A parameter optimization method, device and medium for a traditional Chinese medicine mask forming process

Abstract

The application discloses a traditional Chinese medicine mask forming process parameter optimization method and device and medium, and relates to the technical field of traditional Chinese medicine preparation continuous production, which comprises the following steps: collecting the stirring shaft torque value to calculate the apparent viscosity, detecting the particle size value, dynamically adjusting the rotating speed according to the particle size value to generate high-dispersion traditional Chinese medicine extract; starting the coating machine to spray based on the initial coating parameter set, capturing the quantum dot fluorescence signal in real time to generate a quantum dot fluorescence intensity distribution image; calculating the average penetration depth value and the liquid lateral diffusion uniformity value of the medicine liquid according to the quantum dot fluorescence intensity distribution image, and dynamically adjusting the coating parameters according to the average penetration depth value and the liquid lateral diffusion uniformity value of the medicine liquid to generate an optimized coating parameter set. The application realizes online closed-loop optimization of the film layer penetration-diffusion behavior, ensures the three-dimensional uniform distribution of the medicine liquid in the base cloth, and strengthens the precise control of the film layer function gradient and the consistency of the medicine efficacy release.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of continuous production of traditional Chinese medicine preparations, and in particular to a parameter optimization method, device and medium for traditional Chinese medicine mask forming process. BACKGROUND

[0002] In the industrial production of traditional Chinese medicine masks, the conventional process uses segmented parameter control: solid-liquid mixing is achieved by constant speed stirring in the traditional Chinese medicine extraction stage, and production is carried out based on preset speed and tension parameters in the coating stage. The industry generally relies on offline detection methods (such as high performance liquid chromatography) to randomly check active ingredients, and manually adjusts the coating parameters to ensure quality. The existing technology has realized basic automatic control, such as adjusting the stirring speed through a viscosity sensor, or monitoring the coating uniformity using image processing. Such methods have stability advantages in large-scale production and meet the requirements of GMP specifications, and are the mainstream application scheme in the industry.

[0003] However, the conventional method has limitations in process linkage and real-time control: first, the particle dispersion control in the extraction stage and the coating parameter setting are independent of each other, which leads to insufficient matching of the rheological properties of the liquid medicine and the coating equipment, affecting the uniformity of the film layer; second, quality monitoring relies on end sampling detection, and parameter adjustment lags behind the production process, making it difficult to realize online closed-loop optimization of penetration depth and diffusion uniformity. SUMMARY

[0004] In view of the above existing problems, the present application is proposed.

[0005] Therefore, the present application provides a parameter optimization method for traditional Chinese medicine mask forming process to solve the problems of parameter fragmentation and monitoring lag in the production of traditional Chinese medicine masks.

[0006] To solve the above technical problems, the present application provides the following technical solutions:

[0007] In a first aspect, the present application provides a parameter optimization method for traditional Chinese medicine mask forming process, which comprises: collecting the torque value of the stirring shaft to calculate the apparent viscosity, detecting the particle size value, dynamically adjusting the rotating speed according to the particle size value to generate a highly dispersed traditional Chinese medicine extract; delivering the highly dispersed traditional Chinese medicine extract to a coating batching tank, setting the initial coating parameters according to the apparent viscosity to obtain an initial coating parameter set; starting the coating machine to spray based on the initial coating parameter set, capturing the quantum dot fluorescence signal in real time to generate a quantum dot fluorescence intensity distribution image; calculating the average penetration depth value and the lateral diffusion uniformity value of the liquid medicine according to the quantum dot fluorescence intensity distribution image, dynamically adjusting the coating parameters according to the average penetration depth value and the lateral diffusion uniformity value of the liquid medicine to generate an optimized coating parameter set; starting the coating machine to spray again based on the optimized coating parameter set to generate an optimized wet mask substrate, and detecting the content of the hydroleucic acid and the diameter of the bacteriostatic circle of the wet mask substrate, and generating a process parameter optimization report in combination with the optimized coating parameter set.

[0008] As a preferred scheme of the parameter optimization method for traditional Chinese medicine mask forming process, the generation of the highly dispersed traditional Chinese medicine extract comprises the following steps:

[0009] The apparent viscosity of the extract is calculated by collecting the torque value of the stirring shaft in real time and combining the paddle geometric coefficient;

[0010] The apparent viscosity is compared with the viscosity control threshold to generate a viscosity overrun signal, and the temperature of the extract is adjusted according to the viscosity overrun signal;

[0011] The particle size value of the extract is detected and compared with the particle size control threshold to generate a particle size overrun signal, and the stirring rotating speed is adjusted according to the particle size overrun signal to generate the highly dispersed traditional Chinese medicine extract.

[0012] As a preferred scheme of the parameter optimization method for traditional Chinese medicine mask forming process, the generation of the highly dispersed traditional Chinese medicine extract comprises the following steps:

[0013] The highly dispersed traditional Chinese medicine extract is delivered to the coating batching tank, and biocompatible ZnAgInS quantum dots are added to generate quantum dot traditional Chinese medicine coating liquid;

[0014] The initial coating parameters set is generated by calculating the initial coating speed and the initial value of the base cloth tension according to the apparent viscosity.

[0015] As a preferred scheme of the parameter optimization method for traditional Chinese medicine mask forming process, the generation of the quantum dot fluorescence intensity distribution image comprises the following steps:

[0016] The coating machine is started to spray the quantum dot traditional Chinese medicine coating liquid based on the initial coating parameter set to generate a fluorescent wet mask substrate;

[0017] According to the fluorescent wet mask substrate, the quantum dot light signal is captured by a high-speed fluorescence camera, and a digital gray value conversion is performed to generate an original fluorescence image;

[0018] The original fluorescence image is subjected to real-time noise reduction and contrast enhancement processing, and the continuous frame fluorescence image data is integrated to generate a quantum dot fluorescence intensity distribution image.

[0019] As a preferred scheme of the parameter optimization method of the traditional Chinese medicine mask forming process, the average penetration depth value and the lateral diffusion uniformity value of the liquid medicine are calculated as follows,

[0020] Based on the quantum dot fluorescence intensity distribution image, the longitudinal fluorescence intensity front position coordinates are extracted, and the average penetration depth value of the liquid medicine is calculated;

[0021] The pixel gray value of the quantum dot fluorescence intensity distribution image is analyzed, and the lateral diffusion uniformity value of the liquid medicine is calculated by the image gray variation coefficient analysis method.

[0022] As a preferred scheme of the parameter optimization method of the traditional Chinese medicine mask forming process, the optimized coating parameter set is generated as follows,

[0023] The average penetration depth value of the liquid medicine is compared with the maximum allowed penetration depth threshold value to generate a penetration out-of-tolerance signal, and the coating speed is adjusted according to the penetration out-of-tolerance signal to obtain an optimized coating speed;

[0024] The lateral diffusion uniformity value of the liquid medicine is compared with the lateral diffusion uniformity threshold value to generate a diffusion unevenness signal, and the base cloth tension is adjusted according to the diffusion unevenness signal to obtain an optimized base cloth tension;

[0025] The optimized coating speed and the optimized base cloth tension are integrated to generate an optimized coating parameter set.

[0026] As a preferred scheme of the parameter optimization method of the traditional Chinese medicine mask forming process, the optimized wet mask substrate is generated by starting the coating machine to uniformly spray the quantum dot traditional Chinese medicine coating liquid according to the optimized coating parameter set, and the optimized wet mask substrate is generated.

[0027] As a preferred scheme of the parameter optimization method of the traditional Chinese medicine mask forming process, the process parameter optimization report is generated as follows,

[0028] A standardized film is cut from the optimized wet mask substrate, the HPLC method is used to detect the content of rutin acid, and the film is attached to an agar plate inoculated with bacteria to measure the diameter of the bacteriostatic circle, and a drug efficacy-ingredient correlation data set is obtained;

[0029] The optimized coating parameter set and the drug efficacy-ingredient correlation data set are integrated to generate a process parameter optimization report.

[0030] In a second aspect, the present application provides a computer device comprising a memory and a processor, wherein the memory stores a computer program, and wherein the computer program, when executed by the processor, implements any step of the parameter optimization method for traditional Chinese medicine mask forming process according to the first aspect of the present application.

[0031] In a third aspect, the present application provides a computer readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements any step of the parameter optimization method for traditional Chinese medicine mask forming process according to the first aspect of the present application.

[0032] The present application has the following beneficial effects: through the generation of high-dispersion traditional Chinese medicine extract, the rheological properties of the extract and the particle dispersion degree are synergistically controlled, the uniformity and stability of the extract are ensured, and the dispersion and coating adaptability of high-activity ingredients are improved; through dynamic adjustment of the coating parameters, online closed-loop optimization of the membrane layer penetration-diffusion behavior is realized, the three-dimensional uniform distribution of the extract in the base cloth is ensured, and the precise control of the functional gradient of the membrane layer and the consistency of the drug release are strengthened. BRIEF DESCRIPTION OF DRAWINGS

[0033] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following will briefly introduce the drawings needed to be used in the embodiment description. Obviously, the drawings in the following description are only some embodiments of the present application, and for those skilled in the art, other drawings can also be obtained without creative labor on the basis of these drawings.

[0034] Fig. 1 The flowchart of the parameter optimization method for traditional Chinese medicine mask forming process.

[0035] Fig. 2 The flowchart of the generation of high-dispersion traditional Chinese medicine extract.

[0036] Fig. 3 The flowchart of the fluorescence image contrast enhancement.

[0037] Fig. 4 The flowchart of the terminal detection and report generation. DETAILED DESCRIPTION

[0038] In order to make the above-mentioned purposes, features and advantages of the present application more obvious and easy to understand, the specific embodiments of the present application will be described in detail below with reference to the drawings of the specification.

[0039] In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present application. However, it will be apparent to one skilled in the art that the present application can be practiced without the specific details set forth in this description, that the present application can be practiced with other than the described implementations, and that the present application can be practiced with or in conjunction with other business applications, systems, and techniques.

[0040] Secondly, the "one embodiment" or "embodiment" referred to herein means a specific feature, structure, or characteristic that can be included in at least one implementation of the present application. The "in one embodiment" appearing in different places in the specification does not mean the same embodiment, nor is it an embodiment that is separate or alternative to other embodiments.

[0041] Reference Figs. 1-4 For one embodiment of the present application, the embodiment provides a parameter optimization method for traditional Chinese medicine mask forming process, comprising the following steps:

[0042] S1, collect the stirring shaft torque value to calculate the apparent viscosity, and detect the particle size value, dynamically adjust the rotating speed according to the particle size value, and generate high dispersion traditional Chinese medicine extract;

[0043] Real-time acquisition of stirring shaft torque value, combined with paddle geometric coefficient, calculation of apparent viscosity of extract;

[0044] Further, the strain torque sensor at the bottom of the stirring tank is used to collect the stirring shaft rotation resistance signal in real time: when the shaft is subjected to shear stress, the deformation of the metal strain gauge in the sensor causes the bridge to be unbalanced, and the original torque analog voltage value proportional to the torque is output; The original torque analog voltage value is converted into a digital torque value through high-precision analog-to-digital conversion; The real-time rotating speed is collected by using the servo motor encoder, and the digital torque value and the paddle geometric coefficient are combined to calculate the apparent viscosity of the extract through the rotational rheology formula;

[0045] The expression for calculating the apparent viscosity of the extract is: ;

[0046] Among them, is the apparent viscosity of the extract; is the stirring shaft torque value; is the paddle geometric coefficient; is the real-time rotating speed;

[0047] It should be noted that the paddle geometric coefficient is a dimensionless constant related to the shape / size of the paddle, which is determined in advance through fluid dynamics simulation combined with Newton fluid calibration experiment, and the exemplary value range is 0.012~0.025;

[0048] Compare the apparent viscosity with the viscosity control threshold to generate a viscosity overrun signal, and control the temperature of the extract according to the viscosity overrun signal;

[0049] Further, the apparent viscosity is compared with the viscosity control threshold value: when the apparent viscosity exceeds the viscosity control threshold value, a high-level viscosity overrun signal is generated; based on the high-level viscosity overrun signal, the solid-state relay is triggered to close, allowing the heater (3kW quartz tube) to be powered on to perform the temperature rising operation: the heater converts electrical energy into heat energy to heat the extract liquid through the stainless steel heat exchange plate; at the same time, the temperature of the extract liquid is monitored in real time by the wall-mounted PT100 temperature sensor, and when the temperature of the extract liquid is lower than the viscosity control target temperature threshold value, the driving circuit maintains the power-on state of the heater, and when the temperature of the extract liquid exceeds the viscosity control target temperature threshold value, the driving circuit disconnects the solid-state relay to stop heating, completing the dynamic control of the temperature of the extract liquid;

[0050] It should be noted that the viscosity control threshold value is a rheological safety boundary value set based on the particle dispersion stability experiment, and the exemplary value range is 1.2~1.8; the viscosity control target temperature threshold value is a thermal control optimization target value set by the thermogravimetric-rheological combined test, and the exemplary value range is 48~52℃;

[0051] The particle size value of the extract liquid is detected and compared with the particle size control threshold value to generate a particle size overrun signal, and at the same time, the stirring speed is adjusted according to the particle size overrun signal to generate a highly dispersed traditional Chinese medicine extract liquid;

[0052] Further, the particle size distribution of the particle group in the extract liquid is detected in real time by an online laser particle size analyzer, the particle size value is obtained, and the particle size value is compared with the particle size control threshold value in real time: when the particle size value exceeds the particle size control threshold value, a high-level particle size overrun signal is output; based on the high-level particle size overrun signal, the stirring motor is driven to increase the stirring speed from the reference value (determined by a torque-power consumption balance experiment, and the energy consumption optimal initial value is set based on the fluid flow pattern transition point) to the target value (the agglomeration breaking critical speed value is set based on the flow field CFD simulation and cavitation synergy experiment), and at the same time, the ultrasonic pulse generator is driven to trigger the pulse cavitation effect; finally, the particle size value is rechecked in real time, and when the continuously detected particle size value is within the dispersion standard threshold value, the particle size overrun signal is reset to a low level, the stirring speed returns to the reference value, and the ultrasonic is turned off, outputting a highly dispersed traditional Chinese medicine extract liquid;

[0053] It should be noted that the particle size control threshold value is a control trigger critical value set based on the particle dispersion stability experiment, and the exemplary value range is 15~25μm; the dispersion standard threshold value is a process acceptance standard value set by the online detection of the laser particle size analyzer and the skin penetration experiment, and the exemplary value range is 5~10μm; the pulse cavitation effect refers to the technology mechanism of periodically generating and collapsing micro-bubbles in the liquid by intermittently emitting high-frequency ultrasonic waves, and physically crushing the particle agglomerates by using the high-energy micro-jet and shock wave released in the bubble breaking instant.

[0054] S2, deliver the high-dispersion traditional Chinese medicine extract to a coating ingredient tank, and set coating initial parameters according to the apparent viscosity to obtain an initial coating parameter set;

[0055] Deliver the high-dispersion traditional Chinese medicine extract to the coating ingredient tank, and add biocompatible ZnAgInS quantum dots to generate quantum dot traditional Chinese medicine coating liquid;

[0056] Further, the high-dispersion traditional Chinese medicine extract is delivered to the coating ingredient tank through a sterile pipeline, and the liquid level in the coating ingredient tank is monitored in real time. The biocompatible ZnAgInS quantum dots are precisely added at a fixed ratio according to the liquid level in the coating ingredient tank, and a quantum dot feeding completion signal is output. Based on the quantum dot feeding completion signal, a magnetic stirrer is started to work, and the stirring torque value is monitored in real time. When the stirring torque value fluctuation is lower than a torque stability judgment threshold, a torque stability signal is output. Based on the torque stability signal, an online fluorescence spectrometer is activated to scan fixed detection points in the coating ingredient tank, collect fluorescence intensity original values of each point, and calculate the average fluorescence intensity and the fluorescence intensity standard deviation according to the fluorescence intensity original values of each point. The fluorescence intensity fluctuation rate is obtained according to the ratio relationship between the average fluorescence intensity and the fluorescence intensity standard deviation. If the fluorescence intensity fluctuation rate exceeds a quantum dot dispersion tolerance threshold, a high-speed homogenizer is triggered to run, and the quantum dot traditional Chinese medicine coating liquid is dispersed again until the retested fluorescence intensity fluctuation rate is within the quantum dot dispersion tolerance threshold, and the quantum dot traditional Chinese medicine coating liquid with uniform quantum dot distribution is output.

[0057] The expression for calculating the fluorescence intensity fluctuation rate is:

[0058] ;

[0059] Wherein, is the fluorescence intensity fluctuation rate; is the average fluorescence intensity; is the fluorescence intensity standard deviation;

[0060] It should be noted that the biocompatible ZnAgInS quantum dots are a four-element alloy fluorescent nanoprobes with a silica-silicon dioxide-chitosan composite layer on the surface, which are specially used for real-time tracking of the three-dimensional penetration behavior of traditional Chinese medicine coating liquid in the mask base cloth. The torque stability judgment threshold is a mixed uniformity judgment critical value set through fluid mixing dynamics experiments, and the exemplary value range is 3-8%. The quantum dot dispersion tolerance threshold is the maximum allowed deviation value of the uniformity of quantum dot distribution set through film formation monitoring error inversion experiments, and the exemplary value range is 2-5%.

[0061] The coating initial speed and the base cloth tension initial value are calculated according to the apparent viscosity to generate the initial coating parameter set;

[0062] Further, the apparent viscosity of the high-dispersion traditional Chinese medicine extract liquid is read in real time, and the coating initial speed is calculated according to the apparent viscosity through a rheological-coating speed conversion formula, and the base fabric tension initial value is calculated through a viscosity-tension compensation formula; the coating initial speed and the base fabric tension initial value are integrated as a structured data set to generate an initial coating parameter set;

[0063] The expression for calculating the coating initial speed and the base fabric tension initial value is:

[0064] ;

[0065] wherein, is the coating initial speed; is a rheological-speed conversion coefficient (indicating a viscosity-to-coating speed inhibition factor, which is set through a coating accumulation critical test, and an exemplary value range is 1.3-1.7);

[0066] ;

[0067] wherein, is the base fabric tension initial value; is a viscosity-tension gain coefficient (indicating a viscosity-to-tension mechanical enhancement factor, which is set based on a base fabric elastic modulus and a wrinkle elimination experiment, and an exemplary value range is 0.35-0.45).

[0068] S3, start the coating machine for spraying based on the initial coating parameter set, and capture quantum dot fluorescence signals in real time to generate a quantum dot fluorescence intensity distribution image;

[0069] Based on the initial coating parameter set, start the coating machine to spray the quantum dot traditional Chinese medicine coating liquid to generate a fluorescent wet film base material;

[0070] Further, the coating initial speed and the base fabric tension initial value in the initial coating parameter set are analyzed, the coating roller speed is set according to the rheological-coating speed conversion formula according to the coating initial speed, and the air cylinder pressure is obtained through the tension-pressure balance formula according to the base fabric tension initial value; the base fabric is stretched by the tension roller driven by the coating roller speed and the air cylinder pressure, the base fabric passes through the coating head at a constant speed under the base fabric tension initial value, and the ultrasonic atomizing nozzle is opened to spray the quantum dot traditional Chinese medicine coating liquid to form a uniformly wetted base fabric; the unit area mass of the uniformly wetted base fabric is monitored in real time through an online weighing sensor, if the unit area mass deviates from the coating weight gain target value, the coating initial speed is dynamically adjusted until the weight gain meets the standard, and a weight gain meets the standard signal is output; based on the weight gain meets the standard signal, the UV curing lamp irradiates the uniformly wetted base fabric to activate the quantum dot fluorescence characteristics, and a fluorescent wet film base material is output;

[0071] It should be noted that the target value of coating weight is based on the minimum effective dose of the active ingredient in the prescription and the unit area coating liquid mass set by the experimental saturation point of the base fabric. The exemplary value range is 3.0~4.0mg / cm²;

[0072] According to the fluorescent wet mask substrate, the quantum dot luminescence signal is captured by a high-speed fluorescence camera, and digital gray value conversion is performed to generate an original fluorescence image;

[0073] Further, the fluorescent wet mask substrate is placed on a high-speed transmission belt, and the transmission belt linear speed is accurately controlled by a servo motor to synchronize with the initial coating speed, triggering the high-speed fluorescence camera to start shooting. The high-speed fluorescence camera focuses on the quantum dot luminescence signal on the surface of the base fabric through an optical filter, and releases photoelectrons through the photoelectric multiplier cathode (cesium gallium material) under the bombardment of photons. At the same time, the output photon stream analog signal is amplified by the secondary multiplier and output. The photodiode in the photon stream analog signal generates an array of charge signals under the driving of the gate voltage, and a reference voltage is applied to the array of charge signals. The instantaneous voltage value is locked by the sample and hold circuit. The instantaneous voltage value is converted into a discrete digital value in a fixed interval by an analog-to-digital converter, and the discrete digital value is mapped to a gray scale interval. At the same time, the corresponding coordinate position is sequentially filled according to the physical pixel arrangement of the photoelectric sensor, and a digital gray value matrix is output. The Bayer filter algorithm is executed on the digital gray value matrix: the odd row and odd column pixel values of the digital gray value matrix are taken as the R channel, the even row and even column pixel values are taken as the B channel, and the average value of adjacent pixels is taken as the G channel. After bilinear interpolation to eliminate artifacts, an original fluorescence image is generated.

[0074] It should be noted that the RGGB array is the standard arrangement mode of the Bayer filter, which refers to the periodic arrangement of the color filter mode on the surface of the image sensor (such as CCD / CMOS) with a 2×2 pixel unit.

[0075] The original fluorescence image is processed in real time for noise reduction and contrast enhancement, and the continuous frame fluorescence image data is integrated to generate a quantum dot fluorescence intensity distribution image.

[0076] Further, the original fluorescence image is segmented into 8x8 pixel blocks, similar block groups are searched and 3D transformation is performed (combined with Haar wavelet and discrete cosine transform), and hard threshold shrinkage is performed on the transformation coefficients (significant signal components are retained), and after inverse transformation reconstruction, the fluorescence image after noise reduction is output; the fluorescence image after noise reduction is divided into 64x64 pixel blocks, the gray values of all pixels in each pixel block are extracted, a gray value set is formed, and the mean and standard deviation of the gray value set of each pixel block are calculated, and a local histogram of each block is generated; taking the mean gray value as the center point and the gray value standard deviation as the fluctuation range reference, the determination boundary of the abnormal pixel is dynamically generated, and the pixels outside the determination boundary are determined as abnormal pixels (over-bright / over-dark area), the gray values of the abnormal pixels are redistributed through histogram equalization to generate a contrast-enhanced fluorescence image; based on the contrast-enhanced fluorescence image, a plurality of consecutive frames of fluorescence data are continuously collected, and the displacement amount of each pixel in the X-Y direction is identified through the optical flow method, and after removing the abnormal points, the effective motion trajectory data is output; based on the effective motion trajectory data, the affine transformation parameters are directly solved by the least square method: the initial coordinates and the displacement coordinates of each pixel are associated, the residual sum of squares of the predicted displacement and the actual displacement is minimized, and after residual verification, the affine transformation matrix is output; based on the affine transformation matrix, inverse geometric transformation is performed on the original fluorescence image, and the pixel gray value is resampled to generate a displacement-compensated fluorescence image, and the displacement-compensated fluorescence image is assigned a decreasing weight in time sequence (the first frame has the highest weight), and a plurality of frames of fluorescence data are pixel-by-pixel weighted and averaged to generate a time-integrated fluorescence image; based on the time-integrated fluorescence image, the spatial coordinates and gray values of each pixel are extracted to construct a high-resolution matrix (row-column mapping base cloth physical position), and the gray values are linearly mapped to a standard intensity range, and finally a quantum dot fluorescence intensity distribution image is generated.

[0077] It should be noted that the transformation coefficient is a frequency component value obtained by decomposing the image block in the 3D transform domain (such as Haar wavelet + discrete cosine transform), which is set by the hard threshold shrinkage method, and the example value range is the entire real number domain (after normalization, concentrated in the interval of -1 to 1); the standard intensity range refers to the linear mapping of the pixel gray value of the original fluorescence image to the normalized interval, which is dynamically determined by scanning the minimum gray value and the maximum gray value of the full amplitude pixels of the quantum dot fluorescence intensity distribution image, and the example value range is 0~255.

[0078] S4, according to the quantum dot fluorescence intensity distribution image, calculating the average penetration depth value and the lateral diffusion uniformity value of the liquid medicine, and dynamically adjusting the coating parameters according to the average penetration depth value and the lateral diffusion uniformity value of the liquid medicine to generate an optimized coating parameter set;

[0079] Based on the quantum dot fluorescence intensity distribution image, the longitudinal fluorescence intensity front surface position coordinates are extracted, and the average penetration depth value of the liquid medicine is calculated.

[0080] Further, based on the quantum dot fluorescence intensity distribution image, the pixel points are scanned along the thickness direction (Y axis) of the base cloth, the fluorescence intensity profile data of each column is output, and the fluorescence intensity gradient value is obtained through the central difference method according to the intensity profile data of each column. At the same time, the position of the maximum value point of the gradient is identified according to the fluorescence intensity gradient value, and the longitudinal fluorescence intensity front position coordinate is generated. The longitudinal fluorescence intensity front position coordinate is subtracted from the preset base cloth surface reference coordinate to identify the single column penetration depth, and the arithmetic mean value of all single column penetration depths is taken to output the average penetration depth value of the liquid medicine.

[0081] The expression for calculating the average penetration depth value of the liquid medicine is:

[0082] ;

[0083] Among them, is the average penetration depth value of the liquid medicine; is the physical size of the pixel; is the column index number in the width direction of the base cloth; is the total number of effective columns participating in statistics; is the weight factor (directly generated by the position determination rule, and the example value range is 0~1), which represents the weight of suppressing edge error; is the front surface pixel coordinate, which represents the Y axis position of the liquid medicine penetration front of the column; is the base cloth reference coordinate, which represents the Y axis reference position of the base cloth surface of the column;

[0084] It should be noted that the base cloth surface reference coordinate is generated by pre-scanning the dry base cloth sample, detecting the Y axis position of the fluorescence intensity drop point of the dry base cloth sample, and linearly adjusting the coordinate values of each column according to the base cloth inclination;

[0085] The pixel gray value of the quantum dot fluorescence intensity distribution image in the horizontal direction is analyzed, and the liquid medicine horizontal diffusion uniformity value is calculated by the image gray variation coefficient analysis method.

[0086] Further, based on the quantum dot fluorescence intensity distribution image, the rows are scanned along the width direction (X axis) of the base cloth, the gray values of all pixels in each row are extracted, and the arithmetic mean value of the gray values of all pixels in each row is taken to generate the row average gray value. Based on the gray values of all pixels in each row and the row average gray value, the standard deviation is calculated to generate the row gray standard deviation, and the row gray variation coefficient is obtained according to the ratio relationship between the row average gray value and the row gray standard deviation. Finally, the arithmetic mean value of the row gray variation coefficients of all rows is taken to obtain the liquid medicine horizontal diffusion uniformity value.

[0087] The expression for calculating the liquid medicine horizontal diffusion uniformity value is:

[0088] ;

[0089] wherein, is the liquid transverse diffusion uniformity value; is the single row gray standard deviation, indicating the volatility of the gray value of all pixels in the row; is the single row average gray value, indicating the arithmetic mean of the gray value of all pixels in the row;

[0090] The average penetration depth value of the liquid is compared with the maximum allowed penetration depth threshold value, a penetration out-of-tolerance signal is generated, and the coating speed is adjusted according to the penetration out-of-tolerance signal to obtain an optimized coating speed;

[0091] Further, the average penetration depth value of the liquid is compared with the maximum allowed penetration depth threshold value: if the average penetration depth value of the liquid exceeds the maximum allowed penetration depth threshold value, a high-level penetration out-of-tolerance signal is generated, and if the average penetration depth value of the liquid is lower than the maximum allowed penetration depth threshold value, a low-level signal is maintained; based on the penetration out-of-tolerance signal, a coating speed instruction is triggered: the coating speed is reduced when the level is high, and the original speed is maintained when the level is low; the coating speed instruction is converted into a pulse width modulation (PWM) signal to drive the servo motor, the coating roller speed is adjusted according to the speed conversion formula to obtain a new coating roller speed; finally, the coating machine runs at the new coating roller speed, and the average penetration depth value of the liquid is retested, when the retested average penetration depth value of the liquid is lower than the maximum allowed penetration depth threshold value, the penetration out-of-tolerance signal is reset to a low-level signal, and finally the optimized coating speed is obtained;

[0092] It should be noted that the maximum allowed penetration depth threshold value is a substrate thickness ratio value determined by the capillary adsorption force and gravity balance experiment, and the exemplary value range is 0.3~0.35;

[0093] The liquid transverse diffusion uniformity value is compared with the transverse diffusion uniformity threshold value, a diffusion unevenness signal is generated, and the substrate tension is adjusted according to the diffusion unevenness signal to obtain an optimized substrate tension;

[0094] Further, the liquid medicine transverse diffusion uniformity value is compared with the transverse diffusion uniformity threshold value, if the liquid medicine transverse diffusion uniformity value exceeds the transverse diffusion uniformity threshold value, a high-level diffusion uneven signal is generated, if the liquid medicine transverse diffusion uniformity value is lower than the transverse diffusion uniformity threshold value, a low-level signal is maintained; based on the diffusion uneven signal, a base cloth tension adjustment instruction is triggered: when high, the tension is increased (for example, +0.1MPa, which is set based on a large number of wrinkle elimination experiments), and when low, the original base cloth tension is maintained; then the base cloth tension adjustment instruction is converted into a gas pressure control signal according to a linear conversion formula, and the gas pressure cylinder outputs a pressure increment according to the gas pressure control signal; the gas pressure cylinder receives the pressure increment, pushes the piston to generate a pushing force, converts the linear pushing force into an angular displacement of the tension roller through the connecting rod mechanism, and the angular displacement of the tension roller increases the base cloth tension; at the same time, the liquid medicine transverse diffusion uniformity value is re-measured, if the re-measured liquid medicine transverse diffusion uniformity value is lower than the transverse diffusion uniformity threshold value, the diffusion uneven signal is reset to a low-level signal, and finally the optimized base cloth tension is obtained;

[0095] It should be noted that the transverse diffusion uniformity threshold value is a reference value determined through a large number of coating experiments, and is dynamically adjusted based on the base cloth material characteristics (non-woven fabric / silk), and the value range is 4.5%~5.5%;

[0096] The optimized coating speed and the optimized base cloth tension are integrated to generate an optimized coating parameter set;

[0097] Further, the real-time updated optimized coating speed is read and verified according to the process safety speed range threshold value, if the optimized coating speed exceeds the process safety speed range threshold value, it is forcibly limited to the boundary value (set through the balance experiment of coating liquid surface tension and base cloth capillary adsorption force), and the effective coating speed passing the verification is output; the real-time updated optimized base cloth tension is read synchronously and verified according to the base cloth breaking safety threshold value, if it exceeds the base cloth breaking safety threshold value, it is forcibly limited to the upper limit value (set through the liquid splashing critical experiment), and the effective base cloth tension passing the verification is output; the effective coating speed and the effective base cloth tension are integrated and packaged to generate an optimized coating parameter set;

[0098] It should be noted that the process safety speed range threshold value is a coating speed safety boundary value set through a large number of coating experiments to verify the balance of coating coverage and splash prevention, and the value range is 0.5~2.0m / min; the base cloth breaking safety threshold value is a tension safety boundary value set according to the base cloth material yield strength experiment, and the value range is 0.4~0.48MPa.

[0099] S5, based on the optimized coating parameter set, the coating machine is started again to spray, an optimized wet film base material is generated, and the optimized wet film base material is detected for road road acid content and bacteriostatic circle diameter, and a process parameter optimization report is generated combining the optimized coating parameter set;

[0100] According to the optimized coating parameter set, the coating machine is started to re-uniformly spray the quantum dot Chinese medicine coating liquid to generate an optimized wet film base material;

[0101] Further, the optimized coating speed in the optimized coating parameter set is analyzed, and a rheological-coating speed conversion formula is used to drive a servo motor to set the coating roller speed, and the optimized base cloth tension is analyzed synchronously, a pressing force conversion formula is used to control the air cylinder, and the air cylinder pressure is output. According to the coating roller speed and the air cylinder pressure, the tension roller is driven to stretch the base cloth to the optimized base cloth tension, the base cloth passes through the coating head at the optimized coating speed under the optimized base cloth tension, and the ultrasonic atomizing nozzle is turned on to atomize the quantum dot Chinese medicine coating liquid into droplets and uniformly spray the droplets to the coating surface. The on-line weighing sensor is used to monitor the unit area mass of the coating in real time, if the unit area mass deviates from the coating weight gain target value, the nozzle flow is dynamically adjusted until the weight gain meets the standard, at this time, the base cloth surface forms a continuous wet film layer, and a weight gain meets the standard signal is output. According to the weight gain meets the standard signal, the UV curing lamp is triggered to irradiate the coating to activate the quantum dot fluorescence characteristics, and a wet film base material with stable fluorescent markers is generated. Finally, the thickness of the wet film layer of the wet film base material is scanned by the laser thickness gauge, if the fluctuation of the wet film layer thickness exceeds the wet film thickness tolerance threshold, the coating parameters are recalculated, if the fluctuation of the wet film layer thickness is lower than the wet film thickness tolerance threshold, the qualified optimized wet film base material is output.

[0102] It should be noted that the wet film thickness tolerance threshold is set through the film layer cracking and drug release double critical experiment verification, and the exemplary value range is ±5%;

[0103] The standardized film piece is cut from the optimized wet film base material, the HPLC method is used to detect the content of the linalool acid, and the film piece is pasted to the agar plate inoculated with the bacteria to measure the diameter of the bacteriostatic circle, and the efficacy-component correlation data set is obtained.

[0104] Further, two standardized film pieces are cut from the optimized wet mask substrate, and detection sample A and detection sample B with output coordinate positioning are output, and detection sample A is dehydrated by a freeze dryer and then ground into powder, and dry and uniform powder to be tested is output; the powder to be tested is precisely weighed and added to a methanol solution, ultrasonic extraction is performed, and the supernatant is obtained by centrifugation, and the gentisic acid test solution is output; the gentisic acid test solution is filtered by an organic phase filter membrane and injected into a high-performance liquid chromatograph for elution, the chromatographic peak of the retention time is captured at a specific wavelength, and the peak area is obtained by an external standard method, and compared with a standard curve to obtain the content of gentisic acid; detection sample B is synchronously taken and applied to an agar plate culture inoculated with Staphylococcus epidermidis and Propionibacterium acnes, and a plate with an inhibition zone is output; the diameter of the inhibition zone in the plate with the inhibition zone is measured by a vernier caliper, and the average diameters of the inhibition zones of Staphylococcus epidermidis and Propionibacterium acnes are identified respectively; the content of gentisic acid and the average diameter of the inhibition zone of all samples are integrated to construct a two-dimensional data pair, and a pharmacodynamic-ingredient correlation data set is finally output;

[0105] It should be noted that the standard curve refers to a linear calibration curve drawn by detecting a gradient concentration of a gentisic acid standard solution by a high-performance liquid chromatograph, with concentration as the abscissa and chromatographic peak area as the ordinate, for converting the peak area of the sample to be tested into the content of gentisic acid;

[0106] The optimized coating parameter set and the pharmacodynamic-ingredient correlation data set are integrated to generate a process parameter optimization report.

[0107] Further, the optimized coating speed and the optimized substrate tension in the optimized coating parameter set are extracted, the thickness data of the wet mask substrate are obtained by real-time scanning by a laser thickness gauge, and the thickness fluctuation rate is identified according to the thickness data; the thickness fluctuation rate is compared with the wet film thickness tolerance threshold value, if the thickness fluctuation rate is lower than the wet film thickness tolerance threshold value, it is determined that the process performance meets the standard, if the thickness fluctuation rate exceeds the wet film thickness tolerance threshold value, it is determined that the process performance does not meet the standard, and a process performance evaluation result is output; the content of gentisic acid and the average diameter of the inhibition zone in the pharmacodynamic-ingredient correlation data set are synchronously extracted, and a double-threshold determination rule is executed: if the content of gentisic acid is greater than the gentisic acid content threshold value, and the average diameter of the inhibition zone is greater than the inhibition zone diameter threshold value, it is determined that the pharmacodynamic performance meets the standard; if the content of gentisic acid is less than the gentisic acid content threshold value, and the average diameter of the inhibition zone is less than the inhibition zone diameter threshold value, or the content of gentisic acid is less than the gentisic acid content threshold value, but the average diameter of the inhibition zone is greater than the inhibition zone diameter threshold value, and the content of gentisic acid is greater than the gentisic acid content threshold value, but the average diameter of the inhibition zone is less than the inhibition zone diameter threshold value, it is determined that the pharmacodynamic performance does not meet the standard, and a pharmacodynamic performance evaluation result is output; the process performance evaluation result and the pharmacodynamic performance evaluation result are integrated to generate a process parameter optimization report;

[0108] It should be noted that the double-threshold decision rule is a cooperative decision rule for verifying the efficacy compliance state, which is set based on the active ingredient minimum effective dose experiment and the strain inhibition experiment data, including the guaiacol content threshold and the inhibition zone diameter threshold;

[0109] It should be noted that the guaiacol content threshold is set according to the active ingredient minimum effective dose in the in vitro transdermal release experiment, and the exemplary value range is 1.15-1.25 mg / g; the inhibition zone diameter threshold is set according to the bacteriostatic critical experiment of inoculating Staphylococcus epidermidis and Propionibacterium acnes by agar diffusion method, and the exemplary value range is 15.5-16.5 mm.

[0110] The embodiment also provides a computer device suitable for the parameter optimization method of the traditional Chinese medicine mask forming process, which comprises a memory and a processor; the memory is used to store computer executable instructions, and the processor is used to execute the computer executable instructions to realize the parameter optimization method of the traditional Chinese medicine mask forming process proposed in the above embodiment.

[0111] The computer device can be a terminal, which comprises a processor, a memory, a communication interface, a display screen and an input device connected through a system bus. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device comprises a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operating system and the computer program in the non-volatile storage medium. The communication interface of the computer device is used to communicate with external terminals in a wired or wireless manner. The wireless manner can be realized through WIFI, operator network, NFC (near field communication) or other technologies. The display screen of the computer device can be a liquid crystal display screen or an electronic ink display screen. The input device of the computer device can be a touch layer overlaid on the display screen, or a key, trackball or touchpad arranged on the shell of the computer device, or an external keyboard, touchpad or mouse, etc.

[0112] The embodiment also provides a storage medium on which a computer program is stored, the program being executed by a processor to implement the parameter optimization method for realizing the traditional Chinese medicine mask forming process proposed in the above embodiment; the storage medium can be realized by any type of volatile or non-volatile storage device or a combination thereof, such as a static random access memory (SRAM), an electrically erasable programmable read-only memory (EEPROM), an erasable programmable read-only memory (EPROM), a programmable read-only memory (PROM), a read-only memory (ROM), a magnetic memory, a flash memory, a magnetic disk, or an optical disk.

[0113] To sum up, the present application realizes the synergistic regulation of the rheological properties of the medicinal liquid and the particle dispersion degree by generating a highly dispersed traditional Chinese medicine extract, guarantees the uniformity and stability of the extract, and improves the adaptability of the dispersion and coating of the high-activity ingredients; by dynamically adjusting the coating parameters, the present application realizes the online closed-loop optimization of the permeation-diffusion behavior of the film layer, ensures the three-dimensional uniform distribution of the medicinal liquid in the base cloth, and strengthens the precise control of the functional gradient of the film layer and the consistency of the drug release.

[0114] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present application but not limit the present application, and although the present application has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present application can be modified or replaced equivalently without departing from the spirit and scope of the technical solutions of the present application, and all of them should be covered in the scope of the claims of the present application.

Claims

1. A method for optimizing parameters in the forming process of a traditional Chinese medicine facial mask, characterized in that: Comprising, Collect the stirring shaft torque value to calculate the apparent viscosity, detect the particle size value, dynamically adjust the rotating speed according to the particle size value, and generate a highly dispersed traditional Chinese medicine extract; Transport the highly dispersed traditional Chinese medicine extract to the coating ingredient tank, set the initial coating parameters according to the apparent viscosity, and obtain an initial coating parameter set; Start the coating machine to spray based on the initial coating parameter set, capture the quantum dot fluorescence signal in real time, and generate a quantum dot fluorescence intensity distribution image; Calculate the average penetration depth value and the liquid lateral diffusion uniformity value of the medicine liquid according to the quantum dot fluorescence intensity distribution image, dynamically adjust the coating parameters according to the average penetration depth value and the liquid lateral diffusion uniformity value of the medicine liquid, and generate an optimized coating parameter set; Start the coating machine to spray again based on the optimized coating parameter set, generate an optimized wet film base material, and detect the content of the road acid and the diameter of the bacteriostatic circle of the optimized wet film base material, and generate a process parameter optimization report combining the optimized coating parameter set.

2. The method of claim 1, wherein the parameters of the Chinese medicine mask forming process are optimized. The highly dispersed traditional Chinese medicine extract is generated by the following steps, Collect the stirring shaft torque value in real time, calculate the apparent viscosity of the extract in combination with the paddle geometric coefficient, compare the apparent viscosity with the viscosity control threshold value, generate a viscosity overrun signal, and control the temperature of the extract according to the viscosity overrun signal; Detect the particle size value of the extract, compare it with the particle size control threshold value, generate a particle size overrun signal, and adjust the stirring speed according to the particle size overrun signal to generate a highly dispersed traditional Chinese medicine extract. The initial coating parameter set is obtained by the following steps, 3. The method of claim 1, wherein the parameters of the Chinese medicine mask forming process are optimized. Transport the highly dispersed traditional Chinese medicine extract to the coating ingredient tank, add biocompatible ZnAgInS quantum dots to generate quantum dot traditional Chinese medicine coating liquid, and calculate the initial coating speed and the initial value of the base fabric tension according to the apparent viscosity to generate the initial coating parameter set. The quantum dot fluorescence intensity distribution image is generated by the following steps, Start the coating machine to spray the quantum dot traditional Chinese medicine coating liquid based on the initial coating parameter set to generate a fluorescent wet film base material, capture the quantum dot luminescence signal through a high-speed fluorescence camera according to the fluorescent wet film base material, perform digital gray value conversion to generate an original fluorescence image, perform real-time noise reduction and contrast enhancement processing on the original fluorescence image, and integrate continuous frame fluorescence image data to generate a quantum dot fluorescence intensity distribution image.

4. The method of claim 1, wherein the parameters of the Chinese medicine mask forming process are optimized. The average penetration depth value and the liquid lateral diffusion uniformity value of the medicine liquid are calculated by the following steps, Extract the longitudinal fluorescence intensity front position coordinates from the quantum dot fluorescence intensity distribution image to calculate the average penetration depth value of the medicine liquid, analyze the pixel gray value in the transverse direction of the quantum dot fluorescence intensity distribution image, and calculate the liquid lateral diffusion uniformity value through an image gray scale variation coefficient analysis method. The optimized coating parameter set is generated by the following steps, Compare the average penetration depth value of the medicine liquid with the maximum allowed penetration depth threshold value to generate a penetration out-of-tolerance signal, adjust the coating speed according to the penetration out-of-tolerance signal, and obtain an optimized coating speed, compare the liquid lateral diffusion uniformity value with the lateral diffusion uniformity threshold value to generate a diffusion unevenness signal, adjust the base fabric tension according to the diffusion unevenness signal, and obtain an optimized base fabric tension, and integrate the optimized coating speed and the optimized base fabric tension to generate the optimized coating parameter set.

5. The method of claim 1, wherein the parameters of the Chinese medicine mask forming process are optimized. ​ ​ ​ 6. The method of claim 1, wherein the parameters of the Chinese medicine mask forming process are optimized. ​ ​ ​ ​ 7. The method of claim 1, wherein the parameters of the Chinese medicine mask forming process are optimized. The generating the optimized wet mask substrate refers to starting the coating machine to re-uniformly spray the quantum dot traditional Chinese medicine coating liquid according to the optimized coating parameter set, and generating the optimized wet mask substrate. 8.The method of claim 1, wherein the parameters of the process are optimized by using a computer program. The generating the process parameter optimization report has the following steps, A standardized film piece is cut from the optimized wet mask substrate, the content of linalool is detected by using an HPLC method, meanwhile, the film piece is pasted to an agar plate inoculated with bacteria, the diameter of the bacteriostatic circle is measured, and a pharmacodynamic-ingredient correlation data set is obtained; The optimized coating parameter set and the pharmacodynamic-ingredient correlation data set are integrated to generate the process parameter optimization report. 9.A computer device, comprising a memory and a processor, wherein the memory stores a computer program, and the computer device is characterized in that: The processor executes the computer program to realize the steps of the parameter optimization method of the traditional Chinese medicine mask forming process according to any one of claims 1-8.

10. A computer readable storage medium having stored thereon a computer program, characterized in that: The computer program is executed by the processor to realize the steps of the parameter optimization method of the traditional Chinese medicine mask forming process according to any one of claims 1-8.

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