CN114708926A - Prediction method for yield and recovery rate of pyrrhotite and application thereof - Google Patents

Prediction method for yield and recovery rate of pyrrhotite and application thereof Download PDF

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CN114708926A
CN114708926A CN202210276692.7A CN202210276692A CN114708926A CN 114708926 A CN114708926 A CN 114708926A CN 202210276692 A CN202210276692 A CN 202210276692A CN 114708926 A CN114708926 A CN 114708926A
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叶小璐
肖仪武
武若晨
刘娟
赵明
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Abstract

The invention relates to the technical field of mineral processing, in particular to a prediction method of yield and recovery rate of pyrrhotite and application thereof. The prediction method comprises the following steps: judging the crystal structure type of pyrrhotite in the ore to be processed, and calculating the content M of monoclinic pyrrhotite in the ore to be predicteddAnd/or content M of hexa-pyrrhotitel(ii) a Counting the number of particles of monoclinic pyrrhotite and/or hexagonal pyrrhotite in the ore to be predicted in different particle size ranges, counting the maximum particle size value and the minimum particle size value in each particle size range, and then counting the number of the particles according to the statisticsCalculating a variable D; calculating the content K of monoclinic pyrrhotite with the grain diameter less than 0.02mm in the ore to be predicteddAnd/or the content K of the hexagonal pyrrhotite with the grain diameter less than 0.02mml(ii) a The maximum yield and maximum recovery of the pyrrhotite were calculated separately. The error between the theoretical maximum yield and the theoretical maximum recovery rate calculated by the prediction method is small.

Description

Prediction method for yield and recovery rate of pyrrhotite and application thereof
Technical Field
The invention relates to the technical field of mineral processing, in particular to a prediction method of yield and recovery rate of pyrrhotite and application thereof, and more particularly relates to a prediction method of yield and recovery rate of pyrrhotite, a sorting method of pyrrhotite and a beneficiation method.
Background
Pyrrhotite is a sulfide mineral widely distributed in various non-ferrous metal deposits, and can be used for extracting sulfur and producing sulfuric acid; can also be used for purifying the wastewater containing heavy metals. Therefore, the research on the grading method of pyrrhotite has been one of the hot research problems in the field of mineral processing.
In this regard, the prior art provides methods for the beneficiation of pyrrhotite including magnetic separation, flotation, and the like. However, these methods are prevalent in one or more of the following problems:
(1) the prior art methods are basically process flow methods, but related researches and methods for evaluating (or predicting) a range of indexes to be reached are considered reasonable according to the actual conditions of samples, and the maximum recovery rate is reached (or is close to the maximum recovery rate) are blank.
(2) The influencing factors responsible for the final grading effect are not considered to be numerous. The process flow, process parameters and final grading index may be changed by the particle size composition of pyrrhotite, the amount of pyrrhotite minerals in the sample, the proportions of different types of pyrrhotite and other factors.
(3) The selection method and the selection process (such as magnetic separation and flotation) are provided, but specific technological condition parameters are not provided, so that subsequent researchers are still difficult to obtain good effects due to the fact that accurate technological parameters are not available even according to the given method.
(4) It is stated what method is used to sort pyrrhotite, but it is not specified which type of pyrrhotite is selected, or it is not considered that many types of pyrrhotite may exist in the sample at the same time, and only one method is selected for sorting.
In view of the above, the present invention is particularly proposed.
Disclosure of Invention
The first purpose of the invention is to provide a prediction method of the yield and the recovery rate of pyrrhotite, and the error of the theoretical maximum yield and the theoretical maximum recovery rate calculated by the prediction method is small.
The second purpose of the invention is to provide a method for sorting pyrrhotite.
The third purpose of the invention is to provide a beneficiation method.
In order to achieve the above purpose of the present invention, the following technical solutions are adopted:
the invention provides a prediction method of yield (maximum yield) and recovery (maximum recovery) of pyrrhotite (namely a calculation method of theoretical maximum yield and theoretical maximum recovery of pyrrhotite), which comprises the following steps:
(a) judging the crystal structure type of pyrrhotite in the ore to be processed, and calculating the content (mass percentage content) M of monoclinic pyrrhotite in the ore to be predicteddAnd/or the content (mass percentage content) M of the hexagonal pyrrhotitel。
Specifically, when only the monoclinic pyrrhotite is contained in the ore to be predicted, the content of the monoclinic pyrrhotite in the ore to be predicted only needs to be calculated, for example, the content of the monoclinic pyrrhotite in the ore to be predicted in percentage by mass is calculated.
When the ore to be predicted only contains the hexapyrrhotite, the content of the hexapyrrhotite in the ore to be predicted only needs to be calculated, for example, the content of the hexapyrrhotite in the ore to be predicted in percentage by mass is calculated.
When the ore to be predicted contains both monoclinic pyrrhotite and hexagonal pyrrhotite, the content of the monoclinic pyrrhotite and the content of the hexagonal pyrrhotite in the ore to be predicted need to be calculated simultaneously. For example, the mass percentage content of the monoclinic pyrrhotite in the ore to be predicted and the mass percentage content of the hexagonal pyrrhotite in the ore to be predicted are respectively calculated.
In the present invention, if only one of monoclinic pyrrhotite and hexagonal pyrrhotite is contained in the ore to be predicted, only a single pyrrhotite species contained need be counted, calculated or detected in the following steps. When the ore to be predicted contains monoclinic pyrrhotite and hexagonal pyrrhotite simultaneously, the related parameters of two different types of pyrrhotite need to be counted, calculated or detected simultaneously in the following steps.
(b) Counting the number of particles of monoclinic pyrrhotite and/or hexagonal pyrrhotite in the ore to be predicted in different particle size ranges, counting the maximum particle size value and the minimum particle size value in each particle size range, and then calculating a variable D according to the counting result; wherein the content of the first and second substances,
Figure BDA0003556008330000031
wherein a is the maximum particle size value within the particle size range of less than 0.02 mm; b is the smallest particle size value within the particle size range of less than 0.02 mm; n is the number of particles within the particle size range of less than 0.02 mm; a is the maximum particle size value in the particle size range; b is the smallest particle size value in the particle size range; n is the number of particles in the particle size range; m is the number of grades in the particle size range.
Specifically, the division criterion of the particle diameter range may be divided into 2 levels (grades), 3 levels, 4 levels, 5 levels, 6 levels, 8 levels, or 10 levels. The more levels (levels) divided, i.e., the finer the division, the more advantageous the error reduction. The m represents the number of particle size range classification (grade). That is, m may be 2, 3, 4, 5, 6, 8, or 10.
Among them, at least the standard of the particle size range having a particle size of less than 0.02mm needs to be set.
For example, the number of particles having a statistical particle diameter in the range of less than 0.02mm, and the maximum particle diameter value and the minimum particle diameter value in this range. Meanwhile, the number of particles with the particle size not less than 0.02mm is counted, and the maximum particle size value and the minimum particle size value in the range are counted. In this case, 2 levels (levels) are divided, and m is 2.
For another example, counting the number of particles with the particle size of less than 0.02mm, the number of particles with the particle size of 0.02-0.5 mm, and the number of particles with the particle size of more than 0.5 mm; meanwhile, the maximum particle size value and the minimum particle size value in each range are counted. In this case, the number of classes (levels) is 3, and m is 3.
(c) Calculating the content (mass percentage content) K of monoclinic pyrrhotite with the particle size less than 0.02mm in the ore to be predicteddAnd/or the content (mass percentage content) K of the hexagonal pyrrhotite with the grain diameter less than 0.02mml。
Wherein the content K of monoclinic pyrrhotite with the particle size of less than 0.02mm in the ore to be predictedd＝MdX D; the content K of the hexagonal pyrrhotite with the particle size of less than 0.02mm in the ore to be predictedl＝Ml×D。
(d) Respectively calculating the maximum yield and the maximum recovery rate of the pyrrhotite;
theoretical maximum yield Y of pyrrhotite when the type of crystal structure of pyrrhotite in the ore to be treated is only monoclinic pyrrhotited＝Md-Kd×QdWherein Q isdIs the loss coefficient, Q, in the process of low intensity magnetic separationd0.4-0.6; theoretical maximum recovery H of pyrrhotited＝Yd/Md×100％；
Theoretical maximum yield Y of pyrrhotite when the type of crystal structure of pyrrhotite in the ore to be treated is only hexagonal pyrrhotitel＝Ml-Kl×QlWherein Q islIs the loss coefficient, Q, in the course of strong magnetic separationl0.4-0.6; theoretical maximum recovery H of pyrrhotitel＝Yl/Ml×100％；
Of pyrrhotite in the ore to be treatedWhen the crystal structure type contains monoclinic pyrrhotite and hexagonal pyrrhotite, the theoretical maximum yield of the pyrrhotite comprises the maximum yield Y of the weak magnetic separationWeak (weak)And maximum yield Y of strong magnetic separationHigh strength(ii) a The theoretical maximum recovery rate of pyrrhotite comprises the maximum recovery rate H of low intensity magnetic separationWeak (weak)And strong magnetic separation maximum recovery rate HHigh strength；
Wherein, YWeak (weak)＝Md-Kd×Qd；
Figure BDA0003556008330000041
YHigh strength＝Kd×Qd+(Ml-Kl×Ql)；
Figure BDA0003556008330000042
Monoclinic pyrrhotite and hexagonal pyrrhotite with different crystal structures exist in the nature at the same time, the monoclinic pyrrhotite has strong magnetism, and the hexagonal pyrrhotite only has weak magnetism. Since pyrrhotite with different crystal structures tends to have large difference in magnetism, the magnetic separation process is confronted with the following problems: how to select a reasonable process principle flow based on the proportion of the pyrrhotite with different crystal structures in an actual sample, how to adjust corresponding process parameters, and how to realize high-efficiency separation of different pyrrhotite to the maximum extent, how to predict or judge the rationality of the recovery rate index of the magnetic concentrate, and the like.
Meanwhile, the size of the mineral particles, the amount of the magnetic mineral in the sample, and the like may affect the sorting effect. Particularly, the magnetic separation of the fine grinding product has obvious influence on the separation effect when the proportion of the pyrrhotite in the fine particle fraction is large.
Therefore, the method comprises the steps of dividing the crystal structure types of the pyrrhotite, respectively calculating the contents of monoclinic pyrrhotite and hexagonal pyrrhotite in the ore to be predicted, counting the number of particles of the monoclinic pyrrhotite and/or the hexagonal pyrrhotite in the ore to be predicted in different particle size ranges, and the maximum particle size value and the minimum particle size value in each particle size range, respectively calculating the content of the monoclinic pyrrhotite with the particle size smaller than 0.02mm in the ore to be predicted and the content of the hexagonal pyrrhotite with the particle size smaller than 0.02mm in the ore to be predicted, and finally respectively calculating to obtain the maximum theoretical yield and the maximum theoretical recovery rate, so that the prediction error can be reduced, and the accuracy can be improved. The indexes of the maximum theoretical recovery rate and the maximum theoretical yield measured and calculated by the method are closer to the actual situation, so that accurate guidance is provided for establishing production indexes.
Preferably, in the step (a), the method for judging the crystal structure type of pyrrhotite in the ore to be processed comprises the following steps:
carrying out X-ray diffraction analysis on the ore to be processed to obtain an X-ray diffraction pattern; then judging the crystal structure type of pyrrhotite according to the X-ray diffraction pattern;
preferably, the method for determining the crystal structure type of pyrrhotite specifically includes: when the X-ray diffraction pattern has a double peak at a point value of any one of or a range value between any two of 2 θ ═ 42 ° to 46 ° (including but not limited to 42.2 °, 42.4 °, 42.5 °, 42.7 °, 42.9 °, 43 °, 43.2 °, 43.4 °, 43.6 °, 43.8 °, 44 °, 44.2 °, 44.5 °, 44.8 °, 45 °, 45.3 °, 45.5 °, and 45.8 °), and the absolute value of the difference in intensity of the double peak is less than 0.5 (0.45, 0.4, 0.35, 0.3, 0.25, 0.2, or 0.1 may also be selected), the crystal structure type of the pyrrhotite is determined to be monoclinic pyrrhotite;
or, when the X-ray diffraction pattern is unimodal and its peak shape is smooth with no bifurcation at any one or a range of values between any two of the point values of any one of, but not limited to, 42.2 °, 42.4 °, 42.5 °, 42.7 °, 42.9 °, 43 °, 43.2 °, 43.4 °, 43.6 °, 43.8 °, 44 °, 44.2 °, 44.5 °, 44.8 °, 45 °, 45.3 °, 45.5 °, 45.8 °, 2 θ ° 42 ° (including but not limited to, 42.2 °, 42.4 °, 43.6 °), the crystal structure type of the pyrrhotite is judged to be hexapyrrhotite;
alternatively, when the X-ray diffraction pattern is unimodal and its peak shape is bifurcated at 2 θ ═ 42 ° to 46 ° (including but not limited to, point values of any one of 42.2 °, 42.4 °, 42.5 °, 42.7 °, 42.9 °, 43 °, 43.2 °, 43.4 °, 43.6 °, 43.8 °, 44 °, 44.2 °, 44.5 °, 44.8 °, 45 °, 45.3 °, 45.5 °, and 45.8 °, or a range value therebetween), it is determined that the crystal structure type of the pyrrhotite includes both monoclinic pyrrhotite and hexaferrite.
Specifically, when the X-ray diffraction pattern splits two peak shapes having equivalent intensities at around 44 ° 2 θ, the characteristic peaks split into two peaks 2 θ and d102The values 2 theta are 43.92 deg., d102＝2.0597；2θ＝44.16°，
Figure BDA0003556008330000061
The pyrrhotite in the sample is considered to be monoclinic pyrrhotite. When the X-ray diffraction pattern has tiny branches at the position of about 44 degrees 2 theta, but the branches are not obviously and relatively smooth,
Figure BDA0003556008330000062
when the intensity of (a) is significantly weaker than that of the main peak, the two types of monoclinic pyrrhotite and hexagonal pyrrhotite are considered to be simultaneously present in the sample. When the X-ray diffraction pattern is a smooth sharp-angle single peak around 44 ° at 2 θ, the pyrrhotite in the sample is considered to be hexapyrrhotite.
Preferably, in step (a), the calculating is carried out to calculate the monoclinic pyrrhotite content M in the ore to be predicteddAnd/or content M of hexa-pyrrhotitelThe method comprises the following steps:
firstly, carrying out chemical multi-element analysis on ores to be predicted, and calculating the mass percentage content (mass fraction) of Fe element in pyrrhotite in the ores to be predicted according to the result of the chemical multi-element analysiss。
Wherein after the chemical multi-element analysis, Fe, Cu, S and SiO in the sample can be obtained2、CaO、MgO、Al2O3The mass percentage content (mass fraction) of the iron element in the ore to be predicted is equal, and then the total content of the iron element in the ore to be predicted is subtracted by the content of the iron element in other iron-containing minerals, so that the mass percentage content Fe of the iron element in the pyrrhotite in the ore to be predicted can be obtaineds。
For example, in a sample having a chemical multielement analysis of 3% Fe and 0.2% Cu, the iron-containing minerals include pyrrhotite (chemical formula Fe)1-XS) and chalcopyrite (chemical formula CuFeS)2The iron content is 30.52% and the copper content is 34.56%), whereas the copper-containing minerals are chalcopyrite only, in which case the mineral content of chalcopyrite is 2% ÷ 34.56% × 100 ═ 5.79% as calculated from the Cu content. The content of Fe in the chalcopyrite is as follows: 5.79 × 30.52% ═ 1.77%, the iron content in pyrrhotite was 3% to 1.77% ═ 1.23%.
Then, detecting the content of iron element in a plurality of monoclinic pyrrhotite and/or the hexagonal pyrrhotite (including but not limited to 30, 40, 50, 60, 70, 80, 90, 100, 150 or 200), and calculating the average mass percentage content W of the iron element in the pyrrhotiteFe。
Namely, the content of the iron element in the monoclinic pyrrhotite particles and/or the hexagonal pyrrhotite particles in each ore to be predicted is respectively calculated, and then the average value of the content values is taken as WFe. Wherein, the more the number of the selected particles is, the more accurate the final prediction result is.
When the ore to be predicted only contains one of monoclinic pyrrhotite and hexagonal pyrrhotite, only the corresponding pyrrhotite type is detected; when the ore to be predicted contains both monoclinic pyrrhotite and hexagonal pyrrhotite, the two pyrrhotites need to be detected simultaneously.
In some specific embodiments of the present invention, in the detecting the content of the iron element in a plurality of the monoclinic pyrrhotite and/or the hexagonal pyrrhotite, a step of measuring the area of each monoclinic pyrrhotite particle and/or the hexagonal pyrrhotite particle is further included. So as to obtain SdAnd Sl。
Finally, according to the FesAnd said WFeCalculating the content M of monoclinic pyrrhotite in the ore to be predicteddAnd/or the content M of hexapyrrhotite in the ore to be predictedlWherein, in the step (A),
Figure BDA0003556008330000071
wherein S isdIs the total area of several monoclinic pyrrhotite particles (i.e. the sum of the areas of several monoclinic pyrrhotite particles), SlIs the total area of several particles of hexapyrrhotite (i.e. the sum of the areas of several particles of hexapyrrhotite).
When only monoclinic pyrrhotite is contained in the ore to be predicted, then Sl＝0。
When the ore to be predicted contains only hexa-pyrrhotite, then Sd＝0。
Preferably, in the process of detecting the content of the iron element in a plurality of monoclinic pyrrhotite and/or the hexaferrite pyrrhotite, the detection method comprises electron probe analysis and/or scanning electron microscope analysis.
Preferably, the number of particles detected by the monoclinic pyrrhotite and/or the hexaferrite is not less than 20; it is also possible to select 25, 30, 40 or 50.
Preferably, the total number of the detected particles of the monoclinic pyrrhotite and the hexagonal pyrrhotite is not less than 50, and 70, 80, 100 or 150 particles can be selected.
Preferably, in step (b), the division criteria for the particle size ranges comprise: the particle size is less than 0.02mm, 0.02-0.043 mm, 0.043-0.074 mm, 0.074-0.15 mm and more than 0.15 mm. Then m is 5.
Preferably, in step (b), the statistics are performed using a light reflection microscope.
The invention also provides a method for sorting pyrrhotite, which comprises the following steps:
judging the crystal structure type of pyrrhotite in the ore to be processed, and carrying out magnetic separation according to the crystal structure type;
when the crystal structure type of the pyrrhotite is only monoclinic pyrrhotite, performing low-intensity magnetic separation;
or when the crystal structure type of the pyrrhotite is only hexagonal pyrrhotite, performing strong magnetic separation;
or when the crystal structure types of the pyrrhotite comprise monoclinic pyrrhotite and hexagonal pyrrhotite, performing low-intensity magnetic separation and high-intensity magnetic separation in sequence (namely performing low-intensity magnetic separation first and then performing high-intensity magnetic separation).
According to the method, the crystal structure type of the pyrrhotite is judged, and the magnetic separation method is selected according to the crystal structure type, so that the yield and the recovery rate of the actually obtained pyrrhotite are closer to the numerical values of the yield and the recovery rate obtained by the prediction method. In addition, the sorting method can realize the high-efficiency separation of different types of pyrrhotite.
In some specific embodiments of the invention, the low-intensity magnetic separation is performed in a permanent magnetic drum low-intensity magnetic separator, and the high-intensity magnetic separation is performed in a high-gradient high-intensity magnetic separator.
In some embodiments of the invention, the method of determining the particular type of pyrrhotite (monoclinic pyrrhotite and hexapyrrhotite) in the ore to be predicted may select X-ray diffraction analysis. And judging the specific type of the pyrrhotite by an X-ray diffraction pattern obtained after X-ray diffraction analysis is carried out on the ore to be treated.
Preferably, the magnetic field intensity in the low-intensity magnetic separation process is 0.1T-0.2T; including but not limited to, a point value of any one of 0.11T, 0.12T, 0.13T, 0.14T, 0.15T, 0.16T, 0.17T, 0.18T, 0.19T, or a range of values between any two.
Preferably, the magnetic field strength in the strong magnetic separation process is 0.2T to 0.3T, including but not limited to a point value of any one of 0.21T, 0.22T, 0.23T, 0.24T, 0.25T, 0.26T, 0.27T, 0.28T, 0.29T or a range value between any two.
Preferably, before the magnetic separation, the ore to be processed is subjected to ore grinding treatment.
The grinding treatment refers to a treatment method for further reducing the particle size of ore to powder by means of impact and grinding stripping of media (such as steel balls, steel rods and gravel) and the ore itself in mechanical equipment.
In some specific embodiments of the present invention, the sample is subjected to ore grinding treatment based on the ore grinding fineness actually established for ore feeding, and the fineness that can cause dissociation of pyrrhotite monomers as much as possible should be selected when the ore grinding fineness is established.
Preferably, the ore grinding process is performed until the degree of dissociation of pyrrhotite monomers in the ore to be processed is greater than 90%, including but not limited to the point of any one of 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99% or a range between any two.
The invention also provides a beneficiation method, which comprises the prediction method for the yield and the recovery rate of the pyrrhotite as described above, and the beneficiation method for the pyrrhotite as described above.
The theoretical maximum yield and the theoretical maximum recovery rate obtained by the beneficiation method are respectively high in consistency with the actual yield and the actual recovery rate, and errors are small.
Compared with the prior art, the invention has the beneficial effects that:
(1) the prediction method for the yield and the recovery rate of pyrrhotite provided by the invention can reduce the prediction error of the theoretical maximum yield and the theoretical maximum recovery rate and improve the accuracy of prediction.
(2) The sorting method provided by the invention is closer to the theoretical yield and the theoretical recovery rate obtained by the prediction method. In addition, the sorting method can realize the high-efficiency separation of different types of pyrrhotite.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and other drawings can be obtained by those skilled in the art without creative efforts.
Fig. 1 is an X-ray diffraction pattern of a sulfur concentrate sample provided in example 1 of the present invention.
Detailed Description
The technical solutions of the present invention will be described clearly and completely with reference to the following detailed description, but those skilled in the art will understand that the following described examples are some, not all, of the examples of the present invention, and are only used for illustrating the present invention, and should not be construed as limiting the scope of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention. The examples, in which specific conditions are not specified, were conducted under conventional conditions or conditions recommended by the manufacturer. The reagents or instruments used are conventional products which are not indicated by manufacturers and are commercially available.
Example 1
The embodiment provides a method for predicting the yield and recovery rate of pyrrhotite in sulfur concentrate, wherein the main minerals in the sulfur concentrate are pyrrhotite and chalcopyrite, and also contain a small amount of sphalerite and galena, so that the pyrrhotite in the pyrrhotite needs to be separated to achieve the aim of desulfurization. The prediction method comprises the following steps:
(1) judging the crystal structure type of pyrrhotite in the sulfur concentrate: the sulfur concentrate sample was subjected to X-ray diffraction analysis to obtain an X-ray diffraction pattern, as shown in fig. 1. As can be seen from fig. 1, the characteristic peak at around 44 ° 2 θ is unimodal and there is a fine bifurcation, i.e., there are both monoclinic and hexagonal pyrrhotite types present in the sulfur concentrate sample.
Then, calculating the mass percentage content M of the monoclinic pyrrhotite in the ore to be predicteddAnd the mass percentage content M of the hexagonal pyrrhotitel：
(a) The sulfur concentrate samples were subjected to partial chemical multielement analysis including Fe element, and the results are shown in table 1 below.
TABLE 1 chemical multielement analysis of sulphur concentrate samples
Chemical composition Fe S Cu Zn SiO2 CaO
Content (wt.%) 44.58 27.05 3.81 0.37 7.78 6.13
Chemical composition MgO Al2O3 K2O Na2O As
Content (wt.%) 1.00 1.36 0.20 0.14 1.43
(b) The iron-containing minerals in the sulfur concentrate sample comprise pyrrhotite, chalcopyrite, blende and other minerals, the content of the chalcopyrite is calculated according to the content of copper, the content of iron in the chalcopyrite is further calculated, the mineral content of the blende is calculated according to the content of zinc, the iron content in the blende is further calculated, and the iron content in the iron-containing minerals is subtracted by total iron (namely the total content of iron elements in the sulfur concentrate sample), so that the content of iron in the pyrrhotite, namely Fe, is the content of iron in the pyrrhotites＝41.12％。
(c) The content of the iron element in the pyrrhotite (comprising monoclinic pyrrhotite and hexaferrite) particles in the sulfur concentrate sample is analyzed by adopting a scanning electron microscope, 100 particles are analyzed in total (because the data is too much, the middle 90 groups are not listed), and the area of each particle is measured, and the related data are shown in a table 2.
Table 2 results of measurements of pyrrhotite particles in sulfur concentrate samples
Figure BDA0003556008330000121
Namely, the average mass percentage content W of the iron element in the pyrrhotiteFe＝60.94％。
It can be seen that the total area of the monoclinic pyrrhotite particles: the total area of the hexapyrrhotite particles is 239892: 127524: 1.88: 1.
(d) Calculating the mineral amount (mass percentage content) of the monoclinic pyrrhotite in the sulfur concentrate sample according to the results in (b) and (c):
Figure BDA0003556008330000131
the amount of minerals (mass percentage content) of the hexaferrite in the sulfur concentrate sample is calculated as follows:
Figure BDA0003556008330000132
(2) calculating variable D, and calculating the content K of monoclinic pyrrhotite with the grain diameter less than 0.02mm in the sulfur concentrate sampledAnd the content K of the hexagonal pyrrhotite with the grain diameter less than 0.02mml：
Counting the number of the monoclinic pyrrhotite and the hexagonal pyrrhotite in the sulfur concentrate sample in different particle size ranges by adopting a reflection microscope, and counting the maximum particle size value and the minimum particle size value in each particle size range, wherein the result is shown in a table 3.
TABLE 3 statistics of the particle size and number of the particles of pyrrhotite
Figure BDA0003556008330000133
Calculating the variable D (where m is 5) from the above results:
Figure BDA0003556008330000134
thus, Kd＝Md×D＝44.06％×16.65％＝7.34％。
Kl＝Ml×D＝23.42％×16.65％＝3.90％。
(3) Calculating the maximum yield and the maximum recovery of the pyrrhotite (wherein Q)dAnd QlAll take 0.5, which is set according to the empirical value of a large amount of data counted by a magnetic test of pure pyrrhotite minerals):
maximum yield Y of low intensity magnetic separation theoryWeak (weak)＝Md-Kd×Qd＝44.06％-7.34％×0.5＝40.39％。
Maximum yield Y of strong magnetic separation theoryHigh strength＝Kd×Qd+(Ml-Kl×Ql)＝7.34％×0.5+(23.42％-3.90％×0.5)＝25.14％。
Maximum recovery rate of low intensity magnetic separation theory
Figure BDA0003556008330000141
Maximum recovery rate of strong magnetic separation theory
Figure BDA0003556008330000142
Example 2
The embodiment provides a method for sorting pyrrhotite, which comprises the following steps:
(1) sulphur concentrate sample (this sample is the same as the one used in example 1) treatment:
and grinding the sample by taking the grinding fineness determined by actual ore feeding as a standard. When the grinding fineness is less than 0.074mm and accounts for 80%, the monomer dissociation degree of the chalcopyrite in the sulfur concentrate sample is 92%, the monomer dissociation degree of the pyrrhotite is 95%, and the valuable minerals and the pyrrhotite are basically completely dissociated.
(2) X-ray diffraction analysis of the sulfur concentrate samples:
according to the X-ray diffraction pattern obtained in example 1, the sulfur concentrate sample contains monoclinic pyrrhotite and hexagonal pyrrhotite at the same time.
(3) Performing magnetic separation according to the crystal structure type: from the step (2), the crystal structure types of the pyrrhotite comprise monoclinic pyrrhotite and hexagonal pyrrhotite. The magnetic separation scheme was therefore determined to be: firstly, carrying out low-intensity magnetic separation on a sulfur concentrate sample, and preferentially selecting monoclinic pyrrhotite with the granularity of more than 0.02 mm; then carrying out strong magnetic separation to separate the hexagonal pyrrhotite and the monoclinic pyrrhotite with the granularity of less than 0.02 mm. So that pyrrhotite can be removed as clean as possible.
Specifically, when the permanent magnet drum is used for the low-intensity magnetic separation, the selected magnetic field strength is 0.1T. When a high-gradient strong magnetic machine is adopted for strong magnetic separation, the selected magnetic field intensity is 0.2T. The results of yield, grade and recovery of pyrrhotite obtained are shown in table 4.
The method for calculating the yield of the weak magnetic concentrate comprises the following steps: 202.12 ÷ 502.4 × 100% ═ 40.23%.
The method for calculating the yield of the strong magnetic concentrate comprises the following steps: 125.90 ÷ 502.4 × 100% ═ 25.06%.
The method for calculating the recovery rate of the weak magnetic concentrate comprises the following steps: 40.23 ÷ 44.06 × 100% ═ 91.31%.
The calculation method of the recovery rate of the strong magnetic concentrate comprises the following steps: 25.06 ÷ (44.06-40.23+23.42) × 100% ═ 91.96%.
Wherein "44.06%" in the calculation of the recovery rate of the weakly magnetic concentrate is the mineral amount M of monoclinic pyrrhotite in the sulfur concentrate sample calculated in example 1d. "23.42%" in the calculation of the recovery of the ferromagnetic concentrate was the amount of minerals M of hexa-pyrrhotite in the sulfur concentrate sample calculated in example 1l。
TABLE 4 results of yield, grade and recovery of pyrrhotite
Magnetic separation method Magnetic field intensity Product name Weight (g) Yield (%) Recovery (%)
Low intensity magnetic separation 0.1T Weakly magnetic concentrate 202.12 40.23 91.31
High magnetic separator 0.2T Strong magnetic concentrate 125.90 25.06 91.96
Tailings 174.38 34.71
Ore feeding 502.4 100
Comparing the theoretical maximum yield and the theoretical maximum recovery of example 1 with the actual yield and the actual recovery of example 2 in the tabulated manner, as shown in table 5 below, it can be seen that the values of the theoretical maximum yield and the theoretical maximum recovery obtained by the prediction method provided by the present invention are substantially identical to the values obtained by actual ore dressing. Therefore, the prediction method provided by the invention can be used for effectively predicting or evaluating the relevant indexes.
TABLE 5 comparison of the results obtained in example 1 with example 2
Figure BDA0003556008330000161
Comparative example 1
The method for sorting pyrrhotite provided by the comparative example is basically the same as that of the example 2, and the difference is only that in the step (3), the magnetic field intensity selected when the low-intensity magnetic separation is carried out is 0.3T; the magnetic field strength selected when performing the high-intensity magnetic separation was 0.5T.
The results of yield, grade and recovery of pyrrhotite obtained are shown in table 6.
TABLE 6 results of yield, grade and recovery of pyrrhotite
Magnetic separation method Magnetic field intensity Product name Weight (g) Yield (%) Recovery (%)
Low intensity magnetic separation 0.3T Weakly magnetic concentrate 238.98 45.91 104.21
High magnetic separator 0.5T Strong magnetic concentrate 112.2 21.56 99.96
Tailings 169.31 32.53
Ore feeding 520.49 100
Among them, in this comparative example 1:
the method for calculating the yield of the weak magnetic concentrate comprises the following steps: 238.98 ÷ 520.49 × 100% ═ 45.91%.
The method for calculating the yield of the strong magnetic concentrate comprises the following steps: 112.2 ÷ 520.49 × 100% ═ 21.56%.
The method for calculating the recovery rate of the weak magnetic concentrate comprises the following steps: 45.91 ÷ 44.06 × 100% ═ 104.21%.
The calculation method of the recovery rate of the strong magnetic concentrate comprises the following steps: 21.56%/(45.91-44.06 +23.42) — 91.96%.
Wherein "44.06%" in the calculation of the recovery rate of the weakly magnetic concentrate is the mineral amount M of monoclinic pyrrhotite in the sulfur concentrate sample calculated in example 1d. "23.42%" in the calculation of the recovery of the ferromagnetic concentrate was the amount of minerals M of hexa-pyrrhotite in the sulfur concentrate sample calculated in example 1l。
Because the magnetic field intensity is strengthened in the weak magnetic stage, besides all monoclinic pyrrhotite is recovered, part of hexagonal pyrrhotite is also recovered, the recovery rate of the weak magnetic separation part exceeds 100 percent, and similarly, because the magnetic field intensity of the strong magnetic separation part is also increased, the recovery rate is close to 100 percent, and the loss rate is almost zero.
While particular embodiments of the present invention have been illustrated and described, it will be appreciated that the above embodiments are merely illustrative of the technical solution of the present invention and are not restrictive; those of ordinary skill in the art will understand that: modifications may be made to the above-described embodiments, or equivalents may be substituted for some or all of the features thereof without departing from the spirit and scope of the present invention; the modifications or the substitutions do not make the essence of the corresponding technical solutions depart from the scope of the technical solutions of the embodiments of the present invention; it is therefore intended to cover in the appended claims all such alternatives and modifications that are within the scope of the invention.

Claims (10)

1. A prediction method of yield and recovery of pyrrhotite, characterized in that the prediction method comprises the following steps:
(a) judging the crystal structure type of pyrrhotite in the ore to be processed, and calculating the content M of monoclinic pyrrhotite in the ore to be predicteddAnd/or content M of hexa-pyrrhotitel；
(b) Counting the number of particles of monoclinic pyrrhotite and/or hexagonal pyrrhotite in the ore to be predicted in different particle size ranges, counting the maximum particle size value and the minimum particle size value in each particle size range, and then calculating a variable D according to the counting result; wherein the content of the first and second substances,
Figure FDA0003556008320000011
wherein a is the maximum particle size value within the particle size range of less than 0.02 mm; b is the smallest particle size value within the particle size range of less than 0.02 mm; n is the number of particles within the particle size range of less than 0.02 mm; a is the maximum particle size value in the particle size range; b is the smallest particle size value in the particle size range; n is the number of particles in the particle size range; m is the grading number of the particle size range;
(c) calculating the content K of monoclinic pyrrhotite with the grain diameter less than 0.02mm in the ore to be predicteddAnd/or the content K of the hexagonal pyrrhotite with the grain diameter less than 0.02mml(ii) a Wherein, Kd＝Md×D，Kl＝Ml×D；
(d) Respectively calculating the maximum yield and the maximum recovery rate of the pyrrhotite;
theoretical maximum yield Y of pyrrhotite when the type of crystal structure of pyrrhotite in the ore to be treated is only monoclinic pyrrhotited＝Md-Kd×QdWherein Q isdIs the loss coefficient, Q, in the process of low intensity magnetic separationd0.4-0.6; theoretical maximum recovery H of pyrrhotited＝Yd/Md×100％；
Theoretical maximum yield Y of pyrrhotite when the type of crystal structure of pyrrhotite in the ore to be treated is only hexagonal pyrrhotitel＝Ml-Kl×QlWherein Q islIs the loss coefficient, Q, in the course of strong magnetic separationl0.4-0.6; theoretical maximum recovery H of pyrrhotitel＝Yl/Ml×100％；
When the crystal structure type of the pyrrhotite in the ore to be processed contains monoclinic pyrrhotite and hexagonal pyrrhotite, the theoretical maximum yield of the pyrrhotite comprises the maximum yield Y of the weak magnetic separationWeak (weak)And maximum yield Y of strong magnetic separationHigh strength(ii) a The theoretical maximum recovery rate of pyrrhotite comprises the maximum recovery rate H of low intensity magnetic separationWeak (weak)And maximum recovery of strong magnetic separationRate HStrong strength (S)；
Wherein, YWeak (weak)＝Md-Kd×Qd；
Figure FDA0003556008320000021
YHigh strength＝Kd×Qd+(Ml-Kl×Ql)；
Figure FDA0003556008320000022
2. The prediction method according to claim 1, wherein in the step (a), the method for judging the crystal structure type of pyrrhotite in the ore to be processed comprises:
carrying out X-ray diffraction analysis on the ore to be processed to obtain an X-ray diffraction pattern; then judging the crystal structure type of pyrrhotite according to the X-ray diffraction spectrum;
preferably, the method for determining the crystal structure type of pyrrhotite specifically includes: when the X-ray diffraction pattern has double peaks at 42-46 degrees of 2 theta and the absolute value of the difference of the intensities of the double peaks is less than 0.5, judging that the crystal structure type of the pyrrhotite is monoclinic pyrrhotite;
or when the X-ray diffraction pattern is a single peak at 42 ° to 46 ° 2 θ and the peak shape thereof is smooth without bifurcation, determining that the crystal structure type of the pyrrhotite is hexapyrrhotite;
or when the X-ray diffraction pattern is a single peak at the 2 theta (42-46 degrees) and the peak shape thereof is forked, judging that the crystal structure type of the pyrrhotite comprises monoclinic pyrrhotite and hexapyrrhotite.
3. The prediction method according to claim 1, characterized in that in step (a), the calculation of the content M of monoclinic pyrrhotite in the ore to be predicteddAnd/or content M of hexa-pyrrhotitelThe method comprises the following steps:
carrying out chemical multi-element analysis on the ore to be predicted, and calculating the mass percentage content Fe of the iron element in the pyrrhotite in the ore to be predicted according to the result of the chemical multi-element analysiss；
Detecting the content of iron elements in a plurality of monoclinic pyrrhotite and/or hexagonal pyrrhotite, and calculating the average mass percentage content W of the iron elements in the pyrrhotiteFe；
Then, according to the FesAnd said WFeCalculating the content M of monoclinic pyrrhotite in the ore to be predicteddAnd/or the content M of hexapyrrhotite in the ore to be predictedlWherein, in the step (A),
Figure FDA0003556008320000031
wherein S isdIs the total area of several monoclinic pyrrhotite particles, SlIs the total area of several grains of hexa-pyrrhotite.
4. The prediction method according to claim 3, wherein in the process of detecting the content of iron element in a plurality of monoclinic pyrrhotite and/or hexaferrite pyrrhotite, the detection method comprises electron probe analysis and/or scanning electron microscope analysis;
preferably, the number of particles detected by the monoclinic pyrrhotite and/or the hexaferrite is not less than 20;
preferably, the total number of the particles detected by the monoclinic pyrrhotite and the hexagonal pyrrhotite is not less than 50.
5. The prediction method according to claim 1, wherein in the step (b), the classification criterion of the particle size range includes: the particle size is less than 0.02mm, 0.02-0.043 mm, 0.043-0.074 mm, 0.074-0.15 mm and more than 0.15 mm; and m is 5.
6. The prediction method according to claim 1, wherein in the step (b), the statistics are performed using a light reflection microscope.
7. The method for sorting pyrrhotite is characterized by comprising the following steps of:
judging the crystal structure type of pyrrhotite in the ore to be processed, and carrying out magnetic separation according to the crystal structure type;
when the crystal structure type of the pyrrhotite is only monoclinic pyrrhotite, performing low-intensity magnetic separation;
or when the crystal structure type of the pyrrhotite is only hexagonal pyrrhotite, performing strong magnetic separation;
or when the crystal structure types of the pyrrhotite comprise monoclinic pyrrhotite and hexagonal pyrrhotite, carrying out weak magnetic separation and strong magnetic separation in sequence.
8. The method for sorting pyrrhotite according to claim 7, characterized in that the magnetic field strength during the low-intensity magnetic separation is 0.1T to 0.2T;
preferably, the magnetic field intensity in the strong magnetic separation process is 0.2T-0.3T.
9. The method for sorting pyrrhotite according to claim 7, characterized in that the ore to be processed is subjected to ore grinding treatment before the magnetic separation;
preferably, the ore grinding treatment is carried out until the dissociation degree of pyrrhotite monomers in the ore to be treated is more than 90%.
10. A beneficiation process comprising a prediction method of maximum yield and maximum recovery of pyrrhotite according to any one of claims 1 to 6, and a beneficiation method of pyrrhotite according to any one of claims 7 to 9.
CN202210276692.7A 2022-03-21 2022-03-21 Prediction method for yield and recovery rate of pyrrhotite and application thereof Pending CN114708926A (en)

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