifying mineral distribution and content according to a second embodiment of the invention, as shown in fig. 9, comprises: a back scattering electronic signal acquisition module 100, an image superposition module 200, a region division module 300 and an X-ray energy spectrum acquisition module 400;
the back-scattered electronic signal acquisition module 100 is configured to acquire a mineral sample to be identified; performing flatness treatment and conductivity enhancement treatment on the mineral sample to be identified to obtain a treated mineral sample, and performing back scattering electronic signal image acquisition on the treated mineral sample to obtain a back scattering electronic signal image;
the image superposition module 200 is configured to collect the element plane distribution information of the processed mineral sample in a set view field to obtain an element plane distribution map; extracting element concentration boundaries in the element plane distribution map, and superposing the element concentration boundaries on the back-scattered electronic signal image, wherein the element concentration boundaries divide the back-scattered electronic signal image into a plurality of first-stage boundary regions; the first-stage boundary region is an element phase;
the area dividing module 300 is configured to perform pixel gray scale identification on each level of demarcation region one by one to obtain pixel gray scale information; dividing each first-level boundary region according to the pixel gray information to obtain a second-level boundary region; the secondary boundary region is a two-factor edge control region, namely an element-gray phase;
the X-ray spectrum acquisition module 400 is configured to acquire an X-ray spectrum of the dual-factor edge control region, obtain an X-ray spectrum and element content information, and compare the X-ray spectrum and the element content information with energy spectrum data stored in a mineral spectrum gallery to obtain the type, distribution and content information of minerals of the mineral sample to be identified in the set view.
It should be noted that, the system for identifying mineral distribution and content provided in the foregoing embodiment is only exemplified by the division of the foregoing functional modules, and in practical application, the foregoing functional distribution may be implemented by different functional modules according to needs, that is, the modules or steps in the foregoing embodiment of the present invention are further decomposed or combined, for example, the modules in the foregoing embodiment may be combined into one module, or may be further split into multiple sub-modules to implement all or part of the functions described above. The names of the modules and steps related to the embodiments of the present invention are merely for distinguishing the respective modules or steps, and are not to be construed as unduly limiting the present invention.
An electronic device of 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 for execution by the processor to implement a method for identifying mineral distribution and content as described above.
A fourth embodiment of the invention is a computer readable storage medium storing computer instructions for execution by the computer to implement a method for identifying mineral distribution and content as described above.
It will be clear to those skilled in the art that, for convenience and brevity of description, specific working processes of the electronic device, the computer readable storage medium and related descriptions of the electronic device and the computer readable storage medium described above may refer to corresponding processes in the foregoing method examples, which are not described herein again.
Reference is now made to FIG. 10, which is a block diagram illustrating a computer system suitable for use in implementing embodiments of the methods, systems, and apparatus of the present application. The server illustrated in fig. 10 is merely an example, and should not impose any limitation on the functionality and scope of use of the embodiments of the present application.
As shown in fig. 10, the computer system includes a central processing unit (CPU, central Processing Unit) 1001 which can perform various appropriate actions and processes according to a program stored in a Read Only Memory (ROM) 1002 or a program loaded from a storage section 1008 into a random access Memory (RAM, random Access Memory) 1003. In the RAM1003, various programs and data required for system operation are also stored. The CPU 1001, ROM 1002, and RAM1003 are connected to each other by a bus 1004. An Input/Output (I/O) interface 1005 is also connected to bus 1004.
The following components are connected to the I/O interface 1005: an input section 1006 including a keyboard, a mouse, and the like; an output portion 1007 including a Cathode Ray Tube (CRT), a liquid crystal display (LCD, liquid Crystal Display), and a speaker; a storage portion 1008 including a hard disk or the like; and a communication section 1009 including a network interface card such as a LAN (local area network ) card, a modem, or the like. The communication section 1009 performs communication processing via a network such as the internet. The drive 1010 is also connected to the I/O interface 1005 as needed. A removable medium 1011, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, or the like, is installed as needed in the drive 1010, so that a computer program read out therefrom is installed as needed in the storage section 1008.
In particular, according to embodiments of the present invention, the processes described above with reference to flowcharts may be implemented as computer software programs. For example, embodiments of the present invention include a computer program product comprising a computer program embodied on a computer readable medium, the computer program comprising program code for performing the method shown in the flowcharts. In such an embodiment, the computer program may be downloaded and installed from a network via the communication portion 1009, and/or installed from the removable medium 1011. The above-described functions defined in the method of the present application are performed when the computer program is executed by a Central Processing Unit (CPU) 1001. It should be noted that the computer readable medium described in the present application may be a computer readable signal medium or a computer readable storage medium, or any combination of the two. The computer readable storage medium can be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or a combination of any of the foregoing. More specific examples of the computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the context of this document, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In the present application, however, a computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, with computer-readable program code embodied therein. Such a propagated data signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination of the foregoing. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wire, fiber optic cable, RF, etc., or any suitable combination of the foregoing.
Computer program code for carrying out operations of the present application may be written in one or more programming languages, including an object oriented programming language such as Java, smalltalk, C ++ and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to an external computer (for example, through the Internet using an Internet service provider).
The flowcharts 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 objects and not for describing a particular sequential or chronological order.
The terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus/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/apparatus.
Thus far, the technical solution of the present invention has been described in connection with the preferred embodiments shown in the drawings.
The foregoing is merely exemplary of the present application and is not intended to limit the present application. Various modifications and changes may be made to the present application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc. which are within the spirit and principles of the present application are intended to be included within the scope of the claims of the present application.
Claims (9)
1. A method for identifying mineral distribution and content, the method comprising:
step S100, obtaining a mineral sample to be identified; performing flatness treatment and conductivity enhancement treatment on the mineral sample to be identified to obtain a treated mineral sample, and performing back scattering electronic signal image acquisition on the treated mineral sample to obtain a back scattering electronic signal image;
step S200, acquiring element surface distribution information of the processed mineral sample in a set vision field to obtain an element surface distribution map; extracting element concentration boundaries in the element plane distribution map, and superposing the element concentration boundaries on the back-scattered electronic signal image, wherein the element concentration boundaries divide the back-scattered electronic signal image into a plurality of first-stage boundary regions; the first-stage boundary region is an element phase;
step S300, pixel gray scale identification is carried out on each level of demarcation zone one by one, so as to obtain pixel gray scale information; dividing each first-level boundary region according to the pixel gray information to obtain a second-level boundary region; the secondary boundary region is a two-factor edge control region, namely an element-gray phase;
and S400, collecting an X-ray energy spectrum of the double-factor edge control region to obtain an X-ray energy spectrum and element content information, and comparing the X-ray energy spectrum and the element content information with energy spectrum data stored in a mineral spectrum gallery to obtain the type, distribution and content information of minerals of the mineral sample to be identified in the set view.
2. A method for identifying mineral distribution and content according to claim 1, wherein the mineral sample to be identified is any one of sedimentary, metamorphic, volcanic and merle;
the mineral sample to be identified is a block sample or a granular sample from micron level to centimeter level;
the granular sample is a sample embedded by resin.
3. A method for identifying mineral distribution and content according to claim 1, characterized in that the mineral sample to be identified is subjected to a flatness process, which method comprises: and polishing the mineral sample to be identified.
4. A method for identifying mineral distribution and content according to claim 1, characterized in that the mineral sample to be identified is subjected to a conductivity enhancing treatment, which method comprises:
coating a film on the mineral sample to be identified and/or smearing conductive glue;
wherein, the carbon film or the gold film is adopted for coating, and the thickness of the coating is 5-15 nm;
and when conducting glue solution smearing treatment is carried out, conducting glue solution is smeared on the side face of the mineral sample to be identified.
5. A method for identifying mineral distribution and content according to claim 1, wherein, when collecting the information of the distribution of the element surface of the treated mineral sample in the set view, the collected element types include a single element or a plurality of elements; each element corresponds to an element face profile.
6. The method for identifying mineral distribution and content according to claim 1, wherein when the processed mineral sample is subjected to back scattering electronic signal image acquisition, the acceleration voltage is 5-20 kv, and the beam current is 1-5 na; the acceleration voltage and the beam current are used to excite X-ray signals.
7. A system for identifying mineral distribution and content, the system comprising: the system comprises a back scattering electronic signal acquisition module, an image superposition module, a region division module and an X-ray energy spectrum acquisition module;
the back scattering electronic signal acquisition module is configured to acquire a mineral sample to be identified; performing flatness treatment and conductivity enhancement treatment on the mineral sample to be identified to obtain a treated mineral sample, and performing back scattering electronic signal image acquisition on the treated mineral sample to obtain a back scattering electronic signal image;
the image superposition module is configured to acquire element surface distribution information of the processed mineral sample in a set vision field to obtain an element surface distribution map; extracting element concentration boundaries in the element plane distribution map, and overlapping the element concentration boundaries on the back-scattered electronic signal image to divide the back-scattered electronic signal image into a plurality of first-stage boundary regions; the first-stage boundary region is an element phase;
the region dividing module is configured to recognize pixel gray scales of each level of demarcation region one by one to obtain pixel gray scale information; dividing each first-level boundary region according to the pixel gray information to obtain a second-level boundary region; the secondary boundary region is a two-factor edge control region, namely an element-gray phase;
the X-ray energy spectrum acquisition module is configured to acquire an X-ray energy spectrum of the double-factor edge control area to obtain an X-ray energy spectrum and element content information, and compare the X-ray energy spectrum and the element content information with energy spectrum data stored in a mineral spectrum gallery to obtain the type, distribution and content information of minerals of the mineral sample to be identified in the set view.
8. 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 execution by the processor to implement a method for identifying mineral distribution and content according to any one of claims 1-6.
9. A computer readable storage medium having stored thereon computer instructions for execution by the computer to implement a method for identifying mineral distribution and content according to any of claims 1-6.
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