A method for characterizing and segmenting the surface roughness in a numerical test of a spiral chute sorting system.

Abstract

This invention discloses a method for characterizing the wall roughness value in a numerical test of spiral chute sorting, comprising the following steps: Under selected operating conditions, conducting an actual mineral particle sorting test on a spiral chute; extracting separated products from different sections of the chute surface; and measuring the actual slurry flow rate and iron grade of each product; generating a computational domain for the spiral chute based on its structural parameters and the average wall roughness Ra; and comparing the mineral particle sorting test results under actual and simulated conditions, statistically analyzing the different roughness heights K in the numerical sorting test. s Under the given conditions, the product slurry flow rate and iron grade in different sections of the tank surface were compared numerically. The slurry flow rate and iron grade within the same radial region were then compared. The K value, which showed the smallest deviation between the numerical separation test slurry flow rate and iron grade data and the actual separation test values, was selected. s The value is taken as the actual wall roughness Ra under the same conditions, and the corresponding equivalent relation is obtained.

Description

Technical Field

[0001] This invention belongs to the field of fully automated products and relates to a method for characterizing and segmenting the surface roughness in numerical tests of spiral chute sorting. Background Technology

[0002] Gravity separation, with its advantages of low production cost, high production capacity, and environmental friendliness, has become the primary method for ore beneficiation and enrichment. Spiral chutes, as typical composite force field separation equipment, are widely used in ore resource and waste resource recovery processes due to their simple structure, small footprint, and low cost. However, with increasing wear on the production chute surface and a decline in on-site separation indicators, it is necessary to strengthen research on the theory and influencing mechanisms of roughness to provide a scientific basis for the design of chute surface materials and structures.

[0003] Patent [CN214811658U] discloses a fish-scale-like raised wall surface with good sorting effect. Patent [CN217910880U] discloses a wall structure combining a friction pad, wear-resistant layer, rubber plate, and plexiglass base plate, which can improve the sorting effect of mineral particles and extend the service life of the spiral chute surface. Patent [CN115742387A] discloses a method for repairing damaged surfaces of a gravity separation spiral chute; the repaired surface has the same sorting effect and wear resistance as a new chute. Patent [CN216936446U] discloses a spiral chute for gravity separation, which provides a replaceable chute surface with friction protrusions, friction bumps, and friction surfaces inside, which can increase the friction of the chute plate surface, facilitating the sorting of mineral particles with relatively low density.

[0004] The selection of these designs and optimization combinations is generally based on extensive physical experiments, consuming significant resources and time, and lacking a fundamental method to establish the influence mechanism of wall roughness. With the development of numerical simulation methods, high-precision numerical simulation experiments have created conditions for fundamentally revealing the influence mechanism of wall roughness on the flow field and particle motion behavior of spiral chutes. However, current numerical experiments rarely consider the influence of wall roughness, resulting in a deviation between numerical simulation and actual processes. How to reasonably set the wall roughness of spiral chutes during numerical simulation is a necessary foundation for clarifying the influence mechanism of wall roughness and a key to further developing a method for optimizing chute surface roughness design. Summary of the Invention

[0005] To solve the above problems, the technical solution adopted by the present invention is: a method for characterizing the wall roughness value in a numerical test of a spiral chute sorting system, comprising the following steps:

[0006] Points are evenly distributed throughout the entire spiral groove surface, and the wall roughness at each point is measured. The measured values ​​are then averaged to obtain the average wall roughness Ra of the groove surface.

[0007] Under the selected operating conditions, an actual mineral particle sorting test was conducted on the spiral chute. Separated products were collected from different sections of the chute surface, and the actual slurry flow rate and iron grade of each product were measured.

[0008] The computational domain of the spiral chute is generated based on its structural parameters and the average wall roughness Ra of the chute surface.

[0009] A numerical sorting experiment was conducted under simulated spiral chute conditions identical to those in the actual mineral particle sorting experiment. Numerical calculations were performed on the slurry flow rate and iron grade of the products intercepted in different areas of the spiral chute.

[0010] Comparing the mineral particle sorting test results under actual and simulated conditions of the spiral chute, the numerical results of the sorting tests were statistically analyzed for different roughness heights K. s Under the given conditions, the slurry flow rate and iron grade of the products in different sections of the tank surface were compared numerically. The slurry flow rate and iron grade within the same radial region were compared, and the K value with the smallest deviation between the numerical separation test slurry flow rate and iron grade data and the actual separation test values ​​was selected. s The value is taken as the actual wall roughness Ra under the same conditions, and the corresponding equivalent relation is obtained.

[0011] Furthermore, the simulation conditions for the spiral chute include:

[0012] Import the hexahedral mesh of the computational domain within the discrete spiral chute into the CFD software Fluent, and set up the multiphase flow model and the turbulence model.

[0013] Set the inlet material parameters, calculate the boundary conditions of the calculation area, and input the roughness value;

[0014] The multiphase flow model adopts the Multi-fluid VOF model, and the turbulence model adopts the RNG k-ε model;

[0015] The boundary conditions include the velocity inlet and pressure outlet of the spiral chute, the non-slipping lower wall of the chute and the freely sliding upper wall of the chute, wherein the pressure outlet is set to the local atmospheric pressure, i.e., the relative pressure is 0.

[0016] The roughness value is determined by the input roughness constant C. s and roughness height K s Value control, where the roughness constant C s The default value is 0.5, and the roughness height is determined by K. s =5~10Ra formula determined.

[0017] Furthermore, the wall roughness at each measurement point is measured in the same direction as the main flow direction within the spiral chute.

[0018] Furthermore, the equivalent relation is expressed as follows:

[0019] K s =c Ra

[0020] Where: c is a constant.

[0021] Furthermore, the structural parameters of the spiral chute include cross-sectional shape, outer radius, inner radius, pitch, and number of turns.

[0022] The segmented examination method for characterizing the wall roughness value in a numerical test of a spiral chute sorting system, as described in any one of the above methods, includes the following steps:

[0023] The bottom wall of the tank is divided into several spiral bands along the radial direction, thus obtaining segmented areas where the wall conditions can be freely adjusted.

[0024] The roughness of the bottom wall surface of the tank was investigated in segments. The roughness height K of each segment was determined using Fluent software. s After setting up, a sorting numerical test was conducted to obtain the separation performance of the spiral chute when the wall roughness of each section was adjusted.

[0025] Furthermore: when the spiral ribbon is evenly divided into an inner spiral ribbon, a middle spiral ribbon, and an outer spiral ribbon, a wear-resistant material is used on the wall surface of the middle spiral ribbon to improve separation performance.

[0026] This invention provides a method for characterizing and segmenting the surface roughness of a spiral chute in a numerical sorting test. By measuring the surface roughness of an actual spiral chute wall, and based on actual sorting tests and numerical experiments, it establishes the relationship between the actual surface roughness Ra and the numerical roughness height K. s The relationship is verified by equivalent relation verification, and equivalent relational formulas that represent each other are established. This allows for the examination of the results of mineral particle separation under different wall roughness conditions. Furthermore, by segmenting the radial direction of the tank surface, the influence of wall roughness in different sections on the particle separation process and results is examined. This method has the following advantages:

[0027] 1. The actual wall roughness Ra and roughness height K established by the spiral chute wall roughness value characterization method of the present invention s The equivalent relationship can provide a basis for the reasonable setting of wall roughness in the numerical test of spiral chute separation process, and lay the foundation for accurately examining the influence of wall roughness on the separation results of mineral particles.

[0028] 2. The method for segmented examination of spiral chute wall roughness based on numerical experiments developed in this invention has the outstanding feature of saving manpower and material resources. It provides a feasible way to deeply reveal the influence mechanism of wall roughness in different sections on the particle separation process and has important reference value for the selection of spiral chute wall materials and their roughness.

[0029] This application provides a method for characterizing and segmenting the wall roughness value in numerical tests of spiral chute sorting, which can save economic costs and accurately examine the influence of wall roughness on mineral particle separation. Attached Figure Description

[0030] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0031] Figure 1 This is a flowchart of a method for characterizing the wall roughness value in a numerical test of spiral chute sorting according to the present invention;

[0032] Figure 2 This is a diagram showing the shape of the bottom of the spiral chute.

[0033] Figure 3 This is a schematic diagram of the zoned measurement of the surface roughness of the spiral chute wall;

[0034] Figure 4 This is a distribution diagram of the surface roughness measurement results of the spiral chute wall;

[0035] Figure 5 A comparison chart of simulated and measured values ​​of slurry flow rate for the separated products;

[0036] Figure 6 A comparison chart of simulated and measured iron content values ​​of the separated products;

[0037] Figure 7 A schematic diagram showing the segmentation of the radial region of the spiral chute surface;

[0038] Figure 8 The separation efficiency curve is shown when the surface roughness of the inner edge region of the spiral chute is adjusted.

[0039] Figure 9 The separation efficiency curve is shown when the wall roughness of the central region of the spiral chute is adjusted.

[0040] Figure 10 The separation efficiency curve is shown when the surface roughness of the outer edge region of the spiral chute is adjusted. Detailed Implementation

[0041] It should be noted that, unless otherwise specified, the embodiments and features in the embodiments of the present invention can be combined with each other. The present invention will be described in detail below with reference to the accompanying drawings and embodiments.

[0042] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. The following description of at least one exemplary embodiment is merely illustrative and is in no way intended to limit the present invention or its application or use. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0043] Figure 1 This is a flowchart of a method for characterizing the wall roughness value in a numerical test of spiral chute sorting according to the present invention;

[0044] A method for characterizing the wall roughness value in a numerical test of a spiral chute sorting system includes the following steps:

[0045] S11: Distribute points evenly throughout the entire spiral groove surface, measure the wall roughness at each point, and average the measured values ​​to obtain the average wall roughness Ra of the groove surface.

[0046] The uniform distribution means that the measuring points are evenly arranged along the main flow direction of the spiral chute.

[0047] The average wall roughness Ra is the arithmetic mean of the roughness measurements at all measurement points.

[0048] S12: Under the selected operating conditions, conduct actual mineral particle sorting tests on the spiral chute, extract the separated products from different sections of the chute surface, and determine the actual slurry flow rate and iron grade of each product.

[0049] The sorting index data was obtained through measurement, specifically by timing and sampling during the actual sorting test. To ensure the accuracy of the sorting test, three repeated tests were conducted, and the final result was the average value.

[0050] The operating conditions include the composition of the feed minerals, the feed flow rate, and the feed solids mass concentration.

[0051] The slurry flow rate of each product is the slurry volume of the product per unit time.

[0052] The iron grade of each product is a criterion for evaluating the results of the sorting test.

[0053] S13: Generate the computational domain of the spiral chute based on its structural parameters and the average wall roughness Ra of the chute surface;

[0054] S14: Set up the same spiral chute simulation conditions as the actual mineral particle sorting test to conduct a sorting numerical test, and perform numerical calculations on the slurry flow rate and iron grade of the products intercepted in different chute surface areas;

[0055] S15: Compare the mineral particle sorting test results under actual and simulated conditions of the spiral chute, and statistically analyze the sorting numerical results for different roughness heights K. s Under certain conditions, the slurry flow rate and iron grade of the product in different intervals of the tank surface were measured. Numerical comparisons were made of the slurry flow rate and iron grade of the product in the same radial region. The K value, with the smallest deviation between the numerical test slurry flow rate and iron grade data and the actual separation test values, was selected. s The value is taken as the actual wall roughness Ra under the same conditions, and the corresponding equivalent relation is obtained.

[0056] Steps S11 / S12 are executed in parallel, and then steps S13 / S14 / S15 are executed sequentially.

[0057] The structural parameters of the spiral chute include cross-sectional shape, outer radius, inner radius, pitch, and number of turns;

[0058] The computational domain of the spiral chute is generated by using the 3D modeling software SolidWorks to establish the geometric model of the computational domain within the target spiral chute, and then importing it into the ICEM CFD software to discretize the computational domain into a hexahedral mesh.

[0059] Furthermore, the simulation conditions for the spiral chute include:

[0060] Import the hexahedral mesh of the computational domain within the discrete spiral chute into the CFD software Fluent, and set up a multiphase flow model and a turbulence model. The results under different multiphase flow models and turbulence models would normally be inconsistent, but this method can also be used to verify different turbulence models and multiphase flow models, although the results may be different.

[0061] Set the inlet material parameters, calculate the boundary conditions of the calculation area, and input the roughness value;

[0062] Inlet material conditions include the inlet velocities of the fluid and particles, and the volume fraction (mass percentage) of different particles.

[0063] The multiphase flow model adopts the Multi-fluid VOF model, and the turbulence model adopts the RNG k-ε model;

[0064] The boundary conditions include the velocity inlet and pressure outlet of the spiral chute, the non-slipping lower wall of the chute and the freely sliding upper wall of the chute, wherein the pressure outlet is set to the local atmospheric pressure, i.e., the relative pressure is 0.

[0065] The roughness value is determined by the input roughness constant C. s and roughness height K s Value control, where the roughness constant C s The default value is 0.5, and the roughness height is determined by K. s =5~10Ra formula determined.

[0066] Furthermore, the equivalent relation is expressed as follows:

[0067] K s =c Ra

[0068] Where: c is a constant;

[0069] In the numerical and actual sorting test results, the slurry flow rate and iron grade in the same radial region were numerically compared, and the K value with the higher agreement between the numerical test data was selected. s The value is taken as the actual wall roughness Ra under the same conditions, and the corresponding equivalent relation K is obtained. s =c Ra;

[0070] The segmented examination method for characterizing the wall roughness value in a numerical test of a spiral chute sorting system, as described in any one of the above methods, includes the following steps:

[0071] S21: Divide the bottom wall of the tank into several spiral bands along the radial direction to obtain segmented areas where the wall conditions can be freely adjusted.

[0072] The bottom wall of the trough is divided into several spiral bands along the radial direction. When dividing the wall area, the computational domain mesh of the spiral chute needs to be cut into the same area first to generate different bottom walls of the trough, thereby obtaining segmented areas where the wall conditions can be freely adjusted.

[0073] S22: A segmented roughness test was conducted on the bottom wall surface of the tank. The corresponding roughness height K was determined for each segmented region using Fluent software. s After setting up, numerical experiments were conducted to obtain the separation performance of the spiral chute when the wall roughness of each section was adjusted. Further control measures were derived through segmented optimization analysis of wall roughness: when the spiral band is divided into an inner spiral band, a middle spiral band, and an outer spiral band, wear-resistant materials are used on the wall of the middle spiral band to improve separation performance.

[0074] The corresponding roughness height K s Set the corresponding roughness height K. sSet according to the actual measured value of wall roughness Ra and its combination; if there is no actual wall roughness value as a reference, use the imagined combination setting, such as setting the wall roughness to a uniform value for all, or setting the wall roughness in different areas to increase or decrease sequentially according to the area distribution, etc.

[0075] The separation performance of the spiral chute when adjusting the wall roughness of each section is obtained. The separation performance is evaluated by the separation efficiency, which is the difference between the recovery rates of the target mineral and gangue mineral in the concentrate product.

[0076] The control measures derived from the segmented optimization analysis of wall roughness are based on the calculation results of separation performance.

[0077] Steps S21 and S22 are executed sequentially;

[0078] Example 1: A method for characterizing the wall roughness value in a numerical test of spiral chute sorting, the flowchart of which is shown below. Figure 1 As shown, it includes the following steps:

[0079] S1. Distribute points evenly throughout the entire spiral chute surface, measure the wall roughness at each point, and average the measured values ​​to obtain the average wall roughness Ra of the chute surface.

[0080] The structural parameters of the target spiral chute include cross-sectional shape, outer radius, inner radius, pitch, and number of turns. The bottom shape was obtained through actual measurement based on a laboratory-type spiral chute with a diameter of 400 mm. The results are as follows: Figure 2 As shown, the structural parameter values ​​are shown in Table 1.

[0081] Table 1. Overview of Helical Chute Structural Parameters

[0082] Structural parameters numerical values Outer radius (R) 200mm <![CDATA[Inner radius (r0)]]> 50mm Pitch (P) 240mm Number of turns 3.25

[0083] The uniform distribution of measurement points means that the measurement points are evenly arranged along the main flow direction of the spiral chute, dividing one circumference of the chute surface into eight equal parts around the spiral direction, and measuring the same location range in each part. A schematic diagram of the measurement is shown below. Figure 3 As shown;

[0084] The average wall roughness Ra is calculated by taking the arithmetic mean of the roughness measurements at all measurement points. The arithmetic mean roughness Ra is selected as the indicator of wall roughness. The measuring equipment used is a PS1-M300 handheld roughness measuring instrument manufactured by Mar Precision Instruments GmbH, Germany. The measurement results of the Ra of the groove wall roughness in 24 equal parts of the three groove surfaces are as follows: Figure 4 As shown, to facilitate the verification of the wall roughness in subsequent numerical simulation, the arithmetic mean of the measured data Ra = 4.61 μm is taken as the overall wall roughness of the groove surface;

[0085] S2. Based on the spiral chute, an actual mineral particle separation test was conducted under the selected operating conditions. Separated products were collected from different sections of the chute surface, and the slurry flow rate and iron grade of each product were measured.

[0086] The operating conditions include feed mineral composition, feed flow rate, and feed solids concentration, wherein the feed mineral composition is: the target mineral is hematite with a density of 4950 kg / m³. 3 The median grain size was selected as 107.97 μm, the gangue mineral was quartz, and the density was 2650 kg / m³. 3 The median particle size was selected as 105.49 μm, and the iron content in the feed was 46.12%; the feed flow rate was 12 L / min (7.2 m³ / min). 3 / h), the solid mass concentration in the feed is 16.74%;

[0087] The slurry flow rate of each product is the slurry volume of products in different intervals per unit time;

[0088] The iron grade of each product is a criterion for evaluating the results of the sorting test.

[0089] S3. Generate the computational domain of the spiral chute. Use the 3D modeling software SolidWorks to establish the geometric model of the computational domain inside the target spiral chute, and then import it into the ICEM CFD software to discretize the computational domain into a hexahedral mesh.

[0090] S4. Set the simulation conditions for the spiral chute. Import the mesh generated in step S3 into the CFD software Fluent, set the multiphase flow model and turbulence model, further set the inlet material parameters and calculation domain boundary conditions, input the roughness value, and then perform numerical calculations.

[0091] The multiphase flow model and the turbulence model are respectively the Multi-fluid VOF model and the RNG k-ε model;

[0092] The boundary conditions include the velocity inlet and pressure outlet of the spiral chute, the non-slipping lower wall and the freely sliding upper wall, wherein the pressure outlet is set to the local atmospheric pressure, i.e., the relative pressure is 0.

[0093] The roughness value is determined by the input roughness constant C. s and roughness height K s Value control, where the roughness constant C s The default value is 0.5, and the roughness height K is... s Based on a comprehensive review of literature information containing similar flow processes, five K values ​​of 0.01, 0.02, 0.03, 0.04, and 0.05 mm were selected and set within the range of 5–10 Ra. s value;

[0094] S5. Compare the test results of the spiral chute under actual and simulated conditions, and statistically analyze the five K values ​​of 0.01, 0.02, 0.03, 0.04, and 0.05 mm. s Under the given conditions, the product slurry flow rate and iron grade in different sections of the tank surface were analyzed. Based on the comprehensive analysis of numerical test and actual separation test results, the corresponding equivalent relationship K was obtained. s =c Ra; By comprehensively comparing the actual test and numerical test results of the slurry flow rate and iron grade of the product in different regions, the 2 to 3 sets of results that are closest in magnitude are taken as the judgment, and the intersection of them is taken to obtain the condition with the highest degree of consistency.

[0095] Comparing the mineral particle sorting test results under actual and simulated conditions of the spiral chute, the numerical results of the sorting tests were statistically analyzed for different roughness heights K. s Under the given conditions, the product slurry flow rate and iron grade in different sections of the tank surface were compared numerically. The slurry flow rate and iron grade within the same radial region were then compared. The K value, which showed the smallest deviation between the numerical separation test slurry flow rate and iron grade data and the actual separation test values, was selected. s The value is taken as the actual wall roughness Ra under the same conditions, and the corresponding equivalent relation is obtained.

[0096] The analysis comprehensively examines the results of numerical and actual sorting experiments. In both experiments, the spiral chute outlet is divided into inner, middle, and outer zones. In the numerical experiments, the product slurry flow rate and iron grade for each zone are directly obtained through post-processing calculations using CFD-POST software. In the actual experiments, timed sampling is used to acquire sorting index data. The slurry flow rate and iron grade of the product within each zone are numerically compared, and the K value with the highest agreement between the numerical and actual experimental data is selected. s The value is taken as the actual wall roughness Ra under the same conditions, and the corresponding equivalent relation K is obtained. s =c Ra; the experimental results are for example Figure 5 and Figure 6 As shown, different K values ​​are used. s When setting values, the simulated and measured values ​​of the index deviate to varying degrees. The deviation is smallest when Ks is set to 0.03 mm. Therefore, the equivalent relationship K can be calculated. s ≈6.51Ra.

[0097] 1. In the actual sorting test, timed sampling was conducted to obtain sorting index data. To ensure the accuracy of the sorting test, three repeated tests were performed, and the final result was the average value.

[0098] 2. Simulation calculations are used to obtain the slurry flow rate and iron grade of the corresponding products.

[0099] 3. Compare the results of actual sorting experiments with numerical experiments, and use different K values. sThe simulated values ​​and measured values ​​of the indicators obtained when setting the values ​​deviate to varying degrees, with the smallest deviation occurring at a setting value of 0.03 mm.

[0100] A segmented evaluation method for characterizing the wall roughness value in a numerical test of a spiral chute sorting system includes the following steps:

[0101] S6. In ICEM CFD software, the bottom wall of the tank is divided into several spiral bands along the radial direction, and the corresponding segmented area where the wall conditions can be freely adjusted is obtained.

[0102] The bottom wall of the chute is divided into several spiral bands along the radial direction. When dividing the wall region in ICEM CFD software, the computational domain mesh of the spiral chute needs to be cut into the same region first to generate different bottom walls, thus obtaining segmented regions with freely adjustable wall conditions. A schematic diagram of the single-loop segmentation of the spiral chute surface into inner edge, middle, and outer edge regions in the radial direction is shown below. Figure 7 As shown;

[0103] S7. Segmented roughness test of the bottom wall of the tank: In Fluent software, the roughness height K of the segmented area is set accordingly. s After setting up, numerical experiments were conducted to obtain the separation performance of the spiral chute when adjusting the wall roughness of each segment region. Further analysis of the segmented wall roughness optimization was conducted to derive control measures.

[0104] The corresponding roughness height K s Set the corresponding roughness height K. s Based on the actual measured wall roughness Ra value and its combination settings; in this experiment, according to the combination settings, the overall wall surface equivalent roughness height K is determined. s Based on a minimum roughness of 0.03 mm, the wall roughness height K in the inner, middle, and outer edge regions is further increased. s The values ​​were set to 0.01, 0.05, 0.1, and 0.2 mm respectively.

[0105] The numerical test structural parameters are consistent with those in step S2. In terms of operating conditions, referencing the feeding conditions of a spiral chute beneficiation section at a certain production site, both hematite and quartz were set to two particle size levels, coarse and fine, and the ore was blended and slurry adjusted proportionally to ensure that the iron grade and concentration, among other feeding conditions, remained consistent with those at the site. The experimental particle separation efficiency results for hematite and quartz after adjusting the local wall roughness are as follows: Figures 8-10 As shown;

[0106] The separation performance of the spiral chute when adjusting the wall roughness of the segmented area is obtained. The separation performance is evaluated by the separation efficiency, which is the difference between the recovery rates of the target mineral and gangue mineral in the concentrate product.

[0107] The control measures derived from the segmented optimization analysis of the wall roughness are based on the calculation results of the separation performance. The analysis shows that as the roughness of the middle and outer regions increases, the maximum separation efficiency of hematite and quartz will decrease significantly, thereby reducing the separation performance of the spiral chute. The inner region only shows a significant decrease when its roughness is greater than 0.1 mm. The optimal product splitting position only shifts significantly outward when the roughness of the middle region increases.

[0108] Furthermore, to obtain better and more stable prediction indicators for spiral chute separation, this method can propose specific control measures for the segmented optimization and control of the roughness of the chute wall: prevent the overall and local wall roughness values ​​of the chute surface from being too large, and ensure the stability of the spiral chute separation performance; strengthen the control of the wall roughness in the middle of the chute bottom, while improving the wear resistance of the wall surface in the middle region and expanding the radial distribution difference between hematite and quartz; the inner edge of the chute bottom should be kept smooth to promote the inward migration of hematite, thereby improving the separation performance of the spiral chute.

[0109] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for characterizing the surface roughness value in a spiral chute sorting numerical test, characterized in that: Includes the following steps: Points are evenly distributed throughout the entire spiral groove surface, and the wall roughness at each point is measured. The measured values ​​are then averaged to obtain the average wall roughness Ra of the groove surface. Under the selected operating conditions, an actual mineral particle sorting test was conducted on the spiral chute. Separated products were collected from different sections of the chute surface, and the actual slurry flow rate and iron grade of each product were measured. The computational domain of the spiral chute is generated based on its structural parameters and the average wall roughness Ra of the chute surface. A numerical sorting experiment was conducted under simulated spiral chute conditions identical to those in the actual mineral particle sorting experiment. Numerical calculations were performed on the slurry flow rate and iron grade of the products intercepted in different areas of the spiral chute. Comparing the mineral particle sorting test results under actual and simulated conditions of the spiral chute, the numerical results of the sorting tests were statistically analyzed for different roughness heights K. s Under the given conditions, the slurry flow rate and iron grade of the products in different sections of the tank surface were compared numerically. The slurry flow rate and iron grade within the same radial region were compared, and the K value with the smallest deviation between the numerical separation test slurry flow rate and iron grade data and the actual separation test values ​​was selected. s The value is taken as the actual wall roughness Ra under the same conditions, and the corresponding equivalent relation is obtained.

2. The method for characterizing the wall roughness value in a spiral chute sorting numerical test according to claim 1, characterized in that: The simulation conditions for the spiral chute include Import the hexahedral mesh of the computational domain within the discrete spiral chute into the CFD software Fluent, and set up the multiphase flow model and the turbulence model. Set the inlet material parameters, calculate the boundary conditions of the calculation area, and input the roughness value; The multiphase flow model adopts the Multi-fluid VOF model, and the turbulence model adopts the RNG k-ε model; The boundary conditions include the velocity inlet and pressure outlet of the spiral chute, the non-slipping lower wall of the chute and the freely sliding upper wall of the chute, wherein the pressure outlet is set to the local atmospheric pressure, i.e., the relative pressure is 0. The roughness value is determined by the input roughness constant C. s and roughness height K s Value control, where the roughness constant C s The default value is 0.5, and the roughness height is determined by K. s =5~10Ra formula determined.

3. The method for characterizing the wall roughness value in a spiral chute sorting numerical test according to claim 1, characterized in that: The wall roughness at each measurement point is measured in the same direction as the main flow direction within the spiral chute.

4. The method for characterizing the wall roughness value in a spiral chute sorting numerical test according to claim 1, characterized in that: The equivalent relation is expressed as follows: K s =c Ra Where: c is a constant.

5. The method for characterizing the wall roughness value in a spiral chute sorting numerical test according to claim 1, characterized in that: The structural parameters of the spiral chute include cross-sectional shape, outer radius, inner radius, pitch, and number of turns.

6. The segmented examination method for characterizing the wall roughness value in a numerical test of a spiral chute sorting according to any one of claims 1-5, characterized in that: Includes the following steps: The bottom wall of the tank is divided into several spiral bands along the radial direction, thus obtaining segmented areas where the wall conditions can be freely adjusted. The roughness of the bottom wall surface of the tank was investigated in segments. The roughness height K of each segment was determined using Fluent software. s After setting up, a sorting numerical test was conducted to obtain the separation performance of the spiral chute when the wall roughness of each section was adjusted.

7. The segmented examination method for characterizing the wall roughness value in a spiral chute sorting numerical test according to claim 6, characterized in that: When the spiral ribbon is divided into an inner spiral ribbon, a middle spiral ribbon, and an outer spiral ribbon, a wear-resistant material is used on the wall surface of the middle spiral ribbon to improve separation performance.

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