An oil-in-water microcapsule spray drying granulation process

Abstract

The present invention discloses an oil-in-water microcapsule spray drying granulation process, which relates to the technical field of drying and granulation. This method uses a high-speed camera to collect real-time vertical cross-sectional images of the granulation chamber, and generates cross-sectional images of the granulation chamber by microwave tomography. Calculate the first feature difference between the vertical cross-sectional image and the first template feature, and the second feature difference between the cross-sectional image and the second template feature, and adjust the working parameters of the primary medium, secondary medium, suspended material, and rotary wall according to the first feature difference and the second feature difference. Further, to improve production efficiency and product quality, in the curing stage, a first cumulative difference is generated based on multiple groups of first feature differences, and a second cumulative difference is generated based on multiple groups of second feature differences. The first template feature and the second template feature are respectively updated based on the first cumulative difference and the second cumulative difference to achieve optimal control of the granulation process.

Description

Technical Field

[0001] The present invention relates to the technical field of drying and granulation, and particularly to an oil-in-water microcapsule spray drying granulation process. Background Art

[0002] As described in Chinese Patent Publication Nos. CN116036017A, CN111655362A, etc., the oil-in-water microcapsule consists of an internal oily core material and an external aqueous wall material. The particle size of the microcapsule particles and the humidity change during their formation are important indicators for evaluating the microcapsule granulation process. The prior art has disclosed methods for monitoring the particle size based on images of the granulation area. For example, the fluidized bed comprehensive monitoring system and method for tracking particles and spray movement disclosed in Chinese Patent Publication No. CN112973586A. This method uses image processing technology to track the velocity field of all fluidized particles in the fluidized bed, monitors the particle size distribution of the spray droplets in the fluidized bed, quantifies the influence relationship between the fluidized particles and the spray droplets in the fluidized bed based on the velocity field of the fluidized particles and the particle size distribution of the spray droplets, and then adjusts the spray parameters. This method estimates the particle size distribution using an algorithm and describes the three-dimensional space based on the two-dimensional motion state, which can improve the accuracy of particle size prediction. However, in the actual granulation process, the formation of microcapsule particles is jointly affected by multiple dynamic factors in the three-dimensional space. The humidity change in the granulation area can indirectly reflect the curing degree of the wall material, thereby affecting the stability of the final particle size distribution. A single two-dimensional instantaneous state cannot comprehensively reflect the dynamic characteristics of the granulation process. Therefore, it is necessary to propose a process for adjusting granulation parameters by combining multiple instantaneous states. Summary of the Invention

[0003] In view of the above problems, the present invention provides an oil-in-water microcapsule spray drying granulation process, which sets the granulation working parameters according to multiple groups of vertical cross-section images and state templates, and at the same time adjusts the state template of the granulation work according to the granulation characteristics at historical moments, so as to improve the accuracy of granulation parameter calibration.

[0004] The object of the invention of the present application can be achieved by the following technical means:

[0005] An oil-in-water microcapsule spray drying granulation process, comprising the following steps:

[0006] Step 1: Prepare a suspension material from an oily core material and an aqueous wall material, preset a parameter template, a first state template, and a second state template, convey a primary medium to the granulation chamber, and recover a secondary medium from the granulation chamber;

[0007] Step 2: Control the working parameters of the primary medium until the granulation chamber reaches the preheating temperature, initialize the working duration t, and open the rotary wall;

[0008] Step 3: The atomizing nozzle sprays the suspension material into the granulation chamber, and controls the working parameters of the secondary medium, the suspension material, and the rotary wall according to the parameter template;

[0009] Step 4: Collect multiple groups of vertical cross-section images and cross-section images of the granulation chamber at the working time t, respectively extract multiple groups of first template features and second template features of the first state template and the second state template at the working time t, and calculate the first feature difference between the vertical cross-section image and the first template features, and the second feature difference between the cross-section image and the second template features;

[0010] Step 5: If the absolute value of the first feature difference is greater than D1 or the absolute value of the second feature difference is greater than D2, adjust the working parameters of the primary medium, the secondary medium, the suspension material, and the rotary wall according to the first feature difference and the second feature difference;

[0011] Step 6: If t is less than the curing time T1, return to Step 3, otherwise enter Step 7;

[0012] Step 7: Close the atomizing nozzle, calculate the first cumulative difference and the second cumulative difference respectively based on multiple groups of the first feature differences and the second feature differences within the curing time T1, and update multiple groups of the first template features and the second template features according to the first cumulative difference and the second cumulative difference;

[0013] Step 15: Repeat Steps 4 to 5, and then adjust the working parameters of the primary medium, the secondary medium, and the rotary wall;

[0014] Step 18: If t - T1 is less than the fluidization time T2, return to Step 8, otherwise close the circulation channel and collect the microcapsule particles.

[0015] In the present invention, in Step 1, the oily core material is plant essential oil, wherein thymol ≥ 13.5 wt% and cinnamaldehyde ≥ 6.5 wt% in the plant essential oil, the aqueous wall material is an aqueous solution of dextrin and starch, and the mass ratio of the oily core material to the aqueous wall material in the suspension material is 1:4 to 1:6.

[0016] In the present invention, in Step 2, the parameter template consists of the working parameters of the primary medium, the secondary medium, the suspension material, and the rotary wall at multiple working times. The working parameters of the primary medium include the medium flow rate and the medium temperature, the working parameters of the suspension material include the material flow rate and the atomization pressure, the working parameter of the secondary medium is the medium pressure, and the working parameter of the rotary wall is the rotation speed of the rotary wall.

[0017] In the present invention, in Step 4, the first state template includes multiple groups of first template features at multiple observation orientations at multiple working times, the second state template includes multiple groups of second template features at multiple cross-section positions at multiple working times, the first template features are standard vertical cross-section images, and the second template features are standard cross-section images.

[0018] In the present invention, in step 4, multiple sets of vertical cross-sectional images are obtained. For each set of vertical cross-sectional images, first, the particle contours of the microcapsule particles therein are extracted, the equivalent diameter of the particle contours is calculated, and then the particle size difference between the equivalent diameter and the standard vertical cross-sectional image corresponding to the observation orientation is calculated. The average value of the multiple sets of particle size differences is used as the first characteristic difference Δ1.

[0019] In the present invention, in step 4, multiple sets of cross-sectional images are obtained, and the gray value differences between each set of cross-sectional images and the standard cross-sectional images at the corresponding cross-section positions are calculated respectively. The average value of the multiple sets of gray value differences is used as the second characteristic difference Δ2.

[0020] In the present invention, in step 5, if the absolute value of the first characteristic difference is greater than D1 and the absolute value of the second characteristic difference is greater than D2, the working parameters of the primary medium, secondary medium, suspension material, and rotary wall are adjusted once. If the absolute value of the first characteristic difference is greater than D1 and the absolute value of the second characteristic difference is less than or equal to D2, the working parameters of the suspension material and rotary wall are adjusted. If the absolute value of the first characteristic difference is less than or equal to D1 and the absolute value of the second characteristic difference is greater than D2, the working parameters of the primary medium and secondary medium are adjusted.

[0021] In the present invention, in step 5, the adjustment amplitude δ1 is calculated according to Δ1 and D1, the adjustment amplitude δ2 is calculated according to Δ2 and D2, and the adjustment amounts of the respective working parameters are calculated based on the adjustment amplitude δ1, adjustment amplitude δ2, particle size weight W1, and humidity weight W2.

[0022] In the present invention, in step 7, the first cumulative difference , the second cumulative difference , where α1 is the mean value of the first characteristic difference within the curing duration T1, α2 is the mean value of the second characteristic difference within the curing duration T1, σ1 is the standard deviation of the first characteristic difference within the curing duration T1, σ2 is the standard deviation of the second characteristic difference within the curing duration T1, Δ1(t) is the first characteristic difference at the working duration t, and Δ2(t) is the second characteristic difference at the working duration t.

[0023] In the present invention, in step 7, the first template feature S1(t) of the working duration t = S1(t) + λ1Δ3, and the second template feature S2(t) = S2(t) + λ2Δ4, where λ1 and λ2 are template adjustment parameters.

[0024] Implementing the oil-in-water microcapsule spray drying granulation process of the present invention, its beneficial effects are as follows: The present invention adopts a dynamic control strategy that combines a parameter template with a first state template and a second state template. During the granulation process, by real-time collecting the vertical cross-sectional image and the cross-sectional image of the granulation chamber, and calculating the first feature difference between the vertical cross-sectional image and the first template feature and the second feature difference between the cross-sectional image and the second template feature, accurate process monitoring is achieved. When the first feature difference or the second feature difference exceeds the preset threshold, the system automatically adjusts the working parameters of the primary medium, secondary medium, suspension material, and rotary wall once to ensure the stability of the microcapsule particle formation process. In addition, this method conducts cumulative difference analysis during the curing stage and dynamically updates the first template feature and the second template feature, effectively avoiding the structural defects of microcapsule particles caused by excessive fluctuations in working parameters in the traditional method. Brief Description of the Drawings

[0025] Figure 1 It is a schematic diagram of the microcapsule granulation production line of the present invention;

[0026] Figure 2 It is a schematic diagram of the granulation chamber of the present invention;

[0027] Figure 3 It is a schematic diagram of the first template feature of the present invention;

[0028] Figure 4 It is a schematic diagram of the second template feature of the present invention;

[0029] Figure 5 It is a flowchart of the oil-in-water microcapsule spray drying granulation process of the present invention;

[0030] Figure 6 It is a schematic diagram of various working parameters of the parameter template of the present invention;

[0031] Figure 7 It is a schematic diagram of multiple groups of second template features of the second state template of the present invention;

[0032] Figure 8 It is a schematic diagram of generating the first feature difference of the present invention;

[0033] Figure 9 It is a schematic diagram of generating the first cumulative difference of the present invention.

[0034] Reference numerals in the drawings: granulation chamber 10, material bin 11, finished product bin 12, cyclone collector 13, medium bin 14, heat exchanger 15, pressure pump 16, first controller 21, second controller 22, third controller 23, fourth controller 24, fifth controller 25, sixth controller 26. Detailed Embodiments

[0035] The technical solutions in the embodiments of the present invention will be described clearly and completely below in conjunction with the accompanying drawings in the embodiments of the present invention.

[0036] In the composite granulation process of oily core material and water-based wall material, the existing technology adopts a static setting mode to control the working parameters of the granulator, which cannot be dynamically adjusted according to the state changes in the material generation process, and is difficult to adapt to the needs of different formulations, resulting in large differences in product quality between different batches, which limits the performance optimization and large-scale production of microcapsule particles. Figure 1 and Figure 2 , used in the microcapsule granulation production line based on the water-in-oil microcapsule spray drying granulation process of the present invention, the material bin 11 passes the suspended material mixed with the oily core material and the aqueous wall material into the granulation chamber 10, and the pressure pump 16 sprays the primary medium into the granulation chamber 10. The finished product bin 12 recovers the microcapsule particles. The cyclone collector 13 recovers the secondary medium. The microcapsule particles remaining in the secondary medium are recovered to the finished product bin 12 again. The secondary medium returns to the pressure pump 16 after passing through the medium bin 14 and the heat exchanger 15. The parameter template consists of the working parameters of the primary medium, the secondary medium, the suspended material and the rotating wall with multiple working times. Specifically, the first controller 21 adjusts the material flow rate. The second controller 22 adjusts the atomization pressure. The third controller 23 adjusts the working parameters of the primary medium (medium flow rate). The fourth controller 24 adjusts the working parameters of the primary medium (medium temperature). The fifth controller 25 adjusts the working parameters of the secondary medium (medium pressure). The sixth controller 26 adjusts the rotation speed of the rotating wall.

[0037] The present invention constructs a dual-template dynamic control mechanism: the first state template is used to quantify the average particle size characteristics of the microcapsule particles, and the second state template is a standard cross-sectional image in the granulation chamber, whose gray value distribution is used to characterize the humidity characteristics of the microcapsule particles, combined with real-time image analysis to achieve precise control. Figure 3 and Figure 4 As shown, the present invention sets multiple groups of first template features of the first state template at different working times and multiple groups of second template features of the second state template at different working times according to the optimal process state of different microcapsule particles. In the granulation process, the stability of the microcapsule particle formation process is ensured by adjusting multiple parameters in a coordinated manner. This method significantly improves the consistency of the product and provides a reliable technical solution for the large-scale production of high-performance microcapsules. Furthermore, in response to the errors in the curing stage, the template characteristics are adjusted to more accurately control the working parameters of the fluidization stage, ensure timely correction of the subsequent granulation process, and enable the process to have adaptive optimization capabilities. Embodiment 1

[0038] Reference Figures 5 to 9 The oil-in-water microcapsule spray drying granulation process of the present invention described in detail in this embodiment includes the following steps.

[0039] Step 1: Prepare a suspension material from an oily core material and an aqueous wall material, preset parameter templates, a first state template, and a second state template, convey a primary medium to the granulation chamber, and recover a secondary medium from the granulation chamber. The oily core material is a plant essential oil, in which thymol ≥ 13.5 wt% and cinnamaldehyde ≥ 6.5 wt%. The aqueous wall material is an aqueous solution of dextrin and starch. The mass ratio of the oily core material to the aqueous wall material in the suspension material is 1:4 to 1:6. The primary medium is a high-temperature gas medium (air or nitrogen) entering the granulation chamber, and the secondary medium is a gas medium discharged from the granulation chamber, which contains volatile gaseous water and a small amount of residual microcapsule particles.

[0040] Step 2: Control the working parameters of the primary medium until the granulation chamber reaches the preheating temperature, initialize the working duration t, and open the rotary wall. In this embodiment, the preheating temperature is 110 - 120 °C, and the preheating stage can be not included in the working duration t. In another embodiment, the curing duration T1 is increased, and the preheating stage is included in the working duration. The types of working parameters in different stages are different. For example, Figure 6 , the parameter template consists of the working parameters of the primary medium, secondary medium, suspension material, and rotary wall for multiple working durations. The working parameters of the primary medium include the medium flow rate and medium temperature, the working parameters of the suspension material include the material flow rate and atomization pressure, the working parameter of the secondary medium is the medium pressure, and the working parameter of the rotary wall is the rotation speed of the rotary wall. A preferred parameter template includes at least the working parameters of the curing stage and the fluidization stage, as shown in the following table (the unit of the working duration is min).

[0041]

[0042] Step 3: The atomizing nozzle sprays the suspension material into the granulation chamber, and controls the working parameters of the secondary medium, suspension material, and rotary wall according to the parameter template. By adjusting the medium pressure of the secondary medium, the gas discharge rate in the granulation chamber can be controlled, thereby affecting the drying uniformity and final humidity distribution of the microcapsule particles. By adjusting the material flow rate and atomization pressure of the suspension material, the particle size of the microcapsule particles can be changed. The rotary wall is a rotating structure in the granulation chamber. By optimizing the rotation speed of the rotary wall, the uniform dispersion of the microcapsule particles can be effectively promoted, thereby improving the uniformity of the particle size distribution. When the rotation speed is set too low, the particle adhesion phenomenon is aggravated, and the microcapsule particles are easily agglomerated, seriously affecting the uniformity of the particle size.

[0043] Step 4: Collect multiple groups of vertical cross-section images and cross-section images of the granulation chamber at the working duration t, respectively extract multiple groups of first template features and second template features of the first state template and the second state template at the working duration t, and calculate the first feature difference between the vertical cross-section image and the first template features, and the second feature difference between the cross-section image and the second template features. The first state template includes multiple groups of first template features of multiple observation orientations for multiple working durations, such as Figure 7, the second state template includes second template features of multiple sets of cross-section positions with multiple working durations. The first template feature is a standard vertical cross-section image, which is an ideal distribution state diagram of microcapsule particles with a standard particle size in the granulation chamber. The second template feature is a standard cross-section image, and the gray value of the pixel value in the standard cross-section image represents humidity. The standard cross-section image is an ideal distribution state diagram of the humidity of microcapsule particles in the granulation chamber.

[0044] Four sets of vertical cross-section images with different observation orientations are collected by a high-speed industrial camera. The vertical cross-section images are visible light images. For each set of vertical cross-section images, first, the particle contours of the microcapsule particles are extracted, the equivalent diameter of the particle contours is calculated, and then the particle size difference between the equivalent diameter and the standard vertical cross-section image of the corresponding observation orientation is calculated. Refer to Figure 8 , and finally, the average value of the four sets of particle size differences is taken as the first feature difference Δ1. Four sets of complex permittivity distribution maps are collected by a microwave antenna array, and four cross-section images at different cross-section positions are generated according to the microwave tomography method. The gray value differences between each set of cross-section images and the standard cross-section images of the corresponding cross-section positions are calculated respectively, and the average value of the four sets of gray value differences is taken as the second feature difference Δ2. The specific calculation method of the first feature difference Δ1 refers to Example 2, and the specific calculation method of the second feature difference Δ2 refers to Example 3.

[0045] Step 5: If the absolute value of the first feature difference is greater than D1 or the absolute value of the second feature difference is greater than D2, the working parameters of the primary medium, secondary medium, suspension material, and rotary wall are adjusted according to the first feature difference and the second feature difference. In this embodiment, the particle size of the microcapsule particles is, for example, 125 - 750 microns. As the working duration increases, the particle size of the microcapsule particles will gradually decrease as a whole. The value of D1 is determined according to the standard particle size E' in the standard vertical cross-section image in the first template feature, and D1 takes 5% - 8%E'. D2 is set according to the production process requirements. In this embodiment, a ±2% fluctuation in humidity is allowed during the production process. According to the influence of humidity on the permittivity in the microwave tomography method and the mapping relationship between the permittivity and the gray value, D2 is set to 10 - 30.

[0046] If the absolute value of the first characteristic difference is greater than D1 and the absolute value of the second characteristic difference is greater than D2, adjust the working parameters of the primary medium, secondary medium, suspension material, and rotary wall once. If the absolute value of the first characteristic difference is greater than D1 and the absolute value of the second characteristic difference is less than or equal to D2, adjust the working parameters of the suspension material and rotary wall. If the absolute value of the first characteristic difference is less than or equal to D1 and the absolute value of the second characteristic difference is greater than D2, adjust the working parameters of the primary medium and secondary medium. Calculate the adjustment amplitude δ1 according to Δ1 and D1, calculate the adjustment amplitude δ2 according to Δ2 and D2, and calculate the adjustment amount of each working parameter based on the adjustment amplitude δ1, adjustment amplitude δ2, particle size weight W1, and humidity weight W2. For the specific adjustment method, refer to Embodiment 5.

[0047] Step 6: If t is less than the curing duration T1, return to Step 3; otherwise, proceed to Step 7. In this embodiment, the curing duration T1 in the curing stage is, for example, 120 min.

[0048] Step 7: Close the atomizing nozzle, calculate the first cumulative difference and the second cumulative difference respectively based on multiple sets of the first characteristic difference and the second characteristic difference within the curing duration T1, and update multiple sets of the first template features and the second template features according to the first cumulative difference and the second cumulative difference. In this embodiment, cross-sectional images and vertical cross-sectional images are collected once per unit time (e.g., 1 minute). Refer to Figure 9 , the first cumulative difference , the second cumulative difference , where α1 is the mean of the first characteristic differences within the curing duration T1, α2 is the mean of the second characteristic differences within the curing duration T1, σ1 is the standard deviation of the first characteristic differences within the curing duration T1, σ2 is the standard deviation of the second characteristic differences within the curing duration T1, Δ1(t) is the first characteristic difference at the working duration t, and Δ2(t) is the second characteristic difference at the working duration t.

[0049] The first template feature S1(t) of the working duration t = S1(t) + λ1Δ3, and the second template feature S2(t) = S2(t) + λ2Δ4, where λ1 and λ2 are template adjustment parameters that reflect the sensitivity of the update. The update process of the first template feature is to update the standard particle size of the microcapsule particles in the standard vertical cross-sectional image, and the update process of the second template feature is to update the average gray value of the standard cross-sectional image. By updating the first template features and the second template features of multiple working durations, the first state template and the second state template are further updated. In this embodiment, λ1 ∈ [0.05, 0.3], and λ2 ∈ [0.1, 0.5]. The determination method of the template adjustment parameters λ1 and λ2 can adopt conventional algorithms (such as the gradient descent method or particle swarm optimization), which will not be elaborated in this embodiment.

[0050] Step 8: Repeat Steps 4 to 5 and adjust the operating parameters of the primary medium, secondary medium, and rotary wall once again. At this time, the atomization of the suspended material has stopped, and the microcapsule particles have entered the fluidized drying stage. There is no need to adjust the operating parameters of the suspended material. Instead, repeat Steps 4 to 5 and further adjust the operating parameters of the primary medium, secondary medium, and rotary wall according to the first state template and the second state template.

[0051] Step 9: If t - T1 is less than the fluidization duration T2, return to Step 8; otherwise, close the circulation channel and collect the microcapsule particles. The fluidization duration T2 is the time required for the microcapsule particles to complete fluidized drying in the granulation chamber. In this embodiment, the fluidization duration T2 in the fluidization stage is, for example, 30 min. After the fluidization ends, collect the microcapsule particles. Embodiment 2

[0052] This embodiment further discloses a preferred calculation method for the first characteristic difference.

[0053] Obtain the particle contour of the vertical cross-sectional image. The vertical cross-sectional image is a visible light image collected by a high-speed industrial camera from the observation window on the side wall of the granulation chamber. Four groups of vertical cross-sectional images are obtained each time of sampling. For each group of vertical cross-sectional images, first, identify the potential contour of the microcapsule particles in the vertical cross-sectional image based on the edge detection algorithm. For each pixel point p on the potential contour, take the pixel point p - n inside the potential contour and the pixel point p + n outside the potential contour along its normal vector, where n can be 3 - 5. Calculate the normal brightness gradient ▽I of the pixel point p p =(I p+n -I p-n ) / 2, where I p-n is the gray value of the pixel point p - n, and I p+n is the gray value of the pixel point p + n. Set the global maximum gradient ▽I max . If ▽I p >▽I max , it is considered that there is potential occlusion at this pixel point. If there are more than 3 consecutive pixel points on the potential contour with potential occlusion (i.e., the outside of the potential contour is brighter than the inside), it is considered that there is an occlusion boundary on the potential contour, and this potential contour is excluded. The finally retained potential contour is the particle contour.

[0054] Calculate the first characteristic difference. Calculate the equivalent diameter of each particle contour. The microcapsule particles in this embodiment belong to a highly viscoelastic system. During the drying process, the microcapsule particles are prone to slight deformation due to shrinkage but can maintain a continuous and complete contour, and the sphericity of the finally generated microcapsule particles is greater than 0.85. For such a situation, the equivalent diameter can be calculated, for example, by the equivalent area method. First, calculate the pixel area A inside the particle contour. According to the circular projection hypothesis, calculate the equivalent diameter . Combine the calibration scale to convert the equivalent diameter from pixel size to actual size and calculate the particle size difference , where M is the number of particle contours, and E m is the equivalent diameter of the m-th particle contour, and E' is the standard particle size of the standard vertical cross-sectional image in the first template feature. Finally, the average value of the four groups of particle size differences is used as the first feature difference Δ1. Example 3

[0055] This example further discloses a preferred calculation method for the second feature difference.

[0056] Generate a cross-sectional image. Install the microwave antenna array on the outer wall of the granulation chamber and keep a distance of 5 - 10 mm from the outer wall of the granulation chamber. Each group of microwave antenna arrays includes 8 - 16 antennas arranged at equal intervals. Generate a complex permittivity distribution map according to each group of microwave antenna arrays. The complex permittivity ε of each pixel grid in the complex permittivity distribution map is ε = ε' - jε'', where the real part ε' is the permittivity, ε'' is the loss factor, and j is the imaginary unit. Map the permittivity ε' to a cross-sectional image with 256 levels of gray through piecewise linear mapping. Example 4 further discloses a method for obtaining a cross-sectional image using microwave tomography.

[0057] Calculate the second feature difference. In this example, four groups of circular microwave antenna arrays are set on the outer wall of the granulation chamber, and four groups of cross-sectional images are generated for each working duration. For each group of cross-sectional images, calculate the average value μ1 of the gray values of the cross-sectional image and the average value μ2 of the gray values of the standard cross-sectional image, and find the gray value difference Δμ = μ1 - μ2. Take the average value of the gray value differences Δμ of the four groups of cross-sectional images as the second feature difference Δ2. Example 4

[0058] This example further discloses a preferred method for obtaining a cross-sectional image using microwave tomography.

[0059] Set the frequency of the microwave signal. Select the frequency of the microwave signal based on the radius of the granulation chamber. The larger the radius R of the corresponding cross-sectional position of the granulation chamber, the lower the required frequency f, and the frequency . Where c is the speed of light and ε'' is the loss factor, which represents the absorption characteristics of the microcapsule particles to the microwave signal. For example, if the radius of the granulation chamber is 0.25 - 1.5 meters, the corresponding frequency is 1 - 5 GHz.

[0060] Generate a complex permittivity distribution map. When the microwave antenna array is working, a single antenna emits microwave signals of a specific frequency, and the remaining antennas synchronously collect the scattered signals after being scattered by the microcapsule particles. Then, an iterative reconstruction algorithm is used to perform inverse calculation on the scattered signals: First, divide the cross-section of the granulation chamber into pixel grids, and assign an initial complex permittivity to each pixel grid (for example, set it as the complex permittivity of air). Then, solve the Maxwell's equations through the finite-difference time-domain method to simulate the propagation of microwave signals under the current complex permittivity distribution, calculate the theoretical scattered signals, and then construct an error function between the scattered signals and the theoretical scattered signals. Iteratively update the complex permittivity of each pixel grid by minimizing the error function, and finally generate a complex permittivity distribution map.

[0061] Generate a cross-sectional image according to the complex permittivity distribution map. The complex permittivity ε of each pixel grid is ε = ε' - jε'', where j is the imaginary unit, and the real part ε' is the permittivity. Map the permittivity ε' to a cross-sectional image with 256 levels of gray through piecewise linear mapping: When ε' < 2, the gray value G is set to 0 (pure black); when 20 > ε' ≥ 2, the gray value G = round(12.75×ε' - 25.5); when 80 > ε' ≥ 20, the gray value G = round(2.55×ε' + 178.5); when ε' ≥ 80, the gray value G is set to 255 (pure white). Finally, a cross-sectional image is generated. Since the permittivity of water is significantly higher than that of dry materials, that is, the permittivity ε' of water is about 80, and the permittivity ε' of dry materials is about 2, the change in the gray value of the pixel grid can reflect the humidity distribution of the microcapsule particles in the granulation chamber, and the gray value of each pixel grid is positively correlated with the permittivity ε'. Example Five

[0062] This example further discloses the method for adjusting the medium flow rate V1 and medium temperature T' of the primary medium, the material flow rate V2 and atomization pressure F1 of the suspended material, the medium pressure F2 of the secondary medium, and the rotation speed R' of the rotary wall according to the first characteristic difference Δ1 and the second characteristic difference Δ2 in step 5.

[0063] If the absolute value of the first characteristic difference is greater than D1 and the absolute value of the second characteristic difference is greater than D2, it indicates that the particle size distribution of the microcapsule particles in the granulation chamber is uneven, and the humidity of the microcapsule particles is quite different from the standard humidity. Calculate the adjustment amplitude δ1 = Δ1 / E' and the adjustment amplitude δ2 = Δ2 / 255, then the adjustment amount of the medium flow rate ΔV1 = (W1δ1 + W2δ2)V1, the adjustment amount of the medium temperature ΔT = (W1δ1 + W2δ2)T', the adjustment amount of the material flow rate ΔV2 = (W1δ1 + W2δ2)V2, the adjustment amount of the atomization pressure ΔF1 = (W1δ1 + W2δ2)F1, the adjustment amount of the medium pressure ΔF2 = (W1δ1 + W2δ2)F2, and the adjustment amount of the rotation speed ΔR = (W1δ1 + W2δ2)R'. Adjust the corresponding working parameters according to the adjustment amounts of each working parameter. In addition, set the particle size weight W1 and the humidity weight W2 according to the influence degree of each working parameter on the particle size and humidity, W1 + W2 = 1. The working parameters of the suspended material and the rotating wall have a greater influence on the particle size, and the working parameters of the primary medium and the secondary medium have a greater influence on the humidity. When adjusting the working parameters of the suspended material and the rotating wall, W1 > W2, for example, W1 is 0.7 and W2 is 0.3. When adjusting the working parameters of the primary medium and the secondary medium, W1 < W2, for example, W1 is 0.3 and W2 is 0.7.

[0064] If the absolute value of the first characteristic difference is greater than D1 and the absolute value of the second characteristic difference is less than or equal to D2, it indicates that the particle size is uneven. Adjust the working parameters of the suspended material and the rotating wall. Calculate the adjustment amplitude δ1 = Δ1 / E', then the adjustment amount of the material flow rate ΔV2 = δ1V2, the adjustment amount of the atomization pressure ΔF1 = δ1F1, and the adjustment amount of the rotation speed ΔR = δ1R'.

[0065] If the absolute value of the first characteristic difference is less than or equal to D1 and the absolute value of the second characteristic difference is greater than D2. It indicates that the humidity difference is large. Adjust the working parameters of the primary medium and the secondary medium. Calculate the adjustment amplitude δ2 = Δ2 / 255, then the adjustment amount of the medium flow rate ΔV1 = δ2V1, the adjustment amount of the medium temperature ΔT = δ2T', and the adjustment amount of the medium pressure ΔF2 = δ2F2.

[0066] The above are only the preferred embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. An oil-in-water microcapsule spray drying granulation process, characterized in that It includes the following steps: Step 1: Prepare a suspension material from an oily core material and an aqueous wall material, preset a parameter template, a first state template, and a second state template, convey a primary medium to the granulation chamber, and recover a secondary medium from the granulation chamber; Step 2: Control the working parameters of the primary medium until the granulation chamber reaches the preheating temperature, initialize the working duration t, and open the rotary wall; Step 3: The atomizing nozzle sprays the suspension material into the granulation chamber, and control the working parameters of the secondary medium, the suspension material, and the rotary wall according to the parameter template; Step 4: Collect multiple groups of vertical cross-section images and cross-section images of the granulation chamber at the working duration t, respectively extract multiple groups of first template features and second template features of the first state template and the second state template at the working duration t, calculate the first feature difference between the vertical cross-section image and the first template features, and the second feature difference between the cross-section image and the second template features; Step 5: If the absolute value of the first feature difference is greater than D1 or the absolute value of the second feature difference is greater than D2, adjust the working parameters of the primary medium, the secondary medium, the suspension material, and the rotary wall according to the first feature difference and the second feature difference; Step 6: If t is less than the curing duration T1, return to Step 3, otherwise enter Step 7; Step 7: Close the atomizing nozzle, calculate the first cumulative difference and the second cumulative difference respectively based on multiple groups of first feature differences and second feature differences within the curing duration T1, and update multiple groups of first template features and second template features respectively according to the first cumulative difference and the second cumulative difference; Step 8: Repeat Steps 4 to 5, and then adjust the working parameters of the primary medium, the secondary medium, and the rotary wall; Step 9: If t - T1 is less than the fluidization duration T2, return to Step 8, otherwise close the circulation channel and collect the microcapsule particles.

2. The oil-in-water based microcapsule spray drying granulation process according to claim 1, characterized in that, In Step 1, the oily core material is plant essential oil, in which thymol ≥ 13.5 wt% and cinnamaldehyde ≥ 6.5 wt%, the aqueous wall material is an aqueous solution of dextrin and starch, and the mass ratio of the oily core material to the aqueous wall material in the suspension material is 1:4 to 1:

6.

3. The oil-in-water-based microcapsule spray drying granulation process according to claim 1, characterized in that, In Step 2, the parameter template consists of the working parameters of the primary medium, the secondary medium, the suspension material, and the rotary wall at multiple working durations. The working parameters of the primary medium include the medium flow rate and the medium temperature. The working parameters of the suspension material include the material flow rate and the atomization pressure. The working parameter of the secondary medium is the medium pressure. The working parameter of the rotary wall is the rotation speed of the rotary wall.

4. The oil-in-water-based microcapsule spray drying granulation process according to claim 1, characterized in that, In Step 4, the first state template includes multiple groups of first template features in multiple observation orientations at multiple working durations, and the second state template includes multiple groups of second template features in multiple cross-section positions at multiple working durations. The first template features are standard vertical cross-section images, and the second template features are standard cross-section images.

5. The oil-in-water-based microcapsule spray drying granulation process according to claim 4, characterized in that, In Step 4, obtain multiple groups of vertical cross-section images. For each group of vertical cross-section images, first extract the particle contour of the microcapsule particles therein, calculate the equivalent diameter of the particle contour, then calculate the particle size difference between the equivalent diameter and the standard vertical cross-section image in the corresponding observation orientation, and take the average value of multiple groups of particle size differences as the first feature difference Δ1.

6. The oil-in-water-based microcapsule spray drying granulation process according to claim 5, characterized in that, In step 4, multiple groups of cross-sectional images are obtained, and the gray value differences between each group of cross-sectional images and the standard cross-sectional images at the corresponding cross-sectional positions are calculated respectively. The average value of the multiple groups of gray value differences is used as the second feature difference Δ2.

7. The oil-in-water-based microcapsule spray drying granulation process according to claim 1, characterized in that, In step 5, if the absolute value of the first feature difference is greater than D1 and the absolute value of the second feature difference is greater than D2, the working parameters of the primary medium, secondary medium, suspension material, and rotary wall are adjusted once. If the absolute value of the first feature difference is greater than D1 and the absolute value of the second feature difference is less than or equal to D2, the working parameters of the suspension material and rotary wall are adjusted. If the absolute value of the first feature difference is less than or equal to D1 and the absolute value of the second feature difference is greater than D2, the working parameters of the primary medium and secondary medium are adjusted.

8. The oil-in-water based microcapsule spray drying granulation process according to claim 6, characterized in that, In step 5, the adjustment amplitude δ1 is calculated according to Δ1 and D1, the adjustment amplitude δ2 is calculated according to Δ2 and D2, and the adjustment amounts of the respective working parameters are calculated based on the adjustment amplitude δ1, adjustment amplitude δ2, particle size weight W1, and humidity weight W2.

9. The oil-in-water-based microcapsule spray drying granulation process according to claim 1, characterized in that, In step 7, the first cumulative difference , the second cumulative difference , where α1 is the mean of the first feature difference within the curing duration T1, α2 is the mean of the second feature difference within the curing duration T1, σ1 is the standard deviation of the first feature difference within the curing duration T1, σ2 is the standard deviation of the second feature difference within the curing duration T1, Δ1(t) is the first feature difference at the working duration t, and Δ2(t) is the second feature difference at the working duration t.

10. The oil-in-water-based microcapsule spray drying granulation process according to claim 9, characterized in that, In step 7, the first template feature S1(t) of the working duration t is S1(t) = S1(t) + λ1Δ3, and the second template feature S2(t) is S2(t) = S2(t) + λ2Δ4, where λ1 and λ2 are template adjustment parameters.

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