Complex iron mineral quantitative distinguishing method and iron mineral content analysis method

Abstract

The present application relates to the technical field of mineralogy, and particularly provides a complex iron mineral distinguishing and quantifying method and an iron mineral content analysis method, which combines chemical dissolution, automatic mineralogy analysis and micro-area magnetic verification technology for the first time to realize the distinguishing and quantifying of complex iron minerals. The analysis method constitutes a closed and mutually checked analysis system, which combines acid treatment of carbonates, automatic mineralogy analysis of residual minerals, micro-area magnetic verification to correct the misjudgment of magnetic hematite, element surface scanning to check the accuracy of overall mineralogy quantification, and final calculation results, and checks the total iron content of chemical analysis to ensure the reliability of the final results and facilitate the standardized popularization and application.

Description

Technical Field

[0001] This invention relates to the field of mineralogy, specifically to methods for distinguishing and quantifying complex iron minerals and methods for analyzing the content of iron minerals. Background Technology

[0002] Accurate analysis of iron mineral content is a crucial prerequisite for the efficient utilization of iron ore resources, directly impacting beneficiation process design, recovery rate prediction, and product quality control. Currently, numerous technical challenges exist in the process mineralogical analysis of iron ore, including the difficulty in distinguishing between magnetite and hematite. Magnetite (Fe3O4) and hematite (Fe2O3) are both major iron oxides, but they differ in physical properties (such as magnetism and reflectivity) and crystal structure. While conventional methods such as magnetic analysis can provide preliminary differentiation, they are easily confused in ores with fine-grained dispersion, complex coexistence, or severe surface oxidation. Furthermore, in X-ray diffraction analysis, significant errors exist in quantitative results due to peak overlap and preferred orientation effects. Summary of the Invention

[0003] Therefore, it is necessary to provide a method for distinguishing and quantifying complex iron minerals and a method for analyzing the content of iron minerals, which can distinguish the content of magnetite, hematite, and maghemite.

[0004] The present invention adopts the following technical solution:

[0005] This invention provides a method for distinguishing and quantifying complex iron minerals, comprising the following steps: selecting a rich iron ore sample, cutting it into blocks, preferably with the length, width and height of the blocks ranging from 2 to 3 cm, 2 to 3 cm and 1 to 2 cm respectively;

[0006] Randomly select iron ore samples and cut them into blocks, preferably 10 to 15 blocks. Perform reflectance color area scanning based on an automated mineralogical analysis system to measure the area regions of different minerals as Sn, where n is an integer from 1 to 3, where 1 represents magnetite, 2 represents hematite, and 3 refers to the area of ​​other minerals.

[0007] Then, randomly select iron ore samples and cut them into pieces, preferably 10 to 15 pieces, and measure the magnetism of the magnetite and hematite regions based on the reflection color using a magnetic probe.

[0008] In the magnetite region S1, which is divided according to the reflective color, if the probe detects that the magnetism is stronger than the average frequency offset of -19.0 Hz, the magnetite region identified by the automatic mineralogical analysis system is confirmed to be correct, and the number of magnetic points in the magnetite is determined to be N1; if the probe detects that there is no magnetism, the magnetite region identified by the automatic mineralogical analysis system is corrected to other iron-containing metal oxide mineral regions, and the number of non-magnetic points in the magnetite is determined to be N2.

[0009] In the hematite region S2, which is divided according to the reflective color, if the probe detects that the magnetism is weaker than the average frequency offset of -1.5 Hz, the hematite region identified by the automatic mineralogical analysis system is confirmed to be correct, and the number of non-magnetic points in the hematite is determined to be N3; if the probe detects that the magnetism is stronger than the average frequency offset of -19.0 Hz, the hematite region identified by the automatic mineralogical analysis system is corrected to a magnetohematopois region, and the number of magnetic points in the hematite is determined to be N4.

[0010] Calculate the corrected iron oxide content coefficient:

[0011] Magnetite mineral content coefficient L1 = N1 / (N1+N2)

[0012] Hematite mineral content coefficient L3 = N3 / (N3+N4),

[0013] The content coefficient of magnetite minerals is L4 = N4 / (N3+N4).

[0014] The content coefficient of other iron-containing metal oxide minerals is L2 = N2 / (N1+N2;

[0015] The actual contents of magnetite, hematite, maghemite, and other iron-containing metal oxide minerals in complex iron minerals are calculated based on the modified iron oxide content coefficient.

[0016] Preferably, the rich iron ore is selected using a handheld instrument for rapid testing, and the iron content is not less than 50%. The rich iron ore sample dimensions are all greater than 7cm in length, width, and height; it is then cut into blocks. The dimensions of the blocks are 2-3cm in length, 2-3cm in width, and 1-2cm in height, respectively. The number of blocks is 20-30, and the lower surface is then polished until there are no obvious scratches.

[0017] Preferably, an Olympus polarizing microscope is used to scan the area of ​​the reflected color, measuring 100 to 200 fields of view at equal intervals, with a magnification of 50 to 500 times.

[0018] Preferably, the magnetic probe is selected from MFM (Magnetic Force Microscopy) probes. The minerals are preferably larger than 0.050 mm; and measurement points that are too close to the edge of the mineral grains (e.g., within 5 micrometers) are excluded.

[0019] This invention provides a method for distinguishing and quantifying complex iron minerals, comprising the following steps: obtaining a sample to be tested, subjecting it to grinding, epoxy resin curing, cutting, embedding, polishing, and carbon spraying to prepare a sample for automated mineralogical analysis; using an automated mineralogical analysis system to detect and obtain the content mi of the main minerals, where i is at least an integer from 1 to 3, where 1 represents magnetite, 2 represents hematite, and 3 represents other iron-containing metal oxide minerals; and calculating based on a corrected iron oxide content coefficient:

[0020] The actual content of magnetite is m1 L1,

[0021] The actual content of hematite is m2 L3,

[0022] The actual content of maghematite is m2 L4,

[0023] The actual content of other iron-containing metal oxide minerals is m1 L2+m3.

[0024] In addition, it is worth noting that after analyzing existing technologies, the inventors' team also discovered the following challenges:

[0025] (1) Severe interference from carbonate minerals. The ore often contains iron-bearing carbonate minerals such as siderite and iron dolomite. Since these minerals partially overlap with iron oxide minerals in chemical composition and have similar response characteristics in different analytical methods (such as chemical analysis and X-ray diffraction), it is difficult to accurately distinguish and quantify them by relying solely on chemical content or conventional phase analysis, resulting in deviations in iron phase distribution and affecting subsequent sorting results.

[0026] (2) Iron-bearing silicate gangue minerals have not been effectively identified and recovered. Iron-bearing silicate minerals (such as fir olivine, amphibole, biotite, etc.) are often found in ores. The iron in these minerals is usually considered "non-recoverable iron" and is not distinguished independently in traditional chemical phase analysis, but is generally classified into phases such as iron silicate. However, with the advancement of mineral processing technology, some iron-bearing gangues can be utilized under certain conditions, so there is an urgent need for more accurate methods for analyzing their occurrence state and determining their content.

[0027] (3) Limitations of reliance on micro-area methods such as electron probe microanalysis. Although electron probe microanalysis (EPMA) can achieve quantitative analysis of single minerals, its analytical range is extremely small, its statistical representativeness is insufficient, and it has high requirements for predictive mineral identification, making it unsuitable for systematic analysis of large batches and multiple types of ores. In addition, this method has limited detection capabilities for low-content minerals and fine-grained disseminated ores, making it difficult to meet the comprehensive, rapid, and accurate analytical needs of process mineralogy.

[0028] To simultaneously address the aforementioned problems, the present invention also provides a method for analyzing the content of iron minerals, comprising the following steps:

[0029] Obtain an iron ore sample to be tested, grind it, and obtain a ground sample a1 with a fineness of 200 mesh or more (90%).

[0030] Grinding sample a1 was subjected to acid treatment to obtain sample a2 and acid solution a21. The acid treatment yield d1 was calculated. The theoretical iron carbonate content m was calculated using acid solution a21. CO3 :

[0031] m CO3 =2.075C 铁离子 V 酸 C 铁离子 V represents the iron ion content in the acid solution. 酸 This refers to the volume of the acid solution;

[0032] Sample a2 was washed and deslimed to obtain slime a3 and washed concentrate a4. The washing yield d2 was calculated.

[0033] Take a4 sample of washed ore concentrate and prepare a5 sample for automatic mineralogical analysis. Detect the content of major minerals mi, where i is an integer from 1 to 6, where 1 represents magnetite, 2 represents hematite, 3 represents other iron-bearing metal oxide minerals, 4 represents iron-bearing metal sulfide minerals, 5 represents iron-bearing silicate minerals, and 6 represents other gangue minerals.

[0034] Based on the above method for distinguishing and quantifying complex iron minerals, the content coefficients of magnetite minerals (L1), other iron-containing metal oxide minerals (L2), hematite minerals (L3), and maghematite minerals (L4) were calculated.

[0035] The initial revised calculation of the main mineral content mt' in the iron ore sample was performed, where t takes the values ​​1, 2, 3, 4, 5, 6, 7, and 8, representing magnetite, hematite, other iron-bearing metal oxide minerals, iron-bearing metal sulfide minerals, iron-bearing silicate minerals, other gangue minerals, maghemite, and iron-bearing carbonate minerals, respectively.

[0036] Initial correction of magnetite content m1'=m1 L1 d1 d2;

[0037] Initial correction of hematite content m2'=m2 L3 d1 d2;

[0038] The initial corrected content of other iron-bearing metal oxide minerals m3' = (m1) L2+m3) d1 d2;

[0039] Iron-containing metal sulfide mineral content m4'=m4 d1 d2;

[0040] Iron-containing silicate mineral content m5'=m5 d1 d2;

[0041] Magnesite content m7t'=m2 L4 d1 d2;

[0042] Iron-containing carbonate mineral content m8'=m CO3 / e;

[0043] The content of other gangue minerals is m6'=1-Σmt', where t is 1, 2, 3, 4, 5, 7, or 8.

[0044] Preferably, the iron mineral content analysis method of the present invention further includes a step of recalculating the actual content of the main minerals:

[0045] Next, surface scans of silicon, sulfur, and iron were performed on sample a5 to be analyzed by automated mineralogical analysis to exclude iron oxide minerals; electron probe microanalysis was performed on iron-containing metal sulfide minerals and iron-containing silicate minerals to obtain the iron content in the metal sulfide minerals and iron-containing silicate minerals.

[0046] Calculate the total iron content b2=Σmt' ft, where ft is the iron content of the t-th major mineral;

[0047] Calculate the correction factor k = b1 / b2, where b1 is the total iron content in the milled sample a1;

[0048] Calculate the actual content Mt' of the main minerals:

[0049] Mt'=mt' k, M6'=1-ΣMt' (t is 1, 2, 3, 4, 5, 7, 8).

[0050] In some embodiments, the acid treatment uses a 5% to 20% hydrochloric acid aqueous solution, a solid-liquid ratio of 1:(2 to 5), a temperature of 60 to 80°C, and a stirring time of 30 to 60 minutes.

[0051] In some embodiments, during the ore washing and stripping step, the ore washing yield is controlled to be above 0.95, which is the ratio of the mass of the retained solid sample to the mass of the original sample.

[0052] In some embodiments, the amount of iron ore sample to be tested is 0.5~1.0 kg; in the step of preparing the sample a5 for automated mineralogical analysis, the amount of washed concentrate a4 is 4~6 g.

[0053] Compared with the prior art, the core technical advantages and beneficial effects of the present invention are as follows:

[0054] The iron mineral content analysis method of this invention enables the differentiation and quantification of complex iron minerals. In particular, the introduction of in-situ measurement with a magnetic probe completely solves the industry problem that traditional methods cannot accurately distinguish between magnetite, hematite and maghemite, which have similar optical characteristics but different magnetic properties.

[0055] This invention innovatively combines chemical dissolution, automated mineralogical analysis, and micro-area magnetic verification technology to form a closed, mutually verifying analytical system. Specifically, it combines acid treatment of carbonates, automated mineralogical analysis of remaining minerals, micro-area magnetic verification to correct misjudgments of maghemite, elemental surface scanning to verify the accuracy of overall mineralogical quantification, and the final calculation results. This is then compared with the total iron content from chemical analysis to perform closed-loop correction, ensuring the reliability of the final results and facilitating standardized promotion and application.

[0056] The accurate mineralogical data provided by the analytical method of this invention can guide geological exploration and resource evaluation, mineral processing optimization, and smelting and blending. Attached Figure Description

[0057] Figure 1 This is a schematic diagram of the iron mineral content analysis method of the present invention. Detailed Implementation

[0058] Explanation of some terms in this invention:

[0059] Rich iron ore (rich ore): refers to natural iron ore with a high iron content, and iron grade (calculated as total iron) is higher than 50%.

[0060] Magnetite: Its main component is Fe3O4. It is blackish-gray in color and is characterized by strong magnetism. It is a mineral mainly used for iron recovery.

[0061] Hematite: Its main component is Fe2O3. It is reddish-brown and has a diverse structure, ranging from dense to porous. It is mainly used for iron recovery.

[0062] Magnesite: It is a polymorphism of hematite (α-Fe₂O₃), meaning it has the same chemical composition but different crystal structures. Like magnetite, it can be attracted by ordinary magnets and has strong magnetism.

[0063] Other iron-bearing metal oxide minerals: iron-bearing metal oxides other than magnetite, hematite, and maghemite, such as limonite, goethite, and ilmenite.

[0064] Iron-bearing gangue minerals: such as olivine, pyroxene and amphibole, and other iron-containing silicates (referred to as "iron-bearing silicate minerals"). Iron is difficult to extract from these minerals.

[0065] Iron-bearing carbonate minerals: Iron-bearing carbonate minerals such as siderite and siderite-magnesium ore are different from iron-bearing silicate minerals. Iron-bearing carbonate minerals (especially siderite) are very important iron ores. Their iron content is acceptable, and they can be efficiently separated from gangue by magnetic separation, taking advantage of their strong magnetic properties after roasting.

[0066] Other gangue minerals: In addition to the minerals mentioned above, other minerals that do not contain iron cannot be recycled for iron.

[0067] The present invention will be further described in detail below with reference to specific embodiments, so that those skilled in the art can more clearly understand the present invention. The following embodiments are only used to illustrate the present invention, and are not intended to limit the scope of the present invention. Based on the specific embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the protection scope of the present invention. In the embodiments of the present invention, unless otherwise specified, all raw material components are commercially available products well known to those skilled in the art; in the embodiments of the present invention, unless specifically specified, the technical means used are conventional means well known to those skilled in the art.

[0068] Example 1

[0069] This embodiment provides a method for obtaining the iron oxide content coefficient, including the following steps:

[0070] S1, Obtain mineral samples

[0071] Rich iron ore (sourced from an iron mine in Hebei Province; basic physicochemical parameters: iron minerals are mainly magnetite and hematite, with other iron minerals at low levels, and total iron content greater than 50%) was selected. The ore sample dimensions were all greater than 7 cm in length, width, and height. The sample was then cut into blocks.

[0072] The dimensions of the cut blocks were 2cm in length, 2cm in width, and 1cm in height. Twenty blocks were prepared, and their lower surfaces were then polished until no obvious scratches were visible. Handheld testing showed that the selected ore had an iron content higher than the average iron content of the ore body.

[0073] S2, Surface Scan Analysis

[0074] The measurements were performed under an Olympus polarizing microscope. Ten randomly selected sections were used: 150 fields of view were measured at equal intervals (1 mm), magnification was 100x, and the mineral area was determined by area scanning based on reflected color. The mineral area region was Sn, where n represents magnetite, hematite and other minerals.

[0075] S3, Magnetic Analysis

[0076] Ten more cut pieces were randomly selected. Using a magnetic force probe (MFM - magnetic force microscope probe), a field of view was measured at 10 mm intervals. Based on the iron oxide regions (magnetite range and hematite range) defined by the reflected color in the above steps, and combined with coordinate characteristics, the magnetic properties of the minerals were further determined. The magnetic properties of magnetite and hematite were measured by equal-interval analysis and testing.

[0077] Within the magnetite region S1: If the probe detects strong magnetism (stronger than the average frequency offset of -19.0 Hz), the magnetite region and content identified in the automated mineralogical analysis are correct. If the probe detects no magnetism, it should be identified as other iron-bearing metal oxide minerals.

[0078] In the hematite region S2: if the probe detects no or very weak magnetism (weaker than the average frequency offset of -1.5Hz), the hematite content identified in the automated mineralogical analysis is correct. If the probe detects strong magnetism in areas with optical characteristics resembling hematite, then these points are magnetohematopoisite, and the distinction is confirmed.

[0079] The average frequency offset is between -19.0 Hz and -1.5 Hz. Particles are not counted, which is a blurry area, mostly a region where magnetite and hematite are tightly bonded.

[0080] The number of magnetic analysis points Nm was further measured, where m is 1, 2, 3, and 4, respectively representing the number of magnetic points in magnetite, the number of non-magnetic points in magnetite, the number of non-magnetic points in hematite, and the number of magnetic points in hematite.

[0081] Calculate the corrected iron oxide content coefficient:

[0082] Magnetite content coefficient L1 = N1 / (N1+N2)

[0083] Hematite content coefficient L3 = N3 / (N3+N4),

[0084] The content coefficient of magnetite is L4 = N4 / (N3+N4).

[0085] The content coefficient of other iron-containing metal oxide minerals is L2 = N2 / (N1+N2).

[0086] The test results are summarized in the table below:

[0087] Statistical table of complex iron minerals under a microscope

[0088]

[0089] Example 2

[0090] This embodiment provides a method for analyzing the content of iron minerals, including the following steps:

[0091] S1. Select 0.53 kg of the sample to be tested (source: an iron mine in Hebei Province; basic physicochemical parameters: iron minerals are mainly magnetite and hematite, with low content of limonite and total iron content greater than 50%), grind it to a fineness of 200 mesh, and obtain ground sample a1; take a sample from ground sample a1 and send it for multi-element analysis, and obtain the total iron content b1 as 50.22%.

[0092] S2, acid treatment and washing / desliming

[0093] Take 500g of the above-mentioned ground ore sample a1 and perform acid treatment: using a 5% hydrochloric acid aqueous solution, at a solid-liquid ratio of 1:4, stir for 30 minutes at 60℃ to obtain acid-treated mineral sample a2 and acid solution a21. In this step, the acid treatment yield d1 is 0.8233, and the volume of acid solution a21 is V. 酸 The volume was 3.01 L, and the iron ion content C was measured. 酸 It is 1.56 g / L.

[0094] Calculate the iron carbonate content (in FeCO3 form) mCO3:

[0095] 2.075 C 酸 V 酸 =2.075 1.56 3.01 = 9.74 g.

[0096] The acid-treated mineral sample a2 was subjected to washing and desliming operations: the solid-liquid ratio was 1:4, and the upper turbid liquid was extracted by stirring to obtain slime a3 and washed concentrate a4. In this step, the washing yield d2 was 0.9552.

[0097] S3, Automated Mineralogical Analysis

[0098] For the washed concentrate A4, 4~6g samples were taken and subjected to the following processes: crushing, mixing (the reagents were commercially sourced, and the basic composition and physicochemical parameters were epoxy resin and its corresponding curing agent), ultrasonic vibration for 15min, curing followed by side cutting, secondary embedding, and polishing.

[0099] Grinding and polishing include grinding and polishing processes. When grinding, it is preferred to use abrasives of 1200 mesh or higher to grind until the surface is smooth. When polishing, abrasives of 1.0 μm or lower are selected and the grinding and polishing time is controlled within 25 min. Carbon spraying treatment is used to prepare sample a5 for automatic mineralogical analysis.

[0100] The samples were analyzed using an automated mineralogy analysis system (model: MLA650, including functional modules: material composition analysis, elemental surface scanning). The results are shown in the table below:

[0101] Automated mineralogical analysis results

[0102]

[0103] S4, Initial revision calculation of mineral content

[0104] Calculate according to the following formula:

[0105] Initial revision of magnetite content calculation:

[0106] m1'=m1 L1 d1 d2=43.12% 0.8223 0.9552 0.8991 = 30.45%.

[0107] Initial revision of hematite content calculation:

[0108] m2'=m2 L3 d1 d2=34.65% 0.8223 0.9552 0.9823 = 26.73%.

[0109] Initial revision of calculations for the content of other iron-containing metal oxide minerals:

[0110] m3'=(m1 L2+m3) d1 d2 = (43.12%) (0.1009 + 7.22%) 0.8223 0.9552 = 9.09%.

[0111] Initial revised calculation of iron-bearing metal sulfide mineral content:

[0112] m4'=m4 d1 d2=5.92% 0.8223 0.9552 = 4.65%.

[0113] Initial revised calculation of iron-bearing silicate mineral content:

[0114] m5'=m5 d1 d2=4.48% 0.8223 0.9552 = 3.52%.

[0115] Initial revision of the calculation of magnetite content:

[0116] m7'=m2 L4 d1 d2=34.65% 0.8223 0.9552 0.0177 = 0.48%.

[0117] Calculate the content of iron-containing carbonate minerals:

[0118] m8'=m CO3 / e=9.74 / 500=1.95%.

[0119] Initial revision of calculations for the content of other gangue minerals:

[0120] m6'=1-Σmt'=1-(30.45%+26.73%+9.09%+4.65%+3.52%+0.48%+1.95%)=23.13%, (t is 1, 2, 3, 4, 5, 7, 8).

[0121] S5, revised again

[0122] Using the MLA650 automated mineralogical analysis system, sample a5 was subjected to another surface scan for silicon, sulfur, and iron elements to exclude iron oxide minerals. Electron probe microanalysis (EPMA1720H, which includes the component analysis module) was performed on iron-containing metal sulfides and iron-containing silicate minerals to obtain the iron content in the metal sulfide minerals and iron-containing silicate minerals.

[0123] Calculate the total iron content b2 based on the mineral content.

[0124] b2=Σmt' ft, where ft is the iron content of the t-th mineral.

[0125] Calculate the correction factor k:

[0126] k=b1 / b2=50.22% / 49.42%=1.01619.

[0127] The actual content of the main minerals in the ore, Mt', was calculated as follows:

[0128] Mt'=mt' k, M6'=1-ΣMt' (t is 1, 2, 3, 4, 5, 7, 8);

[0129] b2=Σmt' ft=49.42%.

[0130] M1'=m1' k=30.45% 50.22% / 49.42%=30.94%.

[0131] M6'=1-ΣMt'=1-(30.94%+27.16%+...+1.98%)=21.89%.

[0132] Statistical table of actual iron mineral content calculation results

[0133]

[0134] Accurate measurement of the content of other iron-bearing minerals provides data support for the comprehensive utilization of this type of iron ore resource, because whether other iron-bearing minerals, besides the main recovered magnetite and hematite, are worth recovering also depends on the corroboration of these core data.

[0135] See Figure 1 The technical concept of this invention lies in providing a method for distinguishing and quantifying complex iron minerals, as well as a method for analyzing iron mineral content. This method determines the iron oxide content coefficient through surface scanning analysis and magnetic analysis, determines the total iron content through multi-element analysis, obtains the iron carbonate mineral content through grinding acid treatment, and obtains the content of major minerals through ore washing, desliming, and an automated mineralogical analysis system. After data correction, the actual iron mineral content is calculated. This invention innovatively combines chemical dissolution, automated mineralogical analysis, and micro-area magnetic verification technology, completely solving the industry problem that traditional methods cannot accurately distinguish between magnetite, hematite, and maghemite, which have similar optical characteristics but vastly different magnetic properties. It forms a reliable system with multiple cross-validations, a clear method flow, and quantified parameters, which is conducive to the standardization, promotion, and application of the technology.

[0136] It should be noted that the above embodiments are only for further elaboration and explanation of the technical solution of the present invention, and are not intended to further limit the technical solution of the present invention. The method of the present invention is only a preferred embodiment and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A quantitative method for differentiating complex iron minerals, characterized in that, Includes the following steps: Select a rich iron ore sample and cut it into blocks; Randomly selected iron ore samples were cut into blocks, and reflectance color area scanning was performed based on an automated mineralogical analysis system. The area regions of different minerals were measured as Sn, where n is an integer from 1 to 3, where 1 represents magnetite, 2 represents hematite, and 3 represents the area of ​​other minerals. Then, randomly select iron-rich ore samples and cut them into pieces. Magnetic properties of the magnetite and hematite regions, which are divided according to their reflectance color, are measured using a magnetic probe. In the magnetite region S1, which is divided according to the reflective color, if the probe detects that the magnetism is stronger than the average frequency offset of -19.0Hz, the magnetite region identified by the automatic mineralogical analysis system is confirmed to be correct, and the number of magnetic points in the magnetite is determined to be N1; if the probe detects that there is no magnetism, the magnetite region identified by the automatic mineralogical analysis system is corrected to other iron-containing metal oxide mineral regions, and the number of non-magnetic points in the magnetite is determined to be N2. In the hematite region S2, which is divided according to the reflective color, if the probe detects that the magnetism is weaker than the average frequency offset of -1.5 Hz, the hematite region identified by the automatic mineralogical analysis system is confirmed to be correct, and the number of non-magnetic points in the hematite is determined to be N3; if the probe detects that the magnetism is stronger than the average frequency offset of -19.0 Hz, the hematite region identified by the automatic mineralogical analysis system is corrected to a magnetohematopois region, and the number of magnetic points in the hematite is determined to be N4. Calculate the corrected iron oxide content coefficient: Magnetite mineral content coefficient L1 = N1 / (N1+N2) Hematite mineral content coefficient L3 = N3 / (N3+N4), The content coefficient of magnetite minerals is L4 = N4 / (N3+N4). The content coefficient of other iron-containing metal oxide minerals is L2 = N2 / (N1+N2; The actual contents of magnetite, hematite, maghemite, and other iron-containing metal oxide minerals in complex iron minerals are calculated based on the modified iron oxide content coefficient.

2. The method for distinguishing and quantifying complex iron minerals according to claim 1, characterized in that, The iron content in the rich iron ore shall not be less than 50%.

3. The method for distinguishing and quantifying complex iron minerals according to claim 1, characterized in that, The area of ​​the reflected color was scanned using an Olympus polarizing microscope. The number of fields of view was 100 to 200, and the measurements were taken at equal intervals. The magnification was 50 to 500 times.

4. The method for distinguishing and quantifying complex iron minerals according to claim 1, characterized in that, The magnetic probe is selected from MFM-magnetic force microscope probes.

5. The method for distinguishing and quantifying complex iron minerals according to any one of claims 1 to 4, characterized in that, Includes the following steps: The sample to be tested is obtained, and then ground, cured with epoxy resin, cut into blocks, embedded, polished, and carbon sprayed to prepare the sample for automatic mineralogical analysis. Using an automated mineralogical analysis system, the content mi of major minerals is detected, where i is an integer from 1 to 3, where 1 represents magnetite, 2 represents hematite, and 3 represents other iron-containing metal oxide minerals. Calculated based on the corrected iron oxide content coefficient: The actual content of magnetite is m1 L1, The actual content of hematite is m2 L3, The actual content of maghematite is m2 L4, The actual content of other iron-containing metal oxide minerals is m1 L2+m3.

6. A method for analyzing the content of iron minerals, characterized in that, Includes the following steps: Obtain the iron ore sample to be tested, grind it, and obtain a ground sample a1 with a fineness of 200 mesh or more (90%). Grinding sample a1 was subjected to acid treatment to obtain sample a2 and acid solution a21. The acid treatment yield d1 was calculated. The theoretical iron carbonate content m was calculated using acid solution a21. CO3 : m CO3 =2.075C 铁离子 V 酸 C 铁离子 V represents the iron ion content in the acid solution. 酸 This refers to the volume of the acid solution; Sample a2 was washed and deslimed to obtain slime a3 and washed concentrate a4. The washing yield d2 was calculated. Take a4 sample of washed ore concentrate and prepare a5 sample for automatic mineralogical analysis. Detect the content of major minerals mi, where i is an integer from 1 to 6, where 1 represents magnetite, 2 represents hematite, 3 represents other iron-bearing metal oxide minerals, 4 represents iron-bearing metal sulfide minerals, 5 represents iron-bearing silicate minerals, and 6 represents other gangue minerals. According to the method for distinguishing and quantifying complex iron minerals as described in any one of claims 1 to 5, the content coefficients of magnetite mineral L1, hematite mineral L3, maghematite mineral L4, and other iron-containing metal oxide minerals L2 are calculated. The initial revised calculation of the main mineral content mt', where t takes the values ​​1, 2, 3, 4, 5, 6, 7, and 8, representing magnetite, hematite, other iron-bearing metal oxide minerals, iron-bearing metal sulfide minerals, iron-bearing silicate minerals, other gangue minerals, maghemite, and iron-bearing carbonate minerals, respectively. Initial correction of magnetite content m1'=m1 L1 d1 d2; Initial correction of hematite content m2'=m2 L3 d1 d2; The initial corrected content of other iron-bearing metal oxide minerals m3' = (m1) L2+m3) d1 d2; Iron-containing metal sulfide mineral content m4'=m4 d1 d2; Iron-containing silicate mineral content m5'=m5 d1 d2; Magnesite content m7'=m2 L4 d1 d2; Iron-containing carbonate mineral content m8'=m CO3 / e; The content of other gangue minerals is m6'=1-Σmt', where t is 1, 2, 3, 4, 5, 7, or 8.

7. The method for analyzing iron mineral content according to claim 6, characterized in that, It also includes a step to revise the calculation of the actual content of the main minerals: Next, surface scans of silicon, sulfur, and iron were performed on sample a5 to be analyzed by automated mineralogical analysis to exclude iron oxide minerals; electron probe microanalysis was performed on iron-containing metal sulfide minerals and iron-containing silicate minerals to obtain the iron content in the metal sulfide minerals and iron-containing silicate minerals. Calculate the total iron content b2=Σmt' ft, where ft is the iron content of the t-th major mineral; Calculate the correction factor k = b1 / b2, where b1 is the total iron content in the milled sample a1; Calculate the actual content Mt' of the main minerals: Mt'=mt' k, M6'=1-ΣMt' (t is 1, 2, 3, 4, 5, 7, 8).

8. The method for analyzing iron mineral content according to claim 6 or 7, characterized in that, The acid treatment uses a 5%~20% hydrochloric acid aqueous solution with a solid-liquid ratio of 1:(2~5), a temperature of 60~80℃, and a stirring time of 30~60min.

9. The method for analyzing iron mineral content according to claim 6 or 7, characterized in that, In the ore washing and demineralization step, the ore washing yield is controlled at 0.95 or higher.

10. The method for analyzing iron mineral content according to claim 6 or 7, characterized in that, The sample size of the iron ore to be tested is 0.5~1.0 kg; in the step of preparing the sample a5 for automatic mineralogical analysis, the sample size of the washed concentrate a4 is 4~6 g.

Images