Zongzi production process optimization method and system based on compound plant ash alkali preparation

Abstract

The present invention relates to the technical field of rice dumpling production, and in particular to a rice dumpling production process optimization method and system based on composite plant ash alkali preparation. The state characteristics of each raw material in the rice dumpling variety with abnormal taste in the pH gap inducement process sub-process flow are obtained, and the acid-base loss amplitude of the state characteristic change of each raw material is calculated through state characteristic analysis to prepare the composite plant ash alkali essence; based on the prepared composite plant ash alkali essence, the rice dumpling production process is actually added and produced to generate an actual pH index and a final actual state characteristic, and the actual pH index and the final actual state characteristic are analyzed and calculated to determine whether the produced rice dumpling is close to an ideal pH index, so as to optimize the rice dumpling production process. The present invention can accurately optimize the control parameters that affect the compound plant ash alkali essence in the rice dumpling production process, so that the composite plant ash alkali purification can better penetrate and fuse with the rice dumpling, and improve the taste and flavor of the rice dumpling.

Description

Technical Field

[0001] The invention relates to the technical field of rice dumpling production, and in particular to a rice dumpling production process optimization method and system based on composite plant ash alkali preparation. Background Art

[0002] Zongzi is a traditional food in my country, usually eaten during the Dragon Boat Festival. Its characteristics include being wrapped in bamboo leaves or bamboo leaves, containing glutinous rice and other fillings, and being cooked for a long time. In addition to being a delicacy, zongzi also has important cultural symbolic significance. With the advancement of science and technology, the existing zongzi production technology has achieved equipment automation production, replacing the traditional manual zongzi wrapping action, and greatly improving the production efficiency of zongzi. The compound plant ash alkali essence flavoring method is an innovative zongzi production process that integrates tradition and nature. It mainly uses a variety of plant extracts or essences and ash alkali in proportion to adjust the acidity and alkalinity of the food, thereby enhancing the taste and aroma of the zongzi. However, if the traditional zongzi production process is used to use the compound plant ash alkali essence to flavor the zongzi raw materials, the compound plant ash alkali essence will be difficult to penetrate into the raw materials efficiently and accurately. This may be caused by the global optimization error of the traditional zongzi production process, which makes the quality and taste of the produced zongzi not meet the expected requirements of adding the compound plant ash alkali essence for flavoring. In addition, the traditional zongzi production process requires a large amount of manpower and material resources to coordinate operations, and it is difficult to achieve adaptive optimization of the production process, which reduces the quality of zongzi production. Summary of the invention

[0003] The invention overcomes the shortcomings of the prior art and provides a method and system for optimizing the production process of rice dumplings based on compound plant ash alkali preparation.

[0004] To achieve the above object, the technical solution adopted by the present invention is:

[0005] The first aspect of the present invention provides a method for optimizing the production process of rice dumplings based on compound plant ash alkali preparation, comprising the following steps:

[0006] Obtain the historical production process data detected and recorded when the zongzi production line equipment produces each zongzi variety, and analyze whether there is a pH mutation in the historical production process data based on the quadratic Bezier curve method to determine the pH gap of the zongzi variety with abnormal taste;

[0007] Obtain the raw material information table of the zongzi variety with abnormal taste, calculate the pH index deviation corresponding to each sub-process in the production process of the zongzi production line equipment for the zongzi variety with abnormal taste when producing the raw material information table, analyze the probability value of each sub-process to generate the pH gap based on the pH index deviation, and mark the pH gap inducing factor process according to the probability value;

[0008] Obtaining the state characteristics of each raw material in the variety of zongzi with abnormal taste in the process flow of the pH gap inducing factor, calculating the acid-base loss amplitude of the change of the state characteristics of each raw material through the state characteristic analysis, and preparing the composite plant ash-alkali essence based on the acid-base loss amplitude to obtain the prepared composite plant ash-alkali essence;

[0009] The prepared composite plant ash-alkali essence is actually added to the production process of zongzi to generate an actual pH index and final actual state characteristics. The actual pH index and the final actual state characteristics are used to analyze and calculate whether the pH of the produced zongzi is close to the ideal pH index, so as to adaptively optimize the production process of zongzi.

[0010] Furthermore, in a preferred embodiment of the present invention, the historical production process data detected and recorded when the zongzi production line equipment produces each zongzi variety is obtained, and whether there is a pH mutation in the historical production process data based on the quadratic Bezier curve method is analyzed to determine the pH gap of the zongzi variety with abnormal taste, specifically including the following steps:

[0011] Obtain several kinds of zongzi varieties produced and processed by the zongzi production line equipment within a preset time period, and retrieve the historical production process data detected and recorded when the zongzi production line equipment produces each zongzi variety;

[0012] Obtain the production process of each variety of zongzi, obtain the historical time step of each sub-process when the zongzi production line equipment executes the production process according to the production process, and preset multiple key timestamps based on the historical time step of each sub-process;

[0013] The historical acid-base data are extracted through the historical production process data, and the historical acid-base data are used to obtain the historical acid-base values ​​of each rice dumpling variety after the production and processing in each sub-process are completed;

[0014] The quadratic Bezier curve method is introduced, and the key timestamp sequence is set based on the process sequence of each sub-process in the production process. The key timestamp sequence is used as a criterion, and the historical pH value of each zongzi variety after the production and processing in each sub-process is fitted in the Bezier curve method, and the quadratic Bezier curve corresponding to the pH time series change of each zongzi variety is obtained;

[0015] Preset a pH mutation control point parameter interval, construct a quadratic Bezier curve parameter equation for the pH time series change of each rice dumpling variety based on the quadratic Bezier curve, solve the quadratic Bezier curve parameter equation, and generate a number of pH control point parameter values;

[0016] If at least one pH control point parameter value is located in the pH mutation control point parameter interval, the variety of rice dumplings corresponding to the quadratic Bezier curve of the pH control electrical parameter value is marked and defined as the variety of rice dumplings with abnormal taste, and the pH gap of the variety of rice dumplings with abnormal taste is determined based on the pH control point parameter value.

[0017] Furthermore, in a preferred embodiment of the present invention, the raw material information table of the rice dumpling variety with abnormal taste is obtained, the pH index deviation corresponding to each sub-process flow in the production process of the rice dumpling production line equipment for the rice dumpling variety with abnormal taste is calculated when the raw material information table is produced, and the probability value of each sub-process flow generating the pH gap is analyzed based on the pH index deviation, and the pH gap inducing factor process flow is marked according to the probability value, which specifically includes the following steps:

[0018] Based on the big data network, historical evaluation information of consumers on the said rice dumpling variety with abnormal taste is obtained, and the expected taste coefficient is preset according to the said historical evaluation information, and at the same time, the preset control strategy of the rice dumpling production line equipment for the production and processing of the said rice dumpling variety with abnormal taste is obtained;

[0019] Obtain a raw material information table of the variety of zongzi with abnormal taste, and extract preset control parameters corresponding to each raw material in each sub-process in the production process of the variety of zongzi with abnormal taste according to the preset control strategy;

[0020] Obtain a standard food production knowledge graph through big data network retrieval, import the raw material information table and the preset control parameters into the standard food production knowledge graph for identification based on the expected taste coefficient, and output the pH index of each raw material in the raw material information table at which the expected taste coefficient is achieved under the corresponding preset control parameters, which is defined as the ideal pH index;

[0021] Obtain the production and processing log of the rice dumpling production line equipment, obtain the actual pH index of the raw materials in each sub-process flow when the rice dumpling production line equipment executes the preset control strategy through the production and processing log, calculate the deviation between each actual pH index and the ideal pH index, and generate a number of pH index deviations;

[0022] Obtain the flash frequency of the corresponding pH index deviation in each sub-process flow within a preset time period. If the flash frequency exceeds the preset flash frequency, introduce the Bayesian estimation method to calculate the prior probability distribution and the posterior probability distribution of each sub-process flow generating the pH gap when the flash frequency exceeds the preset flash frequency. Determine the probability value of each sub-process flow causing the pH gap based on the prior probability distribution and the posterior probability distribution.

[0023] Only the sub-process flows corresponding to probability values ​​greater than the preset probability values ​​are marked, and the marked sub-process flows are defined as pH gap inducer process flows.

[0024] Furthermore, in a preferred embodiment of the present invention, the state characteristics of each raw material in the abnormal-tasting rice dumpling variety in the pH gap inducing factor process are obtained, the acid-base loss amplitude of the state characteristic change of each raw material is calculated through the state characteristic analysis, and the composite plant ash-alkali essence is formulated based on the acid-base loss amplitude to obtain the formulated composite plant ash-alkali essence, which specifically includes the following steps:

[0025] Obtain the state characteristics of each raw material in the abnormal-tasting rice dumpling variety in the pH gap inducement factor process flow, and obtain the corresponding functional information of the rice dumpling production line equipment in the pH gap inducement factor process flow; wherein the state characteristics include the viscosity state, the air permeability state and the wrapping density state;

[0026] Acquire several groups of state characteristic image data of the abnormal zongzi varieties in the pH gap inducement process when the zongzi production line equipment executes the preset control strategy, and construct a dynamic change model of the state characteristic through the several groups of the state characteristic image data;

[0027] Preset continuous time-series cutting points, perform local time-series slicing on the dynamic change model of the state characteristics based on the continuous time-series cutting points, and obtain local dynamic change characteristics of the state characteristics of the abnormal taste zongzi variety in the pH gap inducer process;

[0028] Based on the functional information, the local dynamic change characteristics are introduced into the standard food production knowledge map for identification, and the acid-base loss amplitude of each raw material state characteristic change in the zongzi production line equipment causing abnormal taste zongzi varieties is generated;

[0029] Obtain the types of plant essences and ash bases used to prepare the composite plant ash base, retrieve the acid-base concentration interaction mechanisms of different plant essences and ash bases in the big data network according to the types of plant essences and ash bases, and construct an acid-base concentration compensation radar chart framework according to the acid-base concentration interaction mechanism;

[0030] Draw an acid-base concentration compensation radar chart required to compensate the acid-base loss amplitude in the acid-base concentration compensation radar chart framework until the acid-base loss amplitude of each raw material state characteristic change is equal to 0, and finally obtain the acid-base concentration compensation value according to the acid-base concentration compensation radar chart;

[0031] Each type of plant essence and ash alkali type is accurately blended according to the acid-base concentration compensation value to generate a blended composite plant ash alkali essence, and the acid-base concentration compensation radar chart is uploaded to the composite plant ash alkali blending equipment terminal.

[0032] Further, in a preferred embodiment of the present invention, the composite plant ash-alkali essence based on the prepared method is actually added to the zongzi production process to generate an actual pH index and a final actual state characteristic, and the actual pH index of the produced zongzi is analyzed and calculated according to the actual pH index and the final actual state characteristic to determine whether it is close to the ideal pH index, so as to adaptively optimize the zongzi production process, which specifically includes the following steps:

[0033] The prepared composite plant ash-alkali essence is added to the rice dumpling production line equipment corresponding to the pH gap inducer process and the preset control strategy is executed for actual production, at which time the actual pH index and final actual state characteristics of the rice dumpling production are recorded in real time;

[0034] Constructing a multiple linear regression model based on the final actual state characteristics, performing multiple linear function fitting on the ideal pH index through the multiple linear regression model, and generating an ideal pH linear function;

[0035] Acquiring ideal pH data according to the ideal pH linear function, introducing the least square method to calculate the residual between the ideal pH index and the actual pH index in a multivariate linear regression model, and obtaining a plurality of residual values;

[0036] Based on the preset random distribution threshold of the ideal pH linear function, only the actual pH index corresponding to the residual value less than the preset residual value is marked in the multivariate linear regression model, which is defined as the actual pH index approaching, and a residual distribution diagram approaching the actual pH index is obtained;

[0037] Taking the random distribution threshold as a constraint benchmark, planning the random distribution area in the multivariate linear regression model until the constraint benchmark is reached to obtain a random distribution field, and obtaining the interference area value of the residual distribution map and the random distribution field;

[0038] If the interference region area value is greater than the preset interference region area value, it means that the actual pH index and the pH of the rice dumplings produced under the final actual state characteristics are close to the ideal pH index, and the rice dumplings are marked as qualified products, generating a first-level judgment result;

[0039] If the interference region area value is not greater than the preset interference region area value, it means that the actual pH index and the pH of the rice dumplings produced under the final actual state characteristics cannot approach the ideal pH index, and the rice dumplings are marked as unqualified products, and a secondary judgment result is generated;

[0040] When the judgment result shows a secondary judgment result, a simulation model of the zongzi production line equipment is constructed. The key process parameter set is obtained through the simulation production of the zongzi production line equipment simulation model. The fuzzy solution values ​​of the key process parameters are analyzed to update the iterative parameter control network, generate new key optimized process parameters, and optimize the zongzi production process flow according to the new key optimized process parameters.

[0041] Furthermore, in a preferred embodiment of the present invention, when the determination result is displayed as a secondary determination result, a simulation model of the zongzi production line equipment is constructed, a set of key process parameters is obtained through simulation of the simulation model of the zongzi production line equipment, the fuzzy solution values ​​of the key process parameters are analyzed to update the iterative parameter control network, and new key optimized process parameters are generated. The zongzi production process is optimized according to the new key optimized process parameters, which specifically includes the following steps:

[0042] Obtaining an initial design drawing of a rice dumpling production line equipment, converting simulation model data in a simulation model software according to the initial design drawing, and constructing a simulation model of the rice dumpling production line equipment through the simulation model data;

[0043] A test signal data is generated in the simulation model software according to the prepared composite plant ash alkali essence, and the test signal data is injected into the simulation model of the rice dumpling production line equipment corresponding to the pH gap inducer process flow for simulation based on the preset control strategy conditions;

[0044] During the simulation process, the parameter control network of the zongzi production line equipment for the pH gap inducement factor process flow is obtained, and the parameter control network is analyzed according to the corresponding functional information of the zongzi production line equipment in the pH gap inducement factor process flow to extract the key process parameter set;

[0045] Based on the key process parameter set, a number of initial populations are generated, and fitness evaluation is performed on the initial populations to obtain a number of fitness functions, and the first generation of key process parameter individuals in the initial populations whose fitness functions are greater than the preset fitness functions are extracted and defined as key process parameter parents;

[0046] A fuzzy genetic algorithm is introduced, and based on the fitness function, the extracted multiple key process parameter parents are combined in the fuzzy genetic algorithm to generate second-generation key process parameter individuals, and fuzzy mutation processing is performed on the second-generation key process parameter individuals to obtain the second-generation key process parameter individuals after fuzzy mutation;

[0047] Preset a satisfactory fuzzy solution threshold, calculate the difference between the interference area value and the preset interference area value, obtain the interference area difference, preset a defuzzification rule in the fuzzy genetic algorithm based on the interference area difference, perform defuzzification calculation on the second-generation key process parameter individuals after fuzzy mutation through the defuzzification rule, and generate a final fuzzy solution value;

[0048] If the final fuzzy solution value can reach the satisfactory fuzzy solution threshold, the key process parameters in the iterative parameter control network are continuously updated through the second-generation key process parameter individuals after the fuzzy mutation, and the updated iteratively optimized parameter control network is output;

[0049] The updated iteratively optimized parameter control network is applied to the control terminal of the zongzi production line equipment and re-run to generate new key optimized process parameters. The zongzi production process flow is adaptively optimized based on the new key optimized process parameters to improve the penetration quality of the compound plant ash alkali essence in the production of zongzi raw materials.

[0050] The second aspect of the present invention provides a rice dumpling making process optimization system based on composite plant ash alkali preparation, the rice dumpling making process optimization system includes a memory and a processor, the memory stores a rice dumpling making process optimization method program, when the rice dumpling making process optimization method program is executed by the processor, any one of the rice dumpling making process optimization method steps is implemented.

[0051] The present invention solves the technical defects existing in the background technology, and the beneficial technical effects of the present invention are:

[0052] The historical production process data detected and recorded when the zongzi production line equipment produces each zongzi variety is obtained, and the pH mutation is analyzed based on the quadratic Bezier curve method to determine whether there is a pH gap in the historical production process data, so as to determine the pH gap of the zongzi variety with abnormal taste; the pH index deviation corresponding to each sub-process in the production process of the zongzi production line equipment for the zongzi variety with abnormal taste is calculated when producing the raw material information table, and the probability value of each sub-process to generate the pH gap is analyzed based on the pH index deviation, and the pH gap inducing factor process is marked according to the probability value; obtain the zongzi variety with abnormal taste. The state characteristics of each raw material in the variety is in the process flow of the pH gap inducer, and the acid-base loss amplitude of each raw material state characteristic change is calculated through the state characteristics analysis, and the composite plant ash-alkali essence is deployed based on the acid-base loss amplitude to obtain the deployed composite plant ash-alkali essence; based on the deployed composite plant ash-alkali essence, the zongzi manufacturing process is actually added and produced to generate an actual pH index and a final actual state characteristic, and the actual pH index and the final actual state characteristic are analyzed and calculated to determine whether the produced zongzi is close to the ideal pH index, and a zongzi manufacturing process optimization scheme is generated. The present invention can accurately and intelligently optimize the control behavior and control parameters that affect the composite plant ash-alkali essence in the zongzi manufacturing process, so that the deployed composite plant ash-alkali essence can better penetrate and fuse with the zongzi, thereby improving the taste and flavor of the zongzi. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, drawings of other embodiments can be obtained based on these drawings without paying creative work.

[0054] Figure 1 A first method flow chart of a method for optimizing the process of making zongzi based on compound plant ash alkali is shown;

[0055] Figure 2 A second method flow chart of the method for optimizing the process of making zongzi based on compound plant ash alkali is shown;

[0056] Figure 3 The system framework diagram of the rice dumpling production process optimization system based on composite plant ash alkali preparation is shown. DETAILED DESCRIPTION

[0057] In order to more clearly understand the above-mentioned purpose, features and advantages of the present invention, the present invention is further described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be noted that the embodiments of the present application and the features in the embodiments can be combined with each other without conflict.

[0058] In the following description, many specific details are set forth to facilitate a full understanding of the present invention. However, the present invention may also be implemented in other ways different from those described herein. Therefore, the protection scope of the present invention is not limited to the specific embodiments disclosed below.

[0059] The first aspect of the present invention provides a method for optimizing the production process of zongzi based on compound plant ash alkali, such as Figure 1 As shown, the following steps are included:

[0060] S102: Obtain historical production process data detected and recorded when the zongzi production line equipment produces each zongzi variety, and analyze whether there is a pH mutation in the historical production process data based on the quadratic Bezier curve method to determine the pH gap of the zongzi variety with abnormal taste;

[0061] S104: Obtaining a raw material information table of the rice dumpling variety with abnormal taste, calculating the pH index deviation corresponding to each sub-process in the production process of the rice dumpling production line equipment for the rice dumpling variety with abnormal taste when producing the raw material information table, analyzing the probability value of each sub-process generating the pH gap based on the pH index deviation, and marking the pH gap inducing factor process according to the probability value;

[0062] S106: Obtaining the state characteristics of each raw material in the variety of zongzi with abnormal taste in the process flow of the pH gap inducing factor, calculating the acid-base loss amplitude of the change of the state characteristics of each raw material through the state characteristic analysis, and preparing the composite plant ash-alkali essence based on the acid-base loss amplitude to obtain the prepared composite plant ash-alkali essence;

[0063] S108: Adding the prepared composite plant ash-alkali essence to the production process of zongzi to generate an actual pH index and final actual state characteristics, and analyzing and calculating whether the pH of the produced zongzi is close to the ideal pH index based on the actual pH index and the final actual state characteristics, so as to adaptively optimize the production process of zongzi.

[0064] Furthermore, in a preferred embodiment of the present invention, the historical production process data detected and recorded when the zongzi production line equipment produces each zongzi variety is obtained, and the pH mutation in the historical production process data is analyzed based on the quadratic Bezier curve method to determine the pH gap of the zongzi variety with abnormal taste, such as Figure 2 As shown, the specific steps include:

[0065] S202: Obtain several kinds of zongzi varieties produced and processed by the zongzi production line equipment within a preset time period, and retrieve historical production process data detected and recorded when the zongzi production line equipment produces each zongzi variety;

[0066] S204: Obtain the production process of each rice dumpling variety, obtain the historical time step of each sub-process when the rice dumpling production line equipment executes the production process according to the production process, and preset multiple key timestamps based on the historical time step of each sub-process;

[0067] S206: extracting historical acid-base data through the historical production process data, and obtaining the historical acid-base values ​​of each rice dumpling variety after the production and processing in each sub-process flow based on the historical acid-base data;

[0068] S208: Introducing the quadratic Bezier curve method, and setting the key timestamp sequence based on the process sequence of each sub-process in the production process, and fitting the historical pH of each zongzi variety after the production and processing in each sub-process in the Bezier curve method, so as to obtain the quadratic Bezier curve of the pH time series change corresponding to each zongzi variety;

[0069] S210: Preset a pH mutation control point parameter interval, construct a quadratic Bezier curve parameter equation for the pH time series change of each rice dumpling variety based on the quadratic Bezier curve, solve the quadratic Bezier curve parameter equation, and generate a number of pH control point parameter values;

[0070] S212: If at least one pH control point parameter value is located in the pH mutation control point parameter interval, the rice dumpling variety corresponding to the quadratic Bezier curve of the pH control electrical parameter value is marked and defined as the rice dumpling variety with abnormal taste, and the pH gap of the rice dumpling variety with abnormal taste is determined based on the pH control point parameter value.

[0071] It should be noted that during the production process of zongzi, the zongzi production process may deviate due to errors in certain control parameters of the zongzi production line equipment, resulting in a sudden change in the pH value of the zongzi raw materials at each process step in the production process, resulting in unsatisfactory taste and flavor of the final zongzi, reducing the desire to eat and buy zongzi, and reducing the sales volume of zongzi. Since a pH gap is usually generated when the pH value of the zongzi raw materials suddenly changes at each process step in the production process, the pH gap reflects the actual production quality of the zongzi production process on the one hand, and provides a reliable basis for the subsequent compound plant ash alkali essence blending analysis on the other hand, ensuring the accuracy of the blending of the compound plant ash alkali essence. The method introduces a quadratic Bezier curve method to analyze and calculate the historical pH changes of the process flow of making different varieties of zongzi, and obtains a quadratic Bezier curve corresponding to the time series change of pH of each zongzi variety. The pH mutation control point parameter interval is the control point parameter interval corresponding to the pH changes in each sub-process flow during the production of the zongzi production process. If there is at least one pH control point parameter value in the quadratic Bezier curve located in the pH mutation control point parameter interval, it means that each zongzi variety corresponding to the quadratic Bezier curve is in each sub-process flow. The historical pH value after the production and processing was completed during the process has undergone a mutation phenomenon, that is, the pH value change has increased significantly and a pH gap has occurred. Therefore, the taste and flavor of the zongzi variety corresponding to the quadratic Bezier curve cannot achieve the expected effect. Therefore, the zongzi variety needs to be marked as an abnormal taste zongzi variety and further optimized in the future, so as to avoid the frequency of pH gap in the production of this zongzi variety and improve the stability of the zongzi manufacturing process. At the same time, the method can ensure the accuracy of the flavoring of the composite plant ash alkali essence in the zongzi manufacturing process through pH gap analysis, and has high reliability.

[0072] Furthermore, in a preferred embodiment of the present invention, the raw material information table of the rice dumpling variety with abnormal taste is obtained, the pH index deviation corresponding to each sub-process flow in the production process of the rice dumpling production line equipment for the rice dumpling variety with abnormal taste is calculated when the raw material information table is produced, and the probability value of each sub-process flow generating the pH gap is analyzed based on the pH index deviation, and the pH gap inducing factor process flow is marked according to the probability value, which specifically includes the following steps:

[0073] Based on the big data network, historical evaluation information of consumers on the said abnormal-tasting rice dumpling varieties is obtained, and the expected taste coefficient is preset according to the said historical evaluation information, and at the same time, the preset control strategy of the rice dumpling production line equipment for the production and processing of the said abnormal-tasting rice dumpling varieties is obtained;

[0074] Obtain a raw material information table of the variety of zongzi with abnormal taste, and extract preset control parameters corresponding to each raw material in each sub-process in the production process of the variety of zongzi with abnormal taste according to the preset control strategy;

[0075] Obtain a standard food production knowledge graph through big data network retrieval, import the raw material information table and the preset control parameters into the standard food production knowledge graph for identification based on the expected taste coefficient, and output the pH index of each raw material in the raw material information table at which the expected taste coefficient is achieved under the corresponding preset control parameters, which is defined as the ideal pH index;

[0076] Obtain the production and processing log of the rice dumpling production line equipment, obtain the actual pH index of the raw materials in each sub-process flow when the rice dumpling production line equipment executes the preset control strategy through the production and processing log, calculate the deviation between each actual pH index and the ideal pH index, and generate a number of pH index deviations;

[0077] Obtain the flash frequency of the corresponding pH index deviation in each sub-process flow within a preset time period. If the flash frequency exceeds the preset flash frequency, introduce the Bayesian estimation method to calculate the prior probability distribution and the posterior probability distribution of each sub-process flow generating the pH gap when the flash frequency exceeds the preset flash frequency. Determine the probability value of each sub-process flow causing the pH gap based on the prior probability distribution and the posterior probability distribution.

[0078] Only processes corresponding to probability values ​​greater than the preset probability values ​​are marked, and the marked sub-process flows are defined as pH gap inducer process flows.

[0079] It should be noted that the zongzi production process is composed of several sub-processes, such as soaking glutinous rice, preparing fillings, wrapping zongzi, and steaming. The zongzi production line equipment may cause a pH gap in the production of each process step. The traditional zongzi production process can usually only globally optimize the process parameters of each step. On the one hand, this will cause an imbalance in the pH of the zongzi in the sub-process steps that are at normal pH, and expand the pH gap. On the other hand, it requires a lot of manpower and material resources to complete, which increases cost output, is time-consuming and labor-intensive, and makes the production cost of zongzi high and the efficiency low. In addition, the taste and flavor of the zongzi produced in the end have large errors, which reduces the overall quality of the zongzi. Therefore, this method first determines the ideal pH index required for each raw material in the raw material information table to achieve the expected taste coefficient when the zongzi production line equipment runs the preset control strategy, and then compares and analyzes the ideal pH index with the actual pH index of the raw materials in each sub-process flow to generate a pH index deviation. The pH index deviation intuitively reflects the influence of the control strategy required for the production of zongzi production line equipment to the pH adjustment and characteristics of the zongzi raw materials when the zongzi production line equipment runs the production of zongzi production process. The pH index deviation is inevitable in the production process of zongzi, but the pH gap phenomenon can be prevented by eliminating the pH index deviation as much as possible. Therefore, when the flash frequency of the pH index deviation in a sub-process exceeds the preset flash frequency, it means that the sub-process will frequently generate pH index deviations when producing and processing zongzi raw materials, so the probability that the sub-process will cause the final zongzi to generate a pH gap is relatively high, that is, it is one of the inducing factor processes that cause the pH gap. This method can locate the sub-process flow that causes the pH gap of the zongzi in the zongzi manufacturing process, and then accurately proportion the specific mixing amount of the required composite plant ash alkali and apply it to the pH gap inducing factor process, thereby effectively improving the targeted improvement of the taste and flavor of the composite plant ash alkali essence, avoiding the global optimization of the zongzi manufacturing process, reducing the output of manpower and material costs, having high economic benefits, and ensuring the accuracy of the taste and flavor of the zongzi in line with expectations.

[0080] Furthermore, in a preferred embodiment of the present invention, the state characteristics of each raw material in the abnormal-tasting rice dumpling variety in the pH gap inducer process are obtained, the acid-base loss amplitude of the state characteristic change of each raw material is calculated by the state characteristic analysis, and the composite plant ash alkali is prepared based on the acid-base loss amplitude to obtain the prepared composite plant ash alkali, which specifically includes the following steps:

[0081] Obtain the state characteristics of each raw material in the abnormal-tasting rice dumpling variety in the pH gap inducement factor process flow, and obtain the corresponding functional information of the rice dumpling production line equipment in the pH gap inducement factor process flow; wherein the state characteristics include the viscosity state, the air permeability state and the wrapping density state;

[0082] Acquire several groups of state characteristic image data of the abnormal zongzi varieties in the pH gap inducement process when the zongzi production line equipment executes the preset control strategy, and construct a dynamic change model of the state characteristic through the several groups of the state characteristic image data;

[0083] Preset continuous time-series cutting points, perform local time-series slicing on the dynamic change model of the state characteristics based on the continuous time-series cutting points, and obtain local dynamic change characteristics of the state characteristics of the abnormal taste zongzi variety in the pH gap inducer process;

[0084] Based on the functional information, the local dynamic change characteristics are introduced into the standard food production knowledge map for identification, and the acid-base loss amplitude of each raw material state characteristic change in the zongzi production line equipment causing abnormal taste zongzi varieties is generated;

[0085] Obtain the types of plant essences and ash bases used to prepare the composite plant ash base, retrieve the acid-base concentration interaction mechanisms of different plant essences and ash bases in the big data network according to the types of plant essences and ash bases, and construct an acid-base concentration compensation radar chart framework according to the acid-base concentration interaction mechanism;

[0086] Draw an acid-base concentration compensation radar chart required to compensate the acid-base loss amplitude in the acid-base concentration compensation radar chart framework until the acid-base loss amplitude of each raw material state characteristic change is equal to 0, and finally obtain the acid-base concentration compensation value according to the acid-base concentration compensation radar chart;

[0087] Each type of plant essence and ash alkali type is accurately blended according to the acid-base concentration compensation value to generate a blended composite plant ash alkali essence, and the acid-base concentration compensation radar chart is uploaded to the composite plant ash alkali blending equipment terminal.

[0088] It should be noted that compound plant ash alkali essence usually refers to the use of a variety of plant extracts or essences mixed with ash alkali to enhance the taste and aroma of food. The compound plant ash alkali essence mainly adjusts the pH of the rice dumplings, improves the balance of its taste and the softness of its taste, making the rice dumplings taste more delicate. The traditional compound plant ash alkali blending method usually makes the blending based on the overall analysis of the rice dumpling production process, making it difficult for the final compound plant ash alkali essence to penetrate into the rice dumpling raw materials, resulting in poor taste of the produced rice dumplings. Therefore, in order to enable the composite plant ash alkali essence to more accurately and better penetrate and integrate with the raw materials for making zongzi to enhance the taste and flavor of zongzi, after locating the sub-process flow that causes the pH gap, this method analyzes the state characteristics of each raw material in the abnormal taste zongzi variety during the production and processing of the pH gap inducer process flow. These state characteristics will affect the penetration, distribution and flavor of the composite plant ash alkali essence, and are the key to the accurate blending analysis of plant essence and ash alkali; by constructing a dynamic change model of state characteristics, the dynamic change model of state characteristics can dynamically display the time series changes of the state characteristics of the zongzi raw materials when they are in the pH gap inducer process flow production and processing, providing a stable and reliable data analysis framework for further determining the acid-base loss amplitude of each raw material in the abnormal taste zongzi variety caused by the zongzi production line equipment. The acid-base loss amplitude is the degree of loss or loss of the pH value of the zongzi raw materials during the production and processing of the zongzi production line equipment, which accurately reflects the negative impact of the zongzi production line equipment on the zongzi raw materials when executing the zongzi production process. It can improve the accuracy of the blending of plant essence and ash alkali with respect to pH loss, and ensure that the formulated composite plant ash alkali essence can completely repair the pH loss of the zongzi raw materials in the pH gap inducing process; and because the acid-base concentrations of the plant essence and the ash alkali themselves will interact with each other, it is necessary to compensate for the acid-base loss amplitude by deeply analyzing the interaction mechanism of the acid-base concentrations of the two, so as to effectively make the composite plant ash alkali essence better penetrate into the zongzi raw materials and improve the taste and flavor of the zongzi.

[0089] Further, in a preferred embodiment of the present invention, the composite plant ash-alkali essence based on the prepared method is actually added to the zongzi production process to generate an actual pH index and a final actual state characteristic, and the actual pH index of the produced zongzi is analyzed and calculated according to the actual pH index and the final actual state characteristic to determine whether it is close to the ideal pH index, so as to adaptively optimize the zongzi production process, which specifically includes the following steps:

[0090] The prepared composite plant ash-alkali essence is added to the rice dumpling production line equipment corresponding to the pH gap inducer process and the preset control strategy is executed for actual production, at which time the actual pH index and final actual state characteristics of the rice dumpling production are recorded in real time;

[0091] Constructing a multiple linear regression model based on the final actual state characteristics, performing multiple linear function fitting on the ideal pH index through the multiple linear regression model, and generating an ideal pH linear function;

[0092] Acquiring ideal pH data according to the ideal pH linear function, introducing the least square method to calculate the residual between the ideal pH index and the actual pH index in a multivariate linear regression model, and obtaining a plurality of residual values;

[0093] Based on the preset random distribution threshold of the ideal pH linear function, only the actual pH index corresponding to the residual value less than the preset residual value is marked in the multivariate linear regression model, which is defined as the actual pH index approaching, and a residual distribution diagram approaching the actual pH index is obtained;

[0094] Taking the random distribution threshold as a constraint benchmark, planning the random distribution area in the multivariate linear regression model until the constraint benchmark is reached to obtain a random distribution field, and obtaining the interference area value of the residual distribution map and the random distribution field;

[0095] If the interference region area value is greater than the preset interference region area value, it means that the actual pH index and the pH of the rice dumplings produced under the final actual state characteristics are close to the ideal pH index, and the rice dumplings are marked as qualified products, generating a first-level judgment result;

[0096] If the interference region area value is not greater than the preset interference region area value, it means that the actual pH index and the pH of the rice dumplings produced under the final actual state characteristics cannot approach the ideal pH index, and the rice dumplings are marked as unqualified products, and a secondary judgment result is generated;

[0097] When the judgment result shows a secondary judgment result, a simulation model of the zongzi production line equipment is constructed. The key process parameter set is obtained through the simulation production of the zongzi production line equipment simulation model. The fuzzy solution values ​​of the key process parameters are analyzed to update the iterative parameter control network, generate new key optimized process parameters, and optimize the zongzi production process flow according to the new key optimized process parameters.

[0098] It should be noted that after the compound plant ash-alkali essence is prepared, it can be added to the pH gap inducing factor process that is prone to pH gap, thereby repairing the pH gap and improving the taste and flavor of the raw materials. However, due to the deviation of certain specific control parameters of the zongzi production line equipment under long-term operation, such as deviations such as too high temperature, uneven stirring, too fast stirring rate, and loose wrapping of zongzi leaves, the pH of the zongzi produced by the zongzi raw materials after the infiltration treatment of the compound plant ash-alkali essence after preparation still cannot reach the pH of the ideal taste, increasing the rework rate of zongzi production and reducing the overall production quality of zongzi. Therefore, this method first determines whether the actual pH index output can approach the ideal pH index by constructing a multivariate linear regression model. By analyzing the residual size and distribution between the ideal pH index and the actual pH index, it can be known whether the actual pH of the zongzi produced finally reaches the ideal pH index. Among them, when the residual value is less than the preset residual value, it means that the actual pH index will better approach the ideal pH linear function, so the residual distribution should be further analyzed based on the actual pH index corresponding to the residual value being less than the preset residual value; wherein, the random distribution field is used to determine whether the residual value approaching the actual pH index is randomly distributed. When the interference area of ​​the residual distribution graph in the random distribution field is larger than the preset interference area, it means that the residual value approaching the actual pH index is randomly distributed, and the randomly distributed residual indicates that the actual pH of the rice dumplings finally produced will be closer and closer to the ideal pH index, that is, the rice dumplings are qualified products, otherwise it cannot be approached, and the production of rice dumplings is unqualified. When the rice dumplings are qualified products, it means that there is no control deviation in the rice dumpling production line equipment for the rice dumpling production process. For unqualified products, there is a control deviation. Therefore, by further locating and calculating the control deviation that causes the pH value of the rice dumpling production to fail to meet the standard, the rice dumpling production process can be accurately optimized, and the taste and flavor quality of the rice dumplings after the action of the compound plant ash alkali essence can be improved.

[0099] Furthermore, in a preferred embodiment of the present invention, when the determination result is displayed as a secondary determination result, a simulation model of the zongzi production line equipment is constructed, a set of key process parameters is obtained through simulation of the simulation model of the zongzi production line equipment, the fuzzy solution values ​​of the key process parameters are analyzed to update the iterative parameter control network, and new key optimized process parameters are generated. The zongzi production process is optimized according to the new key optimized process parameters, which specifically includes the following steps:

[0100] Obtaining an initial design drawing of a rice dumpling production line equipment, converting simulation model data in a simulation model software according to the initial design drawing, and constructing a simulation model of the rice dumpling production line equipment through the simulation model data;

[0101] A test signal data is generated in the simulation model software according to the prepared composite plant ash alkali essence, and the test signal data is injected into the simulation model of the rice dumpling production line equipment corresponding to the pH gap inducer process flow for simulation based on the preset control strategy conditions;

[0102] During the simulation process, the parameter control network of the zongzi production line equipment for the pH gap inducement factor process flow is obtained, and the parameter control network is analyzed according to the corresponding functional information of the zongzi production line equipment in the pH gap inducement factor process flow to extract the key process parameter set;

[0103] Based on the key process parameter set, a number of initial populations are generated, and fitness evaluation is performed on the initial populations to obtain a number of fitness functions, and the first generation of key process parameter individuals in the initial populations whose fitness functions are greater than the preset fitness functions are extracted and defined as key process parameter parents;

[0104] A fuzzy genetic algorithm is introduced, and based on the fitness function, the extracted multiple key process parameter parents are combined in the fuzzy genetic algorithm to generate second-generation key process parameter individuals, and fuzzy mutation processing is performed on the second-generation key process parameter individuals to obtain the second-generation key process parameter individuals after fuzzy mutation;

[0105] Preset a satisfactory fuzzy solution threshold, calculate the difference between the interference area value and the preset interference area value, obtain the interference area difference, preset a defuzzification rule in the fuzzy genetic algorithm based on the interference area difference, perform defuzzification calculation on the second-generation key process parameter individuals after fuzzy mutation through the defuzzification rule, and generate a final fuzzy solution value;

[0106] If the final fuzzy solution value can reach the satisfactory fuzzy solution threshold, the key process parameters in the iterative parameter control network are continuously updated through the second-generation key process parameter individuals after the fuzzy mutation, and the updated iteratively optimized parameter control network is output;

[0107] The updated iteratively optimized parameter control network is applied to the control terminal of the zongzi production line equipment and re-run to generate new key optimized process parameters. The zongzi production process flow is adaptively optimized based on the new key optimized process parameters to improve the penetration quality of the compound plant ash alkali essence in the production of zongzi raw materials.

[0108] It should be noted that when the judgment result is displayed as a secondary judgment result, it means that the final pH index of the rice dumpling is not close to the ideal pH index, so the rice dumpling production process needs to be optimized. However, since the rice dumpling production process can only be completed under the operation control of the rice dumpling production line equipment, the optimization of the rice dumpling production process depends on the precise positioning and analysis and optimization of the corresponding control parameters of the rice dumpling production line equipment that cause the actual pH index to fail to meet the standard. This method constructs a simulation model of the rice dumpling production line equipment to simulate the production process of the rice dumpling production line equipment to obtain the key control parameters of the parameter control network, and introduces a fuzzy genetic algorithm to analyze which key control parameters are the key factors that cause the actual pH index to fail to meet the standard. The fuzzy genetic algorithm is an optimization technology that combines fuzzy logic and genetic algorithms. It can be used to calculate the uncertainty of production errors caused by control parameters in production equipment. It has certain flexibility and global search capabilities, and can be used for efficient and accurate tracing of the key factors of the subsequent actual pH index failure of rice dumpling production. Among them, the defuzzification rule preset based on the area difference of the interference area is a rule that makes the random distribution of the residual value between the actual pH index and the ideal pH index reach the approach requirement, so that the final fuzzy solution value output by the individual second-generation key control parameter after fuzzy mutation can be close to the requirement of random distribution of residuals. If the final fuzzy solution value can reach the satisfactory fuzzy solution threshold, it means that the individual second-generation key control parameter after fuzzy mutation corresponding to the final fuzzy solution value has no correlation with the actual pH index not meeting the standard. Therefore, there is no need to update and iterate the key control parameters corresponding to the second-generation key process parameters after fuzzy mutation in the parameter control network, so as to improve the accuracy and reliability of the optimization of the rice dumpling production process, ensure the penetration quality of the composite plant ash alkali essence in the production of rice dumpling raw materials, avoid more frequent substandard rice dumpling production caused by optimization errors, and reduce the rework rate of the overall production of rice dumplings.

[0109] In addition, the method for optimizing the production process of rice dumplings based on the compound plant ash alkali preparation further comprises the following steps:

[0110] Acquire multiple deployment concentration monitoring values ​​of the composite plant ash alkali essence at preset time nodes in each sub-process when the zongzi production line equipment executes the zongzi production process, and calculate the deployment concentration monitoring change rate in combination with the multiple deployment concentration monitoring values;

[0111] If the monitoring change rate of the deployment concentration is greater than the preset monitoring change rate of the deployment concentration, then several climate factors that can cause the deployment concentration of the composite plant ash alkali essence to increase based on the big data network are obtained, which are defined as the first type of climate factors; and several climate factors that can cause the deployment concentration of the composite plant ash alkali essence to decrease based on the big data network are obtained, which are defined as the second type of climate factors;

[0112] The factor correlation method is introduced to calculate the factor correlation between each of the first-class climate factors and each of the second-class climate factors and the deployment concentration monitoring change rate, and multiple factor correlations are obtained. The first-class climate factors whose factor correlations are greater than the preset factor correlations are extracted and defined as the first-class abnormal climate factors; at the same time, the second-class climate factors whose factor correlations are greater than the preset factor correlations are extracted and defined as the second-class abnormal climate factors;

[0113] Obtain the target blending concentration value and the minimum taste damage index of the composite plant ash alkali essence required in the production process of rice dumplings, identify the target blending concentration value in the standard food production knowledge graph based on the minimum taste damage index, and obtain the characteristic change result of the target blending concentration value when the composite plant ash alkali essence reaches the minimum taste damage index;

[0114] Obtaining the actual climate factor set where the zongzi production line equipment is located, and when the characteristic change result shows that the target blending concentration is increasing, determining whether the actual climate factor set contains at least one of the abnormal climate factors, and if so, monitoring and optimizing the sub-process flow area corresponding to the zongzi production equipment in the abnormal climate factor, and obtaining the first zongzi production monitoring plan;

[0115] When the characteristic change results show that the target preparation concentration changes in a decreasing manner, it is determined whether the actual climate factor set contains at least one Class II abnormal climate factor. If so, the sub-process flow area corresponding to the zongzi production equipment under the Class II abnormal climate factor is monitored and optimized to obtain the second zongzi production monitoring plan.

[0116] It should be noted that in the process of applying the composite plant ash alkali essence to the raw materials of zongzi, the equipment of the zongzi production line is often affected by the surrounding climate. For example, the increase in climate temperature will cause the composite plant ash alkali essence to partially evaporate, thereby reducing its concentration in the raw materials of zongzi, which is not conducive to the high-quality penetration of the composite plant ash alkali essence into the raw materials of zongzi. Therefore, this method can accurately determine the climate factors that affect the increasing and decreasing changes in the concentration of the composite plant ash alkali essence, and analyze whether there are these climate factors in the actual climate factor set according to the characteristic change results, so that the production process of the zongzi production line equipment in the process of producing zongzi can be efficiently and stably monitored, and the abnormal climate factors can be reduced or eliminated to reduce the concentration of the composite plant ash alkali essence affected by the climate factors, improve the taste and flavor of the zongzi, and ensure the production quality. Among them, the minimum taste damage index is the lowest critical index of the taste perception of the zongzi lower than the ideal taste perception, and the characteristic change result is the characteristic change of the target blending concentration value increasing or decreasing when the composite plant ash alkali essence reaches the minimum taste damage index.

[0117] In addition, the method for optimizing the production process of rice dumplings based on the compound plant ash alkali preparation further comprises the following steps:

[0118] Obtaining production requirements for a rice dumpling production order, obtaining a target taste coefficient of the rice dumpling according to the production requirements, and determining a target blending concentration of the composite plant ash alkali essence based on the target taste coefficient;

[0119] Obtaining the equipment nameplate and multiple rated parameters of the composite plant ash alkali blending equipment, and searching in the big data network based on the equipment nameplate and multiple rated parameters to obtain the expected production parameters that should be output when the composite plant ash alkali blending equipment produces composite plant ash alkali essences of different preset blending concentrations;

[0120] The Jaccard similarity coefficient is introduced to calculate the similarity between the target blending concentration and each different preset blending concentration, and the preset blending concentration corresponding to the maximum similarity is extracted, and the expected production parameters that should be output when the composite plant ash alkali blending equipment produces the preset blending concentration corresponding to the maximum similarity are obtained, which are defined as target expected production parameters;

[0121] Obtaining the operation and maintenance log of the composite plant ash alkali preparation equipment, extracting the actual preparation concentration of the composite plant ash alkali preparation equipment running the target expected production parameters through the operation and maintenance log, calculating the difference between the actual preparation concentration and the target preparation concentration, and obtaining the preparation concentration difference;

[0122] Obtaining the allowable control range of the composite plant ash alkali preparation equipment according to the plurality of rated parameters, regulating the composite plant ash alkali preparation equipment based on the preparation concentration difference until the actual expected production parameters meet the target expected production parameters, and outputting the actual control parameters;

[0123] If the actual control parameter exceeds the allowable control range, the maximum critical control value of the allowable control range is obtained, and the actual control parameter is decreased and adjusted back until it is less than the maximum critical control value. At this time, the final actual control parameter is output and uploaded to the control terminal of the composite plant ash alkali preparation equipment.

[0124] It should be noted that when the production quality of zongzi is improved and its quality and taste are favored by consumers, the order volume of zongzi will increase accordingly. However, when the order volume increases, it is necessary to ensure the timely supply of zongzi order goods, and to ensure that the compound plant ash alkali essence is fully absorbed into the flavor during the production process of zongzi. At the same time, it is also necessary to ensure the efficient operation of the compound plant ash alkali blending equipment. If we are in a hurry to quickly produce zongzi that maintains the taste quality, the control behavior of the compound plant ash alkali blending equipment may exceed its own rated allowable range, causing damage and malfunction of the compound plant ash alkali blending equipment. Therefore, this method can calibrate and control the mixing concentration difference of the composite plant ash alkali essence according to the expected production parameters of the composite plant ash alkali mixing equipment. If the actual control parameters after calibration and control exceed the allowable control range, it means that the actual control parameters will cause the mixing equipment to malfunction. Therefore, the actual control parameters need to be controlled within the allowable control range and must be guaranteed to be at the maximum critical control value, so that the composite plant ash alkali essence can exert the maximum mixing performance under the premise of ensuring that no failure occurs due to the control parameters, thereby improving the mixing quality and rate of the composite plant ash alkali essence, greatly improving the efficiency of rice dumpling production, and effectively accelerating the completion progress of rice dumpling orders.

[0125] The second aspect of the present invention provides a system for optimizing the production process of zongzi based on the preparation of composite plant ash alkali, the system comprising a memory 31 and a processor 32, the memory 31 storing a program for optimizing the production process of zongzi, when the program for optimizing the production process of zongzi is executed by the processor 32, Figure 3 As shown, any one of the steps of the method for optimizing the production process of rice dumplings is implemented.

[0126] The above are only specific embodiments of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art who is familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed by the present invention, which should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention should be based on the protection scope of the claims.

Claims

1. A method for optimizing the production process of rice dumplings based on composite plant ash alkali preparation, characterized in that: The following steps are involved: Obtain the historical production process data detected and recorded when the zongzi production line equipment produces each zongzi variety, and analyze whether there is a pH mutation in the historical production process data based on the quadratic Bezier curve method to determine the pH gap of the zongzi variety with abnormal taste; Obtain the raw material information table of the zongzi variety with abnormal taste, calculate the pH index deviation corresponding to each sub-process in the production process of the zongzi production line equipment for the zongzi variety with abnormal taste when producing the raw material information table, analyze the probability value of each sub-process to generate the pH gap based on the pH index deviation, and mark the pH gap inducing factor process according to the probability value; Obtaining the state characteristics of each raw material in the variety of zongzi with abnormal taste in the process flow of the pH gap inducing factor, calculating the acid-base loss amplitude of the change of the state characteristics of each raw material through the state characteristic analysis, and preparing the composite plant ash-alkali essence based on the acid-base loss amplitude to obtain the prepared composite plant ash-alkali essence; The prepared composite plant ash-alkali essence is actually added to the production process of zongzi to generate an actual pH index and final actual state characteristics. The actual pH index of the produced zongzi is calculated and analyzed based on the actual pH index and the final actual state characteristics to determine whether it is close to the ideal pH index, so as to adaptively optimize the production process of zongzi.

2. The method for optimizing the production process of rice dumplings based on composite plant ash alkali preparation according to claim 1, characterized in that, The method of obtaining the historical production process data detected and recorded when the zongzi production line equipment produces each zongzi variety, and analyzing whether there is a pH mutation in the historical production process data based on the quadratic Bezier curve method to determine the pH gap of the zongzi variety with abnormal taste specifically includes the following steps: Obtain several kinds of zongzi varieties produced and processed by the zongzi production line equipment within a preset time period, and retrieve the historical production process data detected and recorded when the zongzi production line equipment produces each zongzi variety; Obtain the production process of each variety of zongzi, obtain the historical time step of each sub-process when the zongzi production line equipment executes the production process according to the production process, and preset multiple key timestamps based on the historical time step of each sub-process; The historical acid-base data are extracted through the historical production process data, and the historical acid-base data are used to obtain the historical acid-base values ​​of each rice dumpling variety after the production and processing in each sub-process are completed; The quadratic Bezier curve method is introduced, and the key timestamp sequence is set based on the process sequence of each sub-process in the production process. The key timestamp sequence is used as a criterion, and the historical pH value of each zongzi variety after the production and processing in each sub-process is fitted in the Bezier curve method, and the quadratic Bezier curve corresponding to the pH time series change of each zongzi variety is obtained; Preset a pH mutation control point parameter interval, construct a quadratic Bezier curve parameter equation for the pH time series change of each rice dumpling variety based on the quadratic Bezier curve, solve the quadratic Bezier curve parameter equation, and generate a number of pH control point parameter values; If at least one pH control point parameter value is located in the pH mutation control point parameter interval, the variety of rice dumplings corresponding to the quadratic Bezier curve of the pH control electrical parameter value is marked and defined as the variety of rice dumplings with abnormal taste, and the pH gap of the variety of rice dumplings with abnormal taste is determined based on the pH control point parameter value.

3. The method for optimizing the production process of rice dumplings based on composite plant ash alkali preparation according to claim 1, characterized in that, The method of obtaining a raw material information table of a variety of zongzi with abnormal taste, calculating the pH index deviation corresponding to each sub-process in the production process of the zongzi production line equipment for the variety of zongzi with abnormal taste when producing the raw material information table, analyzing the probability value of each sub-process generating the pH gap based on the pH index deviation, and marking the pH gap inducing factor process according to the probability value, specifically includes the following steps: Based on the big data network, historical evaluation information of consumers on the said rice dumpling variety with abnormal taste is obtained, and the expected taste coefficient is preset according to the said historical evaluation information, and at the same time, the preset control strategy of the rice dumpling production line equipment for the production and processing of the said rice dumpling variety with abnormal taste is obtained; Obtain a raw material information table of the variety of zongzi with abnormal taste, and extract preset control parameters corresponding to each raw material in each sub-process in the production process of the variety of zongzi with abnormal taste according to the preset control strategy; Obtain a standard food production knowledge graph through big data network retrieval, import the raw material information table and the preset control parameters into the standard food production knowledge graph for identification based on the expected taste coefficient, and output the pH index of each raw material in the raw material information table at which the expected taste coefficient is achieved under the corresponding preset control parameters, which is defined as the ideal pH index; Obtain the production and processing log of the rice dumpling production line equipment, obtain the actual pH index of the raw materials in each sub-process flow when the rice dumpling production line equipment executes the preset control strategy through the production and processing log, calculate the deviation between each actual pH index and the ideal pH index, and generate a number of pH index deviations; Obtain the flash frequency of the corresponding pH index deviation in each sub-process flow within a preset time period. If the flash frequency exceeds the preset flash frequency, introduce the Bayesian estimation method to calculate the prior probability distribution and the posterior probability distribution of each sub-process flow generating the pH gap when the flash frequency exceeds the preset flash frequency. Determine the probability value of each sub-process flow causing the pH gap based on the prior probability distribution and the posterior probability distribution. Only the sub-process flows corresponding to probability values ​​greater than the preset probability values ​​are marked, and the marked sub-process flows are defined as pH gap inducer process flows.

4. The method for optimizing the production process of rice dumplings based on composite plant ash alkali preparation according to claim 1, characterized in that, The method of obtaining the state characteristics of each raw material in the abnormal-tasting rice dumplings in the process of the pH gap inducing factor, analyzing and calculating the acid-base loss amplitude of the state characteristic change of each raw material through the state characteristics, and preparing the composite plant ash-alkali essence based on the acid-alkali loss amplitude to obtain the prepared composite plant ash-alkali essence, specifically comprises the following steps: Obtain the state characteristics of each raw material in the abnormal-tasting rice dumpling variety in the pH gap inducement factor process flow, and obtain the corresponding functional information of the rice dumpling production line equipment in the pH gap inducement factor process flow; wherein the state characteristics include the viscosity state, the air permeability state and the wrapping density state; Acquire several groups of state characteristic image data of the abnormal zongzi varieties in the pH gap inducement process when the zongzi production line equipment executes the preset control strategy, and construct a dynamic change model of the state characteristic through the several groups of the state characteristic image data; Preset continuous time-series cutting points, perform local time-series slicing on the dynamic change model of the state characteristics based on the continuous time-series cutting points, and obtain the local dynamic change characteristics of the state characteristics of the abnormal taste zongzi variety in the pH gap inducement process; Based on the functional information, the local dynamic change characteristics are introduced into the standard food production knowledge map for identification, and the acid-base loss amplitude of each raw material state characteristic change in the zongzi production line equipment causing abnormal taste zongzi varieties is generated; Obtain the types of plant essences and ash bases used to prepare the composite plant ash base, retrieve the acid-base concentration interaction mechanisms of different plant essences and ash bases in the big data network according to the types of plant essences and ash bases, and construct an acid-base concentration compensation radar chart framework according to the acid-base concentration interaction mechanism; Draw an acid-base concentration compensation radar chart required to compensate the acid-base loss amplitude in the acid-base concentration compensation radar chart framework until the acid-base loss amplitude of each raw material state characteristic change is equal to 0, and finally obtain the acid-base concentration compensation value according to the acid-base concentration compensation radar chart; Each type of plant essence and ash alkali type is accurately blended according to the acid-base concentration compensation value to generate a blended composite plant ash alkali essence, and the acid-base concentration compensation radar chart is uploaded to the composite plant ash alkali blending equipment terminal.

5. The method for optimizing the production process of rice dumplings based on composite plant ash alkali preparation according to claim 1, characterized in that, The method of actually adding the prepared composite plant ash-alkali essence to the zongzi manufacturing process to generate an actual pH index and a final actual state characteristic, and analyzing and calculating whether the actual zongzi pH index produced is close to the ideal pH index according to the actual pH index and the final actual state characteristic to adaptively optimize the zongzi manufacturing process, specifically includes the following steps: The prepared composite plant ash-alkali essence is added to the rice dumpling production line equipment corresponding to the pH gap inducer process and the preset control strategy is executed for actual production, at which time the actual pH index and final actual state characteristics of the rice dumpling production are recorded in real time; Constructing a multiple linear regression model based on the final actual state characteristics, performing multiple linear function fitting on the ideal pH index through the multiple linear regression model, and generating an ideal pH linear function; Acquiring ideal pH data according to the ideal pH linear function, introducing the least square method to calculate the residual between the ideal pH index and the actual pH index in a multivariate linear regression model, and obtaining a plurality of residual values; Based on the preset random distribution threshold of the ideal pH linear function, only the actual pH index corresponding to the residual value less than the preset residual value is marked in the multivariate linear regression model, which is defined as the actual pH index approaching, and a residual distribution diagram approaching the actual pH index is obtained; Taking the random distribution threshold as a constraint benchmark, planning the random distribution area in the multivariate linear regression model until the constraint benchmark is reached to obtain a random distribution field, and obtaining the interference area value of the residual distribution map and the random distribution field; If the interference region area value is greater than the preset interference region area value, it means that the actual pH index and the pH of the rice dumplings produced under the final actual state characteristics are close to the ideal pH index, and the rice dumplings are marked as qualified products, generating a first-level judgment result; If the interference region area value is not greater than the preset interference region area value, it means that the actual pH index and the pH of the rice dumplings produced under the final actual state characteristics cannot approach the ideal pH index, and the rice dumplings are marked as unqualified products, and a secondary judgment result is generated; When the judgment result shows a secondary judgment result, a simulation model of the zongzi production line equipment is constructed. The key process parameter set is obtained through the simulation production of the zongzi production line equipment simulation model. The fuzzy solution values ​​of the key process parameters are analyzed to update the iterative parameter control network, generate new key optimized process parameters, and optimize the zongzi production process flow according to the new key optimized process parameters.

6. The method for optimizing the production process of rice dumplings based on composite plant ash alkali deployment according to claim 5, characterized in that, When the determination result is displayed as a secondary determination result, a simulation model of the zongzi production line equipment is constructed, a key process parameter set is obtained through simulation of the zongzi production line equipment simulation model, the fuzzy solution values ​​of the key process parameters are analyzed to update the iterative parameter control network, and new key optimized process parameters are generated. The zongzi production process is optimized according to the new key optimized process parameters, which specifically includes the following steps: Obtaining an initial design drawing of a rice dumpling production line equipment, converting simulation model data in a simulation model software according to the initial design drawing, and constructing a simulation model of the rice dumpling production line equipment through the simulation model data; A test signal data is generated in the simulation model software according to the prepared composite plant ash alkali essence, and the test signal data is injected into the simulation model of the rice dumpling production line equipment corresponding to the pH gap inducer process flow for simulation based on the preset control strategy conditions; During the simulation process, the parameter control network of the zongzi production line equipment for the pH gap inducement factor process flow is obtained, and the parameter control network is analyzed according to the corresponding functional information of the zongzi production line equipment in the pH gap inducement factor process flow to extract the key process parameter set; Based on the key process parameter set, a number of initial populations are generated, and fitness evaluation is performed on the initial populations to obtain a number of fitness functions, and the first generation of key process parameter individuals in the initial populations whose fitness functions are greater than the preset fitness functions are extracted and defined as key process parameter parents; A fuzzy genetic algorithm is introduced, and based on the fitness function, the extracted multiple key process parameter parents are combined in the fuzzy genetic algorithm to generate second-generation key process parameter individuals, and fuzzy mutation processing is performed on the second-generation key process parameter individuals to obtain the second-generation key process parameter individuals after fuzzy mutation; Preset a satisfactory fuzzy solution threshold, calculate the difference between the interference area value and the preset interference area value, obtain the interference area difference, preset a defuzzification rule in the fuzzy genetic algorithm based on the interference area difference, perform defuzzification calculation on the second-generation key process parameter individuals after fuzzy mutation through the defuzzification rule, and generate a final fuzzy solution value; If the final fuzzy solution value has reached the satisfactory fuzzy solution threshold, the key process parameters in the iterative parameter control network are continuously updated through the second-generation key process parameter individuals after the fuzzy mutation, and the updated iteratively optimized parameter control network is output; The updated iteratively optimized parameter control network is applied to the control terminal of the zongzi production line equipment and re-run to generate new key optimized process parameters. The zongzi production process flow is adaptively optimized based on the new key optimized process parameters to improve the penetration quality of the compound plant ash alkali essence in the production of zongzi raw materials.

7. A rice dumpling manufacturing process optimization system based on composite plant ash alkali preparation, characterized in that: The rice dumpling making process optimization system includes a memory and a processor, wherein the rice dumpling making process optimization method program is stored in the memory. When the rice dumpling making process optimization method program is executed by the processor, the rice dumpling making process optimization method steps as described in any one of claims 1-6 are implemented.

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