Coal blending system automatic calculation method and system

Abstract

The present application relates to a kind of automatic coal blending system calculation method and system.Automatic coal blending system calculation method includes multiple coal real-time moisture detection, dry material quantity benchmark accounting, target wet coal flow backstepping, PLC fuzzy closed-loop flow regulation steps.The present application is by online microwave moisture meter real-time acquisition each single coal moisture content, with dry coal material as unified calculation benchmark accounting each bin target dry material quantity, combined with process target moisture content reverse conversion belt target wet coal flow;With flow deviation, bias change rate as double input PLC fuzzy controller dynamic adjustment belt speed, compensate belt slip, coal flow partial load, moisture fluctuation and other types of interference.The present application can improve dry basis control precision, flow regulation response speed is fast, coke ash, cold and hot intensity index fluctuation is greatly reduced, unqualified product rate is reduced;Only upgrade PLC program can be landed, without large-scale reconstruction field hardware, low cost of transformation, strong popularization, applicable to various coking enterprises coking automatic coal blending production.

Description

Technical Field

[0001] This invention relates to the field of automatic control technology for coking coal blending, and more specifically, to a precise automatic coal blending calculation and control method and system for coking that integrates online pre-moisture detection, dynamic calculation of dry material baseline, and PLC fuzzy closed-loop regulation. Background Technology

[0002] Coal blending is a core process in coking production that determines coke quality. Currently, most coking enterprises in China generally use the traditional fixed-value belt scale coal blending mode. The system directly uses the instantaneous flow rate of wet coal as the control benchmark and does not incorporate the real-time moisture fluctuation of raw coal into the closed-loop control calculation logic. This has resulted in multiple intractable technical defects in long-term production.

[0003] Moisture fluctuations cause severe inaccuracies in the dry basis blending ratio. The moisture content of coking coal varies from 8% to 15% depending on the origin, storage period, and washing process. Exposure to rain, air drying during storage, and watering during transportation further exacerbate moisture variations. Traditional coal blending only controls the amount of wet coal transported, ignoring the deviation in the actual proportion of dry coal caused by moisture differences. The dry basis blending ratio entering the furnace deviates from the process set value by more than 3%, directly altering core indicators such as ash content, sulfur content, and caking index of the blended coal.

[0004] Multiple disturbances on-site amplify flow control errors. During the operation of coal blending conveyor belts, common disturbances include belt slippage, uneven coal loading, uneven raw coal particle size, and momentary material interruption. Traditional setpoint control cannot dynamically compensate for these disturbances, resulting in a continuous deviation of the flow rate from the set value. Imbalanced blending ratios lead to significant fluctuations in the thermal properties of coke, increasing the product defect rate, and causing secondary production problems such as uneven heating of the coke oven walls, increased coke pushing resistance, and accelerated furnace wear.

[0005] Conventional PID control has poor adaptability and suffers from large regulation lag and overshoot. Coal blending systems are industrial control objects with large inertia, multiple disturbances, and pure time delay. Conventional linear PID algorithms rely solely on a single flow deviation for adjustment, resulting in slow response and large overshoot when faced with sudden changes in coal flow. They cannot quickly offset instantaneous coal flow disturbances and are difficult to achieve long-term, high-precision, and stable coal blending.

[0006] Existing coking coal blending control schemes only optimize belt weighing or single-bin speed regulation logic separately, lacking a complete integrated calculation and control scheme that covers the entire chain from real-time moisture collection, unified dry basis ratio calculation, reverse conversion of wet coal flow to intelligent closed-loop speed regulation. This cannot fundamentally eliminate the coal blending accuracy defects caused by both moisture and on-site disturbances. The industry urgently needs a low-cost, high-precision automatic coal blending calculation and control method that can be quickly upgraded and implemented. Summary of the Invention

[0007] The technical problem to be solved by this invention is that existing coking coal blending technologies suffer from strong interference from raw coal moisture content, low accuracy of dry basis blending control, sluggish flow regulation response, and weak anti-disturbance capability.

[0008] To solve the above-mentioned technical problems, according to one aspect of the present invention, an automatic coal blending system calculation method is provided, comprising the steps of: real-time moisture detection of multiple coal types, wherein online microwave moisture detectors are respectively installed at the discharge front end of each clean coal bin to collect the real-time moisture content R1, R2...R of n types of clean coal. n The moisture data is uploaded to the PLC control system in real time; the dry material quantity benchmark is calculated, and the dry basis ratios P1, P2...P of each single coal are preset in the PLC. n Given the total dry material quantity M per unit time, calculate the target dry material quantity D of the i-th type of refined coal per unit time. i The target wet coal flow rate is calculated by reverse calculation, based on the preset target moisture content R of the blended coal, and the target wet coal flow rate F of the i-th belt conveyor. i ; PLC fuzzy closed-loop flow regulation, adjusting the target wet coal flow rate F of each channel. i As the setpoint for the fuzzy controller, the belt weighing instrument collects the real-time wet coal flow rate, calculates the flow deviation e and the deviation change rate ec as dual inputs to the fuzzy controller, calls the coal blending-specific fuzzy rule library to complete the inference calculation, and outputs the frequency converter frequency adjustment signal to adjust the belt speed, dynamically compensate for on-site disturbances, and stabilize the actual conveying flow rate.

[0009] According to an embodiment of the present invention, in the real-time moisture detection step for multiple coal types, the moisture content of the clean coal is uploaded to the PLC control system as a 4-20mA analog signal.

[0010] According to an embodiment of the present invention, in the dry material quantity benchmark calculation step, formula D is used. i =P i Calculate the target dry matter quantity D per unit time for the i-th type of refined coal using ×M / 100. i .

[0011] According to an embodiment of the present invention, in the step of back-calculating the target wet coal flow rate, the formula F is used. i =D i ×100 / (100-R) Calculate the target wet coal flow rate F of the i-th belt conveyor in reverse. i .

[0012] According to an embodiment of the present invention, the PLC control system adopts a Siemens S7-400 series PLC.

[0013] According to an embodiment of the present invention, the online microwave moisture detector and the belt weighing instrument are both connected to the PLC via a 4-20mA analog input module.

[0014] According to an embodiment of the present invention, the fuzzy rule base is pre-tuned offline based on the large inertia and multiple disturbances of coking coal blending, and divides the fuzzy subsets of flow deviation and deviation change rate to limit the single frequency conversion adjustment amplitude to suppress flow overshoot.

[0015] According to an embodiment of the present invention, the entire computational control method is deployed simply by updating the PLC's internal control program, without the need to replace the belt conveyor, weighing instrument, or moisture detection hardware.

[0016] According to another aspect of the present invention, an automatic coal blending system calculation system is provided, comprising: a multi-coal real-time moisture detection module, used to install online microwave moisture detectors at the discharge front end of each clean coal bin to collect the real-time moisture content R1, R2...R of n types of clean coal. n The moisture data is uploaded to the PLC control system in real time; the dry material quantity benchmark calculation module is used to preset the dry basis ratio P1, P2...P of each single coal in the PLC. n Given the total dry material quantity M per unit time, calculate the target dry material quantity D of the i-th type of refined coal per unit time. i The target wet coal flow rate reverse calculation module is used to preset the target moisture content R of the blended coal and reversely calculate the target wet coal flow rate F of the i-th belt conveyor. i The PLC fuzzy closed-loop flow control module is used to adjust the target wet coal flow rate F of each channel. i As the setpoint for the fuzzy controller, the belt weighing instrument collects the real-time wet coal flow rate, calculates the flow deviation e and the deviation change rate ec as dual inputs to the fuzzy controller, calls the coal blending-specific fuzzy rule library to complete the inference calculation, and outputs the frequency converter frequency adjustment signal to adjust the belt speed, dynamically compensate for on-site disturbances, and stabilize the actual conveying flow rate.

[0017] According to an embodiment of the present invention, in the multi-coal type real-time moisture detection module, the moisture content of clean coal is uploaded to the PLC control system as a 4-20mA analog signal; in the dry material quantity benchmark calculation module, the moisture content is calculated using formula D. i =P i Calculate the target dry matter quantity D per unit time for the i-th type of refined coal using ×M / 100. i In the target wet coal flow rate back-calculation module, the formula F is used to calculate the flow rate. i =D i ×100 / (100-R) Calculate the target wet coal flow rate F of the i-th belt conveyor in reverse. i .

[0018] Compared with the prior art, the technical solution provided by the embodiments of the present invention can achieve at least the following beneficial effects:

[0019] This invention provides an automatic coal blending system calculation method that upgrades the existing PLC control system without requiring large-scale replacement of on-site hardware. Using dry-based coal as a unified calculation benchmark, and combining online real-time moisture detection and fuzzy closed-loop control, it achieves high-precision and stable control of the dry-based blending ratio, reducing coke quality fluctuations and improving the overall operational stability of the coking system. It is applicable to the continuous automated blending of multiple types of refined coal in the coking industry, and can stably control the dry-based blending ratio of the coal fed into the furnace, suppressing fluctuations in key coke quality indicators.

[0020] The automatic coal blending system calculation method and system of the present invention can significantly improve the accuracy of dry basis ratio control and completely eliminate moisture interference. This invention is the first to embed a unified dry basis calculation logic into the real-time closed-loop control of coal blending. Field measurements show that the accuracy of dry basis ratio control has improved from the traditional ±3% to within ±0.5%. Large fluctuations in raw coal moisture content of 8% to 15% will not change the actual dry coal ratio entering the furnace, thus solving the problem of coke index drift caused by moisture fluctuations at its source.

[0021] The automatic coal blending system calculation method and system of the present invention adopts dual-input fuzzy control to replace the traditional single-parameter PID linear regulation, which shortens the system flow regulation response time by 60% and controls the flow regulation overshoot within 2%. It can quickly offset random disturbances on site such as belt slippage, uneven coal flow, and instantaneous material interruption, and is suitable for complex industrial conditions with large lag and multiple disturbances in coal blending. Its intelligent automatic coal blending system calculation method has strong anti-disturbance capability and faster regulation speed.

[0022] After continuous production using the invented automatic coal blending system calculation method, the ash content fluctuation of coke is controlled within ±0.2%; the cold strength of coke M40 increases by more than 1%, while the abrasion resistance of M10 decreases by 0.5%; the defective product rate of coke decreases by more than 90%; at the same time, it stabilizes the parameters of the coal feed into the furnace, balances the heating conditions of the coke oven, reduces coke pushing failures, extends the service life of the coke oven masonry, and reduces production and maintenance costs. This significantly improves the stability of coke product quality and reduces production losses.

[0023] The automatic coal blending system calculation method and system of the present invention have low transformation costs, short implementation cycle, and strong applicability. The entire solution only requires upgrading and optimizing the existing PLC control program of the coking plant, without the need for large-scale replacement of belt conveyors, weighing, and detection hardware. Small, medium and large coking production lines can be quickly and cost-effectively transformed, and it has extremely high industrial popularization and promotion value. Attached Figure Description

[0024] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings of the embodiments will be briefly described below. Obviously, the drawings described below only relate to some embodiments of the present invention and are not intended to limit the present invention.

[0025] Figure 1 This is a schematic diagram illustrating the calculation method of an automatic coal blending system according to an embodiment of the present invention. Detailed Implementation

[0026] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the described embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0027] Unless otherwise defined, the technical or scientific terms used herein shall have the ordinary meaning as understood by one of ordinary skill in the art to which this invention pertains. The terms “first,” “second,” and similar terms used in the specification and claims of this patent application do not indicate any order, quantity, or importance, but are merely used to distinguish different components. Similarly, the terms “an” or “a” and similar terms do not indicate a limitation of quantity, but rather indicate the presence of at least one.

[0028] Figure 1 This is a schematic diagram illustrating the calculation method of an automatic coal blending system according to an embodiment of the present invention.

[0029] like Figure 1 As shown, the calculation method of the automatic coal blending system includes the following steps: real-time moisture detection of multiple coal types, dry material quantity benchmark calculation, target wet coal flow rate back calculation, and PLC fuzzy closed-loop flow rate adjustment.

[0030] Real-time moisture detection for multiple coal types: Online microwave moisture detectors are installed at the discharge front end of each clean coal bin to collect real-time moisture content R1, R2...R of n types of clean coal. n The moisture data is uploaded to the PLC control system in real time, enabling uninterrupted real-time collection of moisture content for each coal, providing real-time basic data for subsequent dry basis conversion.

[0031] Dry material quantity benchmark calculation, the dry basis ratio of each single coal P1, P2...P is preset in the PLC. n Given the total dry material quantity M per unit time, calculate the target dry material quantity D of the i-th type of refined coal per unit time. i This step uniformly locks all coal blending calculations to dry, moisture-free coal, completely isolating the interference of raw coal moisture fluctuations on the blending calculation results.

[0032] The target wet coal flow rate is calculated by back-calculating the target wet coal flow rate F of the i-th belt conveyor, with a preset target moisture content R for the blended coal. iThis step unifies and controls the overall moisture content of all coal types after blending, stabilizes the overall moisture content of the blended coal, and eliminates the problem of uncontrolled overall moisture content in the blended coal caused by differences in the moisture content of different individual coal types.

[0033] PLC fuzzy closed-loop flow regulation will adjust the target wet coal flow rate F of each channel. i As the setpoint for the fuzzy controller, the belt weighing instrument collects the real-time wet coal flow rate, calculates the flow deviation e and the deviation change rate ec as dual inputs to the fuzzy controller, calls the coal blending-specific fuzzy rule library to complete the inference calculation, and outputs the frequency converter frequency adjustment signal to adjust the belt speed; continuously and dynamically compensates for field disturbances such as belt slippage, coal flow imbalance, particle size unevenness, and instantaneous material interruption, and stably controls the actual wet coal flow rate within the target allowable error range, dynamically compensates for field disturbances, and stabilizes the actual conveying flow rate.

[0034] The automatic coal blending system calculation method and system of the present invention adopts dual-input fuzzy control to replace the traditional single-parameter PID linear regulation, which shortens the system flow regulation response time by 60% and controls the flow regulation overshoot within 2%. It can quickly offset random disturbances on site such as belt slippage, uneven coal flow, and instantaneous material interruption, and is suitable for complex industrial conditions with large lag and multiple disturbances in coal blending. Its intelligent automatic coal blending system calculation method has strong anti-disturbance capability and faster regulation speed.

[0035] According to one or more embodiments of the present invention, in the real-time moisture detection step for multiple coal types, the moisture content of the clean coal is uploaded to the PLC control system as a 4-20mA analog signal.

[0036] According to one or more embodiments of the present invention, in the dry material quantity benchmark calculation step, formula D is used. i =P i Calculate the target dry matter quantity D per unit time for the i-th type of refined coal using ×M / 100. i In the formula: D i Let P be the target dry material quantity per unit time for the i-th type of refined coal; i is the dry basis ratio of the i-th type of clean coal; M is the total dry material quantity per unit time of the system.

[0037] According to one or more embodiments of the present invention, in the target wet coal flow rate back-calculation step, the formula F is used. i =D i ×100 / (100-R) Calculate the target wet coal flow rate F of the i-th belt conveyor in reverse. i In the formula: F i D represents the target wet coal flow rate of the i-th conveyor belt; i R represents the target dry material quantity per unit time for the i-th type of clean coal; R represents the target moisture content of the blended coal process.

[0038] According to one or more embodiments of the present invention, the PLC control system adopts a Siemens S7-400 series PLC.

[0039] According to one or more embodiments of the present invention, the online microwave moisture detector and the belt weighing instrument are both connected to the PLC through a 4-20mA analog input module.

[0040] According to one or more embodiments of the present invention, the fuzzy rule base is pre-tuned offline based on the large inertia and multiple disturbances of coking coal blending, and divides the fuzzy subsets of flow deviation and deviation change rate to limit the single frequency conversion adjustment amplitude to suppress flow overshoot.

[0041] According to one or more embodiments of the present invention, the entire computational control method is deployed simply by updating the PLC's internal control program, without the need to replace the belt conveyor, weighing instrument, or moisture detection hardware.

[0042] The automatic coal blending system calculation method and system of the present invention can significantly improve the accuracy of dry basis ratio control and completely eliminate moisture interference. This invention is the first to embed a unified dry basis calculation logic into the real-time closed-loop control of coal blending. Field measurements show that the accuracy of dry basis ratio control has improved from the traditional ±3% to within ±0.5%. Large fluctuations in raw coal moisture content of 8% to 15% will not change the actual dry coal ratio entering the furnace, thus solving the problem of coke index drift caused by moisture fluctuations at its source.

[0043] According to another aspect of the present invention, an automatic coal blending system calculation system is provided, which includes: a multi-coal type real-time moisture detection module, a dry material quantity benchmark calculation module, a target wet coal flow rate back-calculation module, and a PLC fuzzy closed-loop flow regulation module.

[0044] The multi-coal-type real-time moisture detection module is used to install online microwave moisture detectors at the discharge front end of each clean coal bin to collect the real-time moisture content R1, R2...R of n types of clean coal. n The moisture data is then uploaded to the PLC control system in real time.

[0045] The dry material quantity benchmark calculation module is used to preset the dry basis ratios P1, P2...P of each single coal in the PLC. n Given the total dry material quantity M per unit time, calculate the target dry material quantity D of the i-th type of refined coal per unit time. i .

[0046] The target wet coal flow rate reverse calculation module is used to preset the target moisture content R of the blended coal and reverse calculate the target wet coal flow rate F of the i-th belt conveyor. i .

[0047] The PLC fuzzy closed-loop flow control module is used to adjust the target wet coal flow rate F of each path. iAs the setpoint for the fuzzy controller, the belt weighing instrument collects the real-time wet coal flow rate, calculates the flow deviation e and the deviation change rate ec as dual inputs to the fuzzy controller, calls the coal blending-specific fuzzy rule library to complete the inference calculation, and outputs the frequency converter frequency adjustment signal to adjust the belt speed, dynamically compensate for on-site disturbances, and stabilize the actual conveying flow rate.

[0048] This invention provides an automatic coal blending system calculation method that upgrades the existing PLC control system without requiring large-scale replacement of on-site hardware. Using dry-based coal as a unified calculation benchmark, and combining online real-time moisture detection and fuzzy closed-loop control, it achieves high-precision and stable control of the dry-based blending ratio, reducing coke quality fluctuations and improving the overall operational stability of the coking system. It is applicable to the continuous automated blending of multiple types of refined coal in the coking industry, and can stably control the dry-based blending ratio of the coal fed into the furnace, suppressing fluctuations in key coke quality indicators.

[0049] According to one or more embodiments of the present invention, in the multi-coal real-time moisture detection module, the moisture content of clean coal is uploaded to the PLC control system as a 4-20mA analog signal; in the dry material quantity benchmark calculation module, the moisture content is calculated using formula D. i =P i Calculate the target dry matter quantity D per unit time for the i-th type of refined coal using ×M / 100. i In the target wet coal flow rate back-calculation module, the formula F is used to calculate the flow rate. i =D i ×100 / (100-R) Calculate the target wet coal flow rate F of the i-th belt conveyor in reverse. i .

[0050] The automatic coal blending system calculation method and system of the present invention have low transformation costs, short implementation cycle, and strong applicability. The entire solution only requires upgrading and optimizing the existing PLC control program of the coking plant, without the need for large-scale replacement of belt conveyors, weighing, and detection hardware. Small, medium and large coking production lines can be quickly and cost-effectively transformed, and it has extremely high industrial popularization and promotion value.

[0051] The technical solution of the present invention will be described in detail below with reference to specific production embodiments, but the scope of protection of the present invention is not limited to this embodiment.

[0052] A metallurgical coke production enterprise with an annual capacity of 600,000 tons has a coal blending system with four coking coal silos. It uses a blend of four types of coking coal to produce first-grade metallurgical coke. The implementation steps of the automatic coal blending system calculation method of this invention are as follows:

[0053] 1. Implementation of real-time moisture detection for multiple coal types

[0054] Online microwave moisture detectors were installed at the discharge ports of coal bins #1, #2, #3, and #4. The detection signals were connected to the main Siemens S7-400 PLC in the plant area. During a stable production period, the moisture content of the four coal bins was collected in real time: R1=10.2%, R2=9.7%, R3=11.5%, and R4=8.9%. The moisture data was refreshed and uploaded to the PLC every second.

[0055] 2. Implementation of Dry Material Quantity Benchmark Calculation

[0056] Based on the first-level metallurgical coke process standard, four dry basis ratios of clean coal are preset in the PLC program: P1=30%, P2=25%, P3=25%, P4=20%; the total dry material quantity per unit hour of the system is set to M=120t / h, and the target dry material quantity is calculated line by line using the dry material quantity calculation formula:

[0057] D1 = (30 × 120) / 100 = 36 t / h

[0058] D2 = (25 × 120) / 100 = 30 t / h

[0059] D3 = (25 × 120) / 100 = 30 t / h

[0060] D4 = (20 × 120) / 100 = 24 t / h

[0061] 3. Implementation of target wet coal flow rate backwards

[0062] The coking process specifies a target moisture content R=10% for the blended coal. The target dry material quantity for each bin is then substituted into the wet coal flow rate conversion formula to deduce the set wet coal flow rate for each conveyor belt.

[0063] F1 = (36 × 100) / (100 - 10) = 40 t / h

[0064] F2=(30×100) / (100-10)≈33.3t / h

[0065] F3=(30×100) / (100-10)≈33.3t / h

[0066] F4=(24×100) / (100-10)≈26.7t / h

[0067] 4. Implementation of PLC fuzzy closed-loop flow regulation

[0068] The four target wet coal flow rates F1, F2, F3, and F4 are imported into the PLC's built-in fuzzy control module as control setpoints; the four belt scales continuously collect real-time wet coal flow rates, and the controller synchronously calculates the single-channel flow rate deviation e and deviation change rate ec; the fuzzy rule library pre-built for coal blending conditions is retrieved, and the frequency adjustment signals of the four belt conveyor inverters are output through fuzzy inference calculation to dynamically adjust the speed and compensate for various on-site disturbances.

[0069] Continuous 72-hour uninterrupted stable production verification: The actual wet coal flow deviation of the four conveyor belts was consistently controlled within ±0.3t / h; the ash content of the produced coke was stable within the range of 12.3% to 12.5%, the average M40 cold strength was 88.2%, and all indicators met the technical standards for first-grade metallurgical coke; compared with the traditional PID fixed-value coal blending mode before the transformation, the rate of unqualified coke quality decreased by more than 90%, the frequency of coke oven pushing failures was significantly reduced, and the overall production efficiency was greatly improved.

[0070] After continuous production using the invented automatic coal blending system calculation method, the ash content fluctuation of coke is controlled within ±0.2%; the cold strength of coke M40 increases by more than 1%, while the abrasion resistance of M10 decreases by 0.5%; the defective product rate of coke decreases by more than 90%; at the same time, it stabilizes the parameters of the coal feed into the furnace, balances the heating conditions of the coke oven, reduces coke pushing failures, extends the service life of the coke oven masonry, and reduces production and maintenance costs. This significantly improves the stability of coke product quality and reduces production losses.

[0071] The above description is merely an exemplary embodiment of the present invention and is not intended to limit the scope of protection of the present invention, which is determined by the appended claims.

Claims

1. A calculation method for an automatic coal blending system, wherein, Includes the following steps: Real-time moisture detection for multiple coal types: Online microwave moisture detectors are installed at the discharge front end of each clean coal bin to collect real-time moisture content R1, R2...R of n types of clean coal. n The moisture data is then uploaded to the PLC control system in real time. Dry material quantity benchmark calculation, the dry basis ratio of each single coal P1, P2...P is preset in the PLC. n Given the total dry material quantity M per unit time, calculate the target dry material quantity D of the i-th type of refined coal per unit time. i ; The target wet coal flow rate is calculated by back-calculating the target wet coal flow rate F of the i-th belt conveyor, with a preset target moisture content R for the blended coal. i ; PLC fuzzy closed-loop flow regulation will adjust the target wet coal flow rate F of each channel. i As the setpoint for the fuzzy controller, the belt weighing instrument collects the real-time wet coal flow rate, calculates the flow deviation e and the deviation change rate ec as dual inputs to the fuzzy controller, calls the coal blending-specific fuzzy rule library to complete the inference calculation, and outputs the frequency converter frequency adjustment signal to adjust the belt speed, dynamically compensate for on-site disturbances, and stabilize the actual conveying flow rate.

2. The calculation method for the automatic coal blending system as described in claim 1, wherein, In the real-time moisture detection step for multiple coal types, the moisture content of clean coal is uploaded to the PLC control system as a 4-20mA analog signal.

3. The calculation method for the automatic coal blending system as described in claim 1, wherein, In the dry material quantity benchmark calculation step, formula D is used. i =P i Calculate the target dry matter quantity D per unit time for the i-th type of refined coal using ×M / 100. i .

4. The calculation method for the automatic coal blending system as described in claim 1, wherein, In the back-calculation step of the target wet coal flow rate, the formula F is used. i =D i ×100 / (100-R) Calculate the target wet coal flow rate F of the i-th belt conveyor in reverse. i .

5. The calculation method for the automatic coal blending system as described in claim 1, wherein, The PLC control system uses a Siemens S7-400 series PLC.

6. The calculation method for the automatic coal blending system as described in claim 1, wherein, The online microwave moisture analyzer and belt weighing instrument are both connected to the PLC via a 4-20mA analog input module.

7. The calculation method for the automatic coal blending system as described in claim 1, wherein, The fuzzy rule base is pre-tuned offline based on the large inertia and multiple disturbances of coking coal blending, and divides the fuzzy subsets of flow deviation and deviation change rate to limit the single frequency conversion adjustment amplitude to suppress flow overshoot.

8. The calculation method for the automatic coal blending system as described in claim 1, wherein, The entire computational control method can be deployed simply by updating the PLC's internal control program, without needing to replace the belt conveyor, weighing instrument, or moisture detection hardware.

9. A calculation system for an automatic coal blending system, wherein, include: The multi-coal-type real-time moisture detection module is used to install online microwave moisture detectors at the discharge front end of each clean coal bin to collect the real-time moisture content R1, R2...R of n types of clean coal. n The moisture data is then uploaded to the PLC control system in real time. The dry material quantity benchmark calculation module is used to preset the dry basis ratios P1, P2...P for each single coal in the PLC. n Given the total dry material quantity M per unit time, calculate the target dry material quantity D of the i-th type of refined coal per unit time. i ; The target wet coal flow rate reverse calculation module is used to preset the target moisture content R of the blended coal and reverse calculate the target wet coal flow rate F of the i-th belt conveyor. i ; The PLC fuzzy closed-loop flow control module is used to adjust the target wet coal flow rate F of each channel. i As the setpoint for the fuzzy controller, the belt weighing instrument collects the real-time wet coal flow rate, calculates the flow deviation e and the deviation change rate ec as dual inputs to the fuzzy controller, calls the coal blending-specific fuzzy rule library to complete the inference calculation, and outputs the frequency converter frequency adjustment signal to adjust the belt speed, dynamically compensate for on-site disturbances, and stabilize the actual conveying flow rate.

10. The automatic coal blending system calculation system as described in claim 1, wherein, In the multi-coal type real-time moisture detection module, the moisture content of clean coal is uploaded to the PLC control system as a 4-20mA analog signal; in the dry material quantity benchmark calculation module, the moisture content is calculated using formula D. i =P i Calculate the target dry matter quantity D per unit time for the i-th type of refined coal using ×M / 100. i In the target wet coal flow rate back-calculation module, the formula F is used to calculate the flow rate. i =D i ×100 / (100-R) Calculate the target wet coal flow rate F of the i-th belt conveyor in reverse. i .

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