A control method and system for the loading material pile of a coal silo

Abstract

The present invention provides a method and system for controlling the loading material pile of a coal silo, which relates to the technical field of material transportation. A method for controlling the loading material pile of a coal silo includes the following steps: S1. Obtain vehicle model data and determine whether the vehicle is a long-hopper vehicle model. If so, proceed to step S2; otherwise, proceed to step S5; S2. Obtain the empirical values of the loading weights of different material piles for manual loading of the long-hopper vehicle model; S3. Construct a dynamic calculation model, and use the empirical values of the loading weights of different material piles and the data of the long-hopper vehicle model to train the dynamic calculation model to obtain the trained dynamic calculation model; S4. Use the trained dynamic calculation model to calculate the loading weights of different material piles of the long-hopper vehicle model; S5. Allocate the material pile weights for non-long-hopper vehicle models according to the actual empirical values. The present invention has the advantages of increasing the practicability of the system, being able to detect the system status in real time, having universality, and achieving smooth loading without material scattering.

Description

Technical Field

[0001] The present invention relates to the technical field of material transportation, and more particularly, to a method and system for controlling the loading pile of a coal silo for loading trucks. Background Art

[0002] In coal mines, coal washing enterprises, and sand factories, it is often necessary to load bulk powder materials on the ground. Usually, trucks are used to transport the bulk materials. In order to move the bulk materials into the truck carriage, loading equipment is required for loading.

[0003] In the existing material loading process, it is necessary to manually command and remind workers and drivers to cooperate in loading in real time; the existing quantitative loading system on the market has a single function and cannot reflect the system situation in time; the real-time information of material loading cannot be dynamically monitored, and there are many problems such as loading overflow and overloading. This manual loading mode requires repeated loading and metering, which not only has a large error and takes a long time, but also is prone to omissions. The labor cost is high, the loading process is cumbersome, and when calculation errors occur, workers are prone to spill materials during the loading process. Summary of the Invention

[0004] The purpose of the present invention is to provide a method and system for controlling the loading pile of a coal silo for loading trucks, which can reduce labor costs, reduce the loading time, have a small loading error, and have a flat loading without spilling materials.

[0005] The present invention is implemented as follows:

[0006] In a first aspect, the present application provides a method for controlling the loading pile of a coal silo for loading trucks, including the following steps:

[0007] S1. Obtain vehicle model data, and determine whether the vehicle is a long-hopper vehicle model. If so, proceed to step S2; otherwise, proceed to step S5;

[0008] S2. Obtain the empirical values of the loading weights of different loading piles for manual loading of the long-hopper vehicle model;

[0009] S3. Construct a dynamic calculation model, and use the empirical values of the loading weights of different loading piles and the data of the long-hopper vehicle model to train the dynamic calculation model to obtain a trained dynamic calculation model;

[0010] S4. Use the trained dynamic calculation model to calculate the loading weights of different loading piles of the long-hopper vehicle model;

[0011] S5. Allocate the loading pile weights for non-long-hopper vehicle models according to the actual empirical values.

[0012] Further, the basis for determining whether the vehicle is a long-hopper vehicle model in step S1 includes the following steps:

[0013] S1-1. Use a camera to obtain vehicle model data;

[0014] S1-2. Define the truck bed shape with a length greater than 9 meters and a depth less than 2 meters as the long-bed truck type, and the remaining truck types as non-long-bed truck types.

[0015] Further, step S3 includes the following sub-steps:

[0016] S3-1. Obtain the estimated net loading weight value t of the long-bed truck type based on the data of the long-bed truck type; and obtain the number of loading material piles n according to the empirical values of the loading weights of different material piles.

[0017] S3-2. Calculate the predicted weight value t of the intermediate material pile based on the estimated net loading weight value t and the number of loading material piles n. 中预 ; where, t 中预 = t / n;

[0018] S3-3. Set the deviation value t of the first material pile. 首偏 Based on the deviation value t of the first pile, 首偏 and the predicted weight value t of the intermediate material pile, 中预 calculate the weight t of the first material pile. 首堆 ; where, t 首堆 = t 首偏 + t 中预 ;

[0019] S3-4. Set the deviation value t of the last material pile. 尾偏 Based on the deviation value t of the last material pile, 尾偏 and the predicted weight value t of the intermediate material pile, 中预 calculate the weight t of the last material pile. 尾堆 ; where, t 尾堆 = t 中预 - t 尾偏 ;

[0020] S3-5. Calculate the weight value t of the intermediate material pile based on the weight t of the last material pile 尾堆 and the weight t of the first material pile. 首堆 ; where, t 中 =(t - t 中 - t 首堆 - t 尾堆 ) / (n - 2);

[0021] S3-6. Repeat steps S3-1 to S3-5, and adjust the deviation value t of the first material pile 首偏 , the deviation value t of the last material pile 尾偏 , and the number of loading material piles n until the loading accuracy rate of the long-bed truck type reaches the set threshold to obtain the trained dynamic calculation model.

[0022] Further, step S5 includes the following steps:

[0023] S5-1. Obtain the specific vehicle model of non-long-hopper vehicle types;

[0024] S5-2. For the specific vehicle model of non-long-hopper vehicle types, obtain the number of loading piles and the weight of each pile and record them;

[0025] S5-3. Repeat steps S5-1 to S5-2 until the common vehicle models of non-long-hopper vehicle types are recorded to obtain a loading file;

[0026] S5-4. Allocate the pile weight for non-long-hopper vehicle types according to the loading file.

[0027] In a second aspect, the present application provides a coal silo loading pile control system, including a data acquisition module, a control module, a dynamic calculation model, and a static allocation module;

[0028] The data acquisition module is used to obtain vehicle model data, determine whether the vehicle is a long-hopper vehicle type, obtain the empirical values of the loading weights of different piles for manual loading of long-hopper vehicle types; obtain the empirical values of the loading weights of different piles for manual loading of non-long-hopper vehicle types; wherein, the data acquisition module includes a camera;

[0029] The dynamic calculation model is used to calculate the loading weights of different piles for long-hopper vehicle types by the model;

[0030] The static allocation module is used to record the number of loading piles and the weight of each pile for non-long-hopper vehicle types according to experience;

[0031] The control module is used to control the pile loading according to the number of loading piles and the weight of each pile obtained by the dynamic calculation model and the static allocation module, enable communication between each module, perform self-check on the system, and send the system status and loading status to the management personnel.

[0032] In a third aspect, the present application provides an electronic device, which includes a memory for storing one or more programs; a processor; when the above one or more programs are executed by the above processor, the method described in any item of the first aspect is implemented.

[0033] In a fourth aspect, the present application provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the method described in any item of the first aspect is implemented.

[0034] Compared with the prior art, the present invention has at least the following advantages or beneficial effects:

[0035] The present invention provides a method and system for controlling the loading material pile in a coal silo. By classifying different vehicle types and adopting different loading methods, it can accurately load different vehicle types, increasing the practicality of the system. A control module is added to detect the system status in real time and provide timely feedback in case of emergencies. Static allocation is introduced to combine existing experience and propose solutions for vehicle types that cannot be quantified, making it universal. Moreover, the material pile allocation reaches the optimal state, and the loading is flat without spilling materials. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of the present invention and should not be regarded as limiting the scope. For those of ordinary skill in the art, other related drawings can be obtained based on these drawings without creative efforts.

[0037] Figure 1 It is a flowchart of the present invention;

[0038] Figure 2 It is a specific flowchart for constructing and training a dynamic calculation model in an embodiment of the present invention;

[0039] Figure 3 It is a specific flowchart for allocating the weight of the material pile to non-long-hopper vehicle types in an embodiment of the present invention;

[0040] Figure 4 It is a structural block diagram of the present invention;

[0041] Figure 5 It is a structural block diagram of an electronic device provided by an embodiment of the present invention.

[0042] Reference Signs: 101, memory; 102, processor; 103, communication interface. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0043] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions in the embodiments of this application will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of this application. Obviously, the described embodiments are some, but not all, of the embodiments of this application. The components of the embodiments of this application usually described and illustrated in the drawings here can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of this application provided in the drawings is not intended to limit the scope of the claimed application, but merely represents selected embodiments of this application. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of this application without creative efforts fall within the scope of protection of this application. The following will describe in detail some implementation manners of this application in conjunction with the drawings. Without conflict, the following various embodiments and the various features in the embodiments can be combined with each other. Embodiment

[0044] Please refer to Figure 1 , the method for controlling the loading material pile of a coal silo includes the following steps:

[0045] S1. Obtain vehicle model data, and determine whether the vehicle is a long-hopper vehicle model. If so, proceed to step S2; otherwise, proceed to step S5;

[0046] The basis for determining whether the vehicle is a long-hopper vehicle model in step S1 includes the following steps:

[0047] S1-1. Use a camera to obtain vehicle model data;

[0048] S1-2. Consider a hopper shape with a hopper length greater than 9 meters and a hopper depth less than 2 meters as a long-hopper vehicle model, and consider the remaining vehicle models as non-long-hopper vehicle models.

[0049] Exemplarily, in manual loading, classified by hopper shape, a hopper with a length > 9 meters and a depth less than 2 meters is classified as a long-hopper vehicle model. A hopper with a length less than 9 meters and a depth greater than 2 meters is classified as a short and deep hopper. According to the existing manual loading experience, the short and deep hopper distributes the weight of the material pile. Distinguishing vehicle models helps to achieve precise loading for different vehicle models and improve the practicality of the system.

[0050] S2. Obtain the empirical values of the loading weights of different material piles for manual loading of long-hopper vehicle models;

[0051] S3. Build a dynamic calculation model, and use the empirical values of the loading weights of different material piles and the data of long-hopper vehicle models to train the dynamic calculation model to obtain the trained dynamic calculation model;

[0052] Please refer to Figure 2 , step S3 includes the following sub-steps:

[0053] S3-1. Obtain the predicted net loading weight value t of the long hopper vehicle type based on the data of the long hopper vehicle type; and obtain the number of loading material piles n according to the empirical values of the loading weights of different material piles.

[0054] S3-2. Calculate the predicted value t of the intermediate material pile weight based on the predicted net loading weight value t and the number of loading material piles n. 中预 ; where, t 中预 = t / n;

[0055] S3-3. Set the deviation value t of the first material pile. 首偏 , and calculate the weight t of the first material pile according to the deviation value t of the first pile 首偏 and the predicted value t of the intermediate material pile weight 中预 ; where, t 首堆 = t 首堆 + t 首偏 ; 中预 ;

[0056] S3-4. Set the deviation value t of the last material pile. 尾偏 , and calculate the weight t of the last material pile according to the deviation value t of the last pile 尾偏 and the predicted value t of the intermediate material pile weight 中预 ; where, t 尾堆 = t 尾堆 - t 中预 - t 尾偏 ;

[0057] S3-5. Calculate the weight value t of the intermediate material pile according to the weight t of the last material pile 尾堆 and the weight t of the first material pile 首堆 ; where, t 中 =(t - t 中 - t 首堆 - t 尾堆 ) / (n - 2);

[0058] S3-6. Repeat steps S3-1 to S3-5, and adjust the deviation value t of the first material pile 首偏 , the deviation value t of the last material pile 尾偏 , and the number of loading material piles n until the loading accuracy rate of the long hopper vehicle type reaches the set threshold, and obtain the trained dynamic calculation model.

[0059] Exemplarily, by calculating the parameters of the long hopper vehicle type, fixing the parameters of the deviation value t of the first material pile 首偏 and the deviation value t of the last material pile 尾偏 , the loading requirements of different models of long hopper vehicles can be met by adjusting the net loading weight and the number of material piles. Each long hopper vehicle is loaded according to the corresponding loading weight value, and the effect of no material spillage from the material pile can be achieved.

[0060] S4. Use the trained dynamic calculation model to calculate the loading weights of different material piles for long-hopper vehicle models;

[0061] S5. Allocate the material pile weights for non-long-hopper vehicle models according to actual experience values.

[0062] Please refer to Figure 3 , and step S5 includes the following steps:

[0063] S5-1. Obtain the specific vehicle model of the non-long-hopper vehicle model;

[0064] S5-2. Obtain the number of loading material piles and the weight of each material pile for the specific vehicle model of the non-long-hopper vehicle model and record them;

[0065] S5-3. Repeat steps S5-1 to S5-2 until the common vehicle models of the non-long-hopper vehicle model are recorded to obtain a loading file;

[0066] S5-4. Allocate the material pile weights for the non-long-hopper vehicle model according to the loading file.

[0067] Exemplarily, for special vehicle models that are difficult to calculate, such as container vehicle models, the dynamic calculation method is not suitable, and the static allocation method is selected. For example, for a container truck hopper, the hopper depth is 2.6 meters and the hopper length is 6 meters. The number of manually loaded piles is 4 piles, the weight of the first pile is 19 tons, the second pile is 4.2 tons, the third pile is 4.1 tons, and the fourth pile is 3 tons. The data can be directly entered into the vehicle model file for loading, and the parameter values can be fixed after adjustment and optimization according to the actual situation.

[0068] When the vehicle enters the station, the system automatically identifies the vehicle type, selects different loading methods according to the vehicle data, calculates the loading weight value of each material pile for the long-hopper vehicle model using the dynamic calculation model, differentiates the loading material piles for the vehicle models that are difficult to calculate using experience values, and fixes the experience values, which can realize unmanned loading for multiple vehicle models and improve efficiency.

[0069] Based on the same inventive concept, please refer to Figure 4 , the present invention also provides a control system for loading material piles in a coal silo, including a data acquisition module, a control module, a dynamic calculation model, and a static allocation module;

[0070] The data acquisition module is used to acquire vehicle model data, determine whether the vehicle is a long-hopper vehicle model, acquire the experience values of the loading weights of different material piles for manual loading of the long-hopper vehicle model; acquire the experience values of the loading weights of different material piles for manual loading of the non-long-hopper vehicle model; wherein, the data acquisition module includes a camera;

[0071] The dynamic calculation model is used to calculate the loading weights of different material piles for the long-hopper vehicle model by the model;

[0072] The static allocation module is used to record the number of loading piles of non-long hopper vehicle types and the weight of each pile according to experience;

[0073] The control module is used to control the loading of piles according to the number of loading piles and the weight of each pile obtained from the dynamic calculation model and the static allocation module, enable mutual communication between each module, self-check the system, and send the system status and loading status to the management personnel.

[0074] Please refer to Figure 5 , Figure 5 , which is a structural block diagram of an electronic device provided by an embodiment of the present invention. The electronic device includes a memory 101, a processor 102, and a communication interface 103. The memory 101, the processor 102, and the communication interface 103 are directly or indirectly electrically connected to each other to achieve data transmission or interaction. For example, these components can be electrically connected to each other through one or more communication buses or signal lines. The memory 101 can be used to store software programs and modules, such as program instructions / modules corresponding to a coal silo loading pile control method and system provided by an embodiment of the present application. The processor 102 executes various functional applications and data processing by executing the software programs and modules stored in the memory 101. The communication interface 103 can be used for signaling or data communication with other node devices.

[0075] Among them, the memory 101 can be, but is not limited to, a random access memory (RAM), a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), etc.

[0076] The processor 102 can be an integrated circuit chip with signal processing capabilities. The processor 102 can be a general-purpose processor, including a Central Processing Unit (CPU), a Network Processor (NP), etc.; it can also be a Digital Signal Processing (DSP), an Application Specific Integrated Circuit (ASIC), a Field-Programmable Gate Array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components.

[0077] It can be understood that Figure 5 The structure shown is only schematic, and the electronic device may also include more or fewer components than those shown Figure 5 in the figure, or have a different configuration from that shown Figure 5 in the figure. Figure 5 Each component shown in the figure can be implemented by hardware, software, or a combination thereof.

[0078] In summary, the coal silo loading stockpile control method and system provided by the embodiments of the present application classify different vehicle types and adopt different loading methods, which can accurately load different vehicle types, increasing the practicality of the system; adding a control module can detect the system status in real time and provide timely feedback in case of emergencies. Introducing static allocation can combine existing experience and propose solutions for vehicle types that cannot be quantified, which has universality; and the stockpile allocation reaches the best state, with smooth loading and no material spillage.

[0079] For those skilled in the art, it is obvious that the present application is not limited to the details of the above exemplary embodiments, and without departing from the spirit or basic characteristics of the present application, the present application can be implemented in other specific forms. Therefore, from any point of view, the embodiments should be regarded as exemplary and non-limiting. The scope of the present application is defined by the appended claims rather than the above description. Therefore, all changes falling within the meaning and scope of the equivalent elements of the claims are intended to be included in the present application. Any reference signs in the claims should not be construed as limiting the claimed rights.

Claims

1. A method for controlling the loading material pile in a coal silo, characterized in that It includes the following steps: S1. Obtain vehicle model data, and determine whether the vehicle is a long-hopper model. If so, proceed to step S2; otherwise, proceed to step S5; S2. Obtain the empirical values of the loading weights of different material piles for manual loading of long-hopper models; S3. Construct a dynamic calculation model, and use the empirical values of the loading weights of different material piles and the data of long-hopper models to train the dynamic calculation model to obtain a trained dynamic calculation model. Step S3 includes the following sub-steps: S3-1. Obtain the estimated net loading weight value t of the long-hopper model according to the data of the long-hopper model; and obtain the number of material piles n for loading according to the empirical values of the loading weights of different material piles; S3-2. Calculate the predicted weight value t of the intermediate stockpile based on the predicted net weight value t for loading and the number of stockpiles n for loading materials 中预 ; where t 中预 = t / n; S3-3. Set the deviation value t of the first stockpile 首偏 , according to the deviation value t of the first stockpile 首偏 and the predicted value t of the intermediate stockpile weight 中预 calculate the weight t of the first stockpile 首堆 ; where, t 首堆 =t 首偏 +t 中预 ; S3-4. Set the tail stockpile deviation value t 尾偏 , according to the tail stockpile deviation value t 尾偏 and the predicted value t of the intermediate stockpile weight 中预 calculate the weight t of the tail stockpile 尾堆 ; where, t 尾堆 =t 中预 -t 尾偏 ; S3-5. Calculate the weight value t of the intermediate stockpile according to the weight t of the tail stockpile 尾堆 and the weight t of the head stockpile 首堆 ; where t 中 =(t - t 中 - t 首堆 ) / (n - 2); 尾堆 ​ S3-6. Repeat steps S3-1 to S3-5 to adjust the deviation value t of the first stockpile 首偏 , the deviation value t of the last stockpile 尾偏 , and the number of stockpiles n for loading until the loading accuracy rate of the long-bucket vehicle type reaches the set threshold, and obtain the trained dynamic calculation model; S4. Use the trained dynamic calculation model to calculate the loading weights of different material piles of the long-hopper model; S5. Allocate the material pile weights for non-long-hopper models according to actual empirical values.

2. The coal silo loading stockpile control method according to claim 1, wherein The basis for determining whether the vehicle is a long-hopper model in step S1 includes the following steps: S1-1. Use a camera to obtain vehicle model data; S1-2. Take the hopper shape with a hopper length greater than 9 meters and a hopper depth lower than 2 meters as the long-hopper model, and the rest of the models as non-long-hopper models.

3. The coal silo loading pile control method according to claim 1, characterized in that, The said step S5 includes the following steps: S5-1. Obtain the specific model of the non-long-hopper model; S5-2. Obtain the number of material piles for loading and the weight of each material pile for the specific model of the non-long-hopper model and record them; S5-3. Repeat steps S5-1 to S5-2 until the common models of the non-long-hopper models are recorded to obtain a loading file; S5-4. Allocate the material pile weights for non-long-hopper models according to the loading file.

4. A coal silo loading stockpile control system, which is applied to the coal silo loading stockpile control method described in any one of claims 1 to 3, and is characterized in that, It includes a data acquisition module, a control module, a dynamic calculation model, and a static allocation module; The said data acquisition module is used to obtain vehicle model data, determine whether the vehicle is a long-hopper model, obtain the empirical values of the loading weights of different material piles for manual loading of long-hopper models; obtain the empirical values of the loading weights of different material piles for manual loading of non-long-hopper models; wherein, the data acquisition module includes a camera; The said dynamic calculation model is used to calculate the loading weights of different material piles of the long-hopper model by the model; The said static allocation module is used to record the number of material piles for loading and the weight of each material pile of non-long-hopper models according to experience; The said control module is used to control the loading of material piles according to the number of material piles for loading and the weight of each material pile obtained by the dynamic calculation module and the static allocation module, enable communication between each module, perform self-check on the system, and send the system status and loading status to the management personnel.

5. An electronic device, characterized in that, It includes: A memory for storing one or more programs; A processor; 6. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the said one or more programs are executed by the processor, the method described in any one of claims 1-3 is implemented. When the computer program is executed by the processor, the method described in any one of claims 1-3 is implemented.

Images