Ore grade analysis method and device based on truck scanning station forward calibration

Abstract

The application discloses an ore grade analysis method and device based on forward calibration of a truck scanning station, and the method comprises the following steps: sampling standard material and determining the grade of the sample, dividing the standard material into multiple ton bags, obtaining the counting rate of the ton bags by using the truck scanning station, obtaining the first calibration coefficient and the second calibration coefficient by using the least square method fitting according to the grade of the sample and the counting rate of the ton bags, obtaining the counting rate of the to-be-measured ore by using the truck scanning station, selecting the first calibration coefficient to calculate the first grade of the to-be-measured ore, comparing the first grade of the to-be-measured ore with the grade of the inflection point, if the first grade is less than the grade of the inflection point, then the first grade is taken as the final grade, otherwise, the second calibration coefficient is selected to calculate the second grade of the to-be-measured ore, and the second grade is taken as the final grade. By using different calibration coefficients in different grade intervals, local errors are effectively reduced, and the accuracy of measurement of the scanning station in the low-grade interval is improved.

Description

Technical Field

[0001] This invention belongs to the field of ore grade analysis technology, and more specifically, relates to an ore grade analysis method and apparatus based on forward calibration of a truck scanning station. Background Technology

[0002] Truck scanning stations are radiometric measuring instruments used in uranium mining. They scan and measure the radioactive gamma intensity of the ore inside the trucks and calculate the average grade of the ore inside the trucks, thereby determining whether the material inside the trucks is ore or waste rock. If it is waste rock, it is unloaded to a waste rock dump; if it is ore, it is graded according to the corresponding grade and stacked or supplied to the smelter.

[0003] For radiometric measuring instruments, the principle of measurement is to measure the gamma ray intensity of the target object through the instrument's detector, thereby obtaining the corresponding count rate. Then, based on the calibration coefficients K1 and K2, the grade of the target object is calculated. Generally, the instrument has only one set of calibration coefficients, K1 and K2, within its measurement range.

[0004] In addition, accurate calibration of radioactive instruments is the foundation for accurate instrument measurements. Calibration generally adopts forward calibration, that is, using a set of materials or models with known grades (C1, C2, C3...), the instrument is used to measure and obtain the count rate (CPS1, CPS2, CPS3...) of the corresponding grades. Then, the grade data and count rate data are fitted using the least squares method to calculate the coefficients K1 and K2.

[0005] For the calibration of truck scanning stations, since there are no available industry standards for reference, nor are there any readily available standard materials or models of known grades, there are generally two calibration methods:

[0006] The first method is positive calibration: First, standard processing materials are prepared, corresponding to four grades: SEM, MG, HG, and VHG. Then, the count rate of the materials is measured. Finally, the data from all four grades are used to perform a least-squares fitting to obtain calibration coefficients. A schematic diagram of the calibration curve is shown below. Figure 1 As shown, the horizontal axis of the curve represents the calculation rate, and the vertical axis represents the grade of the material.

[0007] The second method is reverse calibration: that is, by accumulating long-term truck scanning data, the average grade of the scans during that period is compared with the back-calculated grade of the hydrometallurgical plant to obtain or correct the original coefficient.

[0008] The above two calibration methods have the following problems: First, when the particle size of large-volume (2000-4000 tons) materials is large, uneven mixing and stirring are likely to occur, resulting in uneven sampling. The samples taken cannot represent the large pile of materials, affecting the accuracy of the calibration results.

[0009] Secondly, when calculating calibration coefficients in the conventional way, the least squares method is used for fitting. All grades of data are uniformly and without difference to obtain a set of coefficients, which minimizes the global error. However, it cannot guarantee that the error in a certain local area is minimized. Based on parameters with large errors, waste rock may be mistaken for ore and enter the ore storage pile, thereby increasing the ore dilution rate and increasing production costs.

[0010] In practical applications, accurate measurement at the mine-waste separation point is crucial for ensuring the identification of ore and waste rock. The importance of measurement accuracy at this point outweighs the requirement of minimizing overall error. Summary of the Invention

[0011] Based on the above-mentioned technical problems, the main objective of this invention is to propose a method and apparatus for ore grade analysis based on forward calibration of a truck scanning station, so as to improve the accuracy of calibration results, improve the accuracy of measurement of the scanning station in the low-grade range (near the boundary between ore and waste rock), and reduce the dilution rate of mining.

[0012] To achieve the above objectives, according to one aspect of this application, a method for ore grade analysis based on forward calibration using a truck scanning station is proposed, the method comprising:

[0013] Standard materials are sampled, and the grade of the sample is determined, including SEM, MG, HG, and VHG.

[0014] The standard material is divided into multiple ton bags, and the count rate of the ton bags is obtained using a truck scanning station.

[0015] Based on the grade of the sample and the count rate of the ton bags, a first calibration coefficient and a second calibration coefficient are obtained by fitting using the least squares method. The first calibration coefficient corresponds to the SEM and MG grades, and the second calibration coefficient corresponds to the MG, HG, and VHG grades.

[0016] The count rate of the ore to be tested is obtained using a truck scanning station.

[0017] The first grade of the ore to be tested is calculated using the first calibration coefficient.

[0018] The first grade of the ore to be tested is compared with the grade at the inflection point.

[0019] If the first grade of the ore to be tested is less than the grade at the inflection point, then the first grade of the ore to be tested shall be taken as the final grade.

[0020] If the first grade of the ore to be tested is greater than the grade at the inflection point, then the second calibration coefficient is used to calculate the second grade of the ore to be tested, and the second grade is taken as the final grade.

[0021] Optionally, standard materials may be sampled, and the grade of the samples may be determined, including:

[0022] The standard material is divided into multiple small piles of material.

[0023] Sampling was performed on the small pile of materials.

[0024] The sample is graded and its quality is determined.

[0025] Optionally, sampling is performed on the small pile of materials, including:

[0026] For each small pile, the bucket of the front-loading machine is used to scoop and sample it.

[0027] Initial samples were extracted from different areas of the bucket.

[0028] The initial sample is processed to generate multiple processed samples.

[0029] Optionally, the initial sample is processed to generate multiple processed samples, including:

[0030] The initial sample is subjected to a series of processes including mixing, crushing, grinding, and sieving to generate the multiple processed samples.

[0031] Optionally, the sample is graded and its grade is determined, including:

[0032] Two groups of samples from multiple treated samples were selected for analysis to obtain the corresponding first and second analysis results.

[0033] Determine whether the difference between the first analysis result and the second analysis result is less than a preset difference.

[0034] If the difference is less than the preset value, then the first analysis result is determined to be the final analysis result.

[0035] If the difference is greater than the preset value, the average of the first analysis result and the second analysis result will be used as the final analysis result.

[0036] Optionally, the first analysis result and the second analysis result may be obtained from analyses conducted by different institutions.

[0037] Optionally, the standard material is divided into multiple ton bags, and the count rate of the ton bags is obtained using a truck scanning station, including:

[0038] The standard material is divided into multiple small piles of material.

[0039] The small pile of materials is bagged using ton bags, and the small pile of materials is bagged into multiple ton bags.

[0040] The multiple ton bags are loaded onto the truck, and the count rate of the ton bags is obtained by forward calibration using the truck scanning station.

[0041] Optionally, the inflection point grade is calculated using Formula 1.

[0042] Formula 1: |(K2-K2*) / (K1-K1*)|×K1+K2, where K1 and K2 are the first calibration coefficients in the ore grade calculation formula corresponding to SEM and MG grades, and K1* and K2* are the second calibration coefficients in the ore grade calculation formula corresponding to MG, HG and VHG grades.

[0043] According to another aspect of this application, an ore grade analysis apparatus is provided, the apparatus comprising:

[0044] The sampling module is used to sample standard materials and determine the grade of the sample, which includes SEM, MG, HG and VHG.

[0045] The calibration module is used to divide the standard material into multiple ton bags and obtain the count rate of the ton bags using a truck scanning station.

[0046] The processing module is used to obtain a first calibration coefficient and a second calibration coefficient by fitting the sample grade and the count rate of the ton bag using the least squares method. The first calibration coefficient corresponds to the SEM and MG grades, and the second calibration coefficient corresponds to the MG, HG and VHG grades.

[0047] The detection module is used to obtain the count rate of the ore to be tested using a truck scanning station.

[0048] The calculation module is used to calculate the first grade of the ore to be tested by selecting the first calibration coefficient.

[0049] The comparison module is used to compare the first grade of the ore to be tested with the grade at the inflection point.

[0050] The first determining module is used to determine the first grade of the ore to be tested as the final grade if the first grade of the ore to be tested is less than the grade of the inflection point.

[0051] The second determining module is used to calculate the second grade of the ore to be tested by selecting the second calibration coefficient if the first grade of the ore to be tested is greater than the grade of the inflection point, and to take the second grade as the final grade.

[0052] Optionally, the sampling module is used for:

[0053] The standard material is divided into multiple small piles of material.

[0054] Sampling was performed on the small pile of materials.

[0055] The sample is graded and its quality is determined.

[0056] Optionally, the sampling module is used for:

[0057] For each small pile, the bucket of the front-loading machine is used to scoop and sample it.

[0058] Initial samples were extracted from different areas of the bucket.

[0059] The initial sample is processed to generate multiple processed samples.

[0060] Optionally, the sampling module is used for:

[0061] The initial sample is subjected to a series of processes including mixing, crushing, grinding, and sieving to generate the multiple processed samples.

[0062] Optionally, the sampling module is used for:

[0063] Two groups of samples from multiple treated samples were selected for analysis to obtain the corresponding first and second analysis results.

[0064] Determine whether the difference between the first analysis result and the second analysis result is less than a preset difference.

[0065] If the difference is less than the preset value, then the first analysis result is determined to be the final analysis result.

[0066] If the difference is greater than the preset value, the average of the first analysis result and the second analysis result will be used as the final analysis result.

[0067] Optionally, the first analysis result and the second analysis result may be obtained from analyses conducted by different institutions.

[0068] Optionally, the calibration module is used for:

[0069] The standard material is divided into multiple small piles of material.

[0070] The small pile of material is bagged using ton bags, and the small pile of material is bagged into multiple ton bags.

[0071] The multiple ton-bag materials are loaded onto the truck, and the count rate is obtained by forward calibration using the truck scanning station.

[0072] Optionally, the inflection point grade is calculated using Formula 1.

[0073] Formula 1: |(K2-K2*) / (K1-K1*)|×K1+K2, where K1 and K2 are the first calibration coefficients in the ore grade calculation formula corresponding to SEM and MG grades, and K1* and K2* are the second calibration coefficients in the ore grade calculation formula corresponding to MG, HG and VHG grades.

[0074] Based on the above technical solution, the ore grade analysis method and device based on truck scanning station forward calibration has at least the following beneficial effects:

[0075] 1. This invention uses ton bags to store standard materials, ensuring that the grade of standard materials used for each scanning station calibration is consistent. This solves the problem of representativeness in standard material sampling and also addresses the storage problem of bulk standard materials.

[0076] 2. By refining the sampling steps and processing operations, this invention enables materials with larger particle sizes to be fully crushed, improves the uniformity of sample mixing, and thus makes the sampling uniform, which can effectively improve the accuracy of calibration results.

[0077] 3. This invention obtains calibration coefficients through segmented fitting, and uses different coefficients in different grade ranges, which can effectively reduce local errors, improve the accuracy of scanning station measurements in low-grade ranges (near the boundary between ore and waste rock), and reduce mining dilution rate and production costs. Attached Figure Description

[0078] The accompanying drawings, which form part of this specification, are used to provide a further understanding of the invention. The illustrative embodiments of the invention and their descriptions are used to explain the invention and do not constitute an undue limitation of the invention. In the drawings:

[0079] Figure 1 This is a schematic diagram of the calibration results obtained by the traditional forward calibration method;

[0080] Figure 2 This is a flowchart of an embodiment of the ore grade analysis method based on forward calibration of a truck scanning station according to this application;

[0081] Figure 3 This is a flowchart of sample taking in one embodiment of this application;

[0082] Figure 4 This is a flowchart of a sample grade determination process in one embodiment of this application;

[0083] Figure 5 This is a schematic diagram of the piecewise fitting calibration result of a specific embodiment of this application;

[0084] Figure 6 This is a schematic diagram of an ore grade analysis device according to an embodiment of this application. Detailed Implementation

[0085] It should be noted that, unless otherwise specified, the embodiments and features described in the present invention can be combined with each other. The present invention will now be described in detail with reference to the accompanying drawings and embodiments.

[0086] The present invention will be further described in detail below with reference to specific embodiments, which should not be construed as limiting the scope of protection claimed by the present invention.

[0087] Example

[0088] To achieve the above objectives, according to one aspect of this application, a method for ore grade analysis based on forward calibration of a truck scanning station is proposed.

[0089] exist Figure 2 The flowchart of an embodiment of the present application of an ore grade analysis method based on truck scanning station forward calibration is shown below. Figure 2 As shown, the method includes the following steps:

[0090] S1, sample the standard material and determine the grade of the sample.

[0091] like Figure 3 As shown, the specific sampling steps include:

[0092] S101, which divides the standard material into multiple small piles of material on an average basis.

[0093] In one specific embodiment, the standard material is 2,000-4,000 tons, and multiple smaller piles of 300 tons are separated from the standard material pile based on the truck load.

[0094] S102, Sampling is performed on the small pile of materials.

[0095] The specific sampling operation includes: First, for each small pile, the bucket of the front-loading machine is used to scoop and collect samples.

[0096] In the specific embodiment described above, after the standard material pile is divided into multiple smaller piles of 300 tons each, a TLB loader is used to scoop and collect samples from each 300-ton pile, scooping one bucket of about 2 tons each time, until all the samples are collected, for a total of 150 sets of samples.

[0097] Secondly, corresponding initial samples were extracted from different areas of the bucket.

[0098] In the specific embodiment described above, the sample scooped out on the bucket is divided into four square areas, and 5 kg of sample is scooped out from each square area.

[0099] Finally, the initial sample is processed to generate multiple processed samples.

[0100] The processing steps include: mixing, crushing, grinding, and sieving the initial sample in sequence. Specifically, the 5kg samples taken from the four square areas in the above steps are combined into a 20kg sample. The combined sample is then crushed using a small jaw crusher to a particle size of approximately 0.1mm to 2.8cm. The smaller particle size facilitates uniform mixing, thereby ensuring uniform sampling and improving the accuracy of the calibration results.

[0101] After the sample is crushed, it is thoroughly mixed with a mixer. After mixing, the grade is measured and recorded at the center position of the mixer using a directional radiation meter. Finally, the 20kg sample is divided into four equal parts, A, B, C and D, each weighing 5kg, using a sample divider.

[0102] S103, The sample is graded and its grade is determined.

[0103] The sample grades include SEM, MG, HG, and VHG, where SEM (Subeconomic grade matiaral) represents subeconomic grade, MG (Medium grade) represents medium grade, HG (High grade) represents high grade, and VHG (Very high grade) represents very high grade. 。

[0104] like Figure 4 As shown, the process of determining the grade of a sample and assigning a grade value to the sample includes the following steps:

[0105] S1031, Select two groups from multiple processed samples for analysis and obtain the corresponding first and second analysis results.

[0106] Specifically, the first and second analytical results were obtained from analyses conducted by different institutions. In one specific embodiment, samples A and B from four groups of samples (A, B, C, and D) were sent to Hushan Mine's own laboratory and an external laboratory, respectively. Each group contained 150 samples. After experimental analysis, the grade of the 150 samples was obtained. Finally, the average grade of the 150 samples was used as the analytical results for samples A and B, namely, the first analytical result and the second analytical result.

[0107] S1032, determine whether the difference between the first analysis result and the second analysis result is less than a preset difference.

[0108] S1033, if the difference is less than the preset difference, then the first analysis result is determined to be the final analysis result.

[0109] S1034, if the difference is greater than the preset difference, the average of the first analysis result and the second analysis result shall be taken as the final analysis result.

[0110] For example, if the preset difference of the analysis results is set to 10 ppm, the first analysis result is 144 ppm, and the second analysis result is 170 ppm. The actual difference is 26 ppm, which is greater than the preset difference of 10. Therefore, the final analysis result is the average of the first and second analysis results, 157 = (144 + 170) / 2.

[0111] S2, the standard material is divided into multiple ton bags, and the count rate of the ton bags is obtained using a truck scanning station.

[0112] First, the standard material is evenly separated into multiple smaller piles. The specific operation is the same as in S101. In one specific embodiment, the standard material is 2000-4000 tons, and based on the truck load, multiple smaller piles of 300 tons each are evenly separated from the standard material pile.

[0113] Secondly, the small piles of material are bagged using ton bags, forming multiple ton bags. For example, in the above specific embodiment, after dividing the standard material into 300-ton piles, the small piles are filled into ton bags, each weighing 1.5 tons. This ton bag method ensures that subsequent calibration only requires the ton bags, eliminating the need for large piles of material, thus achieving good preservation and ensuring consistency of grade data before and after calibration.

[0114] Finally, the multiple ton bags of material are loaded onto the truck, and the count rate is obtained using the truck scanning station in a forward calibration. Specifically, the principle for obtaining the count rate is as follows: the gamma ray intensity of the ton bags of material is measured by the truck scanning station to obtain the corresponding count rate, i.e., pulses per second, CPS.

[0115] S3. Based on the grade of the sample and the count rate of the ton bags, the first calibration coefficient and the second calibration coefficient are obtained by fitting using the least squares method.

[0116] To address the issue of excessively large errors caused by conventional calibration methods in low-grade ranges, this application proposes a segmented calibration approach. Different calibration coefficients are used in different grade ranges. The first calibration coefficient is obtained by fitting the SEM and MG grade data with the count rate of the ton bags using the least squares method. The second calibration coefficient is obtained by fitting the MG, HG, and VHG grade data with the count rate of the ton bags using the least squares method, thus avoiding the impact of global errors on the accuracy of measurements in that range.

[0117] S4 uses a truck scanning station to obtain the count rate of the ore to be tested.

[0118] S5, the first grade of the ore to be tested is calculated using the first calibration coefficient.

[0119] The specific calculation method is as follows: based on the first calibration coefficients K1 and K2 corresponding to SEM and MG, and according to the grade calculation formula, grade = K1 × count rate + K2, the first grade of the ore to be tested is calculated.

[0120] S6, compare the first grade of the ore to be tested with the grade at the inflection point.

[0121] Specifically, the inflection point grade is calculated using Formula 1: |(K2-K2*) / (K1-K1*)|×K1+K2, where K1 and K2 are the first calibration coefficients in the ore grade calculation formula corresponding to SEM and MG grades, and K1* and K2* are the second calibration coefficients in the ore grade calculation formula corresponding to MG, HG and VHG grades.

[0122] S7. If the first grade of the ore to be tested is less than the grade at the inflection point, then the first grade of the ore to be tested shall be taken as the final grade.

[0123] For example: if the first grade of the ore to be tested is 160, the grade at the inflection point is 170, and 160 < 170, then the final grade of the ore to be tested is 160.

[0124] S8. If the first grade of the ore to be tested is greater than the grade at the inflection point, then the second calibration coefficient is used to calculate the second grade of the ore to be tested, and the second grade is used as the final grade.

[0125] For example: If the first grade of the ore to be tested is 160 and the grade at the inflection point is 140, and 160 > 140, then the second calibration coefficients K1* and K2* corresponding to MG, HG and VHG are used to calculate the second grade of the ore to be tested, that is, the final grade = K1* × count rate + K2*.

[0126] In another specific embodiment, the piecewise fitting calibration result obtained according to this method is as follows: Figure 5 As shown, the horizontal axis represents the material count rate, and the vertical axis represents the material grade. It can be seen that when the sample grade belongs to SEM or MG, the first calibration coefficient corresponding to SEM and MG is used to calculate the functional relationship of the first grade of the material, and when there is an error, the second calibration coefficient corresponding to MG, HG and VHG is used to calculate the functional relationship of the second grade of the material.

[0127] According to another aspect of this application, an ore grade analysis device is proposed.

[0128] Figure 6 The diagram shows a schematic of an ore grade analysis apparatus according to an embodiment of this application, such as... Figure 6As shown, the device includes: a sampling module 61, a calibration module 62, a processing module 63, a detection module 64, a calculation module 65, a comparison module 66, a first determination module 67, and a second determination module 68.

[0129] The sampling module 61 is used to sample standard materials and determine the grade of the sample, which includes SEM, MG, HG and VHG.

[0130] Specifically, the sampling module 61 is used for:

[0131] First, the standard material is divided into multiple small piles of material.

[0132] Secondly, samples are taken from the small pile of materials. Specifically, sampling of the small pile of materials includes:

[0133] For each small pile, the bucket of the front-loading machine is used to scoop and sample it.

[0134] Initial samples were extracted from different areas of the bucket.

[0135] The initial sample is processed to generate multiple processed samples.

[0136] The specific processing method is as follows: the initial sample is sequentially mixed, crushed, ground, and sieved to generate the multiple processed samples.

[0137] Finally, the sample is graded and its quality is determined. This includes:

[0138] Two groups of samples from multiple treated samples were selected for analysis to obtain the corresponding first and second analysis results.

[0139] The first and second analysis results were obtained from analyses conducted by different institutions.

[0140] Determine whether the difference between the first analysis result and the second analysis result is less than a preset difference.

[0141] If the difference is less than the preset value, then the first analysis result is determined to be the final analysis result.

[0142] If the difference is greater than the preset value, the average of the first analysis result and the second analysis result will be used as the final analysis result.

[0143] The calibration module 62 is used to divide the standard material into multiple ton bags and use a truck scanning station to obtain the count rate of the ton bags.

[0144] Specifically, the calibration module 62 is used for:

[0145] The standard material is divided into multiple small piles of material.

[0146] The small pile of material is bagged using ton bags, and the small pile of material is bagged into multiple ton bags.

[0147] The multiple ton-bag materials are loaded onto the truck, and the count rate is obtained by forward calibration using the truck scanning station.

[0148] The processing module 63 is used to obtain a first calibration coefficient and a second calibration coefficient by fitting the sample grade and the count rate of the ton bag using the least squares method. The first calibration coefficient corresponds to the SEM and MG grades, and the second calibration coefficient corresponds to the MG, HG and VHG grades.

[0149] The detection module 64 is used to obtain the count rate of the ore to be tested using a truck scanning station.

[0150] The calculation module 65 is used to calculate the first grade of the ore to be tested by selecting the first calibration coefficient.

[0151] The comparison module 66 is used to compare the first grade of the ore to be tested with the grade at the inflection point.

[0152] The inflection point grade is calculated using Formula 1: |(K2-K2*) / (K1-K1*)|×K1+K2, where K1 and K2 are the first calibration coefficients in the ore grade calculation formula corresponding to SEM and MG grades, and K1* and K2* are the second calibration coefficients in the ore grade calculation formula corresponding to MG, HG and VHG grades.

[0153] The first determining module 67 is used to determine the first grade of the ore to be tested as the final grade if the first grade of the ore to be tested is less than the grade of the inflection point.

[0154] The second determining module 68 is used to calculate the second grade of the ore to be tested by selecting the second calibration coefficient if the first grade of the ore to be tested is greater than the grade of the inflection point, and to take the second grade as the final grade.

[0155] It should be understood that the ore grade analysis device and its corresponding ore grade analysis method based on truck scanning station forward calibration are described in the same way, so they will not be repeated in this embodiment.

[0156] In summary, as can be seen from the above description, the above embodiments of the ore grade analysis method and apparatus based on truck scanning station forward calibration achieve the following technical effects:

[0157] 1. This invention uses ton bags to store standard materials, ensuring that the grade of standard materials used for each scanning station calibration is consistent. This solves the problem of representativeness in standard material sampling and also addresses the storage problem of bulk standard materials.

[0158] 2. By refining the sampling steps and processing operations, this invention enables materials with larger particle sizes to be fully crushed, improves the uniformity of sample mixing, and thus makes the sampling uniform, which can effectively improve the accuracy of calibration results.

[0159] 3. This invention obtains calibration coefficients through segmented fitting, and uses different coefficients in different grade ranges, which can effectively reduce local errors, improve the accuracy of scanning station measurements in low-grade ranges (near the boundary between ore and waste rock), and reduce mining dilution rate and production costs.

[0160] It should be noted that, in this document, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes the element.

[0161] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus or device (such as a computer-based system, a processor-included system or other system that can fetch and execute instructions from, an instruction execution system, apparatus or device).

[0162] It should be understood that various parts of this application can be implemented using hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented using software or firmware stored in memory and executed by a suitable instruction execution system.

[0163] It should be noted that, in the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0164] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for ore grade analysis based on forward calibration using a truck scanning station, characterized in that, include: Sampling of standard materials and determination of sample grade, including SEM, MG, HG and VHG; The standard material is divided into multiple ton bags, and the count rate of the ton bags is obtained using a truck scanning station; Based on the grade of the sample and the count rate of the ton bag, the first calibration coefficient and the second calibration coefficient are obtained by fitting using the least squares method. The first calibration coefficient corresponds to the SEM and MG grades, and the second calibration coefficient corresponds to the MG, HG and VHG grades. The count rate of the ore to be tested is obtained using a truck scanning station; The first grade of the ore to be tested is calculated using the first calibration coefficient. Compare the first grade of the ore to be tested with the grade at the inflection point; If the first grade of the ore to be tested is less than the grade at the inflection point, then the first grade of the ore to be tested shall be taken as the final grade. If the first grade of the ore to be tested is greater than the grade at the inflection point, then the second calibration coefficient is used to calculate the second grade of the ore to be tested, and the second grade is taken as the final grade.

2. The method according to claim 1, characterized in that, Sampling of standard materials and determination of sample grade, including: The standard material is divided into multiple small piles of material on an average basis; Sampling was performed on the small pile of materials; The sample is graded and its quality is determined.

3. The method according to claim 2, characterized in that, Sampling of the small pile of materials includes: For each small pile, the bucket of the front-loading machine is used for shoveling and sampling; Initial samples were extracted from different regions of the bucket. The initial sample is processed to generate multiple processed samples.

4. The method according to claim 3, characterized in that, The initial sample is processed to generate multiple processed samples, including: The initial sample is subjected to a series of processes including mixing, crushing, grinding, and sieving to generate the multiple processed samples.

5. The method according to claim 2, characterized in that, The sample is graded and its grade is determined, including: Two groups of multiple treated samples were selected for analysis to obtain the corresponding first and second analysis results. Determine whether the difference between the first analysis result and the second analysis result is less than a preset difference; If the difference is less than the preset value, then the first analysis result is determined to be the final analysis result; If the difference is greater than the preset value, the average of the first analysis result and the second analysis result will be used as the final analysis result.

6. The method according to claim 5, characterized in that, The first and second analysis results were obtained from analyses conducted by different institutions.

7. The method according to claim 1, characterized in that, The standard material is divided into multiple ton bags, and the count rate of the ton bags is obtained using a truck scanning station, including: The standard material is divided into multiple small piles of material on an average basis; The small pile of materials is bagged using ton bags, and the small pile of materials is bagged into multiple ton bags; The multiple ton bags are loaded onto the truck, and the count rate of the ton bags is obtained by forward calibration using the truck scanning station.

8. The method according to claim 1, characterized in that, The inflection point grade is calculated using Formula 1. Formula 1: |(K2-K2*) / (K1-K1*)|×K1+K2, where K1 and K2 are the first calibration coefficients in the ore grade calculation formula corresponding to SEM and MG grades, and K1* and K2* are the second calibration coefficients in the ore grade calculation formula corresponding to MG, HG and VHG grades.

9. An ore grade analysis device, characterized in that, include: The sampling module is used to sample standard materials and determine the grade of the sample, which includes SEM, MG, HG and VHG. The calibration module is used to divide the standard material into multiple ton bags and use a truck scanning station to obtain the count rate of the ton bags; The processing module is used to obtain a first calibration coefficient and a second calibration coefficient by fitting the sample grade and the count rate of the ton bag using the least squares method. The first calibration coefficient corresponds to the SEM and MG grades, and the second calibration coefficient corresponds to the MG, HG and VHG grades. The detection module is used to obtain the count rate of the ore to be tested using a truck scanning station; The calculation module is used to calculate the first grade of the ore to be tested using the first calibration coefficient; The comparison module is used to compare the first grade of the ore to be tested with the grade at the inflection point; The first determining module is used to determine the first grade of the ore to be tested as the final grade if the first grade of the ore to be tested is less than the grade of the inflection point. The second determining module is used to calculate the second grade of the ore to be tested by selecting the second calibration coefficient if the first grade of the ore to be tested is greater than the grade of the inflection point, and to take the second grade as the final grade.

10. The apparatus according to claim 9, characterized in that, The sampling module is used for: The standard material is divided into multiple small piles of material on an average basis; Sampling was performed on the small pile of materials; The sample is graded and its quality is determined.

11. The apparatus according to claim 10, characterized in that, The sampling module is used for: For each small pile, the bucket of the front-loading machine is used for shoveling and sampling; Initial samples were extracted from different regions of the bucket. The initial sample is processed to generate multiple processed samples.

12. The apparatus according to claim 11, characterized in that, The sampling module is used for: The initial sample is subjected to a series of processes including mixing, crushing, grinding, and sieving to generate the multiple processed samples.

13. The apparatus according to claim 10, characterized in that, The sampling module is used for: Two groups of multiple treated samples were selected for analysis to obtain the corresponding first and second analysis results. Determine whether the difference between the first analysis result and the second analysis result is less than a preset difference; If the difference is less than the preset value, then the first analysis result is determined to be the final analysis result; If the difference is greater than the preset value, the average of the first analysis result and the second analysis result will be used as the final analysis result.

14. The apparatus according to claim 13, characterized in that, The first and second analysis results were obtained from analyses conducted by different institutions.

15. The apparatus according to claim 9, characterized in that, The calibration module is used for: The standard material is divided into multiple small piles of material on an average basis; The small pile of materials is bagged using ton bags, and the small pile of materials is bagged into multiple ton bags. The multiple ton-bag materials are loaded onto the truck, and the count rate is obtained by forward calibration using the truck scanning station.

16. The apparatus according to claim 9, characterized in that, The inflection point grade is calculated using Formula 1. Formula 1: |(K2-K2*) / (K1-K1*)|×K1+K2, where K1 and K2 are the first calibration coefficients in the ore grade calculation formula corresponding to SEM and MG grades, and K1* and K2* are the second calibration coefficients in the ore grade calculation formula corresponding to MG, HG and VHG grades.

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