Control method, device, equipment and system for plant extraction and leaching link

Abstract

The invention provides a control method, device, equipment and system for a plant extraction and leaching link, and belongs to the technical field of plant extraction. The method comprises the steps that image information from a camera device is obtained, the image information comprises image information in a leacher, and a leaching link in the plant extraction process is executed in the leacher; obtaining leaching live information according to the image information, wherein the leaching live information is used for indicating the operation state of the leaching link; obtaining measurement information from the sensor, wherein the measurement information is associated with the leaching efficiency of the plant raw material; generating a control instruction for target equipment according to the leaching live information and the measurement information; and sending the control instruction to the target equipment, so that the target equipment adjusts the working state according to the control instruction. According to the method, relevant equipment parameters can be timely and accurately adjusted in a leaching link, so that the leaching efficiency and the plant extraction quality are improved, and meanwhile, the system stability is ensured.

Description

Technical Field

[0001] The present application relates to the field of plant extraction technology, and in particular to a control method, device, equipment and system for a plant extraction and leaching process. Background Art

[0002] The extraction of plant active ingredients refers to the process of extracting active ingredients from plant raw materials using solvents. During this process, chemical components (such as medicinal ingredients, aroma compounds, and nutrients) are dissolved from the plant raw materials using solvents (such as water, ethanol, and methanol). Traditional techniques for extracting plant active ingredients have numerous drawbacks. In actual production, plant raw material characteristics fluctuate frequently. Plant raw materials from different origins and batches exhibit significant variations in key indicators such as moisture content, particle size, and active ingredient content. Existing extraction systems often face these fluctuations only through frequent adjustments to relevant equipment parameters. This not only affects system stability but also makes timely and accurate adjustments difficult, resulting in varying extraction efficiency and quality. Summary of the Invention

[0003] The present application provides a control method, device, equipment and system for the plant extraction and leaching process, so as to achieve timely and accurate adjustment of relevant equipment parameters in the leaching process to improve the leaching efficiency and plant extraction quality while ensuring system stability.

[0004] The present application provides a control method for plant extraction and leaching, including: Acquiring image information from a camera device, the image information including image information within an extractor, where an extraction step in the plant extraction process is performed; Acquiring leaching real-time information according to the image information, wherein the leaching real-time information is used to indicate the operating status of the leaching process; obtaining measurement information from a sensor, the measurement information being correlated to a leaching efficiency of the plant material; generating a control instruction for a target device according to the actual leaching information and the measurement information; The control instruction is sent to the target device, so that the target device adjusts its working state according to the control instruction.

[0005] According to the control method for the plant extraction and leaching link provided in the present application, the actual leaching information includes the sprinkling speed information, the material level information of the plant raw material in the extractor, and the liquid level information of the leachate in the extractor, and the measurement information includes the temperature information of the mixed leachate at the inlet of the circulation pump and the saturation information of the leachate solvent; the control instructions for the target device are generated according to the actual leaching information and the measurement information, including: obtaining the fluctuation amplitude value and the fluctuation period value of the pumping frequency of the circulation pump, and the circulation pump is used to circulate the leachate; determining the increase rate of the effective component in the leachate according to the saturation information of the leachate; generating the control instructions for the circulation pump according to the sprinkling speed information, the material level information, the liquid level information, the temperature information, the increase rate of the effective component, the fluctuation amplitude value and the fluctuation period value, and the control instructions are used to instruct the circulation pump to adjust the pumping frequency.

[0006] According to the control method for the plant extraction and leaching link provided in the present application, the image information includes image information of the leachate, and determining the increase rate of the effective ingredients in the leachate based on the saturation information of the leachate solvent includes: obtaining the color change of the leachate in the extractor based on the image information of the leachate; and determining the increase rate of the effective ingredients in the leachate based on the color change and the saturation information of the leachate solvent.

[0007] According to the control method for the plant extraction and leaching link provided in the present application, the image information includes continuous video frame images, the actual leaching information includes leaching speed information, and the actual leaching information is obtained based on the image information, including: preprocessing the video frame image to obtain a target video frame image; calculating the target video frame image through an optical flow constraint equation to obtain the average motion vector of the pixel points in a preset window; and determining the leaching speed based on the average motion vector.

[0008] According to the control method for the plant extraction and leaching link provided by the present application, the image information includes a reference marker image, a plant raw material image and an extract image, and the actual leaching information includes the material level information of the plant raw material in the extractor, and / or the liquid level information of the extract in the extractor, and the obtaining of the actual leaching information based on the image information includes: obtaining the pixel length of the reference marker based on the reference marker image; determining the proportional factor based on the actual length of the reference marker and the pixel length; obtaining the boundary of the plant raw material in the plant raw material image and / or the boundary of the extract in the extract image; obtaining the pixel height of the plant raw material based on the boundary of the plant raw material, and / or obtaining the pixel height of the extract based on the boundary of the extract; determining the material level information based on the proportional factor and the pixel height of the plant raw material, and / or determining the liquid level information based on the proportional factor and the pixel height of the extract.

[0009] According to the control method for the plant extraction and leaching link provided in the present application, the measurement information includes the temperature information of the mixed leachate at the inlet of the circulation pump, and the control instructions for the target device are generated based on the actual leaching information and the measurement information, including: obtaining the type and current leaching stage of the plant raw material; generating control instructions for the intelligent temperature control system based on the type, the current leaching stage and the temperature information, the control instructions are used to instruct the intelligent temperature control system to adjust the heating power, and the intelligent temperature control system is used to adjust the temperature of the mixed leachate at the inlet of the circulation pump.

[0010] According to the control method for the plant extraction and leaching link provided in the present application, the actual leaching information includes the flatness of the surface of the plant raw material in the extractor, and the actual leaching information is obtained based on the image information, including: inputting the image information into a preset model to obtain the probability that each pixel in the image output by the preset model belongs to the plant raw material; segmenting the area where the plant raw material is located in the image information according to the probability to obtain a segmentation result; and determining the flatness of the surface of the plant raw material in the extractor based on the segmentation result.

[0011] The present application also provides a control device for the plant extraction and leaching process, comprising: a first acquiring unit, configured to acquire image information from a camera device, wherein the image information includes image information within an extractor, wherein the leaching step in the plant extraction process is performed within the extractor; a second acquiring unit, configured to acquire leaching status information according to the image information, wherein the leaching status information is used to indicate an operating state of the leaching process; a third acquiring unit, configured to acquire measurement information from the sensor, wherein the measurement information is associated with the leaching efficiency of the plant material; a generating unit, configured to generate a control instruction for a target device according to the actual leaching information and the measurement information; The sending unit is configured to send the control instruction to the target device, so that the target device adjusts its working state according to the control instruction.

[0012] The present application also provides an edge computing control system, including an edge server and a computing controller; The edge server is used to obtain image information from a camera device, the image information includes image information inside an extractor, and the extraction link in the plant extraction process is performed in the extractor; and is used to obtain extraction status information based on the image information, and the extraction status information is used to indicate the operating status of the extraction link; and is used to obtain measurement information from a sensor, and the measurement information is associated with the extraction efficiency of the plant raw material; the computing controller is used to generate a control instruction for a target device based on the extraction status information and the measurement information from the edge server, and is used to send the control instruction to the target device, so that the target device adjusts its working status according to the control instruction.

[0013] The present application also provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the control method for the leaching step in the plant extraction process as described above is implemented.

[0014] The present application also provides a non-transitory computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the control method for the leaching step in the plant extraction process as described in any one of the above is implemented.

[0015] The present application also provides a computer program product, including a computer program, which, when executed by a processor, implements any of the above-described control methods for the leaching process in the plant extraction process.

[0016] The present application provides a control method, device, equipment and system for the plant extraction and leaching process. The method first obtains image information from a camera device, wherein the image information includes image information in the extractor, and the leaching process in the plant extraction process is performed in the extractor. Then, the leaching status information is obtained based on the image information, and the leaching status information is used to indicate the operating status of the leaching process. Then, measurement information from a sensor is obtained, and the measurement information is associated with the leaching efficiency of the plant material. Then, a control instruction for a target device is generated based on the leaching status information and the measurement information. Finally, the control instruction is sent to the target device so that the target device adjusts its working state according to the control instruction. In this way, the operating status of the leaching process and the leaching efficiency of the plant material can be monitored in real time, and then the relevant equipment parameters can be adjusted in a timely and accurate manner to improve the leaching efficiency and the quality of plant extraction while ensuring system stability. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the technical solutions in the present invention or the prior art, a brief introduction is given below to the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0018] Figure 1 It is a structural schematic diagram of a plant extraction system provided in this application.

[0019] Figure 2 This is a flow chart of a control method for plant extraction and leaching provided in this application.

[0020] Figure 3 This is a schematic diagram of the composition of a plant extraction system provided in this application.

[0021] Figure 4 This is a block diagram of the functional units of a control device for plant extraction and leaching provided by this application.

[0022] Figure 5 It is a structural diagram of the electronic device provided in this application.

[0023] Reference numerals: 1: Feeding scraper; 2: Sensor monitoring array ①; 3: Mixing oil tank; 4: Extractor microenvironment chamber; 5: Intelligent circulation pump; 6: Sensor monitoring array ②; 7: Hot water jacket; 8: Oil tank connector; 9: Oil tank; 10: Slag bin; 11: Slag scraper; 12: Disc; 13: Siphon spray; 14: Sensor monitoring array ③; 15: Camera; 16: Spray pipe; 17: Sensor monitoring array ④; 18: Sensor monitoring array ⑤; 19: Sensor monitoring array ⑥; 20: Edge computing control cabinet. DETAILED DESCRIPTION

[0024] To make the objectives, technical solutions, and advantages of the present invention more clear, the technical solutions of the present invention will be clearly and completely described below in conjunction with the accompanying drawings. Obviously, the embodiments described are only some of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts shall fall within the scope of protection of the present invention.

[0025] The terms "first," "second," and the like in the specification and claims of this application and the accompanying drawings are used to distinguish between different objects, not to describe a particular order. Furthermore, the terms "including," "having," and any variations thereof, are intended to cover non-exclusive inclusions. For example, a process, method, system, product, or apparatus comprising a series of steps or elements is not limited to the listed steps or elements but may optionally include steps or elements not listed, or may optionally include other steps or elements inherent to the process, method, product, or apparatus.

[0026] References herein to "embodiments" mean that a particular feature, structure, or characteristic described in connection with the embodiments may be included in at least one embodiment of the present application. The appearance of this phrase in various places in the specification does not necessarily refer to the same embodiment, nor does it constitute an independent or alternative embodiment that is mutually exclusive of other embodiments. It is understood, both explicitly and implicitly, by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0027] In the face of changes in the characteristics of plant raw materials, the existing leaching system can only frequently adjust the parameters of related equipment. This not only affects the stability of the system, but also makes it difficult to achieve timely and accurate adjustments, resulting in uneven leaching efficiency and quality.

[0028] To address the above issues, the present application provides a control method, device, equipment, and system for plant extraction and leaching. The embodiments of the present application are described in detail below with reference to the accompanying drawings.

[0029] See also Figure 1The plant extraction system includes a camera monitoring system, a sensor monitoring array, an intelligent circulation pump system, an intelligent temperature control system, a data analysis and decision-making center (edge ​​computing control system), and an extractor. The extractor can be equipped with multiple microenvironmental chambers, each with unique fluid dynamics tailored to the characteristics of the plant material, extraction temperature, leaching pulse characteristics, and active ingredient extraction requirements. The extractor itself is mechanically stable through mechanical calculations and engineering optimization. The camera monitoring system can consist of multiple industrial-grade cameras deployed at key locations within the extractor, allowing users to capture image information within the extractor. The sensor array includes temperature sensors made of specialized materials and advanced sensing technology, as well as solubility sensors or solvent concentration sensors for monitoring solvent saturation. The intelligent circulation pump system includes a circulating pump for circulating the extractant. This circulating pump can be equipped with an intelligent variable frequency control module to adjust the pumping frequency and flow rate based on control commands. The intelligent temperature control system can adjust the temperature of the mixed extractant at the circulation pump inlet, for example, through secondary temperature compensation using a hot water jacket. The heating power can be adjusted based on control commands to regulate the temperature. The edge computing control system is used to monitor the actual leaching situation and efficiency of the leaching process based on image information from the camera monitoring system and measurement information from the sensor monitoring array, and generate corresponding control instructions to control the liquid injection frequency of the circulation pump in the intelligent circulation pump system, and control the heating power of the intelligent temperature control system, etc.

[0030] See also Figure 2 , Figure 2 This is a flow chart of a control method for plant extraction and leaching provided by this application. This control method for plant extraction and leaching can be applied to the above-mentioned edge computing control system, and the method includes the following steps.

[0031] S201, acquiring image information from a camera device.

[0032] Wherein, the image information includes image information in the extractor, and the leaching process in the plant extraction process is performed in the extractor. The camera device may be the above-mentioned camera monitoring system. The image information may be video-based image information. The image information in the extractor in this solution may refer to image information in a microenvironment chamber in the extractor. That is, a plurality of microenvironment chambers with unique fluid dynamic characteristics are constructed inside the extractor, which can flexibly adjust the leaching environment according to the characteristics of the plant raw materials (such as loose or tight texture, water content, particle size, etc.), and can effectively resist fluctuations in raw material characteristics. Compared with traditional leaching systems, it does not require frequent manual adjustments, which greatly improves the stability and adaptability of the system and ensures the consistency of leaching efficiency and quality.

[0033] S202: Acquire leaching status information according to the image information.

[0034] The leaching status information is used to indicate the operating status of the leaching process, for example, the leaching status information includes the leaching speed, the material level of the plant material in the leacher, the liquid level of the leachate in the leacher, the distribution of the plant material in the leacher, etc.

[0035] S203: Acquire measurement information from the sensor.

[0036] The measurement information is associated with the extraction efficiency of the plant material. Different temperatures significantly impact extraction efficiency. For example, high temperatures accelerate molecular diffusion and improve extraction efficiency, while low temperatures significantly reduce extraction efficiency. For example, the measurement information includes temperature information and solvent saturation information.

[0037] S204: Generate a control instruction for a target device according to the actual leaching information and the measurement information.

[0038] Among them, the target device can be the circulation pump in the above-mentioned intelligent circulation pump system, the intelligent temperature control system, etc., or it can be the rotor and double-auger and other devices in the above-mentioned intelligent circulation pump system not mentioned.

[0039] S205: Send the control instruction to the target device, so that the target device adjusts its working state according to the control instruction.

[0040] It can be seen that in this embodiment, image information is first obtained from the camera device, and the image information includes image information inside the extractor. The leaching process in the plant extraction process is performed in the extractor. Then, based on the image information, the leaching real-time information is obtained, and the leaching real-time information is used to indicate the operating status of the leaching process. Then, measurement information is obtained from the sensor, and the measurement information is associated with the leaching efficiency of the plant material. Then, based on the leaching real-time information and the measurement information, a control instruction for the target device is generated. Finally, the control instruction is sent to the target device, so that the target device adjusts its working state according to the control instruction. In this way, the operating status of the leaching process and the leaching efficiency of the plant material can be monitored in real time, and then the relevant equipment parameters can be adjusted in a timely and accurate manner to improve the leaching efficiency and plant extraction quality while ensuring system stability.

[0041] In a possible embodiment, the actual leaching information includes liquid sprinkling speed information, material level information of the plant raw material in the extractor, and liquid level information of the leachate in the extractor, and the measurement information includes temperature information of the mixed leachate at the inlet of the circulation pump and the saturation information of the leachate solvent; the control instructions for the target device generated according to the actual leaching information and the measurement information include: obtaining the fluctuation amplitude value and the fluctuation period value of the pumping frequency of the circulation pump, and the circulation pump is used to circulate the leachate; determining the increase rate of the effective component in the leachate solvent according to the leachate solvent saturation information; generating a control instruction for the circulation pump according to the sprinkling speed information, the material level information, the liquid level information, the temperature information, the increase rate of the effective component, the fluctuation amplitude value and the fluctuation period value, and the control instruction is used to instruct the circulation pump to adjust the pumping frequency.

[0042] A circulating pump frequency adjustment curve can be generated based on the leaching velocity (V), material level (L), liquid level (M), temperature (T), effective ingredient increase rate (R), fluctuation amplitude (G), and fluctuation period (ω). The circulating pump adjusts its leaching frequency based on this curve. This approach increases the pulsation of the circulating fluid, thereby improving the efficiency of molecular diffusion and convection diffusion. For example, if the leaching velocity in a microenvironment chamber is detected to be too slow, affecting leaching efficiency, the circulating pump automatically increases the leaching frequency within a specific time interval based on control instructions, increasing the solvent flow rate and accelerating the leaching velocity. It then reduces the frequency to maintain the appropriate leaching state in an intermittent manner, achieving precise regulation.

[0043] The adjustment curve f(t) can be calculated by the following formula: Among them, A is the initial frequency of the circulation pump. This initial frequency can be set based on equipment characteristics and extensive practical experience to provide basic frequency guarantee for the operation of the circulation pump. B, C, D, E, and F serve as weight coefficients, respectively reflecting the different degrees of influence of liquid level, material level, leaching rate, temperature, and the rate of increase of active ingredients on the circulation pump frequency. These coefficients can be determined through in-depth analysis of data from leaching experiments on different plant materials, combined with theoretical research. G and ω are used to control the fluctuation characteristics of the curve. G determines the fluctuation amplitude. The larger its value, the greater the fluctuation amplitude of the circulation pump frequency. ω determines the fluctuation period. The larger the ω value, the shorter the fluctuation period. By properly setting these two parameters, the pulsation of the circulating liquid can be effectively increased, and the efficiency of molecular diffusion and convection diffusion can be improved.

[0044] As can be seen, in this embodiment, the circulating pump's pumping frequency is dynamically adjusted based on real-time information collected and measurement information from sensors, ensuring that the solvent and raw materials always maintain optimal contact during the leaching process, thereby improving leaching efficiency and quality. By adjusting the frequency using a specific curve, the pulsation of the circulating fluid is enhanced, promoting full contact between the solvent and the raw materials, significantly improving molecular diffusion and convection diffusion efficiency, and thus effectively improving leaching efficiency. At the same time, combined with precise monitoring and control of material level, liquid level, and solvent saturation, solvent usage can be optimized, reducing solvent consumption and energy consumption while ensuring extraction efficiency, effectively reducing production costs.

[0045] In a possible embodiment, the image information includes image information of the leachate, and determining the rate of increase of the effective component in the leachate based on the saturation information of the leachate includes: obtaining the color change of the leachate in the extractor based on the image information of the leachate; and determining the rate of increase of the effective component in the leachate based on the color change and the saturation information of the leachate.

[0046] During the leaching process, dissolved active ingredients often affect the color of the solution. Certain chemical components, such as natural pigments or medicinal ingredients in plants, often cause the solution color to change as their concentration increases. Therefore, image preprocessing can be performed, such as using filters to remove noise, such as Gaussian blur or median filtering. Color correction and segmentation of the solution region are then performed to obtain the target image. The target image is then converted from the RGB color space to the HSV (hue, saturation, value) or Lab (CIELAB) color space. A computer vision library (such as OpenCV) is used to extract the color of the solution region. By comparing color information at different time points, the extent of color change can be determined. This can be accomplished by calculating color difference (e.g., Euclidean distance). To obtain solvent saturation information, conductivity or refractive index sensors can be used to monitor solvent concentration or solubility to indicate saturation. The color change and solvent saturation are then used as inputs, and a regression equation is fitted to the experimental data to output the rate of change in active ingredient concentration.

[0047] As can be seen, in this embodiment, determining the rate of increase of the active ingredient based on color change and saturation information not only allows real-time monitoring of the rate of increase of the active ingredient, but also avoids tedious chemical testing processes, reduces manual intervention, and saves experimental time and costs. Furthermore, it can sensitively capture subtle changes in the dissolution process, improving the accuracy of the determination of the rate of increase of the active ingredient.

[0048] In a possible embodiment, the image information includes continuous video frame images, the actual leaching information includes leaching speed information, and obtaining the actual leaching information based on the image information includes: preprocessing the video frame images to obtain target video frame images; calculating the target video frame images through an optical flow constraint equation to obtain the average motion vector of pixel points in a preset window; and determining the leaching speed based on the average motion vector.

[0049] Assume that in two consecutive frames of images I(x,y,t) and I(x+Δx,y+Δy,t+Δt), the brightness of the pixel (x,y) at time t is I(x,y,t), and it moves to (x+Δx,y+Δy) at time t+Δt. Based on the constant brightness assumption of the optical flow method, I(x,y,t)=I(x+Δx,y+Δy,t+Δt). Taylor expansion in the x and y directions yields: Among them, ε is a high-order infinitesimal and can be ignored. The optical flow constraint equation is obtained by sorting it out: in .

[0050] During the leaching process, the leaching liquid is regarded as a moving target, and the video frame images captured by the camera are preprocessed, including grayscale conversion, noise reduction and other operations to obtain the target video frame images to improve the accuracy of optical flow calculation. Then, the Lucas-Kanade algorithm is used to calculate the optical flow field. The Lucas-Kanade algorithm is based on the assumption that the optical flow in the local window is basically consistent. × In the window W, each pixel satisfies the optical flow constraint equation and constructs the equation group: By solving the equations, we can get the average motion vector (u, v) of the pixels in the window, and then calculate the dripping velocity V = By continuously analyzing multiple video frames, the real-time changes in the dripping speed can also be obtained.

[0051] In a specific implementation, after preprocessing the video frame image, a target detection algorithm can be used to identify the dripping area in the video frame image, extract the image of the dripping area in the video frame as the target video frame image, and eliminate the influence of other interference factors on the dripping speed calculation. The target detection algorithm can be the YOLOv5 algorithm.

[0052] It can be seen that in this embodiment, by analyzing image information through the optical flow method and obtaining the leaching speed in the extractor, the leaching speed can be accurately monitored, thereby producing control instructions for the target equipment in a timely and accurate manner, thereby improving the leaching efficiency and plant extraction quality.

[0053] In one possible embodiment, the image information includes a reference marker image, a plant raw material image and an extract image, and the actual extraction information includes the material level information of the plant raw material in the extractor and / or the liquid level information of the extract in the extractor. The obtaining of the actual extraction information based on the image information includes: obtaining the pixel length of the reference marker based on the reference marker image; determining a scaling factor based on the actual length of the reference marker and the pixel length; obtaining the boundary of the plant raw material in the plant raw material image and / or the boundary of the extract in the extract image; obtaining the pixel height of the plant raw material based on the boundary of the plant raw material and / or obtaining the pixel height of the extract based on the boundary of the extract; determining the material level information based on the scaling factor and the pixel height of the plant raw material, and / or determining the liquid level information based on the scaling factor and the pixel height of the extract.

[0054] Among them, some reference markers of known size can be pre-set in the extractor. Assume that the actual length of the reference marker is L real , the pixel length in the image is L pixel , then the ratio factor k between the image pixels and the actual size is: After the camera captures an image containing the reference marker, plant material, and leachate, the image can be transformed into a front view to eliminate the distortion caused by the shooting angle. Then, an edge detection algorithm (such as the Canny edge detection algorithm) is used to detect the boundaries of the plant material and leachate in the image to obtain the pixel height h of the material level and liquid level in the image. pixel Combined with the proportional factor k, the actual height of the material level and liquid level can be calculated as h=h pixel ×h.

[0055] As can be seen, in this embodiment, a deep learning target detection algorithm is used to more precisely locate the boundaries of the material and liquid levels, improving measurement accuracy. Furthermore, to address complex leaching environments, such as variations in leachate transparency and obstruction by raw materials, a multi-camera collaborative monitoring approach can be employed to capture images from different angles and comprehensively analyze the information from these multiple images to determine the material and liquid levels. This improves the timeliness and accuracy of control command generation.

[0056] In a possible embodiment, the measurement information includes temperature information of the mixed leachate at the inlet of the circulation pump, and the control instructions for the target device are generated based on the actual leaching information and the measurement information, including: obtaining the type and current leaching stage of the plant raw material; generating control instructions for the intelligent temperature control system based on the type, the current leaching stage and the temperature information, the control instructions are used to instruct the intelligent temperature control system to adjust the heating power, and the intelligent temperature control system is used to adjust the temperature of the mixed leachate at the inlet of the circulation pump.

[0057] The intelligent temperature control system's heating power can be dynamically adjusted to regulate the extraction temperature based on the type of plant material and the state of the extraction process at different stages. For example, in the early stages of extraction, for plant materials that require rapid heating to promote the dissolution of active ingredients, the heating power can be rapidly increased to quickly bring the temperature to an appropriate range. During the extraction process, as the set value is approached, a PID algorithm automatically calculates the heating power and generates control instructions to ensure the temperature remains stable near the optimal extraction temperature, preventing temperature fluctuations from damaging the active ingredients. In the final stages of extraction, the temperature is appropriately increased to maintain the extraction rate.

[0058] As can be seen in this example, real-time adjustment of the leachate temperature based on the type of raw material and the leaching stage can improve leaching efficiency. Using advanced PID control algorithms to precisely adjust the temperature ensures stability within the optimal leaching range, preventing deterioration of active ingredients or low leaching efficiency due to improper temperature, thereby reducing raw material waste. Furthermore, precise monitoring and control of material level, liquid level, and solvent saturation optimizes solvent usage, reducing solvent and energy consumption while ensuring extraction efficiency, effectively lowering production costs.

[0059] In a possible embodiment, the actual leaching information includes the flatness of the surface of the plant raw material in the extractor, and the obtaining of the actual leaching information based on the image information includes: inputting the image information into a preset model to obtain the probability that each pixel in the image output by the preset model belongs to the plant raw material; segmenting the area where the plant raw material is located in the image information according to the probability to obtain a segmentation result; and determining the flatness of the surface of the plant raw material in the extractor according to the segmentation result.

[0060] A deep learning-based semantic segmentation algorithm can be used to segment the raw material area to determine the flatness of the plant material surface within the extractor. This pre-set model can include an encoder (downsampling path) and a decoder (upsampling path). The encoder gradually extracts image features through convolution and pooling operations, while the decoder restores the low-resolution feature map to a high-resolution segmentation result through deconvolution and skip connections.

[0061] During the training phase, a large number of extractor images containing different distributions of plant materials are annotated to construct a training dataset. This dataset is used to train a pre-trained model, which can be a U-Net network. The model loss function can be a cross-entropy loss function: L Where N is the number of samples, C is the number of categories (in this scheme, plant materials are identified as one category, and background, etc. are identified as another category, C=2), is the true label (0 or 1) of sample i belonging to category c, is the probability that the model predicts that sample i belongs to category c. The backpropagation algorithm continuously adjusts the model parameters to minimize the loss function, allowing the pre-trained model to learn the characteristic differences between plant materials and other objects such as background and extract, thus obtaining a trained preset model.

[0062] In a specific implementation, images captured by a camera can be fed into a pre-trained model. This model outputs the probability that each pixel in the image belongs to the plant material, thereby segmenting the area to which the plant material belongs and obtaining a segmentation result. Based on the segmentation result, information such as the distribution range and density of the plant material can be obtained, and the flatness of the plant material surface within the extractor can be determined based on the distribution range and density.

[0063] In a specific implementation, after obtaining the flatness of the plant raw material surface, control instructions for the rotor and double auger can be generated based on the flatness of the plant raw material surface. The control instructions are used to enable the rotor and double auger to adjust the rotation speed and direction to optimize the mixing effect of the plant raw material and the extraction solvent.

[0064] It can be seen that in this embodiment, analyzing the flatness of the plant material surface based on the model can improve the accuracy and efficiency of the analysis, so that corresponding adjustment instructions can be generated in a timely manner to improve the leaching efficiency.

[0065] The following combination Figure 3 This application is described in detail.

[0066] See also Figure 3 In the leaching process of plant extraction, the raw materials need to be input first, that is, the plant raw materials are transported to the extractor microenvironment chamber (4) through the feeding scraper (1). During this process, the sensor monitoring array ① (2) performs preliminary detection of the raw material related information.

[0067] Then the leaching process is as follows: the intelligent circulation pump (5) sprays the leaching solvent onto the raw materials in the extractor microenvironment chamber (4) through the spray pipe (16) and siphon spray (13) and other devices to perform the leaching operation. During this period, the camera (15) fully monitors the leaching speed, raw materials and leachate distribution inside the extractor, and transmits the image data to the edge computing control cabinet (20). The edge computing control cabinet (20) can be indicated as the edge computing system in this solution. The sensor monitoring array ② (6), sensor monitoring array ③ (14), sensor monitoring array ④ (17), sensor monitoring array ⑤ (18) and sensor monitoring array ⑥ (19) monitor the key parameters such as the temperature of the mixed leachate at the inlet of the circulation pump and the saturation of the leachate in real time, and also transmit the data to the edge computing control cabinet (20). Then the hot water jacket (7) adjusts the leaching temperature according to the sensor data under the control of the intelligent temperature control system to ensure that the leaching is carried out at the appropriate temperature.

[0068] Then the mixed oil is processed: the leached mixed oil flows into the oil tank (9) through the oil tank connector (8), and then enters the mixed oil tank (3) for temporary storage.

[0069] And slag treatment is performed: the treated slag falls into the slag bin (10), and is transported to the disc (12) by the slag scraper (11) to complete subsequent treatment.

[0070] The edge computing control cabinet (20) receives data from the camera and the sensor monitoring array, performs fusion analysis and processing, makes control decisions according to preset rules and algorithms, and adjusts equipment parameters such as the frequency of the intelligent circulation pump (5) and the heating power of the intelligent temperature control system to achieve dynamic optimization and precise control of the leaching process.

[0071] The following describes a control device for the plant extraction and leaching process provided in the present application. The control device for the plant extraction and leaching process described below corresponds to the control method for the plant extraction and leaching process described above.

[0072] See also Figure 4The control device 400 for the plant extraction and leaching process includes: a first acquisition unit 401, used to acquire image information from a camera device, the image information includes image information in the extractor, and the leaching process in the plant extraction process is performed in the extractor; a second acquisition unit 402, used to acquire leaching real-time information based on the image information, the leaching real-time information is used to indicate the operating status of the leaching process; a third acquisition unit 403, used to acquire measurement information from a sensor, the measurement information is associated with the leaching efficiency of the plant raw material; a generation unit 404, used to generate a control instruction for a target device based on the leaching real-time information and the measurement information; a sending unit 405, used to send the control instruction to the target device, so that the target device adjusts its working state according to the control instruction.

[0073] In a possible embodiment, the actual leaching information includes liquid sprinkling speed information, material level information of the plant material in the extractor, and liquid level information of the leachate in the extractor, and the measurement information includes temperature information of the mixed leachate at the inlet of the circulation pump and the saturation information of the leachate solvent; in terms of generating control instructions for the target device based on the actual leaching information and the measurement information, the generation unit 404 is specifically used to: obtain the fluctuation amplitude value and fluctuation period value of the pumping frequency of the circulation pump, and the circulation pump is used to circulate the leachate; determine the increase rate of the effective component in the leachate solvent according to the leachate solvent saturation information; generate a control instruction for the circulation pump according to the sprinkling speed information, the material level information, the liquid level information, the temperature information, the increase rate of the effective component, the fluctuation amplitude value and the fluctuation period value, and the control instruction is used to instruct the circulation pump to adjust the pumping frequency.

[0074] In a possible embodiment, the image information includes image information of the leachate. In terms of determining the rate of increase of the effective components in the leachate based on the saturation information of the leaching solvent, the generation unit 404 is specifically used to: obtain the color change of the leachate in the extractor based on the image information of the leachate; and determine the rate of increase of the effective components in the leachate based on the color change and the saturation information of the leaching solvent.

[0075] In a possible embodiment, the image information includes continuous video frame images, and the actual leaching information includes leaching speed information. In terms of obtaining the actual leaching information based on the image information, the second acquisition unit 402 is specifically used to: preprocess the video frame image to obtain a target video frame image; calculate the target video frame image through an optical flow constraint equation to obtain an average motion vector of pixel points in a preset window; and determine the leaching speed based on the average motion vector.

[0076] In a possible embodiment, the image information includes a reference marker image, a plant raw material image and an extract image, and the actual extraction information includes the material level information of the plant raw material in the extractor and / or the liquid level information of the extract in the extractor. In terms of obtaining the actual extraction information based on the image information, the second acquisition unit 402 is specifically used to: obtain the pixel length of the reference marker based on the reference marker image; determine the scaling factor based on the actual length of the reference marker and the pixel length; obtain the boundary of the plant raw material in the plant raw material image and / or the boundary of the extract in the extract image; obtain the pixel height of the plant raw material based on the boundary of the plant raw material and / or obtain the pixel height of the extract based on the boundary of the extract; determine the material level information based on the scaling factor and the pixel height of the plant raw material, and / or determine the liquid level information based on the scaling factor and the pixel height of the extract.

[0077] In a possible embodiment, the measurement information includes temperature information of the mixed leachate at the inlet of the circulation pump. In terms of generating control instructions for the target device based on the actual leaching information and the measurement information, the generation unit 404 is specifically used to: obtain the type and current leaching stage of the plant raw material; generate control instructions for the intelligent temperature control system based on the type, the current leaching stage and the temperature information, and the control instructions are used to instruct the intelligent temperature control system to adjust the heating power, and the intelligent temperature control system is used to adjust the temperature of the mixed leachate at the inlet of the circulation pump.

[0078] In a possible embodiment, the actual leaching information includes the flatness of the surface of the plant raw material in the extractor. In terms of obtaining the actual leaching information based on the image information, the second acquisition unit 402 is specifically used to: input the image information into a preset model to obtain the probability that each pixel in the image output by the preset model belongs to the plant raw material; segment the area where the plant raw material is located in the image information according to the probability to obtain a segmentation result; and determine the flatness of the surface of the plant raw material in the extractor based on the segmentation result.

[0079] The present application also provides an edge computing control system, including an edge server and a computing controller; the edge server is used to obtain image information from a camera device, the image information includes image information in an extractor, and the extraction link in the plant extraction process is performed in the extractor; and is used to obtain extraction status information based on the image information, and the extraction status information is used to indicate the operating status of the extraction link; and is used to obtain measurement information from a sensor, and the measurement information is associated with the extraction efficiency of the plant raw material; the computing controller is used to generate a control instruction for a target device based on the extraction status information and the measurement information from the edge server, and is used to send the control instruction to the target device so that the target device adjusts its working status according to the control instruction.

[0080] As can be seen, in this embodiment, based on the edge computing architecture, the edge computing server quickly processes the image data captured by the camera locally, greatly reducing data transmission delays and significantly improving the real-time performance of data processing. The edge computer works closely with the edge computing server, employing a redundant design and a stable operating system. It possesses powerful data processing capabilities and high reliability, enabling it to quickly and accurately process large amounts of real-time data and make stable control decisions. Furthermore, the system's anomaly monitoring and self-repair mechanisms provide timely responses to equipment failures, ensuring continuous and stable system operation and significantly reducing the occurrence of production interruptions.

[0081] The following is an illustration of the extraction process using mint leaves and ginkgo leaves as examples.

[0082] The extraction process for mint leaves is as follows.

[0083] (1) Raw material preparation Fresh, mold-free, and moderately mature mint leaves were selected from a location in Anhui Province. Testing revealed a moisture content of 72%, an average particle size of approximately 2-4 mm, and a menthol content of approximately 2.0%. These parameters were entered into the system database.

[0084] (2) System initialization: There are 5 micro-environment chambers inside the extractor. According to the characteristics of mint leaves being loose in texture and the effective ingredients being easily dissolved, the parameters of each micro-environment chamber are set as follows: Microenvironment Chamber 1: The temperature is set to 40°C, the flow rate is 0.9 m / s, and the specific adjustment frequency curve of the intelligent circulation pump is f1(t)=35+6sin(0.12πt) (f is frequency, t is time, and the unit is minute). The relevant parameters are determined according to the specific curve formula, where A=30, B=0.5, C=0.3, D=2, E=0.8, F=1.5, G=5, and ω=0.12π.

[0085] Microenvironment chamber 2: The temperature is set to 41°C, the flow rate is 1.0 m / s, and the specific adjustment frequency curve of the intelligent circulation pump is f2(t)=37+5sin(0.13πt). The corresponding formula parameters are determined according to the extraction characteristics of mint leaves.

[0086] Microenvironment Chamber 3: The temperature is set to 42°C, the flow rate is 1.1 m / s, and the specific adjustment frequency curve of the intelligent circulation pump is f3(t)=36+4sin(0.11πt). The formula parameters are set accordingly.

[0087] Microenvironment chamber 4: The temperature is set to 41°C, the flow rate is 1.05 m / s, and the specific adjustment frequency curve of the intelligent circulation pump is f4(t)=38+5sin(0.125πt). The parameters meet the leaching requirements.

[0088] Microenvironment chamber 5: The temperature is set to 40°C, the flow rate is 0.95m / s, and the specific adjustment frequency curve of the intelligent circulation pump is f5(t)=35+6sin(0.115πt) to ensure that the conditions in each microenvironment chamber are suitable.

[0089] Turn on the camera monitoring system and sensor monitoring array to ensure the normal operation of all equipment.

[0090] (3) Extraction process: The mint leaves are pre-treated before being added to remove impurities and are appropriately crushed to make them easier to contact with the solvent. The raw materials are transported to the extractor micro-environment chamber via a feeding scraper, and the sensor monitoring array performs preliminary detection of relevant information such as the temperature and humidity of the raw materials. The intelligent circulation pump sprays the precisely adjusted extraction solvent (ethanol, concentration of 75%, with a small amount of co-solvent added) onto the raw materials at an appropriate flow rate according to the frequency curve set for each micro-environment chamber to perform the extraction operation.

[0091] Cameras comprehensively monitor the leaching rate, raw material, and leachate distribution in each microenvironmental chamber within the extractor, transmitting image data to an edge computing server. The leaching rate is calculated using the optical flow method and the YOLOv5 algorithm. The distribution of plant raw materials is acquired through a U-Net network. Material and liquid levels are determined using image processing-based geometric measurement methods and deep learning object detection algorithms. A sensor monitoring array monitors parameters such as the temperature of the mixed leachate at the inlet of the circulating pump in each microenvironmental chamber and the saturation of the leachate solvent in real time, transmitting this data to the edge computing control system. Based on this sensor data, the intelligent temperature control system fine-tunes the temperature of each microenvironmental chamber in real time, ensuring that the temperature remains stable within a range of ±0.8°C from the set value. Furthermore, during the leaching process, microenvironmental chamber parameters are adjusted appropriately based on the leaching status of the raw material. For example, in the early stages of leaching, the flow rate and circulation pump frequency are appropriately increased to accelerate contact between the solvent and the raw material.

[0092] (4) Data processing and control: The edge computing control system integrates and analyzes the received data and uses more advanced algorithm models to conduct an in-depth evaluation of the leaching process. If it is found that the parameters such as the leaching speed, temperature or solvent saturation of a certain microenvironment chamber deviate from the set range, the adjustment strategy is quickly calculated. In addition to adjusting the circulation pump frequency and the temperature control system power, the solvent spraying method and flow rate will be optimized according to the actual situation. For example, when it is detected that the leaching speed of a certain microenvironment chamber is too slow, the intelligent circulation pump frequency adjustment curve formula is combined with the liquid level, material level, temperature and effective ingredient increase rate of the microenvironment chamber to calculate the circulation pump frequency that needs to be increased, increase the solvent flow rate, and speed up the leaching speed; when the temperature deviates from the optimal range, the intelligent temperature control system adjusts the heating power according to the PID control algorithm to restore the temperature to the appropriate range.

[0093] (5) Results: The extraction rate of menthol reached 92%, and the residual menthol content in the residue was reduced to 0.1%. This result shows that the active ingredients in mint leaves were efficiently extracted based on the method of this application, and the system has a significant control effect on the leaching process, which can meet the production requirements of high-quality plant extraction.

[0094] The extraction process for Ginkgo biloba leaves is as follows: (1) Raw material preparation Ginkgo biloba raw materials from a place in Shandong were selected and tested to find that their moisture content was 60%, the average particle size was about 8-10 mm, the content of the active ingredient flavonoid glycosides was about 2.2%, and the content of terpenoid lactones was about 0.6%. These parameters were entered into the system database.

[0095] (2) System initialization: There are 6 micro-environment chambers inside the extractor. In view of the characteristics of the compact structure of ginkgo leaves and the difficulty of extraction, the parameters of each micro-environment chamber are set as follows: Microenvironment chamber 1: The temperature is set to 45°C, the flow rate is 0.3 m / s, and the specific adjustment frequency curve of the intelligent circulation pump is f1(t)=22+3sin(0.06πt). According to the specific curve formula, the relevant parameters are determined to be A=20, B=0.4, C=0.2, D=1.5, E=1, F=1.2, G=3, and ω=0.06π.

[0096] Microenvironment Chamber 2: The temperature is set to 46°C, the flow rate is 0.35 m / s, and the specific adjustment frequency curve of the intelligent circulation pump is f2(t)=23+4sin(0.07πt). The corresponding formula parameters are determined according to the extraction characteristics of ginkgo leaves.

[0097] Microenvironment chamber 3: The temperature is set to 47°C, the flow rate is 0.4 m / s, the specific adjustment frequency curve of the intelligent circulation pump is f3(t)=24+3sin(0.08πt), and the parameter settings are adapted to the leaching requirements.

[0098] Microenvironment chamber 4: The temperature is set to 46°C, the flow rate is 0.38 m / s, and the specific adjustment frequency curve of the intelligent circulation pump is f4(t)=23+4sin(0.075πt) to ensure the leaching effect.

[0099] Microenvironment chamber 5: The temperature is set to 45°C, the flow rate is 0.33 m / s, and the specific adjustment frequency curve of the intelligent circulation pump is f5(t)=22+3sin(0.065πt), which meets the process requirements.

[0100] Microenvironment chamber 6: The temperature was set to 44 °C, the flow rate was 0.3 m / s, and the specific adjustment frequency curve of the intelligent circulation pump was f6(t)=21+3sin(0.055πt) to optimize the leaching conditions.

[0101] Start all devices and ensure they are functioning properly.

[0102] (3) Leaching process: The ginkgo leaf raw material is put into the extractor, and the intelligent circulation pump sprays the leaching solvent (acetone, concentration of 60%) onto the raw material according to the frequency curve set in each micro-environment chamber for leaching. The camera monitors the leaching speed, raw material and leaching liquid distribution in each micro-environment chamber inside the leaching chamber, and transmits the image to the edge computing server. The sensor monitoring array monitors the mixed leaching liquid temperature, leaching solvent saturation and other parameters at the inlet of the circulation pump of each micro-environment chamber in real time, and transmits them to the edge computing control system. The intelligent temperature control system fine-tunes the temperature of each micro-environment chamber in real time based on the sensor data to ensure that the temperature is stable within the set value ±1.5℃. During the leaching process, the relevant algorithms of the camera monitoring system are also used to obtain the leaching speed, raw material distribution, material level and liquid level information to provide data support for system control.

[0103] (4) After testing, the extraction rate of flavonoid glycosides reached 78%, and the extraction rate of terpenoid lactones reached 70%. The residual amount of flavonoid glycosides in the residue was 0.3%, and the residual amount of terpenoid lactones was 0.1%. This shows that the method based on this application can still achieve a high extraction rate in the extraction of plant raw materials such as ginkgo leaves, which have a compact structure and are difficult to extract, and effectively reduces the residual active ingredients in the residue, proving its wide applicability and effectiveness.

[0104] See also Figure 5 , Figure 5 This is a schematic diagram of the structure of the electronic device provided by this application. Figure 5As shown, the electronic device may include: a processor 510, a communications interface 520, a memory 530, and a communications bus 540. The processor 510, the communications interface 520, and the memory 530 communicate with each other via the communications bus 540. The processor 510 may invoke logic instructions in the memory 530 to execute a control method for a plant extraction and leaching process. The method includes: acquiring image information from a camera, the image information including image information within an extractor, wherein the leaching process of the plant extraction process is performed within the extractor; acquiring real-time leaching information based on the image information, the real-time leaching information indicating the operating status of the leaching process; acquiring measurement information from a sensor, the measurement information being associated with the leaching efficiency of the plant material; generating a control instruction for a target device based on the real-time leaching information and the measurement information; and transmitting the control instruction to the target device so that the target device adjusts its operating status according to the control instruction.

[0105] Furthermore, the logic instructions in the aforementioned memory 530 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the portion that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as a USB flash drive, a mobile hard drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0106] On the other hand, the present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, is implemented to execute the control method for the plant extraction and leaching link provided by the above-mentioned methods, the method comprising: obtaining image information from a camera device, the image information including image information in an extractor, the leaching link in the plant extraction process being performed in the extractor; obtaining leaching actual information based on the image information, the leaching actual information being used to indicate the operating status of the leaching link; obtaining measurement information from a sensor, the measurement information being associated with the leaching efficiency of the plant raw material; generating a control instruction for a target device based on the leaching actual information and the measurement information; and sending the control instruction to the target device so that the target device adjusts its working status according to the control instruction.

[0107] On the other hand, the present application also provides a computer program product, including a computer program, which, when executed by a processor, implements any of the above-mentioned control methods for the plant extraction and leaching process, the method including: obtaining image information from a camera device, the image information including image information in an extractor, and the leaching process in the plant extraction process is performed in the extractor; obtaining leaching status information based on the image information, the leaching status information being used to indicate the operating status of the leaching link; obtaining measurement information from a sensor, the measurement information being associated with the leaching efficiency of the plant raw material; generating a control instruction for a target device based on the leaching status information and the measurement information; and sending the control instruction to the target device so that the target device adjusts its working status according to the control instruction.

[0108] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, i.e., they may be located in one location or distributed across multiple network units. Some or all of the modules may be selected based on actual needs to achieve the objectives of the present embodiment. Persons of ordinary skill in the art will be able to understand and implement the present invention without inventive effort.

[0109] Through the above description of the embodiments, those skilled in the art will clearly understand that each embodiment can be implemented using software plus a necessary general-purpose hardware platform, or of course, hardware. Based on this understanding, the essence of the above technical solution, or the portion that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a magnetic disk, or an optical disk, and includes a number of instructions for causing a computer device (such as a personal computer, server, or network device) to execute the methods described in each embodiment or certain portions of the embodiments.

[0110] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the various embodiments of the present invention.

Claims

1. A control method for plant extraction and leaching, characterized in that: include: Acquiring image information from a camera device, the image information including image information within an extractor, where an extraction step in the plant extraction process is performed; Acquiring leaching real-time information according to the image information, wherein the leaching real-time information is used to indicate the operating status of the leaching process; obtaining measurement information from a sensor, the measurement information being correlated to a leaching efficiency of the plant material; generating a control instruction for a target device according to the actual leaching information and the measurement information; The control instruction is sent to the target device, so that the target device adjusts its working state according to the control instruction.

2. The method according to claim 1, characterized in that The actual leaching information includes the information of the leaching speed, the material level information of the plant material in the leacher, and the liquid level information of the leachate in the leacher. The measurement information includes the temperature information of the mixed leachate at the inlet of the circulation pump and the saturation information of the leachate solvent. The generating of a control instruction for a target device according to the actual leaching information and the measurement information includes: Obtaining a fluctuation amplitude value and a fluctuation period value of a pumping frequency of a circulation pump, wherein the circulation pump is used to circulate the leachate; determining an increase rate of the effective component in the leaching solvent according to the saturation information of the leaching solvent; A control instruction for the circulation pump is generated based on the spraying speed information, the material level information, the liquid level information, the temperature information, the effective ingredient increase rate, the fluctuation amplitude value and the fluctuation period value, and the control instruction is used to instruct the circulation pump to adjust the liquid injection frequency.

3. The method according to claim 2, characterized in that The image information includes image information of the leachate, and determining the rate of increase of the effective component in the leachate according to the saturation information of the leachate solvent includes: obtaining a color change of the leachate in the extractor according to the image information of the leachate; The increasing rate of the effective component in the leachate is determined according to the color change and the saturation information of the leaching solvent.

4. The method according to any one of claims 1 to 3, characterized in that The image information includes continuous video frame images, the actual leaching information includes leaching speed information, and obtaining the actual leaching information according to the image information includes: Preprocessing the video frame image to obtain a target video frame image; Calculating the target video frame image using an optical flow constraint equation to obtain an average motion vector of pixels within a preset window; The dripping speed is determined according to the average motion vector.

5. The method according to any one of claims 1 to 3, characterized in that The image information includes a reference marker image, a plant material image, and an extract image. The actual extraction information includes material level information of the plant material in the extractor and / or liquid level information of the extract in the extractor. Acquiring the actual extraction information based on the image information includes: Acquiring a pixel length of a reference marker according to the reference marker image; determining a scaling factor based on the actual length of the reference marker and the pixel length; Acquiring a boundary of the plant material in the plant material image and / or a boundary of the leachate in the leachate image; Obtaining the pixel height of the plant material according to the boundary of the plant material, and / or obtaining the pixel height of the leachate according to the boundary of the leachate; The material level information is determined according to the proportional factor and the pixel height of the plant material, and / or the liquid level information is determined according to the proportional factor and the pixel height of the extract.

6. The method according to claim 1, characterized in that The measurement information includes temperature information of the mixed leachate at the inlet of the circulation pump, and the generating of a control instruction for a target device according to the actual leaching information and the measurement information includes: Obtaining the type and current leaching stage of the plant material; A control instruction for the intelligent temperature control system is generated according to the type, the current leaching stage and the temperature information, wherein the control instruction is used to instruct the intelligent temperature control system to adjust the heating power, and the intelligent temperature control system is used to adjust the temperature of the mixed leachate at the circulation pump inlet.

7. The method according to claim 1, characterized in that The actual leaching information includes the flatness of the surface of the plant material in the extractor, and the acquiring of the actual leaching information based on the image information includes: Inputting the image information into a preset model to obtain the probability that each pixel in the image output by the preset model belongs to the plant material; Segmenting the region where the plant material is located in the image information according to the probability to obtain a segmentation result; The flatness of the plant material surface in the extractor is determined according to the segmentation result.

8. A control device for plant extraction and leaching, characterized in that: include: a first acquiring unit, configured to acquire image information from a camera device, wherein the image information includes image information within an extractor, wherein the leaching step in the plant extraction process is performed within the extractor; a second acquiring unit, configured to acquire leaching status information according to the image information, wherein the leaching status information is used to indicate an operating state of the leaching process; a third acquiring unit, configured to acquire measurement information from the sensor, wherein the measurement information is associated with the leaching efficiency of the plant material; a generating unit, configured to generate a control instruction for a target device according to the actual leaching information and the measurement information; The sending unit is configured to send the control instruction to the target device, so that the target device adjusts its working state according to the control instruction.

9. An edge computing control system, characterized in that: Includes edge servers and computing controllers; The edge server is configured to obtain image information from a camera device, the image information including image information within an extractor, wherein the leaching step in the plant extraction process is performed within the extractor; and to obtain leaching status information based on the image information, the leaching status information being used to indicate an operating status of the leaching step; and for obtaining measurement information from a sensor, the measurement information being correlated to a leaching efficiency of the plant material; The computing controller is used to generate a control instruction for a target device based on the leaching real-time information and the measurement information from the edge server, and to send the control instruction to the target device so that the target device adjusts its working state according to the control instruction.

10. An electronic device comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that: When the processor executes the computer program, the control method for the leaching step in the plant extraction process as described in any one of claims 1 to 7 is implemented.

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