A spray drying microencapsulation prilling system and method with an internal fluidized bed

Abstract

The application discloses a spray drying micro-capsule granulation system and method with an internal fluidized bed, and relates to the technical field of micro-capsule spray granulation. The system comprises a granulation tower, an internal fluidized bed, a first detection unit, a state sensing unit, an external fluidized bed, a second detection unit, a numerical simulation unit and a control unit. The primary particles generated by the internal fluidized bed drying granulation tower form a semi-finished product, and the semi-finished product is dried by the external fluidized bed to obtain a finished product. The numerical model unit creates and updates a first-order numerical model of the internal fluidized bed and a second-order numerical model of the external fluidized bed. The control unit evaluates the credibility of the humidity of the semi-finished product through the first-order numerical model, adjusts the operation parameters of the external fluidized bed through the second-order numerical model, and updates the first-order numerical model based on the updated second-order numerical model after updating the second-order numerical model through the humidity of the finished product. The two-stage drying is realized in a cooperative and adaptive control mode, and the product quality stability and system robustness are effectively improved.

Description

Technical Field

[0001] This invention relates to microcapsule spray granulation technology, and more particularly to a spray drying microcapsule granulation system and method with a built-in fluidized bed. Background Technology

[0002] Spray drying granulation technology is one of the important methods for preparing microencapsulated products. To overcome the problems of uneven particle size and excessive fine powder inherent in traditional single fluidized beds, existing technologies have introduced a scheme combining an internal fluidized bed with a granulation tower. For example, Chinese patent application CN101822963A discloses a dual-fluidized microencapsulation granulation system. This system effectively extends the material residence time by setting an internal fluidized bed within the granulation tower, improves fluidization quality through a stirring device, and utilizes a dust removal and return system to recover fine powder at the top of the granulation tower, effectively improving particle uniformity and raw material utilization. However, the moisture content and other parameters of the semi-finished product produced from the internal fluidized bed directly determine the optimal drying conditions required by the external fluidized bed. The operating parameters of the external fluidized bed in this system are usually set based on fixed empirical values ​​and cannot be adaptively adjusted according to the actual output of the preceding process. When the material state fluctuates, the external fluidized bed, with its fixed operating parameters, is difficult to dynamically adjust based on the semi-finished product from the preceding process, easily causing the drying effect to deviate from the ideal range. If the operating parameters of the external fluidized bed are set too high (such as excessively high inlet air temperature or excessive inlet air volume), overheating may occur when the particles in the external fluidized bed are nearing the drying endpoint, leading to deactivation of the heat-sensitive core material, embrittlement of the microcapsule shell, or even melting and adhesion. Conversely, if the operating parameters of the external fluidized bed are set too low, insufficient dehydration may result in excessive residual moisture in the finished product, affecting the flowability and storage stability of the finished product. Therefore, the existing technology needs further improvement. Summary of the Invention

[0003] To address the aforementioned issues, this invention provides a spray drying microcapsule granulation system and method with a built-in fluidized bed. The system evaluates the reliability of the semi-finished product humidity using a first-order numerical model of the built-in fluidized bed. Based on this reliability, the operating parameters of the external fluidized bed are precisely adjusted in advance using a second-order numerical model and the semi-finished product humidity, achieving active synergy between the two fluidized beds. Furthermore, the two-stage model is updated in reverse based on the accurate finished product humidity, realizing closed-loop optimization control of the model and the drying process.

[0004] The objective of this invention can be achieved through the following technical solutions:

[0005] A spray-drying microcapsule granulation system with a built-in fluidized bed includes:

[0006] A granulation tower, configured to atomize liquid to generate primary particles;

[0007] An internal fluidized bed is provided inside the granulation tower, which is configured to dry the primary particles to form a semi-finished product;

[0008] The first detection unit for detecting the humidity of semi-finished products;

[0009] A state sensing unit that collects built-in fluidized bed state parameters;

[0010] An external fluidized bed is set outside the granulation tower, and this external fluidized bed is configured to dry the semi-finished product to obtain the finished product;

[0011] The second detection unit for detecting the humidity of the finished product;

[0012] A numerical simulation unit configured to create and update first-order and second-order numerical models;

[0013] A control unit configured to adjust at least one set of operating parameters of an external fluidized bed based on the first-order numerical model and the second-order numerical model, wherein,

[0014] The numerical simulation unit creates a first-order numerical model based on the structural parameters of the built-in fluidized bed and a second-order numerical model based on the structural parameters of the external fluidized bed.

[0015] The numerical simulation unit updates the second-order numerical model based on the operating parameters of the external fluidized bed and the finished product humidity, and updates the first-order numerical model based on the second-order numerical model and the state parameters of the internal fluidized bed.

[0016] The control unit calculates the reliability of the semi-finished product humidity based on a first-order numerical model and adjusts the operating parameters of the external fluidized bed according to a second-order numerical model.

[0017] In this invention, the semi-finished product outlet of the built-in fluidized bed and the semi-finished product inlet of the external fluidized bed are connected by a conveying pipe. The first detection unit is set on the conveying pipe. The granulation tower has a packaging material channel. The status sensing unit includes a temperature sensor set on the built-in fluidized bed, a humidity sensor set on the air inlet of the built-in fluidized bed, and a temperature sensor and a humidity sensor set on the air outlet of the granulation tower.

[0018] In this invention, the numerical simulation unit updates the drying kinetic parameters in the second-order numerical model with the finished product humidity obtained by the second detection unit, calculates the calibration value of the semi-finished product humidity based on the updated second-order numerical model, and updates the drying kinetic parameters in the first-order numerical model with the calibration value.

[0019] In this invention, the control unit first predicts the reliability of the semi-finished product humidity using a first-order numerical model. If the reliability is higher than a preset threshold, the operating parameters of the external fluidized bed are calculated based on a second-order numerical model; otherwise, the external fluidized bed uses fixed operating parameters.

[0020] A granulation method for use in the spray-dried microcapsule granulation system includes the following steps:

[0021] Step 1: Create a first-order numerical model based on the structural parameters of the built-in fluidized bed, and create a second-order numerical model based on the structural parameters of the external fluidized bed;

[0022] Step 2: The liquid feed enters the granulation tower from the atomizing nozzle. Packaging material is sprayed into the bottom of the granulation tower. The packaging material coats the liquid feed to form primary particles, which then fall into the built-in fluidized bed at the bottom of the granulation tower.

[0023] Step 3: The primary particles are dried in a built-in fluidized bed to form a semi-finished product, and the moisture content of the semi-finished product is measured.

[0024] Step 4: Obtain the state parameters of the built-in fluidized bed, calculate the reliability of the semi-finished product humidity based on the first-order numerical model, and adjust the operating parameters of the external fluidized bed according to the second-order numerical model.

[0025] Step 5: The semi-finished product enters the external fluidized bed through the conveying pipe. The external fluidized bed performs secondary drying on the semi-finished product to obtain the finished product. The moisture content of the finished product is then measured.

[0026] Step 6: Update the second-order numerical model based on the operating parameters of the external fluidized bed and the finished product humidity, update the first-order numerical model based on the second-order numerical model and the state parameters of the internal fluidized bed, and return to step 2.

[0027] In this invention, in step 1, the first-order numerical model predicts the theoretical humidity of the semi-finished product based on the state parameters of the built-in fluidized bed, and the second-order numerical model predicts the theoretical humidity of the finished product based on the humidity of the semi-finished product and the operating parameters of the external fluidized bed. Both the first-order and second-order numerical models are composed of mutually coupled mass balance equations, drying kinetic equations, and energy balance equations.

[0028] In this invention, in step 4, the theoretical semi-finished product humidity is predicted based on the first-order numerical model and the state parameters of the built-in fluidized bed. The reliability of the semi-finished product humidity is the deviation value between the theoretical semi-finished product humidity and the semi-finished product humidity.

[0029] In this invention, in step 4, if the confidence level of the semi-finished product humidity is higher than a preset threshold, the semi-finished product humidity is used as an input parameter, and the operating parameters of the external fluidized bed are solved using a second-order numerical model as a function to make the theoretical finished product humidity predicted by the second-order numerical model closest to the target finished product humidity; otherwise, the external fluidized bed uses fixed operating parameters.

[0030] In this invention, in step 6, the theoretical finished product humidity is predicted based on the second-order numerical model, the semi-finished product humidity, and the operating parameters of the external fluidized bed. With the goal of minimizing the error between the finished product humidity and the theoretical finished product humidity, the drying kinetic parameters in the second-order numerical model are updated. Then, based on the updated second-order numerical model and the finished product humidity, the calibration value of the semi-finished product humidity is calculated by inversion. Based on the state parameters of the built-in fluidized bed and the calibration value, the drying kinetic parameters in the first-order numerical model are updated.

[0031] The spray drying microcapsule granulation system and method with a built-in fluidized bed of the present invention has the following beneficial effects: The present invention creates a first-order numerical model based on the structural parameters of the built-in fluidized bed and a second-order numerical model based on the structural parameters of an external fluidized bed. The built-in fluidized bed dries primary particles to generate a semi-finished product, and the external fluidized bed dries the semi-finished product to generate the finished product. The humidity of the semi-finished product is obtained through a first detection unit. The theoretical humidity of the semi-finished product is predicted based on the first-order numerical model, and the reliability of the humidity is calculated based on this theoretical humidity. When the reliability exceeds a preset threshold, the operating parameters of the external fluidized bed are adjusted according to the humidity of the semi-finished product; otherwise, the preset fixed operating parameters are automatically activated. To ensure the prediction accuracy of the first-order numerical model, the second-order numerical model is first updated with high-precision finished product humidity, and then the first-order numerical model is updated based on the updated second-order numerical model. Through this cascaded control method, precise control of the drying process is achieved, effectively improving the consistency of the final finished product humidity, and enhancing the system's stable operation capability under complex working conditions. Attached Figure Description

[0032] Figure 1 This is a block diagram of the spray drying microcapsule granulation system with a built-in fluidized bed according to the present invention;

[0033] Figure 2 This is a schematic diagram of the spray-drying microcapsule granulation system of the present invention;

[0034] Figure 3 This is a schematic diagram of the external fluidized bed of the present invention;

[0035] Figure 4 This is a graph showing the particle temperature inside the external fluidized bed of the present invention.

[0036] Figure 5 This is a schematic diagram of the production line for the spray-drying microcapsule granulation system of the present invention;

[0037] Figure 6 These are some of the equipment model parameters for the spray-drying microcapsule granulation system of the present invention;

[0038] Figure 7 This is another part of the equipment model parameters for the spray-drying microcapsule granulation system of the present invention;

[0039] Figure 8 These are some of the process parameters of the spray-drying microcapsule granulation system of the present invention;

[0040] Figure 9 This is a flowchart of the granulation method of the present invention applied to a spray-drying microcapsule granulation system;

[0041] Figure 10 The original near-infrared spectrum of the semi-finished product of this invention;

[0042] Figure 11 This is the near-infrared spectrum of the pretreated semi-finished product of the present invention;

[0043] Figure 12 This is a schematic diagram of the production cycle of the present invention.

[0044] The reference numerals in the attached drawings are as follows: granulation tower 1, atomizing nozzle 101, packaging material channel 102, exhaust port 103, cylinder 104, cone 105, built-in fluidized bed 2, upper chamber 201, lower chamber 202, air distribution plate 203, external fluidized bed 3, spring support 301, frame 302, drying chamber 303, cooling chamber 304, hot air inlet 305, cold air inlet 306, semi-finished product inlet 307, finished product outlet 308, hot air device 4, blower 401, air filter 402, heater 403, first detection unit 5, rotary screen 501, conveying pipe 502, gas-solid separation equipment 601, airlock 602, induced draft fan 603, liquid silo 7, powder silo 8, finished product silo 9. Detailed Implementation

[0045] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention.

[0046] Traditional spray-dried microcapsule granulation typically employs a separate layout of "granulation tower + external fluidized bed." The operation of this traditionally designed external fluidized bed is isolated, with control strategies based either on fixed parameters or relying solely on local feedback from its own inlet or outlet (such as a single humidity sensor). This control mode completely fails to perceive the actual output status of the preceding granulation process, and even less can it proactively adjust the drying intensity of this stage based on the real-time characteristics of the preceding output materials (such as humidity trends). Therefore, traditional systems lack the ability to coordinate and control the material state of the entire production line, resulting in poor adaptability to raw material fluctuations and changes in operating conditions, ultimately manifesting as insufficient product humidity stability and high energy consumption.

[0047] This invention integrates a built-in fluidized bed at the bottom of the granulation tower and an external fluidized bed on the outside, forming a compact and efficient two-stage tandem drying process. The system acquires the semi-finished product humidity in real time, reflecting the output of the semi-finished product from the built-in fluidized bed, based on a first detection unit, and adjusts at least one operating parameter (such as inlet air temperature and air volume) of the external fluidized bed based on this humidity. Furthermore, the working environment where the first detection unit is located is harsh; the sensor probe is easily contaminated by moist, sticky particles or adhering dust, causing its measurement signal to drift slowly or distort suddenly. To verify the accuracy of the semi-finished product humidity, this invention calculates the theoretical semi-finished product humidity using a first-order numerical model and compares this theoretical humidity with the humidity acquired by the first detection unit to assess the reliability of the humidity reading. The first-order numerical model is then updated based on a second-order numerical model, thereby fully leveraging the efficiency advantages of the two-stage drying process while ensuring the accuracy and robustness of the final control. Example 1

[0048] Reference Figures 1 to 8 The spray drying microcapsule granulation system of the present invention, which is equipped with a built-in fluidized bed, as detailed in this embodiment, includes: a granulation tower 1, a built-in fluidized bed 2 disposed in the granulation tower 1, a first detection unit 5 for detecting the humidity of the semi-finished product, a state sensing unit for collecting the state parameters of the built-in fluidized bed 2, an external fluidized bed 3 disposed outside the granulation tower 1, a second detection unit for detecting the humidity of the finished product, a numerical simulation unit, and a control unit.

[0049] The granulation tower 1 is configured to atomize the feed liquid to generate primary particles. An atomizing nozzle 101 for atomizing the feed liquid is located at the top center of the granulation tower 1. The atomizing nozzle 101 is connected to a liquid storage tank 7 containing the feed liquid. A pump delivers the feed liquid from the liquid storage tank 7 to the atomizing nozzle. The pump frequency and the atomizing nozzle frequency are adjusted according to the particle size of the target finished product; the pump frequency is typically 20 Hz, and the nozzle frequency is typically 25 Hz. A packaging material channel 102 is located in the middle of the side of the granulation tower, and an exhaust port 103 is located at the top of the side for discharging drying exhaust gas and guiding it to the subsequent recovery device. The upper part of the granulation tower 1 is a cylindrical body 104, and the lower part is a cone 105 that guides the primary particles to converge. The outlet below the cone 105 is directly connected to the primary particle inlet of the built-in fluidized bed.

[0050] Reference Figure 5 In this embodiment, before spray granulation, crude oil and auxiliary materials need to be added to the oil melting tank, and the auxiliary materials and crude oil in the oil melting tank are heated to 55°C. After the emulsification tank is heated to 65 to 70°C, the mixed solution of crude oil and auxiliary materials is slowly added to the emulsification tank, the agitator is turned on, the emulsification time is usually 35 to 45 minutes, the temperature is maintained at 65 to 70°C, and the viscosity of the liquid obtained after emulsification is usually 200-230 centipoise.

[0051] An internal fluidized bed 2 is installed within the granulation tower 1. This internal fluidized bed 2 is configured to dry the primary particles to form a semi-finished product. The cavity of the internal fluidized bed 2 is divided into an upper chamber 201 at the top and a lower chamber 202 at the bottom, with an air distribution plate 203 between the upper chamber 201 and the lower chamber 202. The upper chamber 201 is an open structure, directly connected to the lower part of the cone of the granulation tower. A semi-finished product outlet is provided on the side of the upper chamber 201, which is connected to the semi-finished product inlet 307 of the external fluidized bed 3 via a conveying pipe 502. An air inlet is provided on the side of the lower chamber 202. Hot air enters the cavity of the internal fluidized bed 2 through the air inlet, penetrates the primary particles, flows upward, and is discharged from the exhaust port at the top of the granulation tower 1. The inlet air temperature of the internal fluidized bed 2 is typically controlled between 80-120℃. In this embodiment, a pressure sensor is also installed inside the granulation tower to detect the negative pressure inside the granulation tower. The negative pressure inside the granulation tower must always be maintained at 100-400Pa, and the negative pressure inside the tower is regulated by the granulation tower exhaust fan.

[0052] The first detection unit 5 is used to detect the moisture content of the semi-finished product. To prevent excessively large or agglomerated abnormal particles from impacting, abrading, or even clogging the probe of the first detection unit 5, and to ensure that the particle group flowing through the probe has uniform physical properties, thereby guaranteeing the accuracy and stability of moisture measurement, a rotary screen 501 is also provided between the semi-finished product outlet of the built-in fluidized bed 2 and the first detection unit 5. The rotary screen 501 is configured to screen the semi-finished product. The undersize material of the rotary screen 501 is guided to the powder silo, while the oversize material is the semi-finished product with qualified particle size, which is then conveyed to the external fluidized bed. The probe of the first detection unit 5 is partially embedded in the wall of the conveying pipe 502, and the detection surface is in direct contact with the semi-finished product.

[0053] A state sensing unit is used to collect state parameters of the built-in fluidized bed 2. The state sensing unit includes a temperature sensor installed on the bed layer of the built-in fluidized bed 2, a humidity sensor installed at the air inlet of the built-in fluidized bed 2, and a temperature sensor and a humidity sensor installed at the exhaust outlet of the granulation tower 1. The temperature at the exhaust outlet of the granulation tower 1 must not exceed 75°C.

[0054] An external fluidized bed 3, located outside the granulation tower 1, is configured to dry the semi-finished product to obtain the finished product. (Refer to...) Figure 3The external fluidized bed 3 is, for example, a vibrating fluidized bed. The bed body of the vibrating fluidized bed is mounted on the frame 302 via spring supports 301, and the vibration force is provided by a vibrating motor installed at the bottom of the bed body. During the secondary drying process of the semi-finished product, the particle temperature is usually lower than the inlet temperature of the hot air. However, at the moment when drying is completed, the temperature rises rapidly until it approaches the inlet temperature of the hot air. At this time, the semi-finished product is in an unstable state, causing its internal heat-sensitive active ingredients to be deactivated or degraded due to overheating. It is also very easy for it to become damp and clump due to condensation caused by temperature differences during subsequent packaging. (Refer to...) Figure 4 To prevent the semi-finished product from continuously heating up, in this embodiment, the bed is divided into a drying chamber 303 and a cooling chamber 304 along the direction of semi-finished product movement. The drying chamber has a hot air inlet 305 at its bottom, and the cooling chamber has a cold air inlet 306 at its bottom. The semi-finished product inlet 307 at the top of the bed connects to the conveying pipe 502, and the finished product outlet 308 at the top of the bed connects to the finished product bin 9. In this embodiment, a vibrating screen is installed between the finished product bin 9 and the built-in fluidized bed 2. The aperture of the vibrating screen is typically 30-100 mesh. Hot air in the drying chamber 303 is provided by the hot air inlet 305, and cold air in the cooling chamber 304 is provided by the cold air inlet 306, thereby rapidly cooling the finished product to a stable state close to ambient temperature, suitable for safe packaging and storage. The cold air is dehumidified dried cold air with a dew point temperature lower than the temperature of the cooled finished product to prevent moisture condensation on the particle surface.

[0055] The second detection unit measures the humidity of the finished product. This unit includes an offline automatic sampler and a rapid moisture analyzer. The automatic sampler periodically collects samples from the finished product compartment 9, and the moisture analyzer uses benchmark methods such as thermogravimetric analysis to perform high-precision analysis on the samples, obtaining accurate finished product humidity data. Offline measurement avoids online sensor drift and provides unique and reliable standard data for subsequent updates to the first-order and second-order numerical models.

[0056] A numerical simulation unit is configured to create and update first-order and second-order numerical models. The unit creates a first-order numerical model based on the structural parameters of the built-in fluidized bed and a second-order numerical model based on the structural parameters of the external fluidized bed. The unit updates the second-order numerical model based on the operating parameters of the external fluidized bed and the finished product humidity, and updates the first-order numerical model based on the second-order numerical model and the state parameters of the built-in fluidized bed. Specifically, the unit updates the drying kinetic parameters in the second-order numerical model with the finished product humidity obtained by the second detection unit, calculates a calibration value for the semi-finished product humidity based on the updated second-order numerical model, and updates the drying kinetic parameters in the first-order numerical model with this calibration value.

[0057] A control unit. This control unit is configured to adjust at least one set of operating parameters of the external fluidized bed based on the first-order numerical model and the second-order numerical model. The control unit first calculates the reliability of the semi-finished product humidity using the first-order numerical model. If the reliability is higher than a preset threshold, it calculates the operating parameters of the external fluidized bed based on the second-order numerical model; otherwise, the external fluidized bed uses fixed operating parameters.

[0058] In this embodiment, a hot air device and a recovery device are also included. The hot air device 4 is configured to supply hot air to the built-in fluidized bed 2 and the external fluidized bed 3. The hot air device includes a blower 401, an air filter 402, and a heater 403. The air inlet of the blower 401 is connected to the ambient air, and the air outlet of the blower 401 is sequentially connected to the air filter 402 and the heater 403. The air outlet of the heater 403 is connected to the air inlet of the built-in fluidized bed 2 or the hot air inlet 305 of the drying chamber 303 of the external fluidized bed 3. A dryer may also be provided between the air filter 402 and the heater 403. The dryer may be a refrigerated dryer or an adsorption dryer. The recovery device is configured to recover the exhaust gas discharged from the exhaust ports of the external fluidized bed 3 and the granulation tower 1. The recovery device includes a gas-solid separation device 601. In this embodiment, the gas-solid separation device 601 includes, for example, a cyclone separator and a bag filter. Before spray granulation, all the starch (packaging material) in the bag filter needs to be discharged and transported back to the powder silo, with discharge occurring approximately every 20-30 minutes. The air inlet of the gas-solid separation device 601 is connected to the exhaust outlets of the granulation tower 1 and the external fluidized bed 3 via ducts. The bottom powder outlet of the gas-solid separation device 601 is equipped with a damper 602, which connects to the powder silo 8. The packaging material contained in the powder silo 8 is, for example, starch. The starch moisture content is typically maintained at 10-11%. If the starch moisture content is too low, the risk of dust explosion increases; if the starch moisture content is too high, it will cause clumping and reduced fluidity. The top of the gas-solid separation device 601 is connected to the inlet of the induced draft fan 603 to discharge the treated exhaust gas. Example 2

[0059] Reference Figures 5 to 11 A granulation method for use in the spray-dried microcapsule granulation system includes the following steps:

[0060] Step 1: Create a first-order numerical model based on the structural parameters of the built-in fluidized bed, and a second-order numerical model based on the structural parameters of the external fluidized bed. The first-order numerical model predicts the theoretical semi-finished product humidity based on the state parameters of the built-in fluidized bed, while the second-order numerical model predicts the theoretical finished product humidity based on the semi-finished product humidity and the operating parameters of the external fluidized bed. Both the first-order and second-order numerical models consist of mutually coupled mass balance equations, drying kinetic equations, and energy balance equations. The specific model structures of the first-order and second-order numerical models are detailed in Example 3.

[0061] Step 2: The feed liquid enters the granulation tower through the atomizing nozzle. Packaging material is sprayed into the bottom of the granulation tower, and the packaging material coats the feed liquid to form primary particles, which then fall into the built-in fluidized bed at the bottom of the granulation tower. Figure 5 Crude oil (e.g., vitamin oil) and excipients (e.g., ethoxyquinoline) are stirred evenly in a dissolving tank and then emulsified in an emulsification tank to obtain a liquid with a certain viscosity (e.g., vitamin emulsion). The screw pump is started, and the feed rate of the liquid is adjusted (200-250 liters / hour, gradually increasing from 200 liters / hour). Simultaneously, the feed rate of the packaging material is adjusted according to a liquid-to-packing-material ratio of 1:10. The atomizing nozzle rotates at 1000-1400 rpm. The atomizing nozzle at the top of the granulation tower atomizes the liquid into droplets. These droplets are coated by the packaging material and come into contact with hot air inside the granulation tower, evaporating approximately 60% of the water and rapidly forming primary granules. These primary granules fall into the built-in fluidized bed located at the bottom of the granulation tower under gravity.

[0062] Step 3: The primary particles are dried in the built-in fluidized bed to form a semi-finished product, and the moisture content of the semi-finished product is measured. The primary particles falling into the built-in fluidized bed are fluidized under the uniform hot air in the upper chamber, undergoing primary drying to further evaporate approximately 30% of the internal moisture, forming a semi-finished product. The semi-finished product is then passed through a rotary screen. The rotary screen, with an aperture of, for example, 120 mesh, guides the semi-finished product with the correct particle size to the external fluidized bed via a conveyor pipe. The undersize material is transported back to the powder silo, while the oversize material is the semi-finished product with the correct particle size. (Refer to...) Figure 10 and Figure 11 To meet the requirements of rapid detection, the first detection unit is, for example, a near-infrared sensor. The probe of the near-infrared sensor is embedded in the wall of the feed pipe. It emits near-infrared light and receives the original near-infrared spectrum of the semi-finished product. The humidity of the semi-finished product is obtained in real time by correcting the original near-infrared spectrum.

[0063] Step 4: Obtain the state parameters of the built-in fluidized bed, calculate the reliability of the semi-finished product humidity based on the first-order numerical model, and adjust the operating parameters of the external fluidized bed according to the second-order numerical model. Predict the theoretical semi-finished product humidity based on the first-order numerical model and the state parameters of the built-in fluidized bed. The reliability of the semi-finished product humidity is the deviation between the theoretical semi-finished product humidity and the actual semi-finished product humidity. If the reliability of the semi-finished product humidity is higher than a preset threshold, then the semi-finished product humidity is used as an input parameter (fixed condition), and an operating parameter optimization problem is constructed using the second-order numerical model as the core function. The operating parameters of the external fluidized bed that make the theoretical finished product humidity predicted by the second-order numerical model closest to the target finished product humidity are solved; otherwise, the external fluidized bed uses fixed operating parameters. Further, refer to... Figure 8 The preset range of operating parameters (e.g., inlet air temperature) for external fluidized beds is used. If the operating parameters predicted by the second-order numerical model exceed this preset range, the fixed operating parameters are also used.

[0064] In this embodiment, the operating parameter of the external fluidized bed is, for example, the inlet temperature of the hot air. To prevent the impact on the mechanical structure of the equipment caused by excessive single adjustment of the hot air inlet temperature, after the target inlet temperature of the external fluidized bed is calculated by a second-order numerical model, the hot air device is not directly instructed to jump to the target inlet temperature. Instead, based on the preset maximum safe temperature change rate and the thermal inertia of the equipment, a smooth transition setting curve from the current inlet temperature to the target inlet temperature is generated. This smooth transition setting curve is usually planned using an S-shaped function or a linear ramp to ensure that the instantaneous slope is never greater than the maximum safe temperature change rate. Subsequently, closed-loop tracking is performed using this smooth transition setting curve as the dynamic set value, so that the actual inlet temperature of the external fluidized bed smoothly and without overshoot approaches the target inlet temperature. This method can avoid the thermal stress impact on mechanical structures such as refractory linings caused by temperature step changes, ensuring the long-term reliability of the equipment.

[0065] Step 5: The semi-finished product enters an external fluidized bed via a feed pipe. The external fluidized bed performs secondary drying on the semi-finished product to obtain the finished product, and the moisture content of the finished product is measured. To ensure the reliability of the finished product moisture content relied upon for subsequent updates to the second-order numerical model, the second detection unit consists of an automatic sampler and a rapid moisture analyzer. The automatic sampler periodically collects samples from the finished product warehouse during the current production cycle and inputs the samples into the rapid moisture analyzer for measurement. The rapid moisture analyzer uses a drying and weighing method for measurement and outputs a high-precision finished product moisture content.

[0066] Step 6: Update the second-order numerical model based on the operating parameters of the external fluidized bed and the finished product humidity; update the first-order numerical model based on the second-order numerical model and the state parameters of the internal fluidized bed; return to Step 2. In this invention, in Step 6, the theoretical finished product humidity is predicted based on the second-order numerical model, the semi-finished product humidity, and the operating parameters of the external fluidized bed. With the goal of minimizing the error between the finished product humidity and the theoretical finished product humidity, the drying kinetic parameters in the second-order numerical model are updated. Then, based on the updated second-order numerical model and the finished product humidity, the calibration value of the semi-finished product humidity is calculated by inversion. Finally, the drying kinetic parameters in the first-order numerical model are updated based on the state parameters of the internal fluidized bed and the calibration value. Example 3

[0067] This embodiment further discloses the model structures of the first-order numerical model and the second-order numerical model. The first-order numerical model consists of a mass balance equation based on the built-in fluidized bed and granulation tower. Drying kinetic equations Energy balance equation The system is interconnected, where t1 is the drying time for the liquid to form a semi-finished product, R1 is the feed rate of the liquid, R2 is the total drying rate of the built-in fluidized bed, F1 is the feed rate of the packaging material, F2 is the discharge rate of the semi-finished product, and k1 is the drying kinetic parameter of the first-order numerical model. Physically, k1 is a lumped time-varying process parameter that comprehensively reflects the overall mass transfer coefficient and effective mass transfer area within the built-in fluidized bed and the connected granulation tower. Its specific value needs to be determined through experiments or system identification. X1 represents the dry basis moisture content. The initial value of X1 can be measured experimentally, i.e., X1 = M2 / M1. M1 is the total mass of dry solid material in the built-in fluidized bed, M2 is the total mass of wet material in the built-in fluidized bed, the initial value of M1 is the total mass of solid solute in the packaging material and feed liquid, the initial value of M2 is the total mass of solvent in the feed liquid, X2 is the equilibrium moisture content of the material under the inlet conditions (inlet temperature and inlet humidity) of the built-in fluidized bed, and C1 is the total heat capacity of the built-in fluidized bed, i.e., C1 = M1c3 + M2c4, c3 are the specific heat capacities of the dry solid materials (the combined average specific heat capacities of the solid solutes in the coating and feed liquid), c4 is the specific heat capacity of the wet materials (the specific heat capacity of the solvent in the feed liquid), ρ1 is the inlet air density of the built-in fluidized bed, V1 is the volumetric flow rate of the inlet air of the built-in fluidized bed, c1 is the isobaric specific heat capacity of the inlet air of the built-in fluidized bed, U1 is the total heat dissipation coefficient of the built-in fluidized bed and the granulation tower (equipment thermal parameters), A1 is the effective heat dissipation area of ​​the built-in fluidized bed and the granulation tower, T1 is the bed temperature in the built-in fluidized bed (equivalent to the temperature of the primary particles in the built-in fluidized bed), which can be measured in real time by thermocouples or resistance thermometers deeply buried in the built-in fluidized bed. The thermocouples or resistance thermometers are mainly in contact with the primary particles. T2 is the inlet air temperature of the built-in fluidized bed, T3 is the ambient temperature (room temperature), ΔH is the latent heat of vaporization of the liquid in the primary particles, Q1 represents the sensible heat brought in by the feed liquid and packaging material, and Q2 represents the sensible heat carried away by the semi-finished product flowing out. The theoretical semi-finished product moisture content (wet basis moisture content) Y1 = X1 / (X1+1). In this embodiment, the state parameters of the built-in fluidized bed include the bed temperature T1 in the built-in fluidized bed, the material equilibrium moisture content X2 when the inlet air humidity and inlet air temperature T2 are balanced, and the total drying rate R2.

[0068] The second-order numerical model is based on the mass balance equation of the external fluidized bed. Drying kinetic equations Energy balance equation The components are interconnected. In the second-order numerical model, the initial dry-to-moisture content X3 of the semi-finished product is equal to X1 output by the first-order numerical model. The bed temperature T4 of the external fluidized bed is equivalent to the temperature of the semi-finished product inside the external fluidized bed. The initial value of T4 is set based on the temperature of the semi-finished product at the outlet of the internal fluidized bed. Here, t2 is the drying time from semi-finished product to finished product, M3 is the total mass of dry solid material inside the external fluidized bed, and M4 is the total mass of wet material inside the external fluidized bed. The initial values ​​of M3 and M4 can be calculated from the moisture content of the semi-finished product; that is, the initial value of M3 is the total mass of dry solid material in the semi-finished product, and the initial value of M4 is the total mass of wet material in the semi-finished product. R3 is the total drying rate of the external fluidized bed, and F3 is the feed rate of the semi-finished product (F3=F2 in a single-batch continuous production process). 2. Drying kinetic parameters of the second-order numerical model: In a physical sense, k2 is also a lumped time-varying process parameter, comprehensively reflecting the overall mass transfer coefficient and effective mass transfer area of ​​the external fluidized bed. Its specific value needs to be determined through experiments or system identification. X4 is the material equilibrium moisture content at equilibrium under the inlet conditions (inlet temperature and inlet humidity) of the built-in fluidized bed. C2 is the total heat capacity of the external fluidized bed. ρ2 is the inlet density of the external fluidized bed. V2 is the volumetric flow rate of the inlet air of the external fluidized bed. C2 is the isobaric specific heat capacity of the inlet air of the external fluidized bed. T5 is the inlet temperature of the external fluidized bed. Q3 represents the sensible heat carried in by the semi-finished product. Q4 represents the sensible heat carried away by the finished product. U2 is the total heat dissipation coefficient of the external fluidized bed (equipment thermal parameters). A2 is the effective heat dissipation area of ​​the external fluidized bed. In this embodiment, the calculation of Q1, Q2, Q3, and Q4 is based on a simplification with the reference temperature at zero. The theoretical finished product moisture content (wet basis moisture content) Y2 = X3 / (X3+1). In this embodiment, the operating parameters of the external fluidized bed are, for example, the inlet temperature of the hot air. Example 4

[0069] The semi-finished product humidity acquired by the first detection unit is instantaneous, localized measurement information, easily affected by errors such as drift of the first detection unit. The external fluidized bed, however, is the final product forming unit. The finished product humidity acquired by the second detection unit is the only offline, high-precision measurement information during the production process. This most reliable finished product humidity can be used to back-correct the drying kinetic parameter k2 in the second-order numerical model. Then, based on the updated second-order numerical model and the finished product humidity inversion, the calibration value of the semi-finished product humidity is calculated. Finally, based on the state parameters of the built-in fluidized bed and the calibration value, the drying kinetic parameter k1 in the first-order numerical model is updated. (Refer to...) Figure 12 This embodiment further discloses a preferred method for updating the first-order numerical model and the second-order numerical model in step 6.

[0070] Update Phase 1: Collect the operating parameters of the external fluidized bed, the semi-finished product humidity Y3 obtained by the first detection unit, and the finished product humidity Y4 obtained by the second detection unit during the (n-1)th production cycle. Calculate the initial value of the corresponding dry-basis moisture content X3 based on the semi-finished product humidity Y3. Using the operating parameters of the external fluidized bed and the initial value of the dry-basis moisture content X3 as input, run the current second-order numerical model to obtain the theoretical finished product humidity Y2. Adjust the drying kinetic parameter k2 in the second-order numerical model through an optimization algorithm to make the theoretical finished product humidity Y2 infinitely close to the measured finished product humidity Y4, i.e., by minimizing (Y2 - Y4). 2 Update the second-order numerical model for the target.

[0071] Update Phase 2: Using the finished product humidity Y4 from the (n-1)th production cycle and the corresponding operating parameters of the external fluidized bed as fixed conditions, the updated second-order numerical model is solved in reverse to obtain the calibration value Y5 for the semi-finished product humidity. Using the state parameters of the built-in fluidized bed from the (n-1)th production cycle as input, the current first-order numerical model is run to obtain the theoretical semi-finished product humidity Y1. The drying kinetic parameter k1 in the first-order numerical model is adjusted using an optimization algorithm to make the theoretical semi-finished product humidity Y1 infinitely close to the calibration value Y5, i.e., by minimizing (Y1 - Y5). 2 Update the first-order numerical model for the target.

[0072] The nth production cycle is executed based on the updated first-order and second-order numerical models.

[0073] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A spray-drying microencapsulation prilling system provided with an internal fluidized bed, characterized in that, The application comprises: a prilling tower configured to generate primary particles after atomizing a feed liquid; an internal fluidized bed arranged in the prilling tower and configured to form semi-finished products after drying the primary particles; a first detection unit configured to detect the humidity of the semi-finished products; a state sensing unit configured to collect state parameters of the internal fluidized bed; an external fluidized bed arranged outside the prilling tower and configured to obtain finished products after drying the semi-finished products; a second detection unit configured to detect the humidity of the finished products; a numerical simulation unit configured to create and update a first-order numerical model and a second-order numerical model; a control unit configured to adjust at least one set of operating parameters of the external fluidized bed based on the first-order numerical model and the second-order numerical model, wherein the numerical simulation unit creates the first-order numerical model based on the structural parameters of the internal fluidized bed and creates the second-order numerical model based on the structural parameters of the external fluidized bed; the numerical simulation unit updates the second-order numerical model based on the operating parameters of the external fluidized bed and the humidity of the finished products, and updates the first-order numerical model based on the second-order numerical model and the state parameters of the internal fluidized bed; the control unit calculates the reliability of the humidity of the semi-finished products based on the first-order numerical model and adjusts the operating parameters of the external fluidized bed according to the second-order numerical model, the control unit first predicts the reliability of the humidity of the semi-finished products through the first-order numerical model, if the reliability is higher than a preset threshold, calculates the operating parameters of the external fluidized bed based on the second-order numerical model, otherwise, uses fixed operating parameters of the external fluidized bed.

2. The spray drying microencapsulation prilling system with built-in fluidized bed according to claim 1, characterized in that, The semi-finished product outlet of the internal fluidized bed is connected to the semi-finished product inlet of the external fluidized bed through a conveying pipe, the first detection unit is arranged on the conveying pipe, the prilling tower has a wrapping material channel, and the state sensing unit comprises temperature sensors arranged in the bed layer of the internal fluidized bed, a humidity sensor arranged at the air inlet of the internal fluidized bed, and temperature and humidity sensors arranged at the air outlet of the prilling tower.

3. The spray drying microencapsulation prilling system with built-in fluidized bed as claimed in claim 1 wherein, The numerical simulation unit updates the drying kinetics parameters in the second-order numerical model with the humidity of the finished products obtained by the second detection unit, inversely calculates the calibration value of the humidity of the semi-finished products based on the updated second-order numerical model, and updates the drying kinetics parameters in the first-order numerical model with the calibration value.

4. A granulation method applied to the spray-drying microcapsule granulation system of claim 1, characterized by, The application comprises the following steps: Step 1: creating a first-order numerical model based on the structural parameters of the internal fluidized bed and a second-order numerical model based on the structural parameters of the external fluidized bed; Step 2: the feed liquid enters the prilling tower from the atomizing nozzle, the wrapping material is sprayed at the bottom of the prilling tower, and the primary particles formed by the wrapping material covering the feed liquid fall into the internal fluidized bed at the bottom of the prilling tower; Step 3: the internal fluidized bed performs primary drying on the primary particles to form semi-finished products, and the humidity of the semi-finished products is detected; Step 4: the state parameters of the internal fluidized bed are obtained, the reliability of the humidity of the semi-finished products is calculated based on the first-order numerical model, and the operating parameters of the external fluidized bed are adjusted according to the second-order numerical model; Step 5: the semi-finished products enter the external fluidized bed through the conveying pipe, the external fluidized bed performs secondary drying on the semi-finished products to obtain finished products, and the humidity of the finished products is detected. Step 6: updating the second-order numerical model based on the operating parameters of the external fluidized bed and the product moisture, updating the first-order numerical model based on the second-order numerical model and the state parameters of the internal fluidized bed, returning to Step 2, wherein, if the reliability of the semi-product moisture is higher than a preset threshold, constructing an operating parameter optimization problem with the second-order numerical model as the core, and solving the operating parameters of the external fluidized bed that make the theoretical product moisture predicted by the second-order numerical model closest to the target product moisture, otherwise, using fixed operating parameters of the external fluidized bed.

5. The granulation method according to claim 4, characterized in that, In Step 1, the first-order numerical model is used to predict the theoretical semi-product moisture based on the state parameters of the internal fluidized bed, the second-order numerical model is used to predict the theoretical product moisture based on the semi-product moisture and the operating parameters of the external fluidized bed, and both the first-order numerical model and the second-order numerical model are composed of mass balance equations, drying kinetics equations and energy balance equations that are coupled with each other.

6. The granulation method according to claim 4, characterized by, In Step 4, the theoretical semi-product moisture is predicted based on the first-order numerical model and the state parameters of the internal fluidized bed, and the reliability of the semi-product moisture is the deviation value between the theoretical semi-product moisture and the semi-product moisture.

7. The granulation method according to claim 4, characterized by, In Step 6, the theoretical product moisture is predicted based on the second-order numerical model, the semi-product moisture and the operating parameters of the external fluidized bed, the error minimization between the product moisture and the theoretical product moisture is taken as the target, the drying kinetics parameters in the second-order numerical model are updated, the calibrated value of the semi-product moisture is calculated based on the updated second-order numerical model and the product moisture, and the drying kinetics parameters in the first-order numerical model are updated based on the state parameters of the internal fluidized bed and the calibrated value.

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