Sample preparation and homogeneity detection method
By monitoring particle size distribution and elemental uniformity indicators, the problem of incomplete sample homogeneity evaluation was solved, thereby improving sample representativeness and the reliability of analytical results.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-12-15
- Publication Date
- 2026-03-27
AI Technical Summary
In existing technologies, the evaluation system for sample homogeneity is imperfect, often focusing only on a single indicator such as particle size, which leads to a high misjudgment rate of homogeneity and causes fluctuations in analytical results.
By taking n portions from the same group of finely crushed samples and grinding them for progressively increasing times, the particle size distribution was monitored, grinding curves were plotted, and the coefficient of variation (CV) was calculated. Finely crushed samples of different masses were ground, and the gold and sulfur grades were calculated by weighting according to their mass percentages. After mixing the samples, multiple sampling points were taken to calculate the average sulfur content and spatial distribution deviation rate (DR) to jointly evaluate the homogeneity of the samples.
Quantifying the uniformity of particle size and elemental distribution ensures sample representativeness, improves the reliability and accuracy of analytical results, and avoids misjudgments caused by uneven particle size or elemental distribution.
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Figure CN121740544A_ABST
Abstract
Description
TECHNICAL FIELD
[0001] The application belongs to the technical field of metallurgical engineering, and particularly relates to a sample preparation and homogeneity detection method. BACKGROUND
[0002] In the fields of ore dressing development, metallurgical process research and environmental monitoring, the representativeness and homogeneity of samples are the premise to ensure the accuracy of analysis results. However, in actual operation, only the single index of particle size is often concerned, which leads to a high misjudgment rate of homogeneity and finally causes fluctuations in analysis results. SUMMARY
[0003] In view of the technical problems in the background art, the application provides a sample preparation and homogeneity detection method, which comprises the following steps: Preparation of a block stone sample and crushing treatment to obtain a plurality of groups of fine crushed samples; Taking n portions of the first group of fine crushed samples for grinding, grinding the n portions of the first group of fine crushed samples according to the time of gradual increase, monitoring the particle size distribution in the process, drawing a grinding curve of the target particle size proportion and the grinding time, obtaining the grinding time t, and calculating the average value x of the target particle size proportion according to the sample formed by the grinding time t 平均 and the standard deviation m 标准差 , calculating the coefficient of variation CV according to the two data; Grinding the fine crushed samples of different qualities and different groups for a time t to obtain the gold grade and sulfur grade of the corresponding fine crushed samples, and calculating the gold grade and sulfur grade of the mixed sample by weighted calculation according to the mass proportion of the corresponding fine crushed samples; Mixing the fine crushed samples of different qualities and different groups to form a mixed sample, taking multiple samples from the mixed sample, calculating the average content y of sulfur element 平均 , the absolute deviation value q of the sample 偏差值 and the spatial distribution deviation rate DR; Using the coefficient of variation CV and the spatial distribution deviation rate DR to jointly evaluate the homogeneity of the sample.
[0004] In some embodiments, the preparation process of the block stone sample comprises: Identifying the block stone sample according to the sampling point, recording the initial weight of each identified sample, denoted as G1, G2, G3...G n ; After pretreating the sample, reserving the sample required for process mineralogy analysis, and using the remaining sample for subsequent crushing treatment.
[0005] In some embodiments, the crushing treatment comprises: The block stone sample is sieved by using sieves with gradually decreasing sizes in turn, the sample on each sieve is crushed to the corresponding sieve size by using a jaw crusher, and the sample on the sieve is returned to the crusher for repeated crushing until it passes through the corresponding sieve; The sample after the classification crushing is crushed to a preset fine size by using a roller crusher, and the crushed sample is mixed, bagged and weighed, and the weight of each identified sample after crushing is recorded as G1 , G2 , G3 ... G n .
[0006] In some embodiments, the sizes of the sieves are 30 mm, 20 mm and 10 mm in turn, and the target sizes after crushing are -30 mm, -20 mm and -10 mm respectively; and the preset fine size is -2 mm.
[0007] In some embodiments, the ball mill is used as the grinding equipment for grinding n portions of the first same group of fine samples, and the particle size distribution is monitored in real time by using a laser particle size analyzer.
[0008] In some embodiments, the average value x 平均 of the target size ratio and the standard deviation m 标准差 of the target size ratio of the sample formed according to the grinding time t are calculated, and the coefficient of variation CV is calculated according to the two data, which includes: A plurality of parallel sub-samples after grinding for the grinding time t are taken, the target size ratio of each sub-sample is determined, the average value x 平均 of the target size ratio and the standard deviation m 标准差 are calculated; The coefficient of variation CV = (m 标准差 / x 平均 ) × 100% is calculated.
[0009] In some embodiments, the fine samples of different qualities and different groups are ground for the grinding time t, the gold grade and the sulfur grade of the corresponding fine samples are obtained, and the gold grade and the sulfur grade of the mixed sample are calculated by weighting according to the mass ratio of the corresponding fine samples, which includes: All the fine samples after crushing are ground for the grinding time t, the gold grade and the sulfur grade of each identified sample are detected, the gold grade is recorded as Au1~Au n , and the sulfur grade is recorded as S1~S n ; The gold grade of the mixed sample Au = (G1 × Au1+ G2 × Au2+…+ G n × Aun ) / (G1 + G2 + … + G n ), the sulfur taste of the mixed sample S = (G1 × S1+ G2 × S2+ … + G n × S n ) / (G1 + G2 + … + G n ).
[0010] In some embodiments, the mixing of different quality and different groups of finely crushed samples to form a mixed sample, multi-point sampling of the mixed sample, and calculating the average content of sulfur element y 平均 , the absolute deviation value q 偏差值 of the sample, and the spatial distribution deviation rate DR include: Mixing all samples after grinding at time t to form a mixed sample, and multi-point sampling from the mixed sample pile; Determining the sulfur element content of each sampling point by X-ray fluorescence spectroscopy technology, denoted as y1~y k ; Calculating the average content of sulfur element, denoted as y 平均 ; Calculating the absolute deviation value q 偏差值 = |y i -y 平均 | of a single sampling point; Calculating the spatial distribution deviation rate DR = (max |y i -y 平均 | / y 平均 ) × 100%.
[0011] In some embodiments, the multi-point sampling includes: Randomly dividing the mixed sample into multiple spatial subsamples, and selecting at least three from the multiple spatial subsamples as sampling points.
[0012] In some embodiments, when the spatial distribution deviation rate DR ≤ 3% and the particle size variation coefficient CV ≤ 5%, the homogeneity is determined to be qualified.
[0013] The application provides a sample preparation and homogeneity detection method, which comprises the following steps: taking n parts of ore grinding according to gradually increasing time from a first same group of fine samples, monitoring the particle size distribution during the process to draw a grinding curve and obtain a grinding time t, combining the average value and the standard deviation of the target particle size proportion to calculate a variation coefficient CV, and replacing the subjective method of determining the grinding time by experience; grinding the fine samples of different qualities and different groups for t time, calculating the gold grade and sulfur grade, and then calculating the mixed sample grade by weight according to the quality proportion, so as to lay a foundation for subsequent evaluation; mixing the fine samples of different groups to form a mixed sample and taking multiple samples, calculating the absolute deviation value of the average content of sulfur element and the spatial distribution deviation rate DR, and ensuring the comprehensiveness of element distribution detection; finally, the variation coefficient CV and the spatial distribution deviation rate DR are combined to evaluate the sample homogeneity, the problem of imperfect traditional homogeneity evaluation system is solved, and the sample representativeness and the reliability of the analysis result are improved. BRIEF DESCRIPTION OF DRAWINGS
[0014] In order to more clearly illustrate the technical solutions of the present application, the following will briefly introduce the drawings used in the present application. Obviously, the drawings described below are only some embodiments of the present application, and other drawings can also be obtained by those skilled in the art without creating any creative labor on the basis of these drawings.
[0015] Figure 1 It is a whole process schematic diagram of a sample preparation and homogeneity detection method provided by the embodiment of the present application. DETAILED DESCRIPTION
[0016] The embodiments of the technical solutions of the present application will be described in detail below with reference to the drawings. The following embodiments are only used to more clearly illustrate the technical solutions of the present application, and therefore only serve as examples, but cannot limit the protection scope of the present application.
[0017] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which the present application belongs; the terms used herein are only for the purpose of describing specific embodiments and are not intended to limit the present application; the terms "include" and "have" and any variations thereof in the specification and claims of the present application and the above description of drawings are intended to cover non-exclusive inclusion.
[0018] In the description of the embodiments of the present application, the technical terms "first", "second", etc. are only used to distinguish different objects, and cannot be understood as indicating or implying relative importance or implicitly indicating the number, specific order or primary and secondary relationship of the indicated technical features. In the description of the embodiments of the present application, the meaning of "multiple" is two or more, unless otherwise specifically limited.
[0019] Reference to“an embodiment” herein means that a particular feature, structure, or characteristic described in connection with the embodiment can be included in at least one embodiment of the application. The appearances of the phrase“in an embodiment” in various places in the specification are not necessarily all referring to the same embodiment, nor are they necessarily mutually exclusive of one another. It is expressly understood that any of the embodiments described herein can be incorporated into any other embodiment in a manner known to those of ordinary skill in the art.
[0020] In the description of the embodiments of the present application, the term“and / or” only means an association relationship of the associated objects, which means that there can be three relationships, for example, A and / or B, which can mean that A exists alone, A and B exist together, and B exists alone. In addition, the character“ / ” herein generally means that the front and rear associated objects are in an“or” relationship.
[0021] In the description of the embodiments of the present application, the term“a plurality of” means two or more (including two), and similarly, “a plurality of groups” means two or more groups (including two groups), and “a plurality of pieces” means two or more pieces (including two pieces).
[0022] In the description of the embodiments of the present application, the technical terms“center”,“longitudinal”,“transverse”,“length”,“width”,“thickness”,“upper”,“lower”,“front”,“rear”,“left”,“right”,“vertical”,“horizontal”,“top”,“bottom”,“inner”,“outer”,“clockwise”,“counterclockwise”,“axial”,“radial”,“circumferential” and the like indicate the orientation or positional relationship based on the orientation or positional relationship shown in the drawings, and are only for the convenience of describing the embodiments of the present application and simplifying the description, and do not indicate or imply that the devices or elements referred to must have a particular orientation, be constructed and operated in a particular orientation, and therefore cannot be understood as limiting the embodiments of the present application.
[0023] In the description of the embodiments of the present application, unless otherwise explicitly specified and limited, the technical terms“mounting”,“connecting”,“connecting”,“fixing” and the like should be understood in a broad sense, for example, it can be fixedly connected, or it can be detachably connected, or it can be integrated; it can be mechanically connected, or it can be electrically connected; it can be directly connected, or it can be indirectly connected through an intermediate medium; it can be the internal communication of two elements or the interaction relationship of two elements. For those of ordinary skill in the art, the specific meaning of the above terms in the embodiments of the present application can be understood according to the specific circumstances.
[0024] In order to make the purpose, technical scheme and advantages of the present application more clear, the following will be further described in combination with embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and not to limit the present application.
[0025] In the fields of beneficiation development, metallurgical process research and environmental monitoring which rely on accurate analysis, the representativeness and homogeneity of the sample directly determine the reliability of the subsequent experimental data, and are the core prerequisite to ensure the accuracy of the analysis results.
[0026] In the prior art, only a single granularity index is concerned, or the element distribution is judged by sampling at a single position, and the hidden danger of uniform granularity but uneven spatial distribution of granularity is ignored, resulting in high misjudgment rate of homogeneity and finally causing fluctuations in the analysis results.
[0027] Reference Figure 1 A sample preparation and homogeneity detection method, comprising: S100, preparing a block sample and performing crushing treatment to obtain a plurality of groups of finely crushed samples; For example, the block sample is numbered as B1, B2, …, B n and weighed, the surface impurities of the block are cleaned, the attached dust and silt are washed away with deionized water, and the block is dried and cooled for standby use. A jaw crusher + cone crusher combination is adopted, and a multi-stage screening process is used. The screened material is returned to the corresponding crusher for recycling and crushing, and the particles are gradually refined. After being crushed to the target particle size, each group of samples is mixed uniformly, weighed according to a fixed weight, and a plurality of groups of finely crushed samples are obtained.
[0028] In some embodiments, the preparation process of the block sample includes: The block sample is uniquely identified according to the sample point, and the initial weight of each identified sample is recorded, denoted as G1, G2, G3, …, G n ; After pretreatment of the sample, the sample required for process mineralogy analysis is reserved, and the remaining sample is used for subsequent crushing treatment.
[0029] In some embodiments, the crushing treatment includes: A plurality of multi-stage decreasing size screens are used to screen the block sample in sequence, and the screened sample at each screening stage is crushed to the corresponding undersize particle size by a jaw crusher. The screened sample is returned to the crusher for recycling and crushing until it passes through the corresponding screen. The sample after the classification crushing is crushed to a preset fine particle size by a roller crusher, and after crushing, it is mixed, bagged and weighed, and the weight of each identified sample after crushing is recorded as G1 , G2 , G3 … G n .
[0030] In some embodiments, the specifications of the multi-stage screens are 30 mm, 20 mm and 10 mm in sequence, and the target particle sizes after corresponding crushing are -30 mm, -20 mm and -10 mm, respectively. The preset fine particle size is -2 mm.
[0031] S200, taking n parts from the first fine sample for grinding, grinding the n parts of the same fine sample according to the time increment, monitoring the particle size distribution during the process, drawing the grinding curve of the target particle size proportion and the grinding time, obtaining the grinding time t, and calculating the average value x of the target particle size proportion of the sample formed according to the grinding time t 平均 And the standard deviation m 标准差 , the variation coefficient CV is calculated according to the two data; In some embodiments, the ball mill is used as the grinding equipment in the grinding of n parts from the first fine sample.
[0032] Specifically, n parts are taken from the first fine sample, and grinding is carried out according to the time increment, and the particle size distribution is monitored in real time during the process. The corresponding relationship between the grinding time and the target particle size proportion is found through gradient experiment, so as to obtain the grinding curve, so as to determine the grinding time t that meets the preset requirements, instead of the rough method of determining the time by experience in the traditional method.
[0033] The average value x of the target particle size proportion of the sample formed according to the grinding time t is calculated 平均 And the standard deviation m 标准差 , wherein the average value x 平均 reflects the overall particle size level, and m 标准差 reflects the dispersion degree of the single sub-sample and the average value, and the variation coefficient CV is used to convert the absolute dispersion into relative dispersion, so as to avoid the misjudgment of homogeneity caused by the difference of the average value, and quantify the particle size homogeneity under the time t.
[0034] CV is the core index for measuring the uniformity of particle size distribution. If CV meets the requirements, it means that the target particle size proportion of multiple parallel sub-samples fluctuates little after grinding for time t, and the overall particle size is uniform, so t can be confirmed as a stable and reliable grinding time. On the contrary, if the calculated value of CV cannot meet the requirements, the grinding time needs to be adjusted, the time needs to be extended, and the mill parameters need to be optimized, and then verified again until it is qualified.
[0035] Particle size uniformity is the prerequisite for sample representation. Only when all samples are ground for time t, the subsequent element grade detection and spatial homogeneity analysis can have fair comparison conditions, and the analysis result deviation caused by the partial sample particle size being coarse or partial being fine can be avoided.
[0036] In some embodiments, the average value x of the target particle size proportion of the sample formed according to the grinding time t is calculated 平均 And the standard deviation m 标准差 , the variation coefficient CV is calculated according to the two data, including: Take multiple parallel samples after grinding for a grinding time t, determine the target particle size ratio of each sample, and calculate the average target particle size ratio x. 平均 and standard deviation m 标准差 ; Calculate the coefficient of variation CV = (m 标准差 / x 平均 ) × 100%.
[0037] S300. Grind finely crushed samples of different masses and groups for a duration of t to obtain the gold grade and sulfur grade of the corresponding finely crushed samples. Calculate the gold grade and sulfur grade of the mixed sample by weighting according to the mass ratio of the corresponding finely crushed samples. Specifically, although the finely crushed samples from different groups have different qualities, they are all ground for a uniform grinding time t to ensure that the particle size of the samples is consistent and to avoid deviations in element detection values due to particle size differences. For example, if elements in coarse particles are not fully exposed, the detection results will be lower, thus establishing fair comparison conditions for subsequent grade detection.
[0038] Each group of ground samples was tested to obtain the individual gold and sulfur grades for each group. Ore grade refers to the proportion of a certain ore element in the ore sample. For example, Au1=0.82g / t means that the gold content in each ton of ore sample is 0.82 grams, which is the basic data for calculating the mixed grade.
[0039] The weighted calculation of the mixed gold and sulfur grades is the baseline value of the elemental content of the mixed sample. When performing subsequent elemental spatial homogeneity analysis, this baseline value should be used as a reference to determine whether the elemental content in different spatial locations is uniform.
[0040] In some implementations, for example, finely crushed samples of different masses and groups are ground for a duration of t to obtain the gold grade and sulfur grade of the corresponding finely crushed samples. The gold grade and sulfur grade of the mixed sample are then calculated by weighting the weights according to the mass percentage of the corresponding finely crushed samples, including: All finely crushed samples were ground for a grinding time t, and the gold and sulfur grades of each labeled sample were determined. The gold grade was denoted as Au1~Au n The sulfur grade is denoted as S1~S n ; The gold grade Au of the mixed sample is calculated by weighting the samples according to their respective mass proportions. Au = (G1) ×Au1+G2 ×Au2+…+G n ×Au n ) / (G1 +G2 +…+G n ), sulfur grade of mixed sample S=(G1) ×S1+G2 ×S2+…+G n ×S n ) / (G1 +G2 +…+G n ).
[0041] S400. Mix finely crushed samples of different masses and groups to form a mixed sample. Take multiple samples from the mixed sample and calculate the average sulfur content y. 平均 The absolute deviation value q of the sample 偏差值 And spatial distribution deviation rate DR; Specifically, different groups and different qualities of finely broken samples are mixed to form a whole mixed sample to be tested. Samples are taken from multiple spatial locations of the sample pile to ensure that the sampling covers the core area of the sample pile and avoids misjudgment of homogeneity caused by local element enrichment and sparseness.
[0042] y 平均 This value reflects the overall sulfur content level of the mixed sample, and the deviation of all subsequent subsamples is referenced to this value. 平均 The sulfur grade must be consistent with that of the previous mixed sample. If the deviation is large, it indicates that there is an unevenness problem in the mixing process. It is necessary to remix and verify to ensure the consistency of the data chain.
[0043] absolute deviation value q 偏差值 It reflects the degree of deviation of a single spatial subsample from the overall average level. If the q-deviation value of a certain subsample is large, it indicates that there is sulfur enrichment or sparsity at that location, providing specific directions for subsequent optimization of the mixing process.
[0044] q 偏差值 The maximum value is used to calculate the spatial distribution deviation rate (DR). DR is an indicator that measures the uniformity of element spatial distribution. If the DR meets the requirements, it means that the sulfur content of the mixed sample fluctuates little in different spatial locations, the element distribution is uniform, and the sample has good representativeness. Conversely, if the DR does not meet the requirements, it means that the elements are not evenly distributed in space, and the sample needs to be remixed until the DR meets the standard.
[0045] In some embodiments, for example, finely crushed samples of different masses and groups are mixed to form a mixed sample, and the mixed sample is sampled at multiple points to calculate the average sulfur content y. 平均 The absolute deviation value q of the sample 偏差值 And the spatial distribution deviation rate DR includes: All samples milled at time t are mixed to form a mixed sample, and multiple samples are taken from the mixed sample pile. In some implementations, for example, multi-point sampling involves randomly dividing the mixed sample into multiple spatial subsamples and selecting at least three of the multiple spatial subsamples as sampling points. The sulfur content at each sampling point was determined using X-ray fluorescence spectroscopy and denoted as y1~y2. k ; Calculate the average sulfur content, denoted as y. 平均 ; Calculate the absolute deviation value q of a single sampling point 偏差值 =|y i -y 平均 |; Calculate the spatial distribution deviation rate DR = (max|y i -y 平均 | / y 平均 ) × 100%.
[0046] S500 uses the coefficient of variation (CV) and spatial distribution deviation rate (DR) to jointly evaluate sample homogeneity.
[0047] Specifically, the coefficient of variation (CV) is an indicator of sample particle size, which verifies whether the particle size distribution is uniform after all samples are processed at a uniform grinding time (t); the spatial distribution deviation rate (DR) is an indicator of element distribution uniformity, which verifies whether the content distribution of key elements in different spatial locations in a mixed sample is uniform.
[0048] If only CV is qualified but DR exceeds the standard, it means that the sample has uniform particle size but uneven element distribution; if only DR is qualified but CV exceeds the standard, it means that the sample has uniform element distribution but uneven particle size distribution. Both fall into the category of non-homogeneity and need to be optimized in the previous step.
[0049] Traditional sample homogeneity evaluation often focuses only on particle size, neglecting the issue of elemental distribution. If a sample has uniform particle size but local areas have high sulfur content and local areas have low sulfur content, subsequent sampling and testing will still result in fluctuations.
[0050] In some implementations, homogeneity is considered acceptable when the spatial distribution deviation rate DR ≤ 3% and the particle size variation coefficient CV ≤ 5%.
[0051] In some embodiments, for example, the specific processing flow of a sample preparation and homogeneity detection method is as follows: Sample preparation: The samples are boulders. The incoming samples are numbered A1, A2, and A3 according to the points, and their weights are G1=729kg, G2=464kg, and G3=655kg respectively. The ground is cleaned, the bags are opened, and the samples are dried separately at each point. After the process mineralogy personnel take away the ore samples, they are ready for use.
[0052] Crushing: For samples numbered A1, A2, and A3, a jaw crusher was first used to crush them separately, followed by a double roll crusher.
[0053] ① Sieving: Use a 30mm sieve to sieve the samples separately, separating them into oversize and undersize samples.
[0054] ② Coarse crushing: Samples ≥30mm on the sieve are crushed to -30mm using a jaw crusher, then sieved again. Samples on the sieve are returned to the crusher for further crushing.
[0055] ③Medium crushing: The coarsely crushed sample is sieved with a 20mm sieve. The sample on the sieve is crushed to -20mm by a jaw crusher, then sieved again. The sample on the sieve is returned to the crusher for further crushing.
[0056] ④ Fine crushing: The medium-crushed sample is sieved with a 10mm sieve. The sample on the sieve is crushed to -10mm by a jaw crusher, then sieved again. The sample on the sieve is returned to the crusher for further crushing.
[0057] ⑤ Roller Crushing: Fine samples A1, A2, and A3 are crushed to -2mm using a roller crusher. They are then mixed thoroughly, bagged in kilograms, and weighed. The weights are G1. =727.65kg, G2 =463.26kg, G3 =654.70kg, for backup.
[0058] Grinding: The A1 sample from step two was ground using a ball mill. Four bags of A1 sample were taken. Based on experience, the grinding time was 5 minutes for the first bag, 10 minutes for the second bag, 15 minutes for the third bag, and 20 minutes for the fourth bag. The particle size distribution was monitored in real time using a laser particle size analyzer. After grinding, the particle size distribution of the four samples was determined to be -200 mesh: X1=48%, X2=72%, X3=84%, X4=90%. The grinding curves were plotted, and the grinding time t=13 minutes was determined based on the grinding curves to be 80% of the -200 mesh size. Five more bags of A1 sample were then ground for 13 minutes and set aside.
[0059] Particle size homogeneity analysis: Five parallel samples were taken, and the proportion of -200 mesh particles in each sample was measured using a laser particle size analyzer and denoted as x1, x2, x3...x n The percentages were 79%, 82%, 80%, 78%, and 81%, with an average of x. = (x1 + x2 + x3 + ... + x5) / 5 = 80% : Standard deviation m 标准差 = =√(1% 2 +4% 2 +0% 2 +4% 2 +1% 2=10% 2 ) / 4=1.58%, coefficient of variation CV=m 标准差 / x ×100%=1.58 / 80=1.98%, CV≤5%, the sample particle size is uniform, therefore the grinding time is determined to be t=13min.
[0060] Mixed sample sites: For samples A1, A2, and A3, the weights are G1 and G2 respectively. =718.65kg, G2 =463.26kg, G3 =654.70kg, grinding time was 13min, the sample after grinding was sent for testing, the gold and sulfur grades were tested, gold grade Au1=0.82g / t, Au2=0.75g / t, Au3=1.78g / t, at this time the Au grade of the mixed sample = [G1 ×Au1+G2 ×Au2+G3 ×Au3】 / (G1 +G2 +G3 =0.11g / t, S grade S1=0.60%, S2=0.70%, S3=0.68%, at this time the S grade of the mixed sample = [G1 ×S1+G2 ×S2+G3 ×S3】 / (G1 +G2 +G3 =0.65%.
[0061] Elemental spatial homogeneity analysis: The above mixed sample was randomly divided into multiple spatial subsamples. Samples were taken from the top, middle, bottom, left, and right positions of the sample pile and sent for analysis. The content of the target element S in each sample was determined by X-ray fluorescence (XRF), denoted as y1=0.65, y2=0.64, y3=0.64, y4=0.66, y5=0.66, where 5 is the sample quantity. The average elemental content y 平均 = (y1 + y2 + ... + y5) / 5 = 0.65, the absolute deviation value of the sample q 偏差值 =|y2-y 平均 |=0.01, Spatial distribution deviation rate DR=max|y2-y 平均 | / y 平均 ×100%=0.01 / 0.65×100%=1.54%, DR≤3%, then the spatial distribution homogeneity of the elements is qualified.
[0062] The above are merely specific embodiments of this application, but the scope of protection of this application is not limited thereto. Any modifications, equivalent substitutions, and improvements made by those skilled in the art within the scope of the technology disclosed in this application, and within the spirit and principles of this application, should be included within the scope of protection of this application.
[0063] 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 sample preparation and homogeneity detection, characterized in that, include: Prepare stone samples and crush them to obtain multiple sets of finely crushed samples; Take n portions from the first group of finely crushed samples and grind them. Grind the n portions of finely crushed samples in progressively increasing time increments, monitoring the particle size distribution during the process. Plot a grinding curve relating the target particle size percentage to the grinding time to obtain the grinding time t. Calculate the average target particle size percentage x based on the samples formed at this grinding time t. 平均 and standard deviation m 标准差 Calculate the coefficient of variation (CV) based on these two data points; Fine crushed samples of different masses and groups were ground for a duration of t to obtain the gold grade and sulfur grade of the corresponding fine crushed samples. The gold grade and sulfur grade of the mixed sample were obtained by weighting the samples according to the mass ratio of the corresponding fine crushed samples. Fine samples of different masses and groups were mixed to form a mixed sample. Multiple samples were taken from the mixed sample, and the average sulfur content y was calculated. 平均 The absolute deviation value q of the sample 偏差值 And spatial distribution deviation rate DR; The homogeneity of samples was evaluated using the coefficient of variation (CV) and the spatial distribution deviation rate (DR).
2. The sample preparation and homogeneity detection method according to claim 1, characterized in that, The preparation process for the stone sample includes: Each stone sample is uniquely identified according to its sampling point, and the initial weight of each identified sample is recorded as G1, G2, G3...G n ; After sample pretreatment, samples are reserved for process mineralogical analysis, and the remaining samples are used for subsequent crushing.
3. The sample preparation and homogeneity detection method according to claim 2, characterized in that, The crushing process includes: The stone samples were screened sequentially using sieves of decreasing size. The oversize samples at each screening stage were crushed to the corresponding undersize particle size using a jaw crusher. The oversize samples were returned to the crusher for recycling until all of them passed through the corresponding sieve. The graded and crushed samples were crushed to the preset fine particle size using a double-roll crusher. After crushing, the samples were mixed, bagged, and weighed. The weight of each labeled sample after crushing was recorded as G1. G2 G3 ...G n .
4. The sample preparation and homogeneity detection method according to claim 3, characterized in that, The screens are 30mm, 20mm, and 10mm in size, respectively, which correspond to target particle sizes of -30mm, -20mm, and -10mm after crushing; the preset fine particle size is -2mm.
5. The sample preparation and homogeneity detection method according to claim 1, characterized in that, In the process of taking n portions from the first group of finely crushed samples for grinding, a ball mill is used as the grinding equipment, and the particle size distribution is monitored in real time by a laser particle size analyzer.
6. The sample preparation and homogeneity detection method according to claim 5, characterized in that, The average target particle size percentage x is calculated based on the sample formed according to the grinding time t. 平均 and standard deviation m 标准差 The coefficient of variation (CV) is calculated based on these two data points, including: Take multiple parallel samples after grinding for a grinding time t, determine the target particle size ratio of each sample, and calculate the average target particle size ratio x. 平均 and standard deviation m 标准差 ; Calculate the coefficient of variation CV = (m 标准差 / x 平均 ) × 100%.
7. The sample preparation and homogeneity detection method according to claim 3, characterized in that, The grinding of finely crushed samples of different masses and groups for a duration of t yields the gold and sulfur grades of the corresponding finely crushed samples. The gold and sulfur grades of the mixed sample are then weighted according to the mass proportion of the corresponding finely crushed samples, resulting in the following: All finely crushed samples were ground for a grinding time t, and the gold and sulfur grades of each labeled sample were determined. The gold grade was denoted as Au1~Au n The sulfur grade is denoted as S1~S n ; The gold grade Au of the mixed sample is calculated by weighting the samples according to their respective mass proportions. Au = (G1) ×Au1+G2 ×Au2+…+G n ×Au n ) / (G1 +G2 +…+G n ), sulfur grade of mixed sample S=(G1) ×S1+G2 ×S2+…+G n ×S n ) / (G1 +G2 +…+G n ).
8. The sample preparation and homogeneity detection method according to claim 7, characterized in that, The process involves mixing finely crushed samples of different masses and groups to form a mixed sample, taking samples from multiple points on the mixed sample, and calculating the average sulfur content y. 平均 The absolute deviation value q of the sample 偏差值 And the spatial distribution deviation rate DR includes: All samples milled at time t are mixed to form a mixed sample, and multiple samples are taken from the mixed sample pile. The sulfur content at each sampling point was determined using X-ray fluorescence spectroscopy and denoted as y1~y2. k ; Calculate the average sulfur content, denoted as y. 平均 ; Calculate the absolute deviation value q of a single sampling point 偏差值 =|y i -y 平均 |; Calculate the spatial distribution deviation rate DR = (max|y i -y 平均 | / y 平均 ) × 100%.
9. The sample preparation and homogeneity detection method according to claim 8, characterized in that, The multi-point sampling includes: The mixed sample is randomly divided into multiple spatial subsamples, and at least three of the multiple spatial subsamples are selected as sampling points.
10. The sample preparation and homogeneity detection method according to claim 1, characterized in that, When the spatial distribution deviation rate DR ≤ 3% and the particle size variation coefficient CV ≤ 5%, the homogeneity is deemed acceptable.