Ternary coal blending method, system and device and medium

Abstract

The invention discloses a ternary coal blending method, system and device and a medium, and the method comprises the steps: obtaining parameters of a to-be-blended coal type, and carrying out the data preprocessing; the parameters comprise quantity, quality, coal rock component analysis characteristics, coal quality analysis characteristics and screening floating and sinking sample analysis characteristic data of to-be-blended coal types; establishing a prediction model, and setting coal blending conditions according to production conditions; according to the coal blending condition, the activation coal feeder is controlled by adjusting the opening degree of a coal locking plate and adjusting the vibration frequency of the coal locking plate; and acquiring the flow, the total amount and the proportion data of each coal type in real time, judging whether an abnormal condition exists or not, and outputting judgment data. According to the method, through data acquisition, model construction and modular architecture and algorithm deep fusion, coal blending whole-process intelligentization from data-driven modeling to dynamic closed-loop control is realized, and coal blending precision, economy and system robustness are remarkably improved.

Description

Technical Field

[0001] The present invention relates to the technical field of coal processing, and in particular to a ternary coal blending method, system, device and medium. Background Art

[0002] With global coal resources becoming increasingly scarce and market demands for coal product quality continuously increasing, how to efficiently and economically utilize the various coal resources available has become a critical issue that the coal industry urgently needs to address. Against the backdrop of the current energy structure transformation and increasingly stringent environmental protection requirements, the coal industry faces unprecedented challenges and opportunities.

[0003] The drawback of existing technologies is that traditional coal blending methods, due to their singularity and limitations, are no longer able to meet the complex and ever-changing demands of modern coal-to-gas processes. These methods often only consider one or a few coal quality parameters, such as ash content, moisture content, or calorific value, while ignoring other equally important coal properties, such as sulfur content, volatile matter, and grindability. This one-sided coal blending approach not only affects the stability and efficiency of the coal-to-gas process but also potentially increases production costs and environmental risks. Summary of the Invention

[0004] The purpose of the present invention is to overcome the deficiencies of the prior art. To achieve the above purpose, a ternary coal blending method is adopted to solve the problems raised in the above background technology.

[0005] A ternary coal blending method comprises the following steps:

[0006] Step S1: Obtain parameters of the coal to be blended and perform data preprocessing; the parameters include the quantity, quality, coal rock component analysis characteristics, coal quality analysis characteristics, and screening float and sink pattern analysis characteristics data of the coal to be blended;

[0007] Step S2: Establish a prediction model and set coal blending conditions according to production conditions;

[0008] Step S3: According to the coal blending conditions, the activation coal feeder is controlled by adjusting the opening of the coal locking plate and the vibration frequency of the coal locking plate;

[0009] Step S4: Obtain the flow rate, total amount, and ratio data of each type of coal in real time, determine whether there is an abnormal situation, and output the judgment data.

[0010] As a further solution of the present invention: the specific steps in step S1 include:

[0011] Step S11, obtaining various parameter data of the coal to be blended and preprocessing the collected data;

[0012] Step S12: Establish a database and input the coal type parameter data in units of coal types.

[0013] As a further solution of the present invention: the specific steps in step S2 include:

[0014] Step S21: Obtain data from the database, remove outliers and error values, and perform statistical analysis on the data;

[0015] Step S22: establishing a prediction model between the quality of the blended coal and the quality indicators of each single type of coal;

[0016] Step S23: Optimize the prediction model and test the prediction accuracy and reliability of the prediction model.

[0017] As a further solution of the present invention: the specific steps in step S3 include:

[0018] The activation coal feeder is controlled by adjusting the opening of the coal locking plate, and the opening range of the coal locking plate is controlled from 1% to 70% by closing the relay.

[0019] As a further solution of the present invention: the specific steps in step S3 include:

[0020] In the step of controlling the activated coal feeder by adjusting the opening of the coal locking plate and the vibration frequency of the coal locking plate according to the coal blending conditions, the method of controlling the activated coal feeder by adjusting the vibration frequency of the coal locking plate is as follows:

[0021] The vibration frequency of the coal locking plate is controlled by adjusting the 4mA to 20mA current through the PLC programmable logic controller hardware. The control formula is:

[0022]

[0023] Where Kp is the proportional coefficient, Ti is the integral time constant, and Td is the differential time constant; Ki = Kp / Ti is the integral coefficient; Kd = Kp*Td is the differential coefficient, e is the percentage error expressed in the range, and dt is the update time used by the loop.

[0024] As a further solution of the present invention: the specific steps in step S4 include:

[0025] Step S41: using flow sensors at multiple coal bunker outlets and weight sensors of belt scales, collect data transmitted by each sensor;

[0026] Step S42: Integrate the collected coal flow data and total amount data, and calculate the proportion data of various coals;

[0027] Set the thresholds for flow, total volume, and ratio data respectively;

[0028] Step S43: Compare the various coal flow data, total amount data, and proportion data of various coals with corresponding thresholds to determine whether there is any abnormality.

[0029] As a further solution of the present invention, the specific steps of determining whether there is an abnormal situation and outputting the judgment data in step S4 include:

[0030] When no abnormal situation occurs, various coal flow data, total amount data, and proportion data of various coals are processed into charts and output for visual display;

[0031] When an abnormal situation occurs, an abnormal visual prompt is generated.

[0032] The technical solution of the second aspect: a system using a ternary coal blending method as described in any one of the above, comprising a data acquisition module, a model building module, a control module, and a monitoring module;

[0033] The data acquisition module is used to obtain parameters of the coal to be blended and perform data preprocessing; the parameters include the quantity, quality, coal rock component analysis characteristics, coal quality analysis characteristics, and screening float and sink pattern analysis characteristics data of the coal to be blended;

[0034] The model building module is used to build a prediction model and set coal blending conditions according to production conditions;

[0035] The control module is used to control the activated coal feeder by adjusting the opening of the coal locking plate and the vibration frequency of the coal locking plate according to the coal blending conditions;

[0036] The monitoring module is used to obtain the flow rate, total amount, and proportion data of each type of coal in real time, determine whether there is an abnormal situation, and output the judgment data.

[0037] The technical solution of the third aspect: a device, further comprising:

[0038] at least one processor;

[0039] at least one memory for storing at least one program;

[0040] When the at least one program is executed by the at least one processor, the at least one processor implements a ternary coal blending method as described in any one of the above items.

[0041] The technical solution of the fourth aspect: a storage medium storing processor-executable instructions, wherein the processor-executable instructions are used to implement a ternary coal blending method as described in any one of the above items when executed by the processor.

[0042] Compared with the prior art, the present invention has the following technical effects:

[0043] Using the above technical solution, the data acquisition module integrates coal quality parameters and establishes a standardized database. The model building module dynamically generates coal blending strategies based on a multi-objective optimization algorithm. The control module achieves precise control of coal quantity through a composite adjustment of the coal lock plate opening and vibration frequency. The monitoring module relies on real-time flow tracking and anomaly detection algorithms to form a closed-loop feedback loop. These four modules work together to build a full-process closed-loop system of "data-driven modeling-dynamic strategy optimization-precise execution and regulation-rapid response to anomalies," ultimately achieving high precision, high stability, and strong adaptability in the coal blending process. The beneficial effect is that through the global optimization of coal quality parameters and dynamic closed-loop production control, the economic efficiency of coal blending is significantly improved, combustion safety, and environmental compliance are guaranteed. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] The specific embodiments of the present invention are described in detail below with reference to the accompanying drawings:

[0045] Figure 1 This is a schematic diagram of the steps of the ternary coal blending method disclosed in the embodiment of this application;

[0046] Figure 2 This is a flowchart of step S1 of the embodiment disclosed in this application;

[0047] Figure 3 This is a flowchart of step S2 of the embodiment disclosed in this application;

[0048] Figure 4 This is a schematic diagram of the coal lock plate opening and coal quantity in step S3 of the embodiment disclosed in this application;

[0049] Figure 5 This is a flowchart of step S4 of the embodiment disclosed in this application;

[0050] Figure 6 This is a block diagram of a ternary coal blending system according to an embodiment disclosed in this application;

[0051] Figure 7 A schematic diagram of an electronic device according to an embodiment of the present application.

[0052] In the figure: 501, data acquisition module; 502, model building module; 503, control module; 504, monitoring module. DETAILED DESCRIPTION

[0053] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0054] Please refer to Figure 1 In an embodiment of the present invention, a ternary coal blending method includes the following steps:

[0055] Step S1: Obtain parameters of the coal to be blended and perform data preprocessing; the parameters include the quantity, quality, coal rock component analysis characteristics, coal quality analysis characteristics, and screening float and sink pattern analysis characteristics data of the coal to be blended;

[0056] like Figure 2 As shown, the specific steps include:

[0057] Step S11, obtaining various parameter data of the coal to be blended and preprocessing the collected data;

[0058] Step S12: Establish a database and input the coal type parameter data in units of coal types.

[0059] In this embodiment, it is necessary to obtain the parameters of the coal type to be blended. The parameters are obtained by asking manufacturers, sales personnel, and self-testing, and the obtained parameters are sorted out; a database is established, and the types of databases include relational databases, memory databases, and distributed databases. The coal type parameter data is input in units of coal type for data storage.

[0060] Step S2: Establish a prediction model and set coal blending conditions according to production conditions;

[0061] like Figure 3 As shown, the specific steps include:

[0062] Step S21: Obtain data from the database, remove outliers and error values, and perform statistical analysis on the data;

[0063] Step S22: establishing a prediction model between the quality of the blended coal and the quality indicators of each single type of coal;

[0064] Step S23: Optimize the prediction model and test the prediction accuracy and reliability of the prediction model.

[0065] In this embodiment, data from a database is first acquired, and statistical analysis is performed on the data after outliers and erroneous values ​​are removed. A prediction model is then established between the quality of the blended coal and the quality indicators of each individual coal type. This is established by using mathematical methods such as linear regression and neural networks to establish a prediction model between the quality of the blended coal and the quality indicators of each individual coal type. The prediction model is optimized using optimization algorithms such as differential evolution and simulated annealing, implemented using programming languages ​​such as MATLAB and Python, and the prediction model's accuracy and reliability are tested. The model can be validated using experimental data or historical data to check its accuracy and reliability.

[0066] Step S3: According to the coal blending conditions, the activation coal feeder is controlled by adjusting the opening of the coal locking plate and the vibration frequency of the coal locking plate. The specific steps include:

[0067] The activation coal feeder is controlled by adjusting the opening of the coal locking plate, and the opening range of the coal locking plate is controlled from 1% to 70% by closing the relay.

[0068] In this embodiment, if Figure 4 As shown, in the step of controlling the activated coal feeder by adjusting the opening of the coal locking plate, the action opening is y, the fluctuation range is x, and the opening of the coal locking plate is controlled by closing the relay to 1% to 70%.

[0069] In this embodiment, the specific steps include:

[0070] In the step of controlling the activated coal feeder by adjusting the opening of the coal locking plate and the vibration frequency of the coal locking plate according to the coal blending conditions, the method of controlling the activated coal feeder by adjusting the vibration frequency of the coal locking plate is as follows:

[0071] The vibration frequency of the coal locking plate is controlled by adjusting the 4mA to 20mA current through the PLC programmable logic controller hardware. The control formula is:

[0072]

[0073] Where Kp is the proportional coefficient, Ti is the integral time constant, and Td is the differential time constant; Ki = Kp / Ti is the integral coefficient; Kd = Kp*Td is the differential coefficient, e is the percentage error expressed in the range, and dt is the update time used by the loop.

[0074] Step S4: Real-time acquisition of the flow rate, total amount, and ratio data of each type of coal, to determine whether there is an abnormality, and output the judgment data. Figure 5 As shown, the specific steps include:

[0075] Step S41: using flow sensors at multiple coal bunker outlets and weight sensors of belt scales, collect data transmitted by each sensor;

[0076] Step S42: Integrate the collected coal flow data and total amount data, and calculate the proportion data of various coals;

[0077] Set the thresholds for flow, total volume, and ratio data respectively;

[0078] Step S43: Compare the various coal flow data, total amount data, and proportion data of various coals with corresponding thresholds to determine whether there is any abnormality.

[0079] Specifically, the specific steps of determining whether an abnormal situation exists and outputting the determination data in step S4 include:

[0080] When no abnormal situation occurs, various coal flow data, total amount data, and proportion data of various coals are processed into charts and output for visual display;

[0081] When an abnormal situation occurs, an abnormal visual prompt is generated.

[0082] In this implementation, data transmitted by flow sensors and weight sensors on belt scales at multiple coal bunker outlets is first collected. The collected data on the flow and total volume of each coal is then integrated, and the proportions of each type of coal are calculated. A prediction model is used to set thresholds for the flow, total volume, and proportion data. Finally, the flow, total volume, and proportion data for each type of coal are compared against the corresponding thresholds to determine if an anomaly exists. If no anomaly exists, the flow, total volume, and proportion data for each type of coal are graphically processed and output for visual display. If an anomaly does occur, a visual notification is generated.

[0083] The technical solution of the second aspect: a system using a ternary coal blending method as described in any one of the above, comprising a data acquisition module 501, a model building module 502, a control module 503, and a monitoring module 504;

[0084] In this embodiment, Figure 6 As shown, the diagram is a block diagram of a ternary coal blending system. In the diagram, the system may include a data acquisition module 501, a model building module 502, a control module 503 and a monitoring module 504;

[0085] Data acquisition module 501 is used to obtain parameters of the coal to be blended and perform data preprocessing; the parameters include the quantity, quality, coal rock component analysis characteristics, coal quality analysis characteristics, and screening float and sink pattern analysis characteristics data of the coal to be blended;

[0086] Model building module 502, used to build a prediction model and set coal blending conditions according to production conditions;

[0087] The control module 503 is used to control the activated coal feeder by adjusting the opening of the coal locking plate and the vibration frequency of the coal locking plate according to the coal blending conditions;

[0088] The monitoring module 504 is used to obtain the flow rate, total amount, and ratio data of each type of coal in real time, determine whether there is an abnormal situation, and output the judgment data.

[0089] The technical solution of the third aspect: a device, further comprising:

[0090] at least one processor;

[0091] at least one memory for storing at least one program;

[0092] When the at least one program is executed by the at least one processor, the at least one processor implements a ternary coal blending method as described in any one of the above items.

[0093] like Figure 7 As shown in the figure, a hardware structure diagram of a ternary coal blending system provided by an embodiment of the present invention is provided in any device with data processing capability, except Figure 7 In addition to the processor, memory, and network interface shown, any device with data processing capabilities in which the apparatus in the embodiment is located may also include other hardware, generally based on the actual functions of the device with data processing capabilities, which will not be described in detail.

[0094] The technical solution of the fourth aspect: a storage medium storing processor-executable instructions, wherein the processor-executable instructions are used to implement a ternary coal blending method as described in any one of the above items when executed by the processor.

[0095] The computer-readable storage medium may be an internal storage unit of any device with data processing capabilities described in any of the aforementioned embodiments, such as a hard disk or memory. The computer-readable storage medium may also be an external storage device, such as a plug-in hard disk, a smart media card (SMC), an SD card, a flash card, etc. equipped on the device. Furthermore, the computer-readable storage medium may also include both an internal storage unit and an external storage device of any device with data processing capabilities. The computer-readable storage medium is used to store the computer program and other programs and data required by any device with data processing capabilities, and may also be used to temporarily store data that has been output or is to be output.

[0096] Although the embodiments of the present invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and variations may be made to these embodiments without departing from the principles and spirit of the present invention. The scope of the present invention is defined by the appended claims and their equivalents, and all should be included within the scope of protection of the present invention.

Claims

1. A ternary coal blending method, characterized in that: The following steps are involved: Step S1: Obtain parameters of the coal to be blended and perform data preprocessing; the parameters include the quantity, quality, coal rock component analysis characteristics, coal quality analysis characteristics, and screening float and sink pattern analysis characteristics data of the coal to be blended; Step S2: Establish a prediction model and set coal blending conditions according to production conditions; Step S3: According to the coal blending conditions, the activation coal feeder is controlled by adjusting the opening of the coal locking plate and the vibration frequency of the coal locking plate; Step S4: Obtain the flow rate, total amount, and ratio data of each type of coal in real time, determine whether there is an abnormal situation, and output the judgment data.

2. A ternary coal blending method according to claim 1, characterized in that: The specific steps in step S1 include: Step S11, obtaining various parameter data of the coal to be blended and preprocessing the collected data; Step S12: Establish a database and input the coal type parameter data in units of coal types.

3. The ternary coal blending method according to claim 1, characterized in that: The specific steps in step S2 include: Step S21: Obtain data from the database, remove abnormal values ​​and error values, and perform statistical analysis on the data; Step S22: establishing a prediction model between the quality of the blended coal and the quality indicators of each single type of coal; Step S23: Optimize the prediction model and test the prediction accuracy and reliability of the prediction model.

4. The ternary coal blending method according to claim 1, characterized in that: The specific steps in step S3 include: The activation coal feeder is controlled by adjusting the opening of the coal locking plate, and the opening range of the coal locking plate is controlled from 1% to 70% by closing the relay.

5. A ternary coal blending method according to claim 4, characterized in that: The specific steps in step S3 include: In the step of controlling the activated coal feeder by adjusting the opening of the coal locking plate and the vibration frequency of the coal locking plate according to the coal blending conditions, the method of controlling the activated coal feeder by adjusting the vibration frequency of the coal locking plate is as follows: The vibration frequency of the coal locking plate is controlled by adjusting the 4mA to 20mA current through the PLC programmable logic controller hardware. The control formula is: Where Kp is the proportional coefficient, Ti is the integral time constant, and Td is the differential time constant; Ki = Kp / Ti is the integral coefficient; Kd = Kp*Td is the differential coefficient, e is the percentage error expressed in the range, and dt is the update time used by the loop.

6. The ternary coal blending method according to claim 1, characterized in that: The specific steps in step S4 include: Step S41: using flow sensors at multiple coal bunker outlets and weight sensors on belt scales, collect data transmitted by each sensor; Step S42: Integrate the collected coal flow data and total amount data, and calculate the proportion data of various coals; Set the thresholds for flow, total volume, and ratio data respectively; Step S43: Compare the various coal flow data, total amount data, and proportion data of various coals with corresponding thresholds to determine whether there is any abnormality.

7. A ternary coal blending method according to claim 6, characterized in that: The specific steps of determining whether there is an abnormal situation and outputting the judgment data in step S4 include: When no abnormal situation occurs, various coal flow data, total amount data, and proportion data of various coals are processed into charts and output for visual display; When an abnormal situation occurs, an abnormal visual prompt is generated.

8. A system using a ternary coal blending method according to any one of claims 1 to 4, characterized in that: It includes data acquisition module, model building module, control module, and monitoring module; The data acquisition module is used to obtain parameters of the coal to be blended and perform data preprocessing; the parameters include the quantity, quality, coal rock component analysis characteristics, coal quality analysis characteristics, and screening float and sink pattern analysis characteristics data of the coal to be blended; The model building module is used to build a prediction model and set coal blending conditions according to production conditions; The control module is used to control the activated coal feeder by adjusting the opening of the coal locking plate and the vibration frequency of the coal locking plate according to the coal blending conditions; The monitoring module is used to obtain the flow rate, total amount, and proportion data of each type of coal in real time, determine whether there is an abnormal situation, and output the judgment data.

9. A device, characterized in that: Also includes: at least one processor; at least one memory for storing at least one program; When the at least one program is executed by the at least one processor, the at least one processor implements the ternary coal blending method as described in any one of claims 1 to 6.

10. A storage medium storing instructions executable by a processor, characterized in that: The processor-executable instructions are used to implement the ternary coal blending method as claimed in any one of claims 1 to 6 when executed by the processor.

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