A cooking control method and apparatus

Abstract

The application provides a cooking control method and device. The method comprises the following steps: blowing and washing target peeled green beans, and monitoring the cleaning degree and damage state of the target peeled green beans; if the cleaning degree meets a preset cleaning standard, determining that the blowing and washing is completed, determining pre-cooking parameters based on the type, quantity and damage state of the target peeled green beans; pre-cooking the target peeled green beans based on the pre-cooking parameters, and monitoring the first softness of the target peeled green beans after pre-cooking; determining steaming parameters based on the first softness, steaming the target peeled green beans based on the steaming parameters, and monitoring the second softness of the target peeled green beans after steaming; determining grinding parameters based on the second softness, and grinding the target peeled green beans based on the grinding parameters. The application can ensure the quality and consistency of green bean processing products.

Description

Technical Field

[0001] This invention relates to the field of food processing technology, and in particular to a cooking control method and apparatus. Background Technology

[0002] In the food processing industry, especially in the deep processing of agricultural products such as mung beans, a series of complex technological steps are involved, aiming to transform raw materials into products with higher added value. These products can include mung bean powder, mung bean pastries, mung bean beverages, and so on. To ensure the processing effect, strict quality control measures need to be implemented throughout the entire processing process, including testing the physical properties, chemical composition, and microbiological indicators of the products at each step to ensure compliance with relevant standards.

[0003] However, traditional processing procedures often rely on experienced operators to determine the optimal processing parameters for each stage, which remains significantly insufficient for pursuing higher levels of quality control and efficiency improvements. For example, judging the cleanliness of mung beans mainly depends on manual inspection and simple physical tests (such as water washing tests). While this method is intuitive, it lacks precision and consistency. Differences in experience among different operators can lead to inconsistent cleaning standards, making it difficult to ensure that each batch of mung beans reaches the same level of cleanliness. Furthermore, traditional processing procedures typically use fixed pre-cooking, steaming, and grinding parameters. This "one-size-fits-all" approach often fails to meet the optimal processing conditions for specific varieties or processing states, thus affecting the consistency of product quality. Summary of the Invention

[0004] This invention provides a cooking control method and apparatus to solve the problem of improving the consistency of deep-processed mung bean products.

[0005] In a first aspect, embodiments of the present invention provide a cooking control method, comprising: The target peeled mung beans were blown and washed, and the cleanliness and damage status of the target peeled mung beans were monitored; If the cleanliness meets the preset cleanliness standard, the rinsing is deemed complete, and the pre-cooking parameters are determined based on the type, quantity, and damage status of the target peeled green vegetables. The target peeled mung beans were pre-cooked based on the pre-cooking parameters, and the first softness and hardness of the target peeled mung beans after pre-cooking were monitored. Steaming parameters are determined based on the first hardness, and the target peeled mung beans are steamed based on the steaming parameters. The second hardness of the target peeled mung beans after steaming is monitored. The grinding parameters are determined based on the second hardness, and the target peeled mung beans are ground based on the grinding parameters.

[0006] In one possible implementation, monitoring the cleanliness of the target peeled mung beans includes: The first area percentage of floating impurities in the water surface image of the premixing pool where the target peeled mung beans are located; Calculate the weight change of the target peeled mung beans before and after washing; Identify the second area ratio of impurities in the image of peeled mung beans after they have been washed. If the first area percentage is less than the first preset threshold, the weight change is greater than the second preset threshold, the second area percentage is less than the third preset threshold, and the blowing and washing time of the target peeled mung beans is greater than the preset time, then the blowing and washing is determined to be completed.

[0007] In one possible implementation, before monitoring the cleanliness of the target peeled mung beans, the following is also included: Multiple groups of peeled mung beans were subjected to a blowing and washing experiment, and the weight change of each group of peeled mung beans before and after blowing and washing was recorded; among them, the peeled mung beans of each group had different varieties, peeling methods and quantities. For each variety and peeling method, based on the number of peeled mung beans in each group and the weight change before and after washing, calculate the unit weight change corresponding to that variety and peeling method. The change in unit weight of the target peeled mung beans is determined based on the variety and peeling method of the target peeled mung beans, and a second preset threshold is determined based on the quantity and change in unit weight of the target peeled mung beans.

[0008] In one possible implementation, monitoring the damage state of the target peeled mung beans includes: Sampling was performed on the target peeled mung beans; If the size and number of the sampled fragments are both within the first preset range, the damage status of the target peeled mung bean is determined to be low damage. If the size and number of the sampled fragments are both within the second preset range, the damage state of the target peeled mung bean is determined to be medium damage. If the size and number of the sampled fragments are both within the third preset range, then the damage state of the target peeled mung bean is determined to be high damage.

[0009] In one possible implementation, before determining the pre-cooking parameters based on the type, quantity, and damage state of the target peeled green, the following is also included: The type and damage state of peeled mung beans were used as input variables, pre-cooking parameters as adjustable variables, and grinding effect as output variables. Multiple levels of each variable were set, and orthogonal experiments were conducted on multiple groups of peeled mung beans after blowing and washing. A regression model was constructed based on the type, damage state, pre-cooking parameters, and grinding effect of the peeled mung beans after washing in each group; Accordingly, pre-cooking parameters are determined based on the type and quantity of the target peeled green and the damage state, including: The type, damage state, and expected grinding effect of the target peeled mung beans are input into the regression model to obtain the pre-cooking parameters of the target peeled mung beans.

[0010] In one possible implementation, the steaming parameters include steaming time; the steaming parameters are determined based on a first hardness / softness, including: The first softness / hardness level is determined by comparing it with the first softness / hardness threshold. If the first hardness is relatively hard, then the steaming parameter is determined to be the first steaming time; If the first softness / hardness is moderate, then the second steaming time is determined as the steaming parameter. If the first hardness is relatively soft, then the steaming parameter is determined to be the third steaming time; The first steaming time is longer than the second steaming time, and the second steaming time is longer than the third steaming time.

[0011] In one possible implementation, the grinding parameters include grinding speed and grinding pressure; the grinding parameters are determined based on the second softness / hardness, including: The second softness / hardness level is determined by comparing it with the second softness / hardness threshold. If the second hardness is relatively hard, then the grinding parameters are determined to be the first grinding speed and the first grinding pressure; If the second hardness is moderate, then the grinding parameters are determined to be the second grinding speed and the second grinding pressure. If the second hardness is relatively soft, then the grinding parameters are determined to be the third grinding speed and the third grinding pressure; The first grinding speed is less than the second grinding speed, and the second grinding speed is less than the third grinding speed; the first grinding pressure is greater than the second grinding pressure, and the second grinding pressure is greater than the third grinding pressure.

[0012] Secondly, embodiments of the present invention provide a cooking control device, comprising: The blowing and washing monitoring module is used to blow and wash the target peeled mung beans and monitor the cleanliness and damage status of the target peeled mung beans; The pre-cooking determination module is used to determine that the rinsing is complete when the cleanliness meets the preset cleanliness standard, and to determine the pre-cooking parameters based on the type, quantity and damage status of the target peeled green. The pre-cooking monitoring module is used to pre-cook the target peeled mung beans based on pre-cooking parameters and monitor the first softness and hardness of the target peeled mung beans after pre-cooking. The steaming monitoring module is used to determine the steaming parameters based on the first softness and hardness, steam the target peeled mung beans based on the steaming parameters, and monitor the second softness and hardness of the target peeled mung beans after steaming. The grinding determination module is used to determine grinding parameters based on the second hardness, and grind the target peeled mung beans based on the grinding parameters.

[0013] Thirdly, embodiments of the present invention provide a terminal, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the method as described in the first aspect or any possible implementation of the first aspect.

[0014] Fourthly, embodiments of the present invention provide a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of the method as described in the first aspect or any possible implementation thereof.

[0015] This invention provides a cooking control method and apparatus. By monitoring the cleanliness and damage state of the target peeled mung beans, and considering different varieties and their damage conditions, the method accurately monitors and adjusts parameters at each stage to perform reasonable pre-cooking, steaming, and grinding. This allows the mung beans to achieve the ideal softness and firmness, which is beneficial for subsequent grinding operations, resulting in a finer and more uniform powder. It also effectively reduces raw material waste caused by over- or under-processing. The process flow is more flexible and adaptable, capable of handling various raw material characteristics, enhancing the adaptability of the production process. By precisely controlling the parameters of each processing step, adjustments can be made flexibly according to the specific conditions of the mung beans, thereby ensuring the quality and consistency of the final product. Attached Figure Description

[0016] To more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0017] Figure 1 This is a flowchart illustrating the implementation of a cooking control method according to an embodiment of the present invention; Figure 2 This is a schematic diagram of a cooking control device provided in an embodiment of the present invention; Figure 3 This is a schematic diagram of a terminal provided in an embodiment of the present invention. Detailed Implementation

[0018] In the following description, specific details such as particular system architectures and techniques are set forth for illustrative purposes and not for limitation, in order to provide a thorough understanding of the embodiments of the invention. However, those skilled in the art will understand that the invention can be implemented in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, apparatuses, circuits, and methods are omitted so as not to obscure the description of the invention with unnecessary detail.

[0019] To make the objectives, technical solutions, and advantages of the present invention clearer, specific embodiments will be described below in conjunction with the accompanying drawings.

[0020] Ideally, the processing steps for peeled mung beans include: Washing: Put the peeled mung beans into the feed basket, use an overhead crane to lift them into the premixing tank, add clean water, turn on the air pump switch to wash for 5 minutes, drain the water, and then add clean water to cover the beans.

[0021] Precooking: Set the time to 30-40 minutes and the water temperature to 70-80℃. Turn on the heating switch. The temperature is automatically controlled. An alarm will sound automatically when the set time is reached. After turning off the heating switch, use a crane to lift the feed frame into the steaming trough.

[0022] Steaming: Cover the lid, tighten the latch, turn on the heating switch, steam for 60 minutes, open the pneumatic lifting lid, and use an overhead crane to lift the material frame to the grinder to grind it into powder for later use.

[0023] However, using fixed pre-cooking, steaming, and grinding parameters often fails to meet the optimal processing conditions for specific varieties or processing states. Therefore, this invention improves the steaming and cooking processing control method for peeled mung beans through the following technical solution.

[0024] See Figure 1 The diagram illustrates a flowchart of a cooking control method provided by an embodiment of the present invention, which is described in detail below: Step 101: Wash the target peeled mung beans and monitor the cleanliness and damage status of the target peeled mung beans.

[0025] In this embodiment, the mung beans need to be thoroughly washed before processing to remove surface dust, dirt, and other impurities. Washing generally refers to using airflow to remove light impurities such as leaves and grass clippings from the surface of the mung beans. This step can be accomplished using specialized washing equipment that generates strong airflow to blow away light impurities from the mung beans, while also filtering out damaged or incomplete beans.

[0026] Traditional mechanical or manual cleaning methods may result in incomplete cleaning, especially for surfaces with many impurities or highly adhesive contaminants. Furthermore, excessive airflow during the washing process can lead to the loss of mung bean particles, particularly smaller or broken ones, which are easily blown away.

[0027] In this embodiment, while the target peeled mung beans are being blown and washed, appropriate detection methods (such as visual inspection, magnifying glass or microscope inspection, water washing test and weight change method) are used to assess their cleanliness. At the same time, the damage status of the mung beans during the blowing and washing process is monitored to avoid damage caused by excessive mechanical action.

[0028] Step 102: If the cleanliness meets the preset cleanliness standard, the rinsing is deemed complete, and the pre-cooking parameters are determined based on the type, quantity, and damage status of the target peeled green.

[0029] In this embodiment, pre-cooking is a process of briefly heating cleaned mung beans in hot water. This process partially softens the mung beans, destroys anti-nutritional factors (such as protease inhibitors), and kills any microorganisms that may be present, thereby improving food safety. The pre-cooking time and temperature need to be adjusted according to the specific mung bean variety and the requirements of the final product.

[0030] Step 103: Precook the target peeled mung beans based on the precooking parameters, and monitor the first softness and hardness of the target peeled mung beans after precooking.

[0031] In this embodiment, ensuring that all mung beans are heated evenly during the pre-cooking process is a challenge, especially in large-scale production. Mung beans in different locations may become overcooked while others do not reach the desired softening level due to uneven heating. In addition, prolonged high-temperature pre-cooking can cause some water-soluble vitamins and other nutrients in the mung beans to be lost into the water.

[0032] Step 104: Determine the steaming parameters based on the first hardness, steam the target peeled mung beans based on the steaming parameters, and monitor the second hardness of the target peeled mung beans after steaming.

[0033] In this embodiment, the pre-cooked mung beans can be further steamed to fully cook them. Steaming makes the mung beans softer and easier to digest, while also better preserving their nutritional value. During the steaming process, the mung beans absorb an appropriate amount of water, which is crucial for the subsequent grinding step.

[0034] Precisely controlling the steaming time and temperature to achieve optimal taste and nutritional value retention is a technical challenge. Over-steaming will cause the mung beans to become too loose, affecting the texture of the final product; conversely, under-steaming may result in a product that is too hard. Furthermore, prolonged high-temperature steaming not only increases energy costs but may also have adverse environmental impacts.

[0035] Step 105: Determine grinding parameters based on the second hardness, and grind the target peeled mung beans based on the grinding parameters.

[0036] In this embodiment, the steamed mung beans can be used directly to make various foods, such as mung bean cakes and mung bean soup; alternatively, they can be further dried and ground into mung bean flour. Drying before grinding prevents the mung beans from clumping during the grinding process due to excessive moisture, which would affect the quality of the flour. Mung bean flour is a common food ingredient that can be used to make various foods such as noodles, desserts, and beverages. Different grinding mills can be selected during grinding, and the grinding effect can be adjusted according to the desired fineness.

[0037] If the equipment is not adjusted properly, the fineness of the ground mung bean powder may be inconsistent, affecting the taste and texture of the final product. If the grinding speed is too slow, the mung beans are prone to oxidation when exposed to air after grinding, leading to a decline in quality. Therefore, it is necessary to set the grinding parameters properly and to introduce nitrogen or other inert gases during the grinding process to replace the air and reduce oxidation.

[0038] This invention monitors the cleanliness and damage status of peeled mung beans, taking into account different varieties and their damage conditions. By accurately monitoring and adjusting parameters at each stage, and performing appropriate pre-cooking, steaming, and grinding, the mung beans achieve the ideal softness, facilitating subsequent grinding and resulting in a finer, more uniform powder. This also effectively reduces raw material waste caused by over- or under-processing. The process is more flexible and adaptable, capable of handling various raw material characteristics and enhancing the adaptability of the production process. By precisely controlling the parameters of each processing step, adjustments can be made flexibly according to the specific conditions of the mung beans, thereby ensuring the quality and consistency of the final product.

[0039] In one possible implementation, monitoring the cleanliness of the target peeled mung beans includes: The first area percentage of floating impurities in the water surface image of the premixing pool where the target peeled mung beans are located; Calculate the weight change of the target peeled mung beans before and after washing; Identify the second area ratio of impurities in the image of peeled mung beans after they have been washed. If the first area percentage is less than the first preset threshold, the weight change is greater than the second preset threshold, the second area percentage is less than the third preset threshold, and the blowing and washing time of the target peeled mung beans is greater than the preset time, then the blowing and washing is determined to be completed.

[0040] In this embodiment, the water surface image of the premixing tank refers to a photograph or video frame taken of the surface of the tank where the mung beans are placed before or after the rinsing process. Analyzing these images can assess the cleanliness of the mung beans after rinsing. A first preset threshold is used to determine whether the first area ratio of floating impurities is sufficiently low. Specifically, a high-resolution camera can be used to capture images of the water surface of the premixing tank, and image processing software (such as OpenCV) can be applied to analyze the images to calculate the proportion of floating impurities to the total area. If the proportion is high, it indicates that there are many impurities on the surface of the mung beans, and more intense rinsing conditions may be required.

[0041] The weight change of the target peeled mung beans before and after washing directly reflects the degree to which impurities on the surface of the mung beans are removed during the washing process, and is one of the important indicators for evaluating the washing effect. A second preset threshold is used to determine whether the weight change of the mung beans before and after washing is significant. Weight reduction means that surface-adhered impurities have been removed.

[0042] The second area ratio of impurities in the image after the target peeled mung beans have been washed is used to further confirm the cleanliness of the mung bean surface after washing, ensuring that there are no excessive impurities remaining that would affect the quality of subsequent processing. A third preset threshold is used to determine whether the second area ratio of residual impurities on the mung bean surface after washing meets the requirements. Similarly, after washing, a high-resolution image of the mung bean surface in the material frame can be taken, and image analysis technology can be used to calculate the proportion of impurities to the total area. If the proportion is lower than the third preset threshold, it is considered that an ideal cleanliness state has been achieved.

[0043] Using the above information along with the preset duration as a standard for judging the degree of cleanliness can ensure that the blowing and washing process has sufficient duration to effectively remove impurities. By comprehensively considering multiple factors (impurity area ratio, weight change, and blowing and washing duration), a comprehensive evaluation standard is provided to ensure that the blowing and washing is thorough but not excessive.

[0044] In one possible implementation, before monitoring the cleanliness of the target peeled mung beans, the following is also included: Multiple groups of peeled mung beans were subjected to a blowing and washing experiment, and the weight change of each group of peeled mung beans before and after blowing and washing was recorded; among them, the peeled mung beans of each group had different varieties, peeling methods and quantities. For each variety and peeling method, based on the number of peeled mung beans in each group and the weight change before and after washing, calculate the unit weight change corresponding to that variety and peeling method. The change in unit weight of the target peeled mung beans is determined based on the variety and peeling method of the target peeled mung beans, and a second preset threshold is determined based on the quantity and change in unit weight of the target peeled mung beans.

[0045] In this embodiment, both the variety of peeled mung beans and the peeling method affect the washing effect. Specifically, the influence of the variety of peeled mung beans includes: Differences in physical properties: Different varieties of mung beans may vary in size, shape, and skin thickness. For example, some varieties may have a rougher surface or more wrinkles, which increases the likelihood of impurities adhering to them, thus affecting the washing effect. Mung beans with varying surface smoothness are easier or more difficult to clean during the washing process, removing dust and other light impurities.

[0046] Differences in chemical composition: The oil content or other chemical components in mung beans can also affect their surface properties. Some varieties may contain a more natural waxy layer, which may reduce the adhesion of impurities, but may also make the cleaning process more complicated.

[0047] Initial impurity content: Mung bean varieties grown under different environments may have different types and quantities of natural impurities at harvest due to different growing conditions (such as soil type, climate conditions, etc.), which indirectly affects the difficulty of washing.

[0048] The effects of peeling methods include: Mechanical peeling: Mechanical peeling typically removes the outer skin of mung beans through friction. This method may cause minor scratches or damage to some mung beans, increasing surface unevenness and making it easier for impurities to adhere, thus increasing the difficulty of subsequent washing. If the peeling force is too great, it may also cause the mung beans to break, further affecting the washing effect and the quality of the final product.

[0049] Chemical peeling: Chemical peeling uses specific chemical reagents to soften and remove the outer skin of mung beans. This method is relatively gentle on mung beans, reducing damage to the beans themselves and theoretically helping to maintain a better surface condition, which is beneficial for subsequent cleaning. However, if chemical residues are not completely removed, new contaminants may be introduced, making cleaning more difficult and potentially affecting food safety.

[0050] Steam peeling: Steam peeling is a gentler method that uses high-temperature steam to cause the outer skin of the mung beans to expand and detach from the main body. Compared to mechanical peeling, this method causes less physical damage to the mung beans, helping to maintain better surface integrity and consistency, and facilitating subsequent washing. However, the mung beans may have high moisture content after steam peeling, requiring an additional drying step to avoid secondary contamination caused by excessive moisture.

[0051] In addition, impurities usually adhere to the surface of mung beans, and the more mung beans there are, the more impurities there will be.

[0052] Therefore, the second preset threshold needs to be determined based on the variety, peeling method, and quantity of peeled mung beans. The specific steps are as follows: 1. Data Collection and Preparation Sample selection: Select a certain number (e.g., at least 30 per variety) of peeled mung beans from different mung bean varieties as samples.

[0053] Record basic information, including mung bean variety name, peeling method (mechanical peeling, chemical peeling, etc.), and initial state (size, color, surface condition, etc.).

[0054] 2. Experimental Design for Washing Set the rinsing conditions: Determine the standard rinsing process, including the type of equipment used (dry air separator or wet cleaner), operating parameters (air velocity, water flow rate, etc.) and rinsing time, to achieve the rinsing completion state specified in step 102.

[0055] Perform rinsing: Rinse the selected mung bean sample according to the set conditions.

[0056] 3. Measure the change in weight. Precise weighing: Use an electronic balance with an accuracy of 0.001 grams to measure the weight of each mung bean before and after washing. Ensure that environmental conditions (such as temperature and humidity) are consistent for each weighing to reduce errors.

[0057] Calculate the mean and standard deviation: For each variety and peeling method combination of the sample, calculate the mean and standard deviation of the weight change before and after washing to understand its distribution.

[0058] 4. Determine the threshold Data Analysis: Based on the collected data, analyze the trend of weight change of mung beans before and after washing under different conditions. Pay attention to identifying outliers (which may be due to defects in the mung beans themselves or other factors), and consider removing these outliers before recalculating the statistics.

[0059] Set a threshold: Based on rules of thumb or through statistical methods (e.g., taking the mean plus twice the standard deviation as an upper limit), set a reasonable weight loss threshold for each variety and peeling method combination. This threshold should reflect the maximum acceptable weight reduction of mung beans after proper washing under most normal conditions.

[0060] 5. Verification and Adjustment Validation test: Repeat the above process using a new mung bean sample to verify whether the set threshold is reasonable and effective. If a large number of samples fail to meet the set standard, the threshold needs to be re-evaluated and adjusted.

[0061] Continuous monitoring: Apply this method in a real production environment by regularly checking and updating the thresholds to ensure they adapt to changing raw material properties and processing conditions.

[0062] In one possible implementation, monitoring the damage state of the target peeled mung beans includes: Sampling was performed on the target peeled mung beans; If the size and number of the sampled fragments are both within the first preset range, the damage status of the target peeled mung bean is determined to be low damage. If the size and number of the sampled fragments are both within the second preset range, the damage state of the target peeled mung bean is determined to be medium damage. If the size and number of the sampled fragments are both within the third preset range, then the damage state of the target peeled mung bean is determined to be high damage.

[0063] In this embodiment, a certain number of samples are randomly selected from a batch of target peeled mung beans for analysis by sampling. The size and number of fragments are measured, which can accurately assess the overall damage status of the mung beans.

[0064] Specifically, multiple samples can be randomly selected from different batches of peeled mung beans. The size and quantity of mung bean fragments in each sample are recorded. The size and quantity of fragments in each sample are statistically analyzed, and the mean and standard deviation are calculated. Based on the statistical results, first, second, and third preset ranges are set. For example: First preset range (low damage): fragment size less than 1mm and number of fragments less than 5%.

[0065] Second preset range (medium damage): fragment size between 1mm and 3mm and the number of fragments accounts for 5%-10% of the total.

[0066] Third preset range (high damage): fragment size greater than 3mm and number of fragments exceeding 10%.

[0067] Adjust subsequent processing parameters (such as pre-cooking temperature and time) based on different damage conditions to ensure product quality.

[0068] In one possible implementation, before determining the pre-cooking parameters based on the type, quantity, and damage state of the target peeled green, the following is also included: The type and damage state of peeled mung beans were used as input variables, pre-cooking parameters as adjustable variables, and grinding effect as output variables. Multiple levels of each variable were set, and orthogonal experiments were conducted on multiple groups of peeled mung beans after blowing and washing. A regression model was constructed based on the type, damage state, pre-cooking parameters, and grinding effect of the peeled mung beans after washing in each group; Accordingly, pre-cooking parameters are determined based on the type, quantity, and damage state of the target peeled green, including: The type, damage state, and expected grinding effect of the target peeled mung beans are input into the regression model to obtain the pre-cooking parameters of the target peeled mung beans.

[0069] In this embodiment, to determine the optimal pre-cooking temperature and time for peeled mung beans through orthogonal experiments, and considering the influence of mung bean type and damage state on grinding effect, a detailed experimental scheme can be designed. The specific implementation steps are as follows: 1. Define objectives and factors Objective: To optimize pre-cooking temperature and time to achieve the best grinding results.

[0070] Input variables (fixed factors): A: Mung bean varieties (e.g., variety A, variety B) B: Damage status (low damage, high damage) Adjustable variables (control factors): C: Precooking temperature (e.g., 70°C, 80°C, 90°C) D: Precooking time (e.g., 10 minutes, 20 minutes, 30 minutes) Output variables: Grinding effect (e.g., uniformity of fineness, particle size distribution). 2. Design an orthogonal experimental table We choose the L9(3^4) orthogonal array, as shown in Table 1.

[0071] Table 1

[0072] 3. Conduct the experiment For each experimental condition, perform the following steps: Prepare the same amount (e.g., 500 grams) of peeled mung beans.

[0073] Process according to the set pre-cooking temperature and time.

[0074] After pre-cooking, cool the mung beans to room temperature and record their condition.

[0075] Grind the pre-cooked mung beans, ensuring that the same equipment and settings are used.

[0076] Measure and record grinding performance indicators, such as fineness uniformity and particle size distribution.

[0077] 4. Regression Analysis After completing all experiments, the values ​​of the output variables (such as fineness uniformity or particle size distribution) under each experimental condition were recorded. As shown in Table 2, the data should include different combinations of levels of all input variables and their corresponding output results.

[0078] Table 2

[0079] If a linear relationship is assumed between the input and output variables, a multiple linear regression model can be used. If a non-linear relationship is anticipated, a quadratic or interaction term can be added to form a quadratic regression model. For categorical variables (such as variety and damage status), they need to be converted into numerical variables. Then, statistical software such as Minitab, SPSS, or R can be used to perform regression analysis. The software will automatically calculate the regression coefficients and significance levels (p-values) of each independent variable and provide an overall goodness-of-fit index for the model. Through the above steps, a mathematical model describing the relationship between the variety, damage status, pre-cooking temperature and time, and grinding effect of peeled mung beans can be constructed, thereby guiding the optimization of the production process.

[0080] This method not only helps to gain a deeper understanding of the impact of various factors on the grinding effect, but also effectively guides the optimization of the production process, ensuring stable and reliable product quality. In this way, the optimal pre-cooking parameters can be scientifically determined for specific mung bean varieties and damage conditions, thereby improving the quality and consistency of the final product.

[0081] In one possible implementation, the steaming parameters include steaming time; the steaming parameters are determined based on a first hardness / softness, including: The first softness / hardness level is determined by comparing it with the first softness / hardness threshold. If the first hardness is relatively hard, then the steaming parameter is determined to be the first steaming time; If the first softness / hardness is moderate, then the second steaming time is determined as the steaming parameter. If the first hardness is relatively soft, then the steaming parameter is determined to be the third steaming time.

[0082] In this embodiment, the effect of the state of the mung beans after pre-cooking on subsequent steps includes: Softness / Hardness: The degree of pre-cooking directly affects the softness / hardness of mung beans. If pre-cooking is insufficient, the mung beans may not fully absorb water and soften inside, which will require a longer steaming time to achieve the desired softening degree, and will also affect the efficiency and fineness of grinding.

[0083] Uniformity: If the mung beans are heated unevenly during the pre-cooking process, some mung beans may be overcooked while others are not fully softened. This unevenness will result in poor steaming and grinding effects, such as inconsistent powder fineness or uneven texture of steamed products.

[0084] Moisture content: The moisture content of pre-cooked mung beans also affects subsequent steps. Excessive moisture content may lead to prolonged steaming time or clumping during grinding; conversely, insufficient moisture may make further processing difficult. Adjusting the parameters for subsequent steaming steps based on the firmness of the pre-cooked peeled mung beans is crucial for ensuring consistent final product quality and optimizing the processing flow. The following are the specific operating steps and considerations: 1. Initial Assessment First, the hardness of mung beans can be measured using equipment such as a texture analyzer to classify them into grades of softness and hardness.

[0085] 2. Data Recording and Classification Based on the firmness of the mung beans after pre-cooking, they are divided into several grades, for example: Very hard: It hardly softens and retains its original hardness.

[0086] Relatively hard: It has softened to some extent but is still relatively hard.

[0087] Moderate: Achieves the ideal softness and hardness, suitable for further processing.

[0088] Too soft: Excessive softening may affect the quality of subsequent processing.

[0089] Record the specific hardness value or grade of each sample, as well as the corresponding pre-cooking conditions (temperature and time).

[0090] 3. Determine the steaming parameters Based on the above classification results, corresponding steaming parameters are set for mung beans with different levels of softness and firmness: For "very hard" or "relatively hard" mung beans, increase steaming time and / or raise the temperature: Since these mung beans are not yet fully softened, it is necessary to extend the steaming time or appropriately increase the steaming temperature so that they can be fully cooked and reach the desired softness. A staged steaming method can also be used: first, use a lower temperature to allow the mung beans to gradually absorb water and expand, then increase the temperature to accelerate the penetration of internal moisture, and finally lower the temperature to stabilize.

[0091] For "moderately cooked" mung beans, if they have reached the ideal firmness, simply follow the pre-set standard steaming conditions. This typically includes a moderate temperature (e.g., 80°C - 90°C) and a fixed time (e.g., 20 - 30 minutes), sufficient to fully cook the mung beans without overcooking them.

[0092] For overly soft mung beans, reduce steaming time and / or lower the temperature: To prevent mung beans from becoming too loose or losing their structural integrity due to over-steaming, shorten the steaming time or lower the steaming temperature. Immediately after steaming, rapid cooling can help stop the cooking process and prevent the mung beans from becoming further soft.

[0093] The first, second, and third steaming times can all be set according to the experiment.

[0094] 4. Experimental Verification and Optimization To find the optimal steaming parameters for each situation, it is recommended to conduct a series of small-scale experiments: Apply the recommended steaming parameter combinations above under different hardness conditions.

[0095] Measure and record the results of each experiment, including key indicators such as the final softness and hardness of the mung beans, their texture, and color changes.

[0096] Analyze the data to identify the optimal steaming conditions and develop operating guidelines accordingly.

[0097] 5. Continuous monitoring and adjustment In actual production, the pre-cooking and steaming effects of mung beans are continuously monitored, and the database and operating guidelines are updated regularly to adapt to changes in raw material characteristics or other external factors.

[0098] This method allows for flexible adjustment of steaming parameters based on the firmness of the pre-cooked, peeled mung beans, ensuring the quality and consistency of the final product. Furthermore, it's a dynamic process; with accumulated experience and technological advancements, the process can be continuously optimized to improve production efficiency and product quality.

[0099] The specific steps for determining the steaming parameters may include: Adjust the steaming time and temperature according to the softness or firmness of the mung beans: If the pre-cooked mung beans are already quite soft, you can appropriately reduce the steaming temperature or shorten the steaming time to prevent overcooking and causing the structure to become too loose.

[0100] If the mung beans are still too hard, you need to increase the steaming time or raise the temperature to ensure that the mung beans are softened enough to be suitable for the next step of processing.

[0101] Monitor the condition of the mung beans and make minor adjustments: During the steaming process, small samples are periodically taken out to check their softening level, and the remaining steaming time and temperature are adjusted accordingly.

[0102] In one possible implementation, the grinding parameters include grinding speed and grinding pressure; the grinding parameters are determined based on the second softness / hardness, including: The second softness / hardness level is determined by comparing it with the second softness / hardness threshold. If the second hardness is relatively hard, then the grinding parameters are determined to be the first grinding speed and the first grinding pressure; If the second hardness is moderate, then the grinding parameters are determined to be the second grinding speed and the second grinding pressure. If the second hardness is relatively soft, then the grinding parameters are determined to be the third grinding speed and the third grinding pressure.

[0103] In this embodiment, the second softness / hardness threshold is different from the first softness / hardness threshold, and both can be set based on actual conditions.

[0104] Determining grinding parameters requires considering the moisture content and hardness of the mung beans. For mung beans with high moisture content and relatively soft texture, a lower speed and pressure can be selected for grinding to avoid generating excessive heat that could cause oxidation or gelatinization. If the mung beans are relatively dry or hard, a higher speed and pressure may be needed to achieve the desired fineness, but it is important to control the temperature to prevent overheating from affecting product quality.

[0105] Conduct small-scale experiments to try different grinding mill settings (such as speed, pressure, etc.) and record the results of each experiment, including indicators such as powder fineness, uniformity and taste. Based on this, determine the optimal parameter combination and determine the first grinding speed, first grinding pressure, second grinding speed, second grinding pressure, third grinding speed and third grinding pressure.

[0106] It should be understood that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0107] The following are device embodiments of the present invention. For details not described in detail, please refer to the corresponding method embodiments described above.

[0108] Figure 2 A schematic diagram of a cooking control device according to an embodiment of the present invention is shown. For ease of explanation, only the parts related to the embodiment of the present invention are shown, and are described in detail below: like Figure 2 As shown, a cooking control device 2 includes: The blowing and washing monitoring module 21 is used to blow and wash the target peeled mung beans and monitor the cleanliness and damage status of the target peeled mung beans. The pre-cooking determination module 22 is used to determine that the rinsing is complete when the cleanliness meets the preset cleanliness standard, and to determine the pre-cooking parameters based on the type, quantity and damage status of the target peeled green. The pre-cooking monitoring module 23 is used to pre-cook the target peeled mung beans based on the pre-cooking parameters and monitor the first softness and hardness of the target peeled mung beans after pre-cooking. The steaming monitoring module 24 is used to determine the steaming parameters based on the first softness and hardness, steam the target peeled mung beans based on the steaming parameters, and monitor the second softness and hardness of the target peeled mung beans after steaming. The grinding determination module 25 is used to determine grinding parameters based on the second softness and hardness, and grind the target peeled mung beans based on the grinding parameters.

[0109] In one possible implementation, the purging monitoring module 21 is specifically used for: The first area percentage of floating impurities in the water surface image of the premixing pool where the target peeled mung beans are located; Calculate the weight change of the target peeled mung beans before and after washing; Identify the second area ratio of impurities in the image of peeled mung beans after they have been washed. If the first area percentage is less than the first preset threshold, the weight change is greater than the second preset threshold, the second area percentage is less than the third preset threshold, and the blowing and washing time of the target peeled mung beans is greater than the preset time, then the blowing and washing is determined to be completed.

[0110] In one possible implementation, the purging monitoring module 21 is also used for: Before monitoring the cleanliness of the target peeled mung beans, a blow-washing test was conducted on multiple groups of peeled mung beans, and the weight change of each group of peeled mung beans before and after blow-washing was recorded; among them, the peeled mung beans of each group had different varieties, peeling methods and quantities. For each variety and peeling method, based on the number of peeled mung beans in each group and the weight change before and after washing, calculate the unit weight change corresponding to that variety and peeling method. The change in unit weight of the target peeled mung beans is determined based on the variety and peeling method of the target peeled mung beans, and a second preset threshold is determined based on the quantity and change in unit weight of the target peeled mung beans.

[0111] In one possible implementation, the purging monitoring module 21 is specifically used for: Sampling was performed on the target peeled mung beans; If the size and number of the sampled fragments are both within the first preset range, the damage status of the target peeled mung bean is determined to be low damage. If the size and number of the sampled fragments are both within the second preset range, the damage state of the target peeled mung bean is determined to be medium damage. If the size and number of the sampled fragments are both within the third preset range, then the damage state of the target peeled mung bean is determined to be high damage.

[0112] In one possible implementation, the pre-cooking determination module 22 is also used for: Before determining the pre-cooking parameters based on the type, quantity, and damage state of the target peeled mung beans, the type and damage state of the peeled mung beans were used as input variables, the pre-cooking parameters as adjustable variables, and the grinding effect as output variables. Multiple levels of each variable were set, and orthogonal experiments were conducted on multiple groups of peeled mung beans after blowing and washing. A regression model was constructed based on the type, damage state, pre-cooking parameters, and grinding effect of the peeled mung beans after washing in each group; The type, damage state, and expected grinding effect of the target peeled mung beans are input into the regression model to obtain the pre-cooking parameters of the target peeled mung beans.

[0113] In one possible implementation, the steaming parameters include the steaming time; the steaming monitoring module 24 is specifically used for: The first softness / hardness level is determined by comparing it with the first softness / hardness threshold. If the first hardness is relatively hard, then the steaming parameter is determined to be the first steaming time; If the first softness / hardness is moderate, then the second steaming time is determined as the steaming parameter. If the first hardness is relatively soft, then the steaming parameter is determined to be the third steaming time; The first steaming time is longer than the second steaming time, and the second steaming time is longer than the third steaming time.

[0114] In one possible implementation, the grinding parameters include grinding speed and grinding pressure; the grinding determination module 25 is specifically used for: The second softness / hardness level is determined by comparing it with the second softness / hardness threshold. If the second hardness is relatively hard, then the grinding parameters are determined to be the first grinding speed and the first grinding pressure; If the second hardness is moderate, then the grinding parameters are determined to be the second grinding speed and the second grinding pressure. If the second hardness is relatively soft, then the grinding parameters are determined to be the third grinding speed and the third grinding pressure; The first grinding speed is greater than the second grinding speed, and the second grinding speed is greater than the third grinding speed; the first grinding pressure is greater than the second grinding pressure, and the second grinding pressure is greater than the third grinding pressure.

[0115] This invention monitors the cleanliness and damage status of peeled mung beans, taking into account different varieties and their damage conditions. By accurately monitoring and adjusting parameters at each stage, and performing appropriate pre-cooking, steaming, and grinding, the mung beans achieve the ideal softness, facilitating subsequent grinding and resulting in a finer, more uniform powder. This also effectively reduces raw material waste caused by over- or under-processing. The process is more flexible and adaptable, capable of handling various raw material characteristics and enhancing the adaptability of the production process. By precisely controlling the parameters of each processing step, adjustments can be made flexibly according to the specific conditions of the mung beans, thereby ensuring the quality and consistency of the final product.

[0116] Figure 3 This is a schematic diagram of a terminal provided in an embodiment of the present invention. Figure 3 As shown, the terminal 3 in this embodiment includes a processor 30, a memory 31, and a computer program 32 stored in the memory 31 and executable on the processor 30. When the processor 30 executes the computer program 32, it implements the steps of each of the above-described embodiments of the cooking control method, for example... Figure 1 Steps 101 to 105 are shown. Alternatively, when processor 30 executes computer program 32, it implements the functions of each module / unit in the above-described device embodiments, for example... Figure 2 The functions of modules 21 to 25 are shown.

[0117] For example, computer program 32 can be divided into one or more modules / units, one or more of which are stored in memory 31 and executed by processor 30 to complete the present invention. One or more modules / units can be a series of computer program instruction segments capable of performing a specific function, which describe the execution process of computer program 32 in terminal 3. For example, computer program 32 can be divided into... Figure 2 Modules 21 to 25 are shown.

[0118] Terminal 3 can be a computing device such as a desktop computer, laptop, handheld computer, or cloud server. Terminal 3 may include, but is not limited to, a processor 30 and a memory 31. Those skilled in the art will understand that... Figure 3 This is merely an example of terminal 3 and does not constitute a limitation on terminal 3. It may include more or fewer components than shown, or combine certain components, or different components. For example, the terminal may also include input / output devices, network access devices, buses, etc.

[0119] The processor 30 may be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor.

[0120] The memory 31 can be an internal storage unit of the terminal 3, such as a hard disk or RAM of the terminal 3. The memory 31 can also be an external storage device of the terminal 3, such as a plug-in hard disk, Smart MediaCard (SMC), Secure Digital (SD) card, or Flash Card equipped on the terminal 3. Furthermore, the memory 31 can include both internal and external storage units of the terminal 3. The memory 31 is used to store computer programs and other programs and data required by the terminal. The memory 31 can also be used to temporarily store data that has been output or will be output.

[0121] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is merely an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiments can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit. Furthermore, the specific names of the functional units and modules are only for easy differentiation and are not intended to limit the scope of protection of this application. The specific working process of the units and modules in the above system can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0122] In the above embodiments, the descriptions of each embodiment have different focuses. For parts that are not described in detail or recorded in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0123] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this invention.

[0124] In the embodiments provided by this invention, it should be understood that the disclosed devices / terminals and methods can be implemented in other ways. For example, the device / terminal embodiments described above are merely illustrative. For instance, the division of modules or units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between devices or units may be electrical, mechanical, or other forms.

[0125] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0126] Furthermore, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0127] If integrated modules / units are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the methods of the above embodiments of the present invention can also be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of each of the above-described embodiments of the cooking control method. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include: any entity or device capable of carrying computer program code, recording media, USB flash drives, portable hard drives, magnetic disks, optical disks, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signals, telecommunication signals, and software distribution media, etc. It should be noted that the content included in the computer-readable medium can be appropriately added or removed according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, the computer-readable medium does not include electrical carrier signals and telecommunication signals.

[0128] The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included within the protection scope of the present invention.

Claims

1. A cooking control method characterized by, include: The target peeled mung beans were blown and washed, and the cleanliness and damage status of the target peeled mung beans were monitored; If the degree of cleanliness meets the preset cleanliness standard, the washing is deemed complete, and the pre-cooking parameters are determined based on the type and quantity of the target peeled mung beans and the damage status. The target peeled mung beans are pre-cooked based on the pre-cooking parameters, and the first softness and hardness of the target peeled mung beans after pre-cooking are monitored. Based on the first hardness, steaming parameters are determined, and the target peeled mung beans are steamed based on the steaming parameters. The second hardness of the target peeled mung beans after steaming is monitored. The grinding parameters are determined based on the second hardness, and the target peeled mung beans are ground based on the grinding parameters; Monitoring the cleanliness of the target peeled mung beans includes: Identify the first area percentage of floating impurities in the water surface image of the premixing pool where the target peeled mung beans are located; Calculate the weight change of the target peeled mung beans before and after washing; Identify the second area ratio of impurities in the image of the target peeled mung beans after they have been blown and washed. If the first area percentage is less than the first preset threshold, the weight change is greater than the second preset threshold, the second area percentage is less than the third preset threshold, and the blowing and washing time of the target peeled mung bean is greater than the preset time, then the blowing and washing is determined to be completed. Before monitoring the cleanliness of the target peeled mung beans, the method further includes: Multiple groups of peeled mung beans were subjected to a blowing and washing experiment, and the weight change of each group of peeled mung beans before and after blowing and washing was recorded; among them, the peeled mung beans of each group had different varieties, peeling methods and quantities. For each variety and peeling method, based on the number of peeled mung beans in each group and the weight change before and after washing, calculate the unit weight change corresponding to that variety and peeling method. The change in unit weight of the target peeled mung beans is determined based on the variety and peeling method of the target peeled mung beans, and the second preset threshold is determined based on the quantity of the target peeled mung beans and the change in unit weight.

2. The cooking control method according to claim 1, characterized by, Monitoring the damage state of the target peeled mung beans includes: Sampling was performed on the target peeled mung beans; If the size and number of the sampled fragments are both within the first preset range, then the damage state of the target peeled mung bean is determined to be low damage. If the size and number of the sampled fragments are both within the second preset range, then the damage state of the target peeled mung bean is determined to be moderate damage. If the size and number of the sampled fragments are both within the third preset range, then the damage state of the target peeled mung bean is determined to be high damage.

3. The cooking control method according to claim 1, characterized by, Before determining the pre-cooking parameters based on the type, quantity, and damage state of the target peeled mung beans, the method further includes: The type and damage state of peeled mung beans were used as input variables, pre-cooking parameters as adjustable variables, and grinding effect as output variables. Multiple levels of each variable were set, and orthogonal experiments were conducted on multiple groups of peeled mung beans after blowing and washing. A regression model was constructed based on the type, damage state, pre-cooking parameters, and grinding effect of the peeled mung beans after washing in each group; Accordingly, determining the pre-cooking parameters based on the type and quantity of the target peeled mung beans and the state of damage includes: The type, damage state, and expected grinding effect of the target peeled mung beans are input into the regression model to obtain the pre-cooking parameters of the target peeled mung beans.

4. The cooking control method according to claim 1, characterized by, The steaming parameters include steaming time; determining the steaming parameters based on the first hardness includes: The first softness / hardness is compared with a first softness / hardness threshold to determine the level of the first softness / hardness. If the first hardness is relatively hard, then the steaming parameter is determined to be the first steaming time; If the first hardness is moderate, then the steaming parameter is determined to be the second steaming time; If the first hardness is relatively soft, then the steaming parameter is determined to be the third steaming time; The first steaming time is longer than the second steaming time, and the second steaming time is longer than the third steaming time.

5. The cooking control method according to claim 1, characterized in that, The grinding parameters include grinding speed and grinding pressure; The determination of grinding parameters based on the second hardness includes: The second softness / hardness is compared with a second softness / hardness threshold to determine the level of the second softness / hardness. If the second hardness is relatively hard, then the grinding parameters are determined to be the first grinding speed and the first grinding pressure; If the second hardness is moderate, then the grinding parameters are determined to be the second grinding speed and the second grinding pressure. If the second hardness is relatively soft, then the grinding parameters are determined to be the third grinding speed and the third grinding pressure; The first grinding speed is greater than the second grinding speed, and the second grinding speed is greater than the third grinding speed; the first grinding pressure is greater than the second grinding pressure, and the second grinding pressure is greater than the third grinding pressure.

6. A cooking control device characterized by comprising: include: The blowing and washing monitoring module is used to blow and wash the target peeled mung beans and monitor the cleanliness and damage status of the target peeled mung beans; The pre-cooking determination module is used to determine that the washing is complete when the cleanliness meets the preset cleanliness standard, and to determine the pre-cooking parameters based on the type and quantity of the target peeled mung beans and the damage state. The pre-cooking monitoring module is used to pre-cook the target peeled mung beans based on the pre-cooking parameters and monitor the first softness and hardness of the target peeled mung beans after pre-cooking. A steaming monitoring module is used to determine steaming parameters based on the first softness and hardness, steam the target peeled mung beans based on the steaming parameters, and monitor the second softness and hardness of the target peeled mung beans after steaming. The grinding determination module is used to determine grinding parameters based on the second hardness, and grind the target peeled mung beans based on the grinding parameters; The blow-wash monitoring module is specifically used for: The first area percentage of floating impurities in the water surface image of the premixing pool where the target peeled mung beans are located; Calculate the weight change of the target peeled mung beans before and after washing; Identify the second area ratio of impurities in the image of peeled mung beans after they have been washed. If the first area percentage is less than the first preset threshold, the weight change is greater than the second preset threshold, the second area percentage is less than the third preset threshold, and the blowing and washing time of the target peeled mung bean is greater than the preset time, then the blowing and washing is determined to be completed. The blow-wash monitoring module is also used for: Before monitoring the cleanliness of the target peeled mung beans, a blow-washing test was conducted on multiple groups of peeled mung beans, and the weight change of each group of peeled mung beans before and after blow-washing was recorded; among them, the peeled mung beans of each group had different varieties, peeling methods and quantities. For each variety and peeling method, based on the number of peeled mung beans in each group and the weight change before and after washing, calculate the unit weight change corresponding to that variety and peeling method. The change in unit weight of the target peeled mung beans is determined based on the variety and peeling method of the target peeled mung beans, and a second preset threshold is determined based on the quantity and change in unit weight of the target peeled mung beans.

7. A terminal, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the method as described in any one of claims 1 to 5 above.

8. A computer-readable storage medium storing a computer program, the computer-readable storage medium comprising: When the computer program is executed by a processor, it implements the steps of the method as described in any one of claims 1 to 5 above.

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