Starching machine temperature control method and system based on data processing
By using real-time data processing and compensation heating power calculation, the problem of temperature fluctuation after the addition of new sizing material in traditional PID control algorithms has been solved, thus improving the stability and quality of the yarn sizing process.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2026-02-11
- Publication Date
- 2026-03-24
AI Technical Summary
Traditional PID control algorithms cannot respond in time after new sizing is added to the sizing tank, resulting in sizing temperature fluctuations that affect the sizing rate and quality of the yarn.
By collecting data such as the flow rate of the slurry valve, the slurry temperature, and the ambient temperature, the compensation heating power value is calculated, and the heating power is corrected by combining the output of the PID algorithm, so as to achieve advance control of the slurry tank temperature.
It effectively reduces temperature fluctuations, improves yarn sizing rate and product quality, and solves the lag problem of traditional PID control.
Smart Images
Figure CN121722192A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of data processing technology, and in particular to a method and system for temperature control of a sizing machine based on data processing. Background Technology
[0002] In the sizing process, the sizing rate and final sizing quality of the yarn directly depend on the viscosity of the sizing agent. The viscosity of the sizing agent is one of the core parameters that determines the sizing rate and quality of the yarn. However, the viscosity of the sizing agent fluctuates drastically with slight changes in the temperature inside the sizing tank. Therefore, in order to keep the viscosity within a stable range suitable for yarn sizing, the temperature inside the sizing tank must be strictly controlled to keep it at the pre-set target value, thereby ensuring that the viscosity of the sizing agent does not fluctuate significantly and ensuring that the sizing process of the yarn is uniform.
[0003] Currently, the industrial sector commonly uses PID (Proportional-Integral-Derivative) control algorithms to regulate heating systems in order to maintain stable temperatures within the slurry tank. The PID control algorithm continuously monitors the deviation between the actual temperature and the set temperature within the slurry tank and calculates the control output based on the proportional, integral, and derivative terms of this deviation, thereby adjusting the heating power. However, traditional PID control algorithms are essentially feedback control mechanisms. Their control action requires the detection of a deviation in the actual temperature. During the yarn sizing process, as the sizing agent is consumed and the liquid level decreases, new sizing agent is added. The temperature of the newly added sizing agent is usually much lower than the process temperature in the sizing tank. Traditional PID control algorithms can only respond after the cold sizing agent is mixed in and the tank temperature begins to drop, resulting in an inherent time delay in the control chain. The temperature drops significantly and takes a long time to recover. Therefore, during temperature fluctuations, the viscosity of the sizing agent changes, directly leading to uneven yarn sizing and affecting the final product quality. Summary of the Invention
[0004] To address the technical problem that traditional PID control algorithms respond only after cold sizing material is added to the sizing tank, causing temperature fluctuations and resulting in changes in sizing material viscosity and uneven sizing rate on yarn, this invention provides a data processing-based temperature control method and system for sizing machines.
[0005] In a first aspect, the present invention provides a temperature control method for a sizing machine based on data processing, employing the following technical solution: A data-processing-based method for temperature control of a sizing machine includes the following steps: The system collects data at each moment, including the flow rate of the grouting valve, the real-time temperature of the new grout, the temperature data of the grout in the grout tank, the ambient temperature of the workshop, and the volume of the grout in the grout tank. Based on the flow rate of the slurry filling valve and the real-time temperature of the new slurry, the heating power value required for slurry filling at the current moment is obtained; based on the temperature distribution in the slurry temperature set, the temperature non-uniformity in the slurry tank at the current moment is obtained; based on the difference between the slurry temperature in the slurry tank and the ambient temperature of the workshop, the heat dissipation factor of the slurry tank at the current moment is obtained. Based on the temperature non-uniformity, heat dissipation factor, and volume of slurry in the slurry tank at the current moment, the buffer factor of the slurry tank against external temperature disturbances at the current moment is obtained; the heating power value is corrected according to the buffer factor of the slurry tank against external temperature disturbances at the current moment to obtain the compensated heating power value at the current moment. The output heating power value of the PID algorithm at the current moment is superimposed with the compensated heating power value at the current moment to obtain the final heating power value at the current moment; the slurry in the slurry tank is heated according to the final heating power value at the current moment.
[0006] The innovation of this invention lies in the fact that by monitoring the slurry flow rate and temperature, the required compensation heating power value is calculated and compensation is applied at the same time as the cold slurry enters, thus solving the lag problem of traditional PID control that must wait for the temperature to drop before responding.
[0007] Preferably, obtaining the heating power value required for grouting at the current moment includes: ; In the formula, This represents the heating power value required for grouting at the current moment; This represents the flow rate of the grouting valve at the current moment; Represents the density of the slurry; Represents the specific heat capacity of the slurry; This represents the real-time temperature of the slurry in the slurry tank at the current moment; This represents the real-time temperature of the new slurry.
[0008] Based on the flow rate of the slurry replenishment valve, the real-time temperature of the new slurry, and the real-time average temperature of the slurry in the slurry tank, the heating power required for the new slurry to assimilate to the current slurry tank temperature is calculated, providing a basis for subsequent preheating control.
[0009] Preferably, obtaining the degree of temperature non-uniformity within the slurry tank at the current moment includes: ; In the formula, This represents the degree of temperature unevenness within the slurry tank at the current moment; This represents the maximum value in the set of slurry temperatures at the current moment; This represents the minimum value in the set of slurry temperatures at the current moment; This represents the target temperature of the slurry in the slurry tank.
[0010] Preferably, obtaining the heat dissipation factor of the slurry tank at the current moment includes: ; In the formula, The heat dissipation factor of the slurry tank at the current moment; This represents the real-time temperature of the slurry in the slurry tank at the current moment; This represents the ambient temperature of the workshop at the current moment; This represents the target temperature of the slurry in the slurry tank.
[0011] Preferably, obtaining the buffer factor of the slurry tank against external temperature disturbances at the current moment includes: ; In the formula, This represents the buffer factor that the slurry tank can withstand external temperature disturbances at the current moment. This represents the volume of slurry in the slurry tank at the current moment; Represents the maximum volume of the slurry tank; This represents the degree of temperature unevenness within the slurry tank at the current moment; The heat dissipation factor of the slurry tank at the current moment is represented by exp(), which represents an exponential function with the natural constant as the base.
[0012] It fully considers the dynamic impact of the volume of slurry in the slurry tank, the degree of temperature non-uniformity, and the environmental heat dissipation conditions on the system stability, thus reflecting the ability of the slurry tank to resist external temperature disturbances.
[0013] Preferably, obtaining the compensated heating power value at the current moment includes: ; In the formula, This represents the compensated heating power value at the current moment; This represents the heating power value required for grouting at the current moment; This represents the buffer factor that the slurry tank can withstand external temperature disturbances at the current moment. This represents the preset hyperparameters.
[0014] This facilitates subsequent compensation of the output heating power value of the PID algorithm at the current moment based on the compensated heating power value.
[0015] Preferably, obtaining the final heating power value at the current moment includes: ; In the formula, This represents the final heating power value at the current moment; This represents the compensated heating power value at the current moment; This represents the output heating power value of the PID algorithm at the current moment.
[0016] The calculated compensation heating power value is applied to the output heating power value of the PID algorithm at the current moment, which solves the lag problem of traditional PID control that must wait for the temperature to drop before responding.
[0017] Preferably, the output heating power value of the PID algorithm at the current moment includes: The difference between the real-time temperature of the slurry in the slurry tank and the target temperature of the slurry in the slurry tank at the current moment is taken as the real-time error. The real-time error is input into the PID control algorithm to obtain the output heating power value of the PID algorithm at the current moment.
[0018] Preferably, heating the slurry in the slurry tank according to the final heating power value at the current moment includes: The final heating power value at the current moment is transmitted to the heating system to heat the slurry in the slurry tank.
[0019] Secondly, the present invention provides a temperature control system for a sizing machine based on data processing, which adopts the following technical solution: A data-processing-based temperature control system for a sizing machine includes a processor and a memory. The memory stores computer program instructions, which, when executed by the processor, implement the aforementioned data-processing-based temperature control method for the sizing machine.
[0020] By adopting the above technical solution, the above-mentioned data processing-based temperature control method for the sizing machine is generated into a computer program and stored in a memory so that it can be loaded and executed by a processor. This allows for the creation of a terminal device based on the memory and processor, making it convenient to use.
[0021] This invention has the following technical effects: Its innovation lies in first calculating the heating power required to assimilate the new sizing material to the current sizing tank temperature based on the flow rate of the replenishing valve and the real-time temperature of the new sizing material. This provides a foundation for subsequent preheating control. Then, based on the temperature non-uniformity within the sizing tank, the heat dissipation factor, and the volume of the sizing material in the tank at the current moment, a buffer factor is obtained to resist external temperature disturbances, reflecting the tank's ability to resist such disturbances. The heating power value is then corrected based on this buffer factor to obtain a compensated heating power value. After iterating between the compensated heating power value and the output heating power value of the PID algorithm, the control system heats the sizing material in the sizing tank. This solves the lag problem of traditional PID control, which requires waiting for the temperature to drop before responding, thus improving yarn sizing rate and product quality. Attached Figure Description
[0022] Figure 1 This is a flowchart of the temperature control method for a sizing machine based on data processing in an embodiment of the present invention. Figure 2 A schematic diagram comparing the temperature stability of the slurry tank under different control methods; Figure 3 A schematic diagram comparing the timing of the heating power output response of the control system. Detailed Implementation
[0023] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are some embodiments of the present invention, but not all embodiments.
[0024] This invention discloses a data processing-based temperature control method for a sizing machine, referring to... Figure 1 This includes steps S1-S4: S1: Collect the flow rate of the slurry replenishment valve, the real-time temperature of the new slurry, the real-time temperature data in the slurry tank, the ambient temperature of the workshop, and the volume of the slurry in the slurry tank at each moment.
[0025] In this embodiment of the invention, the preset sampling frequency is 1 second / time. During the yarn sizing process, a high-precision electromagnetic flowmeter is installed at the inlet of the sizing valve to collect the flow rate of the sizing valve at each moment. A thermal resistor is installed at the inlet of the sizing tank to collect the real-time temperature of the new sizing material at each moment. Multiple thermal resistors are installed at different depths in the sizing tank to collect several real-time temperature data in the sizing tank at each moment, and these several real-time temperature data in the sizing tank at each moment are used as the sizing temperature set at each moment. A temperature sensor is installed in the sizing workshop at a location free from heat source interference within 1 meter of the sizing tank to collect the ambient temperature of the workshop at each moment. A liquid level sensor (such as an ultrasonic level gauge or a hydrostatic level gauge) is installed inside the sizing tank to collect the volume of the sizing material in the sizing tank at each moment.
[0026] S2: Obtain the heating power value required for slurry replenishment at the current moment; based on the temperature inside the slurry tank at the current moment, obtain the temperature non-uniformity inside the slurry tank at the current moment; based on the difference between the real-time temperature of the slurry inside the slurry tank and the ambient temperature of the workshop at the current moment, obtain the heat dissipation factor of the slurry tank at the current moment; based on the temperature non-uniformity inside the slurry tank at the current moment and the heat dissipation factor of the slurry tank at the current moment, obtain the buffer factor of the slurry tank against external temperature disturbances at the current moment.
[0027] It should be noted that after the slurry is consumed and the liquid level drops, new slurry needs to be added. However, the temperature of the newly added slurry is usually much lower than the actual temperature in the slurry tank. After the newly added slurry enters the slurry tank, it will cause the actual temperature in the slurry tank to drop. The PID controller can only start to respond after the cold slurry is mixed in and the overall temperature begins to drop. Its control response chain has an inherent time delay, which causes the temperature to change and thus the viscosity of the slurry to change. Therefore, the present invention first needs to calculate the energy required for the newly added slurry to heat up to the real-time temperature of the slurry in the current slurry tank at the current moment, that is, the heating power value required for slurry replenishment at the current moment. The heating power value is a physical quantity with the same unit as the output of the heating control system.
[0028] In this embodiment of the invention, the average value of all temperatures in the current slurry temperature set is taken as the real-time temperature of the slurry in the slurry tank at the current moment. Get the heating power value required for grouting at the current moment: ; In the formula, This represents the heating power value required for grouting at the current moment; The flow rate of the grouting valve at the current moment is expressed in cubic meters per second, and the volume of grout entering the grout tank at the current moment is also expressed. This represents the density of the slurry, expressed in kilograms per cubic meter, and represents the mass of one cubic meter of slurry. This represents the specific heat capacity of the slurry, expressed in joules per kilogram. Kelvin), representing the amount of heat required to raise the temperature of one Kelvin per kilogram of slurry; This represents the real-time temperature of the slurry in the slurry tank at the current moment, expressed in Kelvin. Represents the real-time temperature of the new slurry, in Kelvin; This represents the mass of the slurry entering the slurry tank at the current moment; This represents the amount of heat required for the slurry entering the slurry tank to rise by 1 Kelvin at the current moment; This represents the difference between the real-time temperature of the slurry in the slurry tank at the current moment and the real-time temperature of the new slurry. This represents the amount of heat required to heat the slurry entering the slurry tank to the current real-time temperature within the slurry tank, and also represents the heating power required for slurry replenishment at the current moment.
[0029] It should be noted that the same volume of cold slurry will produce different temperature changes when it enters the slurry tank under different conditions. If the volume of slurry in the slurry tank is large, the addition of cold slurry to the slurry tank will not easily cause significant temperature fluctuations. However, if the volume of slurry in the slurry tank is small, the addition of the same volume of cold slurry will lead to a significant temperature drop. Therefore, if the volume of slurry in the slurry tank is large, it means that the slurry tank has a stronger ability to resist external temperature disturbances. However, due to insufficient mixing or incomplete integration of the added cold slurry, the temperature of the slurry in different areas of the slurry tank may be inconsistent. If the temperature distribution in the slurry tank is uneven at the current moment, it will lead to differences in the specific heat capacity of different areas. The specific heat capacity of the low-temperature area is small and easily changed by external cold disturbances, which reduces the equivalent heat capacity of the entire slurry tank. At this time, the buffering capacity of the slurry tank against external temperature fluctuations is weakened, and the temperature will fluctuate more quickly with external temperature disturbances. This indicates that the slurry tank has weak resistance to external temperature disturbances. When the temperature distribution is uniform, the specific heat capacity of different areas in the slurry tank tends to be the same, which increases the overall equivalent heat capacity and enhances the resistance of the slurry tank to external temperature disturbances. Furthermore, if the real-time temperature of the slurry in the slurry tank is greater than the ambient temperature of the workshop, it means that the slurry tank itself is constantly dissipating heat to the outside. The heat dissipation process itself consumes the energy provided by the heating system. If cold slurry is added to the slurry tank at this time, the slurry tank needs to resist both the decrease in internal temperature and external heat dissipation. At this time, the slurry tank has a lower resistance to external temperature disturbances. If the real-time temperature of the slurry in the slurry tank is not much different from the ambient temperature of the workshop, the slurry tank is in a lower heat dissipation state, and its resistance to external temperature disturbances is higher. Therefore, this invention obtains the ability of the slurry tank to resist external temperature disturbances at the current moment based on the volume of the slurry in the tank at the current moment, the degree of temperature non-uniformity in the tank at the current moment, and the heat dissipation factor of the tank at the current moment.
[0030] In this embodiment of the invention, the degree of temperature non-uniformity within the slurry tank at the current moment is obtained: ; In the formula, This represents the degree of temperature unevenness within the slurry tank at the current moment; This represents the maximum value in the set of slurry temperatures at the current moment; This represents the minimum value in the set of slurry temperatures at the current moment; This represents the target temperature of the slurry in the slurry tank. The larger the difference, the greater the temperature non-uniformity in the slurry tank at the current moment. This will lead to a smaller specific heat capacity in the low-temperature region, which is easily changed by external cold disturbances. This will reduce the equivalent heat capacity of the entire slurry tank. At this time, the buffering capacity of the slurry tank to external temperature fluctuations will be weakened, and the temperature will fluctuate more quickly with external temperature disturbances. Obtain the heat dissipation factor of the slide tank at the current moment: ; In the formula, The heat dissipation factor of the slurry tank at the current moment; This represents the real-time temperature of the slurry in the slurry tank at the current moment; This represents the ambient temperature of the workshop at the current moment; This represents the target temperature of the slurry in the slurry tank. The larger the value, the greater the real-time temperature of the slurry in the slurry tank at the current moment is than the ambient temperature of the workshop at the current moment. The heat dissipation of the slurry in the slurry tank is accelerated. If cold slurry is added to the slurry tank at this time, the slurry tank needs to resist the decrease in internal temperature and external heat dissipation at the same time. At this time, the resistance of the slurry tank to external temperature disturbance is low. Obtain the buffer factor of the slurry tank against external temperature disturbances at the current moment: ; In the formula, This represents the buffer factor that the slurry tank can withstand external temperature disturbances at the current moment. This represents the volume of slurry in the slurry tank at the current moment; Represents the maximum volume of the slurry tank; This represents the degree of temperature unevenness within the slurry tank at the current moment; The heat dissipation factor of the slurry tank at the current moment is represented by exp(); exp() represents an exponential function with the natural constant as the base. The larger the value, the larger the volume of slurry in the slurry tank at the current moment, the greater the ability of the slurry tank to resist external temperature disturbances, and the greater the buffer factor of the slurry tank to resist external temperature disturbances at the current moment. as well as The larger the value, the lower the resistance of the slurry tank to external temperature disturbances; The larger the value, the greater the buffer factor of the slurry tank against external temperature disturbances at the current moment.
[0031] S3: Based on the buffer factor of the slurry tank against external temperature disturbances at the current moment and the heating power value required for slurry replenishment at the current moment, obtain the compensation heating power value at the current moment; based on the output heating power value of the PID algorithm at the current moment and the compensation heating power value at the current moment, obtain the final heating power value at the current moment.
[0032] It should be noted that if the heating power required for slurry replenishment increases at the current moment, the compensation heating power will inevitably increase. However, if the slurry tank has a stronger ability to resist external temperature disturbances, the impact of slurry replenishment on the temperature of the slurry in the tank will be smaller than expected, and the actual compensation required can be reduced to avoid overcompensation. Conversely, if the slurry tank has a weaker ability to resist external temperature disturbances, the impact of slurry replenishment on the temperature of the slurry in the tank will be larger than expected, and the actual compensation required can be increased to provide additional compensation. Therefore, in this embodiment of the invention, the heating power required for slurry replenishment at the current moment is adjusted based on the slurry tank's ability to resist external temperature disturbances at the current moment to obtain the compensation heating power value at the current moment.
[0033] In this embodiment of the invention, the compensated heating power value at the current moment is obtained: ; In the formula, This represents the compensated heating power value at the current moment; This represents the heating power value required for grouting at the current moment; This represents the buffer factor that the slurry tank can withstand external temperature disturbances at the current moment. Representing preset hyperparameters, in this embodiment of the invention, the preset... In order to avoid When the value approaches 0, the denominator becomes 0. The higher the heating power required for grout replenishment at the current moment, the higher the compensation heating power required at the current moment. If the buffer factor of the grout tank against external temperature disturbances is higher at the current moment, it means that grout replenishment has a smaller impact on the temperature of the grout in the grout tank. In this case, the heating power required for grout replenishment at the current moment should be reduced to avoid overcompensation. If the buffer factor of the grout tank against external temperature disturbances is lower at the current moment, it means that grout replenishment has a greater impact on the temperature of the grout in the grout tank. In this case, the heating power required for grout replenishment at the current moment should be increased, as more heating is needed to offset the external disturbances.
[0034] It should be noted that the compensated heating power value at the current moment is superimposed with the output heating power value of the PID algorithm at the current moment to form the final heating power value, which is then applied to the heating system for execution.
[0035] In this embodiment of the invention, the difference between the real-time temperature of the slurry in the slurry tank at the current moment and the target temperature of the slurry in the slurry tank is taken as the real-time error. The real-time error is input into the PID control algorithm to obtain the output heating power value of the PID algorithm at the current moment. Get the final heating power value at the current moment: ; In the formula, This represents the final heating power value at the current moment; This represents the compensated heating power value at the current moment; This represents the output heating power value of the PID algorithm at the current moment.
[0036] S4: Heat the slurry in the slurry tank according to the final heating power value at the current moment.
[0037] In this embodiment of the invention, the final heating power value at the current moment is transmitted to the heating system to heat the slurry in the slurry tank, thereby offsetting the effect of cold slurry on the overall temperature before it has a significant impact.
[0038] Figure 2 The diagram illustrates the temperature stability of the slurry tank under different control methods. It shows the temperature change curves of the slurry in the tank over time before and after a cold slurry replenishment event during the slurry production process, under different control methods. The blue dashed line (existing PID control method) shows a significant temperature drop after the replenishment event, followed by a slow recovery, demonstrating the hysteresis and temperature fluctuation problems of the existing technology. In contrast, the red solid line (adaptive control method of this application) maintains the temperature almost on a straight line at the target value (e.g., 95°C) immediately after the replenishment event, with only minimal fluctuations, thus solving the hysteresis and temperature fluctuation problems of the existing technology.
[0039] Figure 3 The diagram showing the heating power output response timing of the control system illustrates the heating power output of the prior art and the present invention on the same time axis. The heating power of the blue dashed line (existing PID control) slowly rises as the temperature drops after a period of time after the start of slurry replenishment, missing the optimal control opportunity. In contrast, the red solid line (the present invention) shows that the heating power increases instantaneously when slurry replenishment is started to perform feedforward compensation, quickly injecting heat to offset the influence of cold slurry.
[0040] This invention also discloses a data processing-based temperature control system for a sizing machine, including a processor and a memory. The memory stores computer program instructions, which, when executed by the processor, implement the data processing-based temperature control method for a sizing machine provided by this invention.
[0041] The system also includes other components well-known to those skilled in the art, such as communication buses and communication interfaces, the setup and functions of which are known in the art and will not be described in detail here. In this invention, the aforementioned memory can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.
[0042] The above are all preferred embodiments of the present invention and are not intended to limit the scope of protection of the present invention. Therefore, all equivalent changes made in accordance with the structure, shape and principle of the present invention should be covered within the scope of protection of the present invention.
Claims
1. A temperature control method for a sizing machine based on data processing, characterized in that, include: The system collects data at each moment, including the flow rate of the grouting valve, the real-time temperature of the new grout, the temperature data of the grout in the grout tank, the ambient temperature of the workshop, and the volume of the grout in the grout tank. Based on the flow rate of the grouting valve and the real-time temperature of the new grout, the heating power value required for grouting at the current moment is obtained; based on the temperature distribution in the grout temperature set, the degree of temperature non-uniformity in the grout tank at the current moment is obtained. Based on the difference between the temperature of the slurry in the slurry tank and the ambient temperature in the workshop, the heat dissipation factor of the slurry tank at the current moment is obtained; Based on the temperature non-uniformity, heat dissipation factor, and volume of slurry in the slurry tank at the current moment, the buffer factor of the slurry tank against external temperature disturbances at the current moment is obtained; the heating power value is corrected according to the buffer factor of the slurry tank against external temperature disturbances at the current moment to obtain the compensated heating power value at the current moment. The output heating power value of the PID algorithm at the current moment is superimposed with the compensated heating power value at the current moment to obtain the final heating power value at the current moment; the slurry in the slurry tank is heated according to the final heating power value at the current moment.
2. The temperature control method for a sizing machine based on data processing according to claim 1, characterized in that, The step of obtaining the heating power value required for grouting at the current moment includes: ； In the formula, This represents the heating power value required for grouting at the current moment; This represents the flow rate of the grouting valve at the current moment; Represents the density of the slurry; Represents the specific heat capacity of the slurry; This represents the real-time temperature of the slurry in the slurry tank at the current moment; This represents the real-time temperature of the new slurry.
3. The temperature control method for a sizing machine based on data processing according to claim 1, characterized in that, The process of obtaining the degree of temperature non-uniformity within the slurry tank at the current moment includes: ； In the formula, This represents the degree of temperature unevenness within the slurry tank at the current moment; This represents the maximum value in the set of slurry temperatures at the current moment; This represents the minimum value in the set of slurry temperatures at the current moment; This represents the target temperature of the slurry in the slurry tank.
4. The temperature control method for a sizing machine based on data processing according to claim 1, characterized in that, The process of obtaining the heat dissipation factor of the slurry tank at the current moment includes: ； In the formula, The heat dissipation factor of the slurry tank at the current moment; This represents the real-time temperature of the slurry in the slurry tank at the current moment; This represents the ambient temperature of the workshop at the current moment; This represents the target temperature of the slurry in the slurry tank.
5. The temperature control method for a sizing machine based on data processing according to claim 1, characterized in that, The process of obtaining the buffer factor of the slurry tank against external temperature disturbances at the current moment includes: ； In the formula, This represents the buffer factor that the slurry tank can withstand external temperature disturbances at the current moment. This represents the volume of slurry in the slurry tank at the current moment; Represents the maximum volume of the slurry tank; This represents the degree of temperature unevenness within the slurry tank at the current moment; The heat dissipation factor of the slurry tank at the current moment is represented by exp(), which represents an exponential function with the natural constant as the base.
6. The temperature control method for a sizing machine based on data processing according to claim 1, characterized in that, The step of obtaining the compensated heating power value at the current moment includes: ； In the formula, This represents the compensated heating power value at the current moment; This represents the heating power value required for grouting at the current moment; This represents the buffer factor that the slurry tank can withstand external temperature disturbances at the current moment. This represents the preset hyperparameters.
7. The temperature control method for a sizing machine based on data processing according to claim 1, characterized in that, The process of obtaining the final heating power value at the current moment includes: ； In the formula, This represents the final heating power value at the current moment; This represents the compensated heating power value at the current moment; This represents the output heating power value of the PID algorithm at the current moment.
8. The temperature control method for a sizing machine based on data processing according to claim 7, characterized in that, The output heating power value of the PID algorithm at the current moment includes: The difference between the real-time temperature of the slurry in the slurry tank and the target temperature of the slurry in the slurry tank at the current moment is taken as the real-time error. The real-time error is input into the PID control algorithm to obtain the output heating power value of the PID algorithm at the current moment.
9. The temperature control method for a sizing machine based on data processing according to claim 1, characterized in that, Heating the slurry in the slurry tank according to the final heating power value at the current moment includes: The final heating power value at the current moment is transmitted to the heating system to heat the slurry in the slurry tank.
10. A temperature control system for a sizing machine based on data processing, characterized in that, include: A processor and a memory, the memory storing computer program instructions that, when executed by the processor, implement the data processing-based temperature control method for a sizing machine according to any one of claims 1-9.