Method and apparatus for establishing and calibrating scale model for mobile truck scanning station

Abstract

Disclosed in the present invention are a method and apparatus for establishing and calibrating a scale model for a mobile truck scanning station. The method comprises the following steps: firstly, acquiring dimension parameters of a mobile truck scanning station, and on the basis of the dimension parameters, establishing a Monte Carlo numerical calculation model; then, establishing a scale model for the mobile truck scanning station by means of the Monte Carlo numerical calculation model; next, using the scale model for the mobile truck scanning station to determine a first response result of a measurement system of the scale model for the mobile truck scanning station; establishing a field calculation model on the basis of parameters of the scale model for the mobile truck scanning station, and using the field calculation model to determine a second response result of the measurement system of the scale model for the mobile truck scanning station; and finally, determining an equivalent conversion coefficient on the basis of the first response result and the second response result, and calibrating the scale model for the mobile truck scanning station on the basis of the equivalent conversion coefficient. The method can solve the problem in the prior art of lower accuracy of calibration results of ore grade measurement systems.

Description

A method and device for establishing and calibrating a scale model for a mobile truck scanning station Technical Field

[0001] The present invention relates to the field of ore grade analysis, and more particularly to a method and device for establishing and calibrating a scale model of a mobile truck scanning station. Background Art

[0002] The truck scanning station is a radioactive measuring instrument, which is used in the uranium mining process. It measures the radioactive gamma intensity of the ore in the ore truck by scanning and calculating the average grade of the ore in the truck, thereby identifying whether the material in the truck is ore or waste rock. If it is waste rock, it is unloaded to the waste rock yard. If it is ore, it is piled up according to the corresponding grade classification or supplied to the water smelter for ore. Since the detection system of the portal scanning station can only measure the changes in the uranium and thorium content of the ore on the surface of the mine car, it cannot truly reflect the average uranium and thorium content of the ore in the entire car. Therefore, the radiation measurement physical model and the measurement calibration device for traceability of the measurement value are only for the ore on the surface of the mine car, not the ore in the entire car. In addition, the ore transportation capacity of large mine cars exceeds 300t, and it is difficult to build a standard device for direct measurement based on the measurement conditions of the mine car ore. For example, the standard shape of the mine car ore, the standard ore and its stable content (including uranium and thorium content), and the standard measurement conditions are difficult to meet the measurement standard requirements. In summary, the shortcomings of the existing technology are mainly reflected in the following two aspects:

[0003] (1) Sampling of large-volume (2000-4000 tons) materials is uneven. This is mainly manifested in the fact that when the particle size of the material is large (less than 10 cm), it is difficult to ensure the uniformity of the sampling even after multiple mixing and stirring. In other words, the sample taken is difficult to represent the bulk material well, so the value result after sampling analysis is not enough to truly represent the average grade of the bulk material, resulting in poor accuracy of the calibration result.

[0004] (2) When calculating the calibration coefficients in a conventional way, the least squares method is used for fitting, and all grade data are uniformly and indiscriminately used to calculate a set of coefficients. In actual application, the boundary between ore and waste rock in Hushan uranium mine is 150ppm (U3O8 content), while the lowest grade standard material has a fixed grade of 148ppm. When the calibration parameters obtained by conventional methods are used to measure the grade of this grade when the mine is put into operation (the grade measured by the scanning station is calculated by the measured cps), the obtained grade has a large error from the chemical analysis fixed grade (for example, 170ppm is measured), causing the scanning station to overestimate the boundary between ore and waste rock. Based on this parameter, a lot of waste rock will be mistaken for ore and enter the ore storage pile, which will cause the ore mining depletion rate to increase and increase production costs.

[0005] Existing patent CN201116911Y discloses a device for rapidly measuring the grade of iron ore in a mobile mine car. The device includes a rangefinder, an infrared transmitter and receiver, an electronic track scale, and a central computer processing system. Several rangefinders are installed above the tunnel through which the mine car passes, infrared transmitters and receivers are mounted on either side of the tunnel, the electronic track scale is installed beneath the tracks within the tunnel, and the central computer processing system is installed in a nearby machine room. The rangefinder, infrared transmitter and receiver, and electronic track scale are each connected to the central computer processing system. This measurement device does not address the existing problems of low accuracy in the calibration results of the truck scanning station ore grade measurement system, and the large ore grade measurement errors caused by this low calibration accuracy.

[0006] Existing patent CN104483234A discloses an automatic iron ore grade detection system and method. This system integrates multiple measurement and intelligent control devices to automatically measure the specific gravity of the ore. Using the least squares method, it establishes a relationship between the specific gravity and the grade. The ore grade is then inversely calculated based on the specific gravity. Finally, the measured data is stored in a database and an acceptance certificate is automatically printed. As can be seen from the above, this solution does not address the existing issues of low accuracy in the calibration results of truck scanning station ore grade measurement systems, nor the large ore grade measurement errors caused by this low calibration accuracy.

[0007] In summary, the above two existing patents do not solve the problems in the prior art of low accuracy of the calibration results of the truck scanning station ore grade measurement system and large ore grade measurement errors caused by the low accuracy of the calibration results.

[0008] Summary of the Invention

[0009] Based on the above technical problems, the present invention proposes a method and device for establishing and calibrating a calibration model of a mobile truck scanning station to solve the problems in the prior art of low accuracy of the calibration results of the ore grade measurement system of the truck scanning station and large ore grade measurement errors caused by the low accuracy of the calibration results.

[0010] To achieve the above objectives, the present invention proposes a method for establishing and calibrating a scale model of a mobile truck scanning station.

[0011] A method for establishing and calibrating a scale model of a mobile truck scanning station is disclosed. The method is applied to a scale model measurement system of the mobile truck scanning station. The measurement system includes a gantry, a left detector, a main detector, and a right detector. The method includes:

[0012] Obtain the dimensional parameters of the mobile truck scanning station and establish a Monte Carlo numerical calculation model based on the dimensional parameters. The dimensional parameters include the height of the gantry, the distance and opening direction between the left detector, the main detector, and the right detector, and the height of the object to be measured from the main detector.

[0013] The calibration model of mobile truck scanning station was established through Monte Carlo numerical calculation model;

[0014] Determine the first response result of the mobile truck scanning station calibration model measurement system using the mobile truck scanning station calibration model;

[0015] establishing a field calculation model based on parameters of the mobile truck scanning station calibration model, and determining a second response result of a measurement system of the mobile truck scanning station calibration model using the field calculation model;

[0016] Determine an equivalent conversion coefficient according to the first response result and the second response result;

[0017] The mobile truck scanning station calibration model is calibrated based on the equivalent conversion coefficient.

[0018] Furthermore, a calibration model of a mobile truck scanning station is established through a Monte Carlo numerical calculation model, including:

[0019] The Monte Carlo numerical calculation model is used to simulate and obtain the third response results of the mobile truck scanning station scale model measurement system under different thicknesses;

[0020] determining a thickness of the scale model of the mobile truck scanning station based on the third response result;

[0021] Under the condition of the thickness of the mobile truck scanning station scale model, the Monte Carlo numerical calculation model is used to simulate and obtain the fourth response results of the mobile truck scanning station scale model measurement system under different widths;

[0022] Under the condition of the thickness of the mobile truck scanning station calibration model, the actual response results of the mobile truck scanning station calibration model measurement system at different widths are obtained;

[0023] determining a width of a scale model of the mobile truck scanning station according to the fourth response result and the actual response result;

[0024] A mobile truck scanning station scale model is established based on the thickness and width of the mobile truck scanning station scale model.

[0025] Furthermore, determining a first response result of a measurement system of the mobile truck scanning station calibration model using the mobile truck scanning station calibration model includes:

[0026] The mobile truck scanning station calibration model is placed on the trailer and moved at a uniform speed along the radial and horizontal directions of the main detector to obtain the first detection efficiency spatial distribution curve corresponding to the main detector;

[0027] The detection efficiency data corresponding to the first detection efficiency spatial distribution curve is the first response result.

[0028] Furthermore, a field calculation model is established according to the parameters of the mobile truck scanning station calibration model, and a second response result of the mobile truck scanning station calibration model measurement system is determined using the field calculation model, including:

[0029] The Monte Carlo numerical calculation model is used to simulate the uniform movement of the mobile truck scanning station scale model with the same ore content along the radial and horizontal directions of the main detector to obtain the second detection efficiency spatial distribution curve corresponding to the main detector;

[0030] The detection efficiency data corresponding to the second detection efficiency spatial distribution curve is the second response result.

[0031] Furthermore, determining an equivalent conversion coefficient according to the first response result and the second response result includes:

[0032] determining a first average value of the detection efficiency according to the first response result;

[0033] determining a second average value of the detection efficiency according to the second response result;

[0034] The ratio of the first average value to the second average value is used as the equivalent conversion coefficient.

[0035] Furthermore, determining an equivalent conversion coefficient according to the first response result and the second response result further includes:

[0036] Acquire a plurality of first detection efficiency data corresponding to a position directly below the main detector in the first response result;

[0037] Acquire a plurality of second detection efficiency data corresponding to a position directly below the main detector in the second response result;

[0038] The plurality of first detection efficiency data and the plurality of second detection efficiency data are summed up respectively to determine the corresponding first average value and second average value.

[0039] Furthermore, it also includes:

[0040] After calibrating the mobile truck scanning station calibration model based on the equivalent conversion coefficient, a fifth response result of the mobile truck scanning station calibration model measurement system is determined using a Monte Carlo numerical calculation model;

[0041] determining a response coefficient of a mobile truck scanning station calibration model measurement system based on the first response result and the fifth response result;

[0042] The ore is measured using a calibrated mobile truck scanning station scale model and response factor.

[0043] To achieve the same purpose as the above method, the present invention also proposes a device for establishing and calibrating a scale model of a mobile truck scanning station.

[0044] A device for establishing and calibrating a scale model of a mobile truck scanning station is provided. The device is applied to a scale model measurement system of the mobile truck scanning station. The measurement system includes a gantry, a left detector, a main detector, and a right detector. The device includes:

[0045] An acquisition module is used to obtain the dimensional parameters of the mobile truck scanning station and establish a Monte Carlo numerical calculation model based on the dimensional parameters. The dimensional parameters include the height of the gantry, the distance and opening direction between the left detector, the main detector and the right detector, and the height of the object to be measured from the main detector;

[0046] Establishing a module for establishing a mobile truck scanning station calibration model through a Monte Carlo numerical calculation model;

[0047] A first determining module is configured to determine a first response result of a mobile truck scanning station calibration model measurement system using the mobile truck scanning station calibration model;

[0048] a second determination module, configured to establish a field calculation model according to parameters of the mobile truck scanning station calibration model, and determine a second response result of the mobile truck scanning station calibration model measurement system using the field calculation model;

[0049] A third determining module, configured to determine an equivalent conversion coefficient according to the first response result and the second response result;

[0050] The calibration module is used to calibrate the mobile truck scanning station scale model based on the equivalent conversion coefficient.

[0051] Furthermore, a module is established for:

[0052] The Monte Carlo numerical calculation model is used to simulate and obtain the third response results of the mobile truck scanning station scale model measurement system under different thicknesses;

[0053] determining a thickness of the scale model of the mobile truck scanning station based on the third response result;

[0054] Under the condition of the thickness of the mobile truck scanning station scale model, the Monte Carlo numerical calculation model is used to simulate and obtain the fourth response results of the mobile truck scanning station scale model measurement system under different widths;

[0055] Under the condition of the thickness of the mobile truck scanning station calibration model, the actual response results of the mobile truck scanning station calibration model measurement system at different widths are obtained;

[0056] determining a width of a scale model of the mobile truck scanning station according to the fourth response result and the actual response result;

[0057] A mobile truck scanning station scale model is established based on the thickness and width of the mobile truck scanning station scale model.

[0058] Furthermore, the first determining module is configured to:

[0059] The mobile truck scanning station calibration model is placed on the trailer and moved at a uniform speed along the radial and horizontal directions of the main detector to obtain the first detection efficiency spatial distribution curve corresponding to the main detector;

[0060] The detection efficiency data corresponding to the first detection efficiency spatial distribution curve is the first response result.

[0061] Furthermore, the second determining module is configured to:

[0062] The Monte Carlo numerical calculation model is used to simulate the uniform movement of the mobile truck scanning station scale model with the same ore content along the radial and horizontal directions of the main detector to obtain the second detection efficiency spatial distribution curve corresponding to the main detector;

[0063] The detection efficiency data corresponding to the second detection efficiency spatial distribution curve is the second response result.

[0064] Furthermore, the third determining module is configured to:

[0065] determining a first average value of the detection efficiency according to the first response result;

[0066] determining a second average value of the detection efficiency according to the second response result;

[0067] The ratio of the first average value to the second average value is used as the equivalent conversion coefficient.

[0068] Furthermore, the third determining module is further configured to:

[0069] Acquire a plurality of first detection efficiency data corresponding to a position directly below the main detector in the first response result;

[0070] Acquire a plurality of second detection efficiency data corresponding to a position directly below the main detector in the second response result;

[0071] The plurality of first detection efficiency data and the plurality of second detection efficiency data are summed up respectively to determine the corresponding first average value and second average value.

[0072] Furthermore, a measurement module is included for:

[0073] After calibrating the mobile truck scanning station calibration model based on the equivalent conversion coefficient, a fifth response result of the mobile truck scanning station calibration model measurement system is determined using a Monte Carlo numerical calculation model;

[0074] determining a response coefficient of a mobile truck scanning station calibration model measurement system based on the first response result and the fifth response result;

[0075] The ore is measured using a calibrated mobile truck scanning station scale model and response factor.

[0076] Based on the above technical solution, the present invention has at least the following beneficial effects:

[0077] 1. This invention establishes a small-scale mobile truck scanning station calibration model for different ore contents. Using the first and second response results determined by the on-site calculation model and the mobile truck scanning station calibration model, an equivalent conversion coefficient is determined between the two models. The mobile truck scanning station calibration model is calibrated based on this equivalent conversion coefficient. Calibration of the mobile truck scanning station only requires the calibrated mobile truck scanning station calibration model, eliminating the need for large amounts of material. This results in high calibration efficiency and ensures consistent grade data across calibrations, thereby improving the accuracy of the calibration results.

[0078] 2. The present invention determines the response results of the mobile truck scanning station calibration model measurement system through the Monte Carlo numerical calculation model and the mobile truck scanning station calibration model respectively, and determines the response coefficient of the detector based on the response results. The ore grade is measured using the calibrated mobile truck scanning station calibration model and response coefficient, which can improve the accuracy of ore grade measurement and reduce the problem of increased ore mining depletion rate caused by waste rock being mistaken for ore and entering the ore storage pile due to inaccurate ore grade measurement.

[0079] 3. This invention uses a Monte Carlo numerical calculation model to simulate and obtain the response results of the mobile truck scanning station calibration model measurement system under different thicknesses and widths. Based on the response results, the thickness and width of the mobile truck scanning station calibration model are determined, thereby establishing a mobile truck scanning station calibration model. Compared with on-site calculation models, the mobile truck scanning station calibration model established by this method is easier to store and has higher calibration efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0080] The accompanying drawings, which constitute part of the present invention, are intended to provide a further understanding of the present invention. The exemplary embodiments of the present invention and their descriptions are intended to explain the present invention and do not constitute an undue limitation of the present invention. In the accompanying drawings:

[0081] FIG1 is a flow chart of a method for establishing and calibrating a calibration model of a mobile truck scanning station according to an embodiment of the present invention;

[0082] FIG2 is a schematic diagram of a Monte Carlo numerical calculation model according to an embodiment of the present invention;

[0083] FIG3 is a schematic diagram of an ore body model in a Monte Carlo numerical calculation model according to an embodiment of the present invention;

[0084] FIG4 is a flow chart of establishing a calibration model for a mobile truck scanning station according to one embodiment of the present invention;

[0085] FIG5 is a schematic diagram of a third response result of the mobile truck scanning station calibration model measurement system in one specific embodiment of the present invention;

[0086] FIG6 is a schematic diagram of a fourth response result of a mobile truck scanning station calibration model measurement system according to a specific embodiment of the present invention;

[0087] FIG7 is a schematic diagram of a three-dimensional structure of a scale model layout of a mobile truck scanning station according to one embodiment of the present invention;

[0088] FIG8 is a schematic diagram of a mobile truck scanning station scale model moving at a uniform speed along the radial and horizontal directions of the detector according to one embodiment of the present invention;

[0089] FIG9 is a spatial distribution curve of the first detection efficiency corresponding to the main detector in a specific embodiment of the present invention;

[0090] FIG10 is a flow chart showing how to determine an equivalent conversion coefficient based on a first response result and a second response result in a specific embodiment of the present invention;

[0091] FIG11 is a flow chart of a method for establishing and calibrating a calibration model of a mobile truck scanning station according to another embodiment of the present invention;

[0092] FIG12 is a spatial distribution curve of the first detection efficiency corresponding to the left detector in a specific embodiment of the present invention;

[0093] FIG13 is a first detection efficiency spatial distribution curve corresponding to the right detector in a specific embodiment of the present invention;

[0094] FIG14 is a schematic diagram of a device for establishing and calibrating a calibration model of a mobile truck scanning station according to an embodiment of the present invention;

[0095] FIG15 is a schematic diagram of a device for establishing and calibrating a calibration model of a mobile truck scanning station according to another embodiment of the present invention. DETAILED DESCRIPTION

[0096] It should be noted that, in the absence of conflict, the embodiments and features of the embodiments of the present invention can be combined with each other. The present invention will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0097] The present invention is further described in detail below with reference to specific examples. These examples should not be construed as limiting the scope of protection claimed in the present invention.

[0098] Example

[0099] Based on the above technical problems, the present invention proposes a method and device for establishing and calibrating a scale model of a mobile truck scanning station to solve the problems in the prior art of low accuracy of the calibration results of the ore grade measurement system of the truck scanning station and large ore grade measurement errors caused by the low accuracy of the calibration results.

[0100] To achieve the above objectives, the present invention proposes a method for establishing and calibrating a scale model of a mobile truck scanning station.

[0101] FIG1 shows a flow chart of a method for establishing and calibrating a calibration model of a mobile truck scanning station according to an embodiment of the present invention. As shown in FIG1 , the method includes the following sub-steps:

[0102] S1, obtain the size parameters of the mobile truck scanning station and establish a Monte Carlo numerical calculation model based on the size parameters.

[0103] Specifically, this method is applied to the calibration model measurement system of a mobile truck scanning station. In this embodiment, based on the on-site installation structure of the ore scanning station in the Hushan mining area, the dimensional parameters of the object to be measured and the measurement system, and according to the theory of interaction between matter and rays, the geometric structure of the measurement system and the corresponding physical response process are abstracted to establish a Monte Carlo numerical calculation model.

[0104] The measurement system includes a gantry, a left detector, a main detector and a right detector. The dimensional parameters include the height of the gantry, the distance between the left detector, the main detector and the right detector, and the opening direction, and the height of the object to be measured from the main detector. After determining the above-mentioned dimensional parameters, a Monte Carlo numerical calculation model is established based on the above-mentioned dimensional parameters. As shown in Figure 2, a schematic diagram of the Monte Carlo numerical calculation model of this embodiment is shown. In Figure 2, A is the left detector, B is the main detector, C is the right detector, and D is the ore body model. Among them, the distance between the main detector and the left detector and the right detector is 3.5m, and the height of the main detector from the ground is 10m. As shown in Figure 3, a schematic diagram of the ore body model and a schematic diagram of the detector model in the Monte Carlo numerical calculation model are shown.

[0105] S2, establish the mobile truck scanning station calibration model through Monte Carlo numerical calculation model.

[0106] As shown in FIG4 , step S2 specifically includes the following sub-steps:

[0107] S201 , using a Monte Carlo numerical calculation model to simulate and obtain third response results of a mobile truck scanning station scale model measurement system under different thicknesses.

[0108] In a specific embodiment of the present invention, the Monte Carlo numerical calculation model established in step S1 above was used to simulate models with thicknesses ranging from 0 to 50 cm using a mobile truck scanning station to calibrate the model measurement system. The third response result obtained is shown in Figure 5. The abscissa X represents the thickness of the model, and the ordinate Y represents the relative count rate, which can be understood as the percentage of the effective response to the maximum response under the current model.

[0109] S202: Determine the thickness of the calibration model of the mobile truck scanning station according to the third response result.

[0110] Based on the third response result obtained in step S201, it can be concluded that when the model thickness is 20 cm, its relative count rate is 87%. This means that the effective response has reached 87% of the maximum response. Further increases in thickness will not significantly contribute to the response. Therefore, in this embodiment, the thickness of the calibration model for the mobile truck scanning station is intended to be 20 cm.

[0111] S203 , under the condition of the thickness of the mobile truck scanning station scale model, using a Monte Carlo numerical calculation model to simulate and obtain fourth response results of the mobile truck scanning station scale model measurement system at different widths.

[0112] Taking the above-described embodiment as an example, the thickness of the mobile truck scanning station calibration model, determined in step S202, is used as a reference. A Monte Carlo numerical calculation model is used to simulate and obtain the fourth response results of the mobile truck scanning station calibration model measurement system at different widths. The curve corresponding to the calibration model in Figure 6 shows the response results corresponding to the mobile truck scanning station calibration model when the thickness is 20 cm and the width is 120 cm.

[0113] S204 , obtaining actual response results of the mobile truck scanning station scale model measurement system at different widths under the thickness condition of the mobile truck scanning station scale model.

[0114] Similar to step S203, the actual response of the mobile truck scanning station scale model measurement system is obtained for different widths, using the 20 cm thickness of the mobile truck scanning station scale model determined in step S202 as a benchmark. The curve corresponding to the mine car in Figure 6 shows the response for a mine car with a thickness of 20 cm and a width of 120 cm.

[0115] S205 : Determine the width of the scale model of the mobile truck scanning station according to the fourth response result and the actual response result.

[0116] In this embodiment, by comparing the fourth response results with the actual response results for different widths, Figure 6 shows that when the overall width of the mobile truck scanning station calibration model is greater than 120 cm, the energies above 400 KeV, such as energies at and above 0.5 MeV, are consistent with the actual response results. Furthermore, the energy range above 400 KeV is the primary energy range used when calibrating the mobile truck scanning station calibration model. Based on these conclusions, the width of the mobile truck scanning station calibration model can be determined to be 120 cm.

[0117] S206 , establishing a mobile truck scanning station scale model based on the thickness and width of the mobile truck scanning station scale model.

[0118] Based on the above steps, it can be determined that the thickness of the mobile truck scanning station scale model in this specific embodiment is 20 cm and the width is 120 cm, thereby establishing a 1.2*1.2*0.2m mobile truck scanning station scale model.

[0119] In order to achieve linear calibration for the ore content of Hushan Mine, the present invention established four sets of mobile truck scanning station calibration models, whose uranium contents were 5.0%, 2.0%, 0.5%, and 0.2%, respectively, and the density was 2.0g / cm 3 , and the radon emission coefficient is 0. To facilitate processing and transportation, the present invention divides each mobile truck scanning station calibration model into a nine-square grid. The dimensions of the divided small mobile truck scanning station calibration models are 0.4*0.4*0.4m. Figure 7 shows the three-dimensional structure of the mobile truck scanning station calibration model layout.

[0120] S3, using the mobile truck scanning station calibration model to determine a first response result of the mobile truck scanning station calibration model measurement system.

[0121] In this step, the mobile truck scanning station calibration model is first placed on a trailer and moved at a constant speed in both the radial and horizontal directions of the main detector. Figure 8 shows a schematic diagram of the mobile truck scanning station calibration model moving at a constant speed in both the radial and horizontal directions of the detectors. A represents the left detector, B represents the main detector, and C represents the right detector. The radial direction represents the front-to-back direction on the Y-axis, and the horizontal direction represents the left-to-right direction on the X-axis.

[0122] In another specific embodiment of the present invention, a mobile truck scanning station calibration model is placed on a trailer. With the zero point directly below the main detector (i.e., at y = 0), the main detector is moved horizontally and radially along the X and Y axes, with measurements taken every 1 meter from -10 m to 10 m. The area within the range of -4 m to 4 m horizontally along the X axis and -5 m to 5 m radially along the Y axis is selected as the detector calibration area for the mobile truck scanning station calibration model. This yields a first detection efficiency spatial distribution curve corresponding to the main detector, as shown in Figure 9. The detection efficiency data corresponding to the first detection efficiency spatial distribution curve represents the first response result.

[0123] S4, establishing a field calculation model according to the parameters of the mobile truck scanning station calibration model, and determining a second response result of the mobile truck scanning station calibration model measurement system using the field calculation model.

[0124] In this step, a field calculation model is first established based on the parameters of the mobile truck scanning station calibration model. These parameters include the height of the main detector from the ground, the dimensions, materials, distances, and opening orientations of the main, left, and right detectors. These parameters are then combined with the volume of the mobile truck scanning station calibration model to establish the field calculation model.

[0125] The field calculation model is a ton-bag model, i.e., a model of a large truck loaded with the same volume of ore. Similar to the principle of obtaining the first response result in step S3, in this step, with the zero point directly below the main detector (i.e., y = 0) as the zero point, the field calculation model is moved horizontally and radially along the X- and Y-axes of the main detector, respectively, from -10m to 10m, with measurements taken every 1m. This generates a second detection efficiency spatial distribution curve corresponding to the main detector. The detection efficiency data corresponding to the second detection efficiency spatial distribution curve is the second response result.

[0126] S5, determining an equivalent conversion coefficient according to the first response result and the second response result.

[0127] As shown in FIG10 , step S5 includes the following sub-steps:

[0128] S501: Determine a first average value of detection efficiency according to a first response result.

[0129] Specifically, first, multiple first detection efficiency data corresponding to the position directly below the main detector in the first response result are obtained, namely, the five first detection efficiency data corresponding to the positions y = 0, x = -4m, x = -2m, x = 0m, x = 4m, and x = 2m in Figure 9. Next, these five first detection efficiency data are summed to determine a first average value. Since the first detection efficiency data corresponding to x = 4m and x = 2m in Figure 9 is 0, in the actual calculation, only the three first detection efficiency data corresponding to the positions y = 0, x = -4m, x = -2m, and x = 0m need to be considered, which correspond to the detection efficiencies corresponding to points a, b, and c in Figure 9, respectively.

[0130] S502: Determine a second average value of the detection efficiency according to the second response result.

[0131] Similar to the method for determining the first average value in step S501, in this step, multiple second detection efficiency data corresponding to the position directly below the main detector in the second response result are first obtained, namely, five second detection efficiency data corresponding to the positions y = 0, x = -4m, x = -2m, x = 0m, x = 4m, and x = 2m. Then, these five second detection efficiency data are summed to determine the second average value.

[0132] S503: Taking the ratio of the first average value to the second average value as an equivalent conversion coefficient.

[0133] The ratio of the first average value determined in step S501 to the second average value determined in step S502 is used as an equivalent conversion coefficient between the mobile truck scanning station calibration model and the on-site calculation model.

[0134] S6, calibrate the mobile truck scanning station calibration model based on the equivalent conversion coefficient.

[0135] After calibrating the mobile truck scanning station's calibration model based on these equivalent conversion factors, calibration of the mobile truck scanning station only requires the mobile model, eliminating the need for large piles of material, thus ensuring good preservation. Furthermore, using this mobile truck scanning station's calibration model for each calibration ensures consistent grade data.

[0136] As shown in Figure 11, in another embodiment of the present invention, after executing steps S1 to S6, the method further includes steps S7 to S9. By determining the response coefficient of the mobile truck scanning station calibration model measurement system and using the calibrated mobile truck scanning station calibration model and response coefficient to measure ore, the accuracy of ore grade measurement can be improved, and the problem of waste rock mistaken for ore entering the ore storage pile due to inaccurate ore grade measurement can be reduced, thereby reducing the problem of increased ore mining dilution rate. The specific steps are detailed as follows:

[0137] S7, after calibrating the mobile truck scanning station calibration model based on the equivalent conversion coefficient, determining a fifth response result of the mobile truck scanning station calibration model measurement system using a Monte Carlo numerical calculation model.

[0138] Similar to the principle of obtaining the first response result in step S3, in this step, the Monte Carlo numerical calculation model is first used to simulate the uniform movement of the mobile truck scanning station scale model with the same ore content along the radial and horizontal directions of the main detector to obtain the third detection efficiency spatial distribution curve corresponding to the main detector.

[0139] Specifically, if step S3 obtains the first response result of the mobile truck scanning station calibration model with a uranium content of 5.0% passing through the mobile truck scanning station calibration model measurement system, then in this step, the Monte Carlo numerical calculation model should be used to simulate the mobile truck scanning station calibration model with a uranium content of 5.0% passing through the mobile truck scanning station calibration model measurement system to obtain the third detection efficiency spatial distribution curve corresponding to the main detector, and then the data corresponding to the third detection efficiency spatial distribution curve is used as the fifth response result.

[0140] S8. Determine a response coefficient of the mobile truck scanning station calibration model measurement system according to the first response result and the fifth response result.

[0141] Specifically, this step is similar to the method for determining the equivalent conversion coefficient based on the first and second response results in step S5. First, a first average value of the detection efficiency is determined based on the first response result, as described in step S501. Second, a third average value of the detection efficiency is determined based on the fifth response result. The specific process is as follows: Multiple third detection efficiency data corresponding to the position directly below the main detector in the fifth response result are obtained, namely, five third detection efficiency data corresponding to positions y = 0, x = -4 m, x = -2 m, x = 0 m, x = 4 m, and x = 2 m. Next, these five third detection efficiency data are summed to determine the third average value.

[0142] Next, the ratio of the first average value to the third average value determined above is used as the response coefficient of the mobile truck scanning station calibration model measurement system.

[0143] S9, ore measurements using the calibrated mobile truck scanning station scale model and response factors.

[0144] The ore is measured using the calibration model of the mobile truck scanning station calibrated in step S6 and the response coefficient determined above, thereby improving the accuracy of ore grade measurement.

[0145] It should be understood that when actually determining the first, second, third, fourth, and fifth response results, the mobile truck scanning station calibration model, field calculation model, and Monte Carlo numerical calculation model can also be moved horizontally and radially along the X-axis and Y-axis directions of the left detector, main detector, and right detector, respectively, with measurements taken every 1 meter from -10m to 10m to obtain the detection efficiency spatial distribution curve corresponding to each detector, thereby determining the corresponding response result. Taking the determination of the first response result as an example, Figures 9, 12, and 13 show the first detection efficiency spatial distribution curves corresponding to the main detector, left detector, and right detector, respectively. The detection efficiency data corresponding to the first detection efficiency spatial distribution curves of the three detectors can then be used as the first response result.

[0146] To achieve the same purpose as the above method, the present invention also proposes a device for establishing and calibrating a scale model of a mobile truck scanning station.

[0147] Figure 14 shows a schematic diagram of a mobile truck scanning station calibration model establishment and calibration device, according to one embodiment of the present invention. This device is used in a mobile truck scanning station calibration model measurement system, which includes a gantry, a left detector, a main detector, and a right detector. The device includes an acquisition module 151, an establishment module 152, a first determination module 153, a second determination module 154, a third determination module 155, and a calibration module 156. The specific functions of each module are described in detail below.

[0148] The acquisition module 151 is used to obtain the dimensional parameters of the mobile truck scanning station and establish a Monte Carlo numerical calculation model based on the dimensional parameters. The dimensional parameters include the height of the gantry, the distance and opening direction between the left detector, the main detector and the right detector, and the height of the object to be measured from the main detector.

[0149] The establishing module 152 is used to establish a calibration model of the mobile truck scanning station through a Monte Carlo numerical calculation model.

[0150] Furthermore, a module 152 is established for:

[0151] The Monte Carlo numerical calculation model is used to simulate and obtain the third response results of the mobile truck scanning station scale model measurement system under different thicknesses.

[0152] The thickness of the mobile truck scanning station scale model is determined according to the third response result.

[0153] Under the condition of the thickness of the mobile truck scanning station scale model, the Monte Carlo numerical calculation model is used to simulate and obtain the fourth response results of the mobile truck scanning station scale model measurement system under different widths.

[0154] Under the condition of the thickness of the mobile truck scanning station calibration model, the actual response results of the mobile truck scanning station calibration model measurement system at different widths are obtained.

[0155] The width of the scale model of the mobile truck scanning station is determined according to the fourth response result and the actual response result.

[0156] A mobile truck scanning station scale model is established based on the thickness and width of the mobile truck scanning station scale model.

[0157] The first determining module 153 is configured to determine a first response result of the mobile truck scanning station calibration model measurement system using the mobile truck scanning station calibration model.

[0158] Furthermore, the first determining module 153 is configured to:

[0159] The mobile truck scanning station calibration model is placed on the trailer and moved at a uniform speed along the radial and horizontal directions of the main detector to obtain the first detection efficiency spatial distribution curve corresponding to the main detector.

[0160] The detection efficiency data corresponding to the first detection efficiency spatial distribution curve is the first response result.

[0161] The second determining module 154 is configured to establish a field calculation model according to the parameters of the mobile truck scanning station calibration model, and determine a second response result of the mobile truck scanning station calibration model measurement system using the field calculation model.

[0162] Furthermore, the second determining module 154 is configured to:

[0163] The Monte Carlo numerical calculation model is used to simulate the uniform movement of the mobile truck scanning station scale model with the same ore content along the radial and horizontal directions of the main detector, and the second detection efficiency spatial distribution curve corresponding to the main detector is obtained.

[0164] The detection efficiency data corresponding to the second detection efficiency spatial distribution curve is the second response result.

[0165] The third determining module 155 is configured to determine an equivalent conversion coefficient according to the first response result and the second response result.

[0166] Furthermore, the third determining module 155 is configured to:

[0167] determining a first average value of the detection efficiency according to the first response result;

[0168] determining a second average value of the detection efficiency according to the second response result;

[0169] The ratio of the first average value to the second average value is used as the equivalent conversion coefficient.

[0170] Furthermore, the third determining module 155 is further configured to:

[0171] Acquire a plurality of first detection efficiency data corresponding to a position directly below the main detector in the first response result;

[0172] Acquire a plurality of second detection efficiency data corresponding to a position directly below the main detector in the second response result;

[0173] The plurality of first detection efficiency data and the plurality of second detection efficiency data are summed up respectively to determine the corresponding first average value and second average value.

[0174] The calibration module 156 is configured to calibrate the mobile truck scanning station calibration model based on the equivalent conversion coefficient.

[0175] As shown in FIG15 , in another embodiment of the present invention, the apparatus further includes a measuring module 157 for:

[0176] After calibrating the mobile truck scanning station calibration model based on the equivalent conversion coefficient, a fifth response result of the mobile truck scanning station calibration model measurement system is determined using a Monte Carlo numerical calculation model;

[0177] determining a response coefficient of a mobile truck scanning station calibration model measurement system based on the first response result and the fifth response result;

[0178] The ore is measured using a calibrated mobile truck scanning station scale model and response factor.

[0179] It should be understood that the description of the apparatus for establishing and calibrating a scale model of a mobile truck scanning station is consistent with the description of the corresponding method for establishing and calibrating a scale model of a mobile truck scanning station, and thus will not be repeated in this embodiment.

[0180] In summary, it can be seen from the above description that the above embodiments of the present invention achieve the following technical effects:

[0181] 1. This invention establishes a small-scale mobile truck scanning station calibration model for different ore contents. Using the first and second response results determined by the on-site calculation model and the mobile truck scanning station calibration model, an equivalent conversion coefficient is determined between the two models. The mobile truck scanning station calibration model is calibrated based on this equivalent conversion coefficient. Calibration of the mobile truck scanning station only requires the calibrated mobile truck scanning station calibration model, eliminating the need for large amounts of material. This results in high calibration efficiency and ensures consistent grade data across calibrations, thereby improving the accuracy of the calibration results.

[0182] 2. The present invention determines the response results of the mobile truck scanning station calibration model measurement system through the Monte Carlo numerical calculation model and the mobile truck scanning station calibration model respectively, and determines the response coefficient of the detector based on the response results. The ore grade is measured using the calibrated mobile truck scanning station calibration model and response coefficient, which can improve the accuracy of ore grade measurement and reduce the problem of increased ore mining depletion rate caused by waste rock being mistaken for ore and entering the ore storage pile due to inaccurate ore grade measurement.

[0183] 3. This invention uses a Monte Carlo numerical calculation model to simulate and obtain the response results of the mobile truck scanning station calibration model measurement system under different thicknesses and widths. Based on the response results, the thickness and width of the mobile truck scanning station calibration model are determined, thereby establishing a mobile truck scanning station calibration model. Compared with on-site calculation models, the mobile truck scanning station calibration model established by this method is easier to store and has higher calibration efficiency.

[0184] The foregoing description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Those skilled in the art will readily appreciate that various modifications and variations of the present invention are possible. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of the present invention are intended to be within the scope of protection of the present invention.

[0185] It should be noted that, in this document, relational terms such as first and second, etc., are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "comprises," "comprising," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or device comprising a series of elements includes not only those elements, but also other elements not explicitly listed, or elements inherent to such process, method, article, or device. In the absence of further limitations, an element defined by the phrase "comprising a ..." does not exclude the presence of other identical elements in the process, method, article, or device comprising the element.

[0186] The logic and / or steps represented in the flowchart or otherwise described herein may be considered, for example, as an ordered list of executable instructions for implementing logical functions, and may 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 system including a processor, or other system that can fetch and execute instructions from an instruction execution system, apparatus, or device).

[0187] It should be understood that various parts of the present invention can be implemented using hardware, software, firmware, or a combination thereof. In the above-described embodiments, multiple steps or methods can be implemented using software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented using hardware, as in another embodiment, any one of the following technologies known in the art or a combination thereof can be used: a discrete logic circuit having a logic gate circuit for implementing a logic function on a data signal, an application-specific integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0188] It should be noted that, in the description of this specification, the reference terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" mean that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic expressions of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art can combine and combine different embodiments or examples described in this specification and the features of different embodiments or examples, unless they are contradictory.

Claims

1. A method for establishing and calibrating a scale model of a mobile truck scanning station, which is applied to a scale model measurement system of a mobile truck scanning station. The measurement system includes a gantry, a left detector, a main detector, and a right detector, and is characterized in that Including: Obtain the dimensional parameters of the mobile truck scanning station, and establish a Monte Carlo numerical calculation model according to the dimensional parameters. The dimensional parameters include the height of the gantry, the distances and opening directions between the left detector, the main detector, and the right detector, and the height of the main detector from the ground; Establish a calibration model for the mobile truck scanning station through the Monte Carlo numerical calculation model; Use the calibration model of the mobile truck scanning station to determine the first response result of the measurement system of the calibration model of the mobile truck scanning station; Establish a field calculation model according to the parameters of the calibration model of the mobile truck scanning station, and use the field calculation model to determine the second response result of the measurement system of the calibration model of the mobile truck scanning station; Determine the equivalent conversion coefficient according to the first response result and the second response result; Calibrate the calibration model of the mobile truck scanning station based on the equivalent conversion coefficient.

2. The method according to claim 1, wherein Establish a calibration model for the mobile truck scanning station through the Monte Carlo numerical calculation model, including: Use the Monte Carlo numerical calculation model to simulate and obtain the third response results of the measurement system of the calibration model of the mobile truck scanning station at different thicknesses; Determine the thickness of the calibration model of the mobile truck scanning station according to the third response results; Under the thickness condition of the calibration model of the mobile truck scanning station, use the Monte Carlo numerical calculation model to simulate and obtain the fourth response results of the measurement system of the calibration model of the mobile truck scanning station at different widths; Under the thickness condition of the calibration model of the mobile truck scanning station, obtain the actual response results of the measurement system of the calibration model of the mobile truck scanning station at different widths; Determine the width of the calibration model of the mobile truck scanning station according to the fourth response results and the actual response results; Establish the calibration model of the mobile truck scanning station based on the thickness and width of the calibration model of the mobile truck scanning station.

3. The method according to claim 1 or 2, characterized in that, Use the calibration model of the mobile truck scanning station to determine the first response result of the measurement system of the calibration model of the mobile truck scanning station, including: Place the calibration model of the mobile truck scanning station on the trailer and move it uniformly along the radial direction and the horizontal direction of the main detector to obtain the first detection efficiency spatial distribution curve corresponding to the main detector; The detection efficiency data corresponding to the first detection efficiency spatial distribution curve is the first response result.

4. The method according to any one of claims 1 to 3, characterized in that Establish a field calculation model according to the parameters of the calibration model of the mobile truck scanning station, and use the field calculation model to determine the second response result of the measurement system of the calibration model of the mobile truck scanning station, including: Use the Monte Carlo numerical calculation model to simulate the calibration model of the mobile truck scanning station with the same ore content moving uniformly along the radial direction and the horizontal direction of the main detector to obtain the second detection efficiency spatial distribution curve corresponding to the main detector; The detection efficiency data corresponding to the second detection efficiency spatial distribution curve is the second response result.

5. The method according to any one of claims 1 to 4, characterized in that Determine the equivalent conversion coefficient according to the first response result and the second response result, including: Determine the first average value of the detection efficiency according to the first response result; Determine the second average value of the detection efficiency according to the second response result; Use the ratio of the first average value and the second average value as the equivalent conversion coefficient.

6. The method according to claim 5, wherein Determining the equivalent conversion coefficient according to the first response result and the second response result further includes: Obtain a plurality of first detection efficiency data corresponding to the position directly below the main detector in the first response result; Obtain a plurality of second detection efficiency data corresponding to the position directly below the main detector in the second response result; Sum the plurality of first detection efficiency data and the plurality of second detection efficiency data respectively and determine the corresponding first average value and second average value.

7. The method according to any one of claims 1 to 6, characterized in that, Further includes: After calibrating the scale model of the mobile truck scanning station based on the equivalent conversion coefficient, use the Monte Carlo numerical calculation model to determine the fifth response result of the measurement system of the scale model of the mobile truck scanning station; Determine the response coefficient of the measurement system of the scale model of the mobile truck scanning station according to the first response result and the fifth response result; Measure the ore using the calibrated scale model of the mobile truck scanning station and the response coefficient.

8. An establishment and calibration device for a scale model of a mobile truck scanning station, the device being applied to a scale model measurement system of a mobile truck scanning station, the measurement system including a gantry, a left detector, a main detector, and a right detector, characterized in that, Includes: An acquisition module, configured to acquire the dimensional parameters of the mobile truck scanning station, and establish a Monte Carlo numerical calculation model according to the dimensional parameters, where the dimensional parameters include the height of the gantry, the distances and opening directions between the left detector, the main detector, and the right detector, and the height of the main detector from the ground; A building module, configured to establish a scale model of the mobile truck scanning station through the Monte Carlo numerical calculation model; A first determination module, configured to use the scale model of the mobile truck scanning station to determine the first response result of the measurement system of the scale model of the mobile truck scanning station; A second determination module, configured to establish a field calculation model according to the parameters of the scale model of the mobile truck scanning station, and use the field calculation model to determine the second response result of the measurement system of the scale model of the mobile truck scanning station; A third determination module, configured to determine the equivalent conversion coefficient according to the first response result and the second response result; A calibration module, configured to calibrate the scale model of the mobile truck scanning station based on the equivalent conversion coefficient.

9. The device according to claim 8, characterized in that, The building module is configured to: Use the Monte Carlo numerical calculation model to simulate and obtain the third response result of the measurement system of the scale model of the mobile truck scanning station at different thicknesses; Determine the thickness of the scale model of the mobile truck scanning station according to the third response result; Under the thickness condition of the scale model of the mobile truck scanning station, use the Monte Carlo numerical calculation model to simulate and obtain the fourth response result of the measurement system of the scale model of the mobile truck scanning station at different widths; Under the thickness condition of the scale model of the mobile truck scanning station, obtain the actual response result of the measurement system of the scale model of the mobile truck scanning station at different widths; Determine the width of the scale model of the mobile truck scanning station according to the fourth response result and the actual response result; Establish the calibration model of the mobile truck scanning station based on the thickness and width of the calibration model of the mobile truck scanning station.

10. The device according to claim 8 or 9, characterized in that The first determination module is configured to: Place the calibration model of the mobile truck scanning station on a trailer and move it uniformly along the radial direction and the horizontal direction of the main detector, and obtain the first detection efficiency spatial distribution curve corresponding to the main detector; The detection efficiency data corresponding to the first detection efficiency spatial distribution curve is the first response result.

11. The device according to any one of claims 8 to 10, characterized in that, The second determination module is configured to: Simulate the calibration model of the mobile truck scanning station with the same ore content moving uniformly along the radial direction and the horizontal direction of the main detector through the Monte Carlo numerical calculation model, and obtain the second detection efficiency spatial distribution curve corresponding to the main detector; The detection efficiency data corresponding to the second detection efficiency spatial distribution curve is the second response result.

12. The device according to any one of claims 8 to 11, characterized in that The third determination module is configured to: Determine the first average value of the detection efficiency according to the first response result; Determine the second average value of the detection efficiency according to the second response result; Take the ratio of the first average value and the second average value as the equivalent conversion coefficient.

13. The device according to claim 12, characterized in that, The third determination module is further configured to: Obtain a plurality of first detection efficiency data corresponding to the position directly below the main detector in the first response result; Obtain a plurality of second detection efficiency data corresponding to the position directly below the main detector in the second response result; Sum the plurality of first detection efficiency data and the plurality of second detection efficiency data respectively and determine the corresponding first average value and second average value.

14. The device according to any one of claims 8 to 13, characterized in that, It further includes a measurement module configured to: After calibrating the calibration model of the mobile truck scanning station based on the equivalent conversion coefficient, use the Monte Carlo numerical calculation model to determine the fifth response result of the measurement system of the calibration model of the mobile truck scanning station; Determine the response coefficient of the measurement system of the calibration model of the mobile truck scanning station according to the first response result and the fifth response result; Measure the ore by using the calibrated calibration model of the mobile truck scanning station and the response coefficient.

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