Method for determining type and relative content of mica ore

Abstract

The invention provides a method for determining the type and the relative content of mica ore, and relates to the technical field of mineral measurement, the method comprises the following steps: crushing, grinding and polishing mica ore to be detected to obtain a plurality of mica particles; respectively carrying out in-situ micro-area analysis on the plurality of mica particles, and calculating the characteristic element content ratio of the plurality of mica particles; determining the type of the to-be-detected mica ore according to the content ratio of the characteristic elements to obtain the type of the mica ore; scanning and imaging the plurality of mica particles, and measuring the areas of different types of mica in the plurality of mica particles; calculating according to the areas of different types of mica to obtain the proportion of the target type of mica; and calculating the total mica mineral amount of the to-be-detected mica ore, and obtaining the relative content of the target type of mica mineral according to the total mica mineral amount and the proportion of the target type of mica. According to the method, the mica classification accuracy is improved, the content of different types of mica is accurately calculated, and an accurate basis is provided for lepidolite grading production guidance.

Description

Technical Field

[0001] The present invention relates to the technical field of mineral measurement, and particularly relates to a method for determining the type and relative content of mica ore. Background Art

[0002] With the rapid development of the new energy lithium battery industry, the demand for lithium resources has surged, and mica ore has become an important strategic resource due to its rich lithium reserves. However, due to multiple stages of magmatic-fluid evolution, the types of lithium-bearing mica minerals are complex, and the distribution of lithium content is extremely uneven, seriously affecting the utilization value of lithium ore and the design of ore dressing processes.

[0003] Traditional methods can only classify lithium-bearing mica into a single category and rely on chemical analysis to obtain total data, but cannot divide sub-categories based on the differences in LiO content and FeO content and determine the content of each type of mica. The LiO content and FeO content of different mica sub-types in lithium ore directly affect the selection of ore dressing processes and the quality of concentrates. Existing technologies can only quantify all mica as a whole and cannot classify and quantify each type of lithium-bearing mica through quantitative characterization means, resulting in great blindness in the design of ore dressing processes and low resource utilization rate. Therefore, there is an urgent need for a method to solve the problem that lithium-bearing mica in mica ore cannot be classified and quantified by quantitative characterization means. Summary of the Invention

[0004] In view of the above deficiencies of the prior art, the present invention provides a method for determining the type and relative content of mica ore, which effectively solves the problem that lithium-bearing mica in mica ore cannot be classified and quantified by quantitative characterization means.

[0005] In a first aspect, the present invention provides a method for determining the type and relative content of mica ore, the method comprising:

[0006] Crushing and polishing a mica ore to be detected to obtain a plurality of mica particles;

[0007] Performing in-situ micro-area analysis on each of the plurality of mica particles, and calculating the characteristic element content ratio of the plurality of mica particles;

[0008] Determining the type of the mica ore to be detected according to the characteristic element content ratio to obtain the mica ore type;

[0009] Performing scanning imaging on the plurality of mica particles, and measuring the areas of different types of mica in the plurality of mica particles;

[0010] Calculating according to the areas of different types of mica to obtain the proportion of the target type of mica;

[0011] Calculate the total mica mineral content of the mica ore to be detected, and obtain the relative content of the target type mica minerals based on the total mica mineral content and the proportion of the target type mica.

[0012] In an alternative embodiment, the in-situ micro-area analysis is respectively performed on the multiple mica particles, and the characteristic element content ratios of the multiple mica particles are calculated, including:

[0013] Quantitatively analyze the characteristic element components of the multiple mica particles by using an electron probe to obtain the characteristic element component contents;

[0014] Perform calculations based on the characteristic element component contents to obtain the characteristic element content ratios.

[0015] In an alternative embodiment, the characteristic element components at least include SiO2, Al2O3, F, FeO, MgO, K2O, and Rb2O.

[0016] In an alternative embodiment, the calculation formula for the characteristic element content ratio is as follows:

[0017]

[0018] In the above formula, Q represents the characteristic element content ratio, represents the SiO2 component content, C F represents the F component content, represents the Al2O3 component content.

[0019] In an alternative embodiment, the method for determining the type of the mica ore to be detected based on the characteristic element content ratio and obtaining the mica ore type includes:

[0020] If the characteristic element content ratio is greater than or equal to 1.8, it is determined that the mica ore to be detected is a lepidolite-type mineral;

[0021] If the characteristic element content ratio is greater than or equal to 1.5 and less than 1.8, calculate the Li2O content based on the characteristic element component contents. If the Li2O content is greater than or equal to 2.5%, it is determined that the mica ore to be detected is a lepidolite-type mineral. If the Li2O content is less than 2.5%, it is determined that the mica ore to be detected is a muscovite-type mineral;

[0022] If the characteristic element content ratio is less than 1.5, it is determined that the mica ore to be detected is a muscovite-type mineral.

[0023] In an alternative embodiment, the method for determining the type of the mica ore to be detected based on the characteristic element content ratio and obtaining the mica ore type further includes:

[0024] If the mica ore to be detected is the lepidolite-type mineral, obtain the FeO content of the mica ore to be detected;

[0025] If the FeO content is greater than or equal to 2%, determine that the mica ore to be detected is zinnwaldite; if the FeO content is less than 2%, determine that the mica ore to be detected is lepidolite;

[0026] If the mica ore to be detected is the muscovite-type mineral, calculate the Li2O content of the mica ore to be detected;

[0027] If the Li2O content is greater than or equal to 0, determine that the mica ore to be detected is lithium-bearing muscovite; if the Li2O content is 0, determine that the mica ore to be detected is muscovite.

[0028] In an alternative embodiment, the scanning and imaging of the plurality of mica particles to measure the areas of different types of mica in the plurality of mica particles includes:

[0029] Scanning the plurality of mica particles with a scanning electron microscope to obtain a backscattered image of the mica particles;

[0030] Performing image processing on the backscattered image of the mica particles to demarcate the boundaries of different types of mica;

[0031] Measuring according to the boundaries of different types of mica to obtain the areas of different types of mica.

[0032] In an alternative embodiment, calculating the proportion of the target type of mica according to the areas of different types of mica includes:

[0033] Statistically analyzing the areas of different types of mica to obtain the total area of all the mica particles;

[0034] Determine the area of the target type of mica according to the areas of different types of mica;

[0035] Determine the ratio of the area of the target type of mica to the total area as the proportion of the target type of mica.

[0036] In an alternative embodiment, calculating the total amount of mica minerals in the mica ore to be detected includes:

[0037] Analyze the content of K2O in the mica ore to be detected by the total dissolution sample method to obtain the mineral K2O content;

[0038] Detect the K2O content of non-mica minerals in the mica ore to be detected, and obtain the K2O content of mica minerals based on the mineral K2O content and the K2O content of non-mica minerals;

[0039] Calculate the average K2O content of the mica ore to be detected based on the K2O contents of multiple said mica particles;

[0040] Perform calculations based on the K2O content of the mica mineral and the average K2O content to obtain the total mica mineral amount of the mica ore to be detected.

[0041] In an optional embodiment, the calculation formula for the relative content of the target type of mica mineral is as follows:

[0042] C X = C × D X

[0043] In the above formula, C X represents the relative content of the target type of mica mineral, C represents the total mica mineral amount, and D X represents the proportion occupied by the target type of mica.

[0044] The method for determining the type and relative content of mica ore provided by the present invention determines the type of mica ore by calculating the characteristic element content range of mica particles, improving the accuracy of mica subclass classification and the reliability of analysis. At the same time, weight assignment is carried out using the light and dark differences of backscattered images to achieve accurate calculation of the contents of different types of mica, effectively identifying different types of mica with complex intergrowth relationships and realizing mineral quantification respectively. Based on the accurate mineral quantification results, the beneficiation process parameters can be optimized, thereby providing a more accurate basis for guiding the separation production of lepidolite, optimizing the separation process according to the classification and quantification results, and improving the separation efficiency and product quality. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following will briefly introduce the drawings required for use in the embodiments. It should be understood that the following drawings only show some embodiments of the present invention, and therefore should not be regarded as limiting the scope. For those of ordinary skill in the art, other related drawings can be obtained based on these drawings without creative efforts.

[0046] Figure 1 is a schematic flow chart of the method for determining the type and relative content of mica ore provided by the embodiment of the present invention;

[0047] Figure 2 is a schematic diagram of the backscattered image of mica particles in the embodiment of the present invention;

[0048] Figure 3 is a schematic diagram of the boundary division of different types of mica in the embodiment of the present invention;

[0049] Figure 4It is a schematic diagram of the boundary division and area statistics of the backscattered images of two mica particles in the embodiments of the present invention. Detailed implementation manners

[0050] To make the objectives, technical solutions, and advantages of the present invention clearer, the technical solutions of the present invention will be further described clearly and completely below in conjunction with the accompanying drawings in the embodiments of the present invention. It should be noted that the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts fall within the scope of protection of the present invention.

[0051] In addition, the terms "first" and "second" are only used for descriptive purposes and cannot be construed as indicating or implying relative importance or implicitly specifying the quantity of the indicated technical features. Thus, the features defined with "first" and "second" may explicitly or implicitly include one or more of such features. In the description of the present invention, "a plurality" means two or more, unless otherwise specifically defined.

[0052] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those of ordinary skill in the technical field to which this application belongs. The terms used in the specification of the present invention are only for the purpose of describing specific embodiments and are not intended to limit the present invention. The term "and / or" used herein includes any and all combinations of one or more of the related listed items.

[0053] Classifying mica ores according to their lithium content and achieving quantification for each type is of great significance for establishing the availability of mica ores and the quality of subsequent beneficiated concentrates. Existing conventional technical methods can only classify lepidolite mica into one large category and calculate the total amount of mica minerals through chemical analysis, and cannot calculate the individual mineral amounts of different types of mica containing Li2O separately.

[0054] Although a mineral automatic analysis system can also directly give the contents of muscovite and lepidolite, since the scanning electron microscope energy spectrum cannot directly measure the Li2O content, this method completely relies on the brightness difference under the backscattered image of the mineral microscopic image to divide the two types of mica, and the accuracy of the data often deviates due to different instrument operating conditions, set brightness conditions, etc. At the same time, this method can only classify muscovite and lepidolite, and further types such as lithium-bearing muscovite and zinnwaldite cannot be refined and distinguished. Therefore, there is an urgent need for a method to solve the problem that mica lithium ores cannot be classified and quantified for each type of lithium-bearing mica by quantitative characterization means.

[0055] Embodiment 1

[0056] An embodiment of the present invention provides a method for determining the type and relative content of mica ore. By combining chemical multi-element analysis and mineral microscopic image division, the relative contents of muscovite, lithium-bearing muscovite, zinnwaldite, and lepidolite in mica ore can be quantitatively determined. Figure 1 It is a schematic flowchart of the method for determining the type and relative content of mica ore provided by an embodiment of the present invention. As Figure 1 shown, the method includes the following steps:

[0057] S100. Crush and polish the mica ore to be detected to obtain a plurality of mica particles.

[0058] In an embodiment of the present invention, the mica ore to be detected is crushed into particles with a size of less than 0.1 mm. After mixing and quartering, the particulate sample is embedded and consolidated with a mold and epoxy resin and subjected to multiple polishing treatments, so as to make an epoxy resin polished section with a smooth surface that can be used for scanning electron microscope observation. The epoxy resin polished section includes a plurality of mica particles.

[0059] S200. Perform in-situ micro-area analysis on the plurality of mica particles respectively, and calculate the characteristic element content ratios of the plurality of mica particles.

[0060] In an embodiment of the present invention, an electron probe can be used to perform high-precision in-situ micro-area element analysis on mica particles to obtain the characteristic element composition contents of each mica particle. The electron probe can accurately determine the types and contents of various elements in mica particles by focusing the electron beam on a tiny area, providing key data for studying mica genesis, type classification, and quality evaluation. In an embodiment of the present invention, the characteristic element composition contents include, but are not limited to, the element composition contents such as SiO2, Al2O3, F, FeO, MgO, K2O, and Rb2O.

[0061] Calculate the characteristic element content ratio Q through the element composition contents of SiO2, Al2O3, and F. The calculation formula of the characteristic element content ratio Q is as follows:

[0062]

[0063] In the above formula, Q represents the characteristic element content ratio, represents the SiO2 composition content, C F represents the F composition content, represents the Al2O3 composition content.

[0064] S300. Determine the type of the mica ore to be detected according to the characteristic element content ratio to obtain the mica ore type.

[0065] In an embodiment of the present invention, the type of the mica ore to be detected is determined according to the calculated characteristic element content ratio Q to obtain the mica ore type, specifically as follows:

[0066] If the ratio Q of the characteristic element contents is greater than or equal to 1.8, it is determined that the mica ore to be detected is a lepidolite-type mineral. If the ratio Q of the characteristic element contents is less than 1.5, it is determined that the mica ore to be detected is a muscovite-type mineral. When the ratio Q of the characteristic element contents is greater than or equal to 1.5 and less than 1.8, it is necessary to determine the content range of the corresponding element components according to the characteristic element component contents, and then select a suitable empirical formula according to the content range to calculate the Li2O content. Table 1 is a schematic table of the empirical formula for calculating the Li2O content in mica.

[0067] Table 1. Schematic table of the empirical formula for calculating the Li2O content in mica

[0068]

[0069] In Table 1, C MgO 、C F and respectively represent the Li2O component content, SiO2 component content, MgO component content, F component content and Rb2O component content.

[0070] Select the empirical formula according to Table 1 to calculate the Li2O content. If the Li2O content is greater than or equal to 2.5%, it is determined that the mica ore to be detected is a lepidolite-type mineral. If the Li2O content is less than 2.5%, it is determined that the mica ore to be detected is a muscovite-type mineral.

[0071] Furthermore, for lepidolite-type minerals, the lepidolite and triphylite can be further distinguished by the FeO content of the mica ore to be detected. If the FeO content is greater than or equal to 2%, it is determined that the mica ore to be detected is triphylite. If the FeO content is less than 2%, it is determined that the mica ore to be detected is lepidolite.

[0072] Furthermore, for muscovite-type minerals, the content range of the corresponding element components can be determined again according to the characteristic element component contents, and then a suitable empirical formula can be selected according to the content range to calculate the Li2O content. The lithium-bearing muscovite and muscovite can be further distinguished by the Li2O content of the mica ore to be detected. Table 2 is a schematic table of the empirical formula for calculating the lithium content of muscovite-type minerals.

[0073] Table 2. Schematic table of the empirical formula for calculating the Li2O content of muscovite-type minerals

[0074]

[0075] In Table 2, C F and respectively represent the Li2O component content, F component content and Rb2O component content.

[0076] Select an empirical formula according to Table 2 to calculate the Li2O content. If the Li2O content in muscovite minerals is greater than or equal to 0, it is determined that the mica ore to be detected is lithium-bearing muscovite. If the Li2O content is 0, it is determined that the mica ore to be detected is muscovite.

[0077] S400. Perform scanning imaging on multiple mica particles and measure the areas of different types of mica in the multiple mica particles.

[0078] In the embodiment of the present invention, a scanning electron microscope is used to scan multiple mica particles to obtain mica particle images. Specifically, an epoxy resin polished slice is placed under the scanning electron microscope, and the voltage of the scanning electron microscope is controlled to be constant at 20 kV and the current is constant at 2.0 nA. The imaging of the mineral backscattered image of the mica particles is adjusted by increasing the contrast and reducing the brightness. Figure 2 This is a schematic diagram of the backscattered image of mica particles in the embodiment of the present invention. As Figure 2 shown, the brightness and black-and-white of different types of mica particles are made to be different, so that the boundaries are clear.

[0079] For the backscattered image of mica particles obtained by the scanning electron microscope, image processing software is used for image processing to divide the boundaries of different types of mica. Figure 3 This is a schematic diagram of the boundary division of different types of mica in the embodiment of the present invention. As Figure 3 shown, lepidolite is marked as S, ferro-lepidolite is marked as F, lithium-bearing muscovite is marked as H, and muscovite is marked as M.

[0080] Then, according to the boundaries of different types of mica, measurements are made to obtain the areas of different types of mica. Taking the i-th mica particle as an example, the area of lepidolite measured is S i , the area of ferro-lepidolite measured is F i , the area of lithium-bearing muscovite measured is H i , and the area of muscovite measured is M i .

[0081] S500. Calculate according to the areas of different types of mica to obtain the proportion of the target type of mica.

[0082] In the embodiment of the present invention, statistics are made according to the areas of different types of mica to obtain the total area of all mica particles, and at the same time, the area of the target type of mica is determined. The proportion of the target type of mica is determined according to the ratio of the area of the target type of mica to the total area.

[0083] Specifically, if a total of n mica particles are measured cumulatively, the mica areas of each type of mica are respectively counted, where the mica area of the lepidolite type mica is the mica area of the ferro-lepidolite type mica is the mica area of the lithium-bearing muscovite type mica is The area of muscovite-type mica is Then the total area of all mica particles is

[0084] The calculation formula for the proportion of the target-type mica is as follows:

[0085]

[0086] In the above formula, represents the area of the target-type mica, and the target-type mica can be lepidolite, triphylite, lithium-bearing muscovite, and muscovite.

[0087] When the types of mica in the mica ore to be detected are more complex, the number of mica particles to be observed is more. Generally, when there are two types of mica at the same time, the number of mica particles to be observed should be more than 150. When the number of observed mica particles is larger, the finally obtained data can better represent the overall situation of the mica ore to be detected.

[0088] S600. Calculate the total mica mineral amount of the mica ore to be detected, and obtain the relative content of the target-type mica mineral according to the total mica mineral amount and the proportion of the target-type mica.

[0089] In the embodiment of the present invention, the chemical analysis quantitative method is used to calculate the total mica mineral amount of the mica ore to be detected, specifically as follows:

[0090] First, analyze the content of K2O in the mica ore to be detected by the total dissolution sample method to obtain the mineral K2O content Wt%. Then detect the K2O content Wt (非云母) % of the non-mica minerals in the mica ore to be detected, and obtain the K2O content of the mica minerals according to the mineral K2O content and the K2O content of the non-mica minerals. Specifically, determine whether there are other K2O-containing minerals in the mica ore to be detected. If there are no other K2O-containing minerals, the K2O content Wt (云母) % is Wt%, and if there are other K2O-containing minerals, the K2O content Wt (云母) % = Wt% - Wt (非云母) %.

[0091] Then calculate the average K2O content of the mica ore to be detected according to the K2O content of multiple mica particles. Specifically, calculate the arithmetic mean of the K2O content of all mica particles obtained in step S200 to obtain the average K2O content m of the mica ore to be detected. Finally, calculate according to the K2O content of the mica minerals and the average K2O content to obtain the total mica mineral amount of the mica ore to be detected. The calculation formula for the total mica mineral amount is as follows:

[0092]

[0093] In the above formula, C represents the total amount of mica minerals in the mica ore to be detected, in Wt (云母) %, represents the K2O content of the mica mineral, and m represents the average K2O content of the mica ore to be detected.

[0094] The relative content of the target type mica mineral is obtained based on the total amount of mica minerals and the proportion of the target type mica. The calculation formula for the relative content of the target type mica mineral is as follows:

[0095] C X = C × D X

[0096] In the above formula, C X represents the relative content of the target type mica mineral. The target type mica can be lepidolite, ferro-lepidolite, lithium-bearing muscovite, and muscovite. C represents the total amount of mica minerals in the mica ore to be detected, and D X represents the proportion of the target type mica.

[0097] As a more specific implementation manner of the embodiment of the present invention, in order to verify the effectiveness of the method for determining the type and relative content of mica ore provided by the embodiment of the present invention, a certain granite-type lepidolite ore is selected as the ore sample for verification.

[0098] The main minerals of this ore sample are albite, quartz, potassium feldspar, and mica, etc. The ore sample is crushed to a particle size below 0.1 mm, and after mixing and quartering, an appropriate amount of granular sample is taken to make an epoxy resin polished section for scanning electron microscope observation.

[0099] In-situ micro-area analysis is carried out on the mica particles in the epoxy resin polished section by using an electron probe to obtain the contents of elements such as SiO2, Al2O3, FeO, and F in 197 mica particles, and the characteristic element content ratio Q calculated is shown in Table 3.

[0100] Table 3. In-situ micro-area content analysis table of main elements of mica particles in a certain granite-type lepidolite ore

[0101]

[0102] Based on Table 3, the types of each mica particle are divided according to the characteristic element content ratio Q of each mica particle. It can be seen from Table 3 that the characteristic element content ratio Q values appear in three range intervals at the same time, and it is preliminarily judged that there are multiple types of mica existing at the same time.

[0103] Mica particles with the characteristic element content ratio Q greater than or equal to 1.8 are preliminarily determined as lepidolite-type minerals, and they are further classified as lepidolite or triphylite according to the FeO content therein. The FeO content of all mica particles with the characteristic element content ratio Q greater than or equal to 1.8 in Table 3 is greater than 2%, so it can be determined that this part of mica particles is triphylite.

[0104] Mica particles with the characteristic element content ratio Q less than 1.5 are preliminarily determined as muscovite-type minerals, and they are further classified as lithium-bearing muscovite or muscovite according to the Li2O content therein. The Li2O content of all mica particles with the characteristic element content ratio Q less than 1.5 in Table 3 is greater than 0, so it can be determined that this part of mica particles is lithium-bearing muscovite.

[0105] For mica particles with the characteristic element content ratio Q greater than or equal to 1.5 and less than 1.8, calculate the Li2O content therein. The Li2O content of all mica particles with the characteristic element content ratio Q greater than or equal to 1.5 and less than 1.8 in Table 3 is greater than 0 but less than 2.5%, so it can be determined that this part of mica particles is lithium-bearing muscovite.

[0106] In summary, it can be confirmed that there are actually two types of mica, namely lithium-bearing muscovite and triphylite, in this granite-type lepidolite ore.

[0107] For the divided mica types and their corresponding mica particles and regions, control the current and voltage under the scanning electron microscope, and by increasing the contrast of the image while reducing the brightness, Figure 4 It is a schematic diagram of the boundary division and area statistics of the backscattered images of two mica particles in the embodiment of the present invention. As Figure 4 shown, make the images between triphylite and lithium-bearing muscovite have obvious light and dark differences, and use the image processing software AsioVision to measure the areas of the two types of mica respectively. The area of triphylite is recorded as F i , and the area of lithium-bearing muscovite is recorded as H i . A total of 160 mica particles are measured cumulatively, and the areas of lepidolite and muscovite are respectively recorded in Table 4.

[0108] Table 4. Statistical table of the areas of different types of mica

[0109]

[0110] According to Table 4, the total area of triphylite is obtained by statistics as The total area of lithium-bearing muscovite is Therefore, the proportion of triphylite is: D F = 1585233 / (1585233 + 10430316) = 13.19%, and the proportion of lithium-bearing muscovite is: D H= 10430316 / (1585233 + 10430316) = 86.81%.

[0111] Using chemical analysis and quantification method, the total mineral content C of mica in the ore sample was calculated to be 16.78%. Therefore, the relative content of lepidolite minerals is C F = C × D F = 2.21%, and the relative content of muscovite minerals C H = C × D H = 14.57%.

[0112] In summary, the method for determining the type and relative content of mica ore provided by the present invention determines the type of mica ore by calculating the characteristic element content range of mica particles, improving the accuracy of mica subclass classification and the reliability of analysis. At the same time, weight assignment is carried out using the light and dark differences of backscattered images to achieve accurate calculation of the content of different types of mica, effectively identifying different types of mica with complex intergrowth relationships and realizing mineral quantification respectively. Based on the accurate mineral quantification results, the beneficiation process parameters can be optimized, thus providing a more accurate basis for the production guidance of lepidolite separation, optimizing the separation process according to the classification and quantification results, and improving the separation efficiency and product quality.

[0113] References to "embodiments" in this specification mean that the particular features, structures, or characteristics described in connection with the embodiments can be included in at least one embodiment of the present application. The phrase appears in various places in the specification and does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment mutually exclusive with other embodiments. Those skilled in the art will explicitly and implicitly understand that the embodiments described herein can be combined with other embodiments.

[0114] The above-described embodiments merely represent several implementation manners of the present invention, and their descriptions are relatively specific and detailed, but should not be construed as limiting the scope of the present invention. It should be noted that for those of ordinary skill in the art, without departing from the concept of the present invention, several modifications and improvements can be made, and these all belong to the protection scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the appended claims.

[0115] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements for some of the technical features; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the various embodiments of the present invention.

Claims

1. A method for determining the type and relative content of mica ore, characterized in that, The method includes: Crushing and grinding a mica ore to be detected to obtain a plurality of mica particles; Performing in-situ micro-area analysis on the plurality of mica particles respectively, and calculating the characteristic element content ratio of the plurality of mica particles; Determining the type of the mica ore to be detected according to the characteristic element content ratio to obtain the mica ore type; Performing scanning imaging on the plurality of mica particles, and measuring the areas of different types of mica in the plurality of mica particles; Calculating according to the areas of different types of mica to obtain the proportion of the target type of mica; Calculating the total mica mineral amount of the mica ore to be detected, and obtaining the relative content of the target type of mica mineral according to the total mica mineral amount and the proportion of the target type of mica; 2. The method for determining the type and relative content of mica ore according to claim 1, characterized in that, The performing in-situ micro-area analysis on the plurality of mica particles respectively, and calculating the characteristic element content ratio of the plurality of mica particles includes: Using an electron probe to quantitatively analyze the characteristic element composition of the plurality of mica particles to obtain the characteristic element composition content; Calculating according to the characteristic element composition content to obtain the characteristic element content ratio; 3. The method for determining the type and relative content of mica ore according to claim 2, wherein The characteristic element composition at least includes SiO2, Al2O3, F, FeO, MgO, K2O and Rb2O; 4. The method for determining the type and relative content of mica ore according to claim 3, characterized in that, The calculation formula of the characteristic element content ratio is as follows: In the above formula, Q represents the ratio of characteristic element contents, C SiO2 represents the content of SiO2 component, C F represents the content of F component, C Al2O3 represents the content of Al2O3 component.

5. The method for determining the type and relative content of mica ore according to claim 4, characterized in that The determining the type of the mica ore to be detected according to the characteristic element content ratio to obtain the mica ore type includes: If the characteristic element content ratio is greater than or equal to 1.8, it is determined that the mica ore to be detected is a lepidolite-type mineral; If the characteristic element content ratio is greater than or equal to 1.5 and less than 1.8, calculate the Li2O content according to the characteristic element composition content. If the Li2O content is greater than or equal to 2.5%, it is determined that the mica ore to be detected is a lepidolite-type mineral. If the Li2O content is less than 2.5%, it is determined that the mica ore to be detected is a muscovite-type mineral; If the characteristic element content ratio is less than 1.5, it is determined that the mica ore to be detected is a muscovite-type mineral; 6. The method for determining the type and relative content of mica ore according to claim 5, characterized in that The determining the type of the mica ore to be detected according to the characteristic element content ratio to obtain the mica ore type further includes: If the mica ore to be detected is the lepidolite-type mineral, obtain the FeO content of the mica ore to be detected; If the FeO content is greater than or equal to 2%, it is determined that the mica ore to be detected is zinnwaldite. If the FeO content is less than 2%, it is determined that the mica ore to be detected is lepidolite; If the mica ore to be detected is the muscovite-type mineral, calculate the Li2O content of the mica ore to be detected; If the Li2O content is greater than or equal to 0, it is determined that the mica ore to be detected is lithium-bearing muscovite. If the Li2O content is 0, it is determined that the mica ore to be detected is muscovite; 7. The method for determining the type and relative content of mica ore according to claim 1, characterized in that, The performing scanning imaging on the plurality of mica particles, and measuring the areas of different types of mica in the plurality of mica particles includes: Using a scanning electron microscope to scan the plurality of mica particles to obtain a backscattered image of the mica particles; Performing image processing on the backscattered image of the mica particles to divide the boundaries of different types of mica; Measure according to the boundaries of the different types of mica to obtain the areas of the different types of mica.

8. The method for determining the type and relative content of mica ore according to claim 1, characterized in that, Calculate according to the areas of the different types of mica to obtain the proportion of the target type of mica, including: Statistically analyze according to the areas of the different types of mica to obtain the total area of all the mica particles; Determine the area of the target type of mica according to the areas of the different types of mica; Determine the ratio of the area of the target type of mica to the total area as the proportion of the target type of mica.

9. The method for determining the type and relative content of mica ore according to claim 3, wherein Calculate the total mica mineral content of the mica ore to be detected, including: Chemically analyze the content of K2O in the mica ore to be detected by the total dissolution sample method to obtain the mineral K2O content; Detect the K2O content of the non-mica minerals in the mica ore to be detected, and obtain the K2O content of the mica minerals according to the mineral K2O content and the K2O content of the non-mica minerals; Calculate the average K2O content of the mica ore to be detected according to the K2O contents of multiple mica particles; Calculate according to the K2O content of the mica minerals and the average K2O content to obtain the total mica mineral content of the mica ore to be detected.

10. The method for determining the type and relative content of mica ore according to claim 9, characterized in that, The calculation formula for the relative content of the target type of mica minerals is as follows: C X = C × D X In the above formula, C X represents the relative content of the target type mica mineral, C represents the total amount of mica minerals, and D X represents the proportion of the mica of the target type.

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