Interference bed separator and control method

Abstract

The present application provides an interference bed separator and a control method. The separation area in the interference bed separator is divided into multiple interference bed layers by the density difference between the density characteristics of various separation minerals in the material to be separated. The deviation correction value of the fluid flow rate in each interference bed layer is determined according to the density characteristics of the separation minerals in each interference bed layer and the deviation characteristics of the fluid flow rate in the interference bed separator. When the separation mechanism in the interference bed separator uses the deviation correction value of each fluid flow rate to perform multi-layer mineral separation on the material to be separated, the fluid pressure in the interference bed separator is monitored in real time. The confidence interval of the fluid pressure in the interference bed separator is determined according to the gradient change characteristics of the fluid pressure obtained by monitoring and the deviation correction value of each fluid flow rate. The confidence interval of the fluid pressure is used to perform confidence adjustment on the material receiving rate of the feeding mechanism in the interference bed separator. Based on the above scheme, confidence adjustment of the material receiving rate in the interference bed separator can be achieved.

Description

Technical Field

[0001] The present application relates to the technical field of mining machinery and equipment, and more specifically, to an interference bed separator and a control method thereof. Background Art

[0002] Mining machinery and equipment are various equipment used for mineral mining, transportation, crushing, screening and processing of ores, and interference bed separators are a type of mining machinery and equipment used to separate mixed materials into different grades or components according to physical or chemical properties (such as density, particle size, magnetism, etc.). Interference bed separators are widely used in mining, agriculture, food processing, chemical industry and other fields. In the mining field, separators are mainly used for mineral beneficiation. Through gravity separation, flotation, magnetic separation and other methods, useful minerals are separated from gangue to improve the grade of ore.

[0003] During the interference bed sorting process, due to the differences in the characteristics of the material layers, the fluid flow is usually uneven, resulting in different levels of material being affected during sorting. The uneven fluid flow may cause some mineral layers to be over-separated, while other mineral layers cannot be effectively sorted, thus affecting the overall sorting accuracy. For example, the upper layer of material may be taken away prematurely due to the faster flow rate, while the heavier minerals may stay in the lower layer, failing to achieve the expected separation effect. This unbalanced fluid distribution makes it difficult for traditional sorting technology to accurately adjust the material processing parameters of each layer, making it impossible for the sorting machine to achieve the ideal sorting effect. Incomplete mineral separation may even cause blockage or fluid reflux, further affecting the overall efficiency of the sorting machine. Therefore, how to achieve confidence regulation of the material receiving rate in the interference bed sorting machine has become a difficult problem facing the industry. Summary of the Invention

[0004] The present application provides an interference bed separator and a control method, which can realize confidence regulation of the material receiving rate in the interference bed separator.

[0005] In a first aspect, the present application provides a control method for an interference bed separator, comprising:

[0006] After the mining materials are fed into the interference bed separator, the materials to be separated are received by the feeding mechanism of the interference bed separator;

[0007] Extract the density characteristics of various sorting minerals in the material to be sorted, divide the sorting area in the interference bed separator into multiple interference bed layers based on the density differences between the various density characteristics, and then determine the deviation correction value of the fluid flow rate in each interference bed layer during multi-layer mineral separation based on the density characteristics of the sorting minerals in each interference bed layer and the deviation characteristics of the fluid flow rate in the interference bed separator;

[0008] When the separation mechanism of the interference bed separator uses the deviation correction value of each fluid flow rate to perform multi-layer mineral separation on the material to be separated, the fluid pressure in the interference bed separator is monitored in real time, and the confidence interval of the fluid pressure in the interference bed separator is determined based on the gradient change characteristics of the fluid pressure obtained by monitoring and the deviation correction value of each fluid flow rate;

[0009] The confidence interval for the fluid pressure is used to make a confidence adjustment to the material receiving rate of the feed mechanism in the disturbed bed separator.

[0010] In some embodiments, extracting density characteristics of various sorting minerals in the material to be sorted specifically includes:

[0011] Obtain all types of separation minerals present in the material to be separated;

[0012] For various sorting minerals in the materials to be sorted, collect the physical property data of the sorting minerals;

[0013] The density characteristics of the sorted minerals are determined by the physical property data, and then the density characteristics of various sorted minerals in the material to be sorted are obtained.

[0014] In some embodiments, dividing the sorting area in the interference bed separator into a plurality of interference bed layers according to the density difference between the respective density features specifically comprises:

[0015] All the sorted minerals are layered according to the density mean in each density feature to obtain all the mineral separation beds;

[0016] Extracting the separation density distance between adjacent mineral separation beds from the density differences between the individual density features;

[0017] determining the thickness of each mineral separation bed based on each separation density distance;

[0018] The separation area in the interference bed separator is divided into a plurality of interference beds by the thickness of all mineral separation beds.

[0019] In some embodiments, determining the deviation correction value of the fluid flow rate in each interference bed layer during multi-layer mineral separation based on the density characteristics of the separated minerals in each interference bed layer and the deviation characteristics of the fluid flow rate in the interference bed separator specifically includes:

[0020] Extracting the deviation characteristics of fluid flow rate from the historical sorting records of the interference bed separator;

[0021] For each interference bed, the target fluid flow rate for separating the corresponding sorting minerals in the interference bed is determined according to the density characteristics of the sorting minerals in the interference bed;

[0022] The target fluid flow rate is compensated by the deviation characteristic to obtain a deviation correction value of the fluid flow rate in the interfering bed during multi-layer mineral separation, and further obtain a deviation correction value of the fluid flow rate in each interfering bed during multi-layer mineral separation.

[0023] In some embodiments, using the confidence interval of the fluid pressure to perform confidence adjustment on the material receiving rate of the feeding mechanism in the interference bed separator specifically includes:

[0024] Obtaining a mapping table of the relationship between fluid pressure and material separation rate in an interference bed separator;

[0025] For each interference bed layer of the interference bed separator, a confidence value of the fluid pressure in the interference bed layer is obtained from the confidence interval of the fluid pressure;

[0026] Obtaining the material sorting rate corresponding to the confidence value of the fluid pressure from the relationship mapping table as the sorting rate of the interference bed layer, and then obtaining the sorting rate of each interference bed layer in the interference bed separator;

[0027] A confidence value of the sorting rate of the interference bed separator is determined through all sorting rates, and the confidence value is then used to adjust the material receiving rate of the feeding mechanism in the interference bed separator.

[0028] In some embodiments, the interference bed separator is a mining machinery equipment based on hydraulic fluidized bed separation.

[0029] In some embodiments, the material to be separated includes minerals and gangue.

[0030] In a second aspect, the present application provides an interference bed separator, comprising a control unit, the control unit comprising:

[0031] An acquisition module is used to acquire the materials to be sorted received by the feeding mechanism in the interference bed separator after the mining materials are fed into the interference bed separator;

[0032] A processing module is used to extract the density characteristics of various sorting minerals in the material to be sorted, divide the sorting area in the interference bed separator into multiple interference bed layers according to the density differences between the various density characteristics, and then determine the deviation correction value of the fluid flow rate in each interference bed layer during multi-layer mineral separation based on the density characteristics of the sorting minerals in each interference bed layer and the deviation characteristics of the fluid flow rate in the interference bed separator;

[0033] The processing module is further configured to monitor the fluid pressure in the interference bed separator in real time when the separation mechanism in the interference bed separator uses the deviation correction values ​​of the flow rates of each fluid to perform multi-layer mineral separation on the material to be separated, and then determine a confidence interval of the fluid pressure in the interference bed separator based on the gradient variation characteristics of the fluid pressure obtained by monitoring and the deviation correction values ​​of the flow rates of each fluid;

[0034] An execution module is configured to perform confidence adjustment on a material receiving rate of a feed mechanism in a disturbed bed separator using the confidence interval of the fluid pressure.

[0035] In a third aspect, the present application provides a computer device comprising a memory and a processor, wherein the memory is used to store a computer program, and the processor is used to call and run the computer program from the memory, so that the computer device executes the above-mentioned control method of the interference bed sorting machine.

[0036] In a fourth aspect, the present application provides a computer-readable storage medium, in which instructions or codes are stored. When the instructions or codes are run on a computer, the computer implements the above-mentioned control method of the interference bed sorting machine when executing.

[0037] The technical solutions provided by the embodiments disclosed in this application have the following beneficial effects:

[0038] In an interference bed separator and control method provided by the present application, after mining materials are fed into the interference bed separator, the materials to be separated received by the feeding mechanism in the interference bed separator are obtained; the density characteristics of various separation minerals in the materials to be separated are extracted, and the separation area in the interference bed separator is divided into multiple interference bed layers according to the density differences between the density characteristics, and then the deviation correction values ​​of the fluid flow rates in each interference bed layer during multi-layer mineral separation are determined according to the density characteristics of the separation minerals in each interference bed layer and the deviation characteristics of the fluid flow rates in the interference bed separator; when the separation mechanism in the interference bed separator uses the deviation correction values ​​of each fluid flow rate to perform multi-layer mineral separation on the materials to be separated, the fluid pressure in the interference bed separator is monitored in real time, and then the confidence interval of the fluid pressure in the interference bed separator is determined according to the gradient change characteristics of the fluid pressure obtained by monitoring and the deviation correction values ​​of each fluid flow rate; the confidence interval of the fluid pressure is used to perform confidence adjustment on the material receiving rate of the feeding mechanism in the interference bed separator.

[0039] It can be seen that in this application, the confidence interval of the fluid pressure is used to perform confidence adjustment on the material receiving rate of the feeding mechanism in the interference bed separator; first, determining the deviation correction value of the fluid flow rate can accurately control the sinking and floating behavior of minerals in different density layers. In the mineral sorting process, due to the different density and fluid flow state of the minerals in each interference bed layer, the flow rate deviation may lead to uneven sorting. By extracting the density characteristics of the minerals in each layer and combining the deviation characteristics of the fluid flow rate, a deviation correction value can be assigned to each layer of minerals, thereby optimizing the matching of the fluid flow rate and the mineral layer, which helps the interference bed separator to adjust the fluid flow rate and ensure that the flow characteristics of different interference beds are reasonably controlled. , so that each layer of material is separated at the optimal flow rate. The precise flow rate adjustment not only improves the accuracy of mineral separation, but also helps to avoid sorting failure caused by too fast or too slow flow rate; then, the confidence interval of the fluid pressure reflects the fluctuation range of the fluid pressure under a certain confidence level, which helps the interference bed separator to identify whether the fluid pressure is in the normal range or whether there is abnormal fluctuation. If the fluid pressure exceeds the preset confidence interval, the interference bed separator can immediately adjust the material receiving rate to avoid instability or efficiency reduction in the sorting process due to too high or too low fluid pressure; in summary, based on the above scheme, the confidence adjustment of the material receiving rate in the interference bed separator can be realized. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0041] Figure 1 is an exemplary flow chart of a control method of an interference bed separator according to some embodiments of the present application;

[0042] Figure 2 is a control flow chart of an interference bed separator according to some embodiments of the present application;

[0043] Figure 3 is a schematic diagram of a process for implementing confidence adjustment according to some embodiments of the present application;

[0044] Figure 4 is a schematic structural diagram of a control unit according to some embodiments of the present application;

[0045] Figure 5 It is a structural diagram of a computer device for implementing a control method for an interference bed sorter according to some embodiments of the present application. DETAILED DESCRIPTION

[0046] In order to better understand the technical solution of the present application, the technical solution of the present application will be described in detail below with reference to the accompanying drawings and specific implementation methods.

[0047] refer to Figure 1 , which is an exemplary flow chart of a control method for an interference bed separator according to some embodiments of the present application. The control method for the interference bed separator mainly includes the following steps:

[0048] In step 101, after the mining materials are fed into the interference bed separator, the materials to be separated received by the feeding mechanism in the interference bed separator are obtained.

[0049] It should be noted that, in the present application, the interference bed sorter is a mining machinery and equipment based on hydraulic fluidized bed sorting; the materials to be sorted include minerals and gangue, wherein the minerals can be of multiple types; in specific implementation, after the mining materials are fed into the interference bed sorter, the mineral identification mechanism in the interference bed sorter is used to identify all the minerals and the remaining gangue in the mining materials, and the collection of all minerals and gangue can be used as the material to be sorted received by the feeding mechanism in the interference bed sorter.

[0050] In some embodiments, reference Figure 2 As described, the figure is a control flow chart of the interference bed sorting machine shown in some embodiments of the present application. The control system hardware of the interference bed sorting machine is composed of multiple key components, forming a highly integrated automatic control architecture, mainly including expert system controller, Siemens touch screen, Siemens PLC, servo motor, electric pinch valve, solenoid valve, differential pressure density meter, pressure transmitter, electromagnetic flowmeter and electric butterfly valve. The components realize real-time monitoring and precise control of the operating status of the sorting machine through electrical connection and data transmission, ensuring the efficiency and stability of the sorting process. The servo motor is connected to the forced discharge mechanism through a coupling, which is responsible for The discharge mechanism is driven to realize pulsed continuous discharge of tailings; the electric pinch valve and solenoid valve are connected to the underflow discharge port to control the discharge flow and pressure of the tailings; the electromagnetic flowmeter is installed on the vertical rising water pipeline to monitor the flow of rising water and ensure water flow stability; at the same time, the electric butterfly valve and pressure transmitter are installed on the horizontal rising water pipeline to adjust and monitor the pressure of rising water to ensure the fluid mechanics conditions during the sorting process. The entire system is logically controlled by Siemens PLC, and the expert system controller provides optimized control strategy. The Siemens touch screen serves as the human-computer interaction interface to realize parameter setting and real-time monitoring.

[0051] In step 102, the density characteristics of various sorting minerals in the material to be sorted are extracted, and the sorting area in the interference bed sorter is divided into multiple interference bed layers according to the density differences between the various density characteristics. Then, the deviation correction value of the fluid flow rate in each interference bed layer during multi-layer mineral separation is determined according to the density characteristics of the sorting minerals in each interference bed layer and the deviation characteristics of the fluid flow rate in the interference bed sorter.

[0052] In some embodiments, extracting the density characteristics of various sorting minerals in the material to be sorted can be achieved by using the following steps:

[0053] Obtain all types of separation minerals present in the material to be separated;

[0054] For various sorting minerals in the materials to be sorted, collect the physical property data of the sorting minerals;

[0055] The density characteristics of the sorted minerals are determined by the physical property data, and then the density characteristics of various sorted minerals in the material to be sorted are obtained.

[0056] In specific implementation, first, all types of sorted minerals existing in the material to be sorted are obtained, which can be achieved in the following manner, namely: all minerals in the material to be sorted are classified, and the classification results are used as all types of sorted minerals existing in the material to be sorted; then, for various sorted minerals in the material to be sorted, the physical property data of the sorted minerals are collected, which can be achieved in the following manner, namely: for various sorted minerals in the material to be sorted, the volume and weight of the sorted minerals can be measured in large quantities using the gas displacement method, and the collection of all volumes and weights can be used as the physical property data of the sorted minerals; finally, the density characteristics of the sorted minerals are determined by the physical property data, and then the density characteristics of various sorted minerals in the material to be sorted are obtained, which can be achieved in the following manner, namely: the ratio of the volume and weight of each group is calculated as the density of the sorted mineral, and the average of all densities can be used as the density characteristic of the sorted mineral. The density characteristics of various sorted minerals in the material to be sorted can be obtained in the above manner.

[0057] It should be noted that density characteristics represent the internal density characteristics of various sorted minerals; sorted minerals represent the types of minerals that need to be separated from the materials to be sorted; and physical property data represent data that describe the characteristics of the sorted minerals at the physical level.

[0058] In some embodiments, dividing the sorting area in the interference bed separator into multiple interference bed layers according to the density difference between the respective density features can be achieved by the following steps:

[0059] All the sorted minerals are layered according to the density mean in each density feature to obtain all the mineral separation beds;

[0060] Extracting the separation density distance between adjacent mineral separation beds from the density differences between the individual density features;

[0061] determining the thickness of each mineral separation bed based on each separation density distance;

[0062] The separation area in the interference bed separator is divided into a plurality of interference beds by the thickness of all mineral separation beds.

[0063] In the specific implementation, first, all the sorted minerals are layered according to the density mean in each density feature, and all the mineral separation beds can be obtained in the following way, that is, the density mean in each density feature can be sorted, and the sorted minerals corresponding to the density feature with the largest density mean are used as the bottom layer of the fluid in the sorting area, and the sorted minerals corresponding to the density feature with the smallest density mean are used as the top layer of the fluid in the sorting area, so that all the mineral separation beds can be obtained; secondly, the separation density distance between adjacent mineral separation beds is extracted from the density difference between each density feature, which can be implemented in the following way, that is, for every two density features, the absolute value of the difference between the two density features can be used as the density difference between the two density features. The density difference between every two density features can be obtained by the above method, and the density difference between each density feature can be obtained. For each group of adjacent mineral separation beds, the density difference between the density features of the sorted minerals in the adjacent mineral separation beds can be used as the separation density distance between the adjacent mineral separation beds. The separation density distance between each group of adjacent mineral separation beds can be obtained by the above method, and the separation density distance between adjacent mineral separation beds can be obtained.

[0064] Then, in the specific implementation, the thickness of each mineral separation bed is determined based on each separation density distance, which can be achieved in the following way, namely: for each mineral separation bed, the thickness of the mineral separation bed = (the ratio of the separation density distance of the mineral separation bed / the sum of all separation density distances) * the thickness of the fluid in the interference bed separator. The thickness of each mineral separation bed can be obtained in the above way; finally, the sorting area in the interference bed separator is divided into multiple interference beds according to the thickness of all mineral separation beds. The following way can be used, namely: each mineral separation bed after determining the thickness is used as each interference bed in the fluid of the sorting area, and multiple interference beds can be obtained.

[0065] It should be noted that in this application, the interference bed is the sorting area in the interference bed sorter responsible for separating minerals within a specific density range; the mineral separation bed represents the initial layered structure in the interference bed sorter; and the separation density distance represents the density difference between the mineral separation beds.

[0066] In some embodiments, the deviation correction value of the fluid flow rate in each interference bed layer during multi-layer mineral separation is determined based on the density characteristics of the separated minerals in each interference bed layer and the deviation characteristics of the fluid flow rate in the interference bed separator. The following steps can be used:

[0067] Extracting the deviation characteristics of fluid flow rate from the historical sorting records of the interference bed separator;

[0068] For each interference bed, the target fluid flow rate for separating the corresponding sorting minerals in the interference bed is determined according to the density characteristics of the sorting minerals in the interference bed;

[0069] The target fluid flow rate is compensated by the deviation characteristic to obtain a deviation correction value of the fluid flow rate in the interfering bed during multi-layer mineral separation, and further obtain a deviation correction value of the fluid flow rate in each interfering bed during multi-layer mineral separation.

[0070] In the specific implementation, first, the deviation characteristics of the fluid flow rate are extracted from the historical sorting records of the interference bed separator, which can be achieved in the following way, namely: all historical sorting records of the interference bed separator within a specified time period are collected, and the historical sorting records include the actual fluid flow rate and the input fluid flow rate. For each sorting process, the difference between the actual fluid flow rate and the input fluid flow rate in the historical sorting record of the sorting process can be used as the deviation value in the sorting process. The deviation value in each sorting process can be obtained by the above method, so that the average of all deviation values ​​can be used as the deviation characteristic of the fluid flow rate.

[0071] Then, in the specific implementation, for each interference bed, the target fluid flow rate for separating the corresponding sorted minerals in the interference bed is determined by the density characteristics of the sorted minerals in the interference bed, which can be achieved in the following way, namely: for each interference bed, a density-velocity relationship model based on the fluid mechanics formula is initialized, the density characteristics of the sorted minerals can be used as the mineral density parameter in the density-velocity relationship model, water can be used as the fluid in the density-velocity relationship model, and the average volume of the sorting is obtained from the operating instructions of the sorting machine as the mineral volume in the density-velocity relationship model, so that the density-velocity relationship model can be used to predict the fluid velocity required for separating the corresponding sorted minerals in the interference bed, and the result predicted by the density-velocity relationship model can be used as the target fluid flow rate for separating the corresponding sorted minerals in the interference bed.

[0072] Finally, in a specific implementation, the target fluid flow rate is compensated by the deviation characteristic to obtain the deviation correction value of the fluid flow rate in the interference bed during multi-layer mineral separation, and then the deviation correction value of the fluid flow rate in each interference bed during multi-layer mineral separation is obtained. This can be achieved in the following way, namely: the deviation characteristic can be used as the compensation amount for the target fluid flow rate, and the sum of the compensation amount and the target fluid flow rate can be used as the deviation correction value of the fluid flow rate in the interference bed during multi-layer mineral separation. The deviation correction value of the fluid flow rate in each interference bed during multi-layer mineral separation can be obtained in the above way.

[0073] It should be noted that in this application, the deviation correction value represents the fluid flow rate value corresponding to each interference bed layer in the interference bed sorter during the multi-layer mineral separation process; the deviation characteristic reflects the error characteristics of the fluid flow rate during the sorting process; the target fluid flow rate is the fluid flow rate used to ensure the mineral separation effect; the density-velocity relationship model.

[0074] In step 103, when the sorting mechanism in the interference bed separator uses the deviation correction values ​​of each fluid flow rate to perform multi-layer mineral separation on the material to be sorted, the fluid pressure in the interference bed separator is monitored in real time, and the confidence interval of the fluid pressure in the interference bed separator is determined based on the gradient change characteristics of the fluid pressure obtained by monitoring and the deviation correction values ​​of each fluid flow rate.

[0075] It should be noted that, in the present application, fluid pressure refers to the upward pressure exerted on the fluid in the interference bed separator, and the separation mechanism is a mechanism in the interference bed separator for separating different minerals; in specific implementation, the deviation correction value of each fluid flow rate is used as the multi-layer target flow rate input to the separation mechanism in the interference bed separator, so that when the interference bed separator is used to perform multi-layer mineral separation on the material to be separated, the fluid pressure in the interference bed separator is monitored in real time to obtain the fluid pressure in the interference bed separator every second.

[0076] In some embodiments, the confidence interval of the fluid pressure in the interference bed separator can be determined based on the monitored gradient variation characteristics of the fluid pressure and the deviation correction values ​​of the flow rates of each fluid by using the following steps:

[0077] Obtaining the flow rate influence factor of the fluid flow rate on the sorting effect of the interference bed separator and the pressure influence factor of the fluid pressure on the sorting effect of the interference bed separator;

[0078] For each interference bed layer, the influence deviation of the fluid flow velocity in the interference bed layer on the separation effect of the interference bed separator is determined by using the flow velocity influence factor and the deviation correction value of the fluid flow velocity in the interference bed layer;

[0079] Determining a pressure correction amount required to correct the deviation of the fluid pressure according to the influencing deviation and the pressure influencing factor;

[0080] Determining the gradient change characteristics of the fluid pressure by monitoring all the fluid pressures obtained;

[0081] determining a confidence value of the fluid pressure in the interference bed layer according to the gradient variation characteristics and the pressure correction amount, and then obtaining a confidence value of the fluid pressure in each interference bed layer;

[0082] A confidence interval for the fluid pressure in the disturbed bed separator is determined based on all confidence values.

[0083] In specific implementation, first, obtaining the flow rate influence factor of the fluid flow rate on the sorting effect of the interference bed separator and the pressure influence factor of the fluid pressure on the sorting effect of the interference bed separator can be achieved in the following manner, namely: the flow rate influence factor of the fluid flow rate on the sorting effect of the interference bed separator and the pressure influence factor of the fluid pressure on the sorting effect of the interference bed separator can be obtained from the control console of the interference bed separator, and the control console of the interference bed separator can update the flow rate influence factor and the pressure influence factor in real time by statistically analyzing the sorting effect in the historical separation records. The specific statistical analysis process will not be repeated here; secondly, for each interference bed layer, the deviation of the influence of the fluid flow rate in the interference bed layer on the sorting effect of the interference bed separator is determined by the flow rate influence factor and the deviation correction value of the fluid flow rate in the interference bed layer, which can be achieved in the following manner, namely: for each interference bed layer, the product of the flow rate influence factor and the deviation correction value of the fluid flow rate in the interference bed layer can be used as the deviation of the influence of the fluid flow rate in the interference bed layer on the sorting effect of the interference bed separator.

[0084] Then, in the specific implementation, the pressure correction amount of the fluid pressure that needs to be corrected according to the influence deviation and the pressure influence factor can be determined in the following manner, that is: the ratio of the influence deviation to the pressure influence factor can be used as the pressure correction amount of the fluid pressure that needs to be corrected; then, the gradient change characteristics of the fluid pressure are determined by monitoring all the fluid pressures obtained, which can be implemented in the following manner, that is: all the fluid pressures obtained by monitoring are obtained, and the absolute value of the difference between the fluid pressures at adjacent monitoring moments is used as the gradient value, and the average of all the gradient values ​​can be used as the gradient change characteristics of the fluid pressure.

[0085] Furthermore, in a specific implementation, the confidence value of the fluid pressure in the interference bed is determined according to the gradient change characteristics and the pressure correction amount, and then the confidence value of the fluid pressure in each interference bed is obtained. This can be achieved in the following manner, namely: constructing a multivariate regression model, combining the gradient change characteristics and the pressure correction amount, and calculating the confidence value of the fluid pressure in the interference bed, that is, confidence value = a*gradient change characteristics + b*pressure correction amount + c, wherein a, b, c are parameters of the multivariate regression model, which are obtained by training with historical operation data. The confidence value of the fluid pressure in each interference bed can be obtained by the above method; finally, determining the confidence interval of the fluid pressure in the interference bed separator based on all the confidence values ​​can be achieved in the following manner, namely: the set of all confidence values ​​can be used as the confidence interval of the fluid pressure in the interference bed separator.

[0086] It should be noted that, in this application, the confidence interval represents the reliability range of the fluid pressure; the flow rate influence factor represents the degree of influence of the fluid flow rate change on the sorting effect; the pressure influence factor represents the degree of influence of the fluid pressure change on the sorting effect; the influence deviation represents the influence of the fluid flow rate deviation on the sorting effect; the pressure correction amount represents the pressure adjustment value required to compensate for the sorting effect deviation; the gradient change characteristic represents the temporal change trend of the fluid pressure; and the confidence value is a parameter for measuring the accuracy of the fluid pressure.

[0087] In step 104, the confidence interval of the fluid pressure is used to perform confidence adjustment on the material receiving rate of the feed mechanism in the interference bed separator.

[0088] In some embodiments, the confidence interval of the fluid pressure is used to adjust the material receiving rate of the feed mechanism in the interference bed separator, referring to Figure 3 As described above, this figure is a schematic diagram of a process for implementing confidence adjustment in some embodiments of the present application. In this embodiment, confidence adjustment can be implemented using the following steps:

[0089] In step 1041, a mapping table of the relationship between fluid pressure and material separation rate in the interference bed separator is obtained;

[0090] In step 1042, for each interference bed layer of the interference bed separator, a confidence value of the fluid pressure in the interference bed layer is obtained from the confidence interval of the fluid pressure;

[0091] In step 1043, the material sorting rate corresponding to the confidence value of the fluid pressure is obtained from the relationship mapping table as the sorting rate of the interference bed layer, and then the sorting rate of each interference bed layer in the interference bed separator is obtained;

[0092] In step 1044, a confidence value of the sorting rate of the interference bed separator is determined through all sorting rates, and the confidence value is then used to adjust the material receiving rate of the feeding mechanism in the interference bed separator.

[0093] In specific implementation, first, obtaining the relationship mapping table between the fluid pressure and the material sorting rate in the interference bed separator can be achieved in the following manner, namely: the relationship mapping table between the fluid pressure and the material sorting rate in the interference bed separator can be obtained from the control console of the interference bed separator, and the control console of the interference bed separator can update the relationship mapping table in real time by statistically analyzing the relationship between the fluid pressure and the material sorting rate in the historical separation records. The specific statistical analysis process will not be repeated here; secondly, for each interference bed layer of the interference bed separator, the confidence value of the fluid pressure in the interference bed layer is obtained from the confidence interval of the fluid pressure; then, the confidence value of the fluid pressure in the interference bed layer is obtained from the confidence interval of the fluid pressure; then, the confidence value of the fluid pressure in the interference bed layer is obtained from the confidence interval of the fluid pressure; The material sorting rate corresponding to the confidence value of the fluid pressure obtained is used as the sorting rate of the interference bed layer. The sorting rate of each interference bed layer in the interference bed separator can be obtained in the above manner; finally, the confidence value of the sorting rate of the interference bed separator is determined by all the sorting rates, and then the confidence value is used to adjust the material receiving rate of the feeding mechanism in the interference bed separator. This can be achieved in the following manner, namely: the mode of all sorting rates can be used as the confidence value of the sorting rate of the interference bed separator, and the confidence value can be used as the material receiving rate of the feeding mechanism in the interference bed separator, thereby completing the confidence adjustment of the material receiving rate in the feeding mechanism of the interference bed separator.

[0094] In addition, in another aspect of the present application, in some embodiments, the present application provides an interference bed separator, the interference bed separator includes a control unit, reference Figure 4 , which is a schematic diagram of the structure of a control unit according to some embodiments of the present application. The control unit includes: an acquisition module 201, a processing module 202 and an execution module 203, which are described as follows:

[0095] The acquisition module 201 in this application is mainly used to obtain the material to be sorted received by the feeding mechanism in the interference bed separator after the mining material is fed into the interference bed separator;

[0096] Processing module 202, in this application, is used to extract density characteristics of various sorting minerals in the material to be sorted, divide the sorting area in the interference bed separator into multiple interference bed layers based on the density differences between the various density characteristics, and then determine the deviation correction value of the fluid flow rate in each interference bed layer during multi-layer mineral separation based on the density characteristics of the sorting minerals in each interference bed layer and the deviation characteristics of the fluid flow rate in the interference bed separator;

[0097] It should be noted that the processing module 202 is further configured to monitor the fluid pressure in the interference bed separator in real time when the separation mechanism in the interference bed separator uses the deviation correction values ​​of the flow rates of each fluid to perform multi-layer mineral separation on the material to be separated, and then determine the confidence interval of the fluid pressure in the interference bed separator based on the gradient change characteristics of the fluid pressure obtained by monitoring and the deviation correction values ​​of the flow rates of each fluid;

[0098] The execution module 203 in this application is mainly used to use the confidence interval of the fluid pressure to perform confidence adjustment on the material receiving rate of the feeding mechanism in the interference bed separator.

[0099] The above describes in detail the examples of the interference bed sorting machine and control method provided by the embodiments of the present application. It can be understood that in order to realize the above functions, the corresponding device includes hardware structures and / or software modules corresponding to the execution of each function. It should be easy for those skilled in the art to realize that, in combination with the units and algorithm steps of each example described in the embodiments disclosed herein, the present application can be implemented in the form of hardware or a combination of hardware and computer software. Whether a function is executed in the form of hardware or computer software driving hardware depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0100] In some embodiments, the present application also provides a computer device, which includes a memory and a processor, the memory is used to store computer programs, and the processor is used to call and run the computer programs from the memory, so that the computer device executes the above-mentioned control method of the interference bed sorting machine.

[0101] In some embodiments, reference Figure 5 , the dotted line in the figure indicates that the unit or module is optional. The figure is a structural diagram of a computer device for implementing a control method for an interference bed separator according to an embodiment of the present application. The control method for an interference bed separator described in the above embodiment can be achieved by Figure 5 The computer device shown in the figure is implemented, and the computer device includes at least one processor 301, a memory 302 and at least one communication unit 305. The computer device can be a terminal device, a server or a chip.

[0102] The processor 301 may be a general-purpose processor or a dedicated processor. For example, the processor 301 may be a central processing unit (CPU), which may be used to control the computer device, execute software programs, and process data from the software programs. The computer device may also include a communication unit 305 for inputting (receiving) and outputting (transmitting) signals.

[0103] For example, the computer device may be a chip, the communication unit 305 may be an input and / or output circuit of the chip, or the communication unit 305 may be a communication interface of the chip, and the chip may be a component of a terminal device, a network device, or other device.

[0104] For another example, the computer device may be a terminal device or a server, and the communication unit 305 may be a transceiver of the terminal device or the server, or the communication unit 305 may be a transceiver circuit of the terminal device or the server.

[0105] The computer device may include one or more memories 302, on which a program 304 is stored. The program 304 can be executed by the processor 301 to generate instructions 303, so that the processor 301 executes the method described in the above method embodiment according to the instructions 303. Optionally, data (such as a target audit model) can also be stored in the memory 302. Optionally, the processor 301 can also read data stored in the memory 302. The data can be stored at the same storage address as the program 304, or at a different storage address from the program 304.

[0106] The processor 301 and the memory 302 may be provided separately or integrated together, for example, integrated on a system on chip (SOC) of a terminal device.

[0107] It should be understood that each step of the above method embodiment can be completed by a hardware-based logic circuit or software-based instructions in the processor 301. The processor 301 can be a CPU, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field programmable gate array (FPGA), or other programmable logic devices, such as discrete gates, transistor logic devices, or discrete hardware components.

[0108] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware. Furthermore, the present application may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0109] For example, in some embodiments, the present application also provides a computer-readable storage medium, in which instructions or codes are stored. When the instructions or codes are run on a computer, the computer implements the above-mentioned control method of the interference bed sorting machine when executing.

[0110] Although the preferred embodiments of the present application have been described, those skilled in the art may make additional changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present application.

[0111] Obviously, those skilled in the art may make various changes and modifications to this application without departing from the spirit and scope of this application. Thus, if these modifications and variations of this application fall within the scope of the claims of this application and their equivalents, this application is intended to include these modifications and variations.

Claims

1. A control method for an interference bed separator, wherein the interference bed separator comprises a feeding mechanism and a separating mechanism, wherein: The steps include: After the mining materials are fed into the interference bed separator, the materials to be separated are received by the feeding mechanism of the interference bed separator; Extract the density characteristics of various sorting minerals in the material to be sorted, divide the sorting area in the interference bed separator into multiple interference bed layers based on the density differences between the various density characteristics, and then determine the deviation correction value of the fluid flow rate in each interference bed layer during multi-layer mineral separation based on the density characteristics of the sorting minerals in each interference bed layer and the deviation characteristics of the fluid flow rate in the interference bed separator; When the separation mechanism of the interference bed separator uses the deviation correction value of each fluid flow rate to perform multi-layer mineral separation on the material to be separated, the fluid pressure in the interference bed separator is monitored in real time, and the confidence interval of the fluid pressure in the interference bed separator is determined based on the gradient change characteristics of the fluid pressure obtained by monitoring and the deviation correction value of each fluid flow rate; The confidence interval for the fluid pressure is used to make a confidence adjustment to the material receiving rate of the feed mechanism in the disturbed bed separator.

2. The method according to claim 1, wherein Extracting the density characteristics of various sorting minerals in the material to be sorted specifically includes: Obtain all types of separation minerals present in the material to be separated; For various sorting minerals in the materials to be sorted, collect the physical property data of the sorting minerals; The density characteristics of the sorted minerals are determined by the physical property data, and then the density characteristics of various sorted minerals in the material to be sorted are obtained.

3. The method according to claim 1, wherein The separation area in the interference bed separator is divided into multiple interference bed layers by the density difference between each density feature, specifically including: All the sorted minerals are layered according to the density mean in each density feature to obtain all the mineral separation beds; Extracting the separation density distance between adjacent mineral separation beds from the density differences between the individual density features; determining the thickness of each mineral separation bed based on each separation density distance; The separation area in the interference bed separator is divided into a plurality of interference beds by the thickness of all mineral separation beds.

4. The method according to claim 1, wherein According to the density characteristics of the minerals to be separated in each interference bed layer and the deviation characteristics of the fluid flow rate in the interference bed separator, the deviation correction value of the fluid flow rate in each interference bed layer during multi-layer mineral separation is determined, specifically including: Extracting the deviation characteristics of fluid flow rate from the historical sorting records of the interference bed separator; For each interference bed, the target fluid flow rate for separating the corresponding sorting minerals in the interference bed is determined according to the density characteristics of the sorting minerals in the interference bed; The target fluid flow rate is compensated by the deviation characteristic to obtain a deviation correction value of the fluid flow rate in the interfering bed during multi-layer mineral separation, and further obtain a deviation correction value of the fluid flow rate in each interfering bed during multi-layer mineral separation.

5. The method according to claim 1, wherein The confidence adjustment of the material receiving rate of the feeding mechanism in the interference bed separator using the confidence interval of the fluid pressure specifically includes: Obtaining a mapping table of the relationship between fluid pressure and material separation rate in an interference bed separator; For each interference bed layer of the interference bed separator, a confidence value of the fluid pressure in the interference bed layer is obtained from the confidence interval of the fluid pressure; Obtaining the material sorting rate corresponding to the confidence value of the fluid pressure from the relationship mapping table as the sorting rate of the interference bed layer, and then obtaining the sorting rate of each interference bed layer in the interference bed separator; A confidence value of the sorting rate of the interference bed separator is determined through all sorting rates, and the confidence value is then used to adjust the material receiving rate of the feeding mechanism in the interference bed separator.

6. The method according to claim 1, wherein The interference bed separator is a mining machinery equipment based on hydraulic fluidized bed separation.

7. The method according to claim 1, wherein The materials to be separated include minerals and gangue.

8. An interference bed separator, comprising a control unit, characterized in that: The control unit comprises: An acquisition module is used to acquire the materials to be sorted received by the feeding mechanism in the interference bed separator after the mining materials are fed into the interference bed separator; A processing module is used to extract the density characteristics of various sorting minerals in the material to be sorted, divide the sorting area in the interference bed separator into multiple interference bed layers according to the density differences between the various density characteristics, and then determine the deviation correction value of the fluid flow rate in each interference bed layer during multi-layer mineral separation based on the density characteristics of the sorting minerals in each interference bed layer and the deviation characteristics of the fluid flow rate in the interference bed separator; The processing module is further configured to monitor the fluid pressure in the interference bed separator in real time when the separation mechanism in the interference bed separator uses the deviation correction values ​​of the flow rates of each fluid to perform multi-layer mineral separation on the material to be separated, and then determine a confidence interval of the fluid pressure in the interference bed separator based on the gradient variation characteristics of the fluid pressure obtained by monitoring and the deviation correction values ​​of the flow rates of each fluid; An execution module is configured to perform confidence adjustment on a material receiving rate of a feed mechanism in a disturbed bed separator using the confidence interval of the fluid pressure.

9. A computer device, characterized in that: The computer device includes a memory and a processor, the memory is used to store a computer program, and the processor is used to call and run the computer program from the memory, so that the computer device executes the control method of the interference bed separator according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium stores instructions or codes, which, when executed on a computer, enable the computer to implement the control method for the interference bed separator according to any one of claims 1 to 7.

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