A water content feedforward model control method and device and storage medium

Abstract

The application discloses a moisture content feedforward model control method, device and storage medium in the technical field of moisture control of a cut tobacco dryer, and the method comprises the following steps: calculating an HT water adding prediction value according to a total moisture content change prediction value and a cut tobacco dryer dewatering capacity average value, calculating an HT steam set flow correction value according to the HT water adding prediction value and an HT water adding capacity average value; calculating an HT adjusting flow by superimposing a preset HT set flow value and the HT steam set flow correction value, and adjusting the HT based on the HT adjusting flow; calculating a cut tobacco dryer moisture removal setting correction value based on a cut tobacco dryer dewatering prediction value; calculating a cut tobacco dryer moisture removal adjusting value by superimposing a cut tobacco dryer moisture removal setting value and the cut tobacco dryer moisture removal setting correction value, and adjusting the cut tobacco dryer based on the cut tobacco dryer moisture removal adjusting value. The application can solve the technical problem that the traditional control method is affected by production due to the regulation lag or excessive regulation under the condition that the incoming material moisture fluctuates greatly.

Description

Technical Field

[0001] This invention relates to the field of moisture control technology at the outlet of a yarn drying machine, and in particular to a method, device, and storage medium for moisture content feedforward model control. Background Technology

[0002] The traditional control method of the drying machine in the filament processing workshop of a certain factory is based on the negative feedback PID control of the outlet moisture. The controlled object is the exhaust air volume. When the moisture changes, the moisture PID output directly controls the opening of the exhaust damper. Although this control method responds quickly to changes in outlet moisture, it is prone to adjustment lag or over-adjustment when the moisture of the incoming material fluctuates greatly (mainly during the process of changing the incoming material container). This leads to process oscillation, which cannot be corrected by automatic control in a short time and often requires manual intervention by the operator.

[0003] Therefore, there is an urgent need for a water content feedforward model control method, device, and storage medium to solve the above-mentioned technical problems. Summary of the Invention

[0004] The purpose of this invention is to overcome the shortcomings of the prior art and provide a moisture content feedforward model control method, device and storage medium, which can solve the technical problem that traditional control methods are prone to adjustment lag or over-adjustment when the moisture content of the incoming material fluctuates greatly, thereby affecting production.

[0005] To achieve the above objectives, the present invention is implemented using the following technical solution:

[0006] In a first aspect, the present invention provides a water content feedforward model control method, comprising:

[0007] Acquire first real-time data and historical data;

[0008] The overall moisture content change prediction value is calculated based on the first real-time data. The average dewatering capacity of the drying machine and the average water addition capacity of the HT are calculated based on the historical data within the set period. The HT water addition prediction value is calculated based on the overall moisture content change prediction value and the average dewatering capacity of the drying machine. The HT steam set flow correction value is calculated based on the HT water addition prediction value and the average HT water addition capacity.

[0009] The HT regulating flow rate is calculated by superimposing the preset HT set flow rate value and the HT steam set flow rate correction value, and the HT is regulated based on the HT regulating flow rate.

[0010] Obtain the second real-time data after HT adjustment, calculate the predicted value of dehydration of the drying machine based on the second real-time data, and calculate the moisture removal setting correction value of the drying machine based on the predicted value of dehydration of the drying machine and the average value of dehydration capacity of the drying machine within a set period.

[0011] The moisture removal setting value of the drying machine is calculated by superimposing the moisture removal setting correction value of the drying machine output by the moisture PID controller, and the drying machine is adjusted based on the moisture removal adjustment value.

[0012] Furthermore, calculating the predicted value of overall moisture content change based on the first real-time data includes:

[0013] ,

[0014] in, The total moisture content is the predicted value, W is the material weight measured in advance, M1 is the initial material moisture value, and Msp is the moisture setting value at the outlet of the drying machine.

[0015] Furthermore, the calculation of the average dewatering capacity of the drying machine and the average water addition capacity of the HT within the set period based on the historical data includes:

[0016] ,

[0017] ,

[0018] in, The average dehydration capacity of the drying machine is given by , and W is the pre-measured weight of the material. This represents the real-time material flow rate n seconds ago. This represents the moisture content of the HT inlet material n seconds ago. This represents the moisture content of the material at the feed trough of the filament drying machine n seconds ago. This represents the moisture content of the material in the discharge trough of the filament drying machine n seconds ago. This represents the average water-adding capacity of HT. M1 represents the number of data sampling points, and M1 represents the initial material moisture content. This refers to the moisture content of the material at the feed trough of the filament drying machine. This refers to the moisture content of the material at the discharge trough of the filament drying machine.

[0019] Furthermore, the calculation of the predicted HT water addition value based on the overall moisture content change prediction and the average dewatering capacity of the drying machine includes:

[0020] Subtract the predicted value of the overall moisture content change from the average dehydration capacity of the drying machine to obtain the predicted value of HT water addition;

[0021] The correction value for the HT steam set flow rate is calculated based on the predicted HT water supply value and the average HT water supply capacity, including:

[0022] The predicted HT water supply value is subtracted from the average HT water supply capacity to obtain the HT water supply capacity deviation value. Based on the HT water supply capacity deviation value, the preset first weighting coefficient is multiplied to obtain the HT steam set flow correction value.

[0023] Furthermore, the regulation of HT based on the HT regulating flow rate includes:

[0024] When the HT adjustable flow rate is within the upper and lower threshold range preset by the process standard, the HT adjustable flow rate is confirmed as the final HT set flow rate; when the HT adjustable flow rate is not within the upper and lower threshold range preset by the process standard, the preset upper and lower thresholds are confirmed as the final HT set flow rate.

[0025] The difference between the predicted HT actual flow rate and the final HT set flow rate is obtained. The HT steam flow rate is adjusted by the HT steam flow control PID based on the HT difference to regulate the opening of the steam diaphragm valve and thus regulate the HT steam flow rate.

[0026] Furthermore, calculating the predicted dewatering value of the drying machine based on the second real-time data includes:

[0027] ,

[0028] in, Here, W represents the predicted dehydration value for the drying machine, W is the pre-measured material weight, and M1 is the initial material moisture content. Msp represents the moisture content of the material at the feed trough of the drying machine, while Msp represents the moisture setting at the outlet of the drying machine.

[0029] Furthermore, based on the predicted dehydration value of the drying machine and the average dehydration capacity of the drying machine within a set period, the moisture removal setting correction value of the drying machine is calculated, including:

[0030] Subtract the predicted dehydration value of the drying machine from the average dehydration capacity of the drying machine to obtain the dehydration capacity deviation value of the drying machine. Multiply the dehydration capacity deviation value of the drying machine by the preset second weighting coefficient to obtain the moisture removal setting correction value of the drying machine.

[0031] Adjusting the filament drying machine based on the aforementioned moisture removal adjustment value includes:

[0032] The actual exhaust air volume of the predicted amount and the exhaust air difference value of the drying machine are obtained. The exhaust air volume is adjusted by the exhaust PID controller based on the exhaust air difference value to adjust the opening of the exhaust damper actuator.

[0033] In a second aspect, the present invention provides a water content feedforward model control device, comprising:

[0034] The data acquisition module is used to acquire first real-time data and historical data;

[0035] The HT steam set flow correction value calculation module is used to calculate the overall moisture content change prediction value based on the first real-time data, calculate the average dewatering capacity of the drying machine and the average HT water addition capacity within the set period based on the historical data, calculate the HT water addition prediction value based on the overall moisture content change prediction value and the average dewatering capacity of the drying machine, and calculate the HT steam set flow correction value based on the HT water addition prediction value and the average HT water addition capacity.

[0036] The HT regulation module is used to calculate the HT regulation flow rate based on the preset HT set flow rate value and the HT steam set flow rate correction value, and to regulate the HT based on the HT regulation flow rate.

[0037] The dehumidification setting correction value calculation module for the drying machine is used to obtain the second real-time data after HT adjustment, calculate the dehydration prediction value of the drying machine based on the second real-time data, and calculate the dehumidification setting correction value of the drying machine based on the dehydration prediction value of the drying machine and the average dehydration capacity of the drying machine within the set period.

[0038] The drying machine adjustment module is used to calculate the drying machine moisture removal adjustment value based on the drying machine moisture removal set value output by the moisture PID controller and the drying machine moisture removal set correction value, and to adjust the drying machine based on the drying machine moisture removal adjustment value.

[0039] Thirdly, the present invention provides an electronic terminal, including a processor and a memory connected to the processor, wherein a computer program is stored in the memory, and when the computer program is executed by the processor, the steps of the method described in any of the preceding claims are performed.

[0040] Fourthly, the present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of any of the methods described above.

[0041] Compared with the prior art, the beneficial effects achieved by the present invention are as follows:

[0042] When the moisture content of the incoming material changes significantly, the flow regulation capability of HT is first adjusted through model calculations to compensate for the difference in moisture content of the material at the inlet of the drying machine. Then, by analyzing the changes in moisture content of the material at the inlet of the drying machine, an instantaneous dehumidification setting correction value is provided to adjust the dehumidification volume and compensate for the lag in moisture negative feedback. This achieves feedforward predictive model control based on historical and real-time data. Through two-stage adjustment of HT steam flow and dehumidification air volume, the accuracy of moisture control at the drying machine outlet is optimized, avoiding adjustment lag and over-adjustment, achieving automatic correction, reducing manual intervention, and ultimately improving product quality. Attached Figure Description

[0043] Figure 1This is a flowchart of a water content feedforward model control method provided in an embodiment of the present invention;

[0044] Figure 2 This is a control logic diagram of a water content feedforward model control method provided in an embodiment of the present invention;

[0045] Figure 3 This is a framework diagram of the water content feedforward model in a water content feedforward model control method provided in an embodiment of the present invention. Detailed Implementation

[0046] The technical solution of the present invention will be described in detail below with reference to the accompanying drawings and specific embodiments. It should be understood that the embodiments and specific features in the embodiments are detailed descriptions of the technical solution of the present application, rather than limitations thereof. In the absence of conflict, the embodiments and technical features in the embodiments can be combined with each other.

[0047] In this article, the term "and / or" is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. Additionally, the character " / " in this article generally indicates that the preceding and following related objects have an "or" relationship.

[0048] HT, Humidification Tunnel, is a specialized device used for humidifying and re-moistening materials. It is mainly used in tobacco, food processing and other fields. It is existing technology and will not be described in detail here.

[0049] Example 1:

[0050] Figure 1 This is a flowchart of the water content feedforward model control method in Embodiment 1 of the present invention. This flowchart only illustrates the logical sequence of the method described in this embodiment. Provided there are no conflicts, different methods may be used in other possible embodiments of the present invention. Figure 1 Complete the steps shown or described in the order indicated.

[0051] The water content feedforward model control method provided in this embodiment can be applied to a terminal and can be executed by a mechanical equipment fault identification device. This device can be implemented in software and / or hardware and can be integrated into the terminal, such as any smartphone, tablet, or computer device with communication capabilities. See also... Figures 1 to 3 As shown, the method in this embodiment specifically includes the following steps:

[0052] Step 1: Obtain the first real-time data and historical data. Before obtaining the first real-time data and historical data, in order to ensure the sufficiency and accuracy of data resources in the data pool, it is possible to first determine whether the "cumulative production kilograms" of the current production batch exceeds the preset value. If it exceeds the preset value, the control method will be executed.

[0053] Step 2: Calculate the predicted value of overall water content change based on the first real-time data, including:

[0054] (Appendix) Figure 3 Formula 1 in the text

[0055] in, The total moisture content is the predicted value, W is the material weight measured in advance, M1 is the material moisture value detected by the moisture meter at the beginning, and Msp is the moisture set value at the outlet of the drying machine.

[0056] The average dehydration capacity of the drying machine and the average water addition capacity of HT within the set period are calculated based on the historical data, including:

[0057] (Appendix) Figure 3 Formula 2 in the text.

[0058] (Appendix) Figure 3 Formula 3 in the text.

[0059] in, The average dehydration capacity of the drying machine is given by , and W is the pre-measured weight of the material. This represents the real-time material flow rate n seconds ago. This represents the moisture content of the HT inlet material n seconds ago. This represents the moisture content of the material at the feed trough of the filament drying machine n seconds ago. This represents the moisture content of the material in the discharge trough of the filament drying machine n seconds ago. This represents the average water-adding capacity of HT. M1 represents the number of data sampling points, and M1 represents the initial material moisture content. This refers to the moisture content of the material at the feed trough of the filament drying machine. The moisture content of the material at the discharge chute of the filament drying machine;

[0060] The predicted value of the overall moisture content change is subtracted from the average dehydration capacity of the drying machine to obtain the predicted value of HT water addition. The predicted value of HT water addition is subtracted from the average HT water addition capacity to obtain the deviation value of HT water addition capacity. The deviation value of HT water addition capacity is multiplied by a preset first weighting coefficient to obtain the correction value of HT steam set flow rate.

[0061] Step 3: Calculate the HT regulating flow rate by superimposing the preset HT set flow rate value and the HT steam set flow rate correction value. HT regulation based on the HT regulating flow rate includes:

[0062] When the HT adjustable flow rate is within the upper and lower threshold range preset by the process standard, the HT adjustable flow rate is confirmed as the final HT set flow rate; when the HT adjustable flow rate is not within the upper and lower threshold range preset by the process standard, the preset upper and lower thresholds are confirmed as the final HT set flow rate.

[0063] It should be noted that there are two situations in which the preset upper and lower thresholds are confirmed as the final HT set flow rate: when the HT adjustment flow rate is higher than the upper threshold preset by the process standard, the upper threshold is used as the final HT set flow rate; when the HT adjustment flow rate is lower than the lower threshold preset by the process standard, the lower threshold is used as the final HT set flow rate.

[0064] The difference between the predicted HT actual flow rate and the final HT set flow rate is obtained. The HT steam flow rate is adjusted by the HT steam flow control PID based on the HT difference to regulate the opening of the steam diaphragm valve and thus regulate the HT steam flow rate.

[0065] Step 4: Obtain the second real-time data after HT adjustment, and calculate the predicted dewatering value of the drying machine based on the second real-time data, including:

[0066] (Appendix) Figure 3 Formula 4 in the middle).

[0067] in, Here, W represents the predicted dehydration value for the drying machine, W is the pre-measured material weight, and M1 is the initial moisture content detected by the moisture meter. Msp is the moisture content of the material at the feed trough of the drying machine, and Msp is the moisture setting value at the outlet of the drying machine.

[0068] Based on the predicted dehydration value of the drying machine and the average dehydration capacity of the drying machine within a set period, the moisture removal setting correction value of the drying machine is calculated as follows:

[0069] The dehydration prediction value of the drying machine is subtracted from the average dehydration capacity of the drying machine to obtain the dehydration capacity deviation value of the drying machine. Based on the dehydration capacity deviation value of the drying machine and the preset second weighting coefficient, the moisture removal setting correction value of the drying machine is obtained.

[0070] Step 5: As attached Figure 2 As shown, the dehumidification adjustment value of the drying machine is calculated by superimposing the dehumidification setpoint output by the moisture PID controller and the dehumidification setpoint correction value of the drying machine. Based on the dehumidification adjustment value of the drying machine (i.e., attached...) Figure 2 The moisture regulation value in the appendix Figure 2Due to image size limitations, this is abbreviated as moisture control value. This completes the adjustment of the yarn drying machine.

[0071] The actual exhaust air volume of the predicted amount and the exhaust air difference value of the drying machine are obtained. The exhaust air volume is adjusted by the exhaust PID controller based on the exhaust air difference value to adjust the opening of the exhaust damper actuator.

[0072] Furthermore, adjusting the exhaust air volume will cause a change in the moisture content of the material at the outlet. The changed moisture content is detected by a moisture meter and input into a comparator. The comparator calculates the difference between the set moisture content at the outlet and the changed moisture content to obtain the moisture content difference value. The moisture content difference value is input into the moisture PID controller to obtain the dehumidification set value of the drying machine. It should be noted that this part is based on the specific application of the output results of this patent combined with existing technology. Controls outside the control model (such as PID loops, etc.) are all existing technologies and will not be described in detail.

[0073] Example 2:

[0074] Embodiment 2 of the present invention provides a water content feedforward model control device, comprising:

[0075] The data acquisition module is used to acquire first real-time data and historical data;

[0076] The HT steam set flow correction value calculation module is used to calculate the overall moisture content change prediction value based on the first real-time data, calculate the average dewatering capacity of the drying machine and the average HT water addition capacity within the set period based on the historical data, calculate the HT water addition prediction value based on the overall moisture content change prediction value and the average dewatering capacity of the drying machine, and calculate the HT steam set flow correction value based on the HT water addition prediction value and the average HT water addition capacity.

[0077] The HT regulation module is used to calculate the HT regulation flow rate based on the preset HT set flow rate value and the HT steam set flow rate correction value, and to regulate the HT based on the HT regulation flow rate.

[0078] The dehumidification setting correction value calculation module for the drying machine is used to obtain the second real-time data after HT adjustment, calculate the dehydration prediction value of the drying machine based on the second real-time data, and calculate the dehumidification setting correction value of the drying machine based on the dehydration prediction value of the drying machine and the average dehydration capacity of the drying machine within the set period.

[0079] The drying machine adjustment module is used to calculate the drying machine moisture removal adjustment value based on the drying machine moisture removal set value output by the moisture PID controller and the drying machine moisture removal set correction value, and to adjust the drying machine based on the drying machine moisture removal adjustment value.

[0080] The water content feedforward model control provided in Embodiment 2 of the present invention can execute the water content feedforward model control method provided in Embodiment 1 of the present invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0081] Example 3:

[0082] Embodiment 3 of the present invention also provides an electronic terminal, including a processor and a memory connected to the processor, wherein a computer program is stored in the memory, and the processor is used to perform operations according to the instructions to execute the steps of the method described in Embodiment 1.

[0083] The electronic terminal provided in Embodiment 3 of the present invention can execute the water content feedforward model control method provided in Embodiment 1 of the present invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0084] Example 4:

[0085] Embodiment 4 of the present invention also provides a computer-readable storage medium storing a computer program thereon. When the computer program is executed by a processor, it implements the steps of the method described in Embodiment 1, and has the corresponding functional modules and beneficial effects of the method.

[0086] Those skilled in the art will understand that embodiments of this application can be provided as methods, apparatus, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0087] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (devices), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0088] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0089] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0090] The above description is only a preferred embodiment of the present invention. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the technical principles of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A water content feedforward model control method, characterized in that, include: Acquire first real-time data and historical data; The overall moisture content change prediction value is calculated based on the first real-time data. The average dewatering capacity of the drying machine and the average water addition capacity of the HT are calculated based on the historical data within the set period. The HT water addition prediction value is calculated based on the overall moisture content change prediction value and the average dewatering capacity of the drying machine. The HT steam set flow correction value is calculated based on the HT water addition prediction value and the average HT water addition capacity. The HT regulating flow rate is calculated by superimposing the preset HT set flow rate value and the HT steam set flow rate correction value, and the HT is regulated based on the HT regulating flow rate. Obtain the second real-time data after HT adjustment, calculate the predicted value of dehydration of the drying machine based on the second real-time data, and calculate the moisture removal setting correction value of the drying machine based on the predicted value of dehydration of the drying machine and the average value of dehydration capacity of the drying machine within a set period. The moisture removal setting value of the drying machine is calculated by superimposing the moisture removal setting correction value of the drying machine output by the moisture PID controller and the moisture removal setting of the drying machine. The drying machine is then adjusted based on the moisture removal adjustment value. The average dehydration capacity of the drying machine and the average water addition capacity of HT within the set period are calculated based on the historical data, including: ， ， in, The average dehydration capacity of the drying machine is given by , and W is the pre-measured weight of the material. This represents the real-time material flow rate n seconds ago. This represents the moisture content of the HT inlet material n seconds ago. This represents the moisture content of the material at the feed trough of the wire drying machine n seconds ago. This represents the moisture content of the material in the discharge trough of the filament drying machine n seconds ago. This represents the average water-adding capacity of HT. M1 represents the number of data sampling points, and M1 represents the initial material moisture content. This refers to the moisture content of the material at the feed trough of the filament drying machine. The moisture content of the material at the discharge chute of the filament drying machine; The predicted HT water addition value is calculated based on the overall moisture content change prediction and the average dewatering capacity of the drying machine, including: Subtract the predicted value of the overall moisture content change from the average dehydration capacity of the drying machine to obtain the predicted value of HT water addition; The correction value for the HT steam set flow rate is calculated based on the predicted HT water supply value and the average HT water supply capacity, including: Subtract the predicted HT water addition value from the average HT water addition capacity to obtain the HT water addition capacity deviation value. Multiply the HT water addition capacity deviation value by a preset first weighting coefficient to obtain the HT steam set flow correction value. Based on the predicted dehydration value of the drying machine and the average dehydration capacity of the drying machine within a set period, the moisture removal setting correction value of the drying machine is calculated as follows: Subtract the predicted dehydration value of the drying machine from the average dehydration capacity of the drying machine to obtain the dehydration capacity deviation value of the drying machine. Multiply the dehydration capacity deviation value of the drying machine by the preset second weighting coefficient to obtain the moisture removal setting correction value of the drying machine. Adjusting the filament drying machine based on the aforementioned moisture removal adjustment value includes: The actual exhaust air volume of the predicted amount and the exhaust air difference value of the drying machine are obtained. The exhaust air volume is adjusted by the exhaust PID controller based on the exhaust air difference value to adjust the opening of the exhaust damper actuator.

2. The water content feedforward model control method according to claim 1, characterized in that, The predicted value of overall water content change calculated based on the first real-time data includes: ， in, The total moisture content is the predicted value, W is the material weight measured in advance, M1 is the initial material moisture value, and Msp is the moisture setting value at the outlet of the drying machine.

3. The water content feedforward model control method according to claim 1, characterized in that, HT regulation based on the HT regulating flow rate includes: When the HT adjustable flow rate is within the upper and lower threshold range preset by the process standard, the HT adjustable flow rate is confirmed as the final HT set flow rate; when the HT adjustable flow rate is not within the upper and lower threshold range preset by the process standard, the preset upper and lower thresholds are confirmed as the final HT set flow rate. The difference between the predicted HT actual flow rate and the final HT set flow rate is obtained. The HT steam flow rate is adjusted by the HT steam flow control PID based on the HT difference to regulate the opening of the steam diaphragm valve and thus regulate the HT steam flow rate.

4. The water content feedforward model control method according to claim 3, characterized in that, The predicted dehydration value of the drying machine is calculated based on the second real-time data, including: ， in, Here, W represents the predicted dehydration value for the drying machine, W is the pre-measured material weight, and M1 is the initial material moisture content. Msp represents the moisture content of the material at the feed trough of the drying machine, while Msp represents the moisture setting at the outlet of the drying machine.

5. A water content feedforward model control device, characterized in that, include: The data acquisition module is used to acquire first-real-time data and historical data; The HT steam set flow correction value calculation module is used to calculate the overall moisture content change prediction value based on the first real-time data, calculate the average dewatering capacity of the drying machine and the average HT water addition capacity within the set period based on the historical data, calculate the HT water addition prediction value based on the overall moisture content change prediction value and the average dewatering capacity of the drying machine, and calculate the HT steam set flow correction value based on the HT water addition prediction value and the average HT water addition capacity. The HT regulation module is used to calculate the HT regulation flow rate based on the preset HT set flow rate value and the HT steam set flow rate correction value, and to regulate the HT based on the HT regulation flow rate. The dehumidification setting correction value calculation module for the drying machine is used to obtain the second real-time data after HT adjustment, calculate the dehydration prediction value of the drying machine based on the second real-time data, and calculate the dehumidification setting correction value of the drying machine based on the dehydration prediction value of the drying machine and the average dehydration capacity of the drying machine within the set period. The drying machine adjustment module is used to calculate the drying machine moisture removal adjustment value based on the drying machine moisture removal set value output by the moisture PID controller and the drying machine moisture removal set correction value, and to adjust the drying machine based on the drying machine moisture removal adjustment value; The average dehydration capacity of the drying machine and the average water addition capacity of HT within the set period are calculated based on the historical data, including: ， ， in, The average dehydration capacity of the drying machine is given by , and W is the pre-measured weight of the material. This represents the real-time material flow rate n seconds ago. This represents the moisture content of the HT inlet material n seconds ago. This represents the moisture content of the material at the feed trough of the wire drying machine n seconds ago. This represents the moisture content of the material in the discharge trough of the filament drying machine n seconds ago. This represents the average water-adding capacity of HT. M1 represents the number of data sampling points, and M1 represents the initial material moisture content. This refers to the moisture content of the material at the feed trough of the filament drying machine. The moisture content of the material at the discharge chute of the filament drying machine; The predicted HT water addition value is calculated based on the overall moisture content change prediction and the average dewatering capacity of the drying machine, including: Subtract the predicted value of the overall moisture content change from the average dehydration capacity of the drying machine to obtain the predicted value of HT water addition; The correction value for the HT steam set flow rate is calculated based on the predicted HT water supply value and the average HT water supply capacity, including: Subtract the predicted HT water addition value from the average HT water addition capacity to obtain the HT water addition capacity deviation value. Multiply the HT water addition capacity deviation value by a preset first weighting coefficient to obtain the HT steam set flow correction value. Based on the predicted dehydration value of the drying machine and the average dehydration capacity of the drying machine within a set period, the moisture removal setting correction value of the drying machine is calculated as follows: Subtract the predicted dehydration value of the drying machine from the average dehydration capacity of the drying machine to obtain the dehydration capacity deviation value of the drying machine. Multiply the dehydration capacity deviation value of the drying machine by the preset second weighting coefficient to obtain the moisture removal setting correction value of the drying machine. Adjusting the filament drying machine based on the aforementioned moisture removal adjustment value includes: The actual exhaust air volume of the predicted amount and the exhaust air difference value of the drying machine are obtained. The exhaust air volume is adjusted by the exhaust PID controller based on the exhaust air difference value to adjust the opening of the exhaust damper actuator.

6. An electronic terminal, characterized in that, It includes a processor and a memory connected to the processor, wherein a computer program is stored in the memory, and when the computer program is executed by the processor, it performs the steps of the method as described in any one of claims 1 to 4.

7. A computer-readable storage medium having a computer program stored thereon, characterized in that, When executed by a processor, the computer program implements the steps of the method according to any one of claims 1 to 4.

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