Control method of dry sorting system, dry sorting system, and electronic device

Abstract

The application provides a control method of a dry separation system, the dry separation system and an electronic device, and comprises the following steps: acquiring a particle size distribution curve and a density distribution curve of a material by an X-ray detection device, and determining an average density of the material based on the density distribution curve of the material; calculating an operation parameter of a separation device based on the particle size distribution curve of the material, the density distribution curve of the material and the average density of the material; and controlling the separation device based on the operation parameter. The application can reduce the influence of fluctuations of the feeding amount, the feeding particle size and the gangue content of the feeding on the separation process.

Description

Technical Field

[0001] This invention relates to the field of coal sorting technology, and in particular to a control method for a dry sorting system, a dry sorting system, and electronic equipment. Background Technology

[0002] In the field of coal sorting, sorting equipment is typically used to separate coal. Traditional pneumatic shaking tables, lacking precise actuators, cannot adapt to fluctuations in the feed rate. During the sorting process, if the gangue content is high, the discharge width of the gangue product increases accordingly, and vice versa. Simultaneously, changes in the feed rate also significantly affect the distribution of the bed product. Therefore, in existing sorting processes, fluctuations in feed rate, feed particle size, and feed gangue content all impact the sorting process. Summary of the Invention

[0003] In view of this, the purpose of the present invention is to provide a control method for a dry sorting system, a dry sorting system and an electronic device, so as to reduce the impact of fluctuations in feed amount, feed particle size and feed gangue content on the sorting process.

[0004] To achieve the above objectives, the technical solutions adopted in the embodiments of the present invention are as follows:

[0005] In a first aspect, embodiments of the present invention provide a control method for a dry sorting system, comprising: acquiring the particle size distribution curve and density distribution curve of a material using an X-ray detection device, and determining the average density of the material based on the density distribution curve; calculating the operating parameters of the sorting equipment based on the particle size distribution curve, the density distribution curve, and the average density of the material; and controlling the sorting equipment based on the operating parameters.

[0006] In one embodiment, obtaining the particle size distribution curve and density distribution curve of a material using an X-ray detection device includes: obtaining the projected area of ​​the material as it passes through the X-ray detection device to obtain the particle size of the material, and the particle size distribution curve of the material passing through the X-ray detection device within a preset time period; obtaining the absorption rate of the material as it passes through the X-ray detection device, and obtaining the density distribution curve of the material passing through the X-ray detection device within a preset time period based on the absorption rate.

[0007] In one embodiment, the operating parameters of the sorting equipment are calculated based on the particle size distribution curve, density distribution curve, and average density of the material, including: determining the yield of the dominant particle size class based on the particle size distribution curve, and determining the particle size distribution range of the dominant particle size class based on the yield of the dominant particle size class; determining the density distribution of the dominant particle size class based on the particle size distribution range and density distribution curve of the material; determining the proportion of gangue in the dominant particle size class based on the gangue distribution density threshold and density distribution of the dominant particle size class; and calculating the operating parameters of the sorting equipment based on the feed rate of the sorting equipment, the proportion of gangue in the dominant particle size class, the average density of the material, and the particle size distribution range of the dominant particle size class.

[0008] In one embodiment, the operating parameters of the sorting equipment include at least: the rotational speed of the vibrating motor of the sorting equipment, the air pressure supplied to the sorting equipment, and the rotational speed of the discharge wheel of the sorting equipment; the operating parameters of the sorting equipment are calculated based on the feed rate, the proportion of gangue in the dominant particle size class, the average density of the material, and the particle size distribution range of the dominant particle size class, including: calculating the rotational speed of the vibrating motor of the sorting equipment based on the feed rate and the average density of the material; calculating the air pressure supplied to the sorting equipment based on the thickness of the material layer of the sorting equipment and the particle size distribution range of the dominant particle size class; and calculating the rotational speed of the discharge wheel of the sorting equipment based on the feed rate and the proportion of gangue in the dominant particle size class.

[0009] In one implementation, calculating the rotational speed of the vibrating motor of the sorting equipment based on the feed rate and average density of the sorting equipment includes: calculating the rotational speed of the vibrating motor of the sorting equipment according to the following formula:

[0010]

[0011] Where n0 represents the rotational speed of the vibratory motor, t represents the feed rate of the sorting equipment, K1 represents the speed correction coefficient, B represents the width of the equipment, H represents the thickness of the material layer, A represents the amplitude, δ represents the average density of the material, and α represents the tilt angle of the equipment.

[0012] In one embodiment, calculating the air supply pressure of the sorting equipment based on the particle size distribution range of the dominant particle size class according to the bed thickness of the sorting equipment includes: calculating the air supply pressure of the sorting equipment according to the following formula:

[0013] P max =δHg(1+D max / 100)

[0014] P min =δHg(1-D max / 100)

[0015] Among them, P max P represents the upper limit of the supply air pressure. minThis represents the lower limit of the supply air pressure, g represents the acceleration due to gravity, and D represents the acceleration due to gravity. max This indicates the upper limit of the particle size distribution range of the dominant particle size level, with the particle size unit being millimeters (mm).

[0016] In one implementation, calculating the rotational speed of the discharge wheel of the sorting equipment based on the feed rate and the proportion of gangue in the dominant particle size class includes: calculating the rotational speed of the discharge wheel of the sorting equipment according to the following formula:

[0017]

[0018] Where n1 represents the rotational speed of the discharge wheel, b represents the discharge constant, K2 represents the discharge coefficient, and r δ Indicates the proportion of gangue at the dominant particle size, r D This indicates the yield at the dominant particle size level.

[0019] Secondly, embodiments of the present invention provide a dry sorting system, including: a dry sorting device and a feedforward control device; wherein, the dry sorting device includes: a feeding device and a sorting device, and the feedforward control device includes: a detection module, a calculation module and a control module; the detection module is used to acquire the particle size distribution curve and density distribution curve of the material on the feeding device through an X-ray detection device, and determine the average density of the material based on the density distribution curve of the material; the calculation module is used to calculate the operating parameters of the sorting device based on the particle size distribution curve, the density distribution curve and the average density of the material; the control module is used to control the sorting device based on the operating parameters.

[0020] In one embodiment, the detection module is further configured to: obtain the projected area of ​​the material when it passes through the X-ray detection device, obtain the particle size of the material, and the particle size distribution curve of the material passing through the X-ray detection device within a preset time period; obtain the absorption rate of the material when it passes through the X-ray detection device, and obtain the density distribution curve of the material passing through the X-ray detection device within a preset time period based on the absorption rate.

[0021] Thirdly, embodiments of the present invention provide an electronic device including a processor and a memory, the memory storing computer-executable instructions executable by the processor, the processor executing the computer-executable instructions to implement the steps of any of the methods provided in the first aspect above.

[0022] Fourthly, embodiments of the present invention provide a computer-readable storage medium storing a computer program, which, when executed by a processor, performs the steps of the method provided in any of the first aspects above.

[0023] The embodiments of the present invention bring the following beneficial effects:

[0024] The control method, dry sorting system, and electronic equipment of the dry sorting system provided in this invention first obtain the particle size distribution curve and density distribution curve of the material using an X-ray detection device, and determine the average density of the material based on the density distribution curve; then, calculate the operating parameters of the sorting equipment based on the particle size distribution curve, density distribution curve, and average density; finally, control the sorting equipment based on the operating parameters. This method uses an X-ray detection device to detect the material and obtain its particle size and density distribution, and calculates the operating parameters of the sorting equipment based on the particle size distribution, density distribution, and feed rate, thereby controlling the discharge parameters of the sorting equipment. This reduces the impact of fluctuations in feed rate, feed particle size, and feed gangue content on the sorting process, and improves sorting accuracy.

[0025] Other features and advantages of the invention will be set forth in the description which follows, and will be apparent in part from the description, or may be learned by practicing the invention. The objects and other advantages of the invention are realized and obtained in accordance with the structures particularly pointed out in the description, claims and drawings.

[0026] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, preferred embodiments are described below in detail with reference to the accompanying drawings. Attached Figure Description

[0027] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0028] Figure 1 A flowchart of a control method for a dry sorting system provided in an embodiment of the present invention;

[0029] Figure 2 A schematic diagram of material detection provided in an embodiment of the present invention;

[0030] Figure 3 A schematic diagram of a particle size distribution curve provided in an embodiment of the present invention;

[0031] Figure 4 This is a schematic diagram of a dry sorting system provided in an embodiment of the present invention;

[0032] Figure 5 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention. Detailed Implementation

[0033] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0034] In the field of coal sorting, the existing product testing method is X-ray ash analyzer. Since coal is mostly composed of organic matter and gangue is mostly composed of inorganic matter, the absorption rate of organic matter and inorganic matter to X-rays is quite different. Therefore, the ash content of the product can be detected by measuring the absorption rate of X-rays to a certain thickness of the product. This method has a good tracking effect when the coal quality changes, but it cannot accurately detect the ash content of the product.

[0035] Currently, traditional pneumatic shaking tables, lacking precise actuators, cannot adapt to fluctuations in feed volume during the sorting process. If the gangue content is high, the discharge width of the gangue product increases accordingly, and vice versa. Furthermore, changes in feed volume significantly impact the distribution of the product on the bed. Therefore, in existing sorting processes, fluctuations in feed volume, particle size, and gangue content all affect the sorting process.

[0036] The intelligent tiered flow dry separator is a new type of dry separation equipment developed based on the separation mechanism of air jigging and gas-solid fluidized bed. It features intelligent detection, accurate identification, and can achieve stepless discharge from 0-100%. This equipment can quantitatively control the discharge of multi-stage products by detecting the feed rate and the content of organic and inorganic matter in the feed, thereby addressing the impact of fluctuations in feed rate, feed particle size, and feed gangue content on the separation process.

[0037] Based on this, the control method, dry sorting system and electronic equipment of the dry sorting system provided in the embodiments of the present invention can reduce the impact of fluctuations in feed amount, feed particle size and feed gangue content on the sorting process.

[0038] To facilitate understanding of this embodiment, a control method for a dry sorting system disclosed in this invention will first be described in detail. This method can be executed by an electronic device, such as a smartphone, computer, or iPad. See also Figure 1 The flowchart shown illustrates a control method for a dry sorting system, which mainly includes the following steps S101 to S103:

[0039] Step S101: Obtain the particle size distribution curve and density distribution curve of the material using an X-ray detection device, and determine the average density of the material based on the density distribution curve.

[0040] See Figure 2 The diagram illustrates a material detection method. The X-ray detection device includes an X-ray source and a linear array detector. Before feeding, the projected area and absorptivity of the material as it passes through the X-ray detection device can be obtained. Based on these parameters, the particle size distribution curve and density distribution curve of the material are determined, and the average density is calculated from the density curve. Specifically, the particle size distribution curve represents the relationship between particle size and yield, and the density distribution curve represents the relationship between density and yield. Yield refers to the percentage of material with a specific particle size or density.

[0041] Referring to the detection results of the linear array detector shown in Table 1, after the material passes through the X-ray detection device, the linear array detector can obtain a table showing the relationship between the particle size and yield, and between the density level and yield of the material. Based on this table, the particle size distribution curve and density distribution curve of the material can be obtained.

[0042] Table 1. Detection results of the linear array detector

[0043] Particle size / mm Yield / % <![CDATA[Density level g / cm 3 > Yield / % +50 #### -1.3 #### 50-25 #### 1.3-1.4 #### 25-13 #### 1.4-1.6 #### 13-6 #### 1.6-1.8 #### -6 #### +1.8 ####

[0044] Step S102: Calculate the operating parameters of the sorting equipment based on the particle size distribution curve, density distribution curve, and average density of the material.

[0045] Step S103: Control the sorting equipment based on operating parameters.

[0046] In one implementation, the particle size distribution range and density distribution of the dominant particle size class can be determined first based on the particle size distribution curve and density distribution curve of the material, and the proportion of gangue in the dominant particle size class can be determined. Then, the operating parameters of the sorting equipment are calculated based on the feed rate of the sorting equipment and the proportion of gangue in the dominant particle size class. The dominant particle size class refers to operating parameters including: the rotational speed of the vibrating motor of the sorting equipment, the air pressure supplied to the sorting equipment, and the rotational speed of the discharge wheel of the sorting equipment. Finally, the sorting equipment can be controlled according to the calculated operating parameters to control the discharge rate of the sorting equipment and achieve the optimal sorting effect.

[0047] The effective sorting particle size range of the sorting equipment is specific. Materials smaller or larger than the sorting particle size will cause ineffective sorting and affect the sorting effect. For example, materials smaller than the sorting particle size will not produce an effective stratification effect due to excessive fluidization. If the sorting equipment still maintains the original sorting parameters, the actual effective sorting ratio of gangue will decrease due to the change in the feed particle size. If the sorting equipment maintains the original discharge rate, the discharged gangue will inevitably contain clean coal, and the coal content in the gangue will increase, resulting in a decrease in the gangue discharge accuracy.

[0048] The control method of the dry sorting system provided in this embodiment of the invention uses an X-ray detection device to detect the material to obtain the particle size distribution and density distribution of the material, and calculates the operating parameters of the sorting equipment based on the particle size distribution, density distribution and feed amount, thereby controlling the discharge parameters of the sorting equipment, reducing the impact of fluctuations in feed amount, feed particle size and feed gangue content on the sorting process, and improving the sorting accuracy.

[0049] In one embodiment, for the aforementioned step S101, i.e., when obtaining the particle size distribution curve and density distribution curve of the material using an X-ray detection device, the following methods may be used, including but not limited to:

[0050] First, the projected area of ​​the material as it passes through the X-ray detection device is obtained, thus obtaining the particle size of the material and the particle size distribution curve of the material passing through the X-ray detection device within a preset time period.

[0051] In practical implementation, the projected area of ​​the material passing through the X-ray detection device can be obtained. This projected area is then converted into the diameter D of a circle of equal area. The particle size of the material is calculated based on the diameter D, and the particle size distribution curve of the material passing through the X-ray detection device within a preset time period is obtained. (See [reference needed]). Figure 3 As shown.

[0052] Then, the absorption rate of the material as it passes through the X-ray detection device is obtained, and the density distribution curve of the material passing through the X-ray detection device within a preset time period is obtained based on the absorption rate.

[0053] In practice, the absorption rate γ of the material as it passes through the X-ray detection device can be obtained. Then, the unit absorption rate γ / D can be calculated based on the absorption rate and the diameter of a circle with the same area. Finally, the density distribution curve and the average density δ of the material can be calculated based on the unit absorption rate.

[0054] In one embodiment, for the aforementioned step S102, i.e., when calculating the operating parameters of the sorting equipment based on the particle size distribution curve, density distribution curve, and average density of the material, the following methods can be used, mainly including steps 1 to 4:

[0055] Step 1: Determine the yield of the dominant particle size class based on the particle size distribution curve of the material, and determine the particle size distribution range of the dominant particle size class based on the yield of the dominant particle size class.

[0056] In specific implementation, it can be based on Figure 3 The integral area of ​​the particle size distribution curve of the material shown is defined as the yield r of the dominant particle size class. D r DThe value is taken as 40% to 90%, where r is the proportion of material within a certain particle size range in the total material being tested (i.e., yield); then, based on the yield r of the dominant particle size class... D The upper limit D of the dominant particle size class is determined by combining the particle size distribution curve of the material. max and particle size lower limit D min This involves determining the particle size distribution range. The upper limit D of the dominant particle size level is also considered. max and particle size lower limit D min This refers to the effective sorting particle size range of the sorting equipment.

[0057] Step 2: Determine the density distribution of the dominant particle size class based on the particle size distribution range of the dominant particle size class and the density distribution curve of the material.

[0058] In practical implementation, the upper limit of the granularity D of the dominant granularity level can be used as a reference. max Particle size lower limit D min The density distribution curve of the material is used to determine the density distribution of the dominant particle size.

[0059] Step 3: Determine the proportion of gangue at the dominant particle size level based on the gangue distribution density threshold and the density distribution at the dominant particle size level.

[0060] In practical implementation, the distribution density threshold δ of gangue can be predefined. f δ f The value range is 1.6 to 2.2, and the allocation density threshold δ f The determination is based on the intended use and actual needs of the materials to be sorted and the sorted products, and then on the distribution density threshold δ of the gangue. f The proportion r of gangue at the dominant particle size level is determined by the density distribution at the dominant particle size level. δ Since the sorting equipment can only effectively and precisely sort materials within the effective sorting particle size range, determining the proportion of gangue in the dominant particle size range (i.e., the effective sorting particle size range) allows for accurate adjustment of sorting parameters (including air pressure, vibration parameters, discharge rate, etc.), eliminating the amount of material in the ineffective sorting range, and directly obtaining the amount of gangue to be discharged. This, in turn, determines the rotational speed of the discharge wheel (the faster the wheel rotates, the faster the discharge speed and the larger the discharge rate).

[0061] Step 4: Calculate the operating parameters of the sorting equipment based on the feed rate of the sorting equipment, the proportion of gangue in the dominant particle size class, the average density of the material, and the particle size distribution range of the dominant particle size class.

[0062] In one embodiment, the operating parameters of the sorting equipment include at least: the rotational speed of the vibrating motor of the sorting equipment, the air supply pressure of the sorting equipment, and the rotational speed of the discharge wheel of the sorting equipment. The operating parameters of the sorting equipment can be calculated based on the feed rate, the proportion of gangue in the dominant particle size class, the average density of the material, and the particle size distribution range of the dominant particle size class, using methods including but not limited to the following:

[0063] First, the rotational speed of the vibrating motor of the sorting equipment is calculated based on the feed rate and average density of the material.

[0064] In practical implementation, the rotational speed of the vibratory motor of the sorting equipment can be calculated using the following formula:

[0065]

[0066] Where n0 represents the rotational speed of the vibratory motor, t represents the feed rate of the sorting equipment, which can be obtained from the belt scale of the feed conveyor, K1 represents the speed correction coefficient, with a value of 1.6 to 1.8, B represents the width of the equipment, and H represents the thickness of the material layer, which is 8 to 10 times the upper limit of particle size D. max A represents amplitude, δ represents the average density of the material, and α represents the tilt angle of the equipment.

[0067] Then, the air supply pressure of the sorting equipment is calculated based on the thickness of the material layer and the particle size distribution range of the dominant particle size class.

[0068] In practical implementation, the air supply pressure of the sorting equipment can be calculated according to the following formula:

[0069] P max =δHg(1+D max / 100)

[0070] P min =δHg(1-D max / 100)

[0071] Among them, P max P represents the upper limit of the supply air pressure. min This represents the lower limit of the supply air pressure, g represents the acceleration due to gravity, and D represents the acceleration due to gravity. max This represents the upper limit of the particle size distribution range of the dominant particle size level.

[0072] Finally, the rotational speed of the discharge wheel of the sorting equipment is calculated based on the feed rate and the proportion of gangue in the dominant particle size class.

[0073] In practical implementation, the rotational speed of the discharge wheel of the sorting equipment can be calculated using the following formula:

[0074]

[0075] Where n1 represents the rotational speed of the discharge wheel, b represents the discharge constant, which ranges from 0 to 3.2, and K2 represents the discharge coefficient, which ranges from 0.55 to 1.60.

[0076] The control method of the dry sorting system provided in this embodiment of the invention can positively set parameters such as the rotation speed of the vibrating motor, the air supply pressure, and the rotation speed of the discharge wheel of the sorting equipment by detecting the feed amount and the proportion of gangue in the dominant particle size class, so as to achieve the optimal sorting effect and reduce the impact of fluctuations in feed amount and gangue content on sorting indicators.

[0077] Regarding the control method for the aforementioned dry sorting system, this embodiment of the invention also provides a dry sorting system, see [link to relevant documentation]. Figure 4 The diagram shows a dry sorting system, which mainly includes a dry sorting device 10 and a feedforward control device 20. The dry sorting device 10 includes a feeding device 101 and a sorting device 102, and the feedforward control device 20 includes a detection module 201, a calculation module 202 and a control module 203.

[0078] The detection module 201 is used to acquire the particle size distribution curve and density distribution curve of the material on the feeding device through the X-ray detection device, and to determine the average density of the material based on the density distribution curve of the material.

[0079] The calculation module 202 is used to calculate the operating parameters of the sorting equipment based on the particle size distribution curve, density distribution curve and average density of the material.

[0080] Control module 203 is used to control the sorting equipment based on operating parameters.

[0081] The dry sorting system provided in this embodiment of the invention uses an X-ray detection device to detect the particle size distribution and density distribution of the material, and calculates the operating parameters of the sorting equipment based on the particle size distribution, density distribution and feed rate, thereby controlling the discharge parameters of the sorting equipment, reducing the impact of fluctuations in feed rate and gangue content on the sorting process, and improving sorting accuracy.

[0082] In one embodiment, the detection module 201 is further configured to: obtain the projected area of ​​the material when it passes through the X-ray detection device, obtain the particle size of the material, and the particle size distribution curve of the material passing through the X-ray detection device within a preset time period; obtain the absorption rate of the material when it passes through the X-ray detection device, and obtain the density distribution curve of the material passing through the X-ray detection device within a preset time period based on the absorption rate.

[0083] In one embodiment, the calculation module 202 is further configured to: determine the yield of the dominant particle size class based on the particle size distribution curve of the material, and determine the particle size distribution range of the dominant particle size class based on the yield of the dominant particle size class; determine the density distribution of the dominant particle size class based on the particle size distribution range of the dominant particle size class and the density distribution curve of the material; determine the proportion of gangue in the dominant particle size class based on the gangue distribution density threshold and the density distribution of the dominant particle size class; and calculate the operating parameters of the sorting equipment based on the feed rate of the sorting equipment, the proportion of gangue in the dominant particle size class, the average density of the material, and the particle size distribution range of the dominant particle size class.

[0084] In one embodiment, the operating parameters of the sorting equipment include at least: the rotational speed of the vibrating motor of the sorting equipment, the air supply pressure of the sorting equipment, and the rotational speed of the discharge wheel of the sorting equipment; the calculation module 202 is further used to: calculate the rotational speed of the vibrating motor of the sorting equipment based on the feed rate and the average density of the material; calculate the air supply pressure of the sorting equipment based on the thickness of the material layer and the particle size distribution range of the dominant particle size; and calculate the rotational speed of the discharge wheel of the sorting equipment based on the feed rate and the proportion of gangue in the dominant particle size.

[0085] In one embodiment, the calculation module 202 is further configured to: calculate the rotational speed of the vibratory motor of the sorting equipment according to the following formula:

[0086]

[0087] Where n0 represents the rotational speed of the vibratory motor, t represents the feed rate of the sorting equipment, K1 represents the speed correction coefficient, B represents the width of the equipment, H represents the thickness of the material layer, A represents the amplitude, δ represents the average density of the material, and α represents the tilt angle of the equipment.

[0088] In one embodiment, the calculation module 202 is further configured to: calculate the air supply pressure of the sorting equipment according to the following formula:

[0089] P max =δHg(1+D max / 100)

[0090] P min =δHg(1-D max / 100)

[0091] Among them, P max P represents the upper limit of the supply air pressure. min This represents the lower limit of the supply air pressure, g represents the acceleration due to gravity, and D represents the acceleration due to gravity. max This represents the upper limit of the particle size distribution range of the dominant particle size level.

[0092] In one embodiment, the calculation module 202 is further configured to: calculate the rotational speed of the discharge wheel of the sorting equipment according to the following formula:

[0093]

[0094] Where n1 represents the rotational speed of the discharge wheel, b represents the discharge constant, K2 represents the discharge coefficient, and r δ Indicates the proportion of gangue at the dominant particle size, r D This indicates the yield at the dominant particle size level.

[0095] The system provided in this embodiment of the invention has the same implementation principle and technical effects as the aforementioned method embodiment. For the sake of brevity, any parts not mentioned in the system embodiment can be referred to the corresponding content in the aforementioned method embodiment.

[0096] It should be noted that the specific values ​​provided in the implementation of this invention are merely illustrative and are not intended to be limiting.

[0097] This invention also provides an electronic device, specifically, the electronic device includes a processor and a storage device; the storage device stores a computer program, and the computer program, when run by the processor, executes the method described in any of the above embodiments.

[0098] Figure 5 The present invention provides a schematic diagram of the structure of an electronic device 100, which includes a processor 50, a memory 51, a bus 52 and a communication interface 53. The processor 50, the communication interface 53 and the memory 51 are connected through the bus 52. The processor 50 is used to execute executable modules, such as computer programs, stored in the memory 51.

[0099] The memory 51 may include high-speed random access memory (RAM) or non-volatile memory, such as at least one disk storage device. Communication between this system network element and at least one other network element is achieved through at least one communication interface 53 (which can be wired or wireless), such as the Internet, wide area network, local area network, metropolitan area network, etc.

[0100] Bus 52 can be an ISA bus, PCI bus, or EISA bus, etc. The bus can be divided into address bus, data bus, control bus, etc. For ease of representation, Figure 5 The symbol is represented by a single double-headed arrow, but this does not mean that there is only one bus or one type of bus.

[0101] The memory 51 is used to store programs. After receiving an execution instruction, the processor 50 executes the programs. The method executed by the device for defining the flow process disclosed in any of the foregoing embodiments of the present invention can be applied to the processor 50 or implemented by the processor 50.

[0102] Processor 50 may be an integrated circuit chip with signal processing capabilities. In implementation, each step of the above method can be completed by the integrated logic circuitry in the hardware of processor 50 or by instructions in software form. Processor 50 can be a general-purpose processor, including a Central Processing Unit (CPU), a Network Processor (NP), etc.; it can also be a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field-Programmable Gate Array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. It can implement or execute the methods, steps, and logic block diagrams disclosed in the embodiments of this invention. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the methods disclosed in the embodiments of this invention can be directly embodied in the execution of a hardware decoding processor, or executed by a combination of hardware and software modules in the decoding processor. The software modules can reside in random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, registers, or other mature storage media in the art. The storage medium is located in memory 51. The processor 50 reads the information in memory 51 and, in conjunction with its hardware, completes the steps of the above method.

[0103] The computer program product of the readable storage medium provided in the embodiments of the present invention includes a computer-readable storage medium storing program code. The instructions included in the program code can be used to execute the methods described in the foregoing method embodiments. For specific implementation, please refer to the foregoing method embodiments, which will not be repeated here.

[0104] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, essentially, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0105] Finally, it should be noted that the above-described embodiments are merely specific implementations of the present invention, used to illustrate the technical solutions of the present invention, and not to limit it. The scope of protection of the present invention is not limited thereto. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that any person skilled in the art can still modify or easily conceive of changes to the technical solutions described in the foregoing embodiments within the technical scope disclosed in the present invention, or make equivalent substitutions for some of the technical features; and these modifications, changes, or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be covered within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A control method for a dry sorting system, characterized in that, include: The particle size distribution curve and density distribution curve of the material are obtained by an X-ray detection device, and the average density of the material is determined based on the density distribution curve of the material. The operating parameters of the sorting equipment are calculated based on the particle size distribution curve, the density distribution curve, and the average density of the material. The sorting equipment is controlled based on the aforementioned operating parameters; The operating parameters of the sorting equipment are calculated based on the particle size distribution curve, density distribution curve, and average density of the material, including: determining the yield of the dominant particle size class based on the particle size distribution curve, and determining the particle size distribution range of the dominant particle size class based on the yield of the dominant particle size class; determining the density distribution of the dominant particle size class based on the particle size distribution range and the density distribution curve of the material; determining the proportion of gangue in the dominant particle size class based on the gangue distribution density threshold and the density distribution of the dominant particle size class; and calculating the operating parameters of the sorting equipment based on the feed rate of the sorting equipment, the proportion of gangue in the dominant particle size class, the average density of the material, and the particle size distribution range of the dominant particle size class. The operating parameters of the sorting equipment include at least: the rotational speed of the vibrating motor of the sorting equipment, the air pressure supplied by the sorting equipment, and the rotational speed of the discharge wheel of the sorting equipment. The operating parameters of the sorting equipment are calculated based on the feed rate, the proportion of gangue in the dominant particle size class, the average density of the material, and the particle size distribution range of the dominant particle size class, including: calculating the rotational speed of the vibrating motor of the sorting equipment based on the feed rate and the average density of the material; calculating the air pressure supplied by the sorting equipment based on the thickness of the material layer and the particle size distribution range of the dominant particle size class; and calculating the rotational speed of the discharge wheel of the sorting equipment based on the feed rate and the proportion of gangue in the dominant particle size class.

2. The control method according to claim 1, characterized in that, The particle size distribution curve and density distribution curve of the material are obtained using an X-ray detection device, including: The projected area of ​​the material as it passes through the X-ray detection device is obtained, and the particle size of the material is obtained, as well as the particle size distribution curve of the material passing through the X-ray detection device within a preset time period. The absorption rate of the material as it passes through the X-ray detection device is obtained, and the density distribution curve of the material passing through the X-ray detection device within a preset time period is obtained based on the absorption rate.

3. The control method according to claim 1, characterized in that, The rotational speed of the vibrating motor of the sorting equipment is calculated based on the feed rate and the average density of the sorting equipment, including: The rotational speed of the vibratory motor of the sorting equipment is calculated using the following formula: in, n 0 indicates the rotational speed of the vibratory motor. t This indicates the feed rate of the sorting equipment. K 1 represents the speed correction factor. B Indicates the width of the device. H Indicates the thickness of the material layer. A Indicates amplitude. δ Indicates the average density of the material. α Indicates the tilt angle of the equipment.

4. The control method according to claim 1, characterized in that, The air supply pressure of the sorting equipment is calculated based on the bed thickness and the particle size distribution range of the dominant particle size class, including: Calculate the air supply pressure of the sorting equipment using the following formula: P max = δHg （1+ D max / 100） P min = δHg （1- D max / 100） in, P max This indicates the upper limit of the air supply pressure. P min This indicates the lower limit of the supply air pressure. g Represents gravitational acceleration. D max This represents the upper limit of the particle size distribution range of the dominant particle size level.

5. The control method according to claim 1, characterized in that, The rotational speed of the discharge wheel of the sorting equipment is calculated based on the feed rate and the proportion of gangue in the dominant particle size class, including: The rotational speed of the discharge wheel of the sorting equipment is calculated using the following formula: in, n 1 indicates the rotational speed of the discharge wheel. b Indicates the discharge constant. K 2 represents the material discharge coefficient. r δ This indicates the proportion of gangue at the dominant particle size. r D This indicates the yield at the dominant particle size level.

6. A dry sorting system, characterized in that, The control method for implementing any one of claims 1 to 5 includes: a dry sorting device and a feedforward control device; wherein the dry sorting device includes: a feeding device and a sorting equipment, and the feedforward control device includes: a detection module, a calculation module and a control module; The detection module is used to obtain the particle size distribution curve and density distribution curve of the material on the feeding device through an X-ray detection device, and to determine the average density of the material based on the density distribution curve of the material. The calculation module is used to calculate the operating parameters of the sorting equipment based on the particle size distribution curve, the density distribution curve, and the average density of the material. The control module is used to control the sorting equipment based on the operating parameters.

7. The dry sorting system according to claim 6, characterized in that, The detection module is also used for: The projected area of ​​the material as it passes through the X-ray detection device is obtained, and the particle size of the material is obtained, as well as the particle size distribution curve of the material passing through the X-ray detection device within a preset time period. The absorption rate of the material as it passes through the X-ray detection device is obtained, and the density distribution curve of the material passing through the X-ray detection device within a preset time period is obtained based on the absorption rate.

8. An electronic device, characterized in that, The method includes a processor and a memory, the memory storing computer-executable instructions executable by the processor, the processor executing the computer-executable instructions to implement the steps of the method according to any one of claims 1 to 5.

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