Traditional Chinese medicine low-temperature belt drying control system and control method

Abstract

The present application relates to the technical field of automatic control of traditional Chinese medicine drying process, and discloses a low-temperature belt drying control system and control method for traditional Chinese medicine. A closed-loop control strategy is proposed, which integrates multi-point moisture sampling, trend analysis, target and fluctuation control, temperature feedforward, belt speed feedback, vacuum coordination, stability criterion freezing and tail detection and archiving. By arranging multiple sampling points along the conveyor belt and monitoring moisture in real time, combined with time series difference analysis, not only static water content deviation is captured, but also drying rate and trend are dynamically perceived, realizing multi-channel coordinated adjustment of temperature, belt speed and vacuum. The system sets safety boundaries and minimum resolution to ensure that the control operation is executable and accurate. The stability interval criterion effectively avoids frequent invalid adjustment, and the multi-point detection at the tail and the whole process data archiving provide a solid basis for quality traceability.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of automatic control of traditional Chinese medicine drying process, in particular to a low-temperature belt drying control system and method for traditional Chinese medicine. BACKGROUND

[0002] Traditional Chinese medicinal materials and their tonifying preparations are highly sensitive to temperature, vacuum degree and time during the drying process. Slight improper operation may cause loss of volatile components, degradation of polysaccharide / saponin activity or excessive residual moisture, which may lead to mold growth and storage risk. Low-temperature belt drying equipment has become one of the main drying methods for valuable traditional Chinese medicines due to its continuous operation, strong controllability and gentle heating of materials. The equipment usually operates under vacuum conditions. Wet materials are evenly distributed on the conveying belt by the material distribution device. The materials move along with the belt and obtain heat through conduction and radiation between the heating plate and the conveying belt. The internal moisture of the materials is evaporated and removed by the vacuum pump. When the materials reach the discharge end, the cutting device removes them, and the finished products are obtained after crushing. This process involves heat transfer, mass transfer and phase equilibrium changes, and is a typical complex process industrial control object with multiple variables, strong coupling, nonlinearity and time delay.

[0003] Existing production practices generally rely on empirical setting or conventional modular combined control (such as fixed temperature rising curve combined with segmented setting of belt speed and vacuum degree), and some use proportional-integral-derivative adjustment, fuzzy rules or predictive control based on mechanism / experience model. However, for the quality target of valuable traditional Chinese medicines that the average final moisture content and the within-batch standard deviation are simultaneously constrained, these methods still have common bottlenecks: first, hysteresis. Online measurement of moisture content usually relies on infrared or near-infrared methods. The signal needs to be sampled and estimated to reflect the real moisture change, resulting in a lag in the response of the adjustment action to the trend, which is prone to overshoot or under-drying. Second, coupling difficulty. The heating plate temperature, conveying belt speed and vacuum pumping volume flow rate all affect the evaporation driving force and residence time, and traditional single-loop or weakly coupled strategies cannot balance the average moisture content and spatial uniformity. Third, parameter dependence on experience. A large number of methods require manual tuning of gains, weights and safety factors, which have poor parameter portability, insufficient batch consistency, and difficulty in forming deterministic traceable basis. Fourth, spatial non-uniformity. The thickness of the material, the difference in heat exchange at the edge and the local accumulation can cause the moisture content on the belt surface to be dispersed, and the conventional adjustment driven by the "global mean error" cannot directly suppress the standard deviation, resulting in excessive fluctuations in the final inspection. Fifth, boundary and implementability. Under strict equipment constraints (temperature, belt speed, vacuum upper and lower limits and minimum step), control laws containing indeterminate weights or requiring complex model support will increase the implementation difficulty and verification cost.

[0004] To this end, the case aims to propose a traditional Chinese medicine low-temperature belt drying control system and control method, forms a sampling network along the conveying belt to continuously obtain the speed and trend information of the moisture content of the material, and decides the coordinated regulation of the feedforward of the heating temperature, the feedback of the belt speed and the vacuum exhaust in the same control cycle; when the average moisture content and the spatial fluctuation enter the stable interval at the same time, the control amount is frozen, the final independent detection point is set at the tail end before discharging to perform "all-point standard" judgment, and the whole process parameters and results are archived. SUMMARY

[0005] The application provides a traditional Chinese medicine low-temperature belt drying control system and control method, which promotes the solution to the problems mentioned in the background art.

[0006] The application provides the following technical scheme: a traditional Chinese medicine low-temperature belt drying control method, comprising:

[0007] S1, a plurality of moisture sampling points are arranged on the conveying belt of the belt drying device in the conveying direction, each sampling point is uniquely numbered, a moisture detection unit is configured and a fixed sampling period is set, initial moisture content data is recorded, and an allowed setting range and a minimum adjustment resolution of temperature, conveying belt speed and vacuum exhaust volume flow are established;

[0008] S2, based on the continuous sampling sequence, the first-order and second-order time series difference of the moisture content with time is calculated to obtain the local trend of each sampling point and the average trend of the whole field, and the effective interval and boundary condition of the trend calculation are set;

[0009] S3, the drying target moisture content and the allowed fluctuation index are determined, the current average moisture content and spatial dispersion of the whole field are obtained according to the sampling period;

[0010] S4, under the conditions of a preset temperature reference and a step length, the temperature feedforward increment is obtained according to the trend estimation result, the heating plate temperature set value is updated, and the upper and lower boundary projections are applied to the updated result;

[0011] S5, according to the deviation of the current moisture content and the target and the available speed dynamic range, the feedback adjustment amount of the conveying belt speed is calculated, the belt speed set value is updated and the upper and lower boundary projections are executed;

[0012] S6, in the moving time window, the coordinated adjustment amount of the vacuum exhaust volume flow is obtained by referring to the evaporation rate representation, the vacuum set value is updated and the upper and lower boundary projections are executed;

[0013] S7, when the average moisture content approaches the target and the spatial fluctuation is within the threshold value and remains stable in the continuous period, it is determined that the control state is stable, and the set values of the heating plate temperature, the conveying belt speed and the exhaust volume flow are frozen;

[0014] S8, setting detection points at the tail of the conveying belt, detecting the moisture content of each point, and determining that the drying is completed and triggering the cutting when all the points meet the preset completion condition, and archiving the drying cycle, moisture content distribution, and the whole process record of each control parameter.

[0015] Optionally, the plurality of moisture sampling points are arranged along the conveying direction of the conveying belt of the belt drying device, each sampling point is uniquely numbered, a moisture detection unit is configured and a fixed sampling period is set, initial moisture content data is recorded, and an allowed setting range and a minimum adjustment resolution of temperature, conveying belt speed, and vacuum air volume flow are established, specifically including:

[0016] The length and width of the belt conveying system of the drying machine are obtained, denoted as L belt and W belt , respectively;

[0017] The wet material is uniformly distributed on the conveying belt using a distributing device;

[0018] The moisture sampling points are arranged at equal intervals Δx moist along the length direction of the conveying belt, numbered as j m ; wherein Δx moist is the interval of adjacent moisture sampling points along the length direction of the belt; j m ∈{1,...,N m} is the serial number of the moisture sampling point; N m is the total number of moisture sampling points,

[0019] An infrared moisture detection unit is installed at each number j m , the sampling period is set as Δt moist , and the moisture content is recorded as wherein Δt moist is the moisture sensing sampling period; is the moisture content at the j m th sampling point at time t k ; t k is the kth discrete sampling time; k is the discrete time index;

[0020] Each sampling is bounded:

[0021] The discrete time index t k = t0+k·Δt moist is calculated; wherein t0 is the system start time;

[0022] All initial moisture data

[0023] The minimum resolution of the sensor is obtained, denoted as r H ;

[0024] The minimum resolution for temperature control is denoted as r. T ;

[0025] The minimum resolution for obtaining the vacuum pumping volumetric flow rate is denoted as r. P ;

[0026] Set the lower and upper temperature limits of the heating plate to T respectively. min and T max ;

[0027] Set the lower and upper limits of the conveyor belt speed as v. min and v max ;

[0028] Set the lower and upper limits of the vacuum pumping volumetric flow rate to P respectively. min and P max .

[0029] Optionally, based on the continuous sampling sequence, the first and second time-series differences of moisture content over time are calculated to obtain the local trend of each sampling point and the average trend of the entire field, and the effective interval and boundary conditions for trend calculation are set, specifically including:

[0030] Construct the first-order time difference function for water content: in, For the jth m Point at time t k The first-order time difference of water content;

[0031] When k=0, set

[0032] Constructing the backward second-order time difference function in, For the j-th m Point at time t k The second-order time difference of water content;

[0033] When k = 0 or 1, set

[0034] Calculate time t k The second difference of the whole game average

[0035] Set the positive lower bound for second-order difference calculation as

[0036] Optionally, determining the target moisture content and allowable fluctuation index for drying, and obtaining the current average moisture content and spatial dispersion of the entire field according to the sampling period, specifically includes:

[0037] The target moisture content of dried Chinese medicinal herbs is obtained and denoted as H.target ;

[0038] Set the moisture content allowable standard deviation as σ max = 2%;

[0039] Calculate the full-field average moisture content at time t k

[0040] Calculate the spatial standard deviation at time t k

[0041] Optionally, the temperature feedforward increment is obtained according to the trend estimation result under the preset temperature reference and step size condition, the heating plate temperature set value is updated, and the upper and lower boundary projections are applied to the updated result, specifically including:

[0042] Set the temperature control reference temperature as T

[0043] Set the temperature adjustment step size ΔT step = r T ;

[0044] Let the reference evaporation acceleration reference be a ref :

[0045]

[0046] Bind the initial temperature as T plate (t0) = T base ;

[0047] Construct a feedforward temperature adjustment function: Wherein, T add (t k ) is the temperature feedforward increment at time t k ;

[0048] Update the heating plate temperature in real time: T plate (t k+1 ) = T plate (t k ) + T add (t k ); wherein, T plate (t k ) is the heating plate temperature set at time t k ;

[0049] Implement boundary projection T plate (t k+1 ) <- min(max(T plate (t k+1 ), T min ), T max ).​​

[0050] Optionally, the feedback adjustment amount of the conveying belt speed is calculated according to the deviation of the current moisture content from the target and the available speed dynamic range, the belt speed set value is updated, and upper and lower limit projection is performed, specifically including:

[0051] Setting the initial reference speed of the conveying belt

[0052] Obtaining the moisture error scale

[0053] Obtaining the available dynamic range v of the belt speed span = v max -v min ;

[0054] Obtaining the feedback adjustment coefficient of the belt speed

[0055] Setting the time t k of the moisture content deviation

[0056] Binding the initial belt speed to v belt (t0) = v base ; wherein v belt (t k ) is the belt speed set at time t k ;

[0057] Constructing the feedback speed regulation function: v belt (t k+1 ) = v base - κ v · e H (t k );

[0058] Implementing limit projection: v belt (t k+1 )←min(max(v belt (t k+1 ),v min ),v max ).

[0059] Optionally, the coordinated adjustment amount of the vacuum air extraction volume flow is obtained by referring to the evaporation rate representation within the moving time window, the vacuum set value is updated, and upper and lower limit projection is performed, specifically including:

[0060] For k≥1, the first-order derivative average of moisture is calculated: wherein is the first-order difference full-field average at time t k ;

[0061] When k=0, let

[0062] Set the reference vacuum pumping volume flow rate

[0063] Set the vacuum pumping volume flow rate adjustment step size ΔP = r P ;

[0064] Set the reference window length K0 = 3;

[0065] Calculate the reference evaporation rate reference Where k' is the temporary time index for calculating r ref ;

[0066] And bind the initial value P vac (t0) = P base ;

[0067] Construct the pumping adjustment function: Where P add (t k ) is the vacuum pumping volume flow rate increment at time t k ;

[0068] The vacuum pumping volume flow rate is updated to: P vac (t k+1 ) = P vac (t k ) + P add (t k ); Where P vac (t k ) is the vacuum pumping volume flow rate setting at time t k ;

[0069] Implement the limit projection: P vac (t k+1 ) <- min(max(P vac (t k+1 ), P min ), P max ).

[0070] Optionally, when the average moisture content approaches the target and the spatial fluctuations are within the threshold and remain stable within a continuous period, it is determined that the control state is stable, and the setting values of the heating plate temperature, the conveying belt speed, and the vacuum pumping volume flow rate are frozen, specifically including:

[0071] Set the allowable threshold value of moisture error ∈ H = r H ;

[0072] If |e H (t k )| < ∈ H and σ H (tk )<σ max If the control is stable, the control parameters will be frozen.

[0073] T plate (t k+1 ) = T plate (t k ), v belt (t k+1 ) = v belt (t k ), P vac (t k+1 ) = P vac (t k );

[0074] If |e H (t k )|≥∈ H or σ H (t k )≥σ max If the control parameters are not frozen, the calculation and update of steps S2 to S6 will continue.

[0075] Optionally, the step of setting detection points at the tail of the conveyor belt to detect the moisture content at each point, and determining that drying is complete and triggering cutting when all preset completion conditions are met, while simultaneously archiving the entire drying cycle, moisture content distribution, and records of various control parameters, specifically including:

[0076] N is installed at the tail of the conveyor belt tail There are one detection point, numbered j. tail ; where N tail Let N be the total number of tail detection points, and 1 ≤ N. tail ≤N m ;j tail ∈{N m -N tail +1,...,N m} represents the serial number of the tail detection point;

[0077] When all tail points satisfy Then, drying is considered complete, and the cutting mechanism is activated; among which, For the jth tail tail Point at time t k Moisture content;

[0078] Get the minimum time index k for the first time to satisfy the tail full point achievement criteria. end :

[0079]

[0080] Obtain the actual time of completion judgment

[0081] The following data are recorded and archived:

[0082] Total drying cycle time T dry = t end -t0; final moisture distribution Control parameter full pass sequence Wherein, K end is a discrete completion index,

[0083] If any j tail does not satisfy Then continue to perform the calculation and update of steps S2 to S6 until all j tail satisfy In the cutting material archive.

[0084] A system for implementing the traditional Chinese medicine low-temperature belt drying control method, comprising:

[0085] A conveying belt assembly for carrying traditional Chinese medicine materials and moving along the belt conveying system;

[0086] A plurality of infrared moisture detection units are arranged on the surface of the conveying belt for real-time collection of moisture content at each sampling point;

[0087] A heating plate assembly is installed below the conveying belt for providing controllable heat source to the material;

[0088] A vacuum air extraction module is in communication with the drying chamber for providing adjustable vacuum air volume flow rate;

[0089] A running drive module is used to control the running speed of the conveying belt.

[0090] The present application has the following beneficial effects:

[0091] 1. By arranging a plurality of moisture sampling points at equal intervals along the full length of the conveying belt and uniquely numbering each sampling point, the entire material spreading area is fully covered and high-resolution monitoring is achieved. Through automatic collection and normalization processing, the data reliability and representativeness are improved. Unlike the existing technology which mainly uses single-point or manual sampling, the present scheme realizes multi-point simultaneous online detection and intelligent numbering management, which improves the spatial distribution information and data quality. This not only improves the monitoring accuracy of the material drying process and timely detects and corrects local dry or wet phenomena, but also provides a solid data foundation for subsequent trend analysis and dynamic adjustment, effectively solving the problems of control lag and large batch-to-batch fluctuations caused by sparse measurement points in traditional processes.

[0092] 2、The application introduces first-order and second-order time difference analysis in the data processing of the drying process, dynamically captures the rate of moisture change and its acceleration trend. Unlike traditional methods that rely only on end-point detection or average moisture criteria, this method can timely discover the change inflection point of the dehydration rate through real-time calculation of local trends and global average trends, providing early warning and quantitative basis for subsequent temperature, speed and other adjustments. By setting the effective interval and boundary conditions for trend calculation, the interference of abnormal values is effectively suppressed. This technical means not only enhances the forward-looking and anti-interference ability of the control algorithm, but also improves the fine-tuning level of the regulation, breaking through the existing process quality instability problem caused by adjustment lag and lack of dynamic trend analysis.

[0093] 3、The target moisture content and spatial standard deviation are used as double criteria for the drying process, emphasizing both the compliance rate of the end point and the strict control of spatial uniformity. The system automatically calculates the average moisture content and standard deviation of the whole field, and uses them as inputs for the feedback loop, achieving precise control and batch consistency. Compared with traditional methods that only use average values or empirical judgments to determine the drying end point, this scheme effectively prevents local drying unevenness or local under-drying by setting fluctuation thresholds. This provides data support for the production of high-value, composition-sensitive traditional Chinese medicinal materials, effectively improving product consistency and safety, and helping the industry move towards standardized and traceable production mode.

[0094] 4、Unlike traditional passive feedback or manual temperature adjustment, the application proposes a temperature feedforward adjustment mechanism based on moisture change trend. The system predicts future moisture content changes based on real-time second-order difference results, actively adjusts the heating temperature, and prevents temperature over-limiting through upper and lower boundary projection. This mechanism reduces the impact of feedback lag, making temperature adjustment more intelligent and efficient. Compared with existing technologies that mainly rely on fixed programs or single-point error feedback, feedforward adjustment can suppress mutations and fluctuations in the drying process in advance, ensuring that the composition of medicinal materials is not damaged by high temperature, and avoiding energy waste. It is a key innovation to improve drying flexibility and efficiency.

[0095] 5、The application uses the deviation between the target moisture content and the real-time measured moisture content to dynamically calculate and adjust the conveying belt speed, achieving fine control of the residence time of the material in the heating zone. Compared with traditional methods that use fixed belt speed or manual periodic adjustment, automatic feedback adjustment can flexibly adapt to actual fluctuations in raw material moisture, material thickness and other factors, improving the adaptability of the drying process and the stability of the production line. This mechanism helps to prevent over-drying or local under-drying caused by improper belt speed, while also improving the utilization rate of production capacity, providing support for continuous industrial production.

[0096] 6. The proposed solution uses the vacuum pumping volumetric flow rate as an independent and dynamically adjustable third control variable. The pumping intensity is adjusted synchronously based on changes in evaporation rate and moisture content, constructing a ternary control system that couples heat and mass transfer. Unlike traditional methods that rely solely on heating or belt speed adjustment, this synergistic vacuum adjustment better controls cavity humidity and pressure, improving drying uniformity and process response speed. This method reduces re-humidification and condensation caused by insufficient pumping, and surface cracking and dust escape from medicinal materials caused by excessive pumping, effectively extending equipment life and ensuring the integrity and safety of medicinal material quality.

[0097] 7. This invention innovatively proposes a "dual threshold" criterion (achieving both average moisture content and spatial standard deviation) as the basis for control stability and introduces a control parameter freezing mechanism. Once the system reaches the set stable range, the heating temperature, belt speed, and vacuum settings are actively frozen to prevent mechanical wear and control fluctuations caused by frequent adjustments. This strategy reduces unnecessary changes in equipment operation, improves production cycle time and product consistency, and is an effective measure to ensure process stability and equipment lifespan. In stark contrast to previous processes involving continuous adjustments and frequent fluctuations, this demonstrates a higher level of automation and intelligent management capabilities.

[0098] 8. The solution establishes multiple inspection points at the tail end of the conveyor belt, using "full compliance at the tail end" as the drying endpoint criterion, and archives and saves all key parameters throughout the drying cycle. This ensures the consistency of moisture content across batches of finished products and provides detailed data for subsequent quality traceability and process optimization. Compared to traditional methods relying primarily on surface inspection or random sampling, this method achieves full-process data-driven management, a core element in promoting the intelligent and standardized production of traditional Chinese medicine drying, and effectively improves product quality assurance and production management levels. Attached Figure Description

[0099] Figure 1 This is a schematic diagram of the process of the present invention. Detailed Implementation

[0100] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0101] Example, refer to Figure 1 A method for controlling low-temperature belt drying of traditional Chinese medicine, comprising:

[0102] S1, multiple moisture sampling points are arranged on the conveying belt of the belt drying device along the conveying direction, each sampling point is uniquely numbered, a moisture detection unit is configured and a fixed sampling period is set, initial moisture content data is recorded, and an allowed setting range and a minimum adjustment resolution of temperature, conveying belt speed, and vacuum air volume flow are established;

[0103] S2, based on the continuous sampling sequence, a first-order and second-order time series difference of the moisture content with time is calculated to obtain a local trend of each sampling point and an average trend of the whole field, and an effective interval and boundary conditions of the trend calculation are set;

[0104] S3, the drying target moisture content and the allowed fluctuation index are determined, and the current average moisture content and spatial dispersion of the whole field are obtained according to the sampling period;

[0105] S4, under the condition of a preset temperature reference and a step length, a temperature feed increment is obtained according to the trend estimation result, the heating plate temperature set value is updated, and the upper and lower boundary projections are applied to the updated result;

[0106] S5, according to the deviation of the current moisture content and the target and the available speed dynamic range, the feedback adjustment amount of the conveying belt speed is calculated, the belt speed set value is updated, and the upper and lower boundary projections are executed;

[0107] S6, in the moving time window, the cooperative adjustment amount of the vacuum air volume flow is obtained by referring to the evaporation rate representation, the vacuum set value is updated, and the upper and lower boundary projections are executed;

[0108] S7, when the average moisture content approaches the target and the spatial fluctuation is within the threshold and remains stable within a continuous period, it is determined that the control state is stable, and the set values of the heating plate temperature, the conveying belt speed and the vacuum air volume flow are frozen;

[0109] S8, a detection point is arranged at the tail of the conveying belt, the moisture content of each point is detected, and when all the points meet the preset completion condition, it is determined that the drying is completed and the cutting is triggered, and the drying period, the moisture content distribution and the whole process record of each control parameter are archived.

[0110] A low-temperature belt drying control method for traditional Chinese medicine is proposed, which integrates eight steps of multi-point moisture sampling, time series trend analysis, target and fluctuation control, temperature feedforward, belt speed feedback, vacuum coordination regulation, stability criterion freezing, and tail detection and whole-process archiving. The sensing, analysis and multi-variable coordinated control are organically integrated into a closed-loop process, changing the previous reliance on manual experience to set a single temperature or time, adjusting the reaction lag, large batch fluctuation, and the quality cannot be traced. By numbering, collecting and recording real-time moisture data at multiple points along the belt conveying direction, the spatial distribution state is clear at a glance, reducing the risk that local abnormalities cannot be discovered in time. The introduction of trend function enables the system not only to perceive static deviation, but also to dynamically control the acceleration and deceleration of the drying process, thereby realizing advance compensation. The multi-channel control means of advance adjustment of temperature, feedback correction of belt speed and synchronization of vacuum rate enable the coupling of energy input, material residence and quality transfer, improving drying efficiency and uniformity. The stable freezing strategy reduces the frequent invalid adjustment of the standard interval, avoiding over-regulation or fluctuation caused by system inertia. The tail multi-point detection and data archiving provide a solid basis for product quality evaluation and process traceability. Overall, this scheme replaces the traditional process of manual decision and single-point sampling with whole-process digitization and intelligentization, not only improving the batch consistency, but also reducing energy consumption, rehydration and overdrying risk.

[0111] The method comprises the following steps: a plurality of moisture sampling points are arranged along the conveying direction of the conveying belt of the belt drying device, each sampling point is uniquely numbered, a moisture detection unit is configured and a fixed sampling period is set, initial moisture content data are recorded, and an allowed setting range and a minimum adjustment resolution of temperature, conveying belt speed and vacuum pumping volume flow are established, specifically comprising:

[0112] The length and width of the belt conveying system of the drying machine are obtained, denoted as L belt and W belt respectively; the geometric dimensions of the conveying belt are determined, providing boundary conditions and geometric references for subsequent determination of the number, spacing and material residence time of the sampling points, ensuring that the material and sampling cover the entire heating area;

[0113] The wet material is uniformly distributed on the conveying belt by using a material distribution device;

[0114] Moisture sampling points are arranged at equal intervals Δx moist along the length direction of the conveying belt, numbered as j m ; wherein Δx moist is the spacing of adjacent moisture sampling points along the length direction of the belt; j m ∈{1,...,N m} is the serial number of the moisture sampling point; N m is the total number of moisture sampling points, Determine the "point density" in a computable way, which ensures spatial resolution and controls sensing cost; through N m integerization, ensure that the field point can be implemented and strictly match the tape length;

[0115] Install an infrared moisture detection unit at each number j m The sampling period is set to Δt moist , and the moisture content is recorded as Where Δt moist is the moisture sensing sampling period; is the moisture content at time t k at the j m th sampling point; t k is the kth discrete sampling time; k is the discrete time index;

[0116] Each sampling implementation is bounded: Form a consistent discrete data stream, and use [0, 100] clamping to eliminate out-of-bound and bad points, improve data reliability, and provide a unified sampling reference for subsequent difference calculation;

[0117] Calculate the discrete time index t k = t0+k·Δt moist ; Where t0 is the system startup time;

[0118] Record all initial moisture data at the initial time t0

[0119] Get the minimum resolution of the sensor, denoted as r H ;

[0120] Get the minimum resolution of temperature control, denoted as r T ;

[0121] Get the minimum resolution of the vacuum air volume flow, denoted as r P ;

[0122] Set the lower and upper limits of the heating plate temperature to T min and T max ;

[0123] The upper and lower limits constitute a "safety fence" for the temperature channel. On the one hand, it provides an anchor point for the midpoint initialization of the temperature feedforward channel, so that the system is located in the middle of the controlled interval at startup, reducing excessive temperature rise or insufficient heating in the starting stage; on the other hand, it restricts the set value after each temperature update, ensuring that the feedforward increment does not exceed the medicinal material tolerance range and equipment limits, thereby avoiding risks such as effective component thermal degradation, surface hardening, or seal overheating, while also avoiding insufficient evaporation driving force due to excessively low temperature, resulting in abnormally long drying time. The fence also helps audit the control trajectory: even if there is an abnormal data point, the projection can forcibly pull the temperature back into the permitted interval. If the upper limit is too high, it is easy to touch the thermal stability threshold of sensitive medicinal materials during feedforward adjustment, causing the loss of aroma components or color deterioration; if the lower limit is too low, it will significantly weaken the evaporation in the early stage, leading to a larger moisture distribution on the belt, requiring more intense vacuum and belt speed adjustments, and increasing overall fluctuations. If the distance between the upper and lower limits is too narrow, the control action is frequent and the upper limit is reached, and the feedforward benefit is weakened, the system behaves as "passive edge running"; if the distance is too wide, although it is flexible, it is easy to induce unnecessary large thermal shock, and the consistency of the finished product batch decreases. The thermal sensitivity of medicinal materials (such as the stable temperature range of volatile oil, steroidal saponin, and polysaccharide), the low-temperature positioning of the target process, the temperature resistance level of the conveyor belt and sealing material, the uniformity of the heating plate temperature field, and the "highest available temperature without visible quality deterioration" and "the lowest effective temperature that can maintain stable evaporation" determined by small-scale testing should be considered. Also, the long-term running upper limit of the equipment manufacturer, the temperature control resolution, and the overall effect after coupling with vacuum and belt speed should be considered. First, determine the temperature point at which "quality deterioration occurs" through small-scale sample testing, and set the upper limit to a safe margin below this point in industrialization; then find the "lowest temperature that can maintain stable evaporation under the set vacuum and moderate belt speed" and use it as the lower limit; maintain a sufficient adjustable window between the two to allow the feedforward to function. For extremely sensitive varieties, the upper limit is recommended to be more conservative, and the lower limit is moderately raised and compensated by the vacuum channel for driving force; for heat-resistant root materials, the window can be widened to exchange for rhythm and energy efficiency.

[0124] The lower and upper limits of the belt speed are set as v min and v max , respectively.

[0125] The upper and lower limits define the shortest and longest residence time boundaries of the material in the drying zone, and are hard constraints for the feedback loop to map the average moisture content deviation to "time correction". On one hand, it provides the speed midpoint as the starting speed, reducing the risk of starting pile or under-drying; on the other hand, it limits the result of each speed update, avoiding over-drying caused by too slow belt speed due to instantaneous large error, or not reaching the target moisture content before discharging due to too fast speed, thus directly protecting the finished product to meet the standard and stabilizing the production line rhythm. If the upper limit is too high, the material residence time will be too short, and the end detection point will often not meet the standard, and the standard deviation will rise; if the lower limit is too low, the material will stay too long at high temperature, and the probability of local over-drying, hard shell and dark color will rise, and it may cause upstream accumulation, affecting continuity. If the speed window is too narrow, the feedback adjustment space is insufficient, the system will frequently reach the limit, and the time to meet the standard will be lengthened; if the window is too wide, there will be large speed swings when the error is large, mechanical impact and energy consumption will rise, and the requirement for uniform distribution of the material will be higher. The length of the belt, the effective length of the heating area, the thickness of the single-layer material, the loading capacity per unit area, the target production capacity, and the stable speed range and minimum step of the mechanical system need to be considered. Based on the "shortest residence time that can meet the standard at the target temperature and vacuum" and "longest residence time that will not cause quality deterioration or production congestion" measured by small-scale or pilot tests, the wear resistance of the material and the risk of deviation of the guide system at low speed should also be considered. With "end full-point standard" as a hard constraint, first fix the temperature and vacuum at the midpoint, gradually increase the belt speed, find the highest speed that just meets the standard, and use it as the upper limit of the upper limit reference; then gradually reduce the belt speed and observe whether there are adverse signs such as color, aroma or brittleness and upstream congestion, and the lowest speed that does not appear abnormal is used as the lower limit. For conditions with large fluctuations in material thickness, it is recommended to narrow the speed window appropriately to reduce fluctuations; for production capacity priority conditions, the upper limit can be appropriately increased, but the coordination of tail-end monitoring and vacuum channel evacuation capacity needs to be strengthened simultaneously.

[0126] The lower and upper limits of the vacuum air extraction volume flow rate are set as P min and P max , respectively.

[0127] The upper and lower limits define the effective range of steam removal capacity, which is the third "handle" coupled with temperature and belt speed on the mass transfer side. It not only provides a steady-state basis for the midpoint extraction at startup, but also projects the setting after each update to prevent insufficient extraction causing water vapor retention and moisture regain in the cavity, and to avoid excessive extraction of fine powder, surface subcooling or unnecessary load on the sealing system. Reasonable upper and lower limits can also suppress pressure fluctuations and reduce drying rate fluctuations caused by vacuum fluctuations. If the upper limit is too high, the evaporative cooling effect will be too strong on the surface, the surface will dry quickly, the internal diffusion will be blocked, the convergence will slow down in the later stage, and there is a risk of bringing out fine powder, increasing the burden and wear of filtration. If the lower limit is too low, the water vapor will not be removed in time, the local saturation in the cavity will increase, and there will be moisture regain, condensation or high moisture at the end, and the standard deviation will expand. A narrow window will not have enough space for coordinated adjustment and frequent ceiling; a wide window may cause energy consumption and mechanical fatigue due to excessive extraction, and the cooperation with temperature feedforward will be worse. The nominal extraction speed, cavity volume and leakage level, condensation and dust removal unit capacity, powder entrainment threshold, product sensitivity and desired steady-state vacuum level should be considered. The end moisture distribution and moisture regain probability under different extraction intensities for typical batches, as well as the effect of extraction speed on temperature trajectory during startup, should also be considered. The minimum step of the device and the control response time will also affect the reasonable setting of the upper and lower limits. Under the conditions of fixed temperature and midpoint speed, gradually increase the extraction intensity, monitor the end moisture distribution, moisture regain signs and dust carry-out, find the threshold of "just appearing fine powder escape or obvious surface cold contraction", and set the upper limit below it with a safety margin; then gradually reduce the extraction, observe the condensation and end wetness, and set the interval above it as the lower limit; at the same time, consider the capacity of the filtration and condensation unit to leave a margin. For light and flaky or easily powdered medicinal materials, the upper limit should be more conservative and the dust removal or baffle should be strengthened; for thick layer of material or high initial moisture batch, the lower limit can be increased to avoid the increase of saturation in the cavity;

[0128] The initial state of solidification and the minimum adjustable particle size are clear safety boundaries, which ensure that the denominator of all subsequent formulas is positive and bounded, and avoid numerical singularities and device overruns.

[0129] By obtaining the length and width of the dryer belt conveying system, the number and spacing of sampling points are reasonably determined to ensure that the data collection covers the entire heating area and avoids quality problems caused by "blind areas" in certain areas. The material distribution device ensures uniform distribution of wet materials on the belt surface, reduces local accumulation or blank areas, and directly improves the uniformity of subsequent drying. All sampling points are equipped with infrared moisture detection units and strictly numbered, and a fixed sampling period ensures data consistency and traceability. At the same time, the sampling process is implemented with boundary and bad point control to improve the effectiveness and anti-interference ability of the collected data. The resolution of sensors, temperature control, vacuum pumps and all execution limits are preset to build the basis of hardware safety boundaries and adjustment sensitivity. These details work together to solve the problems of sparse sampling, arbitrary point distribution, parameter boundary uncertainty leading to control failure and unstable quality batches in existing technology. Through scientific data collection and parameter initialization, all subsequent adjustment steps have a unified engineering basis and quality assurance.

[0130] Based on the continuous sampling sequence, the first and second order time difference of moisture content with time is calculated to obtain the local trend of each sampling point and the average trend of the whole field, and the effective interval and boundary conditions of trend calculation are set, including:

[0131] The first order time difference function of moisture is constructed: Where, is the first order time difference of moisture at the j m th point at time t k ;

[0132] When k = 0, set

[0133] Provide "moisture change rate" observation for judging the speed of dehydration process, and provide rate reference for vacuum linkage and convergence criterion;

[0134] The backward second order time difference function is constructed Where, is the second order time difference of moisture at the j m th point at time t k ;

[0135] When k = 0 or 1, set

[0136] Capture the "curvature / acceleration" of the moisture curve to identify the acceleration or deceleration trend of the drying rate in advance, provide quantitative basis for feedforward heat increase or decrease, and reduce lag;

[0137] Calculate the second order difference average value of the whole field at time t k ​Smooth local noise and individual outliers into global trend as the only "global variable" of feedforward channel, to improve the robustness of the adjustment direction;

[0138] Set the lower bound of the second-order difference calculation as Provide a uniform lower bound for all denominators involving reference acceleration to avoid numerical instability; this lower bound is directly related to sensor resolution and sampling period, and is measurable and calculable.

[0139] Focus on moisture time series trend calculation based on continuous sampling sequence. Specifically, it includes constructing first-order and second-order time difference functions to extract the local dehydration speed and acceleration of each sampling point and capture the overall moisture change trend. This approach solves the problem of traditional single-point measurement or static moisture data feedback, which cannot determine the "fast and slow change" trend in the process, leading to lagging or excessive adjustment. By calculating the trend, the system can predict whether the drying process has entered a "bottleneck" or "overshoot", providing a quantitative basis for advance and coordinated adjustment of temperature, belt speed, and vacuum. The setting of trend interval and boundary conditions effectively filters measurement noise and extreme outliers, improving the robustness of overall adjustment. Compared with the drying control mode relying on experience or single data, this step not only improves the sensitivity and foresight of control, but also provides a data basis for subsequent adaptive adjustment and fault warning, which is conducive to reducing the misjudgment rate and improving the stability of the drying process.

[0140] The determination of the drying target moisture content and the allowable fluctuation index obtains the current full-field average moisture content and spatial dispersion according to the sampling period, specifically including:

[0141] Obtain the target moisture content of traditional Chinese medicine drying, denoted as H target ; as the center value of feedback error calculation and termination criterion, unify the product moisture target;

[0142] Set the allowable standard deviation of moisture content as σ max = 2%; set a hard constraint for spatial uniformity to ensure the consistency of valuable and nourishing traditional Chinese medicine within the batch;

[0143] Calculate the full-field average moisture content at time t k Provide the "system output" scalar of the feedback loop, directly compare with H target to generate error;

[0144] Calculate the spatial standard deviation at time t k Quantify the drying uniformity as a parallel threshold for freezing and release, to prevent local over-drying / residual moisture.

[0145] ​​A double criterion of drying target moisture content and allowable fluctuation index is proposed, and the full-field average moisture content and spatial standard deviation are calculated in real time through the sampling period. Through this double threshold mechanism, the shortcomings of traditional process only focusing on average moisture content and not paying attention to batch uniformity are solved. The standard deviation as a hard constraint of spatial uniformity makes the system not only pursue the overall standard when adjusting, but also prevent local over-drying or residual moisture. Under the joint action of the double indicators, the risk of batch difference and local unqualified can be effectively reduced, and the consistency of finished products can be improved. Real-time calculation of full-field mean and standard deviation provides quantitative basis for freezing strategy and tail-end criterion. Compared with the traditional scheme of judging the quality of finished products only by end-point sampling, this control method can detect local abnormalities in advance and adjust in time, reduce rework rate, and improve overall line efficiency and quality assurance capability.

[0146] The temperature feedforward increment is obtained according to the trend estimation result under the condition of preset temperature reference and step length, the heating plate temperature setting value is updated, and the upper and lower boundary projections are applied to the updated result, and the specific steps include:

[0147] Setting temperature control reference temperature

[0148] Setting temperature adjustment step length ΔT step = r T ;

[0149] The reference evaporation acceleration reference is denoted as a ref :

[0150] The smallest temperature step that can be distinguished by the device and the average second-order difference that can be measured in the start-up stage are used as the deterministic coefficient; when k<2, the "sample term" on the right side of the above formula is not available, and ε a is provided to ensure that the calculation is available. Further, when k<2, let a ref = ε a ; when k≥2 and a ref is calculated according to the above formula, it is regarded as a constant and fixed in subsequent calculation, and does not change with k;

[0151] The initial temperature is bound as T plate (t0) = T base ;

[0152] The thermal level is initialized at the midpoint of the safety range, and the reference scale is defined by the minimum step of the device and the observable quantity, to ensure smooth start and traceable parameters;

[0153] The feedforward temperature adjustment function is constructed: Where, T add (t k ) is the time t kTemperature feedforward increment; linearly mapping the global "acceleration potential" to temperature increase / decrease, achieving advance compensation for impending moisture change trends, and reducing overshoot caused by feedback lag;

[0154] Real-time updates of heating plate temperature: T plate (t k+1 ) = T plate (t k )+T add (t k ); where T plate (t k (t) represents time t k The heating plate temperature is set; feedforward correction is superimposed using discrete integral method to form a temperature trajectory within a continuous time period, ensuring smooth transition of the execution quantity;

[0155] Implement boundary projection T plate (t k+1 )←min(max(T plate (t k+1 ),T min ),T max The forced temperature setting is within the equipment's permissible range to avoid thermal overload or insufficient heating.

[0156] This paper details the implementation of a temperature feedforward control strategy. Starting with a temperature baseline and step size, the temperature feedforward increment is obtained based on trend estimation results, and the heating plate temperature is updated in real time and maintained within a safe range through projection. This method, driven by trends rather than solely relying on deviation feedback, enables proactive temperature control, preventing lag and overshoot issues during the drying process. The real-time temperature control trajectory is smooth and controllable, avoiding thermal overload, localized carbonization, or energy waste caused by traditional constant temperature or crude manual adjustment. Boundary projection further ensures the safety of equipment and materials, eliminating extreme situations of overheating or insufficient heating. Compared to the simple "heat-hold-cool" mode of previous drying lines, this method, through dynamic and feedforward approaches, better adapts to changes in batch size, material properties, or external environment, improving energy efficiency and product quality stability.

[0157] The process of calculating the feedback adjustment amount of the conveyor belt speed based on the deviation between the current moisture content and the target, and the available speed dynamic range, updating the belt speed setpoint, and performing upper and lower bound projection specifically includes:

[0158] Set the initial reference speed of the conveyor belt

[0159] Obtaining the water content error scale

[0160] Obtain the available dynamic range v of the belt speed span =vmax -v min ;

[0161] get the belt speed feedback adjustment coefficient

[0162] set the time t k of the moisture content deviation

[0163] bind the initial belt speed to v belt (t0)=v base ; wherein v belt (t k ) is the belt speed setting at time t k ;

[0164] Compare the system output with the target to generate a scalar error, and use the speed midpoint as the initial value to avoid the extreme influence of the initial state bias on the residence time;

[0165] Construct a feedback speed regulation function: v belt (t k+1 )=v base -κ v ·e H (t k ); use the "error-speed" first-order relationship to adjust the material residence time: if the moisture content is too high, slow down and delay, if the moisture content is too low, speed up and increase the flux, the control is intuitive and can be realized;

[0166] Implement limit projection: v belt (t k+1 )←min(max(v belt (t k+1 ),v min ),v max ); prevent belt speed from exceeding the limit to cause material stacking / dispersion or excessive delay, and ensure mechanical safety and smooth production line.

[0167] Focus on the feedback regulation of the belt speed to realize the real-time adaptation of the material residence time and the drying demand. Through the belt speed reference, deviation scale, dynamic range and other parameters, the belt speed adjustment amount is calculated in real time, so that the moisture content is automatically slowed down and delayed when it is too high, and the flux is increased when it is too low. Limit projection prevents mechanical failure or system congestion caused by excessive adjustment. This scheme breaks through the problems of batch fluctuation and low compliance rate caused by the traditional "constant belt speed" process, and realizes adaptive correction with end-point compliance as a hard constraint. Its advantages are that it can dynamically respond to actual production disturbances such as raw material fluctuations, environmental changes, and uneven material thickness, reducing the "local under-drying or over-drying" phenomenon, and improving the production line rhythm and batch stability. It is more flexible and intelligent than the traditional scheme, and does not require frequent manual intervention, reducing the maintenance burden.

[0168] The reference evaporation rate characterization within the moving time window obtains the coordinated adjustment amount of the vacuum air exhaust volume flow, updates the vacuum set value, and performs upper and lower bound projection, specifically including:

[0169] For k≥1, calculate the moisture first-order derivative average value: Wherein, is the first-order difference full-field average at time t k ;

[0170] When k=0, let

[0171] Extract the full-field dehydration rate indicator, which reflects the matching degree of evaporation and exhaust, and provide unified input for the coordinated adjustment of the vacuum side;

[0172] Set the initial vacuum air exhaust volume flow reference ;

[0173] Set the vacuum air exhaust volume flow adjustment step ΔP=r P ;

[0174] Set the reference window length K0=3;

[0175] Calculate the reference evaporation rate reference , wherein k' is the temporary time index for calculating r ref ;

[0176] And bind the initial value P vac (t0) = P base ;

[0177] Construct the air exhaust adjustment function: , wherein P add (t k ) is the vacuum air exhaust volume flow increment at time t k ;

[0178] Take the average rate as the proportional input to generate an air exhaust increment consistent with the minimum step of the device, avoiding steam retention caused by insufficient exhaust or material surface rapid cooling caused by excessive exhaust;

[0179] The vacuum air exhaust volume flow is updated to: P vac (t k+1 ) = P vac (t k ) + P add (t k ); wherein P vac (t k ) is the vacuum air exhaust volume flow set at time t k ; Discretely accumulate the vacuum set to form a third execution channel parallel to the feedforward-feedback, so that the heat and mass transfer coupling is coordinated;

[0180] Implementing the projection of the boundary: P vac (t k+1 ) = min(max(P vac (t k+1 ), P min ), P max ); Ensure that the vacuum pump operating point is in the safe efficiency zone to prevent over-pumping or insufficient pumping.

[0181] For the coordinated regulation of the vacuum pumping volume flow, the first-order difference mean of the overall field moisture, the evaporation rate window, the step size, and other parameters are comprehensively considered to dynamically update the vacuum set value. Through the coordinated heat and mass transfer, the problem that pure temperature or speed regulation cannot match the evaporation characteristics of different stages of materials is solved. This coordinated mechanism not only inhibits the surface layer dryness, fine powder escape, and energy waste caused by local cavity water vapor retention or excessive pumping and exhaust, but also guarantees drying uniformity and energy saving. Compared with traditional "constant pumping" or manual adjustment, this coordinated mechanism improves the steady-state and self-adaptive ability of the system, which helps to maintain the best pumping efficiency and product consistency under complex working conditions.

[0182] When the average moisture content approaches the target and the spatial fluctuation is within the threshold and remains stable within a continuous period, it is determined that the control state is stable, and the set values of the heating plate temperature, the conveying belt speed, and the vacuum pumping volume flow are frozen, specifically including:

[0183] Setting the allowable threshold of moisture error ∈ H = r H ;

[0184] If |e H (t k )| < ∈ H and σ H (t k ) < σ max , it is determined that the control is stable, and the control parameters are frozen:

[0185] T plate (t k+1 ) = T plate (t k ), v belt (t k+1 ) = v belt (t k ), P vac (t k+1 ) = P vac (t k );

[0186] Using sensor resolution as the achievable accuracy, a "dual threshold" criterion is constructed to ensure that both the average target and uniformity are met, avoiding the masking of local deviations by simply achieving the average value; within the target range, the execution quantity is locked to suppress mechanical wear and quality fluctuations caused by back-and-forth adjustments, and to maintain stable output.

[0187] If |e H (t k )|≥∈ H or σ H (t k )≥σ max If the control parameters are not frozen, the calculation and update of steps S2 to S6 will continue.

[0188] The system clearly defines freezing as requiring an average moisture content close to the target and spatial fluctuations within a threshold. Freezing of temperature, belt speed, and vacuum setpoints only occurs when both thresholds are met simultaneously. This strategy solves the problems of repeated adjustments, equipment wear, and batch quality fluctuations caused by traditional compliance judgments relying on a single parameter or lacking time stability constraints. This freezing criterion also effectively suppresses over-adjustment due to system inertia, reducing energy consumption and mechanical losses. In existing drying lines prone to "over-adjustment" or "repeated fluctuations at the critical point," this stable freezing strategy improves system reliability and production efficiency, while providing a stable quality foundation for subsequent material cutting and release.

[0189] The process involves setting detection points at the tail end of the conveyor belt to monitor the moisture content at each point. When all points meet the preset completion conditions, drying is deemed complete, and material cutting is triggered. Simultaneously, a complete record of the drying cycle, moisture content distribution, and all control parameters is archived. Specifically, this includes:

[0190] N is installed at the tail of the conveyor belt tail There are one detection point, numbered j. tail ; where N tail Let N be the total number of tail detection points, and 1 ≤ N. tail ≤N m ;j tail ∈{N m -N tail +1,...,N m} is the serial number of the tail inspection point; the judgment position is anchored at the "last segment" before cutting, and the actual moisture content before offline is used as the criterion for finished product, so as to avoid the material being discharged when the middle section is qualified but the tail section is not dry;

[0191] When all tail points satisfy Then, drying is considered complete, and the cutting mechanism is activated; among which, For the jth tail tail Point at time t k Moisture content;

[0192] Obtain the minimum time index k that first meets the tail full point standard end :

[0193]

[0194] Obtain the actual time of completion determination

[0195] Take the earliest time of "tail full point standard" as the drying completion time, give strict and executable cutting time, avoid under-drying or over-drying;

[0196] Record the following data and archive:

[0197] Total drying cycle time T dry =t end -t0; final moisture content distribution Control parameter full process sequence Wherein, K end is the discrete completion index, Solidification full process traceable data: total duration, finished product moisture distribution and control trajectory, which can be used for batch comparison, deviation analysis and verification of final moisture standard deviation ≤2%;

[0198] If any j tail does not meet , continue to perform calculation and update of steps S2 to S6 until all j tail meet Cutting is archived; ensure that in the actual disturbance or local anomaly, it can still continue to converge until the tail full point meets the finished product standard, and then execute the cutting, to ensure the consistency of the finished product.

[0199] It is proposed to set multiple point detection at the tail of the conveying belt, and cutting is released only after all detection points meet the standard, and all cycle parameters are archived. The tail full point standard ensures the consistency of the final product, avoiding the instability of batches with "mid-section qualified and tail not dry"; the full process parameter archive provides a data basis for batch comparison, quality traceability, abnormal analysis and continuous improvement. Compared with the traditional process relying only on end-point single-point sampling or manual plate shooting judgment, this mechanism improves the scientificity and traceability of quality assurance, and can better adapt to compliance and modern digital management needs.

[0200] The embodiment also provides a traditional Chinese medicine low-temperature belt drying control method system, which comprises:

[0201] A conveying belt assembly for carrying traditional Chinese medicine materials and moving along a belt conveying system;

[0202] A plurality of infrared moisture detection units distributed on the surface of the conveying belt for real-time acquisition of the moisture content of each sampling point;

[0203] A heating plate assembly is installed below the conveying belt to provide controllable heat source for the material;

[0204] A vacuum pumping module is communicated with the drying chamber to provide adjustable vacuum pumping volume flow rate;

[0205] A running driving module is used to control the running speed of the conveying belt.

[0206] It should be noted that the relative terms such as first and second, etc. are used herein only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "contain" or any other variants thereof are intended to cover non-exclusive inclusion, so that the process, method, article or equipment including a series of elements not only includes those elements, but also includes other elements not explicitly listed or inherent to such process, method, article or equipment.

[0207] The above description is only the preferred embodiments of the present application, and it should be noted that for those skilled in the art, without departing from the technical principles of the present application, a number of improvements and refinements can be made, and these improvements and refinements should be considered as the protection scope of the present application.

Claims

1. A low-temperature belt drying control method for traditional Chinese medicine, characterized in that, The method comprises the following steps: S1, a plurality of moisture sampling points are arranged along the conveying direction of the conveying belt of the belt drying device, each sampling point is uniquely numbered, a moisture detection unit is configured, a fixed sampling period is set, initial moisture content data is recorded, and an allowed setting range and a minimum adjustment resolution of temperature, conveying belt speed, and vacuum air volume flow are established; S2, based on a continuous sampling sequence, a first-order and a second-order time series difference of moisture content with time are calculated to obtain a local trend of each sampling point and an average trend of the whole field, and an effective interval and boundary conditions of trend calculation are set; S3, a drying target moisture content and an allowed fluctuation index are determined, and a current average moisture content of the whole field and a spatial dispersion degree are obtained according to the sampling period; S4, under the condition of a preset temperature reference and a step length, a temperature feedforward increment is obtained according to the trend estimation result, the heating plate temperature set value is updated, and upper and lower boundary projections are applied to the updated result; S5, according to the deviation of the current moisture content and the target and the available speed dynamic range, a feedback adjustment amount of the conveying belt speed is calculated, the belt speed set value is updated, and upper and lower boundary projections are performed; S6, within a moving time window, a cooperative adjustment amount of the vacuum air volume flow is obtained by referring to the evaporation rate representation, the vacuum set value is updated, and upper and lower boundary projections are performed; S7, when the average moisture content approaches the target and the spatial fluctuation is within a threshold and remains stable within a continuous period, it is determined that the control state is stable, and the set values of the heating plate temperature, the conveying belt speed, and the vacuum air volume flow are frozen; S8, a detection point is arranged at the tail of the conveying belt, the moisture content of each point is detected, and when all the detection points meet the preset completion condition, it is determined that the drying is completed and the cutting is triggered, and the drying period, the moisture content distribution, and the whole process record of each control parameter are archived.

2. The low-temperature belt drying control method of traditional Chinese medicine according to claim 1, characterized in that, The plurality of moisture sampling points are arranged along the conveying direction of the conveying belt of the belt drying device, each sampling point is uniquely numbered, a moisture detection unit is configured, a fixed sampling period is set, initial moisture content data is recorded, and an allowed setting range and a minimum adjustment resolution of temperature, conveying belt speed, and vacuum air volume flow are established, which specifically comprises: Obtain the length and width of the dryer belt conveyor system, respectively, as L belt and W belt ; The wet material is uniformly distributed on the conveying belt by using a distributing device; equally spaced by Δx along the length of the conveyor belt moist Water sampling points are set, numbered as j m ; wherein Δx moist is the spacing of adjacent water sampling points along the length of the belt; j m ∈{1,...,N m} is the serial number of the water sampling point; N m is the total number of water sampling points, At each number j m An infrared moisture detection unit is installed, and the sampling period is set as Δt moist , and the moisture content is recorded as Where Δt moist is the moisture sensing sampling period; is the moisture content at the j k th sampling point at time t m ; t k is the kth discrete sampling time; k is the discrete time index. Each sampling implementation has a bounding: Compute discrete-time index t k = t0+ k · Δt moist ; where t0is the system start time; At initial time t0 record all initial moisture data acquire the minimum resolution of the sensor, denoted r H ; Acquiring a temperature control minimum resolution, denoted r T ; Obtaining the minimum resolution of the vacuum pumping volume flow rate, denoted r P ; The lower and upper limits of the temperature of the hot plate are set to T min and T max , respectively. The lower and upper limits of the feeding conveyor speed are set as v min and v max , respectively. The lower and upper limits of the vacuum pumping volume flow rate are set to P min and P max , respectively.

3. The low-temperature belt drying control method of traditional Chinese medicine according to claim 2, characterized in that, The first-order and the second-order time series difference of moisture content with time are calculated based on a continuous sampling sequence to obtain a local trend of each sampling point and an average trend of the whole field, and an effective interval and boundary conditions of trend calculation are set, which specifically comprises: The moisture first-order time difference function is constructed as: wherein, is the moisture first-order time difference at the j m point at the time t k . When k = 0, set Constructing a backward second-order time-difference function wherein, is the second-order time-difference of moisture at the j m point at time t k ; When k = 0 or 1, set Computing the second order difference full field average value at time t k of the second order difference full field average value The lower bound of the second-order difference calculation is set as 4. The low-temperature belt drying control method of traditional Chinese medicine according to claim 3, characterized in that, The drying target moisture content and the allowed fluctuation index are determined, and a current average moisture content of the whole field and a spatial dispersion degree are obtained according to the sampling period, which specifically comprises: Obtaining the target moisture content of the dried traditional Chinese medicine, denoted as H target ; The moisture content setting allows a standard deviation of σ max = 2%; Computing the time instant t k the full-field average water content Computing time instant t k spatial standard deviation 5. The low-temperature belt drying control method of traditional Chinese medicine according to claim 4, characterized in that, Under the condition of a preset temperature reference and a step length, a temperature feedforward increment is obtained according to the trend estimation result, the heating plate temperature set value is updated, and upper and lower boundary projections are applied to the updated result, which specifically comprises: Setting a temperature control reference temperature Setting temperature adjustment step ΔT step = r T ; The reference evaporation acceleration will be denoted a ref : Bind initial temperature as T plate (t0) = T base ; Constructing the feedforward temperature adjustment function: where T add (t k ) is the temperature feedforward increment at time t k . Perform real-time update of hot plate temperature: T plate (t k+1 ) = T plate (t k ) + T add (t k ); wherein T plate (t k ) is the hot plate temperature setting at time t k ; Implementing the bound projection T plate (t k+1 )←min(max(T plate (t k+1 ),T min ),T max ).

6. The low-temperature belt drying control method of traditional Chinese medicine according to claim 5, characterized in that, According to the deviation of the current moisture content and the target and the available speed dynamic range, a feedback adjustment amount of the conveying belt speed is calculated, the belt speed set value is updated, and upper and lower boundary projections are performed, which specifically comprises: Setting initial reference speed of feed conveyor Obtaining a water-containing error scale acquisition band speed available dynamic range v span = v max - v min ; obtaining a speed feedback adjustment coefficient Setting time t k moisture content deviation bind the initial tape speed to v belt (t0) = v base ; wherein v belt (t k ) is the tape speed setting at time t k ; Constructing feedback speed regulation function: v belt (t k+1 ) = v base - κ v · e H (t k ) Implementing the bound projection: v belt (t k+1 )←min(max(v belt (t k+1 ), v min ), v max ).

7. The low-temperature belt drying control method of traditional Chinese medicine according to claim 6, characterized in that, Within a moving time window, a cooperative adjustment amount of the vacuum air volume flow is obtained by referring to the evaporation rate representation, the vacuum set value is updated, and upper and lower boundary projections are performed, which specifically comprises: For k≥1, calculate the moisture first derivative average value: wherein, is the first difference full field average at time t k ; When k = 0, let Setting an initial vacuum pumping volume flow reference Setting the vacuum pumping volume flow regulation step size Δp = r P ; The reference window length K0 is set to 3. Computing a reference evaporation rate benchmark where k' is a temporary time index for computing r ref of the reference evaporation rate benchmark. and bind the initial value P vac (t0) = P base ; The air extraction adjustment function is constructed as follows: where P add (t k ) is the vacuum air extraction volume flow rate increment at time t k . The vacuum pumping volume flow rate is updated as: P vac (t k+1 ) vac (t k ) add (t k ) ; wherein P vac (t k ) is the vacuum pumping volume flow rate setting at time t k . Implementing the bound projection: P vac (t k+1 )←min(max(P vac (t k+1 ), P min ), P max ).

8. The low-temperature belt drying control method of traditional Chinese medicine according to claim 7, characterized in that, When the average moisture content approaches the target and the spatial fluctuation is within the threshold and remains stable within a continuous period, it is determined that the control state is stable, and the set values of the heating plate temperature, the conveying belt speed, and the vacuum pumping volume flow are frozen. Setting an allowable threshold value ε of the water content error H = r H ; If |e H (t k )| < ∈ H and σ H (t k ) < σ max , it is determined that the control is stable, and the control parameter is frozen. T plate (t k+1 ) = T plate (t k ), v belt (t k+1 ) = v belt (t k ), P vac (t k+1 ) = P vac (t k ); if |e H (t k ) | ≥ ∈ H or σ H (t k ) ≥ σ max , then the control parameters are not frozen and the calculation and update of steps S2 to S6 are continued.

9. The low-temperature belt drying control method of traditional Chinese medicine according to claim 8, characterized in that, A detection point is arranged at the tail of the conveying belt, and the moisture content at each point is detected. When all the detection points meet the preset completion condition, it is determined that the drying is completed, and the cutting is triggered. At the same time, the drying cycle, the moisture content distribution, and the whole-process record of each control parameter are archived. N is installed at the tail of the conveyor belt tail There are one detection point, numbered j. tail ; where N tail Let N be the total number of tail detection points, and 1 ≤ N. tail ≤N m ;j tail ∈{N m -N tail +1, ..., N m } represents the serial number of the tail detection point; When all tail points satisfy then determine that drying is completed, and start the cutting mechanism; wherein, is the moisture content of the tail j tail point at time t k ; acquiring the minimum time index k at which the tail-end full point criterion is first satisfied end : Actual time of acquisition completion determination The following data are recorded and archived: Total drying cycle time T dry = t end Final moisture content profile Control parameter full pass sequence where K end is the discrete completion index, If any j tail Not satisfied The calculation and update of steps S2 to S6 are continued until all j tail Satisfied In the cutting file.

10. A system for low-temperature belt drying of traditional Chinese medicine using the method of claim 9, characterized in that, The conveying belt assembly is used to carry the traditional Chinese medicine materials and move along the belt conveying system. A plurality of infrared moisture detection units are arranged on the surface of the conveying belt to collect the moisture content of each sampling point in real time. The heating plate assembly is installed below the conveying belt to provide a controllable heat source for the materials. The vacuum pumping module is connected with the drying chamber to provide an adjustable vacuum pumping volume flow. The operation driving module is used to control the running speed of the conveying belt. ​

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