Multi-stage temperature and humidity closed-loop control system and method for inhibiting browning of day lily during drying

Abstract

The invention relates to the technical field of hemerocallis citrina baroni drying, in particular to a multi-section temperature and humidity closed-loop control system and method for inhibiting browning of hemerocallis citrina baroni drying. The device comprises an environment state sensing unit, and the environment state sensing unit is used for obtaining environment state parameters in a drying cavity and material state parameters related to browning; carrying out quantitative analysis on the development trend of browning in the day lily drying process, and generating a browning trend parameter and a browning parameter set; a piecewise function mapping model is adopted to perform stage division on a day lily drying full life cycle, a multi-stage temperature and humidity control strategy is generated according to different drying stages and browning risk grades, and the temperature and humidity control strategy is dynamically corrected to continuously adjust the temperature and humidity in a drying cavity. By introducing a temperature and humidity decoupling coefficient and performing cross correction in a PID algorithm, the system effectively eliminates the interference of temperature adjustment on humidity and the interference of humidity adjustment on temperature.

Description

Technical Field

[0001] This invention relates to the field of dried daylily technology, and more specifically, to a multi-stage temperature and humidity closed-loop control system and method for inhibiting browning during the drying of dried daylilies. Background Technology

[0002] Daylily is a typical heat-sensitive and climacteric agricultural product. After harvesting, fresh daylilies still have a vigorous metabolism and contain highly active polyphenol oxidase and peroxidase. In actual production, fresh daylilies will undergo significant enzymatic browning within 2-6 hours after harvesting due to the high activity of polyphenol oxidase (PPO). In the subsequent drying process, if the temperature is not properly controlled, non-enzymatic browning (such as Maillard reaction) can easily occur, resulting in a dark, reddish, or black color of the finished product. Moreover, traditional drying methods cannot simultaneously achieve blanching (enzyme inactivation) and dehumidification, resulting in a dull color of the finished product and severe loss of vitamin C. Therefore, this paper provides a multi-stage temperature and humidity closed-loop control system and method to inhibit browning in dried daylilies, for the segmented inhibition of different browning mechanisms. Summary of the Invention

[0003] The purpose of this invention is to provide a multi-stage temperature and humidity closed-loop control system and method for inhibiting browning during the drying of daylilies, in order to solve the problem mentioned in the background art that fresh daylilies undergo significant enzymatic browning after harvesting due to the high activity of polyphenol oxidase; and that non-enzymatic browning is easily triggered if the temperature is not properly controlled during the subsequent drying process, resulting in the finished product being dark, reddish or black in color.

[0004] To achieve the above objectives, on the one hand, the present invention aims to provide a multi-segment temperature and humidity closed-loop control system for inhibiting browning during the drying of daylilies, including an environmental state sensing unit, which is used to acquire environmental state parameters within the drying chamber and material state parameters related to browning. The environmental state parameters include the dry bulb temperature and relative humidity inside the drying chamber, and the material state parameters include the material moisture content, brightness parameter, and red-green axis parameter. The browning trend assessment unit, based on the environmental and material state parameters, quantitatively analyzes the browning trend during the drying process of daylilies and generates a set of browning trend parameters and browning parameters. ; The control decision unit, based on the browning trend parameters and material state parameters, uses a piecewise function mapping model to divide the entire life cycle of daylily drying into stages. According to different drying stages and browning risk levels, it generates multi-stage temperature and humidity control strategies and dynamically modifies the temperature and humidity control strategies to continuously adjust the temperature and humidity in the drying chamber. At the same time, it introduces brightness parameters and red-green axis parameters to adjust the temperature and humidity control strategies to suppress browning during the drying process of daylilies. An environmental control execution unit, which coordinates the temperature and humidity within the drying chamber according to the temperature and humidity control strategy.

[0005] As a further improvement to this technical solution, the environmental state sensing unit includes a multi-point temperature and humidity monitoring module, a moisture content detection module, and a color state acquisition module. Among them, the multi-point temperature and humidity monitoring module is used to collect the dry bulb temperature and relative humidity at different spatial locations inside the drying chamber in real time; The moisture content detection module uses a weighing sensor to continuously monitor the weight change of daylilies during the drying process. By calculating the water loss rate of the material, the moisture content of the material is obtained. The color status acquisition module acquires images of the daylily surface and captures RGB images of the daylily surface in real time, converting them into Lab color space data to extract lightness parameters and red-green axis parameters, which are used to characterize the color change trend of the daylily surface.

[0006] As a further improvement to this technical solution, the browning trend assessment unit constructs browning trend parameters, and the specific steps involved are as follows: Environmental and material state parameters are normalized and mapped to standard ranges. ; Furthermore, by introducing the time dimension, characteristic quantities reflecting the rate of change in temperature and humidity, the rate of material water loss, and the rate of color change are constructed. The rates of temperature and humidity change, material water loss rate, and color change rate were used to construct a set of browning parameters. ; And the set of browning parameters The browning trend parameters are obtained by weighted fusion of various feature quantities. .

[0007] As a further improvement to this technical solution, the control decision unit includes a multi-stage process formula library module, a browning risk assessment logic module, and a closed-loop PID control module. The multi-segment process formula library module is used to store the set of process control parameters corresponding to different browning risk levels, and divides the entire life cycle of daylily drying into stages based on the piecewise function mapping model, and defines the temperature set value and relative humidity set value corresponding to each interval, and generates the reference temperature and humidity control parameters for the current drying stage. The piecewise function mapping model includes a drying stage determination function and a temperature and humidity piecewise mapping function. Based on the browning trend parameters, the browning risk assessment logic module uses a two-way browning risk discrimination algorithm to dynamically correct the baseline temperature and humidity control parameters and generate corrected temperature and humidity setpoints. The closed-loop PID control module is used to compare the corrected temperature and humidity setpoint with the actual temperature and humidity parameters fed back by the environmental state sensing unit, and generate corresponding execution control commands based on the temperature and humidity decoupled PID control algorithm. The closed-loop PID control module introduces decoupling coefficients in the temperature control loop and the humidity control loop respectively to reduce mutual interference between temperature regulation and humidity regulation, and outputs the execution control command to the environmental regulation execution unit.

[0008] As a further improvement to this technical solution, the multi-segment process formula library module generates reference temperature and humidity control parameters for the current drying stage, involving the following specific steps: Get current drying time The system also monitors the real-time moisture content of the material and determines the current drying range using a drying stage determination function. The drying zone It includes at least the enzyme-inactivating blanching zone, the constant-rate dehydration zone, and the deceleration color-fixing zone; Based on the determined drying range The corresponding temperature setpoint and relative humidity setpoint are obtained from the set of process control parameters through the temperature and humidity piecewise mapping function; The temperature setpoint and relative humidity setpoint are combined to generate reference temperature and humidity control parameters for the current drying stage.

[0009] As a further improvement to this technical solution, the browning risk assessment logic module generates corrected temperature and humidity setpoints, involving the following specific steps: Based on the browning trend parameters output by the browning trend assessment unit The system uses the current material state parameters and introduces color parameters as an auxiliary criterion to independently distinguish between the risks of enzymatic browning and non-enzymatic browning. When the risk index of enzymatic browning exceeds the preset threshold, it is determined that there is a risk of enzymatic browning in the current drying stage. When the non-enzymatic browning risk index exceeds the preset threshold, it is determined that there is a non-enzymatic browning risk in the current drying stage. To address the risk of enzymatic browning, a temperature and humidity control approach aimed at inhibiting enzyme activity was determined. To address the risk of non-enzymatic browning, a temperature and humidity control approach was identified with the goal of reducing the browning reaction rate under high temperature and high humidity conditions. Based on the reference temperature and humidity control parameters, and in accordance with the determined control direction, a two-way browning risk discrimination algorithm is used to correct the temperature setpoint and relative humidity setpoint, generating temperature and humidity correction setpoints for the current drying stage.

[0010] As a further improvement to this technical solution, the closed-loop PID control module generates corresponding execution control commands based on a temperature and humidity decoupled PID control algorithm. The specific steps involved are as follows: The real-time drying temperature setpoint output by the control decision unit is obtained respectively. Relative humidity setpoint And the actual dry-bulb temperature monitored by the environmental state sensing unit (1) relative humidity The temperature error was calculated. and humidity error ; Based on the temperature and humidity error, a decoupled PID algorithm is used to calculate the temperature control command separately. Humidity control instructions ; The temperature and humidity change gradient constraint parameters output by the control decision unit , Introduce control commands to limit the rate of temperature and humidity control signals; The control command after gradient constraint is smoothed by low-pass filtering to generate a smoothed temperature control command. Humidity control instructions .

[0011] As a further improvement to this technical solution, the environmental control execution unit coordinates the temperature and humidity within the drying chamber, involving the following specific steps: Receives smooth temperature control commands from the closed-loop PID control module. With smooth humidity control command ; According to the temperature control command Adjust the power of the heating device, cooling device, and fan inside the drying chamber to dynamically regulate the chamber temperature and record the actual temperature. Feedback is sent to the closed-loop PID control module to form a temperature closed loop; According to the humidity control command Adjust the humidification device, dehumidification device, and fan status within the drying chamber to dynamically regulate the relative humidity of the chamber and record the actual humidity. Feedback is sent to the closed-loop PID control module to form a humidity closed loop.

[0012] On the other hand, the present invention provides a multi-segment temperature and humidity closed-loop control method for inhibiting browning of dried daylily, used in any of the above-mentioned multi-segment temperature and humidity closed-loop control systems for inhibiting browning of dried daylily, comprising the following steps: S1. Collect environmental state parameters and material state parameters related to browning in the drying chamber. The environmental state parameters include dry bulb temperature and relative humidity, and the material state parameters include material moisture content, lightness parameters and red-green axis parameters. S2. Based on the environmental state parameters and material state parameters, quantitatively analyze the browning development trend during the drying process of daylily, and generate browning trend parameters and browning parameter set for closed-loop control input. S3. Based on the browning trend parameters and material state parameters, a piecewise function mapping model is used to divide the entire life cycle of daylily drying into stages, and multi-stage temperature and humidity control strategies are generated according to different drying stages and browning risk levels. S4. Based on the multi-segment temperature and humidity control strategy generated in step S3, adjust the temperature and humidity inside the drying chamber in real time to suppress browning during the drying process of daylilies, ensure that each drying stage is executed according to the predetermined temperature and humidity change gradient, and dynamically correct the control strategy based on real-time monitoring data.

[0013] Compared with the prior art, the beneficial effects of the present invention are as follows: 1. A multi-stage temperature and humidity closed-loop control system and method for inhibiting browning in dried daylily, by segmenting and controlling the enzymatic browning of fresh daylily after harvest and the non-enzymatic browning during the drying process, a two-stage browning inhibition is achieved; in the post-harvest stage, the system can dynamically assess the activity of polyphenol oxidase and trigger enzyme inactivation, effectively inhibiting enzymatic browning and maintaining the initial color of the fresh daylily; in the drying stage, the system can monitor the trend of non-enzymatic browning in real time and adjust the temperature and humidity conditions, effectively inhibiting Maillard reaction and other non-enzymatic browning, ensuring that the dried product has a uniform and bright color.

[0014] 2. In a multi-stage temperature and humidity closed-loop control system and method for inhibiting browning during the drying of daylily, a closed-loop control mechanism with enzymatic and non-enzymatic browning as dual control indicators is established. The temperature and humidity of each drying stage are dynamically adjusted according to the real-time evaluation results to achieve synergistic optimization of blanching and dehumidification, thus avoiding the problems of darkening of color, loss of nutrients and destruction of vitamin C caused by fixed parameters in traditional drying processes.

[0015] 3. In a multi-segment temperature and humidity closed-loop control system and method for inhibiting browning during the drying of daylily, by introducing a temperature and humidity decoupling coefficient and performing cross correction in the PID algorithm, this system effectively eliminates the interference of temperature regulation on humidity and the interference of humidity regulation on temperature, ensuring that the cavity environment can quickly and stably reach the set value when switching between different drying stages, and avoiding material quality fluctuations caused by control oscillations. Furthermore, to address potential thermal shocks or surface crusting issues that materials may suffer, the system introduces variable gradient constraint parameters. By limiting the rate of change in temperature and humidity, it prevents physical damage caused by sudden changes in environmental parameters, ensuring a smooth drying process and effectively protecting the tissue structure and color of daylilies. Attached Figure Description

[0016] Figure 1 This is a flowchart illustrating the overall process of the present invention.

[0017] The meanings of the labels in the diagram are as follows: 1. Environmental condition sensing unit; 11. Multi-point temperature and humidity monitoring module; 12. Moisture content detection module; 13. Color status acquisition module; 2. Browning Trend Assessment Unit; 3. Control Decision Unit; 31. Multi-stage Process Recipe Library Module; 32. Browning Risk Assessment Logic Module; 33. Closed-Loop PID Control Module; 4. Environmental control and control execution unit. Detailed Implementation

[0018] 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.

[0019] Example 1: Please refer to Figure 1 As shown, a multi-segment temperature and humidity closed-loop control system for inhibiting browning during the drying of daylilies is provided, comprising: Environmental state sensing unit 1 is used to acquire environmental state parameters and material state parameters related to browning inside the drying chamber. The environmental state parameters include the dry bulb temperature and relative humidity inside the drying chamber, and the material state parameters include the material moisture content, brightness parameter, and red-green axis parameter. In this embodiment, the environmental state sensing unit 1 includes a multi-point temperature and humidity monitoring module 11, a moisture content detection module 12, and a color state acquisition module 13; Among them, the multi-point temperature and humidity monitoring module 11 is set at the upper, middle and lower parts of the drying chamber, as well as at the air inlet and air outlet (the multi-point layout is used to identify the temperature and humidity gradient that may exist in the chamber, and to avoid local browning of materials caused by local high temperature or high humidity). It is used to collect the dry bulb temperature and relative humidity at different spatial locations in the drying chamber in real time, thereby reflecting the uniformity of temperature and humidity distribution in the drying chamber. The moisture content detection module 12 uses a weighing sensor to continuously monitor the weight change of daylily during the drying process, and calculates the water loss rate of the material to obtain the moisture content of the material. In this embodiment, the weighing platform for placing daylilies is designed as a semi-sealed structure, with ventilation holes (≤2mm in diameter) reserved only in the material placement area. This ensures normal contact between the material and the airflow within the drying chamber for dehydration while significantly reducing the force of the airflow directly impacting the sensors. Simultaneously, arc-shaped guide vanes are installed around the weighing platform to allow the forced-circulation hot air to flow along them, preventing pressure fluctuations caused by the vertical impact of the airflow on the weighing platform. Furthermore, pressure balancing holes are provided in the sealed structure of the weighing platform to maintain consistent air pressure between the weighing platform and the drying chamber, preventing pressure differences caused by airflow circulation and thus avoiding additional pressure interference. Dust filters are installed inside the pressure balancing holes to prevent material debris from entering and affecting structural stability.

[0020] The specific calculation method for the moisture content of the material is as follows: Before drying begins, the daylily buds to be dried are evenly spread on the weighing platform. At this time, the hot air circulation in the drying chamber is not activated, and the initial weight data from the sensor is recorded. (Unit: g), this data represents the initial total weight of the material (including dry weight and initial moisture content); simultaneously, the dry weight of the same batch of daylilies was pre-measured. (Unit: g), serving as the baseline parameter for moisture content calculation (only needs to be calibrated once at the start of the batch, without the need for repeated destructive testing on each batch of material); During the manufacturing process, the weighing sensor collects material weight data at a sampling frequency of 1Hz. (Unit: g) To address any potential residual minor airflow pulsations, a moving average filtering algorithm is used to process the original data, as shown in the following formula: ; In the formula, The filtered Material weight at all times The sliding window size (preferred in this embodiment) ), for The raw weighing data at any given time can be further filtered using this algorithm to eliminate weight data fluctuations caused by pulsating impact forces, ensuring the stability of the monitoring data. Based on the filtered stable weight data, the real-time water loss rate of the material is calculated. (Unit: g / min): ; In the formula, The sampling time interval (preferred, in this embodiment) ), for The weight of the material after filtering at any given time; Real-time moisture content The calculation (unit: %) uses the weight method, as detailed below: ; Based on the ratio of weight change to dry weight during the material drying process, non-destructive testing can be achieved without damaging the material. At the same time, since the weighing data has been processed by structural anti-interference and filtering, the real-time (1 time / min) and accuracy of moisture content calculation can be guaranteed.

[0021] The color status acquisition module 13 acquires images of the daylily surface and captures RGB images of the daylily surface in real time and converts them into Lab color space data to extract lightness parameters and red-green axis parameters, which are used to characterize the color change trend (browning trend) of the daylily surface. When the color parameters (lightness parameters and red-green axis parameters) are detected to deviate from the preset color range, the control decision unit 3 makes adjustments based on the temperature and humidity control strategy of the color parameters.

[0022] In this embodiment, the color state acquisition module 13 includes an industrial camera and an image processing unit. The industrial camera is used to periodically acquire images of the daylily surface during the drying process. The image processing unit is used to perform color space conversion on the acquired images and extract brightness parameters and red-green axis parameters from the converted color space. The brightness parameters are used to characterize the brightness change of the daylily surface, and the red-green axis parameters are used to characterize the trend of the daylily surface changing from yellow to reddish-brown.

[0023] Furthermore, an image sensor (industrial camera) is selected and installed at least 5 points, including the top center and four corners of the drying chamber. The sensor lens is vertically downward, and the vertical distance between it and the material bearing surface (weighing platform) is set to 30±5cm (to maximize the coverage of a single lens while ensuring image resolution). Furthermore, at least one point is placed on each side of the drying chamber, with the lens horizontally facing the center of the material pile and at a horizontal distance of 25±3cm from the surface of the material pile. This is used to supplement the collection of color information of the material pile from the sides and deep inside, and to avoid blind spots in the coverage of the bottom layer of the material pile from the top view. All sensor mounting brackets adopt a detachable quick-installation structure. The brackets are fixed to the cavity wall by shock-absorbing buffer pads. The installation spacing can be adjusted according to the size of the material bearing surface (compatible with standard weighing platforms of 50cm×50cm~100cm×100cm) to ensure coverage of the entire batch of materials.

[0024] Further, single-lens field of view parameters: Employing an industrial lens with a focal length of 8mm, the horizontal field of view is ≥60° and the vertical field of view is ≥45°. A single top sensor can cover a circular area with a diameter ≥40cm. The fields of view of the five top sensors have an overlap rate of ≥30% in the center area of ​​the bearing surface, with no blind spots in the edge area, ensuring that the entire batch of materials (maximum laying area 100cm×100cm) is within the field of view.

[0025] Meanwhile, to address material tumbling / dynamic drying scenarios, the sensor continuously acquires images at a sampling frequency of 2Hz, with each group consisting of 5 frames (corresponding to 2.5 seconds, matching half of the material tumbling cycle, ensuring coverage of different material tumbling postures). In each group of images, 9 feature regions are extracted according to a fixed rule of 3 sampling points in the central area, 4 sampling points in the edge area, and 2 sampling points in the side area. The image size of each feature region is 100×100 pixels (to avoid random errors of a single pixel). The average value of the Lab data of the 9 feature regions in each group is taken as the representative color parameter of the entire batch of materials during that time period, effectively eliminating the influence of local color differences caused by dynamic material tumbling. Furthermore, to cope with the impact forces within the drying chamber (mainly from the airflow impact generated by the hot air circulation and the slight vibrations during material tumbling): a wedge-shaped air guide is installed at the front end of the sensor lens. The air guide is made of polytetrafluoroethylene (high temperature resistant and low reflectivity), and its tilt angle is consistent with the airflow direction inside the chamber (30° with the horizontal direction), so that the forced circulating hot air flows along the surface of the air guide and avoids the airflow impacting the lens surface vertically; a dustproof filter (pore size ≤1μm) is set inside the air guide to prevent material debris and moisture from adhering to the lens without affecting the transmission of visible light (transmittance ≥95%, attenuation rate of RGB three-channel light ≤3%). Furthermore, the sensor mounting bracket adopts a composite structure of rigid fixation and elastic buffer: the main body of the bracket is made of stainless steel and is rigidly connected to the cavity wall through expansion bolts (to ensure installation accuracy); a silicone shock-absorbing pad (Shore hardness 50±5) is added between the bracket and the sensor. The shock-absorbing pad is 8mm thick and can absorb vibrations with a frequency of 20~200Hz (covering the main vibration frequencies generated by material rolling and fan operation), so that the vibration displacement of the sensor is ≤0.1mm; To ensure the measurement accuracy of brightness and red-green axis parameters: a 12-megapixel industrial camera (4000×3000 resolution) is used as the image sensor, with a 16-bit color depth for the RGB three channels (each channel can recognize 65536 gray levels, exceeding the color resolution of a conventional 8-bit camera). The lens has a color reproduction index (CRI) ≥90, ensuring that the acquired RGB image accurately reflects the actual color of the material. The sensor has a built-in temperature compensation module, and the color shift is ≤0.5 within the range of -10~80℃ (covering the working temperature range of the drying chamber 45~65℃). (CIE 1976 color difference formula) to avoid color distortion caused by temperature changes.

[0026] RGB to Lab conversion algorithm: Utilizing the internationally standardized CIE1976 Lab conversion formula, and considering the light source characteristics of the drying chamber (three uniformly distributed white LED light sources inside the chamber, color temperature 5500K, color rendering index ≥92, avoiding the impact of light source spectral differences on conversion accuracy), a light source spectral correction term is introduced during the conversion process to ensure a conversion error ≤0.2%. Outlier detection was performed on the Lab data for each feature region. If a single data point deviates from the other data in the same group by more than 1.0, it is considered an outlier. If the value is not found, it is considered an outlier (possibly caused by accidental factors such as material debris obstruction or lens reflection). The median of the same data set is then used to replace it to ensure the reliability of the final average value.

[0027] The multi-segment temperature and humidity closed-loop control system for inhibiting browning during the drying of daylilies also includes a browning trend assessment unit 2. Based on environmental and material state parameters, the browning trend assessment unit 2 quantitatively analyzes the development trend of browning during the drying process of daylilies and generates a set of browning trend parameters and browning parameters. This is used to provide closed-loop control input for control decision unit 3; In this embodiment, the browning trend assessment unit 2 constructs browning trend parameters, and the specific steps involved are as follows: Environmental and material state parameters are normalized (using linear mapping or standardization methods) and mapped to a standard range. ; Furthermore, by introducing the time dimension, characteristic quantities reflecting the rate of change in temperature and humidity, the rate of material water loss, and the rate of color change are constructed. The rates of temperature and humidity change, material water loss rate, and color change rate were used to construct a set of browning parameters. In the formula, express The normalized value of the rate of temperature change within the drying chamber at all times is used to reflect the degree of impact of thermal shock on the material (referring to the rated heating / cooling rate of daylily drying equipment (industry standard is 0.5~3℃ / min), combined with temperature sensitivity experiments of enzymatic browning (PPO activity) and non-enzymatic browning (Maillard reaction), the reference range is determined to be [0, 3℃ / min]; when it exceeds 3℃ / min, thermal shock will cause the material surface to form a crust or abnormal activation of enzyme activity, and when it is below 0, it has no practical physical meaning, so 0 is taken as the lower limit). express The normalized value of the relative humidity change rate within the drying chamber at all times is used to reflect the severity of environmental dehumidification or rehumidification (based on the safe range of humidity regulation in the drying process (the industry's conventional dehumidification / humidification rate is 1~5%RH / min). Exceeding 5%RH / min can easily lead to crusting or rehumidification on the material surface; therefore, the reference range is determined as follows). ); express The normalized value of the water loss rate of the material at any given time is used to characterize the drying speed (too fast a drying speed can easily lead to surface crusting, while too slow a drying speed can easily lead to enzymatic browning). (The water loss rate range of fresh daylily (initial moisture content of about 80%) under safe drying conditions was determined experimentally (0.5~2g / (100g)). min), less than 0.5g / (100g) The risk of enzymatic browning increases significantly at (min), above 2g / (100g) The risk of surface crust formation increases when the temperature reaches 0 min, therefore the reference range is determined to be 0 min. ); express The normalized value of the rate of decrease in lightness of the material surface at any given time is used to characterize the trend of the material's color darkening (absolute value for negative changes) (based on the safe range of color change for daylily in the Lab color space; the rate of decrease in lightness exceeding...). (At this time, the degree of browning is irreversible). Based on industry quality requirements for the color of dried daylily, the reference range is determined as follows: ); express The normalized rate of increase of the red-green axis parameter on the material surface at any given time is used to characterize the trend of the material's color changing from yellow to reddish-brown (the rate of increase of the red-green axis parameter (a value) exceeds 0.2). At this time, the material will quickly turn reddish-brown, therefore the reference range is determined to be [0, 0.2]. ]); In this embodiment, the present invention uses a linear mapping method for normalization: ; In the formula, express Normalized value of a feature at time t (mapped to the interval [0,1]); This represents the real-time raw detection value of the feature. This represents the maximum value (fixed value, no dynamic prediction required) of the reference range for this feature quantity. This represents the minimum value (fixed value, no dynamic prediction required) of the reference range for this characteristic quantity; specifically, in this embodiment, if the original temperature change rate is 1.5℃ / min, the normalized value is calculated as 0.5; if the original value exceeds... (e.g., 3.5℃ / min), then the normalized value is taken as 1 (considered as high browning risk); if the original value is lower than (e.g., 0.2℃ / min), then the normalized value is 0 (considered as having no relevant risk); And the set of browning parameters The browning trend parameters are obtained by weighted fusion of various feature quantities. In the formula, This indicates the weight used to characterize the effect of the rate of temperature change on browning development (preferred, This is used to characterize the combined effects of thermal shock on enzymatic browning (PPO activity activation) and non-enzymatic browning (Maillard reaction rate). This indicates the weight used to characterize the effect of the rate of change in relative humidity on browning development (preferred). This is used to characterize the effect of humidity fluctuations on the moisture distribution of materials, and thus indirectly affect the browning reaction environment. This indicates the weight used to characterize the effect of material dehydration rate on browning development (preferred). This directly affects enzymatic browning (when water loss is too slow, enzyme activity is maintained for a longer time) and non-enzymatic browning (when water loss is too rapid, surface crusting occurs, and internal water retention leads to browning). This indicates the weight used to characterize the impact of lightness changes on browning development. (used to characterize the degree of darkening of color caused by browning). This represents the weight used to characterize the impact of changes in red and green axis parameters on browning development. This is used to characterize the rate of material transformation to reddish-brown; it has the highest sensitivity to non-enzymatic browning and therefore the highest weight. It also satisfies the following conditions: The aforementioned weighting coefficients are dynamically invoked based on the different drying stages defined in the segment process formula library module 31: Specifically, in the enzyme-inactivated blanching range (moisture content 80-60%): at this point, enzymatic browning dominates, and adjustments should be made to... (Increase the weighting of the effect of temperature on enzyme activity). (Weight of the effect of increasing the rate of water loss on enzymatic browning) The remaining weights will be adjusted accordingly. , The sum is still 1. In the constant rate dehydration range (moisture content 60-30%): enzymatic browning weakens, and non-enzymatic browning begins to appear, using standard weights; In the deceleration and color-fixing range (moisture content 30-12%): non-enzymatic browning predominates, and should be adjusted accordingly. , (Increase the weight of color parameters) The remaining weights will be adjusted accordingly. , ).

[0028] The multi-segment temperature and humidity closed-loop control system for inhibiting browning during the drying of daylilies also includes a control decision unit 3. Based on the browning trend parameters and material state parameters, the control decision unit 3 uses a piecewise function mapping model to divide the entire life cycle of daylily drying into stages. According to different drying stages and browning risk levels, it generates multi-segment temperature and humidity control strategies and dynamically corrects the temperature and humidity control strategies to continuously adjust the temperature and humidity in the drying chamber. At the same time, it introduces brightness parameters and red-green axis parameters to adjust the temperature and humidity control strategies to inhibit browning during the drying process of daylilies. In this embodiment, the control decision unit 3 includes a multi-stage process formula library module 31, a browning risk assessment logic module 32, and a closed-loop PID control module 33. The multi-stage process formulation library module 31 is used to store a set of process control parameters corresponding to different browning risk levels (the process control parameters include at least drying temperature parameters (including target drying temperature and allowable fluctuation range), drying relative humidity parameters (including target relative humidity and its variation gradient), drying air velocity parameters (used to control the mass transfer rate per unit time), drying airflow reversal cycle parameters (used to suppress browning caused by local moisture retention), and temperature and humidity variation gradient parameters and stage duration parameters corresponding to the drying stage (temperature rise and fall gradient parameters; humidity decrease gradient parameters; drying stage duration parameters); and also includes parameters for... The process control parameters include enzyme activity inhibition temperature control threshold parameters, critical water activity control parameters, and surface-to-internal moisture gradient control coefficients to inhibit browning reactions. These parameters are stored and retrieved hierarchically according to browning risk levels (browning risk levels are divided into low-risk, medium-risk, and high-risk multi-stage process formulations). A piecewise function mapping model is used to divide the entire life cycle of daylily drying into stages (the model includes a drying stage determination function and a temperature and humidity piecewise mapping function). Temperature and relative humidity setpoints are defined for each interval, generating baseline temperature and humidity control parameters for the current drying stage. The specific steps involved are as follows: Get current drying time The system also monitors the real-time moisture content of the material and determines the current drying range using a drying stage determination function. The drying zone It includes at least the enzyme-inactivating blanching zone, the constant-rate dehydration zone, and the deceleration color-fixing zone; Based on the determined drying range The corresponding temperature setpoint and relative humidity setpoint are obtained from the set of process control parameters through the temperature and humidity piecewise mapping function; The temperature setpoint and relative humidity setpoint are combined to generate reference temperature and humidity control parameters for the current drying stage.

[0029] Specifically, in this embodiment, the current drying time is obtained. and the real-time moisture content of daylily raw materials ; Based on real-time moisture content The current drying interval is determined by the drying stage determination function. : ; In the formula, The enzyme-inactivating blanching range (moisture content range 80%) ~60 ), The constant rate dehydration range (moisture content range 60%) ~30 ), For deceleration and color fixation range (moisture content range 30) ~12 ), and To preset the moisture content threshold, and (Preferred) , ); Based on the determined drying range The temperature and relative humidity setpoints corresponding to the drying range are retrieved from the process control parameter set using a temperature and humidity segmented mapping function. ; ; in, , , These are the preset temperature control values ​​within the corresponding drying stage (specifically, in this embodiment...). ; ); , , These are the preset values ​​within the relative humidity control range corresponding to the drying stage (specifically, in this embodiment, the enzyme-inactivating blanching range). Constant rate dehydration zone It should be noted that the relative humidity control range corresponding to each drying interval is a phased target control parameter, used to characterize the preferred humidity control interval under different drying stages. When the drying stage is switched, the control decision unit 3 does not directly switch the relative humidity of the cavity to the next stage target interval, but performs a gradual transition control on the humidity set value, so that the relative humidity of the cavity changes continuously under the preset change rate constraint, thereby avoiding abnormal water loss or increased browning risk on the surface of the material due to sudden humidity changes. Specifically, based on the characteristics of moisture content change during the drying process of daylilies, the entire drying life cycle is divided into an enzyme inactivation and blanching interval, a constant-rate dehydration interval, and a deceleration and color-fixing interval. When the daylily is in the enzyme-inactivating blanching zone, the corresponding first temperature setpoint is invoked. and the first relative humidity setpoint As a reference temperature and humidity control parameter; When the daylily is in the constant-rate dehydration zone, the corresponding second temperature setpoint is invoked. Second relative humidity setting value As a reference temperature and humidity control parameter; When the daylily is in the deceleration and color-fixing range, the corresponding third temperature setting value is invoked. and the third relative humidity setting value As a reference temperature and humidity control parameter; The first temperature setting, the second temperature setting, and the third temperature setting are decreased sequentially, as are the first relative humidity setting, the second relative humidity setting, and the third relative humidity setting, in order to adapt to the dehydration and browning inhibition requirements of daylilies at different drying stages. Furthermore, the temperature setpoint relative humidity setting value Combined, these parameters generate a reference temperature and humidity control parameter to represent the drying stage. , used to characterize time-series temperature and humidity reference curves, where, This indicates the total number of sampling points in the current drying stage, which determines the resolution of the baseline temperature and humidity curve. This represents the discrete sampling time corresponding to the drying stage, used to construct a temperature and humidity reference curve; and the reference temperature and humidity control parameters are output to the browning risk assessment logic module 32 as the initial control reference for dynamically correcting the reference temperature and humidity control parameters.

[0030] Among them, the browning risk assessment logic module 32, based on the browning trend parameters, uses a two-way browning risk discrimination algorithm to dynamically correct the baseline temperature and humidity control parameters, generating corrected temperature and humidity setpoints. The specific steps involved are as follows: Based on the browning trend parameters output by browning trend assessment unit 2 and current material state parameters (including material temperature, material water activity, surface-to-internal moisture gradient, and duration of drying stage), the browning trend parameters It is used at least to characterize the enzymatic browning and non-enzymatic browning trends of materials at the current drying stage, and by introducing color parameters (lightness parameter and red-green axis parameter) as auxiliary criteria, it independently distinguishes between enzymatic browning risk and non-enzymatic browning risk, and is used to quantify the risk levels of enzymatic browning and non-enzymatic browning at the current drying stage: When the risk index of enzymatic browning exceeds the preset threshold, it is determined that there is a risk of enzymatic browning in the current drying stage. When the non-enzymatic browning risk index exceeds the preset threshold, it is determined that there is a non-enzymatic browning risk in the current drying stage. To address the risk of enzymatic browning, a temperature and humidity control approach aimed at inhibiting enzyme activity was determined. To address the risk of non-enzymatic browning, a temperature and humidity control direction aimed at reducing the browning reaction rate under high temperature and high humidity conditions was determined. Based on the baseline temperature and humidity control parameters, a two-way browning risk discrimination algorithm was used to correct the temperature setpoint and relative humidity setpoint according to the determined control direction, generating corrected temperature and humidity setpoints for the current drying stage (the correction includes drying temperature, drying relative humidity, temperature and humidity change gradient, and stage duration control parameters). The temperature and humidity correction setpoint is used as the updated control reference and output to the closed-loop PID control module 33 for coordinated adjustment of temperature and humidity in the drying chamber.

[0031] In this embodiment, a comprehensive browning risk index is constructed based on the collected material temperature, water activity, and moisture gradient. :

[0032] in, The current water activity of the material; This indicates the preset lower limit threshold for water activity; This indicates the preset upper limit threshold for water activity; Indicates the maximum allowable material temperature during the drying process; The actual measured temperature of the material; The temperature at which polyphenol oxidase activity is inhibited; A surface-to-internal moisture gradient; For reference moisture gradient; These are the normalized weighting coefficients, and Among them, the comprehensive indicator of browning risk For dimensionless scalar parameters, specifically, This indicates the weight of water activity, reflecting the contribution of the material's moisture state to the risk of browning. This indicates the weight of the influence of material temperature, reflecting the degree of influence of temperature changes on the rates of enzymatic and non-enzymatic browning. This indicates the influence weight of the surface-interior moisture gradient, reflecting the impact of uneven moisture distribution on local browning.

[0033] In this embodiment, the weighting coefficient can be set according to the actual drying process characteristics and the sensitivity of different drying stages: in stages where humidity changes are sensitive to enzymatic browning, the weighting coefficient can be increased. The value of can be improved during the high-temperature rapid drying stage. The value of can be increased when there is a significant moisture gradient difference. The value of .

[0034] Based on the comprehensive browning risk index The numerical range of browning risk is used to classify browning risk into low browning risk, medium browning risk and high browning risk levels. In this embodiment, the comprehensive browning risk index Combining browning trend parameters The classification criteria are as follows: Specifically, the threshold ranges for the comprehensive browning risk index are pre-defined. ,in , This indicates the threshold at which the browning risk index rises from low to medium risk. This indicates the threshold value at which the browning risk index rises from medium to high risk; and it is based on the comprehensive browning risk index. The range of values ​​is used to initially classify browning risk: when At that time, it was determined to be at a low browning risk level; when At that time, it was determined to be at a medium browning risk level; when At that time, it was determined to be at a high browning risk level; Among them, the low browning risk level is: the drying temperature and humidity are within a safe range, enzyme activity is controllable, and non-enzymatic browning reaction is slow. Medium browning risk level: Local temperature or humidity deviates from the baseline, and the trend of enzymatic or non-enzymatic reactions is enhanced; High browning risk level: Temperature and humidity deviate significantly from the baseline or the drying stage approaches the sensitive critical point, and enzymatic or non-enzymatic browning reactions are significantly accelerated.

[0035] Specifically, in this embodiment, the independent identification and quantification steps for the risk of enzymatic browning are as follows: During the enzyme inactivation and blanching phase (material moisture content) >60%), during which enzymatic browning is dominant; The input parameters at this point should include at least the browning trend parameter. (Extracting the rate of temperature change) Water loss rate Rate of change of brightness and related weighting percentages); The input parameters also include a comprehensive browning risk index. (Key points extracted) This item reflects the basic conditions for enzyme activity and the real-time material temperature. The threshold temperature for polyphenol oxidase activity inhibition (This embodiment is preset to 55℃), color auxiliary parameters (brightness decrease) Preset brightness change threshold (In this embodiment, the brightness change threshold is preset to 0.1) )).

[0036] For rate-type data (temperature change rate) in the input parameters Water loss rate Rate of change of brightness Preprocessing is performed, and the data is normalized to the [0,1] interval using a linear mapping method; Calculate the characteristic quantities of enzymatic browning: ; in, This indicates the stage dominated by enzymatic browning. Normalized value of the rate of temperature change within the drying chamber at any given time; This indicates the stage dominated by enzymatic browning. Normalized value of the water loss rate of the material at any given time; This indicates the stage dominated by enzymatic browning. Normalized value of the rate of decrease in the brightness of the material surface at any given time; A quantitative characterization index representing the development trend of enzymatic browning, with a value range of [0,1]. The larger the value, the higher the probability and the faster the rate of enzymatic browning. In the calculation of enzymatic browning characteristic parameters, the weights of each parameter are allocated based on the dominant characteristics of enzymatic browning in the enzyme-inactivating blanching interval, and the sum is combined with the browning trend parameter. Weight matching for the corresponding stage; The enzymatic browning trend parameters were calculated as follows: ; in, The preferred fusion weights for enzymatic browning characteristic quantities within the enzyme-inactivating blanching range are as follows: ; Preset enzymatic browning threshold: Set (Low-to-medium risk threshold) (Medium-to-high risk threshold) (Enzymatic browning threshold determined based on experimental data); Preliminary grading is performed based on a preset enzymatic browning threshold: when and Preliminary assessment indicates low risk of enzymatic browning; when and Preliminary assessment indicates medium risk of enzymatic browning. when and Preliminary assessment indicates a high risk of enzymatic browning.

[0037] Furthermore, calculate the decrease in brightness: ( Initial brightness, (For real-time brightness), the initial risk level is corrected: If the initial assessment is low / medium risk, but (0.1) The risk level has been raised by one level. If initially determined to be high risk, and Maintaining a high-risk level triggers emergency enzyme inactivation regulation; If the color parameter is within the safe range ( ): Retain the preliminary classification results; Finally, risk quantification and output are performed: Low risk (corrected): Enzyme activity is controllable, output risk quantification value is 0.1~0.3, and the regulation direction is to maintain the current reference temperature and humidity and stably inactivate the enzyme; Medium risk (corrected): Enzyme activity increases, output risk quantification value is 0.3~0.6, the regulation direction is to increase temperature by 1~2℃, maintain stable humidity, and accelerate enzyme inactivation rate; High risk (corrected): Enzyme activity is high, output risk quantification value ≥0.6, regulation direction is to increase temperature by 2~3℃, limit the rate of humidity decrease, and urgently inhibit enzyme activity.

[0038] The steps for independently determining and quantifying the risk of non-enzymatic browning are as follows: The real-time moisture content of the material is obtained by the moisture content detection module. ,when When the concentration is ≤60%, it is determined to be in the constant-rate dehydration zone or the deceleration color fixation zone (non-enzymatic browning-dominated stage), and this discrimination procedure is initiated: At this point, the main input parameters include: browning trend parameters. (Extracting the rate of change in humidity) rate of change of red and green axes and related weighting percentages), comprehensive browning risk index (Key points extracted) and Item), material state parameters (material water activity) Surface-internal moisture gradient Color auxiliary parameters (red and green axis offset) Preset color offset threshold (In this embodiment, the preset color shift threshold is preferably 0.08) )); For the rate class and gradient class data in the input parameters ( , , Preprocessing is performed, and the data is normalized to the [0,1] interval using a linear mapping method; Calculate the characteristic quantities of non-enzymatic browning: ; in, This indicates that the non-enzymatic browning stage is dominant. Normalized value of the rate of change of relative humidity inside the drying chamber at all times; This indicates that the non-enzymatic browning stage is dominant. Normalized value of the water loss rate of the material at any given time; This indicates that the non-enzymatic browning stage is dominant. The normalized value of the rate of increase of the red and green axis parameters on the material surface at any given time; A quantitative characterization index representing the development trend of non-enzymatic browning, with a value range of [0,1]. The larger the value, the higher the reaction intensity of non-enzymatic browning and the more serious the damage to color. Furthermore, in the calculation of non-enzymatic browning characteristic parameters, the weights of the above-mentioned components are allocated based on the characteristics of the dominant stage of non-enzymatic browning, and the sum is combined with the browning trend parameter. Weight matching for the corresponding stage; Calculate non-enzymatic browning trend parameters: ; In the formula, The fusion weights of non-enzymatic browning characteristics at this stage are preferably... ; Preset non-enzymatic browning threshold: Set (Low-to-medium risk threshold) (Medium-to-high risk threshold), (Non-enzymatic browning threshold determined based on experimental data); Preliminary grading is performed based on a preset non-enzymatic browning threshold: when and Preliminary assessment indicates low risk of non-enzymatic browning; when and Preliminary assessment indicates non-enzymatic browning is of medium risk. when and Preliminary assessment indicates a high risk of non-enzymatic browning.

[0039] Further, calculate the red-green axis offset: ( This serves as the initial reference value for the red and green axes. (Real-time red and green axis values) are used to correct the initial risk level: If the initial assessment is low / medium risk, but ( The preferred value is 0.08. The risk level has been raised by one level. If initially determined to be high risk, and Maintaining a high-risk level triggers emergency temperature and humidity control measures. If the color parameter is within the safe range ( ): Retain the preliminary classification results.

[0040] Finally, risk quantification and output are performed: Low risk (after correction): Maillard response is slow, output risk quantification value is 0.1~0.25, the control direction is to maintain the current temperature and humidity gradient, and to achieve stable dehydration; Medium risk (after correction): The Maillard reaction is enhanced, and the output risk quantification value is 0.25~0.55. The control direction is to reduce the temperature by 1~1.5℃, increase the humidity by 3~4%RH, and slow down the reaction rate. High risk (after correction): The Maillard reaction is violent, with an output risk quantification value ≥0.55. The control direction is to lower the temperature by 1.5~2℃ and increase the humidity by 4~5%RH, which will intensify the inhibition of the reaction.

[0041] Furthermore, in this embodiment, after obtaining the comprehensive browning risk index... Subsequently, color parameters (brightness parameter and red-green axis parameter) are further introduced as auxiliary criteria to jointly determine the browning risk level. Specifically, the brightness parameter and red-green axis parameter are compared with the preset color reference range respectively. When the decrease in brightness parameter exceeds the preset brightness change threshold, or the red-green axis parameter shifts positively and exceeds the preset color shift threshold, it is determined that the surface of daylily under the current dried state has shown an accelerated browning color evolution trend. When the browning trend characterized by the color parameter is consistent with the comprehensive browning risk index When the obtained risk levels are inconsistent, the control decision unit 32 prioritizes adjusting the browning risk level upward based on the apparent browning trend reflected by the color parameters: Based on the collected color parameters, calculate the color auxiliary judgment function: ; In the formula, This indicates that the color evolution under the current dry state is accelerating towards browning; This indicates that the color parameters are within the safe range, suggesting that the apparent browning risk is acceptable; Indicates relative to initial brightness The larger the decrease in color, the darker the surface color and the more severe the browning. Indicates the time during the drying process. The brightness value measured at that time; This represents the offset of the red and green axis parameters, where This serves as the initial reference value for the red and green axes. This represents the values ​​measured on the red and green axes; This indicates a preset color shift threshold. When the red-green axis shift exceeds this value, it is determined to be an enhanced apparent browning. This indicates a preset threshold for brightness change. When the decrease in brightness exceeds this value, it is determined to be an increase in apparent browning. Introducing color parameters into the browning risk index to generate a joint correction index: ; A corrected browning risk index supplemented by color parameters; This is the weighting coefficient for the color parameter, used to adjust the degree of influence of the color parameter risk assessment; it is set according to experimental experience (0.1~0.3) to ensure stability; and subsequent settings will still follow the same principle. Thresholds are used to classify risk levels as low / medium / high; After completing the browning risk level assessment and correction, the baseline temperature and humidity control parameters were used. The call and current drying phase Temperature and humidity parameters , , as a scalar reference temperature and humidity parameter; Browning risk comprehensive index based on the corrected browning risk level A two-way browning risk discrimination algorithm is used to determine the baseline process control parameters (temperature setpoint). and relative humidity setting value This will be corrected to generate a real-time drying temperature setpoint for the current drying stage. and real-time dry relative humidity setpoint : ; ; in, This is the temperature risk suppression coefficient, used to reduce the drying temperature when the risk of browning increases; This is a humidity-release adjustment coefficient used to increase drying humidity when the risk of browning increases; among which, and All of these were pre-calibrated based on the equipment's rated adjustment capacity and safe temperature and humidity variation range. In this embodiment, the "bidirectional" in the bidirectional browning risk discrimination algorithm means that the algorithm can simultaneously identify both enzymatic browning risk and non-enzymatic browning risk, and select the corresponding regulatory strategy based on the dominant risk in the drying stage, rather than simultaneously executing opposing regulatory operations; the input of the algorithm is the browning trend parameter. The current drying stage (determined by moisture content), real-time material state parameters (moisture content, color parameters), and the output are the corrected temperature and humidity setpoints; specifically, the output is determined by the real-time moisture content. Determine the current drying stage: when >60%: This is determined to be the stage dominated by enzymatic browning, and key monitoring should be conducted on enzymatic browning risk indicators. when ≤60%: This indicates the stage dominated by non-enzymatic browning, and non-enzymatic browning risk indicators should be monitored.

[0042] Furthermore, to avoid abnormal water loss or thermal shock on the material surface caused by rapid changes in temperature and humidity setpoints, the control decision unit 32 uses a corrected comprehensive browning risk index. Gradient constraints are introduced to the rates of change of drying temperature and relative humidity, and temperature change gradient constraint parameters are generated respectively. and humidity change gradient constraint parameters And limit it to not exceed the upper bound function of the gradient associated with browning risk: ; ; Based on the corrected comprehensive index of browning risk (combining temperature and humidity, water activity, moisture gradient, and color parameters). Generate the upper bound function for the gradient: ; ; Compare the expected rate of change of temperature and humidity with the corresponding upper limit of the gradient. If the expected rate of change is less than the upper limit, the expected rate is directly used as the actual gradient. If the expected rate of change exceeds the upper limit, the actual gradient is limited to the upper limit value. The corrected temperature and humidity settings must meet the temperature change gradient requirements. and humidity change gradient If the gradient limit is exceeded, it will be gradually corrected according to the upper limit of the gradient (to avoid sudden environmental changes). The actual gradient parameters are generated after the above judgment. and Used to control the rate of change of temperature and humidity: ; In the formula, This indicates the upper limit of the reference temperature change rate (°C / min), representing the maximum allowable temperature change rate under risk-free conditions. This indicates the upper limit of the baseline humidity change rate (% / min), representing the maximum allowable humidity change rate under risk-free conditions. This represents the temperature gradient risk adjustment coefficient, used to reduce the permissible rate of temperature change based on the browning risk. This represents the humidity gradient risk adjustment coefficient, used to reduce the permissible rate of humidity change based on the browning risk. This indicates the upper limit of the corrected temperature gradient; This indicates the upper limit of the corrected humidity gradient; It represents the actual temperature change gradient (°C / min) and is used to control the heating or cooling rate; This indicates the actual humidity change gradient (% / min), used to control the dehumidification or humidification rate; In this embodiment, when the risk of enzymatic browning is high: Temperature control: Increase the temperature setpoint (1~3℃ above the reference temperature) to accelerate the heating rate (but not exceeding the temperature change gradient constraint). ), used to rapidly destroy residual enzyme activity.

[0043] Humidity control: Maintain a high humidity setting (±2%RH based on the reference humidity) to avoid excessive water loss leading to surface crusting, ensure uniform heat transfer, and improve enzyme inactivation effect.

[0044] When there is a high risk of non-enzymatic browning: Temperature control: Lower the temperature setpoint (from the reference temperature by -1 to 2°C) to slow down the heating rate, with the aim of reducing the Maillard reaction rate; Humidity control: Appropriately increase the humidity setting value (3~5%RH on the basis of the reference humidity) to alleviate the increase in reducing sugar / amino acid concentration caused by the rapid decrease in the moisture content of the material and inhibit non-enzymatic browning.

[0045] Based on the current changes in material moisture content, the control decision unit 32 introduces the drying air velocity. and mass transfer efficiency coefficient The stage duration control parameters for the current drying stage are calculated. : ; In the formula, This indicates the initial moisture content of the material in the current drying stage; This indicates the target moisture content for the current drying stage; Indicates the duration of this drying stage; This represents the mass transfer efficiency coefficient, used to characterize the efficiency of moisture migration from the surface to the interior of a material (value range: 0.3~0.9), and is dimensionless. Finally, the control decision unit 32 will generate the drying temperature setpoint. Dry relative humidity setting value Temperature change gradient constraint parameters Humidity change gradient constraint parameters and stage duration control parameters As a set of structured control parameters The output is sent to the environmental control execution unit 4 to drive the heating, dehumidification and airflow regulation devices to achieve coordinated, stable and browning-preventing control of temperature and humidity in the drying chamber.

[0046] Among them, the closed-loop PID control module 33 is used to compare the corrected temperature and humidity setpoint with the actual temperature and humidity parameters fed back by the environmental state sensing unit 1, and generate corresponding execution control commands based on the temperature and humidity decoupled PID control algorithm. The closed-loop PID control module 33 introduces decoupling coefficients in the temperature control loop and the humidity control loop respectively to reduce the mutual interference between temperature regulation and humidity regulation, and outputs the execution control command to the environmental regulation execution unit 4 to achieve coordinated and stable regulation of temperature and humidity in the drying chamber.

[0047] Furthermore, the closed-loop PID control module 33 generates corresponding execution control commands based on the temperature and humidity decoupled PID control algorithm, and the specific steps involved are as follows: The real-time drying temperature setpoint output by the control decision unit 32 is obtained respectively. Relative humidity setpoint And the actual dry-bulb temperature monitored by the environmental state sensing unit (1) relative humidity The temperature error was calculated. and humidity error ; In this embodiment, temperature error : ; Humidity error : ; In the formula, Temperature error is defined as the difference between the set temperature and the actual temperature, reflecting the magnitude and direction of the cavity temperature deviating from the set value. Humidity error is defined as the difference between the set humidity and the actual humidity, reflecting the magnitude and direction of the deviation of the cavity humidity from the set value. Based on the temperature and humidity error, a decoupled PID algorithm is used to calculate the temperature control command separately. Humidity control instructions ; In this embodiment: ; ; In the formula, This is the temperature control proportional coefficient, which represents the instantaneous linear amplification of the temperature error to the temperature control command, used for rapid response to temperature deviations. This is the integral coefficient for temperature control, representing the impact of temperature error accumulating over time on the temperature control command, used to eliminate steady-state temperature deviation; This is the temperature control differential coefficient, representing the effect of the rate of change of temperature error on the temperature control command, used to suppress rapid temperature fluctuations and oscillations; This is the humidity control proportional coefficient, which represents the instantaneous linear amplification of the humidity error to the humidity control command, used for rapid response to humidity deviations; This is the integral coefficient for humidity control, representing the impact of humidity error accumulating over time on the humidity control command, used to eliminate steady-state humidity deviation; The differential coefficient for humidity control represents the effect of the rate of change of humidity error on the humidity control command, and is used to suppress rapid fluctuations and oscillations in humidity. This is the temperature and humidity decoupling coefficient, used to correct interference signals caused by humidity changes in the temperature loop, thereby reducing the impact of temperature and humidity loop coupling effect on temperature control. This is the humidity-temperature decoupling coefficient, used to correct interference signals caused by temperature changes in the humidity loop, thereby reducing the impact of the temperature-humidity loop coupling effect on humidity control. This represents the control time variable, indicating the continuous time of system operation; This represents the integration time variable, used for calculating cumulative error; This indicates a temperature control command, which is an output signal that controls the heating or cooling device inside the drying chamber, used to adjust the actual temperature of the chamber to approach the set temperature. This indicates a humidity control command, representing the output signal that controls the humidification or dehumidification device, used to adjust the actual relative humidity of the cavity towards the set humidity. Specifically, temperature and humidity decoupling coefficient During the equipment calibration phase, a step change of a preset amplitude is applied to the relative humidity within the drying chamber, and the corresponding dry-bulb temperature response curve is collected. Based on the rate of change of temperature response to humidity disturbance, the humidity-temperature cross-coupling channel is systematically identified, and the temperature-humidity decoupling coefficient is obtained. The initial value, used to characterize the basic disturbance intensity of humidity change on temperature control during the current drying stage, is calculated as follows: ; in, This represents the change in relative humidity. This represents the corresponding temperature response change. Humidity-temperature decoupling coefficient During the equipment calibration phase, a preset amplitude change is applied to the temperature of the drying chamber during the drying stage, and the dynamic response value of relative humidity is collected simultaneously. Based on the proportional relationship between the temperature change and the humidity response change, the humidity-temperature decoupling coefficient is calculated. The initial value is used to characterize the basic disturbance intensity of temperature change on humidity control during the current drying stage, and its calculation method is as follows: ; In the formula, Indicates the amount of temperature change; This indicates the corresponding change in humidity response; Furthermore, during the drying process, the aforementioned and It can be updated or modified according to the material moisture content, browning trend parameters or drying stage switching to adapt to the temperature and humidity coupling characteristics under different drying stages.

[0048] The temperature and humidity change gradient constraint parameters output by the control decision unit 32 , Introducing control commands (temperature control commands) Humidity control instructions Rate limiting is applied to temperature and humidity control signals: ; ; In the formula, clip(*) (clipping function) is used to limit the rate of change of control commands to prevent material dehydration or thermal shock caused by drastic fluctuations in temperature and humidity; This indicates the temperature control command for the previous sampling period, and the temperature control value output by the closed loop at the previous moment. This indicates the humidity control command for the previous sampling period, and the humidity control value output by the closed loop at the previous moment. This indicates the control sampling period, which is the time interval between updates to the temperature and humidity control signal; This indicates the final temperature control command after gradient limiting; This indicates the final humidity control command after gradient limiting; The control command after gradient constraint is smoothed by low-pass filtering to generate a smoothed temperature control command. Humidity control instructions To reduce high-frequency interference, the temperature control command is smoothed. Humidity control instructions The output is sent to the environmental control execution unit 4 to drive heating, cooling, humidification, dehumidification and fan devices, so as to realize closed-loop precise regulation of temperature and humidity in the drying chamber.

[0049] In this embodiment, the smoothed temperature control command : ; Humidity control command after smoothing : ; In the formula, For filter coefficients ( The value is used to adjust the smoothness of the low-pass filter; the larger the value, the faster the response, and the smaller the value, the stronger the smoothing effect. The temperature control command is smoothed out. This indicates the smoothed humidity control command.

[0050] Furthermore, the multi-segment temperature and humidity closed-loop control system for inhibiting browning during the drying of daylilies also includes an environmental control execution unit 4. The environmental control execution unit 4, according to the aforementioned temperature and humidity control strategy, coordinates the temperature and humidity within the drying chamber. The specific steps involved are as follows: Receives smooth temperature control commands output by the closed-loop PID control module 33 With smooth humidity control command ; According to the temperature control command Adjust the power of the heating device, cooling device, and fan inside the drying chamber to dynamically regulate the chamber temperature and record the actual temperature. Feedback is sent to the closed-loop PID control module 33 to form a temperature closed loop; According to the humidity control command Adjust the humidification device, dehumidification device, and fan status within the drying chamber to dynamically regulate the relative humidity of the chamber and record the actual humidity. Feedback is sent to the closed-loop PID control module 33 to form a humidity closed loop; Furthermore, temperature and humidity control commands are executed synchronously in sequence, and temperature and humidity change gradient constraint parameters are incorporated. The control signal after low-pass filtering limits the output rate of the actuator to prevent sudden changes in temperature and humidity from affecting the quality of the material. Specifically, a closed-loop control mechanism with enzymatic browning and non-enzymatic browning as dual risk indicators is established. Enzymatic browning is suppressed in the early stage, and non-enzymatic browning is controlled in the later stage to achieve dynamic regulation and ensure the color stability and quality control of daylilies throughout the post-harvest and drying process. Using temperature and humidity decoupling coefficient Together with the coordinated control logic, it achieves a balance between closed-loop stability and rapid response in the temperature and humidity regulation loop.

[0051] In this embodiment, the actuator includes at least: Heating device for increasing the temperature of the cavity; A refrigeration device used to lower the temperature of the cavity; Humidification device, used to increase the humidity of the cavity; Dehumidification device, used to reduce the humidity in the cavity; The fan is used for air circulation and uniform temperature and humidity distribution in the cavity; the operating status of each actuator and the temperature and humidity of the cavity are fed back to the environmental status sensing unit 1 in real time to support the control decision unit 32 in dynamically adjusting the gradient constraints, PID parameters and filter coefficients to achieve closed-loop optimization control.

[0052] Example 2: The difference between Example 2 and Example 1 is that this example introduces a multi-segment temperature and humidity closed-loop control method for inhibiting browning of dried daylily, which is used in a multi-segment temperature and humidity closed-loop control system for inhibiting browning of dried daylily.

[0053] A multi-segment closed-loop temperature and humidity control method for inhibiting browning in dried daylily, used in any of the above-mentioned multi-segment closed-loop temperature and humidity control systems for inhibiting browning in dried daylily, comprising the following steps: S1. Collect environmental state parameters and material state parameters related to browning in the drying chamber. The environmental state parameters include dry bulb temperature and relative humidity, and the material state parameters include material moisture content, lightness parameters and red-green axis parameters. S2. Based on the environmental state parameters and material state parameters, quantitatively analyze the browning development trend during the drying process of daylily, and generate browning trend parameters and browning parameter set for closed-loop control input. S3. Based on the browning trend parameters and material state parameters, a piecewise function mapping model is used to divide the entire life cycle of daylily drying into stages, and multi-stage temperature and humidity control strategies are generated according to different drying stages and browning risk levels. S4. Based on the multi-segment temperature and humidity control strategy generated in step S3, adjust the temperature and humidity inside the drying chamber in real time to suppress browning during the drying process of daylilies, ensure that each drying stage is executed according to the predetermined temperature and humidity change gradient, and dynamically correct the control strategy based on real-time monitoring data.

[0054] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely preferred examples and are not intended to limit the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the present invention as claimed. The scope of protection of the present invention is defined by the appended claims and their equivalents.

Claims

1. A multi-segment temperature and humidity closed-loop control system for inhibiting browning during the drying of daylilies, characterized in that, include: An environmental state sensing unit (1) is used to acquire environmental state parameters and material state parameters related to browning within the drying chamber. The environmental state parameters include the dry bulb temperature and relative humidity inside the drying chamber, and the material state parameters include the material moisture content, brightness parameter, and red-green axis parameter. Browning trend assessment unit (2) quantifies the browning trend during the drying process of daylily based on the environmental state parameters and material state parameters, and generates a set of browning trend parameters and browning parameters. ; The control decision unit (3) divides the entire life cycle of daylily drying into stages based on the browning trend parameters and material state parameters using a piecewise function mapping model. According to different drying stages and browning risk levels, it generates multi-stage temperature and humidity control strategies and dynamically modifies the temperature and humidity control strategies to continuously adjust the temperature and humidity in the drying chamber. At the same time, it introduces brightness parameters and red-green axis parameters to adjust the temperature and humidity control strategies to suppress browning during the drying process of daylilies. The environmental control execution unit (4) adjusts the temperature and humidity inside the drying chamber in a coordinated manner according to the temperature and humidity control strategy.

2. The multi-segment temperature and humidity closed-loop control system for inhibiting browning during the drying of daylilies according to claim 1, characterized in that: The environmental state sensing unit (1) includes a multi-point temperature and humidity monitoring module (11), a moisture content detection module (12), and a color state acquisition module (13). Among them, the multi-point temperature and humidity monitoring module (11) is used to collect the dry bulb temperature and relative humidity at different spatial locations in the drying chamber in real time; The moisture content detection module (12) uses a weighing sensor to continuously monitor the weight change of daylily during the drying process. By calculating the water loss rate of the material, the moisture content of the material is obtained. The color status acquisition module (13) acquires images of the daylily surface and captures RGB images of the daylily surface in real time and converts them into Lab color space data to extract lightness parameters and red-green axis parameters to characterize the color change trend of the daylily surface.

3. The multi-segment temperature and humidity closed-loop control system for inhibiting browning during the drying of daylilies according to claim 1, characterized in that: The browning trend assessment unit (2) constructs browning trend parameters, and the specific steps involved are as follows: Environmental and material state parameters are normalized and mapped to standard ranges. ; Furthermore, by introducing the time dimension, characteristic quantities reflecting the rate of change in temperature and humidity, the rate of material water loss, and the rate of color change are constructed. The rates of temperature and humidity change, material water loss rate, and color change rate were used to construct a set of browning parameters. ; And the set of browning parameters The browning trend parameters are obtained by weighted fusion of various feature quantities. .

4. The multi-segment temperature and humidity closed-loop control system for inhibiting browning during the drying of daylilies according to claim 1, characterized in that: The control decision unit (3) includes a multi-stage process formula library module (31), a browning risk assessment logic module (32), and a closed-loop PID control module (33). The multi-stage process formula library module (31) is used to store the set of process control parameters corresponding to different browning risk levels, and to divide the entire life cycle of daylily drying into stages based on the piecewise function mapping model, and to define the temperature set value and relative humidity set value corresponding to each interval, and to generate the reference temperature and humidity control parameters for the current drying stage. The piecewise function mapping model includes a drying stage determination function and a temperature and humidity piecewise mapping function. The browning risk assessment logic module (32) dynamically corrects the baseline temperature and humidity control parameters based on the browning trend parameters and uses a two-way browning risk discrimination algorithm to generate corrected temperature and humidity setpoints. The closed-loop PID control module (33) is used to compare the corrected temperature and humidity setpoint with the actual temperature and humidity parameters fed back by the environmental state sensing unit (1), and generate corresponding execution control instructions based on the temperature and humidity decoupled PID control algorithm. The closed-loop PID control module (33) introduces decoupling coefficients in the temperature control loop and the humidity control loop respectively to reduce the mutual interference between temperature regulation and humidity regulation, and outputs the execution control command to the environmental regulation execution unit (4).

5. The multi-segment temperature and humidity closed-loop control system for inhibiting browning during the drying of daylilies according to claim 4, characterized in that: The multi-stage process formula library module (31) generates reference temperature and humidity control parameters for the current drying stage, and the specific steps involved are as follows: Get current drying time The system also monitors the real-time moisture content of the material and determines the current drying range using a drying stage determination function. The drying zone It includes at least the enzyme-inactivating blanching zone, the constant-rate dehydration zone, and the deceleration color-fixing zone; Based on the determined drying range The corresponding temperature setpoint and relative humidity setpoint are obtained from the set of process control parameters through the temperature and humidity piecewise mapping function; The temperature setpoint and relative humidity setpoint are combined to generate reference temperature and humidity control parameters for the current drying stage.

6. The multi-segment temperature and humidity closed-loop control system for inhibiting browning during the drying of daylilies according to claim 4, characterized in that: The browning risk assessment logic module (32) generates the corrected temperature and humidity setpoints, and the specific steps involved are as follows: Based on the browning trend parameters output by the browning trend assessment unit (2) The system uses the current material state parameters and introduces color parameters as an auxiliary criterion to independently distinguish between the risks of enzymatic browning and non-enzymatic browning. When the risk index of enzymatic browning exceeds the preset threshold, it is determined that there is a risk of enzymatic browning in the current drying stage. When the non-enzymatic browning risk index exceeds the preset threshold, it is determined that there is a non-enzymatic browning risk in the current drying stage. To address the risk of enzymatic browning, a temperature and humidity control approach aimed at inhibiting enzyme activity was determined. To address the risk of non-enzymatic browning, a temperature and humidity control approach was identified with the goal of reducing the browning reaction rate under high temperature and high humidity conditions. Based on the reference temperature and humidity control parameters, and in accordance with the determined control direction, a two-way browning risk discrimination algorithm is used to correct the temperature setpoint and relative humidity setpoint, generating temperature and humidity correction setpoints for the current drying stage.

7. The multi-segment temperature and humidity closed-loop control system for inhibiting browning during the drying of daylilies according to claim 4, characterized in that: The closed-loop PID control module (33) generates corresponding execution control commands based on the temperature and humidity decoupled PID control algorithm. The specific steps involved are as follows: The real-time drying temperature setpoint output by the control decision unit (32) is obtained respectively. Relative humidity setpoint And the actual dry-bulb temperature monitored by the environmental state sensing unit (1) relative humidity The temperature error was calculated. and humidity error ; Based on the temperature and humidity error, a decoupled PID algorithm is used to calculate the temperature control command separately. Humidity control instructions ; The temperature and humidity change gradient constraint parameters output by the control decision unit (32) , Introduce control commands to limit the rate of temperature and humidity control signals; The control command after gradient constraint is smoothed by low-pass filtering to generate a smoothed temperature control command. Humidity control instructions .

8. The multi-segment temperature and humidity closed-loop control system for inhibiting browning during the drying of daylilies according to claim 1, characterized in that: The environmental control unit (4) coordinates the temperature and humidity within the drying chamber, and the specific steps involved are as follows: Receive the smooth temperature control command output by the closed-loop PID control module (33) With smooth humidity control command ; According to the temperature control command Adjust the power of the heating device, cooling device, and fan inside the drying chamber to dynamically regulate the chamber temperature and record the actual temperature. Feedback is sent to the closed-loop PID control module (33) to form a temperature closed loop; According to the humidity control command Adjust the humidification device, dehumidification device, and fan status within the drying chamber to dynamically regulate the relative humidity of the chamber and record the actual humidity. Feedback is sent to the closed-loop PID control module (33) to form a humidity closed loop.

9. A multi-segment closed-loop temperature and humidity control method for inhibiting browning in dried daylily, used in the multi-segment closed-loop temperature and humidity control system for inhibiting browning in dried daylily as described in any one of claims 1-8, characterized in that, Includes the following steps: S1. Collect environmental state parameters and material state parameters related to browning in the drying chamber. The environmental state parameters include dry bulb temperature and relative humidity, and the material state parameters include material moisture content, lightness parameters and red-green axis parameters. S2. Based on the environmental state parameters and material state parameters, quantitatively analyze the browning development trend during the drying process of daylily, and generate browning trend parameters and browning parameter set for closed-loop control input. S3. Based on the browning trend parameters and material state parameters, a piecewise function mapping model is used to divide the entire life cycle of daylily drying into stages, and multi-stage temperature and humidity control strategies are generated according to different drying stages and browning risk levels. S4. Based on the multi-segment temperature and humidity control strategy generated in step S3, adjust the temperature and humidity inside the drying chamber in real time to suppress browning during the drying process of daylilies, ensure that each drying stage is executed according to the predetermined temperature and humidity change gradient, and dynamically correct the control strategy based on real-time monitoring data.

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