Method for determining the porosity of heap leaching process ores

Abstract

The application provides a heap leaching process ore porosity detection method, and belongs to the technical field of ore porosity detection. The application takes heap leaching ore bodies, screens, mixes, divides, and then enters a heap leaching column to obtain the volume of the sample after division in the heap leaching column, then performs fine grinding, enters the heap leaching column again to obtain the volume of the sample after fine grinding in the heap leaching column, then performs image analysis on the sample after fine grinding to obtain the pore volume between the sample particles after fine grinding, and finally performs conversion through the three volumes to obtain the porosity of the heap leaching ore. Through screening treatment, the sample representativeness is effectively improved; the ore before and after superfine grinding is introduced into the heap leaching column, and the uniformity of sampling and the heap flow under the same test column are controlled, so that the accuracy and stability of data are improved; the image analysis algorithm is introduced, and a correction coefficient is introduced at the same time, so that the small pores between the particles are accurately calculated. The method has a simple process and convenient operation, and can quickly and accurately calculate the ore porosity.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of ore porosity detection, and particularly relates to a detection method for ore porosity in heap leaching process. BACKGROUND

[0002] Ore porosity is one of the key factors affecting the heap leaching effect. The porosity determines the permeability and diffusion speed of leaching agent in the ore heap. Suitable porosity can ensure the leaching agent to fully contact with the ore, so that the chemical reaction can proceed smoothly, thereby improving the leaching rate of useful components. If the porosity is too large, the leaching agent may pass through the ore heap too quickly and cannot fully react with the ore, resulting in incomplete leaching. If the porosity is too small, the permeation of the leaching agent will be hindered, which also affects the leaching effect.

[0003] Traditional ore porosity detection methods, such as mercury intrusion method, gas adsorption method, drainage method, etc., usually need to collect ore samples and take them back to the laboratory for processing and analysis. However, for heap leaching ore, this method has many limitations. On the one hand, the experimental instrument has small sample size and poor representativeness for single measurement, which leads to that the detection result cannot accurately reflect the real porosity of the ore. On the other hand, the physical and chemical properties of minerals in the ore are different, and water-soluble minerals cannot be used for porosity volume determination by the drainage method. In addition, the laboratory detection period is long and the cost is high, which cannot provide porosity data for the heap leaching process in time, and is not conducive to real-time monitoring and optimization of the heap leaching process. Therefore, there is an urgent need for a method that can quickly and accurately detect the porosity of ore to meet the needs of the development of in-situ heap leaching technology. SUMMARY

[0004] In view of the technical problems in the background art, the present application provides a detection method for ore porosity in heap leaching process, which aims to solve the problems of insufficient representativeness, long period, high cost and inability to real-time monitoring of the existing detection results of ore porosity in heap leaching.

[0005] The present application provides a detection method for ore porosity in heap leaching process, which comprises the following steps:

[0006] S1. Preparation of experimental sample: taking the crushed heap leaching ore on site, dispersing and mixing uniformly to obtain a uniformly dispersed ore sample;

[0007] S2. Sample screening: oscillating screening the uniformly dispersed ore sample on standard sieves stacked from top to bottom, wherein the pore size of the standard sieves decreases from top to bottom, and the screened sample and the undersize sample are taken and weighed, respectively, and the weights are recorded as G i上 , G 下 , respectively. The total mass of the screened sample is G=G i上 +G 下W i上 = G i上 / W 下 = G 下 / i; where i=1, 2, 3, …, represents the layer number of the screen from top to bottom.

[0008] S3. Sample configuration: mix the oversize sample and undersize sample in proportion, divide, get the divided sample, place the divided sample in the heap leaching column with radius R, measure the pile height of the divided sample in the heap leaching column as H, then the pore volume V between the particles of the dispersed uniform ore sample = πR 2 *H;

[0009] S4. Ultrafine grinding heap leaching column: ultrafine grind the divided sample to get the fine ground sample with particle size L, place the fine ground sample in the heap leaching column, measure the pile height of the fine ground sample in the heap leaching column as H1, then the volume V1 of the fine ground sample in the heap leaching column = πR 2 *H1, then the pore volume difference V2 between the particles of the divided sample and the fine ground sample = πR 2 *(H-H1);

[0010] S5. Image analysis sample preparation: uniformly disperse the fine ground sample on conductive glue, then perform carbon spraying treatment to get the image analysis sample;

[0011] S6. Image analysis: take a photo of the image analysis sample under a scanning electron microscope with magnification m, then open the photo taken in the picture processing software, circle different areas in the photo, the area of the different areas is S n , outline the pore profile between the sample particles in the different areas to get the area S n ’ of the pores between the sample particles in the different areas, the average area S n平均 = (∑S n ) / n of the different areas, the average area S n平均 ’ of the pores between the sample particles in the different areas = (∑S n ’) / n, the standard deviation S 标准差 = of the area of the pores between the sample particles in the different areas, introduce the area representative correction coefficient k, k = 1 / (1+CV), then the pore volume V3 between the sample particles of the fine ground sample = ((k*S n平均 ’ / m)*L)*(πR 2 / (S n平均 / m)*(H1 / L) = (πR2 *S n平均 '*k*H1) / S n平均 Where CV is the coefficient of variation, CV = (S 标准差 / S n平均 ') * 100%, n = 1, 2, ..., N, where N represents the number of the different regions;

[0012] S7. Calculate the porosity B of the heap leaching ore, B = (V3 + V2) / V = ​​1 + H1 / H * (S n平均 '*k / S n平均 )-1).

[0013] In the technical solution of this application embodiment, ore is taken on-site, sieved, mixed, and reduced in size before being fed into a heap leaching column. The volume of the reduced sample in the heap leaching column is obtained. Then, it is finely ground and fed into the heap leaching column again to obtain the volume of the finely ground sample in the heap leaching column. Next, the finely ground sample particles are image-analyzed to obtain the pore volume between the finely ground sample particles. Then, the porosity of the heap leached ore is obtained by converting the three volumes. Through sieving pretreatment, the representativeness of the sample is effectively improved, laying a solid foundation for the reliability of experimental data. The innovative introduction of ore before and after ultrafine grinding into the heap leaching column, and strict control of the uniformity of sampling and the heap entry process under the same test column, effectively avoids the interference of objective factors on the experimental results, greatly improving the accuracy and stability of the data. In addition, the introduction of image analysis algorithm and correction coefficients precisely calculates the small pores between micron-sized particles, making the data more realistic. This method is simple and easy to operate, and can quickly and accurately calculate the porosity of ores, while overcoming the shortcomings of small sample size and insufficient representativeness in a single measurement.

[0014] In some embodiments, in step S1, the mass of the heap leaching ore is ≥50kg.

[0015] In this embodiment, the minimum sampling amount is controlled to ensure that the mineral sample is representative.

[0016] In some embodiments, in step S2, the vibration screening time is 8-10 minutes; the aperture of the standard sieve is 40mm, 30mm, 20mm, and 10mm from top to bottom.

[0017] In this embodiment, particles of different sizes are obtained by vibrating sieving.

[0018] In some embodiments, in step S3, during the proportional mixing, the total mass of the mixed sample is A, and the sampling amounts of the oversize sample and the undersize sample are A and A, respectively. i上 and A 下 Then A i上 =W i上 *A, A下 =W 下 *A; where A ranges from 20 to 30 kg.

[0019] In this embodiment, by sampling samples of each particle size according to a certain ratio, the representativeness of the samples is effectively improved.

[0020] In some embodiments, the reduction includes the following steps: breaking the mixed sample into a ring and then taking the ore from opposite corners.

[0021] In this embodiment, a reduction process is used to further make the sampling more representative.

[0022] In some embodiments, in step S4, the particle size L ranges from 20 to 25 μm.

[0023] In this embodiment, if the particle size is too small (e.g., <10μm, close to the lower limit of traditional ultrafine grinding), the finely ground particles are prone to agglomeration due to excessive surface energy. If the particle size is too large (e.g., >30μm), the fine grinding is insufficient, and the particles still retain a lot of internal pores. When piled up, the "particle-to-particle gaps" are still quite obvious. The particle size range of 20~25μm is an optimized choice after comprehensively considering "eliminating interference from internal pores in particles", "reducing particle agglomeration errors", "adapting to the accuracy of SEM image analysis", and "balancing fine grinding efficiency". Its core objective is to ensure the measurement accuracy of V2 (the difference in pore volume between particles) and V3 (the pore volume between particles in the finely ground sample), and ultimately improve the detection accuracy of the porosity B of the heap leaching ore.

[0024] The above description is only an overview of the technical solution of this application. In order to better understand the technical means of this application and to implement it in accordance with the contents of the specification, and to make the above and other objects, features and advantages of this application more obvious and understandable, the following are specific embodiments of this application. Attached Figure Description

[0025] To more clearly illustrate the technical solutions of this application, the accompanying drawings used in this application will be briefly described below. Obviously, the drawings described below are merely some embodiments of this application. For those skilled in the art, other drawings can be obtained from these drawings without any creative effort.

[0026] Figure 1 This is a schematic diagram of image analysis in Example 1. Detailed Implementation

[0027] The embodiments of the technical solution of this application are described in detail below. The following embodiments are only used to illustrate the technical solution of this application more clearly, and are therefore only examples, and should not be used to limit the scope of protection of this application.

[0028] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0029] To address the problems of insufficient representativeness, long cycle time, high cost, and inability to monitor porosity in heap leaching ores, this application provides a method for detecting porosity in heap leaching ores. The method involves taking ore samples on-site, screening, mixing, and reducing their volume before feeding them into a heap leaching column. The volume of the reduced sample in the column is then calculated. The sample is then finely ground and fed back into the column, and its volume is calculated. Image analysis of the finely ground sample particles is then performed to obtain the pore volume between the particles. Finally, the porosity of the heap-leached ore is calculated by converting these three volumes. By pre-treating through sieving, the representativeness of the samples was effectively improved, laying a solid foundation for the reliability of experimental data. Innovatively, both pre- and post-ultra-fine-grind ore were introduced into the heap leaching column, and the uniformity of sampling and the heap entry process under the same experimental column were strictly controlled. This effectively avoided the interference of objective factors on the experimental results, greatly improving the accuracy and stability of the data. Furthermore, image analysis algorithms and correction coefficients were introduced to precisely calculate the small pores between micron-sized particles, making the data more realistic. This method is simple in process and easy to operate, enabling rapid and accurate calculation of ore porosity. Compared to conventional drainage methods, this scheme perfectly solves the problem of interference from water-soluble minerals in pore volume measurement. Compared to traditional methods such as mercury intrusion porosimetry and gas adsorption, it overcomes the shortcomings of small sample size and insufficient representativeness in single measurements. It provides reliable key permeability parameters for heap leaching processes, helping to scientifically select process flows and rationally determine core parameters such as leachate flow rate and distribution method, thereby significantly improving leaching efficiency and resource recovery rate. It demonstrates extremely high practical value and application prospects in the field of ore processing.

[0030] This application provides a method for detecting the porosity of ores in a heap leaching process, comprising the following steps:

[0031] S1. Preparation of experimental samples: Take the crushed heap leaching ore from the site, disperse it, mix it evenly, and obtain a uniformly dispersed ore sample.

[0032] S2. Sample sieving: The uniformly dispersed ore sample is vibrated and sieved on a set of standard sieves stacked from top to bottom. The aperture of the standard sieves decreases from top to bottom. The oversize and undersize samples after sieving are weighed separately, and the weights are recorded as: G i上 G 下Then the total mass of the sieved sample G = G i上 +G 下 Then, the percentages of the oversize and undersize samples to the total mass of the sieved sample are respectively W i上 =G i上 / G,W 下 =G 下 / G; where i=1, 2, 3, ..., represents the layer number of the sieve from top to bottom;

[0033] S3. Sample Preparation: The oversize and undersize samples are mixed in a certain proportion and reduced to obtain a reduced sample. The reduced sample is placed in a heap leaching column with radius R, and the height of the reduced sample in the heap leaching column is measured as H. Then, the pore volume between the particles of the uniformly dispersed ore sample is V = πR. 2 *H;

[0034] S4. Ultrafine Grinding and Heap Leaching Column: The reduced sample is ultrafine ground to obtain a finely ground sample with a particle size of L. The finely ground sample is placed in the heap leaching column, and the height of the finely ground sample in the heap leaching column is measured as H1. Then, the volume of the finely ground sample in the heap leaching column is V1 = πR. 2 *H1, then the pore volume difference between the particles in the reduced sample and the finely ground sample is V2 = V - V1 = πR 2 *(H-H1);

[0035] S5. Image analysis sample preparation: The finely ground sample is evenly dispersed on conductive adhesive, and then carbon spraying is performed to obtain the image analysis sample;

[0036] S6. Image Analysis: The sample for image analysis is photographed under a scanning electron microscope with a magnification of m. The photograph is then opened in image processing software, and different regions are circled in the photograph. The area of ​​each different region is S. n The pore contours between sample particles in different regions are outlined to obtain the area S of the pores between sample particles in different regions. n The average area S of the different regions n平均 =(∑S n ) / n; the average area S of the pores between sample particles in the different regions. n平均 '=(∑S n ') / n, the standard deviation S of the pore area between sample particles in the different regions. 标准差 = Introducing a regional representativeness correction coefficient k, k = 1 / (1+CV), then the pore volume between the particles in the finely ground sample, V3 = ((k*S) / (1+CV)). n平均 ' / m)*L)*(πR2 / (S) n平均 / m))*(H1 / L)=(πR 2 *S n平均 '*k*H1) / S n平均 Where CV is the coefficient of variation, CV = (S 标准差 / S n平均 ') * 100%, n = 1, 2, ..., N, where N represents the number of the different regions;

[0037] S7. Calculate the porosity B of the heap leaching ore, B = (V3 + V2) / V = ​​1 + H1 / H * (S n平均 '*k / S n平均 )-1).

[0038] In the technical solution of this application embodiment, ore is taken on-site, sieved, mixed, and reduced in size before being fed into a heap leaching column. The volume of the reduced sample in the heap leaching column is obtained. Then, it is finely ground and fed into the heap leaching column again to obtain the volume of the finely ground sample in the heap leaching column. Next, the finely ground sample particles are image-analyzed to obtain the pore volume between the finely ground sample particles. Then, the porosity of the heap leached ore is obtained by converting the three volumes. Through sieving pretreatment, the representativeness of the sample is effectively improved, laying a solid foundation for the reliability of experimental data. The innovative introduction of ore before and after ultrafine grinding into the heap leaching column, and strict control of the uniformity of sampling and the heap entry process under the same test column, effectively avoids the interference of objective factors on the experimental results, greatly improving the accuracy and stability of the data. In addition, the introduction of image analysis algorithm and correction coefficients precisely calculates the small pores between micron-sized particles, making the data more realistic. This method is simple and easy to operate, and can quickly and accurately calculate the porosity of ores, while overcoming the shortcomings of small sample size and insufficient representativeness in a single measurement.

[0039] Furthermore, in some embodiments, in step S1, the mass of the heap leaching ore is ≥50kg.

[0040] In the technical solution of this application embodiment, the minimum sampling amount is controlled to ensure that the mineral sample is representative.

[0041] Furthermore, in some embodiments, in step S2, the shaking sieving time is 8-10 minutes; the aperture of the standard sieve is 40mm, 30mm, 20mm, and 10mm from top to bottom.

[0042] In the technical solution of this application embodiment, particles of different sizes are obtained by vibrating sieving.

[0043] Furthermore, in some embodiments, in step S3, during the proportional mixing, the total mass of the mixed sample is A, and the sampling amounts of the oversize sample and the undersize sample are A and A, respectively. i上 and A 下 Then A i上 =W i上 *A, A 下 =W 下 *A; where A ranges from 20 to 30 kg.

[0044] In the technical solution of this application embodiment, the representativeness of the samples is effectively improved by sampling samples of each particle size according to a ratio.

[0045] Furthermore, in some embodiments, the reduction includes the following steps: breaking the mixed sample into rings, and then taking the diagonal ore.

[0046] In the technical solution of this application embodiment, a reduction process is adopted to further make the sampling more representative.

[0047] Furthermore, in some embodiments, in step S4, the particle size L ranges from 20 to 25 μm.

[0048] In the technical solution of this application embodiment, if the particle size is too small (e.g., <10μm, close to the lower limit of traditional ultrafine grinding), the finely ground particles are prone to agglomeration due to excessive surface energy. If the particle size is too large (e.g., >30μm), the fine grinding is insufficient, and the particles still retain a lot of internal pores. When piled up, the "particle-to-particle gaps" are still quite obvious. The particle size range of 20~25μm is an optimized choice after comprehensively considering "eliminating interference from internal pores of particles", "reducing particle agglomeration error", "adapting to the accuracy of SEM image analysis" and "balancing fine grinding efficiency". Its core objective is to ensure the measurement accuracy of V2 (particle-to-particle pore volume difference) and V3 (particle-to-particle pore volume of finely ground sample), and ultimately improve the detection accuracy of porosity B of heap leaching ore.

[0049] Furthermore, in some embodiments, the region in step S6 is circular.

[0050] The following are some specific embodiments. It should be noted that the embodiments described below are exemplary and are only used to explain this application, and should not be construed as limiting this application. Where specific techniques or conditions are not specified in the embodiments, they shall be performed in accordance with the techniques or conditions described in the literature in this field or according to the product instructions. Reagents or instruments whose manufacturers are not specified are all conventional products that can be obtained commercially.

[0051] Example 1

[0052] This embodiment provides a method for detecting the porosity of ores in a heap leaching process, specifically including the following steps:

[0053] (1) Take 50 kg of crushed heap leaching ore sample from the site, mix the sample thoroughly and evenly to obtain a uniformly dispersed ore sample.

[0054] (2) Select standard sieves with apertures of 10mm, 20mm, 30mm, and 40mm. Stack the selected sieves on the vibrating screen in descending order of aperture size, with a receiving tray at the bottom. Pour the uniformly dispersed ore sample into the top sieve and start the vibrating screen for 10 minutes. Weigh the ore on and off the sieve separately to obtain the weights of the sieve samples from top to bottom as G. 1上 =5.42kg, G 2上 =5.42kg, G 3上 =13.56kg, G 4上 =14.11kg, the weight of the sample that passed through the sieve is G 下 =7.32kg, the total mass of the sample after sieving G=G 1上 +G 2上 +G 3上 +G 4上 +G 下 =50kg, the percentages of samples over and under the sieves in the total sample mass are W respectively. 1上 =G 1上 / G=10.84%, W 2上 =G 2上 / G=19.18%, W 3上 =G 3上 / G=27.12%, W 4上 =G 4上 / G=28.22%, W 下 =G 下 / G=14.64%.

[0055] (3) Take samples from the above-mentioned sieves for both the over-sieve and under-sieve samples, with a sampling amount of A = 20 kg. The sampling amounts for each sieve sample from top to bottom are A. 1上 =W 1上 *A=2.17kg, A 2上 =W 2上 *A=3.84kg, A 3上 =W 3上 *A=5.42kg, A 4上 =W 4上 *A=5.64kg, A 下 =W 下*A = 2.93 kg. Then, the samples from each layer are mixed, formed into a ring, and diagonal ore is taken to obtain a reduced sample. This reduced sample is then placed in a heap leaching column with a radius R = 12.5 cm. At this point, the height of the sample in the heap leaching column is H = 0.28 m. Therefore, the volume of the reduced sample in the heap leaching column is V = πR. 2 *H=0.013738m 3 .

[0056] (4) The sample in the heap leaching column was ultra-finely ground to obtain a finely ground sample with a particle size of L = 20 μm. Then it was placed in the same heap leaching column with a heap height of H1 = 0.21 m. The volume of the finely ground sample in the heap leaching column was V1 = πR. 2 *H1=0.0103m 3 Then, the pore volume difference between the particles in the sample after reduction and the sample after fine grinding is V2 = V - V1 = πR. 2 *(H-H1)=0.003434m 3 .

[0057] (5) The finely ground sample is evenly dispersed on the conductive adhesive, carbon sprayed, and then observed and photographed using a scanning electron microscope, where the magnification m=800.

[0058] (6) For example Figure 1 As shown, a circular area is circled in the above photo. The area of ​​the circle is S1 = π × 0.15. 2 =0.07065mm 2 The outline of the circular inner hole was drawn using the free curve tool in Photoshop, and then the area of ​​the hole within the circular region was calculated using the software: S1' = 0.00719 mm². 2 Four additional circular regions were selected, and the area of ​​each region, S2 = 0.1256 mm², was obtained using the method described above. 2 S3 = 0.113354 mm 2 S4 = 0.015386 mm 2 S5 = 0.045216 mm 2 The area of ​​the pores in each region is S2' = 0.0142 mm². 2 S3'=0.01264mm 2 S4'=0.001802mm 2 S5'=0.004807mm 2 Then the average area S of different regions n平均 =(∑S n ) / n=0.07404mm 2 The average area S of the pores between sample particles in different regions n平均 '=(∑Sn ') / n=0.00813mm 2 The standard deviation S of the pore area between sample particles in different regions = =0.004672, introduce the regional representativeness correction coefficient k=1 / (1+CV), where CV=(S 标准差 / S n平均 ')*100%=57.47%, then k=0.63505, then the pore volume between the sample particles after fine grinding V3=((k*S n平均 ' / m)*L)*(πR 2 / (S) n平均 / m))*(H1 / L)=0.000718m 3 .

[0059] (7) Calculate the porosity B of the heap leaching ore, B = (V3 + V2) / V = ​​1 + H1 / H * (S n平均 '*k / S n平均 )-1)=30.22%.

[0060] In summary, this application provides a method for detecting the porosity of ores in a heap leaching process. The method involves taking ore samples on-site, sieving, mixing, and reducing their volume before feeding them into a heap leaching column. The volume of the reduced sample in the column is then calculated. The sample is then finely ground and fed back into the column, and its volume is calculated. Image analysis of the finely ground sample particles is then performed to obtain the pore volume between the particles. The porosity of the heap leached ore is then calculated by converting these three volumes. The sieving pretreatment effectively improves the representativeness of the samples, laying a solid foundation for the reliability of the experimental data. The innovative approach of introducing both pre- and post-finely ground ore into the heap leaching column, along with strict control over sampling uniformity and the same feed procedure within the same test column, effectively avoids interference from objective factors, greatly improving the accuracy and stability of the data. Furthermore, the introduction of image analysis algorithms and correction coefficients allows for precise calculation of the small pores between micron-sized particles, making the data more accurate. This method is simple and easy to operate, enabling rapid and accurate calculation of ore porosity. Compared to conventional drainage methods, this approach perfectly solves the problem of interference from water-soluble minerals in pore volume measurement. Compared to traditional methods such as mercury intrusion porosimetry and gas adsorption, it overcomes the shortcomings of small sample size and insufficient representativeness in single measurements. It provides reliable and key permeability parameters for heap leaching processes, helping to scientifically select process flows and rationally determine core parameters such as leachate flow rate and distribution method, thereby significantly improving leaching efficiency and resource recovery rate. It demonstrates extremely high practical value and application prospects in the field of ore processing.

[0061] It should be noted that this application is not limited to the above-described embodiments. The above embodiments are merely examples, and any embodiments with the same structure and effect as the technical concept within the scope of this application are included in the technical scope of this application. Furthermore, various modifications that can be conceived by those skilled in the art to the embodiments, and other ways of constructing by combining some of the constituent elements of the embodiments, without departing from the spirit of this application, are also included in the scope of this application.

Claims

1. A method for detecting the porosity of ores in a heap leaching process, characterized in that, Includes the following steps: S1. Preparation of experimental samples: Take the crushed heap leaching ore from the site, disperse it, mix it evenly, and obtain a uniformly dispersed ore sample. S2. Sample sieving: The uniformly dispersed ore sample is vibrated and sieved on a set of standard sieves stacked from top to bottom. The aperture of the standard sieves decreases from top to bottom. The oversize and undersize samples after sieving are weighed separately, and the weights are recorded as: G i上 G 下 Then the total mass of the sieved sample G = G i上 +G 下 Then, the percentages of the oversize and undersize samples to the total mass of the sieved sample are respectively W i上 =G i上 / G,W 下 =G 下 / G; where i=1, 2, 3, ..., represents the layer number of the sieve from top to bottom; S3. Sample Preparation: The oversize and undersize samples are mixed in a certain proportion and reduced to obtain a reduced sample. The reduced sample is placed in a heap leaching column with radius R, and the height of the reduced sample in the heap leaching column is measured as H. Then, the pore volume between the particles of the uniformly dispersed ore sample is V = πR. 2 *H; S4. Ultrafine Grinding and Heap Leaching Column: The reduced sample is ultrafine ground to obtain a finely ground sample with a particle size of L. The finely ground sample is placed in the heap leaching column, and the height of the finely ground sample in the heap leaching column is measured as H1. Then, the pore volume between the particles of the finely ground sample is V1 = πR. 2 *H1, then the pore volume between the particles of the reduced sample is V2=V-V1=πR 2 *(H-H1); S5. Image analysis sample preparation: The finely ground sample is evenly dispersed on conductive adhesive, and then carbon spraying is performed to obtain the image analysis sample; S6. Image Analysis: The sample for image analysis is photographed under a scanning electron microscope with a magnification of m. The photograph is then opened in image processing software, and different regions are circled in the photograph. The area of ​​each different region is S. n The pore contours between sample particles in different regions are outlined to obtain the area S of the pores between sample particles in different regions. n The average area S of the different regions n平均 =(∑S n ) / n; the average area S of the pores between sample particles in the different regions. n平均 '=(∑S n ') / n, the standard deviation S of the pore area between sample particles in the different regions. 标准差 = Introducing a regional representativeness correction coefficient k, k = 1 / (1+CV), then the pore volume between the particles in the finely ground sample, V3 = ((k*S) / (1+CV)). n平均 ' / m)*L)*(πR 2 / (S) n平均 / m))*(H1 / L)=(πR 2 *S n平均 '*k*H1) / S n平均 Where CV is the coefficient of variation, CV = (S 标准差 / S n平均 ') * 100%, n = 1, 2, ..., N, where N represents the number of the different regions; S7. Calculate the porosity B of the heap leaching ore, B = (V3 + V2) / V = ​​1 + H1 / H * (S n平均 '*k / S n平均 )-1).

2. The method for detecting the porosity of ore in heap leaching process according to claim 1, characterized in that, In step S1, the mass of the heap leaching ore is ≥50kg.

3. The method for detecting the porosity of ore in heap leaching process according to claim 1, characterized in that, In step S2, the shaking and screening time is 8-10 minutes.

4. The method for detecting the porosity of ore in heap leaching process according to claim 1, characterized in that, In step S2, the apertures of the standard sieve are 40mm, 30mm, 20mm, and 10mm from top to bottom.

5. The method for detecting the porosity of ore in heap leaching process according to claim 1, characterized in that, In step S3, during the proportional mixing, the total mass of the mixed sample is A, and the sampling amounts of the oversize and undersize samples are A and A, respectively. i上 and A 下 Then A i上 =W i上 *A, A 下 =W 下 *A; where A ranges from 20 to 30 kg.

6. The method for detecting the porosity of ore in heap leaching process according to claim 5, characterized in that, The reduction process includes the following steps: breaking the mixed sample into a ring, and then taking the ore from opposite corners.

7. The method for detecting the porosity of ore in heap leaching process according to claim 1, characterized in that, In step S4, the particle size L ranges from 20 to 25 μm.

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