A production and processing control method for traditional Chinese medicine material slicing and drying process

Abstract

The application provides a production and processing control method for traditional Chinese medicine material slicing and drying process, and relates to the technical field of production control. The method comprises the following steps: obtaining a slicing thickness distribution sequence and dividing the thickness into sections, counting the moisture permeation resistance coefficients of each thickness section, and generating a correlation mapping table of thickness and moisture migration characteristics; calculating the heat accumulation value required to reach the target moisture content according to the resistance coefficients of each thickness section, and constructing a drying energy demand spectrum for thickness difference compensation; dynamically adjusting the segmented temperature curve and the duration of each section of the drying equipment according to the energy demand spectrum difference, so that the moisture migration rates of slices with different thicknesses tend to be consistent; real-time monitoring of the temperature gradient between the surface and the center of the slice, feedback correction of the temperature curve step amplitude when the gradient deviates from the preset synchronization interval, and output of the self-adaptive drying process parameters. The application improves the drying uniformity and the consistency of the final moisture content, prevents the loss of medicinal effect or local carbonization caused by uneven thickness, and improves the quality stability.

Description

Technical Field

[0001] This invention relates to the field of production control technology, and more specifically, to a production processing control method for the slicing and drying process of Chinese medicinal materials. Background Technology

[0002] With the rapid development of the modern Chinese medicine industry and the continuous improvement of the preparation process of Chinese medicinal materials, slicing and drying, as key links in the processing of Chinese medicinal materials, play a decisive role in the preservation of the overall medicinal components and the stability of product quality. Traditional processing of Chinese medicinal materials usually relies on experience-based operations. For example, the slicing stage is mostly completed manually or by simple machinery, lacking precise control over the uniformity of the product thickness, which in turn affects the efficiency of heat and moisture transfer during the subsequent drying process. In recent years, automated slicing equipment and energy-saving drying equipment have been developed, and some factories have tried to introduce intelligent control systems based on temperature and humidity sensors to improve the uniformity of slicing and drying quality. However, most existing technologies focus on the control of macroscopic operating parameters (such as overall temperature, humidity, and drying cycle), but have not yet deeply considered the essential impact of microscopic differences in slice thickness on the moisture migration dynamics and heat demand within the material. This results in problems such as uneven drying, local carbonization of medicinal materials, or excessively high moisture content still existing during the processing.

[0003] Specifically, existing technologies for controlling the slicing and drying processes of Chinese medicinal herbs often rely on homogeneity assumptions, neglecting the fundamental differences in key physical parameters such as water penetration resistance, heat accumulation, and migration rate among slices of different thicknesses. This approach easily leads to critical issues in practical applications, such as thick slices not being thoroughly dried and thin slices losing excessive moisture, thus affecting the medicinal properties of the finished product. Some improvement methods optimize drying effects by setting multi-stage temperature control strategies or adding auxiliary air circulation, but without dynamic monitoring of thickness distribution and data-driven regulation, these methods often only achieve limited improvements. Especially considering the complex internal structure and active ingredient retention requirements of Chinese medicinal herbs, simply increasing the temperature can cause degradation of effective components, while insufficient temperature cannot guarantee complete dehydration, making it difficult to achieve a scientific balance between processing efficiency and herb quality. Therefore, how to intelligently and finely regulate the drying energy distribution and heat accumulation process based on the dynamic characteristics of the thickness distribution of Chinese medicinal herb slices is a pressing technical challenge for the industry. Summary of the Invention

[0004] To address the aforementioned technical problems, this invention provides a production and processing control method for the slicing and drying of Chinese medicinal materials. This method can, to some extent, solve the problems caused by the lack of precise understanding of the moisture migration characteristics under thickness distribution and thickness differences in Chinese medicinal material slices. Existing drying processes are unable to dynamically allocate energy and adaptively adjust parameters in real time for slices of different thicknesses, resulting in uneven drying of slices of different thicknesses, large fluctuations in moisture content, and unsatisfactory preservation of medicinal components.

[0005] According to one aspect of the present invention, a production and processing control method for slicing and drying Chinese medicinal materials is provided, comprising:

[0006] Obtain the slice thickness distribution sequence at the slicer outlet, divide the slice sequence into multiple thickness segments according to the thickness gradient, calculate the water permeation resistance coefficient of the slices in each thickness segment, and generate a correlation mapping table between thickness and water migration characteristics.

[0007] Based on the moisture penetration resistance coefficient of each thickness segment in the aforementioned correlation mapping table, the cumulative heat required for slices of different thicknesses to reach the target moisture content is calculated, and a drying energy demand spectrum with thickness difference compensation is constructed.

[0008] Based on the differences in heat accumulation values ​​of each thickness segment in the drying energy demand spectrum, the segmented temperature curves of the drying equipment and the duration of each temperature segment are dynamically adjusted to make the moisture migration rate of slices of different thicknesses tend to be consistent.

[0009] The surface temperature and center temperature gradient of slices of different thicknesses in the drying chamber are monitored in real time. When the center temperature gradient deviates from the preset synchronization range, the step amplitude of the segmented temperature curve is corrected by feedback, and the drying process parameters are output for adaptive control.

[0010] Furthermore, the calculation of the water permeability resistance coefficient includes:

[0011] A radial distribution model of the water concentration field inside the slice is established, and the governing equation of the radial distribution model is expressed as:

[0012]

[0013] in, This represents the water concentration inside the slice. Drying time, The coordinates are in the thickness direction, with the center of the slice thickness as the origin. The local moisture diffusion coefficient varies with thickness, location, and time.

[0014] The local moisture diffusion coefficient Using a function that varies with thickness, location, and time, the formula is expressed as:

[0015]

[0016] in, The effective diffusion coefficient of the core layer, The effective diffusion coefficient of the surface layer. As the core-edge transition point, For the thickness of the transition layer, To maintain the long-term diffusion coefficient ratio, The characteristic time of structural relaxation;

[0017] The governing equations are solved numerically to calculate the water migration time constant required for the average moisture content of each thickness section to decrease from the initial value to the target moisture content.

[0018] The water permeability resistance coefficient is defined as the ratio of the square of the thickness representative value to the equivalent water diffusion coefficient.

[0019] Furthermore, the calculation of the accumulated heat value includes:

[0020] Establish the energy conservation equation:

[0021]

[0022] in, This refers to the slicing temperature; The convective heat transfer coefficient is... The surface area of ​​the slice participating in convective heat transfer. The temperature of the hot air used for drying the medium; The latent heat of vaporization of water, This represents the rate of water evaporation.

[0023] Record the instantaneous heating intensity requirement at each time step:

[0024]

[0025] The instantaneous heat supply intensity demand is numerically integrated over the entire time interval from the start of drying to reaching the target moisture content to obtain the total heat demand of each thickness segment, i.e., the cumulative heat value.

[0026] Furthermore, the construction of the drying energy demand spectrum includes:

[0027] The time axis of the drying process is divided into multiple continuous time windows, and the average heat intensity requirement of each thickness section within the window is calculated for each time window.

[0028] Introducing a moisture content deviation correction factor The moisture content deviation correction factor is close to 1 in the early stage of drying, gradually decreases as the drying process progresses, and becomes zero when the slices reach the target moisture content; wherein, The average moisture content, For the target moisture content, This represents the initial moisture content.

[0029] Calculate the overall heating weight and normalize it to obtain the heating intensity allocation ratio;

[0030] By combining the total heating power of each time window with the heating intensity distribution ratio of each thickness section, a drying energy demand spectrum is generated with the time window as the horizontal axis and the heating power demand of each thickness section as the vertical axis.

[0031] Furthermore, the calculation formulas for the effective diffusion coefficient of the core layer and the effective diffusion coefficient of the surface layer are as follows:

[0032]

[0033]

[0034] in, The baseline moisture diffusion coefficient, Fiber density is a structural parameter in tissue organization. The fiber density influence coefficient. For surface roughness parameters in slice geometry data, This is the surface roughness influence coefficient.

[0035] Furthermore, the temperature setpoint for the temperature range is determined in the following manner:

[0036] Calculate the total heating power of the time window corresponding to each temperature range. The total heating power of the window is the sum of the average heating intensity requirements of all thickness sections within the window;

[0037] Based on the total heating power of the window and the convective heat transfer model, the hot air temperature setpoint and hot air velocity setpoint are calculated using the following formula:

[0038]

[0039] in, This represents the total surface area of ​​the batch slices. For window The mass-weighted average of the slice temperature in each thickness section within the slice. For the first Hot air temperature setting for each time window For the first Hot air flow rate setting value for each time window;

[0040] The hot air temperature setpoint and hot air velocity setpoint are solved by an estimation-correction iterative strategy. The positive verification is performed by a coupled model of the moisture diffusion equation and the energy conservation equation. The iteration continues until the temperature deviation and power deviation both meet the convergence conditions.

[0041] Furthermore, the division of the thickness segment includes:

[0042] The range of the slice thickness distribution sequence is calculated and divided by the preset number of thickness segments to obtain the thickness grading step size. Starting from the minimum value of the thickness distribution, the thickness grading step size is incremented upwards to establish a thickness segment boundary value sequence.

[0043] If the number of slices in a certain thickness segment is less than the preset minimum sample size, the thickness segment is merged with the adjacent thickness segments. The representative thickness value after merging is recalculated based on the weighted average of the thickness measurements of all slices in the merged segment, with the weighting factor being the proportion of each slice in the batch.

[0044] According to another aspect of the present invention, a production and processing control system for the slicing and drying process of Chinese medicinal materials is provided, comprising:

[0045] The thickness grading module is used to obtain the slice thickness distribution sequence at the slicer outlet, divide the slice sequence into multiple thickness segments according to the thickness gradient, calculate the water permeation resistance coefficient of the slices in each thickness segment, and generate a correlation mapping table between thickness and water migration characteristics.

[0046] The energy allocation module is used to calculate the cumulative heat required for slices of different thicknesses to reach the target moisture content based on the moisture penetration resistance coefficient of each thickness segment in the association mapping table, and to construct the drying energy demand spectrum with thickness difference compensation.

[0047] The temperature control module is used to dynamically adjust the segmented temperature curves of the drying equipment and the duration of each temperature segment based on the difference in heat accumulation values ​​of each thickness segment in the drying energy demand spectrum, so that the moisture migration rate of slices of different thicknesses tends to be consistent.

[0048] The feedback correction module is used to monitor the surface temperature and center temperature gradient of slices of different thicknesses in the drying chamber in real time. When the center temperature gradient deviates from the preset synchronization range, it provides feedback to correct the step amplitude of the segmented temperature curve and outputs adaptively controlled drying process parameters.

[0049] Compared with existing technologies, this invention obtains the slice thickness distribution sequence at the slicer's outlet, divides the slices into sections based on thickness gradients, and establishes a mapping table relating thickness to moisture migration characteristics. This enables precise statistical analysis of the moisture penetration resistance coefficient of slices with different thicknesses. Furthermore, by monitoring the temperature gradient between the slice surface and center in real time and providing feedback to correct temperature curve parameters, it achieves adaptive control of the drying process for slices of different thicknesses. This not only significantly improves the drying uniformity and final moisture content consistency of medicinal herb slices but also effectively prevents the loss of medicinal components or localized carbonization caused by uneven thickness, thereby comprehensively improving the quality stability and process intelligence of the finished medicinal materials. Attached Figure Description

[0050] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort. In the drawings:

[0051] Figure 1 This is a flowchart of a production and processing control method for slicing and drying Chinese medicinal materials according to an embodiment of the present invention;

[0052] Figure 2 This is a comparison diagram of heat transfer paths for slices of different thicknesses according to an embodiment of the present invention. Detailed Implementation

[0053] Hereinafter, exemplary embodiments according to the present invention will be described in detail with reference to the accompanying drawings. Obviously, the described embodiments are merely some embodiments of the present invention, and not all embodiments of the present invention. It should be understood that the present invention is not limited to the exemplary embodiments described herein.

[0054] As mentioned in the background section above, the existing technology has two main problems: First, the process control parameters are generally coarse, and it is impossible to dynamically manage the moisture migration characteristics and heat requirements of slices of different thicknesses, resulting in uneven drying of slices of different thicknesses and large fluctuations in moisture content, which seriously affects the quality of medicinal materials; Second, there is a lack of real-time, multi-dimensional monitoring and adaptive feedback adjustment mechanisms during the drying process, making it difficult to achieve fine dynamic correction of drying process parameters, resulting in phenomena such as local carbonization or component loss.

[0055] Figure 1 This is a system block diagram of a production and processing control method for slicing and drying Chinese medicinal materials according to an embodiment of the present invention. Figure 1 and Figure 2 As shown, the production and processing control methods for slicing and drying Chinese medicinal materials include:

[0056] S1: Obtain the slice thickness distribution sequence at the slicer outlet, divide the slice sequence into multiple thickness segments according to the thickness gradient, calculate the water penetration resistance coefficient of the slices in each thickness segment, and generate a correlation mapping table between thickness and water migration characteristics.

[0057] Based on the slice thickness distribution sequence data and initial moisture content data of each slice output from the slicer's discharge end, as well as the tissue structure parameters of the Chinese medicinal material and the geometric morphology data of the slices, the following steps are performed:

[0058] Statistical analysis was performed on the slice thickness distribution sequence data to calculate the range, standard deviation, and skewness of the thickness distribution. The thickness grading step size was obtained by dividing the range of the thickness distribution by the preset number of thickness segments. Starting from the minimum value of the thickness distribution, the thickness segment boundary value sequence was established by accumulating upwards according to the thickness grading step size. Based on the thickness segment boundary value sequence, each slice was classified into the corresponding thickness segment according to its thickness measurement value. For each thickness segment, the lower boundary value, upper boundary value, and representative thickness value of the segment were recorded. The representative thickness value was taken as the weighted average of the thickness measurements of all slices within the segment, with the weighting factor being the weight of each slice's thickness measurement within that segment. In this batch, if the number of slices in a certain thickness segment is less than the preset minimum sample number, the thickness segment is merged with the adjacent thickness segment. The lower boundary value of the thickness of the merged thickness segment is the smaller of the lower boundary values ​​of the two merged segments, and the upper boundary value of the thickness is the larger of the upper boundary values ​​of the two merged segments. The representative thickness value is recalculated based on the weighted average of the thickness measurements of all slices in the merged segment. The preset minimum sample number is determined based on the statistical confidence level requirements of the moisture migration characteristic parameters, and the value range is three percent to eight percent of the total number of slices in a single batch.

[0059] For each thickness segment, the representative thickness value of that segment is used as the characteristic dimension of the slice thickness for subsequent establishment of the moisture migration model. Since slices of Chinese medicinal herbs are typically thin sheet-like structures with a thickness much smaller than their diameter, moisture evaporation during drying mainly occurs on the upper and lower large surfaces. Moisture migration within the slice is primarily diffusion along the thickness direction. Therefore, the slice is considered a one-dimensional plate with symmetry in the thickness direction, and a mathematical-physical model describing the distribution of moisture concentration along the thickness direction within the slice is established. This model consists of the following governing equations, boundary conditions, and initial conditions. The governing equations are expressed as follows:

[0060]

[0061] in, This represents the water concentration inside the slice. Drying time, The coordinates are in the thickness direction, with the center of the slice thickness as the origin. The local moisture diffusion coefficient varies with thickness, location, and time; the governing equation represents the local moisture diffusion coefficient at any thickness location. At a given location, the rate of change of water concentration over time is equal to the rate of change of water diffusion flux at that location.

[0062] The centrally symmetric boundary conditions are expressed as:

[0063]

[0064] in, This indicates the center position of the slice thickness. This boundary condition means that the gradient of water concentration along the thickness direction is zero at the center of the slice, that is, there is no net flux of water at the center.

[0065] The surface convection mass transfer boundary condition is expressed as:

[0066]

[0067] in, This represents the thickness of this thickness range. Indicates the position of the upper surface of the slice; The local water diffusion coefficient at the surface of the slice. The convective mass transfer coefficient represents the water exchange capacity between the slice surface and the drying medium. The water concentration at the surface of the slice is expressed in kilograms per cubic meter. The moisture concentration at which equilibrium is reached with the drying medium environment is determined by the temperature and relative humidity of the drying medium. This boundary condition indicates that, on the slice surface, the moisture flux diffusing from the interior to the surface is equal to the moisture flux transferred to the drying medium via convection mass transfer.

[0068] The initial conditions are expressed as follows:

[0069]

[0070] in, The initial moisture content of this thickness segment is obtained from the initial moisture content data. This initial condition indicates that at the start of drying, the moisture concentration at all locations inside the slice is the same and equal to the initial moisture content.

[0071] In addition, to close the above model, it is necessary to determine the local moisture diffusion coefficient. and convective mass transfer coefficient The specific expression, specifically:

[0072] The local moisture diffusion coefficient is expressed as a function of thickness, location, and time to reflect the non-uniformity of the internal tissue structure of the slice and the influence of structural relaxation during drying on moisture migration ability. The formula is as follows:

[0073]

[0074] in, The effective diffusion coefficient of the core layer represents the water diffusion capacity of the dense region at the center of the slice; The effective diffusion coefficient is the surface layer diffusion capacity, representing the ability of water to diffuse in the loose areas of the slice surface. The core-edge transition location represents the dimensionless thickness direction where the diffusion coefficient transitions from the core value to the surface value. The transition layer thickness represents the thickness of the transition region, while the width of the transition region represents the width of the transition layer. The long-term diffusion coefficient retention ratio represents the degree to which the diffusion coefficient remains relative to its initial value after the structural relaxation during the drying process stabilizes. The structural relaxation characteristic time represents the characteristic timescale of relaxation changes that occur in the tissue section structure during the drying process.

[0075] It should be noted that the aforementioned core-edge transition location Transition layer thickness The long-term diffusion coefficient remains proportional. and structural relaxation characteristic time All were obtained through drying experiments. and Determined by the baseline moisture diffusion coefficient and the corresponding tissue structure correction factor, specifically: , ,in The baseline moisture diffusion coefficient was obtained from a database of the physical properties of Chinese medicinal herbs. The center density correction factor reflects the inhibitory effect of fiber density on moisture diffusion in the central region, and is expressed by the formula:

[0076]

[0077] in, Fiber density, a tissue structure parameter, represents the mass of fibrous material per unit volume and is determined by the tissue structure parameters of the Chinese medicinal herb variety. The fiber density influence coefficient was obtained through drying experiments.

[0078] This is the surface porosity correction factor, reflecting the enhancing effect of surface roughness on surface moisture diffusion. The formula is as follows:

[0079]

[0080] in, The surface roughness parameter in the slice geometry data represents the arithmetic mean deviation of the microscopic undulations on the slice surface, and is obtained by profilometry or microscopic imaging. The surface roughness influence coefficient is obtained through drying experiments.

[0081] Convection mass transfer coefficient The mass transfer coefficient is determined by the reference mass transfer coefficient, air velocity, temperature, and humidity, and can be expressed by the formula:

[0082]

[0083] in, The reference mass transfer coefficient represents the convective mass transfer capability under reference operating conditions. The real-time Reynolds number is calculated from air velocity, characteristic length, and air kinematic viscosity. The reference Reynolds number is calculated from the reference air velocity, characteristic length, and reference kinematic viscosity. The Reynolds number exponent represents the sensitivity of the mass transfer coefficient to changes in air velocity. The actual temperature of the air used as the drying medium. For reference temperature, The temperature index represents the sensitivity of the mass transfer coefficient to temperature changes. The humidity-driven enhancement coefficient represents the degree to which ambient humidity enhances or inhibits the mass transfer coefficient. Critical relative humidity represents the environmental relative humidity threshold at which the mass transfer coefficient begins to be significantly affected by humidity. The relative humidity of the drying medium environment is obtained in real time by a humidity sensor inside the drying equipment.

[0084] It should be noted that the aforementioned Reynolds number index Temperature index Humidity-driven enhancement coefficient and critical relative humidity All were obtained through drying experiments.

[0085] Furthermore, after determining the above model parameters, the governing equations are solved numerically, specifically:

[0086] The slice is discretized along its thickness direction into multiple thin layers parallel to the surface. The number of layers is determined based on a representative thickness value and a preset discretization length, with the discretization length ranging from one-tenth to one-twentieth of the representative thickness value. Each thin layer has a defined thickness-direction coordinate and a layer thickness value. In the numerical solution process, the local moisture diffusion coefficient at the center of each thin layer is directly derived from the aforementioned continuous function. The value is obtained at this location, thus ensuring the consistency between the discrete model and the continuous model.

[0087] Meanwhile, when simplifying calculations or estimating initial parameter values, the local moisture diffusion coefficient can also be approximated by multiplying the baseline moisture diffusion coefficient by a porosity correction factor. The formula for the porosity correction factor is as follows:

[0088]

[0089] in, The distance from the center of the thin layer to the surface of the slice is calculated from the coordinates of the thin layer's position. The characteristic attenuation length represents the characteristic scale by which the porosity correction factor decreases with increasing distance. ,in The cell wall permeability coefficient was obtained from a database of the physical properties of Chinese medicinal herbs. This is a dimensionless porosity correction factor, ranging from 0 to 1. The closer to the surface, the larger the factor, indicating more pores and easier water diffusion.

[0090] A non-uniform grid is used to numerically solve this governing equation, and the grid nodes are distributed according to the following formula:

[0091]

[0092] in, For the first The thickness direction coordinates of each grid node. The mesh refinement strength coefficient controls the degree of mesh refinement near the surface. It is a preset constant with a value ranging from 0.2 to 0.5. This represents the total number of grid nodes, preset according to the required calculation accuracy. This refers to the grid node number.

[0093] By solving the above governing equations, the evolution of the moisture concentration field within the slice over time is obtained. Further calculations are made of the time required for the average moisture content of the slice in this thickness section to decrease from its initial value to the target moisture content; this time is the moisture migration time constant for this thickness section. The equivalent moisture diffusion coefficient is calculated using a harmonic average method that weights the local moisture diffusion coefficients of each thin layer according to volume. The volume weight is the ratio of the volume of each thin layer to the total volume of the slice. Since the thickness and cross-sectional area of ​​each thin layer are the same, the volume weight equals the proportion of the thickness of each thin layer to the total thickness of the slice. The equivalent moisture diffusion coefficient reflects the overall moisture migration capacity of the slice along the thickness direction. Tissue structure parameters and geometric morphology data influence the value of the equivalent moisture diffusion coefficient through the spatial distribution of the local moisture diffusion coefficient. The moisture migration time constant can also be quickly estimated using the following approximate formula:

[0094]

[0095] in, The water migration time constant, This represents the thickness of this thickness range. The equivalent moisture diffusion coefficient is calculated by harmonic averaging the local moisture diffusion coefficients of each thin layer according to volume weights. This approximate formula shows good agreement with the exact numerical solution when the spatial variation of the diffusion coefficient is not drastic.

[0096] For slices with the same representative thickness but different tissue structure parameters, the equivalent water diffusion coefficient differs due to variations in the local distribution of water diffusion coefficients, resulting in differences in the water migration time constant. For slices with the same tissue structure parameters but different representative thickness values, since the water migration time constant is proportional to the square of the representative thickness, doubling the thickness will quadruple the water migration time constant, demonstrating the strong nonlinear influence of thickness on the water migration process. Simultaneously, a water migration resistance coefficient is constructed based on the representative thickness and the equivalent water diffusion coefficient. This resistance coefficient is defined as the ratio of the square of the representative thickness to the equivalent water diffusion coefficient. It has the same physical dimensions and value as the water migration time constant and is used to characterize the overall resistance that water must overcome to migrate from the center to the surface within the slice. A larger thickness or a smaller equivalent water diffusion coefficient results in a larger water migration resistance coefficient and a slower water migration process.

[0097] The lower and upper boundary values ​​of thickness, representative thickness values, equivalent moisture diffusion coefficients, moisture migration time constants, and moisture migration resistance coefficients of each thickness segment are stored in a structured manner. Thickness segment indexes and parameter type indexes are established. The thickness segment indexes number each thickness segment in ascending order of the representative thickness value. The parameter type indexes classify and identify the various moisture migration characteristic parameters stored for each thickness segment. Combining the proportion of each thickness segment in the slice thickness distribution sequence and the total mass of the batch of medicinal materials, the total moisture mass to be removed from each thickness segment during the drying process is calculated. The total moisture mass is the slice mass of that thickness segment multiplied by the initial moisture content and the target moisture content. The difference in the rate generates a set of moisture migration characteristic parameters for thickness stratification. The set of moisture migration characteristic parameters for thickness stratification includes a thickness feature vector composed of representative thickness values ​​of each thickness segment, a time constant vector composed of moisture migration time constants of each thickness segment, a diffusion coefficient vector composed of equivalent moisture diffusion coefficients of each thickness segment, a resistance coefficient vector composed of moisture migration resistance coefficients of each thickness segment, and a dewatering load vector composed of the total mass of moisture to be removed from each thickness segment. The set of moisture migration characteristic parameters for thickness stratification is stored in the form of a data structure. Any moisture migration characteristic parameter of any thickness segment can be accessed through the thickness segment index and parameter type index.

[0098] S2: Based on the moisture penetration resistance coefficient of each thickness segment in the association mapping table, calculate the cumulative heat required for slices of different thicknesses to reach the target moisture content, and construct the drying energy demand spectrum with thickness difference compensation.

[0099] Based on the moisture migration time constant and equivalent moisture diffusion coefficient of each segment in the moisture migration characteristic parameter set of thickness stratification, heat transfer paths for slices of different thicknesses to decrease from the initial moisture content to the target moisture content are constructed. For each thickness segment, it is assumed that all slices within that segment have the same representative thickness value. Diameter representative value Initial moisture content Target moisture content and quality ratio slice density and specific heat capacity Obtained from the database of physical properties of Chinese medicinal materials.

[0100] Furthermore, since the slices of Chinese medicinal herbs are on the order of millimeters in thickness, have high thermal conductivity, and a Bishop number far less than 0.1, assuming a uniform temperature inside the slices, an energy conservation equation is established:

[0101]

[0102] in, This refers to the slicing temperature; The convective heat transfer coefficient is calculated from the hot air velocity and temperature inside the drying equipment based on the heat transfer correlation. To determine the surface area of ​​the slice participating in convective heat transfer, the areas of the upper and lower main surfaces are taken. , This represents the slice diameter. The temperature of the hot air used for drying the medium; The latent heat of vaporization of water is obtained from the water vapor property table based on the slice temperature. The water evaporation rate is calculated from the surface convection mass transfer boundary conditions in S1, i.e. .

[0103] The above energy equation and the one-dimensional moisture diffusion equation in S1 form a coupled system. The time-progression method is used for numerical solution. In each time step, the moisture diffusion equation is solved first to obtain the new moisture concentration distribution and surface flux. Then the energy equation is updated to obtain the new slice temperature. This process is iterated until the average moisture content of the slice reaches the target moisture content.

[0104] During the numerical solution process, the instantaneous heating intensity demand at each time step is recorded, and the formula is expressed as:

[0105]

[0106] in, This is for the instantaneous heating intensity requirement.

[0107] The curve showing the change of instantaneous heating intensity over time is the intensity-time characteristic curve of the heat transfer path of the slice in this thickness section. It rises rapidly in the early stage of drying, and then shows a single peak shape of high at the beginning and low at the end of the drying and dehydration stage, eventually approaching the level that only compensates for sensible heat loss.

[0108] like Figure 2 The figure shows a comparison of heat transfer paths for slices of different thicknesses generated in an embodiment of the present invention. The figure plots the heat demand evolution trajectories of thin slices (1.5mm, red curve), medium-thickness slices (3.0mm, blue curve), and thick slices (4.5mm, green curve) during the drying process, with time as the horizontal axis and instantaneous heat intensity as the vertical axis. The peak heat intensity of the thin slice (approximately 85W) occurs around 20 minutes, the peak heat intensity of the medium-thickness slice (approximately 72W) occurs around 35 minutes, and the peak heat intensity of the thick slice (approximately 95W) occurs around 50 minutes. The peak positions of each curve are marked with dashed lines, and the half-peak width of the curve is indicated by double-headed arrows to represent the duration of heat demand. The comparison chart intuitively illustrates the core technical problem of the method of the present invention: the heat demand of slices of different thicknesses is significantly misaligned on the time axis. Compared with the traditional fixed temperature curve, which cannot take into account the synchronous drying needs of slices of different thicknesses, resulting in thin slices being over-dried or thick slices being under-dried, the present invention constructs a drying energy demand spectrum and dynamically adjusts the segmented temperature curve to ensure that slices of each thickness segment receive appropriate heat intensity during their respective peak demand period, thereby achieving synchronous control of the moisture migration progress of slices in the same batch and significantly improving the uniformity of product quality.

[0109] The total heat demand for the slice in each thickness section is obtained by numerically integrating the heat transfer path over the entire time interval from the start of drying to reaching the target moisture content. The formula is as follows:

[0110]

[0111] in, The moment when the average moisture content of the slice in this thickness section drops from the initial value to the target moisture content is given by the coupled model.

[0112] Each thickness section According to its quality proportion Weighted summation yields the total energy requirement for drying the entire batch of slices. .

[0113] The timeline of the entire drying process is set from 0 to the maximum. (The latest time when the target moisture content is reached among all thickness sections) is divided into... A continuous time window, The value range is from 5 to 20. The method of dividing the time window is selected according to the equipment control accuracy requirements: if equal duration is used, the duration of each window is... If a variable duration division is used, the mass-weighted average value of the peak time of heat transfer path in each thickness segment is used. ,exist The system allocates approximately 60% of the time window within the current period and approximately 40% of the remaining time window. For each time window... Calculate the thickness of each section The average heating intensity demand within this window is expressed by the formula:

[0114]

[0115] in, For the first The thickness section is in the first Average heating intensity demand within the time window For the first Duration of the time window For the first Instantaneous heating intensity demand function for the thickness section.

[0116] If a certain thickness section has already reached the target moisture content at the beginning of the window, then the subsequent windows... Set it to 0.

[0117] window The sum of the average heating intensity of all thickness sections within the interior This refers to the total heating power that the drying equipment needs to output within this window.

[0118] Furthermore, for in the window Internal thickness difference compensation is implemented, and a normalized weight allocation method is used to determine the heat intensity distribution ratio of each thickness section. Specifically:

[0119] First, calculate the basic importance index. This indicator reflects the window The contribution of this thickness section to the overall drying process; and the introduction of a moisture content deviation correction factor. , defined as the average moisture content of the thickness segment at the start of the current window. With target moisture content The degree of deviation is expressed by the formula: The correction factor is close to 1 in the early stages of drying, gradually decreasing as drying progresses, and reaching zero when the slices reach the target moisture content. Multiplying the basic importance index by the correction factor yields the corrected importance index. .

[0120] Furthermore, calculate the overall heating weight. ,in, For the first Mass percentage of the thickness section;

[0121] Then, the thickness ranges are normalized, as expressed by the formula:

[0122]

[0123] in, For the first The thickness section is in the first The heat intensity distribution ratio within the time window is dimensionless and satisfies... .

[0124] The allocation ratio automatically reflects the dynamic differences in the drying process: in the initial window, the thinner sections have relatively high importance indicators and a higher allocation ratio because of their rapid moisture migration and high evaporation rate; the thicker sections have a lower allocation ratio because their surface evaporation is limited by the internal moisture supply; in the middle window, the thinner sections are close to the drying end point, and their importance indicators drop rapidly, while the thicker sections enter the vigorous evaporation stage, and their allocation ratio increases; in the later window, all sections enter a slow-down drying process, and the heating is mainly used for sensible heat compensation, so the differences naturally narrow.

[0125] Furthermore, depending on whether the drying equipment has the capability for layered or zoned heating, the windows... The allocation ratio is converted into actual control instructions:

[0126] If the device has the capability to layer or partition, then for each thickness segment... The layer or area in the window The heating power setting value is ;

[0127] If a layer or region contains multiple thickness sections, they are weighted and combined according to their mass proportion. If the equipment does not have the capability to layer or zone, the overall heating power setting is [value missing]. At this point, it is not possible to apply different powers to sections of different thicknesses, but thickness compensation can be approximated by adjusting the window duration. Specifically, the segmented energy distribution scheme is substituted into the coupled model for forward simulation to obtain the actual average water content of each thickness section at the end of each window. The difference between the actual average moisture content and the expected moisture content of each thickness section within the window is defined as the time deviation. The expected moisture content is estimated by dividing the energy allocated to that section within that window by the energy required for unit water evaporation; if This indicates insufficient dehydration; the duration of the next window should be extended by 5% to 10%. This indicates excessive dehydration, and the duration of the next window should be shortened by 5% to 10%. Simultaneously, the following constraints are imposed: the actual moisture content of any thickness segment at the end of any window must not be lower than the target moisture content minus a safety margin, nor higher than the target moisture content plus a maximum tolerance. The safety margin is 5% to 10% of the target moisture content, and the maximum tolerance is 10% to 15% of the target moisture content. This process is iterated until the deviation of each thickness segment from reaching the target moisture content does not exceed a preset tolerance. In one example, the preset tolerance is 2% of the target moisture content.

[0128] A segmented energy distribution scheme with thickness compensation is generated and stored in the form of a structured data table. The table header includes the time window number, window start time, window end time, window duration, total heating power of the window, and the heating intensity distribution ratio and corresponding power setting value for each thickness segment. For each time window, if the equipment supports hot air temperature and air velocity adjustment, the hot air temperature setting value and hot air velocity setting value for that window are also included.

[0129] Furthermore, based on the total heating power of the window and the convective heat transfer model, the hot air temperature setpoint and hot air velocity setpoint are calculated in reverse. The inverse calculation formula is as follows:

[0130]

[0131] in, This represents the total surface area of ​​the batch slices. For window The mass-weighted average of the slice temperature in each thickness section within the slice. For the first Hot air temperature setting for each time window For the first The hot air flow rate setting value for each time window.

[0132] It should be noted that, due to the inverse calculation formula It is impossible to predict precisely before the window opens, and temperature and flow rate are controlled by... Nonlinear coupling necessitates an iterative solution using a predictor-corrector strategy. The specific steps are as follows: First, assume... It is equal to the slice temperature at the end of the previous window and is fixed. Substituting the value of the middle value of the usable range of the wind turbine into the above power balance equation, we obtain the corresponding value. Check if the temperature is within the equipment's allowable range; if it is outside, adjust it. Solve again; then obtain the result and Substitute the values ​​into the coupled model to perform a forward simulation of the time window, obtaining the actual average slice temperature within the window; if the deviation between the actual value and the assumed value exceeds a preset threshold, then update the model with the actual value. The above solution process is repeated iteratively until both the temperature deviation and power deviation satisfy the convergence condition. The final result is... and This refers to the setpoints for the hot air temperature and flow rate within that time window, which guide the adjustment of the heating power and fan operating parameters of the drying equipment within that window.

[0133] The above-mentioned prediction-correction iteration process is completed offline before the window begins. It belongs to the planning calculation of the control scheme. Once the window begins execution, the drying equipment will operate according to the hot air temperature setpoint and flow rate setpoint determined in the window. The prediction-correction iteration in this method will not be performed during the window execution. If a deviation occurs in the actual operation, it will be automatically compensated in the planning calculation before the next window begins.

[0134] S3: Based on the difference in heat accumulation value of each thickness segment in the drying energy demand spectrum, dynamically adjust the segmented temperature curve of the drying equipment and the duration of each temperature segment to make the moisture migration rate of slices of different thicknesses tend to be consistent.

[0135] Based on the segmented energy distribution scheme with thickness compensation, the drying process is decomposed into a combination sequence of heating, constant temperature and cooling stages. By adjusting the temperature setpoint of each stage, the switching time between stages and the hot air flow rate, the moisture migration progress of slices of different thicknesses is kept synchronized within the preset synchronization tolerance, generating an adaptive drying temperature control command.

[0136] First, the hot air temperature setpoint, hot air velocity setpoint, and total heating power setpoint for each time window are extracted from the segmented energy distribution scheme and arranged in chronological order to form a window-level control parameter sequence. The hot air temperature setpoint and hot air velocity setpoint are optimized variables obtained through iterative solutions to the power balance equation in S2, while the total heating power setpoint is the sum of the average heating intensity of each thickness segment within the window. If the equipment itself does not support hot air velocity adjustment, the velocity remains a fixed value during the back-calculation process in S2, and the corresponding hot air velocity setpoint column in S3 uses this fixed value; no further active adjustment of the velocity is performed. After extraction, adjacent time windows need to be merged into temperature segments based on temperature change characteristics to reduce the switching frequency of control commands.

[0137] The merging criteria are as follows: if the difference between the temperature settings of adjacent windows is less than the temperature change threshold. If the temperature control accuracy requirements of the two windows are similar, they can be merged into the same isothermal range. This threshold is jointly determined by the temperature control accuracy of the equipment and the sensitivity of the slice to temperature fluctuations. In one example, it can be set to 3 K to 5 K. If the temperature of the latter window is higher than that of the former window and the difference exceeds [a certain threshold], then [the threshold is considered to be missing from the original text]. If the temperature of the next window is lower than that of the previous window and the difference exceeds a certain threshold, it is identified as a heating phase; If the peak power demand exceeds a certain threshold, it is identified as a cooling segment. However, before merging, it is necessary to check whether there is a significant peak power demand within each window to avoid the time-weighted average masking local peaks after merging. Specifically, if the heating power setpoint of any thickness segment within a window exceeds the average heating power of that window... If the peak power is multiple times the threshold, it is considered that there is a local peak demand within the window. This window will not participate in the merging of adjacent windows and will be retained as a separate temperature range. The peak power retention threshold is... The value is determined based on the deviation in the time when each thickness segment reaches the target moisture content before and after merging in historical batch simulations. In one example, a value of 1.5 can be used. After completing the above checks, adjacent windows that can be merged are merged into a temperature segment. The temperature setpoint within the segment is taken as the time-weighted average of the temperature setpoints of the windows contained in the segment, with the weight being the duration of each window.

[0138] Based on the initial temperature segment division, the synchronization of the switching time between segments is further optimized to ensure that thick and thin slices reach the target moisture content as simultaneously as possible. To this end, the moisture migration progress of each thickness segment is defined as follows: ,in For the first Thickness section at time The average moisture content is obtained through a soft measurement method in actual production. This method uses the one-dimensional moisture diffusion model of S1 as the core, and collects data online on hot air temperature, hot air velocity, relative humidity in the drying chamber, and surface temperature of the slices. These measurable variables are then used as boundary conditions input into the model to calculate the moisture content distribution of each thickness section in real time.

[0139] Meanwhile, since the model recursion accumulates errors over time, it is necessary to periodically sample representative slices for rapid moisture detection, using the detected values ​​to correct the bias of the soft-sensor model. Considering the significant differences in moisture evaporation rates at different stages of the drying process, a fixed calibration period could lead to a rapid increase in accumulated model errors during the rapid evaporation stage, while frequent sampling during the deceleration stage would increase detection costs. Therefore, the sampling calibration period needs to be dynamically adjusted according to the drying stage: in the early and middle stages of drying when moisture evaporation rates change drastically, the calibration period is set to 5 minutes to ensure model accuracy; in the later stages of deceleration drying when moisture changes are gradual, the calibration period can be extended to 10 to 15 minutes to balance calibration accuracy and detection costs. Based on the above progress definition, the initial temperature segment scheme is substituted into the coupled model of the S1 moisture diffusion equation and energy conservation equation for forward simulation, recording the time when each thickness segment reaches the target moisture content. Calculate the difference between the times when the maximum and minimum are reached. .like Exceeding the preset synchronization tolerance This indicates poor synchronization between the drying of thick and thin sheets, requiring adjustment of the inter-section switching time or temperature setting; the preset synchronization tolerance is also relevant. The timeframe is determined by the production cycle time, the requirements for subsequent processes, and the requirements for quality uniformity. In one example, it can be set to 10 minutes.

[0140] Furthermore, the rules are adjusted as follows:

[0141] For thickness sections that significantly exceed the target moisture content, advance the end time of their high-temperature segment or reduce the temperature setpoint of that segment by 3% to 5%. For thickness sections that significantly lag behind in reaching the target moisture content, extend the duration of their high-temperature isothermal segment or increase the temperature setpoint of that segment by 3% to 5%. After adjustment, perform a new forward simulation and repeat the above process. Synchronous optimization iterations require setting a maximum number of iterations; in one example, this can be set to 20 to avoid infinite loops. If convergence to the target moisture content cannot be achieved within the maximum number of iterations... If the result is not satisfactory, the synchronization optimization is considered to have failed. In this case, the following measures should be taken according to priority: First, try to increase the tolerance to 1.5 times the original tolerance and re-evaluate; if it is still not satisfactory, split the batch into multiple sub-batches according to the thickness distribution and dry them separately; if it is still not satisfactory, adjust the blade gap of the slicer or the feeding speed to improve the uniformity of the thickness distribution.

[0142] Once synchronization optimization is complete, engineering verification of the temperature change rate for each temperature range is required to ensure the equipment can perform the necessary operations. This includes:

[0143] For the heating section, the heating rate is equal to the temperature difference within the section divided by the duration of the section. If the rate exceeds the maximum heating capacity of the drying equipment's heating system, the duration of the section is extended to reduce the rate to within the allowable range of the equipment. The maximum heating capacity is determined by the heating power and hot air circulation system design provided by the equipment manufacturer and is an inherent parameter of the equipment.

[0144] For the cooling section, the cooling rate is a negative value, and its absolute value should simultaneously satisfy the constraints of the equipment's active cooling capacity and natural heat dissipation characteristics. If the equipment relies solely on natural heat dissipation, the cooling rate cannot exceed the maximum natural cooling rate. This value is determined by the equipment's insulation performance and the current ambient temperature and can be measured through natural cooling experiments. If the required cooling rate exceeds this value, a constant-temperature platform needs to be inserted within the section for segmented cooling to prevent temperature runaway. If the equipment is equipped with an active cooling system, first determine the difference between the required cooling rate and the maximum natural cooling rate. When the difference exceeds the active cooling trigger threshold... When the temperature difference does not exceed the threshold, the active cooling device is activated first, achieving controlled rapid cooling through cold air injection or water cooling circulation. When the temperature difference does not exceed the threshold, segmented natural cooling is adopted by inserting a constant temperature platform to balance energy efficiency and control accuracy. Active cooling trigger threshold The response time and energy efficiency characteristics of the equipment's active cooling system are determined by this factor; in one example, it can be taken as 2 K / min.

[0145] For the constant temperature range, the rate of temperature change is zero, but a temperature fluctuation tolerance needs to be set. When the actual temperature fluctuates within this range, no correction action is triggered, avoiding frequent adjustments to the control system. This tolerance is jointly determined by the slice's sensitivity to temperature fluctuations, the temperature sensitivity of the active ingredient degradation rate, and the accuracy of the temperature sensor. In one example, The set temperature can be ±2 K to ±5 K.

[0146] Furthermore, depending on the specific control method of the drying equipment, the temperature control commands need to be adapted, including:

[0147] If the equipment uses on / off heating control, the constant temperature section is achieved by adjusting the duty cycle. The duty cycle is equal to the average heating power required for this section divided by the rated power of the heater. The control system switches the heater on and off periodically according to this duty cycle to maintain a constant average temperature. The heating section allows the heater to run at full power until the target temperature is reached. The cooling section stops heating and starts the cooling device or relies on natural heat dissipation.

[0148] If the equipment uses proportional heating control, the constant temperature section is achieved through PID feedback adjustment. The controller collects temperature sensor signals in real time and inputs the deviation between the measured temperature and the set value into the PID algorithm to obtain power adjustment commands.

[0149] If the equipment is equipped with a multi-zone independent heating system, the instruction sequence needs to be expanded into a multidimensional table, with each physical zone corresponding to a column of temperature setpoints. Since the division of physical zones is predetermined by the equipment structure and cannot be dynamically adjusted, when the same heating zone contains multiple thickness segments, the temperature setpoint for each temperature segment in that zone is calculated as a weighted average based on the mass proportion of each thickness segment within that zone. However, if the mass proportion of a certain thickness segment within the zone exceeds the zone's dominant threshold... The regional temperature setpoint is determined primarily by the temperature demand of that section to avoid insufficient heating in the dominant section due to weighted averaging. The regional dominant threshold is determined by the influence of the mass percentage of other thickness sections on the overall regional heating; in one example, it can be set to 60%. If the difference in heating power demand between different thickness sections within the same heating area exceeds the regional power difference threshold... This indicates that the temperature setting of a single area cannot simultaneously meet the needs of each section. In this case, the area adopts secondary optimization within the temperature range, that is, the total heating power of the area is allocated according to the real-time demand ratio of each thickness section, and the differentiated heating within the area is achieved by adjusting the damper opening or local baffles of the area. The regional power difference threshold is determined by the damper adjustment accuracy and the temperature uniformity capability within the area. In one example, it can be taken as 30%.

[0150] In addition, safety constraints and exception handling logic need to be added during the execution of temperature control commands, including:

[0151] When the measured value of any temperature sensor exceeds the upper limit of the set value and the deviation exceeds the safety protection temperature threshold. If the heating power is too high or the temperature control system is malfunctioning, the heating power should be reduced immediately or the heating power should be cut off, and an emergency cooling program should be started to prevent the slices from deteriorating in quality or carbonizing due to overheating.

[0152] When the measured temperature is lower than the set lower limit and the deviation exceeds If the heating power is insufficient or there is abnormal heat dissipation, the heating power should be increased to the rated upper limit, and the oven's sealing and insulation layer integrity should be checked. The safety protection temperature threshold is determined by the equipment's safety standards and the maximum withstand temperature of the slices. It is necessary to ensure that heating is cut off before the slices are damaged. In one example, it can be taken as 10 K.

[0153] For the triggering conditions of adaptive correction, a clear threshold needs to be set to avoid frequent triggering that could lead to instability in the control system: if a certain thickness segment is delayed beyond its expected drying end time by more than [a certain threshold is specified]. The target moisture content has not yet been reached, or the current average moisture content measured by soft sensors in this section deviates from the target value by more than the target value. If so, the adaptive correction mechanism will be activated; where Determined by the maximum allowable delay time in production, which in one example could be 15 minutes, and the moisture content deviation threshold. The maximum allowable moisture content deviation is determined by production; in one example, it can be taken as 5%. After the correction is initiated, based on the current deviation of the section, the temperature setpoint of the area where the section is located is dynamically increased by 3% to 5% in subsequent temperature sections, or the duration of the corresponding high temperature section is extended by 5 to 10 minutes. At the same time, the actual drying data of the section is recorded in the historical database for model parameter calibration in subsequent batches.

[0154] The final generated adaptive drying temperature control command is organized in the form of a structured data table. The table header includes the command number, segment type identifier, segment start time, segment end time, segment duration, segment start temperature, segment end temperature, temperature change rate, hot air flow rate setpoint, auxiliary control enable flag, and auxiliary control parameters. The auxiliary control enable flag is a Boolean value used to indicate whether hot air flow rate adjustment is enabled for this temperature segment.

[0155] If the equipment supports flow rate adjustment and this section requires flow rate auxiliary control, then the flag is set to true, and the flow rate value obtained by back-calculation in S2 is filled into the hot air flow rate setpoint column;

[0156] If the equipment does not support flow rate adjustment or only requires temperature control for this section, the flag is set to false, and the hot air flow rate setpoint column is filled with a fixed flow rate value or left blank. The control system reads this flag and decides whether to adjust the fan operating parameters. The system also synchronizes the evolution trajectory of the ideal temperature difference for each thickness section in each temperature range corresponding to the final optimized solution. Stored as an auxiliary data table.

[0157] This instruction set can be directly issued to the programmable logic controller (PLC) or host computer monitoring system of the drying equipment for execution. During execution, the control system automatically switches the temperature and flow rate setpoints according to the time nodes in the instruction sequence. It collects the equipment status in real time through temperature, humidity, and wind speed sensors, dynamically adjusts the sampling and detection cycle according to the drying stage, corrects the soft measurement estimation results based on the S1 moisture diffusion model with the measured moisture value, and compares the actual moisture migration progress of each thickness section with the expected trajectory. If the deviation exceeds the allowable range, an adaptive correction algorithm is triggered to adjust the temperature setpoint and switching time of subsequent sections. If the deviation is within the allowable range, the original instruction continues to be executed.

[0158] S4: Real-time monitoring of the surface temperature and center temperature gradient of slices of different thicknesses in the drying chamber. When the center temperature gradient deviates from the preset synchronization range, feedback is provided to correct the step amplitude of the segmented temperature curve and output adaptively controlled drying process parameters.

[0159] During the drying process, the internal temperature distribution characteristics of slices of different thicknesses are monitored in real time to evaluate the heat transfer efficiency and moisture migration synergy of each thickness segment under the current temperature control command. Specifically:

[0160] For each thickness segment, temperature measurement points are arranged on a representative slice within that segment: surface temperature measurement points use non-contact infrared temperature sensors or thermocouples attached to the slice surface to measure the temperature of the surface of the slice in direct contact with the hot air, and this temperature is recorded as the measured surface temperature value. ,in This refers to the thickness section number. For the first At each sampling time, a thin thermocouple with a diameter not exceeding 0.5 mm was inserted into the geometric center of the slice to measure the core temperature of the slice, which was recorded as the measured value of the core temperature. .

[0161] For thin slices less than 3 mm thick, a soft measurement method is used instead. This method uses a coupled model consisting of a one-dimensional moisture diffusion model established in S1 and an energy conservation equation established in S2 as its core. The measured surface temperature and current hot air parameters are used as boundary conditions, and the center temperature of the slice is inferred by solving a system of partial differential equations. This soft measurement method undergoes destructive sampling verification upon initial use or when model parameters change significantly to ensure the deviation does not exceed ±2 K. For example, it can be verified at least once every 50 batches. During normal operation, non-destructive rapid moisture detection is used for periodic calibration, such as using a near-infrared moisture meter for non-contact detection every 10 minutes. The sampling frequency of the temperature difference is dynamically adjusted according to the drying stage: 30 to 60 seconds for the heating stage, 2 to 3 minutes for the isothermal stage, and 3 to 5 minutes for the cooling stage.

[0162] At each sampling time , for the Calculate the temperature difference for each thickness section. The temperature difference reflects the resistance to heat transfer within the slice; a larger difference indicates slower heat transfer from the surface to the center, and a more limited driving force for moisture migration from the center to the surface. The temperature differences obtained from continuous sampling are arranged in chronological order to form a sequence, and subsequences are extracted segment by temperature range.

[0163] Regarding the currently ongoing [number]th The temperature range, from the first Sampling points within a segment are extracted from the complete temperature difference sequence of a thickness range to form a subsequence within that segment. Let this subsequence contain... Given 10 sampling points, calculate the maximum value of the subsequence. and minimum value Define absolute fluctuation range This indicator directly reflects the range of temperature difference variation within this segment. It also defines the relative fluctuation intensity. This index eliminates the influence of average levels and is suitable for comparing fluctuation characteristics between different thickness sections or different temperature ranges. The arithmetic mean is... and standard deviation The calculation formula is expressed as:

[0164]

[0165]

[0166] when Exceeding the absolute fluctuation threshold or Exceeding the relative fluctuation threshold When this occurs, it is determined that the temperature difference fluctuation of the thickness segment within that temperature range is abnormal; for example, the absolute fluctuation threshold... It can be set to 20% of the average value of the ideal temperature difference in this segment, as the relative fluctuation threshold. The threshold can be set to 30%, and these two thresholds are determined based on process requirements and historical batch data. In addition, a fixed-duration sliding time window is set within the segment, with a window width of 20% to 30% of the temperature segment duration and not less than 5 minutes. The fluctuation amplitude of the temperature difference subsequence within each window is calculated separately. By comparing the fluctuation amplitudes of different windows, it is possible to identify whether there are local fluctuation abrupt changes within the temperature segment, which serves as supplementary information for segment-level fluctuation amplitude and is used to more precisely locate the source of fluctuations.

[0167] Furthermore, the allowable range of heat transfer synchronicity in different thickness sections is measured by the synchronous control bandwidth. When generating the temperature control command in step S3, the ideal temperature difference evolution trajectory in each temperature range for each thickness section has been obtained through a forward simulation using a coupled model of the S1 moisture diffusion model and the S2 energy conservation equation. This trajectory reflects the change in the temperature difference between the surface and center of the slice over time under ideal heating conditions, and is stored in the parameter library of the control system.

[0168] For the Each temperature range defines the synchronous control bandwidth. The heating stage is set to 15% to 20% of the peak value of the ideal temperature difference, the constant temperature stage is set to 10% to 15% of the average value of the ideal temperature difference, and the cooling stage is set to 20% of the average value of the ideal temperature difference.

[0169] If the standard deviation of the thickness distribution of a batch of slices exceeds 30% of the average thickness, the bandwidth of each segment will be uniformly increased by 1.5 times.

[0170] In the temperature range During execution, for each thickness segment The deviation between the actual temperature difference and the ideal trajectory is calculated and expressed as:

[0171]

[0172] And calculate the average absolute value of the deviation sequence within that segment:

[0173]

[0174] like Or, there are 3 or more consecutive sampling points where the absolute value of the deviation exceeds If the limit is exceeded, closed-loop correction will be triggered.

[0175] At the same time, the inconsistency of temperature difference between sections is calculated. That is, the maximum difference in the average temperature difference among all thickness sections within that section. This was determined to be a deviation in synchronicity between segments.

[0176] When an out-of-limit condition is detected, a closed-loop correction mechanism is activated. First, the thickness sections that meet the out-of-limit conditions are included in the correction target list, and then corrected according to priority indicators. Sort, where This represents the mass percentage of the thickness segment, derived from the segmented energy distribution scheme in step S2. Before performing correction, a preliminary diagnosis of the deviation is conducted: if the actual temperature difference consistently exceeds the ideal value and the surface temperature is below the set value, insufficient heating is determined; if the surface temperature is close to the set value but the center temperature rises slowly, excessive internal heat transfer resistance is determined; if the actual temperature difference consistently falls below the ideal value and the surface temperature exceeds the set value, excessive heating is determined; if the temperature difference fluctuates drastically but the average value is close to the ideal value, the control system is oscillating.

[0177] For areas with insufficient heating, calculate the temperature setpoint increment. ,in To correct the gain coefficient, which is obtained through regression analysis of historical batch data or equipment response testing, a value of 0.5 to 0.8 can be used, for example. The absolute value of a single increment must not exceed 8% of the original setpoint and must not exceed 5 K. For sections with excess heating, the same strategy is used, but the increment is negative. In addition to immediate correction, the temperature setpoint for subsequent constant-temperature sections is pre-adjusted, including:

[0178] When heating is insufficient, the setting value of subsequent sections is increased by 50% to 70% of the current correction increment, decreasing as the section number increases;

[0179] Reverse adjustment is made when there is excess heating. If the correction involves a multi-zone heating system, the adjustment amount for each zone is weighted and averaged according to the mass ratio of the thickness section within the zone. If the weighted adjustment amount is less than 1 K, it is not executed.

[0180] If a certain dominant section accounts for more than 60% of the quality and the correction requirement is opposite to that of other sections, then the dominant section shall be used as the standard, and other sections shall be compensated separately by damper opening or the next temperature section.

[0181] For equipment equipped with flow rate adjustment capability, when the deviation stems from insufficient surface heat transfer coefficient, the hot air flow rate can be adjusted as an auxiliary measure. The flow rate adjustment amount is as follows: Calculation, where The flow rate correction factor needs to be calibrated according to the characteristics of the equipment duct and the stacking method of the slices. For example, it can be taken as 0.1 to 0.3 m / s / K. The single adjustment amount should not exceed 15% of the initial flow rate, and the total flow rate should be within the allowable range of the equipment.

[0182] The correction and adjustment quantities are packaged into a calibration command and sent to the programmable logic controller (PLC). The PLC verifies the validity of the command and then updates the control parameters of the current and subsequent segments. If the verification fails, an exception code is returned and manual intervention is triggered.

[0183] After the calibration command is issued, an evaluation time window is set to observe the changes in deviation. The length of the evaluation window depends on the thermal response time constant of the equipment: 3 to 5 minutes for hot air circulating ovens and 8 to 10 minutes for steam-heated drying rooms.

[0184] Continue collecting data within the window and calculate the average deviation: if the average deviation is lower than... If the result reaches 80%, the correction is considered converged, and the closed-loop correction is exited.

[0185] If the deviation decreases but remains above 80%, a second correction is performed, with the gain of the second correction reduced to 70% of that of the first correction.

[0186] If the deviation does not decrease or increases, the correction is deemed invalid. Automatic correction is paused and a diagnostic subroutine is initiated or manual intervention is initiated.

[0187] A maximum number of calibration iterations is set for each thickness segment within a single temperature range. If this limit is exceeded, the following priority-based processing is implemented: First, the actual thickness deviation is checked. If it exceeds the nominal value by 20%, the segment is separated for individual drying or reclassified. If the thickness is normal, the operating conditions of equipment such as heaters, fans, ducts, and sensors are checked. If any abnormalities are found, the equipment is shut down for maintenance. If the equipment is functioning normally, the tolerance is increased to 1.5 times the original bandwidth, and this is a key area for spot checks in subsequent quality inspections. Complete records of each calibration are stored in a historical database. High-frequency calibration segments, common deviation patterns, and effective gain coefficient ranges are periodically analyzed to optimize S1 model parameters and the S2 energy allocation scheme.

[0188] After the drying process is completed, the optimized process control parameters are output. The actual temperature control parameters executed are compiled, including the final temperature setpoint, actual duration, hot air flow rate setpoint, and average heating power for each segment, and stored and compared with the preset parameters.

[0189] Output the actual temperature difference sequence, moisture content change curve, time to reach target moisture content, and final moisture content uniformity index for each thickness section, and plot them by overlaying them with the ideal curve.

[0190] Calculate synchronous control performance indicators, including the standard deviation of the time when the target moisture content is reached, the proportion of temperature difference exceeding the limit, the total number of correction triggers, the average number of iterations, and the correction convergence rate, and evaluate the control quality by comparing with historical batches.

[0191] Based on the closed-loop calibration data, the deviation of the S1 model parameters is inferred. Through sensitivity analysis and inversion optimization, the suggested correction values ​​and confidence intervals are calculated. The model parameter library is updated when multiple batches are consistent in direction.

[0192] Based on the data from this batch, a pre-adjustment plan for the next batch is generated: for temperature segments that frequently trigger correction, the initial temperature setpoint is pre-biased in S2; for segments where the actual duration deviates significantly from the preset value, the switching time in synchronization optimization is adjusted; for equipment response lag or oscillation, the PID parameters are adjusted. The process parameters, correction records, drying curves, and product quality inspection data for this batch are linked and stored to establish a process-quality mapping relationship, supporting subsequent quality traceability.

[0193] Here, those skilled in the art will understand that the specific operations of each step in the above-described production and processing control method for slicing and drying Chinese medicinal materials have been referenced above. Figure 1 and Figure 2 The description of the production and processing control method for slicing and drying Chinese medicinal materials is detailed here, and therefore, its repeated description will be omitted.

[0194] According to another aspect of the present invention, a production and processing control system for the slicing and drying process of Chinese medicinal materials is provided, comprising:

[0195] The thickness grading module is used to obtain the slice thickness distribution sequence at the slicer outlet, divide the slice sequence into multiple thickness segments according to the thickness gradient, calculate the water permeation resistance coefficient of the slices in each thickness segment, and generate a correlation mapping table between thickness and water migration characteristics.

[0196] The energy allocation module is used to calculate the cumulative heat required for slices of different thicknesses to reach the target moisture content based on the moisture penetration resistance coefficient of each thickness segment in the association mapping table, and to construct the drying energy demand spectrum with thickness difference compensation.

[0197] The temperature control module is used to dynamically adjust the segmented temperature curves of the drying equipment and the duration of each temperature segment based on the difference in heat accumulation values ​​of each thickness segment in the drying energy demand spectrum, so that the moisture migration rate of slices of different thicknesses tends to be consistent.

[0198] The feedback correction module is used to monitor the surface temperature and center temperature gradient of slices of different thicknesses in the drying chamber in real time. When the center temperature gradient deviates from the preset synchronization range, it provides feedback to correct the step amplitude of the segmented temperature curve and outputs adaptively controlled drying process parameters.

[0199] In summary, the production and processing control method for slicing and drying Chinese medicinal materials based on embodiments of the present invention has been clarified. It obtains the slice thickness distribution sequence at the slicer's outlet, divides the slices into sections based on the thickness gradient, and establishes a mapping table relating thickness to moisture migration characteristics. This enables precise statistical analysis of the moisture penetration resistance coefficient of slices with different thicknesses. Furthermore, by real-time monitoring of the temperature gradient between the slice surface and center, and feedback correction of temperature curve parameters, adaptive control of the drying process for slices with different thicknesses is achieved. This not only significantly improves the drying uniformity and final moisture content consistency of the Chinese medicinal material slices but also effectively prevents the loss of medicinal components or localized carbonization caused by uneven thickness, thereby comprehensively improving the quality stability and process intelligence level of the finished medicinal materials.

Claims

1. A production and processing control method for slicing and drying Chinese medicinal materials, characterized in that, include: Obtain the slice thickness distribution sequence at the slicer outlet, divide the slice sequence into multiple thickness segments according to the thickness gradient, calculate the water permeation resistance coefficient of the slices in each thickness segment, and generate a correlation mapping table between thickness and water migration characteristics. Based on the moisture penetration resistance coefficient of each thickness segment in the aforementioned correlation mapping table, the cumulative heat required for slices of different thicknesses to reach the target moisture content is calculated, and a drying energy demand spectrum with thickness difference compensation is constructed. Based on the differences in heat accumulation values ​​of each thickness segment in the drying energy demand spectrum, the segmented temperature curves of the drying equipment and the duration of each temperature segment are dynamically adjusted to make the moisture migration rate of slices of different thicknesses tend to be consistent. The surface temperature and center temperature gradient of slices of different thicknesses in the drying chamber are monitored in real time. When the center temperature gradient deviates from the preset synchronization range, the step amplitude of the segmented temperature curve is corrected by feedback, and the drying process parameters are output for adaptive control.

2. The production and processing control method for slicing and drying Chinese medicinal materials according to claim 1, characterized in that, The calculation of the water permeability resistance coefficient includes: A radial distribution model of the water concentration field inside the slice is established, and the governing equation of the radial distribution model is expressed as: in, This represents the water concentration inside the slice. Drying time, The coordinates are in the thickness direction, with the center of the slice thickness as the origin. The local moisture diffusion coefficient varies with thickness, location, and time. The local moisture diffusion coefficient Using a function that varies with thickness, location, and time, the formula is expressed as: in, The effective diffusion coefficient of the core layer, The effective diffusion coefficient of the surface layer. As the core-edge transition point, For the thickness of the transition layer, To maintain the long-term diffusion coefficient ratio, The characteristic time of structural relaxation; The governing equations are solved numerically to calculate the water migration time constant required for the average moisture content of each thickness section to decrease from the initial value to the target moisture content. The water permeability resistance coefficient is defined as the ratio of the square of the thickness representative value to the equivalent water diffusion coefficient.

3. The production and processing control method for slicing and drying Chinese medicinal materials according to claim 2, characterized in that, The calculation of the cumulative heat value includes: Establish the energy conservation equation: in, This refers to the slicing temperature; The convective heat transfer coefficient is... The surface area of ​​the slice participating in convective heat transfer. The temperature of the hot air used for drying the medium; The latent heat of vaporization of water, This represents the rate of water evaporation. Record the instantaneous heating intensity requirement at each time step: The instantaneous heat supply intensity demand is numerically integrated over the entire time interval from the start of drying to reaching the target moisture content to obtain the total heat demand of each thickness segment, i.e., the cumulative heat value.

4. The production and processing control method for slicing and drying Chinese medicinal materials according to claim 3, characterized in that, The construction of the drying energy demand spectrum includes: The time axis of the drying process is divided into multiple continuous time windows, and the average heat intensity requirement of each thickness section within the window is calculated for each time window. Introducing a moisture content deviation correction factor The moisture content deviation correction factor is close to 1 in the early stage of drying, gradually decreases as the drying process progresses, and becomes zero when the slices reach the target moisture content; wherein, The average moisture content, For the target moisture content, This represents the initial moisture content. Calculate the overall heating weight and normalize it to obtain the heating intensity allocation ratio; By combining the total heating power of each time window with the heating intensity distribution ratio of each thickness section, a drying energy demand spectrum is generated with the time window as the horizontal axis and the heating power demand of each thickness section as the vertical axis.

5. The production and processing control method for slicing and drying Chinese medicinal materials according to claim 4, characterized in that, The calculation formulas for the effective diffusion coefficient of the core layer and the effective diffusion coefficient of the surface layer are as follows: in, The baseline moisture diffusion coefficient, Fiber density is a structural parameter in tissue organization. The fiber density influence coefficient. For surface roughness parameters in slice geometry data, This is the surface roughness influence coefficient.

6. The production and processing control method for slicing and drying Chinese medicinal materials according to claim 5, characterized in that, The temperature setpoint for the temperature range is determined in the following way: Calculate the total heating power of the time window corresponding to each temperature range. The total heating power of the window is the sum of the average heating intensity requirements of all thickness sections within the window; Based on the total heating power of the window and the convective heat transfer model, the hot air temperature setpoint and hot air velocity setpoint are calculated using the following formula: in, This represents the total surface area of ​​the batch slices. For window The mass-weighted average of the slice temperature in each thickness section within the slice. For the first Hot air temperature setting for each time window For the first Hot air flow rate setting value for each time window; The hot air temperature setpoint and hot air velocity setpoint are solved by an estimation-correction iterative strategy. The positive verification is performed by a coupled model of the moisture diffusion equation and the energy conservation equation. The iteration continues until the temperature deviation and power deviation both meet the convergence conditions.

7. The production and processing control method for slicing and drying Chinese medicinal materials according to claim 6, characterized in that, The division of the thickness range includes: The range of the slice thickness distribution sequence is calculated and divided by the preset number of thickness segments to obtain the thickness grading step size. Starting from the minimum value of the thickness distribution, the thickness grading step size is incremented upwards to establish a thickness segment boundary value sequence. If the number of slices in a certain thickness segment is less than the preset minimum sample size, the thickness segment is merged with the adjacent thickness segments. The representative thickness value after merging is recalculated based on the weighted average of the thickness measurements of all slices in the merged segment, with the weighting factor being the proportion of each slice in the batch.

8. A production and processing control system for slicing and drying Chinese medicinal materials, characterized in that, include: The thickness grading module is used to obtain the slice thickness distribution sequence at the slicer outlet, divide the slice sequence into multiple thickness segments according to the thickness gradient, calculate the water permeation resistance coefficient of the slices in each thickness segment, and generate a correlation mapping table between thickness and water migration characteristics. The energy allocation module is used to calculate the cumulative heat required for slices of different thicknesses to reach the target moisture content based on the moisture penetration resistance coefficient of each thickness segment in the association mapping table, and to construct the drying energy demand spectrum with thickness difference compensation. The temperature control module is used to dynamically adjust the segmented temperature curves of the drying equipment and the duration of each temperature segment based on the difference in heat accumulation values ​​of each thickness segment in the drying energy demand spectrum, so that the moisture migration rate of slices of different thicknesses tends to be consistent. The feedback correction module is used to monitor the surface temperature and center temperature gradient of slices of different thicknesses in the drying chamber in real time. When the center temperature gradient deviates from the preset synchronization range, it provides feedback to correct the step amplitude of the segmented temperature curve and outputs adaptively controlled drying process parameters.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the production and processing control method for the slicing and drying process of Chinese medicinal materials as described in any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the steps of the production and processing control method for the slicing and drying process of Chinese medicinal materials as described in any one of claims 1 to 7.

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