Artificial intelligence-based oatmeal food processing control method and system

Abstract

This invention discloses an artificial intelligence-based method and system for controlling the processing of oatmeal porridge, relating to the fields of food science and engineering technology. The method includes: constructing conditional and result determination parameters for each process step; using process analysis methods to obtain compliant mapping intervals; using mapping influence testing to obtain the influence trend of conditions; and controlling the oatmeal porridge processing based on the influence trend of preceding process parameters. This invention addresses the problem in existing oatmeal porridge processing control methods that lack a method for correlating controllable conditions and nutritional quality indicators in adjacent processes. This results in rigid and fixed process parameters that cannot dynamically adapt to the material state, leading to significant differences in the nutritional quality of batches of oatmeal porridge and its susceptibility to rancidity and spoilage during storage.

Description

Technical Field

[0001] This invention relates to the field of food science and engineering technology, specifically to an artificial intelligence-based method and system for controlling the processing of oatmeal porridge. Background Technology

[0002] Oatmeal porridge processing involves using oat grains as the main raw material, cleaning, removing impurities, and inactivating enzymes to produce semi-finished products such as oat flakes or oat flour, and then processing them through blending, cooking, sterilization, and packaging to create ready-to-eat, quick-cooking, or traditionally cooked oatmeal porridge products. Oatmeal porridge processing control requires strict control over four aspects: raw materials, processes, hygiene, and quality. It is essential to strictly control the moisture content and enzyme activity of the raw materials, accurately manage the cooking temperature, avoid nutrient loss and scorching, and ensure stable product taste and safety compliance.

[0003] Existing methods for controlling the processing of oatmeal porridge typically involve controlling the heating time of the heating device, the rotation speed of the blades during pulverization, and the cooking temperature, or acquiring characteristic data of the ingredients to control ingredient sorting during processing. While these methods ensure the continuous operation of the food processing process while avoiding common errors, they lack methods for linking controllable conditions and nutritional quality indicators in adjacent processes. This results in rigid and fixed process parameters that cannot dynamically adapt to the material's state, leading to over-heating and mechanical damage during processing. Consequently, this causes significant batch-to-batch variations in nutritional quality, weakened health benefits, and susceptibility to rancidity during storage. For example, in patent application CN120052488A... A method for monitoring and controlling the processing of miscellaneous grains has been developed. This method involves obtaining the target formula based on user needs, acquiring the characteristic data of the miscellaneous grains to be tested, adjusting the parameters of the photoelectric sorter based on the characteristic data to sort various miscellaneous grains, and then processing and packaging the sorted grains. Other improvements to oatmeal porridge food processing control methods usually focus on improvements to processing equipment. In terms of process parameter control, there is still a lack of methods to correlate controllable conditions and nutritional quality indicators in adjacent processes. This results in fixed and rigid process parameters for each process that cannot be dynamically adapted to the material state, leading to excessive heat processing and mechanical damage during processing. Consequently, oatmeal porridge batches exhibit significant differences in nutritional quality, weakened health attributes, and susceptibility to rancidity and spoilage during storage. Therefore, it is necessary to improve the existing oatmeal porridge food processing control methods. Summary of the Invention

[0004] This invention aims to at least partially solve one of the technical problems in the prior art by proposing an artificial intelligence-based oatmeal porridge food processing control method and system. This method addresses the lack of a mechanism in existing oatmeal porridge food processing control methods that correlates controllable conditions and nutritional quality indicators in adjacent processes. This results in rigid and fixed process parameters for each process that cannot be dynamically adapted to the material state, leading to excessive heat processing and mechanical damage during processing. Consequently, the nutritional quality of oatmeal porridge varies greatly from batch to batch, its health attributes are weakened, and it is prone to rancidity and spoilage during storage.

[0005] To achieve the above objectives, in a first aspect, this application provides an artificial intelligence-based method for controlling the processing of oatmeal porridge, comprising the following steps: The process of oat porridge food processing is obtained. Based on the historical processing data of oat porridge food processing, condition judgment parameters and result judgment parameters in the process are constructed. Based on artificial intelligence, process analysis methods are used to obtain the compliance mapping range of each condition judgment parameter and result judgment parameter. Based on the compliance mapping range of all condition judgment parameters and result judgment parameters in each process, the mapping influence test method is used to obtain the condition influence trend of all result judgment parameters in each process. When controlling the processing of oatmeal porridge, the result judgment parameters obtained in real time in each process are recorded as the preceding process parameters, and the processing of oatmeal porridge is controlled based on the conditional influence trend of the preceding process parameters.

[0006] Furthermore, the processing steps of oatmeal porridge are obtained, and based on historical processing data, conditional and result determination parameters for each step are constructed, including: Based on the technological requirements for processing oatmeal porridge, the processing steps for oatmeal porridge are sequentially labeled as processing step JG1 to processing step JG. t For any processing step JG r Based on historical processing data of oatmeal porridge food processing, obtain JG for each processing step performed. r The conditional judgment parameters and result judgment parameters corresponding to the time process, where r is a positive integer less than or equal to t and greater than or equal to 1; The condition determination parameter is the processing step JG. r The ambient temperature, processing time, process pressure, and material moisture content within the process, especially during processing step JG r When there is a sealing device inside the material enclosure, the process pressure is the pressure inside the sealing device. During processing step JG... r When there is no sealing device containing encapsulated material, the process pressure is the processing pressure JG. r The pressure of the environment.

[0007] Furthermore, the condition determination parameters and result determination parameters in the construction process also include: The result determination parameter is the processing procedure JG. r After completion, the β-glucan retention rate, polyphenol retention rate, real-time GI value corresponding to starch gelatinization, and enzyme inactivation rate were obtained from the material detection. Among them, the enzyme inactivation rate is the sum of the inactivation rates of lipase and oxidase. Obtain the condition and result parameters for each processing step when it is executed.

[0008] Furthermore, process analysis methods include: For any processing step JG r From the historical processing data of oat food processing, processing steps JG r The executed processes are sequentially denoted as process process XC1 to process process XC. e ; For any conditional decision parameter α, process XC1 to process XC e The values ​​of the conditional decision parameter α are denoted as α1 to α2 respectively. e , from α1 to α e The closed interval formed by the minimum and maximum values ​​in the process is denoted as processing step JG. r The compliance mapping interval corresponding to the conditional decision parameter α.

[0009] Furthermore, process analysis methods also include: For any result determination parameter β, process XC1 to process XC e The values ​​of the result determination parameter β are denoted as β1 to β2 respectively. e , from β1 to β e The closed interval formed by the minimum and maximum values ​​in the process is denoted as processing step JG. r The compliance mapping interval corresponding to the result judgment parameter β; Obtain processing steps JG r Compliance mapping range corresponding to all conditional and result determination parameters.

[0010] Furthermore, the mapping effect testing method includes: For any processing step JG r Given any conditional decision parameter α and result decision parameter β, denote the units corresponding to conditional decision parameter α and result decision parameter β as Q and P respectively; establish a Cartesian coordinate system with units of P and Q for the X-axis and Y-axis respectively, and denote it as the influence analysis coordinate system; For processing steps JG r Any process XC wIn the influence analysis coordinate system, point [β] w α w This is denoted as process progress XC. w The parameter point is denoted by , where w is a positive integer less than or equal to e and greater than or equal to 1.

[0011] Furthermore, the mapping effect test method also includes: Obtain the machining process JG within the influence analysis coordinate system. r The parameter points corresponding to all process steps are identified, and the curve obtained by fitting all parameter points is recorded as the influence analysis curve; when the influence analysis curve is monotonically increasing, the condition judgment parameter α is recorded as the positive influence parameter of the result judgment parameter β. When the influence analysis curve is monotonically decreasing, the condition judgment parameter α is recorded as the reverse influence parameter of the result judgment parameter β; When the influence analysis curve has peaks or troughs, the ordinate of the point corresponding to the peak is marked as the increase value of the result judgment parameter β, and the ordinate of the point corresponding to the trough is marked as the decrease value of the result judgment parameter β. The positive influence parameter, negative influence parameter, increase value, and decrease value obtained after analyzing the result judgment parameter β with all condition judgment parameters are denoted as the condition influence trend of the result judgment parameter β. Obtain the influence trend of all result judgment parameters in all processing steps.

[0012] Furthermore, when controlling the processing of oatmeal porridge, the result judgment parameters obtained in real time in each process are recorded as preceding process parameters, and the processing of oatmeal porridge is controlled based on the conditional influence trend of the preceding process parameters, including: When controlling the processing of oatmeal porridge, for any processing step JG v When processing step JG v Upon completion, process JG will be performed. v All result determination parameters obtained in the process are recorded as preceding process parameters, where v is a positive integer less than or equal to t-1 and greater than or equal to 1; For any preceding process parameter, if the preceding process parameter is outside the interval γ, the processing step JG is stopped. v And notify the staff about the processing procedure JG v The equipment in the process is inspected, where interval γ represents the processing step JG. v Compliance mapping range corresponding to preceding process parameters; When the preceding process parameter is in the upper range of interval Ω, or greater than the maximum value in interval Ω, the preceding process parameter is recorded as the downward adjustment control parameter, where interval Ω represents the processing step JG. v+1The compliance mapping interval corresponding to the preceding process parameters, the upper interval of the interval Ω is the closed interval formed by the maximum value and the median value in the interval Ω; When the preceding process parameter is in the lower interval of the interval Ω, or is less than the minimum value in the interval Ω, the preceding process parameter is recorded as the upward control parameter. The lower interval of the interval Ω is the closed interval formed by the minimum value and the median value in the interval Ω. If the preceding process parameter is equal to the midpoint of the interval Ω, the preceding process parameter is not marked.

[0013] Furthermore, controlling the oatmeal porridge food processing process based on the influence trends of preceding process parameters also includes: In the processing step JG v After completion, proceed with the processing step JG v+1 At that time, for the processing step JG v For any one of the preceding process parameters obtained, perform mapping control analysis on the preceding process parameter; Mapping control analysis includes: when the preceding process parameter is recorded as a downward control parameter, the processing step JG is... v+1 The positive influence parameters of the preceding process parameters are denoted as the downward adjustment condition parameters, and the processing step JG is used. v+1 The reverse influence parameters of the preceding process parameters are denoted as the adjustment condition parameters, and the processing step JG is used. v+1 The decrease in the preceding process parameters is recorded as a value to be determined; When the preceding process parameter is recorded as an upward control parameter, the processing step JG will be... v+1 The positive influence parameters of the preceding process parameters are denoted as the adjustment condition parameters, and the processing steps JG are... v+1 The reverse influence parameters of the preceding process parameters are denoted as the adjustment condition parameters, and the processing step JG is used. v+1 The increase value of the preceding process parameters is recorded as the undetermined value; When the processing step JG v After performing mapping control analysis on all acquired preceding process parameters, for any conditional decision parameter α: when the conditional decision parameter α is only recorded as a down-adjustment conditional parameter and there is no value corresponding to the conditional decision parameter α among the pending values, in processing step JG v+1 The conditional decision parameter α is lowered, while maintaining the lowered conditional decision parameter α within the processing step JG. v+1 Within the compliance mapping range corresponding to the conditional decision parameter α; When the conditional decision parameter α is recorded as a downward adjustment conditional parameter and the value corresponding to the conditional decision parameter α in the undetermined values ​​is only a decrease, in processing step JG v+1 The conditional decision parameter α is adjusted to the value corresponding to the conditional decision parameter α in the undetermined value; When the conditional decision parameter α is only recorded as an upward adjustment conditional parameter and there is no value corresponding to the conditional decision parameter α among the pending values, in processing step JG v+1 The conditional decision parameter α is increased, and the increased conditional decision parameter α is kept within the processing step JG. v+1 Within the compliance mapping range corresponding to the conditional decision parameter α; When the conditional judgment parameter α is recorded as an upward adjustment conditional parameter and the value corresponding to the conditional judgment parameter α in the undetermined values ​​is only an increase value, in the processing step JG v+1 The conditional decision parameter α is adjusted to the value corresponding to the conditional decision parameter α in the undetermined value.

[0014] Secondly, this application also provides an artificial intelligence-based oatmeal porridge food processing control system, including a process parameter acquisition module, a parameter mapping analysis module, and a parameter collaborative control module; The process parameter acquisition module is used to acquire the process of oat porridge food processing. Based on the historical processing data of oat porridge food processing, it constructs the condition judgment parameters and result judgment parameters in the process, and uses process analysis methods based on artificial intelligence to obtain the compliance mapping range of each condition judgment parameter and result judgment parameter. The parameter mapping analysis module is used to obtain the conditional influence trend of all result judgment parameters in each process based on the compliance mapping range of all condition judgment parameters and result judgment parameters in each process, using the mapping influence test method. The parameter collaborative control module is used to record the result judgment parameters obtained in real time in each process as the preceding process parameters when controlling the processing of oat porridge food, and to control the processing of oat porridge food based on the condition influence trend of the preceding process parameters.

[0015] The beneficial effects of this invention are as follows: This application first obtains the processing steps of oat porridge food, and based on the historical processing data of oat porridge food, constructs condition judgment parameters and result judgment parameters in the process. Then, based on artificial intelligence, it uses process analysis methods to obtain the compliant mapping range of each condition judgment parameter and result judgment parameter. The advantage of this is that by constructing condition judgment parameters and result judgment parameters in the process, the parameters related to controllable conditions and nutritional quality indicators in each process can be marked. This allows for the use of process analysis methods to obtain the compliant mapping range of each condition judgment parameter and result judgment parameter, which can provide data support and effective constraints for the parameter analysis between subsequent processes. As a result, the condition influence trend obtained in the mapping influence test method conforms to the actual correlation between controllable conditions and nutritional quality indicators within the process, thereby improving the control accuracy when controlling the oat porridge food processing process. This application also uses the mapping influence test method to obtain the conditional influence trend of all result judgment parameters in each process based on the compliance mapping range of all condition judgment parameters and result judgment parameters in each process. Finally, when controlling the oat porridge food processing, the result judgment parameters obtained in real time in each process are recorded as the preceding process parameters, and the oat porridge food processing process is controlled based on the conditional influence trend of the preceding process parameters. The advantage of this is that by using the mapping influence test method to obtain the conditional influence trend of all result judgment parameters in each process, the influence change trend of controllable conditions in the process on the nutritional quality result indicators can be effectively analyzed. This allows for flexible adjustment of process parameters in each process based on the conditional influence trend of the result judgment parameters when controlling the oat porridge food processing, so that the material state can be dynamically adapted, thereby avoiding the loss of nutritional components in the oat porridge during processing and improving the nutritional quality of the oat porridge batch. Attached Figure Description

[0016] Figure 1 This is a schematic diagram of the system of the present invention; Figure 2 This is a flowchart illustrating the steps of the method of the present invention; Figure 3 This is a schematic diagram illustrating the acquisition of the influence analysis curves of the present invention; Figure 4 This is a schematic diagram of the electronic device of the present invention. Detailed Implementation

[0017] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0018] Example 1, please refer to Figure 1 As shown, this application provides an artificial intelligence-based oatmeal porridge food processing control system, including a process parameter acquisition module, a parameter mapping analysis module, and a parameter collaborative control module; The process parameter acquisition module is used to acquire the process of oat porridge food processing. Based on the historical processing data of oat porridge food processing, it constructs the condition judgment parameters and result judgment parameters in the process, and uses process analysis methods based on artificial intelligence to obtain the compliance mapping range of each condition judgment parameter and result judgment parameter. The process parameter acquisition module includes a process parameter acquisition unit, which is configured with a process parameter acquisition strategy. The process parameter acquisition strategy includes: Based on the technological requirements for processing oatmeal porridge, the processing steps for oatmeal porridge are sequentially labeled as processing step JG1 to processing step JG. t For any processing step JG r Based on historical processing data of oatmeal porridge food processing, obtain JG for each processing step performed. r The conditional judgment parameters and result judgment parameters corresponding to the time process, where r is a positive integer less than or equal to t and greater than or equal to 1; In the data analysis of this embodiment, for example, in one data analysis, the processing steps of oatmeal porridge are as follows: raw material cleaning and screening, oat soaking and conditioning, low-temperature enzyme inactivation and inactivation, steaming and gelatinization, tableting / crushing and granulation, extrusion puffing, low-temperature air drying, cooling and softening homogenization, ingredient mixing and cooking, and filling, sealing and sterilization. In summary, the above 10 steps can be sequentially denoted as processing steps JG1 to JG. 10 That is, the value of t is 10; The condition determination parameter is the processing step JG. r The ambient temperature, processing time, process pressure, and material moisture content within the process, especially during processing step JG r When there is a sealing device inside the material enclosure, the process pressure is the pressure inside the sealing device. During processing step JG... r When there is no sealing device containing encapsulated material, the process pressure is the processing pressure JG. r The pressure of the environment.

[0019] The process parameter acquisition strategy also includes: the result judgment parameter is the processing process JG. r After completion, the β-glucan retention rate, polyphenol retention rate, real-time GI value corresponding to starch gelatinization, and enzyme inactivation rate were obtained from the material detection. Among them, the enzyme inactivation rate is the sum of the inactivation rates of lipase and oxidase. In the specific implementation process, the condition judgment parameters are the controllable conditions that can be controlled in the process, and the result judgment parameters are the nutritional quality indicators in the process. Based on the controllable conditions and nutritional quality indicators that can be managed within the processing steps during actual analysis, the condition judgment parameters and result judgment parameters can be set to meet actual requirements. Furthermore, since the specific values ​​of the condition judgment parameters and result judgment parameters differ in different processing steps, they can be set to match the specific processing steps according to the actual processing progress. For example, for processing step JG4 "cooking and gelatinization," the environmental temperature, processing time, process pressure, and material moisture content in the condition judgment parameters correspond to the cooking temperature, cooking time, saturated steam pressure of the cooking tank, and moisture content of the cooked material during the "cooking and gelatinization" process, respectively. The β-glucan retention rate, polyphenol retention rate, real-time GI value corresponding to starch gelatinization, and enzyme inactivation rate in the result judgment parameters correspond to the β-glucan retention rate at high temperature, the polyphenol thermal degradation retention rate, the GI value corresponding to starch gelatinization degree, and the secondary inactivation rate of residual enzymes during the "cooking and gelatinization" process, respectively. Obtain the condition and result parameters for each processing step when it is executed.

[0020] Process analysis methods include: for any processing step JG r From the historical processing data of oat food processing, processing steps JG r The executed processes are sequentially denoted as process process XC1 to process process XC. e ; For any conditional decision parameter α, process XC1 to process XC e The values ​​of the conditional decision parameter α are denoted as α1 to α2 respectively. e , from α1 to α e The closed interval formed by the minimum and maximum values ​​in the process is denoted as processing step JG. r The compliance mapping interval corresponding to the conditional decision parameter α.

[0021] The process analysis method also includes: for any result judgment parameter β, transferring the process process XC1 to the process process XC e The values ​​of the result determination parameter β are denoted as β1 to β2 respectively. e , from β1 to β e The closed interval formed by the minimum and maximum values ​​in the process is denoted as processing step JG. r The compliance mapping interval corresponding to the result judgment parameter β; In the data analysis of this embodiment, for example, the processing step analyzed in the process analysis method is "cooking and gelatinization", and the condition judgment parameters and result judgment parameters for analysis are cooking time and polyphenol thermal degradation retention rate, respectively. Through data acquisition, the values ​​of cooking time in all process steps are 12min, 13min, 15min, 13min, 17min, 22min and 20min, and the corresponding polyphenol thermal degradation retention rates are 88.99%, 87.83%, 85.39%, 87.83%, 82.78%, 75.51% and 78.55%, respectively. Through analysis, it can be found that the compliance mapping range between "cooking and gelatinization" and cooking time is [12min, 20min], and the compliance mapping range between "cooking and gelatinization" and polyphenol thermal degradation retention rate is [75.51%, 88.99%]. Obtain processing steps JG r Compliance mapping range corresponding to all conditional and result determination parameters.

[0022] The parameter mapping analysis module is used to obtain the conditional influence trend of all result judgment parameters in each process based on the compliance mapping range of all condition judgment parameters and result judgment parameters in each process, using the mapping influence test method. The parameter mapping analysis module includes a parameter mapping analysis unit, which is configured with a mapping influence test method. The mapping influence test method includes: for any processing operation JG r Given any conditional decision parameter α and result decision parameter β, denote the units corresponding to conditional decision parameter α and result decision parameter β as Q and P respectively; establish a Cartesian coordinate system with units of P and Q for the X-axis and Y-axis respectively, and denote it as the influence analysis coordinate system; In the specific implementation process, since processing step JG1 is the first step in oat porridge food processing, there is no situation where processing step JG1 is controlled based on the results of the previous step. Therefore, in the mapping influence test method, the analysis can start directly from processing step JG2. For processing steps JG r Any process XC w In the influence analysis coordinate system, point [β] w α w This is denoted as process progress XC. w The parameter point is denoted by , where w is a positive integer less than or equal to e and greater than or equal to 1.

[0023] The mapping influence testing method also includes: obtaining the machining process JG within the influence analysis coordinate system. rThe parameter points corresponding to all process steps are identified, and the curve obtained by fitting all parameter points is recorded as the influence analysis curve; when the influence analysis curve is monotonically increasing, the condition judgment parameter α is recorded as the positive influence parameter of the result judgment parameter β. In the data analysis of this embodiment, for example, regarding the conditional parameter "cooking time" and the result parameter "polyphenol thermal degradation retention rate" in processing step JG4 "cooking and gelatinization", after constructing the influence analysis coordinate system, the data obtained from the above analysis shows that the parameter points corresponding to "cooking time" and "polyphenol thermal degradation retention rate" in all process stages are [88.99%, 12 min], [87.83%, 13 min], [85.39%, 15 min], [87.83%, 13 min], [82.78%, 17 min], [75.51%, 22 min], and [78.55%, 20 min]. By fitting all parameter points, the obtained curve is as follows: Figure 3 As shown in the curve YF, analysis reveals that curve YF is a monotonically decreasing curve, indicating a negative correlation between "cooking time" and "polyphenol thermal degradation retention rate". Therefore, "cooking time" can be recorded as the inverse influence parameter of "polyphenol thermal degradation retention rate" to facilitate subsequent control of "polyphenol thermal degradation retention rate" through "cooking time" in the processing step JG4 "cooking and gelatinization". When the influence analysis curve is monotonically decreasing, the condition judgment parameter α is recorded as the reverse influence parameter of the result judgment parameter β; When the influence analysis curve has peaks or troughs, the ordinate of the point corresponding to the peak is marked as the increase value of the result judgment parameter β, and the ordinate of the point corresponding to the trough is marked as the decrease value of the result judgment parameter β. The positive influence parameter, negative influence parameter, increase value, and decrease value obtained after analyzing the result judgment parameter β with all condition judgment parameters are denoted as the condition influence trend of the result judgment parameter β. Obtain the influence trend of all result judgment parameters in all processing steps.

[0024] The parameter collaborative control module is used to record the result judgment parameters obtained in real time in each process as the preceding process parameters when controlling the processing of oat porridge food, and to control the processing of oat porridge food based on the condition influence trend of the preceding process parameters. The parameter coordination control module includes a parameter coordination control unit, which is configured with a parameter coordination control strategy. The parameter coordination control strategy includes: When controlling the processing of oatmeal porridge, for any processing step JG v When processing step JG v Upon completion, process JG will be performed. vAll result determination parameters obtained in the process are recorded as preceding process parameters, where v is a positive integer less than or equal to t-1 and greater than or equal to 1; For any preceding process parameter, if the preceding process parameter is outside the interval γ, the processing step JG is stopped. v And notify the staff about the processing procedure JG v The equipment in the process is inspected, where interval γ represents the processing step JG. v Compliance mapping range corresponding to preceding process parameters; When the preceding process parameter is in the upper range of interval Ω, or greater than the maximum value in interval Ω, the preceding process parameter is recorded as the downward adjustment control parameter, where interval Ω represents the processing step JG. v+1 The compliance mapping interval corresponding to the preceding process parameters, the upper interval of the interval Ω is the closed interval formed by the maximum value and the median value in the interval Ω; In specific implementation, for example, in a data analysis, the preceding process parameter analyzed is the polyphenol heat loss retention rate in processing step JG3 "low-temperature enzyme inactivation and passivation". The polyphenol heat loss retention rate is the specific parameter corresponding to the polyphenol retention rate in processing step JG3 "low-temperature enzyme inactivation and passivation". When processing step JG3 "low-temperature enzyme inactivation and passivation" is completed, the corresponding value of the polyphenol heat loss retention rate is 76%. Through the above analysis, it can be seen that the interval Ω is the compliant mapping interval between processing step JG4 and the polyphenol retention rate, namely [75.51%, 88.99%]. Through analysis, it can be seen that the interval Ω... The lower interval is [75.51%, 82.25%], meaning 76% falls within the lower interval of interval Ω. This indicates that when processing step JG3, "low-temperature enzyme inactivation and passivation," is completed, the polyphenol retention rate is lower compared to subsequent steps. Therefore, in processing step JG4, "cooking and gelatinization," the polyphenol retention rate should be increased by controlling controllable conditions to avoid significant loss of the oat's natural antioxidant activity due to excessively low polyphenol retention, which would affect the nutritional structure of the oat porridge. In conclusion, the polyphenol heat loss retention rate in processing step JG3, "low-temperature enzyme inactivation and passivation," should be recorded as an upward-adjusted control parameter. When the preceding process parameter is in the lower interval of the interval Ω, or is less than the minimum value in the interval Ω, the preceding process parameter is recorded as the upward control parameter. The lower interval of the interval Ω is the closed interval formed by the minimum value and the median value in the interval Ω. If the preceding process parameter is equal to the midpoint of the interval Ω, the preceding process parameter is not marked.

[0025] The parameter-coordinated control strategy also includes: in the machining process JG v After completion, proceed with the processing step JG v+1 At that time, for the processing step JG v For any one of the preceding process parameters obtained, perform mapping control analysis on the preceding process parameter.

[0026] Mapping control analysis includes: when the preceding process parameter is recorded as a downward control parameter, the processing step JG is... v+1 The positive influence parameters of the preceding process parameters are denoted as the downward adjustment condition parameters, and the processing step JG is used. v+1 The reverse influence parameters of the preceding process parameters are denoted as the adjustment condition parameters, and the processing step JG is used. v+1 The decrease in the preceding process parameters is recorded as a value to be determined; When the preceding process parameter is recorded as an upward control parameter, the processing step JG will be... v+1 The positive influence parameters of the preceding process parameters are denoted as the adjustment condition parameters, and the processing steps JG are... v+1 The reverse influence parameters of the preceding process parameters are denoted as the adjustment condition parameters, and the processing step JG is used. v+1 The increase value of the preceding process parameters is recorded as the undetermined value.

[0027] The parameter-coordinated control strategy also includes: when the parameter is controlled by the processing step JG v After performing mapping control analysis on all acquired preceding process parameters, for any conditional decision parameter α: when the conditional decision parameter α is only recorded as a down-adjustment conditional parameter and there is no value corresponding to the conditional decision parameter α among the pending values, in processing step JG v+1 The conditional decision parameter α is lowered, while maintaining the lowered conditional decision parameter α within the processing step JG. v+1 Within the compliance mapping range corresponding to the conditional decision parameter α; In the specific implementation process, the specific values ​​for adjusting the condition judgment parameters downward and upward can be determined according to the maximum range of adjustment allowed for controllable conditions in the actual process requirements. In the data analysis of this embodiment, combined with the above analysis, the polyphenol heat loss retention rate in processing step JG3 "low temperature enzyme inactivation" is recorded as the upward control parameter. And through the analysis in the mapping influence test method, the reverse influence parameter of "polyphenol heat degradation retention rate" in processing step JG4 "cooking and gelatinization" is "cooking time". Therefore, "cooking time" should be recorded as the downward condition parameter. In addition, by performing mapping control analysis on all preceding process parameters of processing step JG3, it was found that "cooking time" was only recorded as a parameter to be adjusted downwards. Therefore, in processing step JG4 "cooking and gelatinization", the "cooking time" should be adjusted downwards to ensure that the polyphenol retention rate in processing step JG4 "cooking and gelatinization" is improved, and to avoid the loss of a large amount of natural antioxidant active substances in oats due to the low polyphenol retention rate. Based on the process requirements obtained in this embodiment, the maximum adjustment of "cooking time" in processing step JG4 "cooking and gelatinization" is 5 minutes. Therefore, the adjustment time of "cooking time" is 5 minutes. When the conditional decision parameter α is recorded as a downward adjustment conditional parameter and the value corresponding to the conditional decision parameter α in the undetermined values ​​is only a decrease, in processing step JG v+1 The conditional decision parameter α is adjusted to the value corresponding to the conditional decision parameter α in the undetermined value; When the conditional decision parameter α is only recorded as an upward adjustment conditional parameter and there is no value corresponding to the conditional decision parameter α among the pending values, in processing step JG v+1 The conditional decision parameter α is increased, and the increased conditional decision parameter α is kept within the processing step JG. v+1 Within the compliance mapping range corresponding to the conditional decision parameter α; When the conditional judgment parameter α is recorded as an upward adjustment conditional parameter and the value corresponding to the conditional judgment parameter α in the undetermined values ​​is only an increase value, in the processing step JG v+1 The conditional decision parameter α is adjusted to the value corresponding to the conditional decision parameter α in the undetermined value.

[0028] Example 2, please refer to Figure 2 As shown, this application also provides an artificial intelligence-based method for controlling the processing of oatmeal porridge, including the following steps: Step S1: Obtain the processing steps of oat porridge food. Based on the historical processing data of oat porridge food, construct the condition judgment parameters and result judgment parameters in the process. Then, use the process analysis method based on artificial intelligence to obtain the compliance mapping range of each condition judgment parameter and result judgment parameter. Step S1 includes: Step S101, based on the technological requirements of oatmeal porridge food processing, the processing steps of oatmeal porridge food processing are sequentially recorded as processing step JG1 to processing step JG. t For any processing step JG r Based on historical processing data of oatmeal porridge food processing, obtain JG for each processing step performed. r The conditional judgment parameters and result judgment parameters corresponding to the time process, where r is a positive integer less than or equal to t and greater than or equal to 1; Step S102, the condition determination parameter is the processing procedure JG r The ambient temperature, processing time, process pressure, and material moisture content within the process, especially during processing step JG r When there is a sealing device inside the material enclosure, the process pressure is the pressure inside the sealing device. During processing step JG... r When there is no sealing device containing encapsulated material, the process pressure is the processing pressure JG. r The pressure of the environment.

[0029] Step S1 also includes: Step S103, where the result determination parameter is the processing procedure JG. rAfter completion, the β-glucan retention rate, polyphenol retention rate, real-time GI value corresponding to starch gelatinization, and enzyme inactivation rate were obtained from the material detection. Among them, the enzyme inactivation rate is the sum of the inactivation rates of lipase and oxidase. Step S104: Obtain the condition judgment parameters and result judgment parameters corresponding to each processing step when it is executed.

[0030] Step S105, the process analysis method includes: Step S1051, for any processing process JG r From the historical processing data of oat food processing, processing steps JG r The executed processes are sequentially denoted as process process XC1 to process process XC. e ; Step S1052, for any conditional decision parameter α, transfer the process process XC1 to the process process XC e The values ​​of the conditional decision parameter α are denoted as α1 to α2 respectively. e , from α1 to α e The closed interval formed by the minimum and maximum values ​​in the process is denoted as processing step JG. r The compliance mapping interval corresponding to the conditional decision parameter α.

[0031] The process analysis method also includes: step S1053, for any result judgment parameter β, transferring the process process XC1 to the process process XC e The values ​​of the result determination parameter β are denoted as β1 to β2 respectively. e , from β1 to β e The closed interval formed by the minimum and maximum values ​​in the process is denoted as processing step JG. r The compliance mapping interval corresponding to the result judgment parameter β; Step S1054, obtain the processing procedure JG r Compliance mapping range corresponding to all conditional and result determination parameters.

[0032] Step S2: Based on the compliance mapping range of all condition judgment parameters and result judgment parameters in each process, use the mapping influence test method to obtain the condition influence trend of all result judgment parameters in each process. The mapping influence test method includes: step S201, for any processing operation JG r Given any conditional decision parameter α and result decision parameter β, denote the units corresponding to conditional decision parameter α and result decision parameter β as Q and P respectively; establish a Cartesian coordinate system with units of P and Q for the X-axis and Y-axis respectively, and denote it as the influence analysis coordinate system; Step S202, for processing step JG r Any process XCw In the influence analysis coordinate system, point [β] w α w This is denoted as process progress XC. w The parameter point is denoted by , where w is a positive integer less than or equal to e and greater than or equal to 1.

[0033] The mapping influence test method also includes: step S203, obtaining the processing procedure JG in the influence analysis coordinate system. r The parameter points corresponding to all process steps are identified, and the curve obtained by fitting all parameter points is recorded as the influence analysis curve; when the influence analysis curve is monotonically increasing, the condition judgment parameter α is recorded as the positive influence parameter of the result judgment parameter β. Step S204: When the influence analysis curve is monotonically decreasing, the condition judgment parameter α is recorded as the reverse influence parameter of the result judgment parameter β. Step S205: When the influence analysis curve has peaks or troughs, mark the ordinate of the point corresponding to the peak as the increase value of the result judgment parameter β, and mark the ordinate of the point corresponding to the trough as the decrease value of the result judgment parameter β. Step S206: The positive influence parameter, negative influence parameter, increase value and decrease value obtained after analyzing the result judgment parameter β with all condition judgment parameters are recorded as the condition influence trend of the result judgment parameter β. Step S207: Obtain the conditional influence trend corresponding to all result judgment parameters in all processing steps.

[0034] Step S3: When controlling the oat porridge food processing, the result judgment parameters obtained in real time in each process are recorded as the preceding process parameters, and the oat porridge food processing process is controlled based on the condition influence trend of the preceding process parameters. Step S3 includes: Step S301, when controlling the processing of oatmeal porridge, for any processing step JG v When processing step JG v Upon completion, process JG will be performed. v All result determination parameters obtained in the process are recorded as preceding process parameters, where v is a positive integer less than or equal to t-1 and greater than or equal to 1; Step S302: For any preceding process parameter, if the preceding process parameter is outside the range γ, stop the processing step JG. v And notify the staff about the processing procedure JG v The equipment in the process is inspected, where interval γ represents the processing step JG. v Compliance mapping range corresponding to preceding process parameters; Step S303: When the preceding process parameter is in the upper range of interval Ω or greater than the maximum value in interval Ω, the preceding process parameter is recorded as the downward adjustment control parameter, where interval Ω is the processing step JG. v+1 The compliance mapping interval corresponding to the preceding process parameters, the upper interval of the interval Ω is the closed interval formed by the maximum value and the median value in the interval Ω; Step S304: When the preceding process parameter is in the lower interval of interval Ω or is less than the minimum value in interval Ω, the preceding process parameter is recorded as the upward control parameter. The lower interval of interval Ω is the closed interval formed by the minimum value and the median value in interval Ω. Step S305: When the preceding process parameter is equal to the median value of the interval Ω, the preceding process parameter is not marked.

[0035] Step S3 also includes: step S306, in processing step JG v After completion, proceed with the processing step JG v+1 At that time, for the processing step JG v For any one of the preceding process parameters obtained, perform mapping control analysis on the preceding process parameter; Step S307, the mapping control analysis includes: Step S3071, when the preceding process parameter is recorded as a downward control parameter, the processing operation JG is... v+1 The positive influence parameters of the preceding process parameters are denoted as the downward adjustment condition parameters, and the processing step JG is used. v+1 The reverse influence parameters of the preceding process parameters are denoted as the adjustment condition parameters, and the processing step JG is used. v+1 The decrease in the preceding process parameters is recorded as a value to be determined; Step S3072: When the preceding process parameter is recorded as an upward control parameter, the processing step JG is... v+1 The positive influence parameters of the preceding process parameters are denoted as the adjustment condition parameters, and the processing steps JG are... v+1 The reverse influence parameters of the preceding process parameters are denoted as the adjustment condition parameters, and the processing step JG is used. v+1 The increase value of the preceding process parameters is recorded as the undetermined value; Step S308, when the processing operation JG v After performing mapping control analysis on all acquired preceding process parameters, for any conditional decision parameter α: when the conditional decision parameter α is only recorded as a down-adjustment conditional parameter and there is no value corresponding to the conditional decision parameter α among the pending values, in processing step JG v+1 The conditional decision parameter α is lowered, while maintaining the lowered conditional decision parameter α within the processing step JG. v+1 Within the compliance mapping range corresponding to the conditional decision parameter α; Step S309: When the conditional judgment parameter α is recorded as a downward adjustment conditional parameter and the value corresponding to the conditional judgment parameter α in the pending values ​​is only a decrease, in processing step JG v+1 The conditional decision parameter α is adjusted to the value corresponding to the conditional decision parameter α in the undetermined value; Step S310: When the conditional judgment parameter α is only recorded as an upward adjustment conditional parameter and there is no value corresponding to the conditional judgment parameter α among the pending values, in processing step JG v+1 The conditional decision parameter α is increased, and the increased conditional decision parameter α is kept within the processing step JG. v+1 Within the compliance mapping range corresponding to the conditional decision parameter α; Step S311: When the condition judgment parameter α is recorded as the upward adjustment condition parameter and the value corresponding to the condition judgment parameter α in the pending values ​​is only the increase value, in processing step JG v+1 The conditional decision parameter α is adjusted to the value corresponding to the conditional decision parameter α in the undetermined value.

[0036] Example 3, please refer to Figure 4 As shown, Figure 4 A schematic diagram of an electronic device is provided, which may include a processor, a communication interface, a memory, and a communication bus. The processor, communication interface, and memory communicate with each other via the communication bus. The memory stores computer-readable instructions, and the processor can call these instructions. When the processor executes a computer-readable instruction, it performs steps such as those in an AI-based oatmeal food processing control method to achieve the following functions: First, it acquires the oatmeal food processing steps; based on historical processing data, it constructs conditional and result determination parameters for each step; and uses an AI-based process analysis method to obtain the compliance mapping range for each conditional and result determination parameter. Then, based on the compliance mapping ranges of all conditional and result determination parameters in each step, it uses a mapping influence test method to obtain the conditional influence trend of all result determination parameters in each step. Finally, when controlling the oatmeal food processing, the result determination parameters acquired in real-time in each step are recorded as preceding process parameters, and the oatmeal food processing process is controlled based on the conditional influence trend of the preceding process parameters.

[0037] Furthermore, when the logical instructions in the aforementioned memory can be 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, the technical solution of this application, in essence, or the part 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 to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0038] Example 4: This application also provides a computer-readable storage medium storing a computer program. When the computer program is executed by a processor, it performs the steps of the above-mentioned AI-based oatmeal porridge food processing control method to achieve the following functions: First, it acquires the processing steps of the oatmeal porridge food; based on historical processing data, it constructs condition judgment parameters and result judgment parameters in the processing steps; and uses a process analysis method based on artificial intelligence to obtain the compliance mapping interval of each condition judgment parameter and result judgment parameter. Then, based on the compliance mapping intervals of all condition judgment parameters and result judgment parameters in each process, it uses a mapping influence test method to obtain the condition influence trend of all result judgment parameters in each process. Finally, when controlling the oatmeal porridge food processing, it records the result judgment parameters acquired in real time in each process as the preceding process parameters, and controls the oatmeal porridge food processing process based on the condition influence trend of the preceding process parameters.

[0039] Based on the above description of the embodiments, the embodiments of the present invention can be provided as methods, systems, or computer program products. Based on this understanding, the above technical solutions, in essence or in terms of their contribution 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, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or certain parts of the embodiments.

[0040] In the embodiments provided in this application, it should be understood that the disclosed system or method can be implemented in other ways. The embodiments described above are merely illustrative. For example, the division of modules or units is only a logical functional division, and there may be other division methods in actual implementation. Furthermore, multiple modules or units may be combined or integrated into another system, or some features may be ignored or not executed. Additionally, the coupling or direct coupling or communication connection shown or discussed may be through some communication interfaces. The indirect coupling or communication connection between systems, modules, and units may be electrical, mechanical, or other forms.

[0041] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application 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 this application.

Claims

1. An artificial intelligence-based method for controlling the processing of oatmeal porridge, characterized in that, Includes the following steps: The process of oat porridge food processing is obtained. Based on the historical processing data of oat porridge food processing, condition judgment parameters and result judgment parameters in the process are constructed. Based on artificial intelligence, process analysis methods are used to obtain the compliance mapping range of each condition judgment parameter and result judgment parameter. Based on the compliance mapping range of all condition judgment parameters and result judgment parameters in each process, the mapping influence test method is used to obtain the condition influence trend of all result judgment parameters in each process. When controlling the processing of oatmeal porridge, the result judgment parameters obtained in real time in each process are recorded as the preceding process parameters, and the processing of oatmeal porridge is controlled based on the conditional influence trend of the preceding process parameters.

2. The method for controlling the processing of oatmeal porridge based on artificial intelligence according to claim 1, characterized in that, The process steps for processing oatmeal porridge are obtained. Based on historical processing data, conditional and result determination parameters for each step are constructed, including: Based on the technological requirements for processing oatmeal porridge, the processing steps for oatmeal porridge are sequentially labeled as processing step JG1 to processing step JG. t For any processing step JG r Based on historical processing data of oatmeal porridge food processing, obtain JG for each processing step performed. r The conditional judgment parameters and result judgment parameters corresponding to the time process, where r is a positive integer less than or equal to t and greater than or equal to 1; The condition determination parameter is the processing step JG. r The ambient temperature, processing time, process pressure, and material moisture content within the process, especially during processing step JG r When there is a sealing device inside the material enclosure, the process pressure is the pressure inside the sealing device. During processing step JG... r When there is no sealing device containing encapsulated material, the process pressure is the processing pressure JG. r The pressure of the environment.

3. The method for controlling the processing of oatmeal porridge based on artificial intelligence according to claim 2, characterized in that, The conditional and result determination parameters in the construction process also include: The result determination parameter is the processing procedure JG. r After completion, the β-glucan retention rate, polyphenol retention rate, real-time GI value corresponding to starch gelatinization, and enzyme inactivation rate were obtained from the material detection. Among them, the enzyme inactivation rate is the sum of the inactivation rates of lipase and oxidase. Obtain the condition and result parameters for each processing step when it is executed.

4. The artificial intelligence-based oatmeal porridge food processing control method according to claim 3, characterized in that, Process analysis methods include: For any processing step JG r From the historical processing data of oat food processing, processing steps JG r The executed processes are sequentially denoted as process process XC1 to process process XC. e ; For any conditional decision parameter α, process XC1 to process XC e The values ​​of the conditional decision parameter α are denoted as α1 to α2 respectively. e , from α1 to α e The closed interval formed by the minimum and maximum values ​​in the process is denoted as processing step JG. r The compliance mapping interval corresponding to the conditional decision parameter α.

5. The method for controlling the processing of oatmeal porridge based on artificial intelligence according to claim 4, characterized in that, Process analysis methods also include: For any result determination parameter β, process XC1 to process XC e The values ​​of the result determination parameter β are denoted as β1 to β2 respectively. e , from β1 to β e The closed interval formed by the minimum and maximum values ​​in the process is denoted as processing step JG. r The compliance mapping interval corresponding to the result judgment parameter β; Obtain processing steps JG r Compliance mapping range corresponding to all conditional and result determination parameters.

6. The method for controlling the processing of oatmeal porridge based on artificial intelligence according to claim 5, characterized in that, Mapping effect testing methods include: For any processing step JG r Given any conditional decision parameter α and result decision parameter β, denote the units corresponding to conditional decision parameter α and result decision parameter β as Q and P respectively; establish a Cartesian coordinate system with units of P and Q for the X-axis and Y-axis respectively, and denote it as the influence analysis coordinate system; For processing steps JG r Any process XC w In the influence analysis coordinate system, point [β] w α w This is denoted as process progress XC. w The parameter point is denoted by , where w is a positive integer less than or equal to e and greater than or equal to 1.

7. The method for controlling the processing of oatmeal porridge based on artificial intelligence according to claim 6, characterized in that, The mapping effect test method also includes: Obtain the machining process JG within the influence analysis coordinate system. r The parameter points corresponding to all process steps are identified, and the curve obtained by fitting all parameter points is recorded as the influence analysis curve; when the influence analysis curve is monotonically increasing, the condition judgment parameter α is recorded as the positive influence parameter of the result judgment parameter β. When the influence analysis curve is monotonically decreasing, the condition judgment parameter α is recorded as the reverse influence parameter of the result judgment parameter β; When the influence analysis curve has peaks or troughs, the ordinate of the point corresponding to the peak is marked as the increase value of the result judgment parameter β, and the ordinate of the point corresponding to the trough is marked as the decrease value of the result judgment parameter β. The positive influence parameter, negative influence parameter, increase value, and decrease value obtained after analyzing the result judgment parameter β with all condition judgment parameters are denoted as the condition influence trend of the result judgment parameter β. Obtain the influence trend of all result judgment parameters in all processing steps.

8. The method for controlling the processing of oatmeal porridge based on artificial intelligence according to claim 7, characterized in that, When controlling the processing of oatmeal porridge, the result judgment parameters obtained in real time in each process are recorded as the preceding process parameters, and the processing of oatmeal porridge is controlled based on the conditional influence trend of the preceding process parameters, including: When controlling the processing of oatmeal porridge, for any processing step JG v When processing step JG v Upon completion, process JG will be performed. v All result determination parameters obtained in the process are recorded as preceding process parameters, where v is a positive integer less than or equal to t-1 and greater than or equal to 1; For any preceding process parameter, if the preceding process parameter is outside the interval γ, the processing step JG is stopped. v And notify the staff about the processing procedure JG v The equipment in the process is inspected, where interval γ represents the processing step JG. v Compliance mapping range corresponding to preceding process parameters; When the preceding process parameter is in the upper range of interval Ω, or greater than the maximum value in interval Ω, the preceding process parameter is recorded as the downward adjustment control parameter, where interval Ω represents the processing step JG. v+1 The compliance mapping interval corresponding to the preceding process parameters, the upper interval of the interval Ω is the closed interval formed by the maximum value and the median value in the interval Ω; When the preceding process parameter is in the lower interval of the interval Ω, or is less than the minimum value in the interval Ω, the preceding process parameter is recorded as the upward control parameter. The lower interval of the interval Ω is the closed interval formed by the minimum value and the median value in the interval Ω. If the preceding process parameter is equal to the midpoint of the interval Ω, the preceding process parameter is not marked.

9. The method for controlling the processing of oatmeal porridge based on artificial intelligence according to claim 8, characterized in that, Controlling the oatmeal porridge food processing process based on the influence trends of preceding process parameters also includes: In the processing step JG v After completion, the processing step JG v+1 is executed. At this time, for any one of the preceding process parameters acquired by the processing step JG v , mapping control analysis is executed on the preceding process parameter. The mapping control analysis includes: the current sequence process parameter is recorded as a down control parameter, the processing process JG v+1 The positive influence parameter of the previous sequence process parameter in the JG v+1 The reverse influence parameter of the previous sequence process parameter in the JG v+1 The reduced value of the previous sequence process parameter in the JG is recorded as a pending value; The current sequence process parameter is recorded as an up-regulation control parameter, and the machining process JG v+1 The positive influence parameter of the previous sequence process parameter is recorded as an up-regulation condition parameter, and the machining process JG v+1 The negative influence parameter of the previous sequence process parameter is recorded as a down-regulation condition parameter, and the machining process JG v+1 The lifting value of the previous sequence process parameter is recorded as a pending value. When performing mapping control analysis on all the preceding process parameters acquired by the machining process JG v , for any one condition determination parameter α: when the condition determination parameter α is only recorded as a down-regulation condition parameter and there is no value corresponding to the condition determination parameter α in the pending value, the condition determination parameter α is down-regulated in the machining process JG v+1 , and the down-regulated condition determination parameter α is kept within the compliance mapping interval corresponding to the condition determination parameter α in the machining process JG v+1 . When the condition determination parameter a is noted as a down-condition parameter and the value corresponding to the condition determination parameter a in the pending value is only a reduced value, the condition determination parameter a is down-regulated to the value corresponding to the condition determination parameter a in the pending value in the processing step JG v+1 . When the condition determination parameter a is only noted as an up-condition parameter and there is no value corresponding to the condition determination parameter a in the pending value, the condition determination parameter a is up-regulated in the processing step JG v+1 and the up-regulated condition determination parameter a is maintained within the compliance mapping interval corresponding to the condition determination parameter a in the processing step JG v+1 corresponding to the condition determination parameter a. When the condition determination parameter a is noted as an up-condition parameter and the value corresponding to the condition determination parameter a in the pending value is only the up value, the condition determination parameter a is up-regulated to the value corresponding to the condition determination parameter a in the pending value in the processing procedure JG v+1 .

10. An artificial intelligence-based oatmeal food processing control system, used to implement the artificial intelligence-based oatmeal food processing control method according to any one of claims 1-9, characterized in that, It includes a process parameter acquisition module, a parameter mapping analysis module, and a parameter collaborative control module; The process parameter acquisition module is used to acquire the process of oat porridge food processing. Based on the historical processing data of oat porridge food processing, it constructs the condition judgment parameters and result judgment parameters in the process, and uses process analysis methods based on artificial intelligence to obtain the compliance mapping range of each condition judgment parameter and result judgment parameter. The parameter mapping analysis module is used to obtain the conditional influence trend of all result judgment parameters in each process based on the compliance mapping range of all condition judgment parameters and result judgment parameters in each process using the mapping influence test method. The parameter collaborative control module is used to record the result judgment parameters obtained in real time in each process as the preceding process parameters when controlling the processing of oat porridge food, and to control the processing of oat porridge food based on the condition influence trend of the preceding process parameters.

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