CN116040352A

CN116040352A - Loading control method, device, system and computer equipment

Info

Publication number: CN116040352A
Application number: CN202211482966.4A
Authority: CN
Inventors: 李明; 孙景阳; 石建光; 武源; 狄培义; 李季; 寇伟; 戈勇; 张刚; 孙卫东
Original assignee: Ccteg Beijing Huayu Engineering Co ltd; Coal Washing Branch Of Guoneng Baotou Energy Co ltd
Current assignee: Ccteg Beijing Huayu Engineering Co ltd; Coal Washing Branch Of Guoneng Baotou Energy Co ltd
Priority date: 2022-11-24
Filing date: 2022-11-24
Publication date: 2023-05-02

Abstract

The present disclosure proposes a loading control method, apparatus, system and computer device, the method comprising: obtaining target vehicle information of a vehicle to be loaded, wherein the target vehicle information comprises: vehicle identification information and loading demand information, and determining a target loading channel according to the vehicle identification information, wherein the target loading channel comprises: the device comprises a buffer bin, a quantitative bin and a flat coal scraper, wherein the quantitative bin and the buffer bin are controlled to obtain materials to be loaded according to loading demand information, and the quantitative bin and the flat coal scraper are controlled to load the materials to be loaded to a vehicle to be loaded. By implementing the method disclosed by the invention, the reliability of the loading control process can be ensured, and the acquisition efficiency and accuracy of the materials to be loaded are improved, so that the loading control effect is effectively improved.

Description

Loading control method, device, system and computer equipment

Technical Field

The disclosure relates to the technical field of automatic loading, in particular to a loading control method, device, system and computer equipment.

Background

Along with the continuous improvement of the demands of users for the loading efficiency of the loading station, a plurality of loading channels are generally configured in the loading station so as to realize simultaneous loading of multiple coal types in multiple channels.

In the related art, the control effect on the loading process is poor, and the batching and loading efficiency of a loading station are affected.

Disclosure of Invention

The present disclosure aims to solve, at least to some extent, one of the technical problems in the related art.

Therefore, an object of the present disclosure is to provide a loading control method, a device, a computer device and a storage medium, which can ensure the reliability of the loading control process, and improve the obtaining efficiency and accuracy of the material to be loaded, thereby effectively improving the loading control effect.

The loading control method provided by the embodiment of the first aspect of the present disclosure includes:

obtaining target vehicle information of a vehicle to be loaded, wherein the target vehicle information comprises: vehicle identification information and loading demand information;

determining a target loading channel according to the vehicle identification information, wherein the target loading channel comprises: a buffering bin, a quantitative bin and a flat coal scraper machine;

according to the loading demand information, controlling the quantitative bin and the buffer bin to acquire materials to be loaded;

and controlling the quantitative bin and the flat coal scraper machine to fill the materials to be filled into the vehicles to be filled.

According to the loading control method provided by the embodiment of the first aspect of the disclosure, target vehicle information of a vehicle to be loaded is obtained, wherein the target vehicle information comprises: vehicle identification information and loading demand information, and determining a target loading channel according to the vehicle identification information, wherein the target loading channel comprises: the buffer bin, the quantitative bin and the flat coal scraper are controlled to acquire materials to be loaded according to loading demand information, the quantitative bin and the flat coal scraper are controlled to load the materials to be loaded to the vehicle to be loaded, reliability of a loading control process can be guaranteed, and acquiring efficiency and accuracy of the materials to be loaded are improved, so that loading control effect is effectively improved.

The loading control device provided by the embodiment of the second aspect of the disclosure comprises:

the first acquisition module is used for acquiring target vehicle information of a vehicle to be loaded, wherein the target vehicle information comprises: vehicle identification information and loading demand information;

the first determining module is configured to determine a target loading channel according to the vehicle identification information, where the target loading channel includes: a buffering bin, a quantitative bin and a flat coal scraper machine;

the first control module is used for controlling the quantitative bin and the buffer bin to acquire materials to be loaded according to the loading demand information;

and the second control module is used for controlling the quantitative bin and the flat coal scraper machine and filling the materials to be filled into the vehicles to be filled.

According to the loading control device provided by the embodiment of the second aspect of the disclosure, target vehicle information of a vehicle to be loaded is obtained, wherein the target vehicle information comprises: vehicle identification information and loading demand information, and determining a target loading channel according to the vehicle identification information, wherein the target loading channel comprises: the buffer bin, the quantitative bin and the flat coal scraper are controlled to acquire materials to be loaded according to loading demand information, the quantitative bin and the flat coal scraper are controlled to load the materials to be loaded to the vehicle to be loaded, reliability of a loading control process can be guaranteed, and acquiring efficiency and accuracy of the materials to be loaded are improved, so that loading control effect is effectively improved.

A loading control system according to an embodiment of a third aspect of the present disclosure includes: the automatic continuous loading system comprises a feeding subsystem, a batching subsystem, a metering weighing subsystem, an automatic continuous loading subsystem, an electric subsystem, a software subsystem, a hydraulic subsystem and a lubricating subsystem; wherein,

the feeding subsystem is used for filling materials into the surge bin to a specified weight;

the batching subsystem is used for batching the quantitative bin to the weight of the materials to be loaded of the vehicles to be loaded;

the metering and weighing subsystem is used for determining the actual weight of the material to be loaded;

the automatic continuous loading subsystem is used for realizing automatic continuous loading of a plurality of vehicles to be loaded.

According to the loading control system provided by the embodiment of the third aspect of the disclosure, target vehicle information of a vehicle to be loaded is obtained, wherein the target vehicle information comprises: vehicle identification information and loading demand information, and determining a target loading channel according to the vehicle identification information, wherein the target loading channel comprises: the buffer bin, the quantitative bin and the flat coal scraper are controlled to acquire materials to be loaded according to loading demand information, the quantitative bin and the flat coal scraper are controlled to load the materials to be loaded to the vehicle to be loaded, reliability of a loading control process can be guaranteed, and acquiring efficiency and accuracy of the materials to be loaded are improved, so that loading control effect is effectively improved.

A computer device according to an embodiment of a fourth aspect of the present disclosure includes: the system comprises a memory, a processor and a computer program stored on the memory and capable of running on the processor, wherein the processor realizes the loading control method according to the embodiment of the first aspect of the disclosure when executing the program.

An embodiment of a fifth aspect of the present disclosure proposes a non-transitory computer-readable storage medium having stored thereon a computer program which, when executed by a processor, implements a loading control method as proposed by an embodiment of the first aspect of the present disclosure.

Embodiments of a sixth aspect of the present disclosure propose a computer program product, which when executed by a processor, performs a loading control method as proposed by embodiments of the first aspect of the present disclosure.

Additional aspects and advantages of the disclosure will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the disclosure.

Drawings

The foregoing and/or additional aspects and advantages of the present disclosure will become apparent and readily appreciated from the following description of the embodiments, taken in conjunction with the accompanying drawings, in which:

FIG. 1 is a flow chart of a loading control method according to an embodiment of the disclosure;

FIG. 2 is a flow chart of a loading control method according to another embodiment of the present disclosure;

FIG. 3 is a schematic diagram of a loading process according to an embodiment of the disclosure;

fig. 4 is a periodic time-sharing bin timing diagram according to an embodiment of the present disclosure;

FIG. 5 is a flow chart of a loading control method according to another embodiment of the present disclosure;

FIG. 6 is a timing diagram of a bin according to an embodiment of the present disclosure;

FIG. 7 is a schematic diagram of a fuzzy control according to an embodiment of the present disclosure;

FIG. 8 is a schematic diagram of a learning neural network according to an embodiment of the present disclosure;

FIG. 9 is a schematic view of an impact curve according to an embodiment of the present disclosure;

FIG. 10 is a schematic diagram of a binning strategy according to an embodiment of the present disclosure;

FIG. 11 is a schematic diagram of a multi-channel collaborative loading centralized control system according to an embodiment of the present disclosure;

FIG. 12 is a schematic view of a loading control device according to an embodiment of the present disclosure;

fig. 13 is a schematic structural view of a loading control device according to another embodiment of the present disclosure;

FIG. 14 is a schematic diagram of a loading control system according to an embodiment of the present disclosure;

fig. 15 illustrates a block diagram of an exemplary computer device suitable for use in implementing embodiments of the present disclosure.

Detailed Description

Embodiments of the present disclosure are described in detail below, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to like or similar elements or elements having like or similar functions throughout. The embodiments described below by referring to the drawings are exemplary only for explaining the present disclosure and are not to be construed as limiting the present disclosure. On the contrary, the embodiments of the disclosure include all alternatives, modifications, and equivalents as may be included within the spirit and scope of the appended claims.

Fig. 1 is a flow chart of a loading control method according to an embodiment of the disclosure.

It should be noted that, the execution main body of the loading control method in this embodiment is a loading control device, and the device may be implemented in a software and/or hardware manner, and the device may be configured in a computer device, where the computer device may include, but is not limited to, a terminal, a server, and the like, and the terminal may be, for example, a mobile phone, a palm computer, and the like.

As shown in fig. 1, the loading control method includes:

s101: obtaining target vehicle information of a vehicle to be loaded, wherein the target vehicle information comprises: vehicle identification information and loading demand information.

The vehicle to be loaded refers to a vehicle to be loaded based on the loading control method provided by the embodiment of the disclosure, and may be, for example, a truck for transporting coal.

The target vehicle information may be used to indicate information about the vehicle to be loaded. The vehicle identification information may be used to identify the vehicle to be loaded from among a plurality of vehicles, and may be, for example, a vehicle type, a vehicle number, or the like. The loading requirement information may be used to indicate the loading requirement of the vehicle to be loaded, for example, the type, weight, etc. of the material to be loaded.

In the embodiment of the disclosure, when the target vehicle information of the vehicle to be loaded is acquired, the target vehicle information may be based on a pre-established vehicle information database, or may also be based on a third-party vehicle information acquisition device, which is not limited.

In the embodiment of the disclosure, when target vehicle information of a vehicle to be loaded is acquired, the target vehicle information includes: when the vehicle identification information and the loading demand information are used, the obtained vehicle identification information can provide reliable reference basis for the follow-up determination of the target loading channel, and the obtained loading demand information can accurately indicate the loading control process of the vehicle to be loaded.

S102: determining a target loading channel according to the vehicle identification information, wherein the target loading channel comprises: a buffer bin, a quantitative bin and a flat coal scraper.

It can be understood that the loading control method provided by the embodiment of the disclosure may be applied to a multi-channel loading station, and the material types configured in the buffer bin of each loading channel may be different, so that when the target loading channel is determined according to the vehicle identification information, the suitability between the subsequent loading process and the vehicle to be loaded can be ensured.

Wherein, the surge bin is used for temporarily storing materials. And the quantitative bin is used for acquiring materials with specified weight. The flat coal scraper is used for transporting the materials in the quantitative bin to the vehicle to be loaded.

S103: and controlling the quantitative bin and the buffer bin to obtain materials to be loaded according to the loading demand information.

The material to be filled refers to the material to be filled into the vehicle to be filled.

S104: and controlling the quantitative bin and the flat coal scraper to fill the materials to be filled into the vehicles to be filled.

In this embodiment, by acquiring target vehicle information of a vehicle to be loaded, the target vehicle information includes: vehicle identification information and loading demand information, and determining a target loading channel according to the vehicle identification information, wherein the target loading channel comprises: the buffer bin, the quantitative bin and the flat coal scraper are controlled to acquire materials to be loaded according to loading demand information, the quantitative bin and the flat coal scraper are controlled to load the materials to be loaded to the vehicle to be loaded, reliability of a loading control process can be guaranteed, and acquiring efficiency and accuracy of the materials to be loaded are improved, so that loading control effect is effectively improved.

Fig. 2 is a flow chart illustrating a loading control method according to another embodiment of the present disclosure.

As shown in fig. 2, the loading control method includes:

s201: obtaining candidate vehicle information of at least one candidate vehicle, wherein the vehicle to be loaded belongs to the at least one candidate vehicle, and the candidate vehicle information comprises: candidate vehicle identification information and candidate loading demand information.

The candidate vehicles refer to all vehicles waiting for loading in the loading station. The candidate vehicle identification information and the candidate loading demand information refer to vehicle identification information and loading demand information corresponding to the candidate vehicle.

S202: and determining the feeding type and the feeding weight of the buffer bin according to the candidate loading demand information.

Wherein, the feeding is the process of pointing to the filling materials in the surge bin. And the type of feed refers to the type of material being filled. The feeding weight refers to the weight of the material to be filled in the surge bin.

S203: real-time bin data of the cache bin is determined.

The real-time bin data refer to the real-time bin of the buffer bin in the feeding process.

S204: and filling the cache bin with materials according to the feeding type, the feeding weight and the real-time bin position data.

Optionally, in some embodiments, the number of loading channels is multiple, each loading channel is configured with a buffer bin, when the buffer bins are filled with materials according to the feeding type, the feeding weight and the real-time bin position data, the buffer bins to be fed can be determined, the feeding rate is determined according to the real-time bin position data of the buffer bins to be fed, and the buffer bins to be fed are filled with materials based on the feeding rate, so that the real-time bin position data of the buffer bins to be fed can be effectively combined in the feeding process of the buffer bins, and the applicability of the obtained feeding rate can be effectively improved, and the feeding effect can be effectively improved.

Wherein, the feeding rate refers to the material filling rate of the surge bin to be fed.

Alternatively, in some embodiments, in determining the surge bin to be fed, the surge bin to be fed may be determined based on a step-and-order cycle pattern according to the type of feed.

Alternatively, in some embodiments, when determining the to-be-fed surge bin, the low-coal-level surge bin may be determined according to the real-time bin position data, and the low-coal-level surge bin is taken as the to-be-fed surge bin.

The low coal level buffer bin refers to a buffer bin with the lowest coal level stored in the multiple buffer bins.

Alternatively, in some embodiments, in determining the surge bin to be fed, the feeding period may be determined according to the feeding type, and the surge bin to be fed may be determined based on the feeding period.

Wherein, the feeding period refers to the time of different coal types in the feeding process.

Thus, a flexible feeding strategy can be adopted in the feeding process for a plurality of surge bins, so as to ensure the suitability between the feeding process and the application environment.

That is, the embodiment of the present disclosure may acquire the candidate vehicle information of at least one candidate vehicle before acquiring the target vehicle information of the to-be-loaded vehicle, where the to-be-loaded vehicle belongs to the at least one candidate vehicle, the candidate vehicle information including: candidate vehicle identification information and candidate loading demand information, according to candidate loading demand information, confirm the feed type and the feed weight of buffering storehouse, confirm the real-time position data of buffering storehouse, according to feed type, feed weight and real-time position data, carry out the material to buffering storehouse and pack, from this, can effectively promote the reliability of buffering storehouse feed process based on candidate vehicle information, in order to guarantee that the material that buffering storehouse stored can satisfy the loading demand of every candidate vehicle, can effectively promote loading efficiency.

S205: obtaining target vehicle information of a vehicle to be loaded, wherein the target vehicle information comprises: vehicle identification information and loading demand information.

S206: determining a target loading channel according to the vehicle identification information, wherein the target loading channel comprises: a buffer bin, a quantitative bin and a flat coal scraper.

S207: and controlling the quantitative bin and the buffer bin to obtain materials to be loaded according to the loading demand information.

S208: and controlling the quantitative bin and the flat coal scraper to fill the materials to be filled into the vehicles to be filled.

The descriptions of S205-S208 may be specifically referred to the above embodiments, and are not repeated here.

For example, as shown in fig. 3, fig. 3 is a schematic diagram of a loading process according to an embodiment of the disclosure, and the loading process is as follows:

[1] when the vehicle enters the gate sentry, the driver gets the card, and meanwhile, the vehicle information is as follows: information such as a vehicle number, a vehicle type, a load, a coal type and the like is input into a vehicle management database system.

[2] The intelligent dispatching system automatically distributes the loading channel, the driver holds the card to drive the vehicle to the appointed loading channel, the remote card reader scans the card of the current vehicle, and the control system retrieves the information of the current vehicle in the database.

[3] The control system automatically starts the batching system, opens the batching flat gate below the buffering bin, puts the coal into the weighing bin, measures in real time by a weighing sensor arranged in the weighing bin, and closes the batching gate of the buffering bin when the preset weight is reached, so that static accurate weighing is realized;

[4] After the carriage is in place, a discharging gate under the weighing bin is opened, coal is filled into the carriage through a flat coal scraper, and meanwhile the coal is scraped by the scraper, so that trapezoid accumulation is formed in the carriage by the coal scraper. After the current car is loaded, the discharging gate is automatically closed, and the flat coal scraper is automatically lifted.

[5] When the vehicle runs out and passes through a gate, the driver gets on the card which is picked up when entering the gate.

At the end of a loading cycle, the system waits for the next vehicle to enter the loading tunnel. Meanwhile, the coal level in the buffer bin can be automatically supplied by the automatic bin allocation system, so that the requirements of subsequent vehicles are met.

In this embodiment, by acquiring candidate vehicle information of at least one candidate vehicle, where the vehicle to be loaded belongs to the at least one candidate vehicle, the candidate vehicle information includes: candidate vehicle identification information and candidate loading demand information, according to candidate loading demand information, confirm the feed type and the feed weight of buffering storehouse, confirm the real-time position data of buffering storehouse, according to feed type, feed weight and real-time position data, carry out the material to buffering storehouse and pack, from this, can effectively promote the reliability of buffering storehouse feed process based on candidate vehicle information, in order to guarantee that the material that buffering storehouse stored can satisfy the loading demand of every candidate vehicle, can effectively promote loading efficiency. Through determining to wait to feed the surge bin, according to waiting to feed the real-time bin space data of surge bin, confirm the feed rate, based on the feed rate, wait to feed the surge bin and carry out the material filling, from this, can effectively combine waiting to feed the real-time bin space data of surge bin in the feed process to the surge bin to effectively promote the suitability of gained feed rate, thereby effectively promote the feed effect. Determining a surge bin to be fed, comprising any one of: determining a to-be-fed surge bin based on a stepping sequential circulation mode according to the feeding type; determining a low coal level buffer bin according to the real-time bin data, and taking the low coal level buffer bin as a buffer bin to be fed; according to the feeding type, the feeding period is determined, and the surge bin to be fed is determined based on the feeding period, so that flexible feeding strategies can be adopted in the feeding process of a plurality of surge bins, and the suitability between the feeding process and the application environment is ensured.

For example, according to the multi-channel loading process, the coal belt conveying capacity is assumed to be 5000t/h, the coal belt conveying capacity is respectively unloaded to 4 300 ton buffer bins through 2 heavy-load scrapers with the conveying capacity of 2500t/h, the coal is mixed to a weighing bin through the buffer bins, and the coal is loaded and distributed to a coal conveying automobile. It follows that the belt capacity was 83 tons/min, the single surge bin batching time was 4 minutes, and that the 4 surge bins required 16 minutes to complete a batching cycle.

The vehicle dispatching system inputs the information of the approaching vehicles into the database system in advance, the system can automatically count the distribution of the weight requirements of the vehicles to be loaded on various coals, and then the loading station can select different control flows so as to meet the loading requirements of the vehicles to be loaded.

[1] Different coal types are fed in a stepping sequential circulation mode

The stepping sequential circulation mode starts from a first automobile product bin, sequentially stacks coal on the belt conveyor at the same time interval, and the control system sequentially opens the batching gate at the same time interval, and sequentially stacks the coal after reaching the scraping plate until all the loading coal bins send high coal level signals. If the bin has been filled by a predetermined time, a high level signal is sent and the system stops the coal feeder for that product bin.

[2] Low coal level priority coal feeding mode

The low-coal-level priority coal feeding mode refers to that in the loading process, if one loading coal bin sends out a low-coal-level signal, the coal bin needs to be fed with coal, the bin allocation work of the current cycle coal feeding period is stopped, and the coal bin is memorized. And feeding coal to the coal bin which firstly sends out the low-coal-level signal preferentially, and feeding coal to the loading bins with the low-coal-level signal sequentially after eliminating the low-coal-level signal until all the low-coal-level signals are eliminated. When all the low coal level signals disappear, normal sequential coal feeding is carried out according to the original stored memory logic until all the coal bins send out high coal level signals. After the full coal level signal appears, the program is automatically stopped.

[3] Periodic time-sharing feeding of different coals

According to the loading requirement, when multiple coal types are loaded simultaneously, a periodical time-sharing coal feeding mode is adopted for the coal feeding system for bin allocation. The control system automatically starts the coal-separating scraper machine, the belt is arranged on the station, the coal level of each buffer bin is estimated according to the feedback signal of the material level indicator of the buffer bin, the demand of each coal type is estimated according to the vehicle-loading information in the database, then, the coal feeder of the corresponding coal type is started, the running time of the coal feeder is determined by the control system according to the flow of the belt scale and the material level signal of the buffer bin, and when one coal level reaches 80% of the bin, the material-separating gate is closed. The system feeds the next coal, and in the same process, when the coal is switched, the last coal on the empty belt is required to be carried so as to avoid mixing different coal.

As shown in fig. 4, fig. 4 is a periodic time-sharing bin timing chart according to an embodiment of the present disclosure, where, assuming that A, B, C, D kinds of coal exist, a certain coal bin time is calculated as follows:

the expected ingredient weight M (ton) =300 ton-current weight;

instantaneous flow rate of coal stream: n (ton/second), this parameter being detected by a belt scale;

the binning time t=m/N (seconds).

Fig. 5 is a flow chart of a loading control method according to another embodiment of the disclosure.

As shown in fig. 5, the loading control method includes:

s501: obtaining target vehicle information of a vehicle to be loaded, wherein the target vehicle information comprises: vehicle identification information and loading demand information.

S502: determining a target loading channel according to the vehicle identification information, wherein the target loading channel comprises: a buffer bin, a quantitative bin and a flat coal scraper.

The descriptions of S501 and S502 may be specifically referred to the above embodiments, and are not repeated herein.

S503: an ingredient related parameter is determined.

Wherein, batching refers to the process of distributing materials from a surge bin to a quantitative bin. The ingredients related parameters refer to related parameters affecting the ingredients process, such as material type, material granularity, environmental humidity, etc., and are not limited.

S504: and inputting the batching related parameters into the control information generation model, and acquiring gate control information output by the control information generation model, wherein the gate control information is used for indicating the opening and closing degree of a plurality of gates in the batching process.

The control information generation model may be a machine learning model that is trained in advance based on a large amount of experimental data. The shutter control information refers to related information used to instruct a shutter control process.

S505: and acquiring the material to be filled according to the gate control information, wherein the control information generation model learns the mapping relation between the ingredients related parameters and the gate control information.

Optionally, in some embodiments, a weighing device is configured in the quantitative bin, when the material to be loaded is acquired according to the gate control information, the weight of the material to be loaded and the type of the material to be loaded may be determined according to the loading demand information, based on the weighing device, the real-time weight of the material in the quantitative bin is acquired, and the opening and closing degrees of the gates are controlled according to the gate control information, the weight of the material to be loaded, the real-time weight of the material and the type of the material to be loaded, so that the material to be loaded is obtained, and therefore, the batching parameters of multiple dimensions can be comprehensively considered in the process of acquiring the material to be loaded, so that the accuracy of the obtained material to be loaded is effectively improved.

The weight and the type of the materials to be loaded refer to the weight and the type of the materials required by the vehicle to be loaded. The real-time material weight refers to the real-time weight of the material in the quantitative bin acquired based on the weighing device.

Optionally, in some embodiments, after the material to be loaded is obtained, a static weight of the obtained material to be loaded may be determined, so that the obtained static weight may provide an accurate feedback parameter for the loading control process, so as to facilitate adjustment of a subsequent loading control process.

Wherein, the static weight is the measured weight of the material to be filled in the specified amount bin in a static state. It will be appreciated that during the dosing process of the dosing bin, the material falling process may affect the accuracy of the weight data measured by the weighing device, and thus, when determining the static weight of the resulting material to be loaded, the actual weight of the material to be loaded may be accurately recorded.

That is, according to the embodiment of the disclosure, after the target loading channel is determined according to the vehicle identification information, the batching related parameters may be determined, the batching related parameters may be input into the control information generation model, and the gate control information output by the control information generation model is obtained, where the gate control information is used to indicate the opening and closing degrees of the plurality of gates in the batching process, and the material to be loaded is obtained according to the gate control information, where the control information generation model has learned the mapping relationship between the batching related parameters and the gate control information, thereby, the intelligentization degree of the material to be loaded obtaining process may be effectively improved based on the control information generation model, so as to effectively reduce the labor cost, and improve the accuracy of the obtained material to be loaded.

For example, coal index varies greatly due to the variety of coal requirements. Aiming at the situations, the embodiment of the disclosure can utilize the theory and method of modern control such as optimization control, fuzzy control, self-adaptive control and the like, and adopts an intelligent (servo) double-closed-loop feedback control strategy based on the combination of the batching quality and the quality change rate, so that the batching precision reaches 0.1%.

The batching process is influenced by a plurality of factors such as gate opening, the material level of a coal bunker, the blanking speed and position of a feeding belt, friction between a bunker wall and equipment, the humidity, density, granularity and fluidity of coal, and the like, accurate mathematical description cannot be performed, and a generalized trapezoidal model of single gate two-dimensional input can be established according to a large amount of test data:

V＝∫f(t _x ，t _z )d _t

wherein: v is the loading quantity, t _x For opening time t _z Is the batching time.

As shown in fig. 6, fig. 6 is a timing diagram of a bin according to an embodiment of the present disclosure.

First stage-coarse compounding Using quality control method

Second stage-refined matching by fuzzy control method

The fuzzy control method for quick batching is provided by combining the fuzzy control with the learning type neural network, so that the control has the function of processing fuzzy information and the self-learning function, can effectively control batching errors, improve loading speed and meet the production requirements of accurate and quick loading of a coal mine, and as shown in fig. 7 and 8, fig. 7 is a fuzzy control schematic diagram provided by the embodiment of the disclosure, and fig. 8 is a learning type neural network schematic diagram provided by the embodiment of the disclosure.

The neural network training process may be: firstly randomly setting a connection weight value and a threshold initial value of a neural network; according to the set amplification from small to large, each dustpan is sequentially controlled to train, the error between the network output and the actual loading increment is calculated, and each connection weight of the network is adjusted according to the principle of reducing the error; repeating the steps until the error reaches the requirement, and finally solving the neuron characteristic function f.

The coal flows out from the buffer bin gate at the following speed:

where λ is the discharge coefficient, depending on the nature of the bulk material. 0.5 g is gravity acceleration, 9.8 g is gravity acceleration, delta is buffer coal bin empirical compensation coefficient, 1 is taken when the amount of the buffer coal bin is 40% -80%, 0.8 is less than 40%, 1.1 is more than 80%, 1 and R is the effective radius of the gate in the formula,

(A is the side length of the gate, alpha' is the granularity of coal, and the clean coal is 50 mm)

Calculation of the passing flow of coal from the surge bin gate:

Q＝γ.w ₀ .v＝0.9*2.2*1.75＝3.475t/s

wherein gamma is bulk density of the material, and the cleaned coal is taken to be 0.9, w ₀ Is the gate area.

The buffer bin has four gates, completely meets the speed requirement of 10s internal bin allocation, but has poor precision control, because the physical quantity actually measured by the weighing sensor is force rather than weight, and the feedback weight of the weighing sensor is as follows:

F＝G+Fc＝mg+mf _v，γ

Where mg is the weight to be measured and the latter is a linear function of the coal flow rate and the particle size of the coal, it is known from the previous analysis that the coal flow rate is a constant value, so F _c Is a function proportional to the mass, and when the coal is static, the weight is 0 after the coal is loaded into the quantitative bin, the larger the mass is, F _c The larger the measured real-time weight error is, the greater the measured real-time weight error is, thirty tons of coal are loaded into a quantitative bin in the test, the impact curve obtained by acquisition of acquisition software is shown in fig. 9, and fig. 9 is a schematic diagram of the impact curve according to the embodiment of the disclosure.

From the analysis of fig. 9, it is seen that the Fc generated by the impact when 30t of coal is loaded into the quantitative bin resulted in a peak error of 8t at maximum, and the actual weight was reflected after several oscillations after the coal was loaded into the quantitative bin. The most important precision control in the bin allocation is the control of the buffer bin gate, and the coal discharge flow is reduced as much as possible when the upper limit is close to 62t, so that a strategy of closing the gate in a divided manner is selected, the bin allocation speed and precision are considered, the following bin allocation strategy is obtained through calculation, as shown in fig. 10, fig. 10 is a schematic diagram of the bin allocation strategy according to the embodiment of the disclosure, wherein four gates are all opened when 37t of coal is loaded before the bin allocation, two gates are closed when 37t is reached, three gates are closed when 52t is reached, three half gates are closed when 60.8t is reached, all gates are closed when 61.8t is reached, and 0.2t is discharged in the process of closing the door, so that the bin allocation is finished. The advance of 0.2t is an empirical value obtained through experiments, when the granularity of 50mm of clean coal is changed, the value needs to be correspondingly corrected, and the correction coefficient is as follows:

Wherein D is the granularity of the coal to be charged.

S506: and controlling the quantitative bin and the flat coal scraper to fill the materials to be filled into the vehicles to be filled.

The description of S506 may be specifically referred to the above embodiments, and will not be repeated here.

In this embodiment, the ingredients related parameters are determined and input into the control information generation model, and gate control information output by the control information generation model is obtained, where the gate control information is used to indicate the opening and closing degrees of a plurality of gates in the ingredients process, and the materials to be loaded are obtained according to the gate control information, where the control information generation model has learned the mapping relationship between the ingredients related parameters and the gate control information, so that the intelligentization degree of the materials to be loaded obtaining process can be effectively improved based on the control information generation model, so as to effectively reduce labor cost and improve the accuracy of the obtained materials to be loaded. According to the method, the weight of the material to be loaded and the type of the material to be loaded are determined according to the loading demand information, the real-time weight of the material in the quantitative bin is obtained based on the weighing equipment, and the opening and closing degree of a plurality of gates is controlled according to the gate control information, the weight of the material to be loaded, the material to be loaded and the type of the material to be loaded, so that the material to be loaded can be obtained, and the batching parameters of a plurality of dimensions can be comprehensively considered in the process of obtaining the material to be loaded, so that the accuracy of the obtained material to be loaded is effectively improved. By determining the static weight of the obtained material to be loaded, the obtained static weight can provide accurate feedback parameters for the loading control process, so that the subsequent loading control process can be conveniently adjusted.

For example, the loading control method according to the embodiments of the present disclosure may be implemented based on a multi-channel collaborative loading centralized control system, as shown in fig. 11, fig. 11 is a schematic structural diagram of a multi-channel collaborative loading centralized control system according to the embodiments of the present disclosure, where the multi-channel collaborative loading centralized control system mainly includes an information layer, a control layer and an equipment layer,

information layer: the method is completed through the Ethernet, and 4 upper computers in the control room of the loading station are connected with the PLC by using an Ethernet module of the AB-PLC. And monitoring the loading process and controlling the equipment by using upper software. In addition, the upper computer software is connected with the vehicle dispatching system, structured and solidified information is exchanged on the WEB by utilizing the SOAP protocol, and the information of the vehicle is timely transmitted to the coal mine information management part database, so that the management and planning of the coal transportation and marketing of the coal mine are facilitated.

Control layer: and the PLC master station, the substations, the weighing instrument and the upper station belt substations are connected with the PLC controller in a CONTROL NET bus mode, and the PLC controller refreshes and scans IO modules of all stations to finish execution of all commands under CONTROL logic.

Device layer: the input and output of equipment signals are finished through the AB-PLC I/O module, and the equipment signals comprise four sets of hydraulic systems, four sets of flat coal scraper machines, three sets of dust removal systems, one set of electric control system, four sets of weighing systems, one set of antifreeze liquid spraying system, one set of dust suppressant spraying system, one set of three-stage sampling system, a drainage system and other equipment control and corresponding sensor signals, and the reading of the signals is protected.

The core part is a PLC controller, which is a brain of process control, detects signals necessary for process control through some sensors, such as a belt scale, a buffer bin level gauge, a material distributing gate proximity switch, a coal blocking switch for detecting the full position of the buffer bin, and the like, and controls an executing mechanism to complete expected actions through program algorithm operation, such as: the device comprises a coal feeder, a belt conveyor, a batching scraper machine and a distributing gate.

And (3) a bin allocation intelligent control algorithm:

(1) Semi-automatic algorithm. The semi-automatic algorithm is an implementation algorithm for selectively carrying out bin allocation according to the storage condition of the coal bin and the coal types to be loaded by a user, and the input quantity of the algorithm is a buffer bin number and a coal bin number. The algorithm is described as follows:

(1) Select the buffer bin number N _S And number N for coal bin _O And bN is to _O ＝N _O

(2) If G _N -N _S Not equal to 0, set G _S =t, ensure that the non-bin surge bin charge gate is in the closed state, if G _N -N _S Let =0, set G _S =f, ensuring that the bin buffer bin batching gate to be batching is in an open state.

(3) N is calculated and judged through single-bin fuzzy control algorithm _S Whether the bin coal is full or not, if so, turning to (1), and judging N _O And bN _O Whether or not the same, if N _O -bN _O Not equal to 0, then new N _O The value is stored at bN _O In the process, the coal bunker N is simultaneously fed _O And the time delay is 5s, so that a certain interval exists between two different kinds of coal on the belt.

(2) Full-automatic algorithm. The full-automatic algorithm is an intelligent control algorithm for fully autonomous decision-making, and the system can automatically plan out corresponding [ N ] according to the demand of the coal types and the quantity of the bunker allocation on the same day _S ，N _O ]And combining, namely, the number of the to-be-matched buffer bin and the coal types, and transmitting information to an automobile loading scheduling system to realize multichannel collaborative intelligent loading.

Device and sensor:

[1] batching scraper

The batching scraper spans the tops of the four surge bins, is the last link of coal flow conveying, and respectively conveys the coal conveyed by the belt to each surge bin. The control system can automatically control the start and stop of the motor driven by an alternating current motor.

[2] Material distributing gate

The distributing gate is matched with the scraper for use, is arranged below the batching scraper and is arranged on the upper part of the buffering bin. Under the hydraulic drive, the device can freely do uniform linear motion, the maximum travel is one meter, and the positions of the maximum travel and the minimum travel are provided with proximity switches for detecting the position of the gate. When automatic batching is carried out, the control system can control the electromagnetic coil of the gate cylinder to open or close the gate according to the material level of the buffer bin under the gate.

[3] Buffer bin level gauge

The material level system of the buffering bin is provided with four stress sensors which are arranged at four corners of the buffering bin, the stress sensors output standard current signals with the change of 4-20 ma to the control system after the steel structure is deformed, bin positions can be displayed on a monitoring picture, and meanwhile, the signals are the basis for controlling the opening and closing of the coal separating gate and the starting and stopping of the coal feeder in the material mixing process.

[4] Belt scale

The electronic belt scale weighing bridge frame is arranged on a conveying frame of the loading station, when materials pass through, the detected weight of the materials on the belt is sent to a weighing instrument, meanwhile, a speed signal of the speed sensor belt conveyor is also sent to the weighing instrument, and the instrument integrates the speed signal and the weighing signal to obtain instantaneous flow and accumulated quantity.

Under the periodic time-sharing feeding mode of different coals, the accumulated increment of the belt scale can be used for calculating the coal feeding amount of certain coals.

[5] Coal blocking switch for surge bin

The coal blocking switch of the buffer bin is hung at a position 2 meters away from the top of the buffer bin, when coal is accumulated and touches the switch, the system automatically detects a coal blocking signal, and in order to prevent the coal overflow of the buffer bin, the system automatically closes a coal separating gate corresponding to the buffer bin. If the coal blocking switches of the four buffer bins all act, the system automatically stops all coal feeding and conveying equipment.

Fig. 12 is a schematic structural diagram of a loading control device according to an embodiment of the present disclosure.

As shown in fig. 12, the loading control device 120 includes:

a first obtaining module 1201 is configured to obtain target vehicle information of a vehicle to be loaded, where the target vehicle information includes: vehicle identification information and loading demand information;

a first determining module 1202, configured to determine a target loading channel according to vehicle identification information, where the target loading channel includes: a buffering bin, a quantitative bin and a flat coal scraper machine;

the first control module 1203 is configured to control the quantitative bin and the buffer bin to obtain a material to be loaded according to the loading demand information;

and the second control module 1204 is used for controlling the quantitative bin and the flat coal scraper machine to load the materials to be loaded into the vehicle to be loaded.

In some embodiments of the present disclosure, as shown in fig. 13, fig. 13 is a schematic structural diagram of a loading control device according to another embodiment of the present disclosure, where the loading control device 120 further includes:

a second obtaining module 1205 is configured to obtain candidate vehicle information of at least one candidate vehicle, where the vehicle to be loaded belongs to the at least one candidate vehicle, and the candidate vehicle information includes: candidate vehicle identification information and candidate loading demand information;

a second determining module 1206, configured to determine a feeding type and a feeding weight of the buffer bin according to the candidate loading demand information;

a third determining module 1207, configured to determine real-time bin data of the buffer bin;

the third control module 1208 fills the cache bin with material based on the feed type, feed weight, and real-time bin data.

In some embodiments of the present disclosure, the number of loading lanes is multiple, each loading lane is configured with a buffer bin, wherein the third control module 1208 is specifically configured to:

determining a buffering bin to be fed;

determining a feeding rate according to real-time bin position data of a to-be-fed buffer bin;

and filling the to-be-fed buffer bin with materials based on the feeding rate.

In some embodiments of the present disclosure, the third control module 1208 is further configured to:

determining a to-be-fed surge bin based on a stepping sequential circulation mode according to the feeding type;

determining a low coal level buffer bin according to the real-time bin data, and taking the low coal level buffer bin as a buffer bin to be fed;

according to the feed type, a feed period is determined and a surge bin to be fed is determined based on the feed period.

In some embodiments of the present disclosure, the surge bin comprises a plurality of gates, wherein the first control module 1203 is specifically configured to:

determining ingredients related parameters;

inputting the batching related parameters into a control information generation model, and acquiring gate control information output by the control information generation model, wherein the gate control information is used for indicating the opening and closing degree of a plurality of gates in the batching process;

and acquiring the material to be filled according to the gate control information, wherein the control information generation model learns the mapping relation between the ingredients related parameters and the gate control information.

In some embodiments of the present disclosure, a weighing device is configured in the quantitative bin, wherein the first control module 1203 is further configured to:

according to the loading demand information, determining the weight of the material to be loaded and the type of the material to be loaded;

Based on the weighing equipment, acquiring the weight of the real-time material in the quantitative bin;

and controlling the opening and closing degree of the plurality of gates according to the gate control information, the weight of the material to be loaded, the real-time weight of the material and the type of the material to be loaded so as to obtain the material to be loaded.

In some embodiments of the present disclosure, the first control module 1203 is further configured to:

and determining the static weight of the obtained material to be filled.

It should be noted that the foregoing explanation of the loading control method is also applicable to the loading control device of the present embodiment, and will not be repeated here.

Fig. 14 is a schematic structural diagram of a loading control system according to an embodiment of the present disclosure.

As shown in fig. 14, the loading control system 140 includes: a feeding subsystem 1401, a dosing subsystem 1402, a metering and weighing subsystem 1403, an automatic continuous loading subsystem 1404, an electrical subsystem 1405, a software subsystem 1406, a hydraulic subsystem 1407, a lubrication subsystem 1408; wherein,

a feed subsystem 1401 for filling the surge bin with material to a specified weight;

a dosing subsystem 1402 for dosing the dosing bin to a weight of a material to be loaded of the vehicle to be loaded;

a metering weighing subsystem 1403 for determining the actual weight of the material to be loaded;

an automatic continuous loading subsystem 1404 for implementing automatic continuous loading of a plurality of vehicles to be loaded.

Wherein, the electric subsystem 1405, the software subsystem 1406, the hydraulic subsystem 1407 and the lubrication subsystem 1408 are associated with the feeding subsystem 1401, the batching subsystem 1402, the metering and weighing subsystem 1403 and the automatic continuous loading subsystem 1404, and all the subsystems work cooperatively, and realize continuous, rapid and accurate batching and loading by controlling the accurate actions of key devices such as gates.

Optionally, the loading control system 140 may also display the signals of each bin position, the signals of the hydraulic system, the signals of the gate position, etc. in the loading station based on the man-machine interaction interface, and display the feeder, the belt conveyor, various protection signals thereof, etc. under the product bin. In addition, various alarm information, real-time and historical curve acquisition and other functions are realized.

Fig. 15 illustrates a block diagram of an exemplary computer device suitable for use in implementing embodiments of the present disclosure. The computer device 12 shown in fig. 15 is merely an example and should not be construed as limiting the functionality and scope of use of the disclosed embodiments.

As shown in fig. 15, the computer device 12 is in the form of a general purpose computing device. Components of computer device 12 may include, but are not limited to: one or more processors or processing units 16, a system memory 28, a bus 18 that connects the various system components, including the system memory 28 and the processing units 16.

Bus 18 represents one or more of several types of bus structures, including a memory bus or memory controller, a peripheral bus, an accelerated graphics port, a processor, and a local bus using any of a variety of bus architectures. By way of example, and not limitation, such architectures include industry Standard architecture (Industry Standard Architecture; hereinafter ISA) bus, micro channel architecture (Micro Channel Architecture; hereinafter MAC) bus, enhanced ISA bus, video electronics standards Association (Video Electronics Standards Association; hereinafter VESA) local bus, and peripheral component interconnect (Peripheral Component Interconnection; hereinafter PCI) bus.

Computer device 12 typically includes a variety of computer system readable media. Such media can be any available media that is accessible by computer device 12 and includes both volatile and nonvolatile media, removable and non-removable media.

Memory 28 may include computer system readable media in the form of volatile memory, such as random access memory (Random Access Memory; hereinafter: RAM) 30 and/or cache memory 32. The computer device 12 may further include other removable/non-removable, volatile/nonvolatile computer system storage media. By way of example only, storage system 34 may be used to read from or write to non-removable, nonvolatile magnetic media (not shown in FIG. 15, commonly referred to as a "hard disk drive").

Although not shown in fig. 15, a magnetic disk drive for reading from and writing to a removable nonvolatile magnetic disk (e.g., a "floppy disk"), and an optical disk drive for reading from or writing to a removable nonvolatile optical disk (e.g., a compact disk read only memory (Compact Disc Read Only Memory; hereinafter CD-ROM), digital versatile read only optical disk (Digital Video Disc Read Only Memory; hereinafter DVD-ROM), or other optical media) may be provided. In such cases, each drive may be coupled to bus 18 through one or more data medium interfaces. Memory 28 may include at least one program product having a set (e.g., at least one) of program modules configured to carry out the functions of the various embodiments of the disclosure.

A program/utility 40 having a set (at least one) of program modules 42 may be stored in, for example, memory 28, such program modules 42 including, but not limited to, an operating system, one or more application programs, other program modules, and program data, each or some combination of which may include an implementation of a network environment. Program modules 42 generally perform the functions and/or methods in the embodiments described in this disclosure.

The computer device 12 may also communicate with one or more external devices 14 (e.g., keyboard, pointing device, display 24, etc.), one or more devices that enable a person to interact with the computer device 12, and/or any devices (e.g., network card, modem, etc.) that enable the computer device 12 to communicate with one or more other computing devices. Such communication may occur through an input/output (I/O) interface 22. Moreover, the computer device 12 may also communicate with one or more networks such as a local area network (Local Area Network; hereinafter LAN), a wide area network (Wide Area Network; hereinafter WAN) and/or a public network such as the Internet via the network adapter 20. As shown, network adapter 20 communicates with other modules of computer device 12 via bus 18. It should be appreciated that although not shown, other hardware and/or software modules may be used in connection with computer device 12, including, but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, data backup storage systems, and the like.

The processing unit 16 executes various functional applications and data processing by running programs stored in the system memory 28, for example, implementing the loading control method mentioned in the foregoing embodiment.

In order to implement the above-described embodiments, the present disclosure also proposes a non-transitory computer-readable storage medium having stored thereon a computer program which, when executed by a processor, implements a loading control method as proposed in the foregoing embodiments of the present disclosure.

To achieve the above-described embodiments, the present disclosure also proposes a computer program product which, when executed by an instruction processor in the computer program product, performs a loading control method as proposed in the foregoing embodiments of the present disclosure.

Other embodiments of the disclosure will be apparent to those skilled in the art from consideration of the specification and practice of the disclosure disclosed herein. This disclosure is intended to cover any adaptations, uses, or adaptations of the disclosure following the general principles of the disclosure and including such departures from the present disclosure as come within known or customary practice within the art to which the disclosure pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the disclosure being indicated by the following claims.

It is to be understood that the present disclosure is not limited to the precise arrangements and instrumentalities shown in the drawings, and that various modifications and changes may be effected without departing from the scope thereof. The scope of the present disclosure is limited only by the appended claims.

It should be noted that in the description of the present disclosure, the terms "first," "second," and the like are used for descriptive purposes only and are not to be construed as indicating or implying relative importance. Furthermore, in the description of the present disclosure, unless otherwise indicated, the meaning of "a plurality" is two or more.

Any process or method descriptions in flow charts or otherwise described herein may be understood as representing modules, segments, or portions of code which include one or more executable instructions for implementing specific logical functions or steps of the process, and further implementations are included within the scope of the preferred embodiment of the present disclosure in which functions may be executed out of order from that shown or discussed, including substantially concurrently or in reverse order, depending on the functionality involved, as would be understood by those reasonably skilled in the art of the embodiments of the present disclosure.

It should be understood that portions of the present disclosure may be implemented in hardware, software, firmware, or a combination thereof. In the above-described embodiments, the various steps or methods may be implemented in software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, may be implemented using any one or combination of the following techniques, as is well known in the art: discrete logic circuits having logic gates for implementing logic functions on data signals, application specific integrated circuits having suitable combinational logic gates, programmable Gate Arrays (PGAs), field Programmable Gate Arrays (FPGAs), and the like.

Those of ordinary skill in the art will appreciate that all or a portion of the steps carried out in the method of the above-described embodiments may be implemented by a program to instruct related hardware, where the program may be stored in a computer readable storage medium, and where the program, when executed, includes one or a combination of the steps of the method embodiments.

Furthermore, each functional unit in the embodiments of the present disclosure may be integrated in one processing module, or each unit may exist alone physically, or two or more units may be integrated in one module. The integrated modules may be implemented in hardware or in software functional modules. The integrated modules may also be stored in a computer readable storage medium if implemented in the form of software functional modules and sold or used as a stand-alone product.

The above-mentioned storage medium may be a read-only memory, a magnetic disk or an optical disk, or the like.

In the description of the present specification, a description referring to terms "one embodiment," "some embodiments," "examples," "specific examples," or "some examples," etc., means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the present disclosure. In this specification, schematic representations of the above terms do not necessarily refer to the same embodiments or examples. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.

Although embodiments of the present disclosure have been shown and described above, it will be understood that the above embodiments are illustrative and not to be construed as limiting the present disclosure, and that variations, modifications, alternatives, and variations may be made to the above embodiments by one of ordinary skill in the art within the scope of the present disclosure.

Claims

1. A loading control method, characterized by comprising:

2. The method of claim 1, further comprising, prior to the acquiring the target vehicle information for the vehicle to be loaded:

obtaining candidate vehicle information of at least one candidate vehicle, wherein the to-be-loaded vehicle belongs to the at least one candidate vehicle, and the candidate vehicle information comprises: candidate vehicle identification information and candidate loading demand information;

Determining the feeding type and the feeding weight of the buffer bin according to the candidate loading demand information;

determining real-time bin position data of the cache bin;

and filling the cache bin with materials according to the feeding types, the feeding weights and the real-time bin data.

3. The method of claim 2, wherein a number of loading lanes is a plurality, each loading lane being configured with the buffer bin, wherein the filling the buffer bins with material based on the feedstock type, the feedstock weight, and the real-time bin data comprises:

determining a buffering bin to be fed;

determining a feeding rate according to the real-time bin position data of the to-be-fed buffer bin;

and filling the to-be-fed cache bin with materials based on the feeding rate.

4. A method according to claim 3, wherein said determining a surge bin to be fed comprises any one of:

determining the to-be-fed surge bin based on a stepping sequential circulation mode according to the feeding type;

determining a low coal level buffer bin according to the real-time bin data, and taking the low coal level buffer bin as the to-be-fed buffer bin;

And determining a feeding period according to the feeding type, and determining the to-be-fed surge bin based on the feeding period.

5. The method of claim 1, wherein the surge bin includes a plurality of gates, wherein the controlling the quantitative bin and the surge bin to obtain the material to be loaded according to the loading demand information includes:

determining ingredients related parameters;

inputting the batching related parameters into a control information generation model, and acquiring gate control information output by the control information generation model, wherein the gate control information is used for indicating the opening and closing degree of the plurality of gates in the batching process;

and acquiring the material to be filled according to the gate control information, wherein the control information generation model learns the mapping relation between the batching related parameters and the gate control information.

6. The method of claim 5, wherein a weighing device is disposed in the quantitative bin, wherein the acquiring the material to be loaded according to the gate control information comprises:

determining the weight and the type of the materials to be loaded according to the loading demand information;

and controlling the opening and closing degree of the gates according to the gate control information, the weight of the material to be loaded, the weight of the real-time material and the type of the material to be loaded so as to obtain the material to be loaded.

7. The method as recited in claim 6, further comprising:

and determining the static weight of the obtained material to be filled.

8. A loading control device, characterized by comprising:

9. A loading control system, comprising: the automatic continuous loading system comprises a feeding subsystem, a batching subsystem, a metering weighing subsystem, an automatic continuous loading subsystem, an electric subsystem, a software subsystem, a hydraulic subsystem and a lubricating subsystem; wherein,

10. A computer device, comprising:

at least one processor; and

a memory communicatively coupled to the at least one processor; wherein,

the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method of any one of claims 1-7.