Deviation analysis method for theoretical grade and actual grade of ore wool

Abstract

Compared with the prior art, the ore wool theory and actual grade deviation analysis method disclosed by the invention has the following beneficial effects that the average grade AGn of each ore draw shaft in a preset time period in a mining area is obtained, and then the daily raw ore grade AG total in the mining area is calculated according to the number of mines in the mining area; according to the obtained raw ore grade deviation and the theoretical actual grade deviation, comparative analysis is conducted, it is facilitated that self-inspection and self-correction are conducted on recent ore wool management work regularly, and problems are found in time, and the method comprises the following steps that firstly, the average grade AGn of each ore draw shaft in the preset time period is obtained; and 2, according to the average grade of each ore winze, calculating the raw ore grade AG total in the preset time period of the mining area.

Description

Technical Field

[0001] The present invention relates to the technical field of mineral analysis, and particularly to a method for analyzing the deviation between the theoretical and actual grades of ore wool. Background Art

[0002] In mineral mining, to ensure that both the mining volume and the output of the target mineral meet the indicators smoothly, it is necessary to reasonably allocate the mining volume between the low-grade mining area and the high-grade mining area according to the ore reserves. Currently, due to limited resources, it is difficult to increase the ore output from high-grade ore rooms and it remains difficult continuously. The ore output from low-grade stope cannot be reduced under tight working conditions. Therefore, during the period when there is no high-grade ore available for allocation and the supply ratio of the low-grade stope is relatively large, there is a situation where the selected grade is significantly reduced, which has a greater negative impact on the completion of mineral-related indicators.

[0003] The main reason for the above situation is that the ore wool separation is ineffective, the ore wool is mixed and poured, and there are violations such as over-designed dilution, which lead to a significant reduction in the selected grade. To ensure economic benefits, the most effective means is to adopt ore blending measures to avoid as much as possible the drastic fluctuation of the selected grade. Secondly, once the situation of the selected grade fluctuation occurs, the comparison and analysis between the theoretical and actual grades should be carried out immediately to find the reasons and take corresponding measures. Summary of the Invention

[0004] The purpose of the present invention is to solve the above problems and provide a method for analyzing the deviation between the theoretical and actual grades of ore wool.

[0005] To achieve the above purpose, the technical solution of the present invention is: a method for analyzing the deviation between the theoretical and actual grades of ore wool, including the following steps: Step 1: Obtain the average grade AG of each ore chute within a predetermined time period n ; Step 2: Calculate the raw ore grade AG within the predetermined time period of the mining area according to the average grade of each ore chute 总 .

[0006] Further, in Step 1, the steps for obtaining the average grade AG of each ore chute within a predetermined time period n are as follows: S10: Obtain the geological sampling grade G at the ore outlet of the ore chute within a predetermined time period; S11: Obtain the ore output W at the ore outlet of the ore chute within a predetermined time period; S12: Calculate the average grade of the ore chute within a predetermined time period: AG n = (G 1 * W 1 * D 1 + G 2 * W 2 * D2 +…G m *W m *D m ) / (W 1 +W 2 +…W m ); In the formula, G m is the geological sample grade within the predetermined time period and the predetermined duration range of the ore pass, W m is the ore output within the predetermined time period and the predetermined duration range of the ore pass, D m is the dilution rate of mining within the predetermined time period and the predetermined duration range of the ore pass.

[0007] Furthermore, calculating the raw ore grade AG within the predetermined time period of the mining area 总 includes: S20. Obtain the number of ore-discharging vehicles C for each ore pass within the predetermined time period f ; S21. Obtain the average grade AG of each ore pass within the predetermined time period in the mining area n ; S22. Calculate the raw ore grade within the predetermined time period of the mining area: AG 总 =(AG 1 *C 1 +AG 2 *+C 2 …+AG n *C f ) / (C 1 + C 2 +…+ C f ).

[0008] Furthermore, obtaining the ore output W at the ore-discharging point of the ore pass within the predetermined time period includes the following steps: Detect the weight information and the number information of the vehicles passing through the weight detection device within the predetermined time period by a weight detection sensor; Calculate the ore output W within the predetermined time period according to the number and weight information of the vehicles.

[0009] A method for analyzing the deviation between the theoretical and actual grades of ore wool disclosed by the present invention has the following beneficial effects compared with the prior art: By obtaining the average grade AG of each ore pass within the predetermined time period in the mining area in this application n , and then calculating the raw ore grade AG of the mining area every day according to the number of mine shafts in the mining area 总 , and comparing and analyzing the obtained deviation between the raw ore grade and the theoretical and actual grades, it is beneficial to regularly conduct self-examination and self-correction on the recent ore wool management work, and timely discover problems, including the following steps: Step 1. Obtain the average grade AG of each ore pass within the predetermined time periodn ; Step 2: Calculate the raw ore grade AG within the predetermined period of the mining area based on the average grade of each ore pass 总 . BRIEF DESCRIPTION OF THE DRAWINGS

[0010] Figure 1 It is a schematic flow chart of a method for analyzing the deviation between the theoretical and actual grades of ore wool according to the present invention.

[0011] Figure 2 It is a schematic flow chart of obtaining the average grade AG of each ore pass within the predetermined period in a method for analyzing the deviation between the theoretical and actual grades of ore wool according to the present invention. n of obtaining.

[0012] Figure 3 It is a schematic flow chart of calculating the raw ore grade AG within the predetermined period of the mining area in a method for analyzing the deviation between the theoretical and actual grades of ore wool according to the present invention. 总 of calculating.

[0013] Figure 4 It is a module diagram of the detection system in a method for analyzing the deviation between the theoretical and actual grades of ore wool according to the present invention.

[0014] Figure 5 It is a schematic structural diagram of an implementation manner of the detection system in a method for analyzing the deviation between the theoretical and actual grades of ore wool according to the present invention.

[0015] Figure 6 It is a schematic structural diagram of the elastic support member arranged on the ore truck in a method for analyzing the deviation between the theoretical and actual grades of ore wool according to the present invention.

[0016] Figure 7 It is a schematic structural diagram of an implementation manner of the extrusion chamber in a method for analyzing the deviation between the theoretical and actual grades of ore wool according to the present invention.

[0017] In the figure: 1, vehicle-mounted weight sensor; 2, positioning module; 3, verification unit; 31, radio frequency identification module; 32, identification camera; 41, carriage; 42, wheel; 43, frame; 44, elastic support member; 441, rigid support plate; 4410, avoidance channel; 442, spring; 443, extrusion chamber; 4431, first rigid cylinder; 4432, second rigid cylinder; 444, elastic bladder; 5, wireless transmission module; 6, control terminal; 9, rail. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0018] Now, the present invention will be further described in detail with reference to the accompanying drawings. The accompanying drawings are simplified schematic diagrams, which only illustrate the basic structure of the present invention in a schematic manner, so they only show the components related to the present invention.

[0019] Example 1 Please refer to Figure 1, this application provides a method for analyzing the deviation between the theoretical and actual grades of ore wool. As a specific implementation, this method includes the following steps: Step 1: Obtain the average grade AG of each ore pass during a predetermined period. n ; Step 2: Calculate the raw ore grade AG within the mining area during the predetermined period based on the average grade of each ore pass. 总 .

[0020] Specifically, in the actual application process, the predetermined period is generally calculated in days. This application obtains the average grade AG of each ore pass in the mining area during the predetermined period n , and then calculates the raw ore grade AG of each day in the mining area according to the number of mine shafts in the mining area. 总 By comparing and analyzing the obtained deviation of the raw ore grade with the deviation between the theoretical and actual grades, it is beneficial to regularly conduct self-inspection and self-correction on the recent ore wool management work, promptly discover problems, shorten the response time from problem discovery to solution, use the production connection network diagram of the medium and high-grade areas to predict the average grade of each stage of the monthly gold output, facilitate early mastery of the form of gold output completion, and take feasible measures as early as possible. For the time periods with abnormal fluctuations in the selected grade, the grade data can be intuitively understood in the analysis table of the theoretical raw ore grade and the actual selected grade, and the problem can be quickly discovered by combining the waste rock balance situation of the waste rock surface destination ledger, making the ore wool management work more efficient and sensitive.

[0021] Furthermore, as a specific implementation, referring to Figure 2 , in Step 1, the steps for obtaining the average grade AG of each ore pass during the predetermined period are as follows: n : S10: Obtain the geological sample grade G at the ore outlet of the ore pass during the predetermined period; S11: Obtain the ore output W at the ore outlet of the ore pass during the predetermined period; S12: Calculate the average grade of the ore pass during the predetermined period: AG n = (G 1 * W 1 * D 1 + G 2 * W 2 * D 2 + … G m * W m * D m ) / (W 1 + W 2 + … W m ); In the formula, G m is the geological sample grade within the predetermined time range at the ore pass during the predetermined period, and Wm is the ore output within a predetermined time period and within a predetermined duration for the ore pass, D m is the dilution rate of mining within a predetermined time period and within a predetermined duration for the ore pass.

[0022] Specifically, it should be noted that each mining area includes multiple ore passes. The ore passes in each mining area are numbered 1, 2, 3,... n in sequence. The predetermined time period is generally one day. During the one-day mining operation, the ore extraction points of the ore passes are sampled and detected at intervals of the predetermined duration to obtain the geological sample grade. The value of the predetermined duration is 1 hour - 4 hours. Within one day, the geological sample grade obtained from the first sampling and detection is G 1 , the second is G 2 , and so on. Among them, the ore output between the first sampling and detection and the second sampling and detection is W 1 , and the ore output between the second sampling and the third sampling is W 2 , and so on. Among them, the detection of the geological sample grade can be carried out by manual timed sampling and detection, or by relevant sampling and detection equipment for timed sampling and detection. Among them, the ore output W m can be detected in real time through a detection system set on the ore truck and configured on the track. The detection of the geological sample grade is preferably carried out by equipment for timed sampling and detection. The sampling equipment and the detection system are interconnected to form an Internet of Things, so as to be able to obtain relevant data in real time, improve the calculation efficiency, and then through the formula AG n =(G 1 *W 1 *D 1 +G 2 *W 2 *D 2 +…G m *W m *D m ) / (W 1 +W 2 +…W m ) to calculate the average grade of each ore pass per day.

[0023] Furthermore, as a specific implementation method, referring to Figure 3 , calculating the raw ore grade AG within the predetermined time period of the mining area 总 includes: S20. Obtain the number of ore-discharging trucks C of each ore pass within the predetermined time period f ; S21. Obtain the average grade AG of each ore pass within the predetermined time period in the mining area n ; S22. Calculate the raw ore grade within the predetermined time period of the mining area: AG 总 =(AG 1 *C1 +AG 2 *+C 2 …+AG n *C f ) / (C 1 + C 2 +…+ C f )。

[0024] Specifically, at present, the minerals in the ore pass are transported by rail mine cars. According to the number of the ore pass, the number of ore cars leaving the No. 1 ore pass per day is C1, the number of ore cars leaving the No. 2 ore pass per day is C2... By obtaining the number of ore cars C leaving each ore pass per day f , according to the average grade of the ore mined from each corresponding ore pass per day, according to the formula AG 总 = (AG 1 *C 1 +AG 2 *+C 2 …+AG n *C f ) / (C 1 + C 2 +…+ C f ), calculate the average grade of the mining area per day.

[0025] Example Two This application provides a method for analyzing the deviation between the theoretical and actual grades of ore wool. Refer to Figure 4 , this method includes a detection system. The detection system includes: a vehicle-mounted weight sensor 1, a positioning module 2 and a wireless transmission module 5 arranged on the vehicle. Through the vehicle-mounted weight sensor 1, the weight of the minerals on the vehicle can be detected. The vehicle-mounted positioning module 2 can obtain the position of the vehicle. The wireless transmission module 5 can wirelessly transmit the detection information of the vehicle-mounted positioning module 2 and the vehicle-mounted weight sensor 1 to the control terminal 6. In the specific application process, the position of the vehicle is located through the positioning module, so as to locate which ore pass area the vehicle is in and obtain the load condition of the ore car corresponding to the current time point. And according to the sampling time point of the sampling detection equipment for the geological sampling grade of each ore pass, the load condition of the corresponding ore car can be obtained, so that the load condition of each ore car between two adjacent sampling time points can be accurately obtained, and it can be ensured that the ore output between two adjacent sampling time points is W 2 , ensuring the accuracy of subsequent calculations.

[0026] Furthermore, as a specific step of obtaining the ore output W within a predetermined time period at the ore outlet of the ore pass, it includes the following steps: Detect the weight information and the number information of the vehicles passing through the weight detection device within a predetermined time period through the weight detection sensor; Calculate the ore output W within a predetermined time period based on the number and weight information of the vehicles.

[0027] Furthermore, as a specific implementation manner, in order to ensure the accuracy of obtaining the ore output W, a review unit 3 is also provided on one side of the vehicle track at each ore outlet. The quality review unit 3 includes a radio frequency identification module 31 and a weight review module provided on one side of the track. An identity identification tag is provided on the side of each ore truck. The ore truck identity information is obtained by identifying the identity identification tag through the radio frequency identification module 31. The weight review module is used for reviewing the load quality of the ore truck. By obtaining the review weight M of each vehicle and comparing and reviewing it with the detection value of the on-vehicle weight sensor, the accuracy of quality acquisition is ensured.

[0028] Specifically, as an implementation manner, refer to Figure 5 , the weight review module includes an identification camera 32 provided on one side of the track or between two tracks and an identification reference part provided on the ore truck. Refer to Figure 5 、 Figure 6 , where the ore truck includes a carriage 41 and a frame 43 rigidly connected to the wheels 42. An elastic support member 44 is provided between the carriage 41 and the frame 43. The on-vehicle weight sensor 1 is provided between the elastic support member 44 and the carriage. When the carriage is loaded, the elastic support member 44 will be compressed, and the greater the load in the carriage, the greater the compression amount of the elastic support member 44. The identification camera 32 can identify the compression amount of the elastic support member 44, and thus obtain the load weight of the minerals in the carriage according to the compression amount.

[0029] As a specific implementation manner, refer to Figure 5 , the identification camera is provided on one side of the track. Identification marks are provided on both the side of the carriage and the side of the frame. It can be understood that the greater the load in the carriage, the greater the compression amount of the elastic support member 44, which will cause the distance between the carriage and the frame to decrease. The identification camera obtains the image information of the identification marks on the sides of the carriage and the frame, and then processes the image information to obtain the distance between the two identification marks, and obtains the mass of the minerals loaded in the carriage according to the distance between the two identification marks. Specifically, the identification marks can be the structural features of the ore truck carriage and frame or objects fixed on the carriage and frame for easy camera collection.

[0030] Furthermore, it can be understood that since the working environment of the ore truck has a large amount of dust and dirt, the carriage and the frame are prone to adhering dust and mud. After the ore truck surface adheres to dust and mud, it is not convenient to accurately obtain the identification marks on the ore truck, and it is also not convenient to obtain the structural features of the ore truck, and the calculation amount for acquisition and calculation is large and the error is large. In order to cope with the mining working environment and improve the review accuracy of the weight review module, refer to Figure 6, the specific structure of the elastic support 44 is as follows: It includes two rigid support plates 441 arranged at intervals and a plurality of springs 442 evenly arranged between the two rigid support plates 441. An extrusion cavity 443 is also arranged between the two rigid support plates. An avoidance channel 4410 is arranged on the lower rigid support plate 441. The lower end of the extrusion cavity 443 is connected with an elastic bladder 444. The elastic bladder is arranged corresponding to the avoidance channel. When the load in the carriage is zero, the volume of the elastic bladder 444 is small. When the load in the carriage increases, the extrusion cavity 443 is extruded, so that the fluid in the extrusion cavity is extruded into the elastic bladder 444 to make the volume of the elastic bladder expand. At this time, the shape image information of the elastic bladder is obtained through the recognition camera 32, and then the compression amount of the elastic support 44 is obtained according to the relationship between the current shape image information of the elastic bladder and the compression amount of the elastic support 44, so as to obtain the weight of the minerals in the carriage. Through this detection method, when the volume of the elastic bladder 444 changes, it will have a certain cleaning effect on the sundries attached to its surface, so as to ensure the accuracy. Specifically, the extrusion cavity 443 is a rigid cavity with its own resilience. Refer to Figure 7 , which is a schematic structural diagram of an implementation manner of the extrusion cavity 443. It includes a first rigid cylinder 4431 and a second rigid cylinder 4432 that are sleeved and matched. The first rigid cylinder is sleeved outside the second rigid cylinder and is in sliding seal fit. The upper end of the first rigid cylinder is in sealed fit and is connected to the upper rigid support plate 441. The lower end of the second rigid cylinder is in sealed fit and is connected to the lower rigid support plate. When the relative positions of the two rigid support plates change, it can drive the first rigid cylinder and the second rigid cylinder to move. The elastic bladder 444 is connected to the lower end of the second rigid cylinder and is in communication with the inside of the second rigid cylinder. The elastic bladder 444 is made of rubber material. It should be noted that when the elastic bladder 444 is provided, the recognition camera 32 is arranged between the two rails 9.

[0031] Specifically, as a preferred implementation manner, antifreeze is filled in the elastic bladder 444 and the extrusion cavity 443. The volume change of the antifreeze due to thermal expansion is small when the surrounding temperature changes, so as to reduce the influence of the external temperature difference.

[0032] Specifically, the image processing method for the elastic bladder 444 is as follows: The image of the elastic bladder is collected from bottom to top by the acquisition camera, and then the image information is grayscale processed, binarized, and image filtered to obtain the edge contour information of the elastic bladder. Then the minimum circumscribed rectangle of the edge contour is obtained, and then the geometric dimensions of the minimum circumscribed rectangle are obtained. Then according to the formula: V = a*R 3 +b*R 2 , where V represents the volume of the elastic bladder, R represents the average value of the length and width dimensions of the circumscribed rectangle, and a and b are model coefficients. The value of a is 0.2153×10 -3, the value range of b is 0.02486, the unit of V is cubic millimeters, and the unit of R is millimeters.

[0033] Obviously, the above embodiments are merely examples for clear illustration and not limitations on the implementation manners. For those of ordinary skill in the art, other different forms of changes or variations can be made based on the above description. It is not necessary and impossible to enumerate all the implementation manners here. And the obvious changes or variations derived therefrom are still within the protection scope of the present invention.

Claims

1. A method for analyzing the deviation between theoretical and actual grade of mineral raw materials, characterized in that: The following steps are involved: Step 1: Obtain the average grade AG of each ore chute during a predetermined period of time n ; Step 2: Calculate the ore grade AG within the predetermined period of the mining area based on the average grade of each ore chute 总 .

2. A method for analyzing the deviation between theoretical and actual grade of mineral wool according to claim 1, characterized in that: In step 1, the average grade of each ore chute during the predetermined period is AG n The steps to obtain are: S10, obtaining a geological sampling position G at the ore chute exit point within a predetermined period of time; S11, obtaining the ore output W of the ore chute output point within a predetermined period of time; S12. Calculate the average grade of the ore chute during a predetermined period of time: AG n =(G1*W1*D1+ G2*W2*D2+…G m *W m *D m ) / (W1+W2+…W m ); In the formula, G m W is the geological sampling position of the ore chute within a predetermined time period. m D is the ore output within the predetermined time range of the ore chute. m It is the dilution rate of mining within a predetermined time period in the ore chute.

3. A method for analyzing the deviation between theoretical and actual grade of mineral wool according to claim 1, characterized in that: Calculate the ore grade AG within a predetermined period of time in the mining area 总 Including: S20, obtaining the number of ore cars C placed in each ore chute within a predetermined period of time f ; S21. Obtain the average grade AG of each ore chute in the mining area during a predetermined period of time n ; S22. Calculate the grade of the raw ore within the predetermined period of time in the mining area: AG 总 =(AG1*C1+AG2*+C2…+AG n *C f ) / (C1+ C2+…+ C f )。 4. A method for analyzing the deviation between theoretical and actual grade of ore according to claim 2, characterized in that: Obtaining the ore discharge volume W of the ore chute discharge point within a predetermined period of time includes the following steps: The weight information and the number of vehicles passing through the weight detection device within a predetermined time period are detected by a weight detection sensor; The ore output W within a predetermined time period is calculated based on the number and weight information of the vehicles.

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