A method and system for intelligent state regulation of a chili chopping fermentation jar

Abstract

The application provides a chili chopping fermentation jar intelligent state regulation method and system, relates to the technical field of intelligent regulation, collects fermentation state data of at least two different height layers in the chili chopping fermentation jar; determines the temperature regulation amount of the chili chopping fermentation jar in the current fermentation stage, fuses all the temperature regulation amounts with the fermentation abnormal confidence interval in the corresponding fermentation stage to determine the balance regulation strategy in the corresponding fermentation stage; dynamically switches the balance regulation strategy in the current fermentation stage according to the dynamic turbidity data, generates the environment adaptation characteristics of the fermentation state in the current chili chopping fermentation stage, and then determines the stable operation gradient of the fermentation environment in the current fermentation stage according to the environment adaptation characteristics; and controls the opening and closing ratio of the chili chopping fermentation port sealing valve according to the stable operation gradient, and starts the jar water circulation replacement. The application can realize precise perception regulation of the whole cycle state of chili chopping fermentation, so as to improve the standardization level of the fermentation process.

Description

Technical Field

[0001] This application relates to the field of intelligent control technology, and more specifically, to an intelligent state control method and system for a chopped chili fermentation jar. Background Technology

[0002] Intelligent control is a technology system that relies on online sensing and detection, industrial automatic control and data processing technology to perceive, analyze and automatically manage the production process status and environmental parameters in real time. In the fermentation of pickled vegetables such as chopped peppers, intelligent control is based on the metabolic law of the core beneficial bacteria in fermentation. It automatically completes the precise adjustment of core links such as temperature control, jar sealing control and soaking water circulation by controlling the physicochemical parameters of the fermentation process. It does not require frequent manual intervention and is a supporting technology for standardized production of food fermentation.

[0003] However, traditional methods of controlling the state of chopped chili fermentation jars lack accurate perception of the vertical spatial heterogeneity of the solid-liquid mixed fermentation system. This leads to a disconnect between the fermentation state data collected at a single point and the actual fermentation process within the jar. Furthermore, the failure to integrate temperature control with the prevention of fermentation anomalies results in a low degree of matching between the fermentation environment control and the metabolic needs of beneficial bacteria, leading to poor stability and batch-to-batch quality consistency. Therefore, achieving precise perception and control of the entire fermentation cycle of chopped chili to improve the standardization of the fermentation process is a challenge facing the industry. Summary of the Invention

[0004] This application provides an intelligent state control method and system for a chopped chili fermentation jar, which can achieve precise sensing and control of the entire fermentation cycle of chopped chili, thereby improving the standardization level of the fermentation process.

[0005] In a first aspect, this application provides an intelligent state control method for a chopped chili fermentation jar, the control method comprising the following steps:

[0006] Collect fermentation status data from at least two different height layers inside the chopped chili fermentation jar;

[0007] Based on the fermentation state data of each height layer, the temperature control amount of the chopped pepper fermentation jar in the current fermentation stage is determined. All temperature control amounts are then integrated with the fermentation anomaly confidence interval in the corresponding fermentation stage to obtain the balance control strategy of the fermentation environment of the chopped pepper fermentation jar in the corresponding fermentation stage.

[0008] The dynamic turbidity data of the soaking water in the fermentation jar of chopped peppers is collected in real time. The balance control strategy in the current fermentation stage is dynamically switched according to the dynamic turbidity data, and the environmental adaptation characteristics of the fermentation state in the current fermentation stage of chopped peppers are generated. Then, the stable operation gradient of the fermentation environment in the current fermentation stage is determined according to the environmental adaptation characteristics.

[0009] Based on the stable operation gradient, the opening and closing ratio of the sealing valve of the fermentation port of the chopped pepper is controlled, and the water circulation of the soaking jar is started for replacement.

[0010] In this embodiment, determining the temperature control amount of the chopped chili fermentation jar in the current fermentation stage based on the fermentation status data of each height layer specifically includes:

[0011] The fermentation characteristic parameter set of the chopped chili fermentation jar at the current fermentation stage is determined based on the fermentation status data of each height layer;

[0012] By matching the set of fermentation characteristic parameters with the temperature requirements of the preset fermentation stage, the temperature regulation requirement gradient in the current fermentation stage is determined.

[0013] The temperature control amount in the chopped chili fermentation jar during the current fermentation stage is determined based on the temperature control requirement gradient and the real-time fermentation temperature feedback value.

[0014] In this embodiment, the fermentation stages are the pre-fermentation period, the main fermentation period, and the post-ripening period.

[0015] In this embodiment, all temperature control parameters are integrated with the fermentation anomaly confidence intervals in the corresponding fermentation stages to obtain the specific balance control strategy for the fermentation environment of the chopped chili fermentation jar in the corresponding fermentation stages, which includes:

[0016] The temperature regulation values ​​of each height layer are spatiotemporally registered with the historical fermentation anomaly confidence intervals of the corresponding fermentation stages to obtain the initial regulation feature set before fusion.

[0017] The initial regulatory feature set is fused with the real-time monitored fermentation anomaly confidence interval to obtain the regulatory confidence correlation matrix;

[0018] Based on the weights of the abnormal confidence in the regulation confidence correlation matrix, the temperature regulation amount is dynamically compensated to generate a phased temperature compensation regulation index during the fermentation stage.

[0019] Based on the temperature compensation control index and the humidity control requirements of the chopped chili fermentation jar, a balance control strategy for the fermentation environment of the chopped chili fermentation jar in the corresponding fermentation stage is determined.

[0020] In this embodiment, the real-time acquisition of dynamic turbidity data of the soaking water in the fermentation jar of chopped chili peppers specifically includes:

[0021] Based on the light scattering characteristics and real-time transmitted light intensity of the soaking water in the fermentation jar for chopped chili peppers, an optical feature vector of dynamic turbidity is constructed.

[0022] The dynamic turbidity change gradient at the current moment is determined by the optical feature vector and the temperature compensation coefficient of the soaking water.

[0023] Extract the turbidity data acquisition trigger rules that meet the preset sampling period from the dynamic turbidity change gradient to obtain the dynamic turbidity data of the soaking water in the chopped pepper fermentation jar.

[0024] In this embodiment, the balance control strategy in the current fermentation stage is dynamically switched based on the dynamic turbidity data, and the environmental adaptation characteristics of the fermentation state in the current chopped chili fermentation stage are generated, specifically including:

[0025] Based on the time-series fluctuation information of the dynamic turbidity data and the expected turbidity benchmark at the current fermentation stage, a turbidity deviation index is determined.

[0026] The turbidity deviation index is matched with the preset fermentation state switching rules to determine the current balance control strategy identifier that needs to be switched.

[0027] Environmental control factors are extracted from the set of control parameters corresponding to the balance control strategy identifier to generate environmental adaptation features of the fermentation state in the current chopped chili fermentation stage.

[0028] In this embodiment, the fermentation state refers to the state of the anaerobic fermentation system of chopped chili peppers during the corresponding fermentation stage, including the metabolic process of beneficial bacteria, the physicochemical characteristics of the substances, the stability of the anaerobic environment inside the jar, and the reliability of the water seal.

[0029] In this embodiment, determining the stable operating gradient of the fermentation environment in the current fermentation stage based on the environmental adaptation characteristics specifically includes:

[0030] The initial stable operating gradient of the fermentation environment is determined based on the temporal fluctuation range of temperature and humidity in the environmental adaptation characteristics.

[0031] Based on the initial stable operating gradient and the boundary conditions of microbial metabolic activity in the current fermentation stage, the dynamic constraint range of fermentation environment fluctuations is determined.

[0032] The dynamic control target in the environmental adaptation feature is mapped by the dynamic constraint range to generate the dynamic adjustment amount corresponding to each fermentation environment.

[0033] By weighting and integrating all dynamic adjustment values ​​with the historical inertia coefficient of the fermentation tank environment, the stable operating gradient of the fermentation environment in the current fermentation stage is obtained.

[0034] In this embodiment, the opening and closing ratio of the sealing valve at the fermentation port of the chopped chili pepper is specifically controlled according to the stable operation gradient gradation, including:

[0035] Based on the numerical range of the stable operating gradient and the graded control rules in the chopped pepper fermentation jar, the opening ratio factor of the sealing valve and the starting threshold of the soaking water circulation are extracted.

[0036] Based on the opening ratio factor and the real-time monitored rate of change of pressure inside the tank, the compensation coefficient for the opening and closing action of the sealing valve during dynamic adjustment is determined.

[0037] The control execution command is co-encoded by the opening and closing action compensation coefficient and the cycle start threshold to generate a control signal for the graded opening and closing of the sealing valve.

[0038] Secondly, this application provides an intelligent state control system for a chopped chili fermentation jar, used to execute an intelligent state control method for a chopped chili fermentation jar, the control system comprising:

[0039] The data acquisition module is used to collect fermentation status data at least two different height layers inside the chopped chili fermentation jar;

[0040] The fusion module is used to determine the temperature control amount of the chopped pepper fermentation jar in the current fermentation stage based on the fermentation state data of each height layer, and to fuse all the temperature control amounts with the fermentation anomaly confidence interval in the corresponding fermentation stage to obtain the balance control strategy of the fermentation environment of the chopped pepper fermentation jar in the corresponding fermentation stage.

[0041] The control switching module is used to collect dynamic turbidity data of the soaking water in the fermentation jar of chopped peppers in real time, and dynamically switch the balance control strategy in the current fermentation stage according to the dynamic turbidity data, generate environmental adaptation characteristics of the fermentation state in the current fermentation stage of chopped peppers, and then determine the stable operation gradient of the fermentation environment in the current fermentation stage according to the environmental adaptation characteristics.

[0042] The status control module is used to control the opening and closing ratio of the sealing valve of the fermentation port of chopped pepper according to the stable operation gradient, and to start the circulation and replacement of the soaking water.

[0043] The technical solutions provided by the embodiments disclosed in this application have the following beneficial effects:

[0044] Fermentation state data are collected from at least two different height layers within the chopped chili fermentation jar. Based on the fermentation state data from each height layer, the temperature control parameters for the current fermentation stage are determined. All temperature control parameters are then fused with the fermentation anomaly confidence intervals for the corresponding fermentation stages to obtain the balance control strategy for the fermentation environment in the corresponding fermentation stage. Real-time dynamic turbidity data of the soaking water in the chopped chili fermentation jar is collected. Based on the dynamic turbidity data, the balance control strategy for the current fermentation stage is dynamically switched to generate environmental adaptation characteristics of the fermentation state within the current fermentation stage. Then, based on these environmental adaptation characteristics, a stable operating gradient for the fermentation environment in the current fermentation stage is determined. The opening and closing ratio of the sealing valve at the fermentation port is controlled in stages according to the stable operating gradient, and the soaking water circulation is initiated.

[0045] Therefore, in this application, the opening and closing ratio of the sealing valve of the fermentation port of chopped pepper is controlled according to the stable operation gradient gradation, and the soaking water circulation and replacement are started. Among them, the balanced control strategy in the fermentation stage can obtain a standardized environmental control execution benchmark that is adapted to the microbial metabolic characteristics of each stage of the entire fermentation cycle of chopped pepper, and takes into account the progress of fermentation and the prevention and control of abnormal risks. This achieves the precise matching of fermentation environmental control parameters with the metabolic laws of dominant lactic acid bacteria in each fermentation stage, breaks the inherent limitation of the disconnect between traditional fixed parameter control and dynamic fermentation process, integrates the prevention and control of fermentation abnormal risks into the control logic in advance, achieves a two-way balance between fermentation efficiency and safety control, provides a staged unified execution standard for the whole cycle closed-loop control, and effectively reduces the batch-to-batch quality deviation caused by human experience intervention. By determining the stable operating gradient of the fermentation environment, a graded control execution level can be obtained that precisely matches the real-time stable state and microbial metabolic safety boundary of the chopped chili fermentation system. This enables dynamic linkage between the fermentation terminal execution actions and the real-time state of the fermentation environment, breaking the inherent limitations of the traditional one-size-fits-all control mode. It incorporates fluctuations in the environmental parameters inside the jar and changes in the water seal status into the graded control logic, providing an unambiguous standardized execution basis for graded control of the sealing valve and replacement of the soaking water. This achieves closed-loop coordination of dynamic regulation, effectively avoiding fluctuations in the fermentation state caused by insufficient or excessive control, and ensuring the stability of the entire fermentation process.

[0046] In summary, the technical solution adopted in this application can achieve precise sensing and control of the entire fermentation cycle of chopped chili peppers, thereby improving the standardization level of the fermentation process. Attached Figure Description

[0047] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only for this embodiment of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0048] Figure 1 This is an exemplary flowchart of an intelligent state control method for a chopped chili fermentation jar provided in this application;

[0049] Figure 2 This is a flowchart illustrating the process of determining the balance control strategy provided in this application;

[0050] Figure 3 This is a flowchart illustrating the process of determining a stable operating gradient based on the information provided in this application;

[0051] Figure 4 This is a schematic diagram of the normalized change curve of the colony number of dominant lactic acid bacteria during the anaerobic fermentation of chopped chili peppers provided in this application.

[0052] Figure 5 This is a module structure diagram of an intelligent state control system for a chopped chili fermentation jar provided in this application. Detailed Implementation

[0053] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of this application.

[0054] This application provides an intelligent state control method and system for a chopped chili fermentation jar. The core of this method involves collecting fermentation state data from at least two different height layers within the jar; determining the temperature control amount for the current fermentation stage based on the fermentation state data from each height layer; fusing all temperature control amounts with the corresponding fermentation anomaly confidence intervals to obtain a balance control strategy for the fermentation environment in the corresponding fermentation stage; real-time collection of dynamic turbidity data from the soaking water in the jar; dynamically switching the balance control strategy for the current fermentation stage based on the dynamic turbidity data; generating environmental adaptation characteristics for the fermentation state in the current fermentation stage; determining the stable operating gradient of the fermentation environment in the current fermentation stage based on the environmental adaptation characteristics; and controlling the opening and closing ratio of the sealing valve at the fermentation port according to the stable operating gradient, and initiating the circulation and replacement of the soaking water.

[0055] Example 1: To better understand the above technical solution, the following will provide a detailed description of the technical solution in conjunction with the accompanying drawings and specific implementation methods. (Refer to...) Figure 1 As shown in the figure, this is an exemplary flowchart of an intelligent state control method for a chopped chili fermentation jar according to this embodiment of the present application. The control method includes the following steps:

[0056] In step S1, fermentation status data of at least two different height layers in the chopped chili fermentation jar are collected.

[0057] In practice, firstly, based on the principle that the anaerobic fermentation system of chopped chili peppers exhibits significant vertical spatial heterogeneity, two core detection layers are pre-defined according to the total height of the fermentation tank and the material filling height: the bottom layer is located in the juice-rich area 0.05-0.1m from the bottom of the tank, and the upper layer is located in the near-headspace area 0.05-0.1m from the material surface, covering the two locations with the most significant differences in fermentation state. A range-calibrated food-grade multi-parameter sensor group is installed on the inner wall of the corresponding height layer to simultaneously collect parameters such as temperature, pH, dissolved oxygen, and soluble solids. The collection frequency is set according to the fermentation stage: once every 10 minutes during the pre-fermentation and main fermentation periods, and once every 2 hours during the post-ripening period. After filtering out outliers using a moving average, the average of five consecutive collections is taken as the valid data, which is then used as the fermentation state data for different height layers.

[0058] It should be noted that, in this application, fermentation status data refers to the quantitative information on the fermentation process and physicochemical state at different depths in the chopped chili fermentation jar.

[0059] In step S2, the temperature control amount of the chopped chili fermentation jar in the current fermentation stage is determined based on the fermentation state data of each height layer. All temperature control amounts are then fused with the fermentation anomaly confidence interval in the corresponding fermentation stage to obtain the balance control strategy of the fermentation environment of the chopped chili fermentation jar in the corresponding fermentation stage.

[0060] In this embodiment, determining the temperature control level of the chopped chili fermentation jar in the current fermentation stage based on the fermentation status data of each height layer can be achieved through the following steps:

[0061] The fermentation characteristic parameter set of the chopped chili fermentation jar at the current fermentation stage is determined based on the fermentation status data of each height layer;

[0062] By matching the set of fermentation characteristic parameters with the temperature requirements of the preset fermentation stage, the temperature regulation requirement gradient in the current fermentation stage is determined.

[0063] The temperature control amount in the chopped chili fermentation jar during the current fermentation stage is determined based on the temperature control requirement gradient and the real-time fermentation temperature feedback value.

[0064] In practice, firstly, the effective fermentation state data collected at each height level are processed using the min-max standardization method to normalize all parameters to the 0-1 range, eliminating dimensional differences between different parameters. Then, weighted coefficients are applied: 0.4 for the bottom detection layer, 0.4 for the upper detection layer, and 0.2 for the middle detection layer. The weighting coefficients are determined based on the stacking height of the fermented material in the multi-stage fermentation jar, which will not be elaborated here. The standardized fermentation state data are then weighted and fused to obtain the comprehensive parameter values ​​for the entire jar. Parameters strongly correlated with fermentation temperature are extracted and combined to form a set of fermentation characteristic parameters for the current fermentation stage of the chopped chili fermentation jar. Then, based on the publicly available standardized data of chopped chili fermentation process published in *China Condiments*, the supporting process guidelines for GB2714-2015 National Standard for Food Safety of Pickled Vegetables, and historical verification data from over 100 batches of normal industrial fermentation, a database of standard fermentation characteristic parameters and matching temperature requirements corresponding to each preset fermentation stage is established. The Euclidean distance algorithm is used to calculate the matching degree between the current fermentation characteristic parameter set and the standard parameter sets of each preset stage. Based on the preset interval where the matching degree value is located, the temperature control requirement gradient corresponding to the current fermentation stage is divided and determined. Finally, based on the determined temperature control requirement gradient, the target temperature range of the corresponding gradient and the preset adjustment coefficient are retrieved. This preset adjustment coefficient is optimized based on the proportional coefficient of the PID control algorithm in the field of industrial process control. The difference between the real-time fermentation temperature feedback value and the benchmark value of the target temperature range is calculated. The difference is multiplied by the adjustment coefficient of the corresponding gradient to obtain the temperature control amount of the chopped pepper fermentation jar in the current fermentation stage. Positive values ​​are the temperature increase amplitude, and negative values ​​are the temperature decrease amplitude.

[0065] It should be noted that the fermentation stage described in this application is anaerobic solid-state fermentation dominated by lactic acid bacteria. Based on the laws of microbial metabolism, physical and chemical changes, and process objectives, the entire process is divided into three fermentation stages: pre-fermentation, main fermentation, and post-fermentation. The pre-fermentation stage lasts from 0 to 3 days after fermentation begins and is the period of microbial activation and proliferation. During this stage, beneficial bacteria rapidly colonize and inhibit the activity of other bacteria. The main fermentation stage lasts from 4 to 15 days and is the period of acid production dominated by lactic acid bacteria. During this stage, sugar degradation and lactic acid accumulation are completed, laying the foundation for the product's basic flavor. The post-fermentation stage lasts from 16 days to the end of fermentation and is the period of flavor substance synthesis. During this stage, flavor transformation and balance are completed, forming the product's unique quality.

[0066] It should be noted that, in this application, the fermentation characteristic parameter set refers to the set of quantitative parameters of the current microbial metabolic process, physical physicochemical state, and fermentation progress of the chopped chili fermentation system; the temperature demand matching degree refers to the index that quantitatively determines the degree of conformity between the current fermentation state of the chopped chili fermentation system and the optimal temperature control requirements of the corresponding fermentation stage; the temperature regulation demand gradient refers to the quantitative classification of the urgency and adjustment level of the current fermentation system temperature adjustment; the real-time fermentation temperature feedback value refers to the quantitative value of the real-time temperature of the current chopped chili fermentation system; and the temperature regulation amount refers to the quantitative value of the direction and magnitude of temperature adjustment required to make the temperature of the chopped chili fermentation system reach the target temperature range of the corresponding gradient.

[0067] Preferably, in this embodiment, all temperature control parameters are fused with the fermentation anomaly confidence intervals in the corresponding fermentation stages to obtain a balance control strategy for the fermentation environment of the chopped chili fermentation jar in the corresponding fermentation stages, as referenced. Figure 2 As shown in the figure, this is a flowchart illustrating the process of determining the balance control strategy in some embodiments of this application. In this embodiment, the determination of the balance control strategy can be achieved through the following steps:

[0068] In step S21, the temperature regulation amount of each height layer is spatiotemporally registered with the historical fermentation anomaly confidence interval of the corresponding fermentation stage to obtain the initial regulation feature set before fusion;

[0069] In step S22, the initial regulatory feature set is fused with the real-time monitored fermentation anomaly confidence interval to obtain the regulatory confidence correlation matrix;

[0070] In step S23, the temperature regulation amount is dynamically compensated according to the weight of the abnormal confidence in the regulation confidence correlation matrix to generate a staged temperature compensation regulation index in the fermentation stage.

[0071] In step S24, a balance control strategy for the fermentation environment of the chopped chili fermentation jar in the corresponding fermentation stage is determined based on the temperature compensation control index and the humidity control requirements of the chopped chili fermentation jar.

[0072] In practical implementation, firstly, a database of historical fermentation anomaly confidence intervals corresponding to each fermentation stage and height layer can be established based on full-cycle data from over 100 batches of normal and abnormal batches of chopped chili peppers produced in large quantities. Firstly, in the time dimension, the temperature control values ​​at each height layer are aligned with the historical fermentation anomaly confidence intervals corresponding to the current fermentation stage. Secondly, in the spatial dimension, the temperature control values ​​at each height layer are matched with the historical fermentation anomaly confidence intervals at the same height layer. Finally, the registered temperature control values ​​are integrated with the anomaly interval boundary parameters to obtain an initial control feature set. Next, based on the real-time fermentation status data collected at each height layer during the current fermentation cycle, the normal distribution statistical method used in the food fermentation field is employed to calculate the real-time monitored fermentation anomaly confidence intervals corresponding to the current fermentation stage and each height layer. Using the parameters of each dimension of the initial control feature set as matrix row elements and the real-time anomaly confidence levels corresponding to the real-time monitored fermentation anomaly confidence intervals as matrix column elements, the Pearson correlation coefficient method is used to calculate the correlation value between each row element and each column element. The calculated correlation values ​​are then filled into the corresponding matrix positions to obtain the final control confidence correlation matrix. Then, the real-time anomaly confidence scores for each height level are extracted from the control confidence correlation matrix. The min-max standardization method is used to normalize all anomaly confidence scores to the 0-1 range, obtaining the weights of the anomaly confidence scores for each height level. The weights are positively correlated with the anomaly confidence scores. Based on the feedforward compensation algorithm in industrial process control, the original temperature control values ​​for each height level are corrected and calculated with their corresponding weights to obtain the compensated temperature control values ​​for each height level. After weighted fusion, a stage-specific temperature compensation control index for the current fermentation stage is generated. Finally, based on the research results and mass production verification data of the standardized process for chopped chili fermentation, a humidity control requirement database for each fermentation stage can be established. The humidity control requirements for the current fermentation stage are retrieved, and the execution parameters of the humidity control requirements are collaboratively corrected according to the adjustment direction and magnitude of the temperature compensation control index. This ultimately integrates temperature control execution parameters, humidity control execution parameters, anomaly risk prevention thresholds, and equipment execution timing to form a balanced control strategy for the corresponding fermentation stage.

[0073] It should be noted that, in this application, the fermentation anomaly confidence interval refers to the quantitative interval used to define the risk of fermentation anomalies occurring at the corresponding fermentation stage and at the corresponding height level; the historical fermentation anomaly confidence interval refers to the benchmark interval used to quantitatively define the boundary of the risk of anomalies occurring in the fermentation system; the initial control feature set refers to the comprehensive dataset of temperature control requirements at each height level and the corresponding anomaly risk benchmark; the control confidence correlation matrix refers to the two-dimensional matrix that quantitatively characterizes the correlation between the temperature control amount at each height level and the corresponding fermentation anomaly confidence level; the weight of the anomaly confidence level refers to the quantitative coefficient of the proportion of the impact of fermentation anomaly risk on the correction range of temperature control amount; the temperature compensation control index refers to the temperature control execution parameters adapted to the current fermentation stage and the current anomaly risk level; the humidity control requirement refers to the optimal humidity range and adjustment requirements of the environment inside the fermentation tank at the corresponding fermentation stage; and the balance control strategy refers to the fermentation environment control scheme that includes the advancement of the fermentation process and the prevention and control of fermentation anomaly risks.

[0074] In step S3, dynamic turbidity data of the soaking water in the fermentation jar of chopped chili is collected in real time. The balance control strategy in the current fermentation stage is dynamically switched according to the dynamic turbidity data to generate environmental adaptation characteristics of the fermentation state in the current fermentation stage of chopped chili. Then, the stable operating gradient of the fermentation environment in the current fermentation stage is determined according to the environmental adaptation characteristics.

[0075] In this embodiment, the dynamic turbidity data of the soaking water in the fermentation jar of chopped chili peppers can be collected in real time using the following steps:

[0076] Based on the light scattering characteristics and real-time transmitted light intensity of the soaking water in the fermentation jar for chopped chili peppers, an optical feature vector of dynamic turbidity is constructed.

[0077] The dynamic turbidity change gradient at the current moment is determined by the optical feature vector and the temperature compensation coefficient of the soaking water.

[0078] Extract the turbidity data acquisition trigger rules that meet the preset sampling period from the dynamic turbidity change gradient to obtain the dynamic turbidity data of the soaking water in the chopped pepper fermentation jar.

[0079] In practical implementation, firstly, based on the 90° scattered light-transmitted light dual-optical-path detection principle in the field of turbidity detection, a food-grade dual-optical-path optical detection module is installed in the water seal tank of the soaking water. The module includes an 860nm near-infrared light source, a 90° scattered light photodetector, and a transmitted light photodetector. Real-time data on the scattered light intensity and transmitted light intensity of the soaking water are collected. The scattered light attenuation coefficient corresponding to the light scattering characteristics and the transmittance parameter corresponding to the transmitted light intensity are extracted. After min-max standardization, the scattered light attenuation coefficient and transmittance parameter are combined according to a fixed dimension to construct a dynamic turbidity optical feature vector. Then, based on the national standard for water turbidity detection, a database of the correspondence between the temperature of the soaking water and the detection deviation is established through gradient calibration experiments with standard solutions of different temperatures and turbidities, determining the temperature compensation coefficient of the soaking water for different temperature ranges. The optical feature vector is input into a pre-calibrated turbidity calculation model. After correction by a temperature compensation coefficient, the real-time turbidity value of the fermentation water in the jar is calculated. Then, the first-order difference method is used to calculate the ratio of the turbidity difference between the current moment and the previous sampling moment to the time interval. The dynamic turbidity change gradient at the current moment is determined based on the calculated ratio. Finally, based on the full-cycle change law of the fermentation water in the jar for mass production of chopped peppers, a benchmark preset sampling period and a turbidity change gradient threshold are set. The dynamic turbidity change gradient at the current moment is compared with the preset threshold. If the absolute value of the gradient does not exceed the threshold, turbidity data is collected according to the preset sampling period, and the turbidity value at the corresponding moment is extracted as valid data. If the absolute value of the gradient exceeds the threshold, encrypted acquisition is triggered immediately, and the sampling interval is shortened to complete continuous data acquisition. After removing bubble interference data using the amplitude limiting filtering method known in the field of signal processing, the dynamic turbidity data of the fermentation water in the jar for chopped peppers is obtained.

[0080] It should be noted that, in this application, light scattering characteristics refer to the inherent optical property of the ability of suspended particles in the soaking water to scatter incident light; real-time transmitted light intensity refers to the transmitted light radiation intensity value collected in real time by the photoelectric sensor after the incident light passes through the soaking water; optical feature vector is a set of features with unified dimensions characterizing the optical detection parameters of the soaking water; temperature compensation coefficient refers to a quantitative correction coefficient that corrects the deviation caused by the temperature change of the soaking water to the optical detection results; dynamic turbidity change gradient is a quantitative index characterizing the rate and direction of turbidity change in the soaking water per unit time; preset sampling period refers to the turbidity data benchmark acquisition time interval preset based on the turbidity change law of the soaking water; turbidity data acquisition triggering rule refers to the judgment criterion for determining whether to start the effective acquisition and uploading of turbidity data; dynamic turbidity data refers to the effective quantitative time-series data of the turbidity degree of the soaking water.

[0081] In this embodiment, the dynamic switching of the balance control strategy in the current fermentation stage based on the dynamic turbidity data, and the generation of environmental adaptation characteristics of the fermentation state in the current chopped chili fermentation stage, can be achieved through the following steps:

[0082] Based on the time-series fluctuation information of the dynamic turbidity data and the expected turbidity benchmark at the current fermentation stage, a turbidity deviation index is determined.

[0083] The turbidity deviation index is matched with the preset fermentation state switching rules to determine the current balance control strategy identifier that needs to be switched.

[0084] Environmental control factors are extracted from the set of control parameters corresponding to the balance control strategy identifier to generate environmental adaptation features of the fermentation state in the current chopped chili fermentation stage.

[0085] In practice, firstly, the dynamic turbidity data of the soaking water from the fermentation jars of chopped chili peppers is collected, and the time-series fluctuation information is extracted using the sliding window method. The window width is matched with the preset sampling period, and the time-series mean and fluctuation variance of the turbidity within the window are calculated. Then, the expected turbidity benchmark for the current fermentation stage is retrieved based on the full-cycle verification data of more than 100 batches of chopped chili peppers produced in large quantities. Using a relative deviation calculation model, the difference between the time-series mean and the expected turbidity benchmark is divided by the benchmark value. After correction for fluctuation variance, the turbidity deviation index is obtained. Next, based on the GB 2714-2015 National Standard for Food Safety of Pickled Vegetables and the industrial-scale verification data of chopped chili pepper fermentation, preset fermentation state switching rules corresponding to each fermentation stage are established. Within the fermentation state switching rules, the fermentation state is divided into three continuous intervals: normal, warning, and abnormal, according to the turbidity deviation value. Each interval is bound to a unique balance control strategy identifier. The calculated turbidity deviation index is compared one by one with the interval threshold corresponding to the current fermentation stage to determine the interval to which the index belongs, and the balance control strategy identifier bound to that interval is extracted. Finally, based on the determined balance control strategy identifier, the set of control parameters uniquely corresponding to the identifier is retrieved from the pre-established strategy-parameter mapping database. This strategy-parameter mapping data is established based on the full-cycle process verification data of chopped chili fermentation. Four core environmental control factors, namely temperature control, dissolved oxygen control, pressure control inside the jar, and sealing performance control, are extracted from the control parameter set. The min-max standardization method is used to normalize each control factor to the 0-1 interval. The factors are then combined according to fixed dimensions to generate the environmental adaptation characteristics of the fermentation state in the current chopped chili fermentation stage.

[0086] It should be noted that, in this application, fermentation state refers to the state of the anaerobic fermentation system for chopped chili peppers during the corresponding fermentation stage, including the metabolic process of beneficial bacteria, physical and chemical characteristics, stability of the anaerobic environment within the fermentation jar, and reliability of the water seal; temporal fluctuation information is a set of quantitative information characterizing the variation range and fluctuation pattern of the turbidity of the soaking water in the fermentation jar over a continuous time series; expected turbidity benchmark refers to the standard value of turbidity of the soaking water under normal conditions during the corresponding fermentation stage; turbidity deviation index refers to the numerical value that quantifies the degree of deviation between the real-time turbidity state of the soaking water and the expected turbidity benchmark for the corresponding fermentation stage; fermentation state switching rule refers to the standardized judgment criteria that correspond one-to-one between the turbidity deviation range and the balance control strategy; balance control strategy identifier refers to the uniquely identifiable code bound to each balance control strategy; control parameter set refers to the standardized parameter set for adjusting the fermentation environment; environmental control factor refers to the control parameters that directly affect the environmental stability of the chopped chili pepper fermentation system; and environmental adaptability characteristics refer to the set of characteristics characterizing the current chopped chili pepper fermentation system's control requirements for the fermentation environment, abnormal tolerance boundaries, and environmental adaptability.

[0087] Preferably, in this embodiment, the stable operating gradient of the fermentation environment in the current fermentation stage is determined based on the environmental adaptation characteristics, with reference to... Figure 3 As shown in the figure, this is a flowchart illustrating the process of determining a stable operating gradient in some embodiments of this application. In this embodiment, determining the stable operating gradient can be achieved using the following steps:

[0088] In step S31, the initial stable operating gradient of the fermentation environment is determined based on the temporal fluctuation amplitude of temperature and humidity in the environmental adaptation characteristics.

[0089] In step S32, based on the initial stable operating gradient and the boundary conditions of microbial metabolic activity in the current fermentation stage, the dynamic constraint range of fermentation environment fluctuations is determined.

[0090] In step S33, the dynamic control target in the environmental adaptation feature is mapped through the dynamic constraint range to generate the dynamic adjustment amount corresponding to each fermentation environment;

[0091] In step S34, the stable operating gradient of the fermentation environment in the current fermentation stage is obtained by weighted fusion of all dynamic adjustment quantities and the historical inertia coefficient of the environmental state in the fermentation tank.

[0092] In practice, firstly, the time-series data of temperature and humidity within a preset sliding window of the current fermentation stage are extracted from the environmental adaptation features. The window width is matched with the sampling period of the current fermentation stage. The range method is used to calculate the time-series fluctuation amplitude of temperature and humidity parameters. After the time-series fluctuation amplitude of temperature and humidity parameters is normalized by min-max, it is weighted and summed with a temperature weight of 0.6 and a humidity weight of 0.4 to obtain the comprehensive fluctuation coefficient. The temperature weight and humidity weight can be determined based on the temperature and humidity of multiple batches of fermentation tanks, and are not limited here. Based on 100 batches of mass production verification data, a mapping interval between the comprehensive fluctuation coefficient and the stability level is established. The comprehensive fluctuation coefficient is compared with the interval threshold to determine the initial stable operating gradient of the fermentation environment. Then, based on the publicly available research results on the metabolic characteristics of the dominant Lactobacillus plantarum in chopped pepper fermentation, combined with 100 batches of mass production verification data, a database of microbial metabolic activity boundary conditions corresponding to each fermentation stage is established, and the safety thresholds of temperature, humidity, and dissolved oxygen for the current fermentation stage are retrieved. Based on the initial stable operating gradient, the safety threshold is narrowed in stages. The lower the gradient stability level, the greater the threshold narrowing ratio. The narrowing ratio is pre-calibrated based on the initial gradient stability level, ultimately forming a dynamic constraint range for fermentation environment fluctuations that is fully adapted to the initial gradient and microbial metabolic needs. Next, four core dynamic control targets—temperature, humidity, dissolved oxygen, and pressure within the fermentation tank—are extracted from the environmental adaptation characteristics. Each control target is compared with the upper and lower limits of the dynamic constraint range. Using an interval mapping algorithm, control target values ​​exceeding the constraint range are corrected to the nearest boundary of the constraint range. Control target values ​​within the constraint range are corrected for deviations based on the median of the constraint range. The difference between each control target and the corrected value is calculated to generate the dynamic adjustment amount corresponding to each fermentation environment. Finally, based on the heat and mass transfer characteristics of the fermentation tank and the environmental time-series data of 100 batches of mass-produced fermentation, a first-order autoregressive analysis model is used to calibrate the historical inertia coefficient of the fermentation tank environment state corresponding to each fermentation stage. This historical inertia coefficient ranges from 0 to 1. After all dynamic adjustment values ​​are standardized by min-max, they are weighted and calculated with the historical inertia coefficients of the corresponding environmental parameters to obtain a comprehensive stability score. The comprehensive stability score is then compared with the preset gradient classification threshold to obtain the stable operating gradient of the fermentation environment in the current fermentation stage.

[0093] It should be noted that, in this application, the order fluctuation amplitude refers to the quantitative index of the degree of fluctuation of temperature and humidity parameters in the chopped chili fermentation jar deviating from the target control range in a continuous time series; the initial stable operation gradient refers to the fermentation environment stability level initially divided based on the temperature and humidity fluctuation amplitude; the boundary conditions of microbial metabolic activity refer to the set of safe upper and lower limit thresholds of metabolic characteristics and fermentation environment parameters corresponding to the dominant beneficial bacteria in each stage of chopped chili fermentation; the dynamic constraint range of fermentation environment fluctuation refers to the dynamic range of environmental parameters that are allowed to fluctuate, adapting to the initial stable operation gradient and the metabolic needs of microorganisms; the dynamic control target refers to the target control value of fermentation environment control parameters that match the current chopped chili fermentation stage and real-time fermentation status; the dynamic adjustment amount refers to the quantitative value of the adjustment direction and adjustment amplitude of each environmental parameter in the chopped chili fermentation jar; the historical inertia coefficient refers to the quantitative coefficient of the degree of influence of the historical change trend of environmental parameters in the fermentation jar on the current state; and the stable operation gradient refers to the graded quantitative level of the overall stability of the fermentation environment.

[0094] In step S4, the opening and closing ratio of the sealing valve of the fermentation port of chopped pepper is controlled according to the stable operation gradient, and the water circulation of the soaking jar is started.

[0095] In this embodiment, the opening and closing ratio of the sealing valve at the fermentation port of the chopped pepper, based on the stable operation gradient, can be achieved through the following steps:

[0096] Based on the numerical range of the stable operating gradient and the graded control rules in the chopped pepper fermentation jar, the opening ratio factor of the sealing valve and the starting threshold of the soaking water circulation are extracted.

[0097] Based on the opening ratio factor and the real-time monitored rate of change of pressure inside the tank, the compensation coefficient for the opening and closing action of the sealing valve during dynamic adjustment is determined.

[0098] The control execution command is co-encoded by the opening and closing action compensation coefficient and the cycle start threshold to generate a control signal for the graded opening and closing of the sealing valve.

[0099] In practical implementation, firstly, based on the full-cycle verification data of over 100 batches of chopped chili fermentation and the general specifications for food-grade electric valve control, a graded control rule matching each fermentation stage is established within the chopped chili fermentation jar. Within this graded control rule, a unique corresponding sealing valve opening ratio factor and immersion water circulation start threshold are bound to each stable operating gradient value interval. The currently determined stable operating gradient value is compared one by one with the interval thresholds within the rule to determine the interval to which the stable operating gradient belongs, and the corresponding sealing valve opening ratio factor and immersion water circulation start threshold are extracted. Then, using a food-grade pressure sensor installed at the headspace of the chopped chili fermentation jar, headspace pressure data is collected in real time at a preset sampling frequency. Using the first-order difference method, the ratio of the pressure difference between the current moment and the previous sampling moment to the time interval is calculated to obtain the real-time monitored pressure change rate within the jar. Based on a feedforward compensation algorithm, the opening ratio factor and pressure change rate are coupled for calculation to obtain the correction value for the valve opening and closing speed and amplitude. After standardization, the opening and closing action compensation coefficient of the sealing valve during dynamic adjustment is determined. Finally, based on binary encoding rules, the valve opening ratio factor, corrected by the opening and closing action compensation coefficient, is first converted into the valve control execution code corresponding to the opening degree. Then, the starting threshold of the soaking tank water circulation is compared with the current turbidity data of the soaking tank water to generate the linkage execution code for water circulation start and stop. The two sets of execution codes are integrated collaboratively, and the execution timing and action priority parameters are supplemented to form a control execution command. This command is then converted by the digital output module of the controller to generate a control signal for the graded opening and closing of the sealing valve.

[0100] It should be noted that, in this application, the fermentation jar sealing valve refers to a food-grade electric control valve installed at the headspace of the fermentation jar opening; the graded control rule refers to the control rule for adjusting the stability of the fermentation environment; the opening ratio factor refers to the execution coefficient that quantifies the ratio of the opening flow area of ​​the sealing valve to the total flow area of ​​the valve opening; the immersion water circulation start threshold refers to the critical judgment value that triggers the immersion water circulation replacement operation; the pressure change rate inside the jar refers to the quantitative index of the change amplitude and direction of the headspace pressure inside the fermentation jar per unit time; the opening and closing action compensation coefficient refers to the quantitative correction coefficient used to correct the execution amplitude and execution speed of the opening and closing action of the sealing valve; the control execution command refers to the standardized set of commands used to drive the electric actuator of the sealing valve and the immersion water circulation system; and the graded opening and closing control signal refers to the drive electrical signal that matches the current stable operating gradient of the fermentation environment.

[0101] In practice, the water circulation and replacement in the fermentation jar can be achieved in the following way: Based on the anaerobic sealing and protection principle of the water seal tank of the chopped pepper fermentation jar, the water circulation and replacement can be achieved through a food-grade closed-loop pipeline system. After receiving the start command, the system first opens the electric ball valve at the drain outlet of the water seal tank, starts the miniature food-grade centrifugal pump to discharge all the original water in the tank into the wastewater collection tank, and closes the drain valve after the drainage is completed; then, it opens the electric ball valve at the inlet to inject sterile clean water that meets food hygiene requirements into the tank to the rated water seal level, closes the inlet valve and the pump body, and completes a single circulation replacement. There is no risk of external pollutants entering the tank throughout the process.

[0102] In this embodiment, reference Figure 4 As shown in the figure, this is a schematic diagram of the normalized change curve of the colony count of dominant lactic acid bacteria during the anaerobic fermentation of chopped chili peppers. The horizontal axis represents fermentation time, and the vertical axis represents the normalized amplitude of the colony count. The initial adaptation period corresponds to the pre-fermentation period of this application, during which lactic acid bacteria complete environmental activation and colonization, and the colony count increases slowly at a low amplitude. The rapid growth period corresponds to the main fermentation period, during which lactic acid bacteria enter the logarithmic proliferation stage, rapidly forming an absolute dominance of the microbial community, and simultaneously completing lactic acid accumulation and inhibition of other microorganisms. The stable period corresponds to the post-ripening period, during which the colony count remains at a steady state, ensuring the stability of the fermentation system and the transformation of flavor substances.

[0103] Therefore, in this application, the opening and closing ratio of the sealing valve of the fermentation port of chopped pepper is controlled according to the stable operation gradient gradation, and the soaking water circulation and replacement are started. Among them, the balanced control strategy in the fermentation stage can obtain a standardized environmental control execution benchmark that is adapted to the microbial metabolic characteristics of each stage of the entire fermentation cycle of chopped pepper, and takes into account the progress of fermentation and the prevention and control of abnormal risks. This achieves the precise matching of fermentation environmental control parameters with the metabolic laws of dominant lactic acid bacteria in each fermentation stage, breaks the inherent limitation of the disconnect between traditional fixed parameter control and dynamic fermentation process, integrates the prevention and control of fermentation abnormal risks into the control logic in advance, achieves a two-way balance between fermentation efficiency and safety control, provides a staged unified execution standard for the whole cycle closed-loop control, and effectively reduces the batch-to-batch quality deviation caused by human experience intervention. By determining the stable operating gradient of the fermentation environment, a graded control execution level can be obtained that precisely matches the real-time stable state and microbial metabolic safety boundary of the chopped chili fermentation system. This enables dynamic linkage between the fermentation terminal execution actions and the real-time state of the fermentation environment, breaking the inherent limitations of the traditional one-size-fits-all control mode. It incorporates fluctuations in the environmental parameters inside the jar and changes in the water seal status into the graded control logic, providing an unambiguous standardized execution basis for graded control of the sealing valve and replacement of the soaking water. This achieves closed-loop coordination of dynamic regulation, effectively avoiding fluctuations in the fermentation state caused by insufficient or excessive control, and ensuring the stability of the entire fermentation process.

[0104] In summary, the technical solution adopted in this application can achieve precise sensing and control of the entire fermentation cycle of chopped chili peppers, thereby improving the standardization level of the fermentation process.

[0105] Example 2: This application provides an intelligent status control system for a chopped chili fermentation jar, referencing... Figure 5 As shown in the figure, this is a modular structure diagram of an intelligent state control system for a chopped chili fermentation jar according to this embodiment of the present application. The control system includes:

[0106] The data acquisition module 100 is used to collect fermentation status data of at least two different height layers inside the chopped chili fermentation jar.

[0107] The fusion module 200 is used to determine the temperature control amount of the chopped pepper fermentation jar in the current fermentation stage based on the fermentation state data of each height layer, and to fuse all the temperature control amounts with the fermentation anomaly confidence interval in the corresponding fermentation stage to obtain the balance control strategy of the fermentation environment of the chopped pepper fermentation jar in the corresponding fermentation stage.

[0108] The control switching module 300 is used to collect dynamic turbidity data of the soaking water in the fermentation jar of chopped peppers in real time, dynamically switch the balance control strategy in the current fermentation stage according to the dynamic turbidity data, generate environmental adaptation characteristics of the fermentation state in the current fermentation stage of chopped peppers, and then determine the stable operation gradient of the fermentation environment in the current fermentation stage according to the environmental adaptation characteristics.

[0109] The status control module 400 is used to control the opening and closing ratio of the sealing valve of the fermentation port of chopped pepper according to the stable operation gradient, and to start the circulation and replacement of the soaking water.

[0110] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0111] Those skilled in the art will understand that all or part of the steps in the various methods of the above embodiments can be implemented by a program instructing related hardware. The program can be stored in a computer-readable storage medium, including read-only memory (ROM), random access memory (RAM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), one-time programmable read-only memory (OTPROM), electrically-Erasable Programmable Read-Only Memory (EEPROM), compactdisc read-only memory (CD-ROM) or other optical disc storage, disk storage, magnetic tape storage, or any other computer-readable medium capable of carrying or storing data.

[0112] It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

Claims

1. A method for intelligently controlling the state of a chopped chili fermentation jar, characterized in that, The control method includes the following steps: Collect fermentation status data from at least two different height layers inside the chopped chili fermentation jar; Based on the fermentation state data of each height layer, the temperature control amount of the chopped pepper fermentation jar in the current fermentation stage is determined. All temperature control amounts are then integrated with the fermentation anomaly confidence interval in the corresponding fermentation stage to obtain the balance control strategy of the fermentation environment of the chopped pepper fermentation jar in the corresponding fermentation stage. Specifically, by integrating all temperature control parameters with the fermentation anomaly confidence intervals in the corresponding fermentation stages, the balance control strategy for the fermentation environment of the chopped chili fermentation jar at the corresponding fermentation stages includes: The temperature regulation values ​​of each height layer are spatiotemporally registered with the historical fermentation anomaly confidence intervals of the corresponding fermentation stages to obtain the initial regulation feature set before fusion. The initial regulatory feature set is fused with the real-time monitored fermentation anomaly confidence interval to obtain the regulatory confidence correlation matrix; Based on the weights of the abnormal confidence in the regulation confidence correlation matrix, the temperature regulation amount is dynamically compensated to generate a phased temperature compensation regulation index during the fermentation stage. Based on the temperature compensation control index and the humidity control requirements of the chopped chili fermentation jar, a balance control strategy for the fermentation environment of the chopped chili fermentation jar in the corresponding fermentation stage is determined. The dynamic turbidity data of the soaking water in the fermentation jar of chopped peppers is collected in real time. The balance control strategy in the current fermentation stage is dynamically switched according to the dynamic turbidity data, and the environmental adaptation characteristics of the fermentation state in the current fermentation stage of chopped peppers are generated. Then, the stable operation gradient of the fermentation environment in the current fermentation stage is determined according to the environmental adaptation characteristics. Based on the stable operation gradient, the opening and closing ratio of the sealing valve of the fermentation port of the chopped pepper is controlled, and the water circulation of the soaking jar is started for replacement.

2. The intelligent state control method for a chopped chili fermentation jar as described in claim 1, characterized in that, Based on the fermentation status data at each depth level, the specific temperature control parameters for the chopped chili fermentation jar at the current fermentation stage are determined as follows: The fermentation characteristic parameter set of the chopped chili fermentation jar at the current fermentation stage is determined based on the fermentation status data of each height layer; By matching the set of fermentation characteristic parameters with the temperature requirements of the preset fermentation stage, the temperature regulation requirement gradient in the current fermentation stage is determined. The temperature control amount in the chopped chili fermentation jar during the current fermentation stage is determined based on the temperature control requirement gradient and the real-time fermentation temperature feedback value.

3. The intelligent state control method for a chopped chili fermentation jar as described in claim 1, characterized in that, The fermentation stages are pre-fermentation, main fermentation, and post-fermentation.

4. The intelligent state control method for a chopped chili fermentation jar as described in claim 1, characterized in that, The real-time collection of dynamic turbidity data of the soaking water from the chopped chili fermentation jar specifically includes: Based on the light scattering characteristics and real-time transmitted light intensity of the soaking water in the fermentation jar for chopped chili peppers, an optical feature vector of dynamic turbidity is constructed. The dynamic turbidity change gradient at the current moment is determined by the optical feature vector and the temperature compensation coefficient of the soaking water. Extract the turbidity data acquisition trigger rules that meet the preset sampling period from the dynamic turbidity change gradient to obtain the dynamic turbidity data of the soaking water in the chopped pepper fermentation jar.

5. The intelligent state control method for a chopped chili fermentation jar as described in claim 1, characterized in that, Based on the dynamic turbidity data, the balance control strategy in the current fermentation stage is dynamically switched, and the environmental adaptation characteristics of the fermentation state in the current chopped chili fermentation stage are generated, specifically including: Based on the time-series fluctuation information of the dynamic turbidity data and the expected turbidity benchmark at the current fermentation stage, a turbidity deviation index is determined. The turbidity deviation index is matched with the preset fermentation state switching rules to determine the current balance control strategy identifier that needs to be switched. Environmental control factors are extracted from the set of control parameters corresponding to the balance control strategy identifier to generate environmental adaptation features of the fermentation state in the current chopped chili fermentation stage.

6. The intelligent state control method for a chopped chili fermentation jar as described in claim 1, characterized in that, The fermentation state described refers to the state of the anaerobic fermentation system for chopped chili peppers during the corresponding fermentation stage, including the metabolic process of beneficial bacteria, the physicochemical properties of the substances, the stability of the anaerobic environment inside the jar, and the reliability of the water seal.

7. The intelligent state control method for a chopped chili fermentation jar as described in claim 1, characterized in that, Determining the stable operating gradient of the fermentation environment in the current fermentation stage based on the aforementioned environmental adaptation characteristics specifically includes: The initial stable operating gradient of the fermentation environment is determined based on the temporal fluctuation range of temperature and humidity in the environmental adaptation characteristics. Based on the initial stable operating gradient and the boundary conditions of microbial metabolic activity in the current fermentation stage, the dynamic constraint range of fermentation environment fluctuations is determined. The dynamic control target in the environmental adaptation feature is mapped by the dynamic constraint range to generate the dynamic adjustment amount corresponding to each fermentation environment. By weighting and integrating all dynamic adjustment values ​​with the historical inertia coefficient of the fermentation tank environment, the stable operating gradient of the fermentation environment in the current fermentation stage is obtained.

8. The intelligent state control method for a chopped chili fermentation jar as described in claim 1, characterized in that, The opening and closing ratio of the sealing valve at the fermentation port of the chopped chili pepper, based on the aforementioned stable operation gradient grading control, specifically includes: Based on the numerical range of the stable operating gradient and the graded control rules in the chopped pepper fermentation jar, the opening ratio factor of the sealing valve and the starting threshold of the soaking water circulation are extracted. Based on the opening ratio factor and the real-time monitored rate of change of pressure inside the tank, the compensation coefficient for the opening and closing action of the sealing valve during dynamic adjustment is determined. The control execution command is co-encoded by the opening and closing action compensation coefficient and the cycle start threshold to generate a control signal for the graded opening and closing of the sealing valve.

9. An intelligent state control system for a chopped chili fermentation jar, used to execute the intelligent state control method for a chopped chili fermentation jar as described in any one of claims 1 to 8, characterized in that, The control system includes: The data acquisition module is used to collect fermentation status data at least two different height layers inside the chopped chili fermentation jar; The fusion module is used to determine the temperature control amount of the chopped pepper fermentation jar in the current fermentation stage based on the fermentation state data of each height layer, and to fuse all the temperature control amounts with the fermentation anomaly confidence interval in the corresponding fermentation stage to obtain the balance control strategy of the fermentation environment of the chopped pepper fermentation jar in the corresponding fermentation stage. Specifically, by integrating all temperature control parameters with the fermentation anomaly confidence intervals in the corresponding fermentation stages, the balance control strategy for the fermentation environment of the chopped chili fermentation jar at the corresponding fermentation stages includes: The temperature regulation values ​​of each height layer are spatiotemporally registered with the historical fermentation anomaly confidence intervals of the corresponding fermentation stages to obtain the initial regulation feature set before fusion. The initial regulatory feature set is fused with the real-time monitored fermentation anomaly confidence interval to obtain the regulatory confidence correlation matrix; Based on the weights of the abnormal confidence in the regulation confidence correlation matrix, the temperature regulation amount is dynamically compensated to generate a phased temperature compensation regulation index during the fermentation stage. Based on the temperature compensation control index and the humidity control requirements of the chopped chili fermentation jar, a balance control strategy for the fermentation environment of the chopped chili fermentation jar in the corresponding fermentation stage is determined. The control switching module is used to collect dynamic turbidity data of the soaking water in the fermentation jar of chopped peppers in real time, and dynamically switch the balance control strategy in the current fermentation stage according to the dynamic turbidity data, generate environmental adaptation characteristics of the fermentation state in the current fermentation stage of chopped peppers, and then determine the stable operation gradient of the fermentation environment in the current fermentation stage according to the environmental adaptation characteristics. The status control module is used to control the opening and closing ratio of the sealing valve of the fermentation port of chopped pepper according to the stable operation gradient, and to start the circulation and replacement of the soaking water.

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