Method for detecting porosity of dump leaching process ore

Abstract

The invention provides a method for detecting the porosity of ores in a dump leaching process, and belongs to the technical field of detection of the porosity of the ores. The method comprises the following steps: taking a dump leaching ore body, screening, uniformly mixing, splitting, putting into a dump leaching column to obtain the volume of a sample subjected to splitting in the dump leaching column, then performing fine grinding, putting into the dump leaching column to obtain the volume of the sample subjected to fine grinding in the dump leaching column, and then performing image analysis on the sample subjected to fine grinding to obtain the pore volume among sample particles subjected to fine grinding. And finally, converting the three volumes to obtain the porosity of the heap-leached ore. Through screening treatment, the sample representativeness is effectively improved; the ore before superfine grinding and after superfine grinding is introduced into a dump leaching column, the sampling uniformity is controlled, and the accuracy and stability of data are improved through the in-pile process under the same test column; an image analysis algorithm is introduced, and meanwhile, a correction coefficient is introduced, so that small pores among particles are precisely measured and calculated. The method is simple in process and convenient to operate, and the ore porosity can be rapidly and accurately measured and calculated.

Description

Technical Field

[0001] The present invention relates to the technical field of ore porosity detection, and in particular to a method for detecting the porosity of heap leaching ore. Background Art

[0002] Ore porosity is a key factor influencing heap leaching effectiveness. Porosity determines the penetration and diffusion rate of the leaching agent within the ore heap. Appropriate porosity ensures sufficient contact between the leaching agent and the ore, enabling smooth chemical reactions and improving the leaching rate of useful components. If the porosity is too high, the leaching agent may pass through the ore heap too quickly, failing to fully react with the ore and resulting in incomplete leaching. On the other hand, if the porosity is too low, the leaching agent's penetration will be hindered, similarly affecting leaching effectiveness.

[0003] Traditional methods for testing ore porosity, such as mercury intrusion, gas adsorption, and water displacement methods, usually require collecting ore samples and bringing them back to the laboratory for processing and analysis. However, this method has many limitations for heap leaching ores. On the one hand, the small sample size and lack of representativeness of the experimental instrument for a single measurement result in the test results not accurately reflecting the true porosity of the ore. On the other hand, the physical and chemical properties of minerals in the ore are different, and the water displacement method cannot be used to measure the pore volume of water-soluble minerals. On the other hand, laboratory testing cycles are long and the cost is high, making it impossible to provide porosity data for the heap leaching process in a timely manner, which 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 ore porosity to meet the needs of the development of in-situ heap leaching technology. Summary of the Invention

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

[0005] The present application provides a method for detecting the porosity of heap leaching ore, comprising the following steps: S1. Preparation of experimental samples: Take the crushed heap leaching ore on site, disperse it, mix it evenly, and obtain a uniformly dispersed ore sample; S2. Sample screening: The uniformly dispersed ore sample is vibrated and screened on standard sieves stacked from top to bottom. The aperture of the standard sieves decreases from top to bottom. The sieve samples and undersieve samples after screening are weighed respectively. The weights are recorded as: G i上 , G 下 , then the total mass of the sample after screening G=G i上 +G 下 , then the percentages of the oversize sample and undersize sample in the total mass of the sieved sample are Wi上 =G i上 / G,W 下 =G 下 / G; where i=1, 2, 3, ..., represents the layer number of the screen from top to bottom; S3. Sample preparation: The oversize sample and undersize sample are mixed in proportion, and then reduced to obtain a reduced sample. The reduced sample is placed in a heap leaching column with a radius of R. The pile height of the reduced sample in the heap leaching column is measured as H. The pore volume between the particles of the uniformly dispersed ore sample is V = πR 2 *H; S4. Ultrafine grinding 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. The height of the finely ground sample in the heap leaching column is measured as H1. 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 of the sample after reduction and the sample after fine grinding is V2=V-V1=πR 2 *(H-H1); S5. Image analysis sample preparation: The finely ground sample was evenly dispersed on a conductive adhesive and then carbon sprayed to obtain an image analysis sample; S6. Image analysis: The image analysis sample is photographed under a scanning electron microscope with a magnification of m. The photograph is then opened in an image processing software and different areas are circled in the photograph. The area of ​​each area is S. n , outline the pore contours between the sample particles in the different regions, and obtain the area S of the pores between the sample particles in the 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 the sample particles in the different regions n平均 '=(∑S n ') / n, the standard deviation S of the area of ​​the pores between the sample particles in different regions 标准差 = , introducing the regional representative correction coefficient k, k = 1 / (1 + CV), then the pore volume V3 between the sample particles after fine grinding = ((k * S 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 ; Among them, CV is the coefficient of variation, CV= (S 标准差 / Sn平均 ')*100%, n=1, 2, ... N, N represents the number of different areas; S7. Calculate the porosity B of the heap leached ore, B = (V3 + V2) / V = ​​1 + H1 / H * ((S n平均 '*k / S n平均 )-1).

[0006] In the technical solution of the embodiment of the present application, the ore body is taken on site, screened, mixed, and reduced before being put into the heap leaching column to obtain the volume of the reduced sample in the heap leaching column. The ore body is then finely ground and put into the heap leaching column to obtain the volume of the finely ground sample in the heap leaching column. The finely ground sample particles are then image analyzed to obtain the pore volume between the finely ground sample particles. The three volumes obtained are then converted to obtain the porosity of the heap leached ore. The screening pretreatment effectively improves the representativeness of the sample, laying a solid foundation for the reliability of the experimental data. The ore before and after ultrafine grinding is innovatively introduced into the heap leaching column, and the uniformity of sampling and the heap entry process under the same test column are strictly controlled, effectively avoiding the interference of objective factors on the test results and greatly improving the accuracy and stability of the data. In addition, the image analysis algorithm is introduced, and the correction coefficient is introduced at the same time to accurately measure the small pores between micron-sized particles, making the data more realistic. This method has a simple process and is easy to operate. It can quickly and accurately measure the porosity of ore and overcomes the defects of small sample size and insufficient representativeness in single measurement.

[0007] In some embodiments, in step S1, the mass of the heap leaching ore is ≥50 kg.

[0008] In this embodiment, the minimum sampling amount is controlled to make the ore sample representative.

[0009] In some embodiments, in step S2, the vibration screening time is 8 to 10 minutes; the apertures of the standard sieves are 40 mm, 30 mm, 20 mm, and 10 mm from top to bottom.

[0010] In this embodiment, particles of different sizes are obtained by vibration screening.

[0011] In some embodiments, in step S3, in the proportional mixing, the total mass of the mixed sample is A, and the sampling amounts of the oversize sample and undersize sample are 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.

[0012] In this embodiment, by sampling samples of each particle size according to a ratio, the representativeness of the samples is effectively improved.

[0013] In some embodiments, the fractionation comprises the steps of: forming the mixed sample into rings, and then taking the ore at the diagonal corners.

[0014] In this embodiment, the reduction process is adopted to further make the sampling more representative.

[0015] In some embodiments, in step S4, the particle size L is in the range of 20-25 μm.

[0016] In this embodiment, if the particle size is too small (e.g., <10 μm, close to the lower limit of traditional ultrafine grinding), the finely ground particles are prone to agglomeration due to excessively high surface energy. If the particle size is too large (e.g., >30 μm), fine grinding is insufficient, the particles still retain a large amount of internal pores, and the "inter-particle gaps" are still obvious during accumulation. The particle size range of 20-25 μm is the optimal choice after comprehensively considering "eliminating interference from internal pores in particles," "reducing particle agglomeration errors," "adapting to SEM image analysis accuracy," and "balancing fine grinding efficiency." Its core goal is to ensure the measurement accuracy of V2 (inter-particle pore volume difference) and V3 (inter-particle pore volume of finely ground samples), ultimately improving the detection accuracy of heap leaching ore porosity B.

[0017] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] To more clearly illustrate the technical solution of this application, the following is a brief introduction to the drawings used in this application. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be derived from these drawings without inventive effort.

[0019] Figure 1 Schematic diagram of image analysis in Example 1. DETAILED DESCRIPTION

[0020] The following embodiments of the technical solution of the present application are described in detail. The following embodiments are only used to more clearly illustrate the technical solution of the present application and are therefore only used as examples and are not intended to limit the scope of protection of the present application.

[0021] References herein to "embodiments" mean that a particular feature, structure, or characteristic described in connection with the embodiments may be included in at least one embodiment of the present application. The appearance of this phrase in various places in the specification does not necessarily refer to the same embodiment, nor does it constitute an independent or alternative embodiment that is mutually exclusive of other embodiments. It is understood, both explicitly and implicitly, by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0022] In order to solve the problems of insufficient representativeness of existing heap leaching ore porosity test results, long cycle time, high cost, and inability to monitor in real time, the present application provides a method for detecting the porosity of heap leaching ore. The ore body is collected on-site, screened, mixed, and reduced before being fed into a heap leaching column to obtain the volume of the reduced sample in the heap leaching column. The ore body is then finely ground before being fed into the heap leaching column to obtain the volume of the finely ground sample in the heap leaching column. The finely ground sample particles are then image analyzed to obtain the pore volume between the finely ground sample particles. The three volumes are then converted to obtain the porosity of the heap leached ore. Screening pretreatment effectively improves sample representativeness, laying a solid foundation for the reliability of experimental data. The innovative introduction of pre- and post-ultrafine grinding ore into the heap leaching column, along with strict control over sampling uniformity and the heap loading process within the same test column, effectively mitigates interference from objective factors on the test results and significantly improves the accuracy and stability of the data. Furthermore, the introduction of an image analysis algorithm and a correction factor precisely measures the small pores between micron-sized particles, further enhancing the accuracy of the data. This method boasts a simple workflow and convenient operation, enabling rapid and accurate ore porosity measurement. Compared to conventional drainage methods, this solution effectively addresses the interference of water-soluble minerals on pore volume determination. Compared to traditional methods such as mercury intrusion and gas adsorption, it overcomes the limitations of small sample sizes and insufficient representativeness in single measurements. It provides a reliable basis for key permeability parameters in the heap leaching process, assisting in the scientific selection of process flows and the rational determination of key parameters such as leachate flow rate and distribution method, significantly improving leaching efficiency and resource recovery. This approach demonstrates high practical value and promising application prospects in the field of ore processing.

[0023] The present application provides a method for detecting the porosity of heap leaching ore, comprising the following steps: S1. Preparation of experimental samples: Take the crushed heap leaching ore on site, disperse it, mix it evenly, and obtain a uniformly dispersed ore sample; S2. Sample screening: The uniformly dispersed ore sample is vibrated and screened on standard sieves stacked from top to bottom. The aperture of the standard sieves decreases from top to bottom. The sieve samples and undersieve samples after screening are weighed respectively. The weights are recorded as: G i上 , G 下 , then the total mass of the sample after screening G=G i上 +G下 , then the percentages of the oversize sample and undersize sample in the total mass of the sieved sample are W i上 =G i上 / G,W 下 =G 下 / G; where i=1, 2, 3, ..., represents the layer number of the screen from top to bottom; S3. Sample preparation: The oversize sample and undersize sample are mixed in proportion, and then reduced to obtain a reduced sample. The reduced sample is placed in a heap leaching column with a radius of R. The pile height of the reduced sample in the heap leaching column is measured as H. The pore volume between the particles of the uniformly dispersed ore sample is V = πR 2 *H; S4. Ultrafine grinding 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. The height of the finely ground sample in the heap leaching column is measured as H1. 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 of the sample after reduction and the sample after fine grinding is V2=V-V1=πR 2 *(H-H1); S5. Image analysis sample preparation: The finely ground sample was evenly dispersed on a conductive adhesive and then carbon sprayed to obtain an image analysis sample; S6. Image analysis: The image analysis sample is photographed under a scanning electron microscope with a magnification of m. The photograph is then opened in an image processing software and different areas are circled in the photograph. The area of ​​each area is S. n , outline the pore contours between the sample particles in the different regions, and obtain the area S of the pores between the sample particles in the 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 the sample particles in the different regions n平均 '=(∑S n ') / n, the standard deviation S of the area of ​​the pores between the sample particles in different regions 标准差 = , introducing the regional representative correction coefficient k, k = 1 / (1 + CV), then the pore volume V3 between the sample particles after fine grinding = ((k * S n平均 ' / m)*L)*(πR 2 / (S n平均 / m))*(H1 / L)=(πR 2 *S n平均 '*k*H1) / Sn平均 ; Among them, CV is the coefficient of variation, CV= (S 标准差 / S n平均 ')*100%, n=1, 2, ... N, N represents the number of different areas; S7. Calculate the porosity B of the heap leached ore, B = (V3 + V2) / V = ​​1 + H1 / H * ((S n平均 '*k / S n平均 )-1).

[0024] In the technical solution of the embodiment of the present application, the ore body is taken on site, screened, mixed, and reduced before being put into the heap leaching column to obtain the volume of the reduced sample in the heap leaching column. The ore body is then finely ground and put into the heap leaching column to obtain the volume of the finely ground sample in the heap leaching column. The finely ground sample particles are then image analyzed to obtain the pore volume between the finely ground sample particles. The three volumes obtained are then converted to obtain the porosity of the heap leached ore. The screening pretreatment effectively improves the representativeness of the sample, laying a solid foundation for the reliability of the experimental data. The ore before and after ultrafine grinding is innovatively introduced into the heap leaching column, and the uniformity of sampling and the heap entry process under the same test column are strictly controlled, effectively avoiding the interference of objective factors on the test results and greatly improving the accuracy and stability of the data. In addition, the image analysis algorithm is introduced, and the correction coefficient is introduced at the same time to accurately measure the small pores between micron-sized particles, making the data more realistic. This method has a simple process and is easy to operate. It can quickly and accurately measure the porosity of ore and overcomes the defects of small sample size and insufficient representativeness in single measurement.

[0025] Furthermore, in some embodiments, in step S1, the mass of the heap leaching ore is ≥50 kg.

[0026] In the technical solution of the embodiment of the present application, the minimum sampling amount is controlled to make the ore sample representative.

[0027] Furthermore, in some embodiments, in step S2, the vibration screening time is 8 to 10 minutes; the apertures of the standard sieves are 40 mm, 30 mm, 20 mm, and 10 mm from top to bottom.

[0028] In the technical solution of the embodiment of the present application, particles of different particle sizes are obtained through vibration screening.

[0029] Furthermore, in some embodiments, in step S3, in 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.

[0030] In the technical solution of the embodiment of the present application, by sampling samples of each particle size according to the proportion, the representativeness of the samples is effectively improved.

[0031] Furthermore, in some embodiments, the reduction comprises the following steps: cutting the mixed sample into rings, and then taking the ore at the diagonal corners.

[0032] In the technical solution of the embodiment of the present application, a reduction process is adopted to further make the sampling more representative.

[0033] Furthermore, in some embodiments, in step S4, the particle size L is in the range of 20-25 μm.

[0034] In the technical solution of the embodiment of the present application, if the particle size is too small (such as <10μm, which is close to the lower limit of traditional ultrafine grinding), the particles after fine grinding are prone to agglomeration due to excessively high surface energy. If the particle size is too large (such as >30μm), the fine grinding is insufficient, the particles still retain a large amount of internal pores, and the "inter-particle gaps" are still obvious when stacked. The particle size range of 20~25μm is the optimal choice after comprehensive consideration of "eliminating the interference of internal pores of particles", "reducing particle agglomeration errors", "adapting to the accuracy of SEM image analysis" and "balancing fine grinding efficiency". Its core goal is to ensure the measurement accuracy of V2 (pore volume difference between particles) and V3 (pore volume between particles of finely ground samples), and ultimately improve the detection accuracy of the porosity B of heap leaching ore.

[0035] Furthermore, in some embodiments, in step S6, the area is circular.

[0036] Some specific examples are listed below. It should be noted that the examples described below are exemplary and are only used to explain the present application, and should not be construed as limiting the present application. Where specific techniques or conditions are not specified in the examples, the techniques or conditions described in the literature in this area or the product specifications are used. Reagents or instruments used without manufacturer's indication are all commercially available conventional products.

[0037] Example 1 This embodiment provides a method for detecting the porosity of heap leaching ore, which specifically includes the following steps: (1) Take 50 kg of crushed heap leaching ore sample on site and mix the sample thoroughly to obtain a uniformly dispersed ore sample.

[0038] (2) Select standard sieves with apertures of 10mm, 20mm, 30mm, and 40mm, and stack the selected sieves on the vibrating screen in descending order of aperture, with a receiving tray placed at the bottom. Pour the evenly dispersed ore sample into the top sieve, start vibrating the screen for 10 minutes, and weigh the ore on and under the sieve respectively. The weights of the sieve samples from top to bottom are G and G, respectively. 1上 =5.42kg, G 2上 =5.42kg, G 3上 =13.56kg, G 4上 =14.11kg, the weight of the sample under 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 percentage of each sieve sample and sieve sample in the total mass of the sample is W 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%.

[0039] (3) Take samples of the above-mentioned samples above and below the sieve, and the sampling amount is A = 20 kg, where the sampling amount of each sample above and below the sieve from top to bottom is A respectively. 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=2.93kg. Then mix the samples from each layer, make a ring, take the diagonal ore, get the reduced sample, and then place it in a heap leaching column with a radius of R=12.5cm. At this time, the pile height of the sample in the heap leaching column is H=0.28m, so the volume of the reduced sample in the heap leaching column is V=πR 2 *H=0.013738m 3 .

[0040] (4) The sample in the above heap leaching column is ultrafine ground to obtain a finely ground sample with a particle size of L = 20 μm. Then it is placed in the same heap leaching column. At this time, the heap height H1 = 0.21 m, and the volume of the finely ground sample in the heap leaching column is V1 = πR 2 *H1=0.0103m 3 , then the pore volume difference between the particles of the above-mentioned sample after reduction and the fine grinding sample is V2=V-V1=πR 2 *(H-H1)=0.003434m 3 .

[0041] (5) The finely ground sample was evenly dispersed on the conductive adhesive, carbon-sprayed, and then observed and photographed using a scanning electron microscope at a magnification of m = 800.

[0042] (6) If Figure 1 As shown, a circle is circled in the above photo, and the area of ​​the circle is S1=π×0.15 2 =0.07065mm 2 , use the free curve tool in Photoshop software to outline the outline of the circular pore, and then use the software to calculate the area of ​​the pore in the circular area S1'=0.00719mm 2 , take another 4 circular areas, and use the above method to obtain the area of ​​each area S2 = 0.1256mm 2 、S3=0.113354mm 2 、S4=0.015386mm 2 、S5=0.045216mm 2 The area of ​​pores in each region is S2'=0.0142mm 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 '=(∑S n ') / n=0.00813mm 2 , the standard deviation of the area of ​​pores between sample particles in different regions S standard deviation = =0.004672, introducing the regional representativeness correction factor 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 .

[0043] (7) Calculate the porosity B of the heap leached ore, B = (V3 + V2) / V = ​​1 + H1 / H * ((S n平均 '*k / S n平均 )-1)=30.22%.

[0044] In summary, the present application provides a method for detecting the porosity of heap leaching ore. By taking the ore body on site, screening, mixing, reducing it, and then entering the heap leaching column, the volume of the reduced sample in the heap leaching column is obtained, and then fine grinding is performed and then entering the heap leaching column to obtain the volume of the finely ground sample in the heap leaching column. Then, the finely ground sample particles are subjected to image analysis to obtain the pore volume between the finely ground sample particles, and then the three volumes obtained are converted to obtain the porosity of the heap leaching ore. Through screening pretreatment, the representativeness of the sample is effectively improved, laying a solid foundation for the reliability of the experimental data. The ore before and after ultrafine grinding is innovatively introduced into the heap leaching column, and the uniformity of sampling and the heap entry process under the same test column are strictly controlled, which effectively avoids the interference of objective factors on the test results and greatly improves the accuracy and stability of the data. In addition, the image analysis algorithm is introduced, and the correction coefficient is introduced at the same time to accurately measure the small pores between micron-sized particles, making the data more realistic. This method features a simple process and convenient operation, enabling rapid and accurate calculation of ore porosity. Compared to conventional drainage methods, this solution effectively addresses the interference of water-soluble minerals in pore volume determination. Compared to traditional methods like mercury intrusion and gas adsorption, it overcomes the limitations of small sample sizes and insufficient representativeness associated with single measurements. It provides a reliable basis for key permeability parameters in heap leaching processes, assisting in the scientific selection of process flows and the rational determination of key parameters such as leachate flow rate and distribution method, significantly improving leaching effectiveness and resource recovery. This approach demonstrates significant practical value and promising application prospects in the field of ore processing.

[0045] It should be noted that the present application is not limited to the above-mentioned embodiments. The above-mentioned embodiments are merely examples, and any embodiments having substantially the same structure and effect as the technical concept within the scope of the present application are all included in the technical scope of the present application. In addition, without departing from the scope of the present application, any other embodiments that can be conceived by those skilled in the art and that combine some of the constituent elements in the embodiments are also included in the scope of the present application.

Claims

1. A method for detecting the porosity of heap leaching ore, characterized in that: The following steps are involved: S1. Preparation of experimental samples: Take the crushed heap leaching ore on site, disperse it, mix it evenly, and obtain a uniformly dispersed ore sample; S2. Sample screening: The uniformly dispersed ore sample is vibrated and screened on standard sieves stacked from top to bottom. The aperture of the standard sieves decreases from top to bottom. The sieve samples and undersieve samples after screening are weighed respectively. The weights are recorded as: G i上 , G 下 , then the total mass of the sample after screening G=G i上 +G 下 , then the percentages of the oversize sample and undersize sample in the total mass of the sieved sample are W i上 =G i上 / G,W 下 =G 下 / G; where i=1, 2, 3, ..., represents the layer number of the screen from top to bottom; S3. Sample preparation: The oversize sample and undersize sample are mixed in proportion, and then reduced to obtain a reduced sample. The reduced sample is placed in a heap leaching column with a radius of R. The pile height of the reduced sample in the heap leaching column is measured as H. The pore volume between the particles of the uniformly dispersed ore sample is V = πR 2 *H; S4. Ultrafine grinding 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. The pile height of the finely ground sample in the heap leaching column is measured as H1. The pore volume between the particles of the finely ground sample V1=πR 2 *H1, then the pore volume between the sample particles after the reduction is V2=V-V1=πR 2 *(H-H1); S5. Image analysis sample preparation: The finely ground sample was evenly dispersed on a conductive adhesive and then carbon sprayed to obtain an image analysis sample; S6. Image analysis: The image analysis sample is photographed under a scanning electron microscope with a magnification of m. The photograph is then opened in an image processing software and different areas are circled in the photograph. The area of ​​each area is S. n , outline the pore contours between the sample particles in the different regions, and obtain the area S of the pores between the sample particles in the 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 the sample particles in the different regions n平均 '=(∑S n ') / n, the standard deviation S of the area of ​​the pores between the sample particles in different regions 标准差 = , introducing the regional representative correction coefficient k, k = 1 / (1 + CV), then the pore volume V3 between the sample particles after fine grinding = ((k * S 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 ; Among them, CV is the coefficient of variation, CV= (S 标准差 / S n平均 ')*100%, n=1, 2, ... N, N represents the number of different areas; S7. Calculate the porosity B of the heap leached 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 heap leaching ore according to claim 1, characterized in that: In step S1, the mass of the heap leaching ore is ≥50 kg.

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

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

5. The method for detecting the porosity of heap leaching ore according to claim 1, characterized in that: In step S3, in the proportion mixing, the total mass of the mixed sample is A, and the sampling amounts of the above-sieve sample and the below-sieve sample are A and 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 heap leaching ore according to claim 5, characterized in that: The reduction comprises the following steps: the mixed sample is divided into rings, and then the ore is taken from the diagonal corners.

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

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