Shaping drying equipment control method and system based on field data and storage medium

Abstract

The invention relates to the technical field of shaping and drying equipment, and discloses a shaping and drying equipment control method and system based on field data and a storage medium, and the method comprises the steps that the material amount is obtained, the air inlet power is matched, and the power of a draught fan blowing dry cold air is controlled; the air inlet humidity is generated based on the first humidity sensor, and the air outlet humidity is generated based on the second humidity sensor; the humidity difference value between the air humidity and the inlet air humidity is calculated, and if the humidity difference value is larger than the humidity reference difference value, humidity abnormity prompting is carried out; otherwise, a humidity comparison value is calculated according to the humidity difference value and the humidity reference difference value, and the fan power is adjusted according to humidity comparison positive correlation; if the duration of the humidity abnormity prompt is within the first duration range, a heating module is started, and the heating power is adjusted according to the humidity difference value; and if the duration is within the second duration range, the refrigeration module is started, the heating module is closed, the refrigeration power is adjusted according to the humidity difference value, and the drying work efficiency of the shaping and drying equipment is improved.

Description

Technical Field

[0001] This application relates to the technical field of shaping and drying equipment, and in particular to a shaping and drying equipment control method, system and storage medium based on field data. Background Technology

[0002] Soft capsules are typically manufactured using a compression method, a process that includes ingredient preparation, gelatinization, pelleting, and shaping and drying. Among these steps, shaping and drying are crucial for product quality, as they remove excess moisture from the capsule shell to ensure stable shape and adequate hardness.

[0003] The soft capsule cold air drying equipment is the core device for achieving shape-setting drying. It is mainly used to remove moisture from the soft capsule preform shell, so that the shell reaches the specified moisture content and physical properties. This equipment typically includes a drying chamber, a cold air generator, an airflow circulation system, and an exhaust system. During operation, the cold air generator cools the air to the set temperature and then evenly delivers it to the drying chamber through the airflow circulation system. This allows the surface moisture of the soft capsules to evaporate in the low-temperature airflow environment. The evaporated moisture is then discharged through the exhaust system, thereby achieving the shape-setting drying of the soft capsules.

[0004] Most soft capsule cold air drying equipment on the market currently uses a timed operation mode, meaning a fixed drying time is preset. The equipment operates according to this preset time throughout the entire process, failing to automatically adjust operating parameters based on the actual state of the soft capsules inside the drying chamber, such as real-time moisture content, surface dryness, and changes in ambient temperature and humidity. This operating method easily leads to under-drying or over-drying, which not only affects the quality of the soft capsule products but also wastes energy, reduces drying efficiency, and fails to meet the demands of modern production for precise control and high-efficiency manufacturing. Summary of the Invention

[0005] To improve the drying efficiency of shaping and drying equipment, this application provides a shaping and drying equipment control method, system, and storage medium based on field data.

[0006] In a first aspect, this application provides a control method for a shaping and drying equipment based on on-site data, employing the following technical solution: A method for controlling a shaping and drying equipment based on field data includes the following steps: The material quantity input into the drying drum is obtained based on the counting sensor. The air inlet power is matched from the preset air volume database according to the material quantity. The power of the fan blowing dry cold air into the drying drum is controlled according to the air inlet power. After a preset time period, the inlet humidity is generated based on the first humidity sensor installed on the air inlet side of the shaping and drying equipment, and the outlet humidity is generated based on the second humidity sensor installed on the air outlet side of the shaping and drying equipment. The difference between the outlet humidity and the inlet humidity is calculated as the humidity difference value. If the humidity difference value is greater than the preset humidity reference difference value, a humidity abnormality prompt is issued; otherwise, a humidity comparison value is calculated based on the humidity difference value and the humidity reference difference value, and the fan power is adjusted according to the positive correlation of the humidity comparison value. Based on the humidity anomaly alert, if the duration of the humidity anomaly alert is within a preset first duration range, the heating module located at the fan in the setting and drying equipment is activated, and the heating power of the heating module is adjusted according to the humidity difference. If the duration of the humidity anomaly alert is within a preset second duration range, the cooling module located at the fan in the setting and drying equipment is activated, the heating module is turned off, and the cooling power of the cooling module is adjusted according to the humidity difference. The values ​​in the second duration range are greater than the values ​​in the first duration range. If the humidity difference is less than the preset minimum difference, the shaping and drying process will stop, and the material will be output from the drying drum.

[0007] By adopting the above technical solution, the amount of material input into the drying drum is obtained through a counting sensor, and the corresponding air intake power is matched from the air volume database. The fan is then controlled to blow dry cold air into the drying drum at this power, achieving precise matching between the material amount and the air intake power, which is beneficial for adapting the drying conditions and materials in the initial stage. After a set time, the first humidity sensor generates the inlet humidity on the air intake side of the shaping and drying equipment, and the second humidity sensor generates the outlet humidity on the air outlet side. The humidity difference between the two is calculated. If the humidity difference does not exceed the humidity reference difference, the fan power is adjusted according to the positive correlation between the humidity difference and the humidity reference difference, achieving dynamic adjustment of the fan power. If the humidity difference exceeds the humidity reference difference, a humidity anomaly warning is triggered. If the duration is within the first duration range, the heating module at the fan is activated and the heating power is adjusted positively according to the humidity difference. If the duration is within the second duration range, the cooling module is activated and the heating module is turned off, and the cooling power is adjusted positively according to the humidity difference to dynamically adapt to changes in ambient temperature and humidity and the actual state of the material. When the humidity difference is less than the set minimum difference, the shaping and drying process is stopped and the material is output from the drying drum, ensuring that the material reaches the qualified moisture content and surface dryness, reducing under-drying or over-drying, reducing energy consumption, improving drying efficiency, and meeting the control and production needs of modern production.

[0008] Optionally, the method further includes the following steps: Within a preset batch of materials, the total operating time of the blower is calculated as the drying time, and the time for adjusting the blower power is calculated as the control time. The ratio of control time to drying time is calculated as the control ratio. If the control ratio is within the preset first reference ratio range, the first control ratio value is calculated based on the minimum value between the control ratio and the first reference ratio range, and the set duration is adjusted according to the positive correlation of the first control ratio value. If the control ratio is within the preset second reference ratio range, the second control ratio value is calculated based on the minimum value between the control ratio and the second reference ratio range, and the control coefficient for controlling the fan power based on the air intake power is adjusted according to the positive correlation of the second control ratio value. The values ​​within the second reference ratio range are greater than those within the first reference ratio range.

[0009] By adopting the above technical solution, the fan power control can be dynamically adapted to the material drying process by calculating the control ratio and adjusting the set duration or control coefficient according to the stepped reference ratio range. This helps to maintain the matching between the air intake power, control coefficient and material state, and refine the adjustment process based on different dimensions under different conditions, which helps to improve the shaping and drying effect.

[0010] Optionally, the method further includes the following steps: The blower is located near the material output of the drying drum and can rotate to blow air; The fluctuation value of the humidity difference is calculated within a preset calculation time. If the fluctuation value is less than the preset fluctuation reference value, the fan is controlled to reciprocate to blow the drying drum, and the angle range of the fan rotation is adjusted according to the negative correlation of the fluctuation value; otherwise, the fan's posture is controlled to reset and remain fixed.

[0011] By adopting the above technical solution, the feeding and discharging operations are carried out simultaneously; the residual dry air is used to blow away the newly fed material, and the blower is dynamically adjusted according to the fluctuation of the humidity difference, rotating back and forth or maintaining a fixed posture to adapt to the drying process. This facilitates the matching of drying conditions in different areas of the material, maintains the consistency of the drying state, reduces local drying imbalance, adapts to the drying characteristics of materials at different stages, and makes the drying process more consistent with the actual state of the material.

[0012] Optionally, the method further includes the following steps: Multiple drying drums are set up and connected in series along the material conveying direction. Each drying drum is equipped with a fan, a first humidity sensor and a second humidity sensor. In the material conveying direction, the control coefficient of the fan power gradually decreases, and the sensing accuracy of the first humidity sensor and the second humidity sensor gradually decreases.

[0013] By adopting the above technical solution, the configuration of multiple drying barrels connected in series and their matching fans, first humidity sensor, and second humidity sensor enables the drying process to dynamically adapt to the needs of different stages as the material is transported. The gradient setting of control coefficient and sensing accuracy facilitates the matching of parameters of each drying barrel with the material state, reduces the complexity and fluctuation of the overall equipment control, and maintains the continuity of drying conditions.

[0014] Optionally, the method further includes the following steps: Before feeding materials into the drying drum, the first temporary humidity is collected by the first humidity sensor. If the first temporary humidity is within the preset temporary humidity range, the self-test mode is entered; otherwise, the normal operation mode is entered. In self-test mode, the fan is started according to the first set power, and the heating device is started according to the second set power; the second temporary humidity is collected by the second humidity sensor, and the curve of the second temporary humidity is calculated as the humidity change curve; the graphic matching value of the humidity change curve and the preset humidity reference curve is calculated. If the graphic matching value is greater than the preset reference matching value, the humidity sensor self-test passes the prompt; otherwise, the humidity sensor self-test fails the prompt.

[0015] By adopting the above technical solution, the sensor is checked by dynamically switching between self-test and normal operation modes based on the first temporary humidity. During the self-test, the sensor is verified by matching the humidity change curve with the preset humidity reference curve. This facilitates the detection of the sensor status and helps maintain the accuracy of subsequent drying detection.

[0016] Optionally, the method further includes the following steps: Calculate the real-time power of the fans corresponding to multiple parallel drying drums, and calculate the average value of the multiple real-time power as the power average value. The average value of the power uniformity is calculated within the preset working time. If the average value is less than the preset reference uniform value, the basic power of the fan is increased for multiple fans, and the basic power of the fan is adjusted according to the positive correlation between the reference uniform value and the average value.

[0017] By adopting the above technical solution, the basic power of the fan is dynamically adjusted by calculating the power uniformity and average value, which facilitates the matching of fan power of multiple parallel drying barrels, adapts to the synchronous drying needs of batch materials, reduces the imbalance of drying state caused by power differences, and fits the characteristics of parallel configuration drying scenarios.

[0018] Optionally, the method further includes the following steps: Calculate the average power of the fans corresponding to multiple parallel drying drums within the preset working time, and calculate the uniform value of the multiple average power as the distribution uniform value. If the uniform distribution value is less than the preset reference distribution value, the ratio between multiple average powers is calculated as the average power ratio; the rotation speed of the corresponding drying drum is adjusted according to the negative correlation of the average power ratio.

[0019] By adopting the above technical solution, the rotation speed of multiple parallel drying drums is dynamically adjusted according to the average power ratio, which helps to match the power distribution of multiple parallel drying drums with the material drying requirements, maintain the drying conditions of each drying drum, adapt to batch synchronous drying scenarios, and reduce the additional adverse effects caused by power distribution differences.

[0020] Optionally, the method further includes the following steps: Obtain the real-time power of the shaping and drying equipment. If the real-time power is greater than the preset maximum power, calculate the ratio of the real-time power to the maximum power as the equipment power comparison value, and adjust the basic cooling power of the refrigeration module according to the positive correlation of the equipment power comparison value.

[0021] By adopting the above technical solution, the basic cooling power of the refrigeration module is dynamically adjusted according to the power comparison value of the equipment, which is conducive to matching the cooling effect with the real-time power of the shaping and drying equipment, maintaining the cooling intensity and equipment load compatibility, adapting to working scenarios with excessive power, and reducing the impact of high temperature caused by excessive power on the shaping and drying equipment.

[0022] Secondly, this application provides a control system for a shaping and drying equipment based on field data, which adopts the following technical solution: A field-based data-driven shaping and drying equipment control system includes a processor that executes the steps of the field-based data-driven shaping and drying equipment control method as described in any of the preceding claims.

[0023] Thirdly, this application provides a storage medium, which adopts the following technical solution: A storage medium storing a program that, when executed by a processor, implements the steps of the above-described field data-based shaping and drying equipment control method.

[0024] In summary, this application includes at least one of the following beneficial technical effects: This control method achieves precise matching between material quantity and initial air intake power through counting sensors. It dynamically adjusts fan power based on the humidity difference between the inlet and outlet air sides, and adaptively starts or stops heating or cooling modules according to the duration of humidity abnormality alerts. Simultaneously, it dynamically adjusts the fan blowing posture through stepped adjustment of the set duration and control coefficients. For series drying hoppers, it employs gradient fan control coefficients and sensor accuracy configurations. Furthermore, it incorporates mechanisms such as sensor self-checking, balanced adjustment of fan power across multiple parallel drying hoppers, and adaptive adjustment of cooling power when equipment power exceeds limits. This comprehensive approach achieves precise dynamic adaptation of the sizing drying equipment's operating parameters to the actual drying state of the soft capsule material and changes in ambient temperature and humidity. This effectively reduces under-drying or over-drying, lowering energy consumption, improving drying efficiency, ensuring soft capsule product quality, and meeting the precise control requirements of modern mass production. It also ensures sensor detection accuracy, consistency of drying states across multiple drying hoppers, and equipment operational stability. Attached Figure Description

[0025] Figure 1 This is a flowchart illustrating the steps of a control method for a type-specific drying equipment based on field data.

[0026] Figure 2 This is a simplified structural diagram of multiple drying tanks connected in series.

[0027] Figure 3 This is a simplified structural diagram of multiple drying drums arranged side by side. Detailed Implementation

[0028] The embodiments of this application are described in detail below, and examples of the embodiments are shown in the accompanying drawings.

[0029] In the description of this specification, the references to "certain embodiments," "one embodiment," "some embodiments," "illustrative embodiment," "example," "specific example," or "some examples" refer to specific features, structures, materials, or characteristics described in connection with the described embodiment or example, which are included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0030] This application discloses a control method for a shaping and drying equipment based on on-site data, referring to... Figure 1 It includes the following steps: The amount of material entering the drying drum is obtained based on a counting sensor. Specifically, the amount of material can be collected in real time by a photoelectric counting sensor installed above the feed conveyor belt of the drying drum. This sensor can identify the number of soft capsule particles conveyed on the conveyor belt. The standard weight of each soft capsule is 0.5g, and the total amount of material conveyed into the drying drum can be calculated. For example, when the counting sensor identifies 100,000 soft capsules, the total amount of material is 100,000 × 0.5g = 50kg. The system matches the inlet air power from a pre-set airflow database based on the material quantity, and controls the power of the fan blowing dry, cold air into the rotating drying drum accordingly. The airflow database is built based on extensive experimental data, recording the mapping relationship between different material quantities and corresponding optimal inlet air power. For example, for material quantities of 30-60 kg, the corresponding inlet air power is 1.2-1.5 kW; for 60-100 kg, it is 1.5-1.8 kW; and for 100-150 kg, it is 1.8-2.2 kW. Once the counting sensor acquires the material quantity, the control system automatically matches the appropriate inlet air power from the database. For example, for a material quantity of 50 kg, an inlet air power of 1.2 kW is matched, and the centrifugal fan on the side of the drying drum is activated to blow dry, cold air at a temperature of 15-20℃ and a humidity ≤30%RH into the drying drum.

[0031] After a preset time period, in this embodiment the time period is set to 30 minutes. Relying on the first humidity sensor installed on the air inlet side of the drying barrel and the second humidity sensor installed on the air outlet side, the inlet humidity H1 and the outlet humidity H2 are collected respectively, and the humidity difference of the current drying process is calculated by the formula ΔH=H2-H1.

[0032] If the humidity difference exceeds the preset humidity reference difference, a humidity anomaly warning is issued; otherwise, a humidity comparison value is calculated based on the humidity difference and the humidity reference difference, and the fan power is adjusted according to the positive correlation of the humidity comparison. In this embodiment, the preset humidity reference difference ΔH0 = 15%RH and the preset minimum difference ΔHmin = 5%RH are defined. If the calculated humidity difference ΔH ≤ ΔH0, for example: H1 = 60%RH, H2 = 72%RH, ΔH = 12%RH, then the current drying state is determined to be normal. The control system further calculates the humidity comparison value K = ΔH / ΔH0. At this time, K = 12% / 15% = 0.8, and adjusts the fan power according to the positive correlation of this humidity comparison value. Specifically, the fan power adjustment formula is: adjusted power P = initial air intake power P0 × (1 + K × 0.2). At this time, the adjusted power P = 1.2kW × (1 + 0.8 × 0.2) = 1.2 × 1.16 = 1.39kW. Through this fine adjustment, the fan power can be dynamically adapted to the amount of material moisture evaporation. The more material moisture evaporates, the larger ΔH is, the larger K is, and the higher the fan power is, further accelerating the moisture discharge. If the humidity difference ΔH > ΔH0, for example: H1 = 60%RH, H2 = 80%RH, ΔH = 20%RH, then it is determined that there is an abnormal humidity in the current drying process, which may be caused by a sudden increase in ambient humidity due to capsule damage. The control system will immediately trigger a humidity abnormality prompt, display "Humidity abnormality, please pay attention" on the equipment operation screen and sound an alarm so that the operator can know the status in real time.

[0033] Based on the humidity anomaly alert, if the duration of the humidity anomaly alert is within a preset first duration range, the heating module located at the fan in the setting and drying equipment is activated, and the heating power of the heating module is adjusted according to the humidity difference. If the duration of the humidity anomaly alert is within a preset second duration range, the cooling module located at the fan in the setting and drying equipment is activated, the heating module is turned off, and the cooling power of the cooling module is adjusted according to the humidity difference. The value in the second duration range is greater than the value in the first duration range.

[0034] The heating module is a 220V / 1kW PTC heater, and the cooling module is a 12V / 500W semiconductor refrigeration chip.

[0035] This embodiment presupposes: a first duration range T1 = 5-10 minutes, representing a short-term anomaly; and a second duration range T2 = 10-20 minutes, representing a long-term anomaly, with the minimum value of T2 greater than the maximum value of T1. If the duration of the humidity anomaly warning is t∈T1, for example, t=8 minutes, it is determined to be a short-term humidity anomaly. The control system starts the heating module and adjusts the heating power according to the humidity difference ΔH. The heating power adjustment formula is: heating power Ph=basic heating power Ph0×(ΔH / ΔH0), where Ph0=0.5kW, at this time ΔH=20%RH, Ph=0.5×(20 / 15)=0.67kW. The heating module increases the air inlet temperature from 15-20℃ to 22-25℃, which accelerates the evaporation of moisture on the material surface and quickly reduces ΔH. If the duration of the abnormal humidity warning is t∈T2, for example, t=15 minutes, it is determined to be a long-term abnormal humidity. The control system immediately shuts down the heating module, starts the cooling module, and adjusts the cooling power according to the humidity difference ΔH. The cooling power adjustment formula is: cooling power P_c=basic cooling power P_c0×(ΔH / ΔH0), where P_c0=0.3kW, and at this time P_c=0.3×(20 / 15)=0.4kW. The cooling module reduces the humidity of the incoming air from 60%RH to below 50%RH, improves the moisture absorption capacity of the dry air, and gradually reduces ΔH to the normal range. If the humidity abnormality warning lasts for more than 20 minutes, the control system will trigger an advanced alarm, and the operation screen will display "Humidity abnormality lasts for more than 20 minutes, please check materials or equipment" and keep the refrigeration module running to prevent the abnormality from escalating.

[0036] During the drying process, the control system monitors the humidity difference ΔH in real time. When ΔH < ΔHmin, for example, ΔH = 4%RH, the material is deemed to have reached the required drying standard. At this point, the moisture content of the soft capsule shells has dropped to 8-10%, meeting industry standards, and the morphological hardness meets the Shore hardness requirement of D40-45. The control system immediately sends instructions to stop the fan, heating module (if on), and cooling module, and simultaneously starts the discharge conveyor belt at the bottom of the drying tank to transport the dried soft capsule material to the next production stage, such as screening and packaging, to prevent over-drying. If ΔH continues to drop to 2%RH, the moisture content of the capsule shells will fall below 8%, making them prone to cracking.

[0037] By adopting the above technical solution, the amount of material in the drying drum is obtained by a counting sensor, and the corresponding air intake power is matched with the air volume database to control the fan air supply, achieving precise matching between the material amount and the air intake power, ensuring that the initial drying conditions meet the material requirements. After setting the time, the humidity is collected by the first and second humidity sensors on the air intake and exhaust sides and the difference is calculated. When the difference does not exceed the reference value, the fan power is adjusted according to the positive correlation of the humidity comparison value to achieve dynamic air control. When the difference exceeds the reference value, an abnormality prompt is triggered. When the abnormality duration is within the first range, the heating module is activated and the heating power is adjusted according to the difference. When it is in the second range, which is longer, the cooling module is switched and the cooling power is adjusted to adapt to the environment and material state. When the difference is lower than the set minimum value, drying is stopped and the material is output, ensuring that the material dryness meets the standard, reducing drying deviation, reducing energy consumption, improving efficiency, and meeting the precise control and high efficiency requirements of modern production.

[0038] This embodiment focuses on the dynamic optimization of the set duration and the fan power control coefficient, and is applicable to multi-batch continuous production scenarios. The specific method also includes the following steps: Within a preset batch of materials, the total operating time of the blower is calculated as the drying time, and the time for adjusting the blower power is calculated as the control time. The ratio of the control time to the drying time is the control ratio. For the preset batch of materials, in this embodiment, it is set to 10 batches, each batch containing 100kg of soft capsules. The control system automatically records the total working time T_d of the fan in each batch, for example, T_d = 120 minutes for a certain batch, and the adjustment time T_c of the fan power, that is, the cumulative time for the fan power to be adjusted in that batch, for example, T_c = 40 minutes for a certain batch, and calculates the control ratio R = T_c / T_d. At this time, R = 40 / 120 ≈ 0.33.

[0039] This embodiment presupposes that: the first reference ratio range R1 = 0.2-0.4, with a moderate proportion of control time; and the second reference ratio range R2 = 0.4-0.6, with a relatively high proportion of control time.

[0040] If R∈R1, such as R=0.33, then calculate the first control comparison value ΔR1=R-R1min, where R1min=0.2 and ΔR1=0.13, and adjust the set duration according to the positive correlation of ΔR1. The adjustment formula is: the adjusted set duration T_s'=the original set duration T_s×(1+ΔR1×0.5), the original T_s=30 minutes, and now T_s'=30×(1+0.13×0.5)=30×1.065=31.95 minutes, about 32 minutes. By fine-tuning the set duration, the subsequent humidity detection is made to better match the drying rhythm of this batch of materials.

[0041] If R∈R2, such as R=0.45, then calculate the second control comparison value ΔR2=R-R2min, where R2min=0.4 and ΔR2=0.05. Adjust the intake power control coefficient k according to the positive correlation of ΔR2. This coefficient is used to correct the initial intake power, and the original k=1.0. The adjustment formula is: the adjusted control coefficient k'=k×(1+ΔR2×2), where k'=1.0×(1+0.05×2)=1.1. If the original initial intake power is 1.8kW, the adjusted power is 1.8×1.1=1.98kW. By increasing the control coefficient, the adjustment frequency of the subsequent fan power is reduced, thereby improving the drying stability.

[0042] This embodiment addresses the dynamic adjustment of the blower's purging posture and is suitable for scenarios where the material distribution inside the drying drum is uneven. The specific method also includes the following steps: In this embodiment, the fan is installed near the material output of the drying drum, such as 10cm from the outlet, and a 360° rotatable fan bracket is used, allowing the fan to rotate back and forth horizontally. The control system collects real-time data on the change in humidity difference ΔH within a preset calculation time T_cal = 10 minutes. For example, if ΔH is 12%, 11%, 12%, 13%, and 11% respectively within 10 minutes, the fluctuation value σ is calculated, which is the standard deviation of ΔH. In this case, σ = √[((12-11.8)²×4+(13-11.8)²) / 5] ≈ 0.75%RH. The preset fluctuation reference value σ0 = 5%RH in this embodiment is: If σ < σ0, such as σ = 0.75%, it is determined that the humidity distribution of the material in the drying drum is uniform, but there may be slightly damp areas in some places. The control system controls the fan to blow the drying drum in a reciprocating rotation mode. The rotation angle range θ is negatively correlated with the fluctuation value σ. The adjustment formula is: θ = 180° - (σ / σ0) × 100°. At this time, θ = 180 - (0.75 / 5) × 100 = 165°. The fan reciprocates within the 165° range at a speed of 5° / s to ensure that the drying air covers all areas in the drying drum and avoids local dampness.

[0043] If σ≥σ0, such as σ=6%, it is determined that the humidity distribution of the material in the drying drum is uneven, which may be due to material accumulation. The control system immediately controls the fan to reset its attitude, return to the initial angle of 90°, and keep it fixed. It then uses concentrated air force to blow away the area with high humidity to quickly balance the humidity distribution in the drum. After σ<σ0, it switches back to the reciprocating rotation mode.

[0044] Reference Figure 2 This embodiment focuses on the parameter configuration for a multi-drying drum series layout, and is suitable for continuous drying scenarios involving large quantities of materials. The specific method also includes the following steps: This embodiment sets up three drying drums (numbered 1#, 2#, and 3#) connected in series along the material conveying direction. Drum 1# is the inlet, and drum 3# is the outlet. Each drying drum is independently equipped with a fan, a first humidity sensor, and a second humidity sensor. In the material conveying direction, this embodiment uses gradient parameter settings: Fan power control coefficients: k1=1.0 for drying drum #1, k2=0.8 for drying drum #2, and k3=0.6 for drying drum #3. Because the material has a high moisture content (approximately 15-18%) when entering from drum #1, a higher fan power is required, such as an initial power of 1.8kW for drum #1 to accelerate moisture evaporation. When entering drum #2, the moisture content drops to 12-15%, and the power can be reduced to 1.8 × 0.8 = 1.44kW. When entering drum #3, the moisture content has dropped to 8-12%, and the power is further reduced to 1.8 × 0.6 = 1.08kW, ensuring both drying effect and reducing downstream energy consumption. Humidity sensor accuracy: 1# drying drum sensor accuracy ±1%RH, 2# ±2%RH, 3# ±3%RH; The moisture content of the front-end material fluctuates greatly, requiring a high-precision sensor to ensure accurate control; The moisture content of the back-end material tends to be stable, and appropriately reducing the accuracy can reduce equipment costs. A ±3%RH sensor costs 40% less than a ±1%RH sensor, without affecting the drying effect.

[0045] With this gradient configuration, the three drying drums connected in series can achieve a progressive drying process of high-humidity rapid drying, medium-humidity stable drying, and low-humidity precise drying, thereby improving production efficiency.

[0046] This embodiment focuses on the self-test of the humidity sensor, which is suitable for checking the status before the device is started, and avoids control deviations caused by sensor failure. The specific method also includes the following steps: Before conveying materials to the drying drum, the control system first collects a first temporary humidity H_t1 using a first humidity sensor, for example: H_t1 = 65%RH. In this embodiment, the preset temporary humidity range is H_t0 = 50-70%RH. If H_t1 is within H_t0, such as 65%RH, then the current ambient humidity is determined to be within the range that requires self-testing. Sensor drift is likely to occur within this range, and the control system enters "self-testing mode". If H_t1 is not located within H_t0, such as H_t1=45%RH or 75%RH, then the ambient humidity is determined to be stable, the sensor drift risk is low, and it directly enters the "normal working mode".

[0047] In self-test mode, the control system starts the fan at a first set power of P_s1 = 1.0kW, generating an airflow of 200m³ / h. It then starts the heating device at a second set power of P_s2 = 0.3kW, raising the intake air temperature to 25℃. A second temporary humidity level H_t2 is collected every minute by a second humidity sensor, and this data is collected continuously for 10 minutes to generate a humidity change curve. For example, H_t2 might be 65%, 68%, 70%, 69%, 67%, 65%, 63%, 62%, 61%, and 60% respectively. Simultaneously, the control system calls a preset humidity reference curve. This curve is generated based on data collected by a standard sensor under the same conditions, and its trend is consistent with the H_t2 curve. A cosine similarity algorithm is used to calculate the graphical matching value S between the two curves, ranging from 0 to 1. The closer the value is to 1, the higher the matching degree. In this embodiment, the preset reference matching value S0 = 0.8. If S > S0, such as S = 0.85, the humidity sensor will pass the self-test and the operation screen will display "Sensor self-test passed, production can start". If S≤S0, such as S=0.75, a humidity sensor self-test abnormality prompt will be issued, and the operation screen will display "Sensor self-test abnormality, please calibrate or replace", and the device start-up permission will be locked until the sensor is calibrated successfully. After calibration with a standard humidity generator, S can be raised to above 0.9.

[0048] Reference Figure 3 This embodiment addresses power balancing for a parallel layout of multiple drying drums, and is suitable for multi-line synchronous production scenarios. The specific method also includes the following steps: In this embodiment, four drying drums (numbered A, B, C, and D) are arranged side by side, each corresponding to one fan, with independent inlet and outlet. The control system collects the real-time power P_real of each fan, for example: A=1.2kW, B=1.3kW, C=1.2kW, D=1.3kW, and calculates the power uniformity P_avg=(P_real_A+P_real_B+P_real_C+P_real_D) / 4, where P_avg=1.25kW. Within a preset working time T_work=60 minutes, the control system calculates the average power uniformity P_avg_mean within this time period. For example, if P_avg remains stable at 1.25kW for 60 minutes, then P_avg_mean=1.25kW. In this embodiment, the preset reference uniformity P_ref=1.3kW. If P_avg_mean < P_ref, such as 1.25kW < 1.3kW, then the base power of each fan is determined to be too low and needs to be uniformly increased to meet the drying requirements. First, calculate the power difference ΔP = P_ref - P_avg_mean, where ΔP = 0.05kW. Then, increase the base power ΔP_base of each fan using the formula: ΔP_base = ΔP × 2, where 2 is the optimal adaptation coefficient obtained from the experiment. At this point, ΔP_base = 0.1kW. The base power of each fan is uniformly increased by 0.1kW from the original 1.2kW, 1.3kW, etc., to 1.3kW, 1.4kW, etc., to ensure that the drying speed of each parallel drying barrel is consistent and to avoid the difference of drying barrel A for 120 minutes and barrel B for 100 minutes.

[0049] This embodiment addresses the rotational speed adjustment of parallel drying drums, and is suitable for scenarios where the residence time of materials inside the drum needs to be adapted to the power. The specific method also includes the following steps: Based on the above parallel layout, the control system first calculates the average power P_mean of each drying drum fan during the working time T_work=60 minutes, for example: A=1.25kW, B=1.35kW, C=1.2kW, D=1.4kW. Then, it calculates the uniform distribution value S_p, which is the standard deviation of P_mean. At this time, S_p=√[((1.25-1.3)²+(1.35-1.3)²+(1.2-1.3)²+(1.4-1.3)²) / 4]≈0.087kW. In this embodiment, the preset reference distribution value S_p0=0.08kW is: If S_p < S_p0, such as 0.07kW, then the power distribution is considered uniform and there is no need to adjust the speed. If S_p ≥ S_p0, such as 0.087kW, then calculate the average power ratio R_p = maximum P_mean / minimum P_mean. In this case, maximum P_mean = 1.4kW, minimum = 1.2kW, R_p = 1.4 / 1.2 ≈ 1.167. Adjust the rotation speed of the corresponding drying drum according to the negative correlation of R_p. The drying drum has a built-in stirring paddle, and the rotation speed can be adjusted within the range of 10-30rpm. The adjustment formula is: rotation speed n = original rotation speed n0 / R_p. The original rotation speed n0 = 20rpm. At this time, the rotation speed of the drum with the highest power, D, is n_D = 20 / 1.167 ≈ 17rpm, and the rotation speed of the drum with the lowest power, C, is n_C = 20 / (1.2 / 1.4) ≈ 23rpm. Because the power of C is small, the rotation speed needs to be increased to extend the material residence time and ensure sufficient drying. The power of D is large, so the rotation speed needs to be reduced to avoid over-drying.

[0050] This embodiment addresses the cooling protection of equipment during high-load operation to prevent overheating and its lifespan. The specific method also includes the following steps: The control system collects the real-time power P_eq of the equipment in real time through a power sensor installed at the main power supply of the drying equipment. This includes the total power of all components such as the fan, heating module, and refrigeration module. In this embodiment, the maximum power P_eq_max is preset to 5.0kW, and the rated total power of the equipment is: If P_eq≤P_eq_max, such as 4.8kW, then the cooling module will operate at its original base power. If P_eq > P_eq_max, such as 5.5kW, then calculate the equipment power comparison value K_eq = P_eq / P_eq_max. At this time, K_eq = 5.5 / 5.0 = 1.1. Based on the positive correlation of K_eq, adjust the cooling base power P_c_base of the cooling module. The original P_c_base = 0.8kW. The adjustment formula is: P_c_base' = P_c_base × K_eq. At this time, P_c_base' = 0.8 × 1.1 = 0.88kW. By increasing the cooling base power, the internal temperature of the equipment is reduced from 40℃ to below 35℃. The safe temperature range of the equipment is 0-40℃, avoiding damage to components due to overheating, such as overheating and tripping of the fan motor. At the same time, it ensures that the drying process is not affected by temperature fluctuations.

[0051] This application also discloses a field data-based shaping and drying equipment control system, including a processor, which executes the steps of the field data-based shaping and drying equipment control method as described in any of the above embodiments.

[0052] This application also discloses a storage medium storing a program that, when executed by a processor, implements the steps of the above-described control method for a shaping and drying equipment based on field data.

[0053] Although embodiments of this application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting this application. Those skilled in the art can make changes, modifications, substitutions and variations to the above embodiments within the scope of this application.

Claims

1. A control method for a shaping and drying equipment based on field data, characterized in that, Includes the following steps: The material quantity input into the drying drum is obtained based on the counting sensor. The air inlet power is matched from the preset air volume database according to the material quantity. The power of the fan blowing dry cold air into the drying drum is controlled according to the air inlet power. After a preset time period, the inlet humidity is generated based on the first humidity sensor installed on the air inlet side of the shaping and drying equipment, and the outlet humidity is generated based on the second humidity sensor installed on the air outlet side of the shaping and drying equipment. The difference between the outlet humidity and the inlet humidity is calculated as the humidity difference value. If the humidity difference value is greater than the preset humidity reference difference value, a humidity abnormality prompt is issued; otherwise, a humidity comparison value is calculated based on the humidity difference value and the humidity reference difference value, and the fan power is adjusted according to the positive correlation of the humidity comparison value. Based on the humidity anomaly alert, if the duration of the humidity anomaly alert is within a preset first duration range, the heating module located at the fan in the setting and drying equipment is activated, and the heating power of the heating module is adjusted according to the humidity difference. If the duration of the humidity anomaly alert is within a preset second duration range, the cooling module located at the fan in the setting and drying equipment is activated, the heating module is turned off, and the cooling power of the cooling module is adjusted according to the humidity difference. The values ​​in the second duration range are greater than the values ​​in the first duration range. If the humidity difference is less than the preset minimum difference, the shaping and drying process will stop, and the material will be output from the drying drum.

2. The control method for shaping and drying equipment based on field data according to claim 1, characterized in that, The method also includes the following steps: Within a preset batch of materials, the total operating time of the blower is calculated as the drying time, and the time for adjusting the blower power is calculated as the control time. The ratio of control time to drying time is calculated as the control ratio. If the control ratio is within the preset first reference ratio range, the first control ratio value is calculated based on the minimum value between the control ratio and the first reference ratio range, and the set duration is adjusted according to the positive correlation of the first control ratio value. If the control ratio is within the preset second reference ratio range, the second control ratio value is calculated based on the minimum value between the control ratio and the second reference ratio range, and the control coefficient for controlling the fan power based on the air intake power is adjusted according to the positive correlation of the second control ratio value. The values ​​within the second reference ratio range are greater than those within the first reference ratio range.

3. The control method for a shaping and drying equipment based on field data according to claim 1 or 2, characterized in that, The method also includes the following steps: The blower is located near the material output of the drying drum and can rotate to blow air; The fluctuation value of the humidity difference is calculated within a preset calculation time. If the fluctuation value is less than the preset fluctuation reference value, the fan is controlled to reciprocate to blow the drying drum, and the angle range of the fan rotation is adjusted according to the negative correlation of the fluctuation value; otherwise, the fan's posture is controlled to reset and remain fixed.

4. The control method for shaping and drying equipment based on field data according to claim 3, characterized in that, The method also includes the following steps: Multiple drying drums are set up and connected in series along the material conveying direction. Each drying drum is equipped with a fan, a first humidity sensor and a second humidity sensor. In the material conveying direction, the control coefficient of the fan power gradually decreases, and the sensing accuracy of the first humidity sensor and the second humidity sensor gradually decreases.

5. The control method for shaping and drying equipment based on field data according to claim 1, characterized in that, The method also includes the following steps: Before feeding materials into the drying drum, the first temporary humidity is collected by the first humidity sensor. If the first temporary humidity is within the preset temporary humidity range, the self-test mode is entered; otherwise, the normal operation mode is entered. In self-test mode, the fan is started according to the first set power, and the heating device is started according to the second set power; the second temporary humidity is collected by the second humidity sensor, and the curve of the second temporary humidity is calculated as the humidity change curve; the graphic matching value of the humidity change curve and the preset humidity reference curve is calculated. If the graphic matching value is greater than the preset reference matching value, the humidity sensor self-test passes the prompt; otherwise, the humidity sensor self-test fails the prompt.

6. The control method for shaping and drying equipment based on field data according to claim 4, characterized in that, The method also includes the following steps: Calculate the real-time power of the fans corresponding to multiple parallel drying drums, and calculate the average value of the multiple real-time power as the power average value. The average value of the power uniformity is calculated within the preset working time. If the average value is less than the preset reference uniform value, the basic power of the fan is increased for multiple fans, and the basic power of the fan is adjusted according to the positive correlation between the reference uniform value and the average value.

7. The control method for shaping and drying equipment based on field data according to claim 6, characterized in that, The method also includes the following steps: Calculate the average power of the fans corresponding to multiple parallel drying drums within the preset working time, and calculate the uniform value of the multiple average power as the distribution uniform value. If the uniform distribution value is less than the preset reference distribution value, the ratio between multiple average powers is calculated as the average power ratio; the rotation speed of the corresponding drying drum is adjusted according to the negative correlation of the average power ratio.

8. The control method for shaping and drying equipment based on field data according to claim 1, characterized in that, The method also includes the following steps: Obtain the real-time power of the shaping and drying equipment. If the real-time power is greater than the preset maximum power, calculate the ratio of the real-time power to the maximum power as the equipment power comparison value, and adjust the basic cooling power of the refrigeration module according to the positive correlation of the equipment power comparison value.

9. A control system for a shaping and drying equipment based on field data, characterized in that, Includes a processor, wherein the steps of the field data-based shaping and drying equipment control method as described in any one of claims 1-8 are executed.

10. A storage medium, characterized in that, The storage medium stores a program that, when executed by a processor, implements the steps of the field data-based shaping and drying equipment control method according to any one of claims 1-8.

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