Optimization control method and system for beer fermentation

Abstract

The invention discloses an optimal control method and system for beer fermentation, and relates to the technical field of beer fermentation, and the method specifically comprises the following steps: obtaining the gas exchange information of each region at the top of a fermentation tank in real time, analyzing the information after obtaining, predicting the obstruction degree of a bubble layer formed in each region at the top of the fermentation tank to oxygen, and determining whether the oxygen is obstructed or not; dividing each area at the top of the fermentation tank into a high-barrier area, a medium-barrier area and a low-barrier area according to the prediction result; on the basis of the division result of each region, constructing a bubble suppression and oxygen regulation mechanism, and respectively carrying out different oxygen supply and bubble dissipation regulation on the high-barrier region, the medium-barrier region and the low-barrier region; and in the process of adjusting each region by a bubble suppression and oxygen adjustment mechanism, acquiring gas exchange feedback information of each region in real time, and analyzing the acquired gas exchange feedback information. The problem that a bubble layer hinders oxygen penetration is solved, the fermentation efficiency is improved, and the beer quality is guaranteed.

Description

Technical Field

[0001] The invention relates to the technical field of beer fermentation, and in particular to an optimization control method and system for beer fermentation. Background Art

[0002] Beer fermentation refers to the biochemical process of converting sugars in wort into alcohol and carbon dioxide through yeast. This process directly affects the key qualities of beer, such as flavor, alcohol content, and taste. Since the fermentation process is affected by multiple variables such as temperature, pH value, oxygen concentration, and sugar content, a slight change in any parameter may lead to unstable fermentation results, which in turn affects the final quality of the beer. Therefore, it is very important to optimize and control beer fermentation. By real-time monitoring of key parameters in the fermentation tank, analyzing and predicting the fermentation state, and automatically adjusting conditions such as temperature and oxygen supply, the stability and consistency of the fermentation process can be ensured. At the same time, optimized control can also improve the metabolic efficiency of yeast, shorten fermentation time, and reduce energy and raw material consumption, thereby improving production efficiency and product quality, and ultimately meeting the market demand for high-quality beer.

[0003] Existing optimization control technologies for beer fermentation mainly achieve precise management of the fermentation process through automation systems and advanced sensor networks. First, sensors collect key parameters in the fermentation tank in real time, such as temperature, pH value, dissolved oxygen, sugar content and pressure, and input these data into the central control system. The control system uses built-in prediction models and historical data to analyze the current fermentation status and generate trend forecasts and risk assessment reports. Next, the system calculates fermentation control parameters such as temperature control coefficient and oxygen supply coefficient based on these analysis results, and automatically adjusts the temperature, oxygen supply and stirring speed of the fermentation tank to keep the fermentation conditions within the optimal range. This real-time dynamic adjustment can not only ensure the optimal activity and metabolic rate of yeast, but also prevent problems such as excessive heating or insufficient oxygen during the fermentation process. Finally, the system continuously optimizes the control algorithm by evaluating the overall effect of fermentation, ensuring the consistency of fermentation, reducing fermentation time and energy consumption, thereby significantly improving the production efficiency and product quality of beer.

[0004] The prior art has the following deficiencies: During the fermentation of high-concentration wort, especially when the fermentation temperature is low and the wort contains a large amount of protein and other surfactants, these substances will cause the surface tension of the fermentation liquid to increase significantly, and then form a thick and difficult-to-dissipate bubble layer on the top of the fermenter. Due to the aggregation effect of these bubbles, oxygen cannot effectively penetrate the bubble layer into the fermentation liquid, thereby hindering the normal exchange of oxygen and the fermentation liquid. In the center or upper area of ​​the fermenter, the oxygen supply that yeast relies on is severely reduced, resulting in a decrease in the yeast metabolism rate in the local area, affecting the fermentation start-up efficiency. The existing optimization control technology relies on the detection of the full tank sensor, but the sensor is installed in the center of the tank and fails to sense the gas exchange obstruction caused by the accumulation of bubbles on the top of the fermentation liquid in real time. Since the data fed back by the sensor cannot identify the uneven oxygen supply problem, the system continues to operate in the normal oxygen supply mode, resulting in oxygen shortage not being corrected in time. This local phenomenon of insufficient oxygen supply will reduce the overall fermentation efficiency and weaken the yeast activity. At the same time, excessive accumulation of carbon dioxide in the fermenter will increase the pressure in the tank and produce too many by-products such as higher alcohols, which will not only prolong the fermentation time, but also significantly affect the flavor and taste of the beer, increase production costs, and may cause the quality of the entire batch of products to be unqualified.

[0005] The above information disclosed in this Background section is only for enhancement of understanding of the background of the present disclosure and therefore it may contain information that does not constitute the prior art that is already known to one of ordinary skill in the art. Summary of the invention

[0006] The object of the present invention is to provide an optimization control method and system for beer fermentation to solve the problems in the above-mentioned background technology.

[0007] In order to achieve the above object, the present invention provides the following technical solution: an optimization control method for beer fermentation, specifically comprising the following steps: During the fermentation of high-concentration wort, the top of the fermentation tank is evenly divided into several areas, and the fermentation liquid is evenly distributed in each area. A sensor network is deployed in each area to obtain gas exchange information in real time. The gas exchange information of each area on the top of the fermenter is obtained in real time, and analyzed after acquisition to predict the degree of oxygen obstruction of the bubble layer formed in each area on the top of the fermenter, and the areas on the top of the fermenter are divided into high-barrier area, medium-barrier area and low-barrier area according to the prediction results; Based on the division results of each area, a bubble suppression and oxygen regulation mechanism is constructed to make different oxygen supply and bubble dissipation adjustments for high barrier area, medium barrier area and low barrier area respectively; In the process of adjusting each area by the bubble suppression and oxygen regulation mechanism, the gas exchange feedback information of each area is obtained in real time, and analyzed after acquisition to evaluate whether the adjustment effect of the mechanism in each area can meet the requirements of oxygen penetrating the bubble layer and exchanging with the fermentation liquid normally, and the adjustment mechanism is optimized according to the evaluation results; The gas exchange data, adjustment records and fermentation effects during the entire fermentation process are recorded and comprehensively analyzed in real time, the oxygen supply and bubble suppression strategies are continuously improved, and the adjustment mechanism is improved in real time.

[0008] Preferably, the gas exchange information of each area on the top of the fermenter is obtained in real time, and analyzed after acquisition to predict the degree of oxygen obstruction of the bubble layer formed in each area on the top of the fermenter, and the areas on the top of the fermenter are divided into high barrier areas, medium barrier areas and low barrier areas according to the prediction results, which specifically includes the following steps: Obtain gas exchange information in various areas of the top of the fermenter in real time and perform preprocessing after acquisition; Extracting the bubble obstruction information and the oxygen exchange information from the gas exchange information of each area on the top of the pretreated fermenter, and analyzing them after extraction to generate the bubble coverage factor and the oxygen exchange index of each area on the top of the fermenter respectively; The bubble coverage coefficient and oxygen exchange index of each area on the top of the fermenter are used to construct an obstacle prediction model, and the obstacle coefficient of each area on the top of the fermenter is generated. The generated obstacle coefficient of each area on the top of the fermenter is compared with the preset obstacle coefficient threshold range. The obstacle degree of oxygen formed by the bubble layer in each area on the top of the fermenter is predicted according to the comparison result, and the various areas on the top of the fermenter are divided into high barrier area, medium barrier area and low barrier area according to the prediction result.

[0009] Preferably, the logic for obtaining the bubble coverage factor and oxygen exchange index of each area on the top of the fermenter is as follows: The bubble barrier information in the gas exchange information of each area on the top of the pretreated fermenter was extracted, including the average thickness of the bubble layer, the surface area coverage of the bubble layer, the oxygen permeability, the bubble layer density and the average air pressure of each area on the top of the fermenter at different times within a period of time, and calibrated as , , , and , Indicates the top of the fermentation tank area within a period of time The average thickness of the bubble layer at the time, Indicates the top of the fermentation tank area within a period of time The surface area coverage of the bubble layer at the moment, Indicates the top of the fermentation tank area within a period of time The oxygen permeability at the moment, Indicates the top of the fermentation tank area within a period of time The density of the bubble layer at the moment, Indicates the top of the fermentation tank area within a period of time The average air pressure at the time, , , and are all positive integers; Calculate the bubble coverage factor of each area on the top of the fermentation tank. The specific calculation formula is as follows: In the formula, The top of the fermenter The bubble coverage factor of each area; The oxygen exchange information in the gas exchange information of each area on the top of the pretreated fermenter is extracted, including the oxygen concentration, gas exchange rate, oxygen demand, carbon dioxide concentration and temperature change rate of each area on the top of the fermenter at different times over a period of time, and calibrated as , , , and , Indicates the top of the fermentation tank area within a period of time The oxygen concentration at the time, Indicates the top of the fermentation tank area within a period of time The gas exchange rate at each moment, Indicates the top of the fermentation tank area within a period of time Oxygen demand at any time, Indicates the top of the fermentation tank area within a period of time The carbon dioxide concentration at the time, Indicates the top of the fermentation tank area within a period of time The temperature change rate at each moment; Calculate the oxygen exchange index of each area on the top of the fermenter. The specific calculation formula is as follows: In the formula, The top of the fermenter Oxygen exchange index of a region.

[0010] Preferably, the bubble coverage factor of each area on the top of the fermenter is generated and oxygen exchange index Construct an obstacle prediction model and generate the obstacle coefficients of each area on the top of the fermenter by weighted summation , and the resulting resistance coefficients of each area on the top of the fermenter The threshold interval of the obstacle coefficient is set in advance The comparison is carried out, and the degree of oxygen obstruction of the bubble layer formed in each area on the top of the fermentation tank is predicted according to the comparison results. According to the prediction results, each area on the top of the fermentation tank is divided into a high barrier area, a medium barrier area and a low barrier area. The specific comparison analysis and division process is as follows: like , the bubble layer formed in this area has a low barrier to oxygen, so this area is divided into a low barrier area; like , the bubble layer formed in this area has a medium degree of barrier to oxygen, so this area is divided into a medium barrier area; like , the bubble layer formed in this area has a high barrier degree to oxygen, so this area is divided into a high barrier area.

[0011] Preferably, based on the division results of each area, a bubble suppression and oxygen adjustment mechanism is constructed, specifically including: according to the division results of the high barrier area, the medium barrier area and the low barrier area, different oxygen supply and bubble dissipation parameters are set respectively to form a bubble suppression and oxygen adjustment mechanism; the adjustment mechanism is based on the obstruction coefficient of each area and the current oxygen exchange state, and the adjustment range and method of the oxygen supply and bubble dissipation are automatically determined by pre-set rules; Different oxygen supply and bubble dissipation adjustments are made to the high barrier zone, medium barrier zone and low barrier zone respectively, specifically including: in the high barrier zone, high oxygen supply parameters in the adjustment mechanism are used, and the stirring intensity is increased to accelerate the dissipation of the bubble layer; in the medium barrier zone, the standard oxygen supply parameters in the adjustment mechanism are maintained to maintain the current oxygen supply and bubble dissipation rate; in the low barrier zone, low oxygen supply parameters in the adjustment mechanism are used to reduce the oxygen supply and reduce the stirring intensity for the dissipation of the bubble layer.

[0012] Preferably, in the process of adjusting each area by the bubble suppression and oxygen regulation mechanism, the gas exchange feedback information of each area is obtained in real time, and analyzed after acquisition to evaluate whether the adjustment effect of the mechanism in each area can meet the requirements of oxygen penetrating the bubble layer and exchanging with the fermentation liquid normally, and the adjustment mechanism is optimized according to the evaluation results, which specifically includes the following steps: In the process of adjusting each area by bubble suppression and oxygen regulation mechanism, gas exchange feedback information of each area is obtained in real time and pre-processed after acquisition; Extracting oxygen exchange dynamic information and oxygen penetration resistance dynamic information from the pre-processed gas exchange feedback information of each region, and analyzing them after extraction to generate gas exchange efficiency variation coefficient and oxygen penetration resistance variation coefficient of each region respectively; The generated gas exchange efficiency variation coefficient and oxygen penetration resistance variation coefficient of each area are used to construct an adjustment effect evaluation model to generate an adjustment coefficient for each area. The generated adjustment coefficient for each area is compared with a preset adjustment coefficient threshold. Based on the comparison results, it is evaluated whether the adjustment effect of the mechanism in each area can meet the requirements of oxygen penetrating the bubble layer and exchanging normally with the fermentation liquid, and the adjustment mechanism is optimized based on the evaluation results.

[0013] Preferably, the logic for obtaining the gas exchange efficiency variation coefficient and the oxygen penetration resistance variation coefficient of each region is as follows: Extract the oxygen exchange dynamic information from the gas exchange feedback information of each area after preprocessing, specifically including the oxygen exchange rate, bubble layer thickness, oxygen permeability and corresponding time points at different times during a period of time in the process of bubble suppression and oxygen regulation mechanism adjusting each area, and use function to calculate the oxygen exchange rate, bubble layer thickness and oxygen permeability at different times during a period of time in the process of bubble suppression and oxygen regulation mechanism adjusting each area according to the time series. , and To express, For time point, Indicates the role of bubble suppression and oxygen regulation mechanisms in During the period of adjustment of the region The oxygen exchange rate at each moment, Indicates the role of bubble suppression and oxygen regulation mechanisms in During the period of adjustment of the region The thickness of the bubble layer at the time, Indicates the role of bubble suppression and oxygen regulation mechanisms in During the period of adjustment of the region The oxygen permeability at the moment, , is a positive integer, defining the time period as ; Calculate the coefficient of variation of gas exchange efficiency in each area. The specific calculation formula is as follows: In the formula, For the The coefficient of variation of gas exchange efficiency in each region is Indicates the rate of change of oxygen exchange rate, represents the change rate of the bubble layer thickness, Indicates the rate of change of oxygen permeability; Extract the dynamic information of oxygen penetration resistance from the gas exchange feedback information of each area after preprocessing, specifically including the oxygen concentration, carbon dioxide concentration, bubble layer density and corresponding time points at different times during a period of time when the bubble suppression and oxygen regulation mechanism adjusts each area, and use the function to calculate the oxygen concentration, carbon dioxide concentration and bubble layer density at different times during a period of time when the bubble suppression and oxygen regulation mechanism adjusts each area according to the time series. , and To express, Indicates the role of bubble suppression and oxygen regulation mechanisms in During the period of adjustment of the region The oxygen concentration at the time, Indicates the role of bubble suppression and oxygen regulation mechanisms in During the period of adjustment of the region The carbon dioxide concentration at the time, Indicates the role of bubble suppression and oxygen regulation mechanisms in During the period of adjustment of the region The density of the bubble layer at the moment, is a time point, and the time period is defined as ; Calculate the oxygen penetration resistance variation coefficient of each area. The specific calculation formula is as follows: In the formula, For the The oxygen penetration resistance variation coefficient of each region is represents the rate of change of oxygen concentration, represents the rate of change of carbon dioxide concentration, Indicates the rate of change of the bubble layer density.

[0014] Preferably, the gas exchange efficiency variation coefficient of each region is generated and oxygen penetration resistance variation coefficient Construct an adjustment effect evaluation model and generate adjustment coefficients for each region through weighted summation , the adjustment coefficients for each region generated With the preset adjustment factor threshold Compare and evaluate whether the adjustment effect of the mechanism in each area can meet the requirements of oxygen penetrating the bubble layer and exchanging with the fermentation liquid normally according to the comparison results, and optimize the adjustment mechanism according to the evaluation results. The specific comparison analysis is as follows: like , the adjustment effect of the bubble suppression and oxygen regulation mechanism in this area cannot meet the requirements of oxygen penetrating the bubble layer and exchanging with the fermentation liquid normally. The adjustment mechanism needs to be optimized, including increasing the oxygen supply, increasing the stirring intensity and extending the adjustment time; like , the adjustment effect of the bubble suppression and oxygen regulation mechanism in this area can meet the requirements of oxygen penetrating the bubble layer and exchanging normally with the fermentation liquid. There is no need to optimize the adjustment mechanism and maintain the current adjustment parameters.

[0015] Preferably, an optimization control system for beer fermentation includes a fermentation area division and sensor monitoring module, a gas exchange information prediction and analysis module, a bubble suppression and oxygen regulation optimization module, a feedback and adjustment optimization module, and a fermentation process comprehensive recording and strategy improvement module; The fermentation area division and sensor monitoring module divides the top of the fermentation tank into several areas evenly during the fermentation of high-concentration wort, and evenly distributes the fermentation liquid in each area. A sensor network is deployed in each area to obtain gas exchange information in real time. The gas exchange information prediction and analysis module obtains the gas exchange information of each area on the top of the fermenter in real time, analyzes it after acquisition, predicts the degree of oxygen obstruction of the bubble layer formed in each area on the top of the fermenter, and divides each area on the top of the fermenter into a high-barrier area, a medium-barrier area and a low-barrier area according to the prediction results; The bubble suppression and oxygen regulation optimization module builds a bubble suppression and oxygen regulation mechanism based on the division results of each area, and makes different oxygen supply and bubble dissipation adjustments for high barrier area, medium barrier area and low barrier area respectively; Feedback and adjustment optimization module, in the process of adjusting each area by the bubble suppression and oxygen regulation mechanism, obtains gas exchange feedback information of each area in real time, analyzes it after obtaining, evaluates whether the adjustment effect of the mechanism in each area can meet the requirements of oxygen penetrating the bubble layer and exchanging with the fermentation liquid normally, and optimizes the adjustment mechanism according to the evaluation results; The comprehensive record and strategy improvement module of the fermentation process records and conducts real-time and comprehensive analysis of the gas exchange data, adjustment records and fermentation effects during the entire fermentation process, continuously improves the oxygen supply and bubble suppression strategies, and improves the adjustment mechanism in real time.

[0016] In the above technical solution, the technical effects and advantages provided by the present invention are: 1. The present invention realizes accurate identification and prediction of bubble obstruction in different areas by accurately dividing the top area of ​​the fermentation tank and acquiring real-time gas exchange information. By arranging sensor networks in different areas, the system can obtain gas exchange data at the top of the fermentation tank in real time and predict the degree of oxygen obstruction by the bubble layer based on the data. This solves the problem in the prior art that the full tank sensor cannot perceive the obstruction of the top bubble layer, and greatly improves the ability to identify insufficient oxygen supply.

[0017] 2. The present invention constructs a bubble suppression and oxygen regulation mechanism to make differential adjustments to the high barrier area, medium barrier area and low barrier area. Based on the real-time data fed back by the sensor, the system can dynamically adjust the oxygen supply and bubble dissipation measures in each area to ensure that oxygen can penetrate the bubble layer and exchange normally with the fermentation liquid. This mechanism can provide different control strategies according to the degree of obstruction in different areas, significantly improve the overall efficiency of the fermentation process, and avoid the phenomenon of insufficient local oxygen supply.

[0018] 3. By recording the gas exchange data and adjustment records during the fermentation process, the system can continuously optimize the bubble suppression and oxygen regulation strategies and dynamically improve the adjustment mechanism. The advantage of the present invention is that it can not only provide flexible adjustment measures in real-time control, but also has the ability of self-learning and self-optimization, ensuring that the system can adapt to the changes in bubble obstruction and oxygen demand during the fermentation process, thereby maximizing the activity and fermentation efficiency of yeast, reducing the production of by-products, and improving the flavor and quality of beer. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present invention. For ordinary technicians in this field, other drawings can also be obtained based on these drawings.

[0020] Figure 1 The present invention is a schematic flow chart of an optimization control method and system for beer fermentation.

[0021] Figure 2 The module diagram of an optimization control method and system for beer fermentation of the present invention is shown in FIG. DETAILED DESCRIPTION

[0022] Example embodiments will now be described more fully with reference to the accompanying drawings. However, example embodiments can be implemented in a variety of forms and should not be construed as limited to the examples set forth herein; rather, these example embodiments are provided so that the description of the present disclosure will be more comprehensive and complete, and the concept of the example embodiments will be fully conveyed to those skilled in the art.

[0023] The present invention provides Figure 1 The optimization control method for beer fermentation shown in the figure specifically comprises the following steps: During the fermentation of high-concentration wort, the top of the fermentation tank is evenly divided into several areas, and the fermentation liquid is evenly distributed in each area. A sensor network is deployed in each area to obtain gas exchange information in real time. The division of the top of the fermentation tank into several areas can be achieved by establishing a three-dimensional virtual model. Specifically, a software algorithm is used to divide several equally spaced grid areas according to the shape, diameter and top area of ​​the fermentation tank. First, the system inputs the geometric parameters of the fermentation tank, such as the radius, height and top curvature of the tank body, to generate a three-dimensional fermentation tank model. Then, in the model, the top of the fermentation tank is evenly divided into several equal areas using the equidistant segmentation method with the tank top as the reference plane. These areas can be rectangular, square or hexagonal shapes to ensure that the area of ​​each area is distributed as evenly as possible. The division criteria can be adjusted according to the size of the tank body, and the optimal division scheme can be dynamically generated by setting the maximum side length and minimum area of ​​each area. The algorithm can take into account the boundary effect and central part of the tank body, so that the size of each area is balanced, thereby ensuring the coverage of gas exchange and the representativeness of data collection. After the division is completed, the system assigns an independent number to each area to facilitate subsequent sensor deployment and data association analysis.

[0024] In order to make the fermentation liquid evenly distributed in each divided area, the system can achieve this by intelligently controlling the stirring device in the fermentation tank. The fermentation tank is usually equipped with a stirrer. The software system will dynamically adjust the speed, direction and operation mode of the stirrer according to the real-time feedback of the liquid flow rate, liquid level and density data. First, the system collects the liquid level information of different depths and areas in the fermentation tank to analyze whether the fermentation liquid is unevenly distributed. If it is detected that the liquid is unevenly distributed in some areas, the software will instruct the stirrer to increase the speed or adjust the stirring mode to increase the fluidity of the fermentation liquid in the entire tank and ensure that the liquid can flow effectively between the areas. In addition, the angle and stirring force of the stirring blade can also be automatically controlled by the system to adapt to the viscosity changes of the fermentation liquid. For example, during the fermentation process of high-concentration wort, the viscosity of the fermentation liquid is high. The system can instruct the stirrer to run at a higher power to enhance the liquid flow, so that the fermentation liquid flow rate and liquid level in each area are balanced to avoid liquid accumulation or vacancy in local areas. The real-time monitored flow data will be continuously transmitted to the system. According to the feedback results, the system automatically adjusts the stirring strategy to ensure the uniform distribution of the fermentation liquid in each area.

[0025] When deploying the sensor network, the system will simulate the layout and coverage of each sensor through software according to the results of the regional division to ensure that the gas exchange information of each area can be accurately collected. First, the software system will input the physical parameters of the sensor (such as detection range, response time, accuracy, etc.), and calculate the number of sensors required for each area and the optimal layout location according to the area and shape of each area. For each area, multiple sensors are usually deployed, including oxygen concentration sensors, carbon dioxide concentration sensors, and pressure sensors. These sensors are connected to the central control system wirelessly or wired to transmit data in real time. The system will assign a unique identification number to each sensor and bind the area corresponding to each sensor to the area number of the fermentation tank to ensure the accuracy of data collection and analysis. Through the gas exchange information obtained in real time by the sensor network, the system can keep track of the oxygen supply, carbon dioxide emissions, and air pressure changes in each area at any time, so as to make timely adjustments to the overall dynamics of gas exchange during the fermentation process. In order to ensure the continuity and accuracy of the data, the system can set an automatic adjustment mechanism for the acquisition frequency, that is, when the gas exchange data in a certain area fluctuates greatly, the data acquisition frequency of the sensors in that area will be automatically increased to ensure that the problem can be quickly discovered and handled.

[0026] During the fermentation of high-concentration wort, since wort contains a large amount of protein and surfactant, these substances will increase the surface tension of the fermentation liquid, and then form a thick and difficult-to-dissipate bubble layer, especially in the top area of ​​the fermenter. This bubble layer will significantly hinder oxygen penetration, resulting in insufficient oxygen supply in local areas, which in turn affects the normal exchange of fermentation liquid and oxygen, and the metabolic rate of yeast is reduced, and the fermentation efficiency is inhibited. If only relying on the sensor in the center of the tank for monitoring, it is impossible to accurately monitor the thickness of the bubble layer and the oxygen exchange status in different areas of the top. Therefore, it is necessary to evenly divide the top of the fermenter and obtain gas exchange information in each area by deploying a sensor network. In this way, detailed monitoring of different areas on the top of the fermenter can be achieved, and the uniformity of oxygen supply and bubble obstruction can be grasped in real time. When the bubble layer causes serious obstruction to certain areas, the system can take targeted measures in time, such as increasing oxygen supply or accelerating the bubble dissipation rate. Through regional division and sensor monitoring, the problem of insufficient oxygen in local areas can be effectively solved, ensuring that oxygen is evenly distributed in various areas, improving fermentation efficiency, avoiding the problem of decreased yeast activity and excessive accumulation of carbon dioxide caused by the bubble layer, and ultimately ensuring the stability of the beer fermentation process and product quality.

[0027] The gas exchange information of each area on the top of the fermenter is obtained in real time, and analyzed after acquisition to predict the degree of oxygen obstruction of the bubble layer formed in each area on the top of the fermenter, and the areas on the top of the fermenter are divided into high-barrier area, medium-barrier area and low-barrier area according to the prediction results; In this embodiment, the gas exchange information of each area on the top of the fermenter is obtained in real time, and analyzed after acquisition to predict the degree of oxygen obstruction of the bubble layer formed in each area on the top of the fermenter, and the areas on the top of the fermenter are divided into high barrier areas, medium barrier areas and low barrier areas according to the prediction results, which specifically includes the following steps: Obtain gas exchange information in various areas of the top of the fermenter in real time and perform preprocessing after acquisition; Real-time acquisition of gas exchange information in each area on the top of the fermenter can be achieved through a multi-type sensor network deployed in different areas. Multiple sensors will be installed in each area, such as oxygen concentration sensors, carbon dioxide concentration sensors and pressure sensors. These sensors transmit the gas exchange data of each area to the central control system in real time through wireless transmission technology or wired connection. In order to ensure the timeliness and accuracy of the data, the system will set the time interval and frequency of data collection so that the sensors can collect and transmit information regularly. The gas exchange information specifically includes: oxygen concentration, carbon dioxide concentration, local pressure, temperature, bubble layer thickness and bubble layer coverage in each area. These data can reflect the oxygen supply and gas exchange efficiency in each area, and are the basis for subsequent analysis and regulation.

[0028] The purpose of preprocessing is to ensure that the collected gas exchange information has high accuracy and consistency when analyzed and calculated. Since sensors may be affected by environmental noise, data drift, or differences in sensor accuracy at different time points and regions, directly using unprocessed data may lead to incorrect predictions or inaccurate results. Preprocessing usually includes data cleaning, data smoothing, and data standardization. First, the system will filter out abnormal data points through software to exclude extreme data caused by sensor failure or environmental noise. Then, the data is smoothed using a moving average method or a filtering algorithm to eliminate errors caused by instantaneous fluctuations. Finally, the system standardizes the gas exchange data of each region to ensure that the dimensions of different regions and different types of data are consistent, which is convenient for subsequent analysis and comparison. Through these preprocessing steps, the quality and reliability of the data can be improved, thereby providing more stable input data for subsequent bubble layer obstruction analysis.

[0029] Extracting the bubble obstruction information and the oxygen exchange information from the gas exchange information of each area on the top of the pretreated fermenter, and analyzing them after extraction to generate the bubble coverage factor and the oxygen exchange index of each area on the top of the fermenter respectively; Extracting the bubble obstruction information and oxygen exchange information from the gas exchange information of each area on the top of the pretreated fermenter can be achieved by automatically parsing various types of data through the software system. First, the system will divide the pretreated gas exchange information into multiple data categories, such as oxygen concentration, carbon dioxide concentration, bubble layer thickness, bubble coverage, local pressure, temperature gradient, etc. For the bubble obstruction information, the system will extract parameters related to the bubble layer from these data, such as bubble layer thickness, bubble layer coverage, and local pressure. Through weighted analysis of these parameters, the system can generate a "bubble coverage coefficient" for each area. At the same time, for oxygen exchange information, the system will extract information such as oxygen concentration, carbon dioxide concentration, and local gas flow rate and temperature changes. The software integrates and calculates these extracted parameters through advanced data processing algorithms to generate an "oxygen exchange index" for each area. The system will ensure that the information extracted from each area is targeted and accurate based on the sensor locations and collected data sources in different areas.

[0030] The bubble coverage coefficient and oxygen exchange index of each area on the top of the fermenter are used to construct an obstacle prediction model, and the obstacle coefficient of each area on the top of the fermenter is generated. The generated obstacle coefficient of each area on the top of the fermenter is compared with the preset obstacle coefficient threshold range. The obstacle degree of oxygen formed by the bubble layer in each area on the top of the fermenter is predicted according to the comparison result, and the various areas on the top of the fermenter are divided into high barrier area, medium barrier area and low barrier area according to the prediction result.

[0031] Determining the "pre-set barrier coefficient threshold interval" can be achieved through a software system that combines historical data analysis, experimental verification, and dynamic optimization algorithms. First, the software will collect a large amount of historical fermentation data, including the barrier conditions of gas exchange during fermentation under different conditions (such as different fermentation temperatures, wort concentrations, bubble layer thickness, etc.) and the final fermentation effect. By statistically analyzing these data, the system can preliminarily define the barrier coefficient range corresponding to the different degrees of oxygen barrier of the bubble layer as the initial reference threshold interval. Then, the system uses the experimental verification mode to input different fermentation conditions for simulated fermentation, analyze the relationship between the bubble barrier coefficient and the oxygen exchange effect in real time, and gradually optimize the threshold range. The system will also dynamically adjust the upper and lower limits of the barrier coefficient based on real-time data feedback during the actual fermentation process to ensure that the barrier coefficient threshold interval can adapt to changes under different fermentation batches and conditions. In order to make the threshold more universal, the software will continue to learn historical data and real-time feedback through machine learning algorithms, so as to further refine and adjust the barrier coefficient threshold interval to ensure the accuracy and stability of the prediction results.

[0032] In this embodiment, the logic for obtaining the bubble coverage factor and oxygen exchange index of each area on the top of the fermentation tank is as follows: The bubble barrier information in the gas exchange information of each area on the top of the pretreated fermenter was extracted, including the average thickness of the bubble layer, the surface area coverage of the bubble layer, the oxygen permeability, the bubble layer density and the average air pressure of each area on the top of the fermenter at different times within a period of time, and calibrated as , , , and , Indicates the top of the fermentation tank area within a period of time The average thickness of the bubble layer at the time, Indicates the top of the fermentation tank area within a period of time The surface area coverage of the bubble layer at the moment, Indicates the top of the fermentation tank area within a period of time The oxygen permeability at the moment, Indicates the top of the fermentation tank area within a period of time The density of the bubble layer at the moment, Indicates the top of the fermentation tank area within a period of time The average air pressure at the time, , , and are all positive integers; Extracting bubble obstruction information from various areas on the top of the pretreated fermenter can be achieved by parsing and integrating sensor data through software. First, the system obtains relevant data from the sensor network deployed in various areas on the top of the fermenter. For example, the average thickness of the bubble layer can be measured in real time by ultrasonic or laser sensors to measure the height of the bubble layer in each area, and these data will be transmitted to the system at regular intervals. The surface area coverage of the bubble layer can be obtained by optical sensors or image processing technology, and the system will calculate the coverage by analyzing the proportion of the area covered by the bubble layer. The oxygen permeability is detected by oxygen concentration sensors to detect the efficiency of oxygen passing through the bubble layer into the fermentation liquid per unit time. These sensors are usually installed at multiple locations below the bubble layer to monitor the oxygen penetration effect. The bubble layer density is derived by combining the data of bubble layer thickness and coverage with the fluid dynamics model inside the fermenter. The average air pressure data is collected in real time by the air pressure sensor installed on the top of the tank body. The system will regionalize these data to reflect the local pressure conditions in different areas. After preprocessing these multi-type sensor data, the software will automatically extract the relevant bubble obstruction information through the algorithm, and normalize and standardize these data to ensure comparability and consistency between different data types. This automated extraction process ensures the timeliness and accuracy of the data, and can provide high-quality data support for subsequent bubble obstruction analysis.

[0033] Calculate the bubble coverage factor of each area on the top of the fermentation tank. The specific calculation formula is as follows: In the formula, The top of the fermenter The bubble coverage factor of each area; Bubble coverage factor of each area on the top of the fermenter The calculation formula provides an indicator for comprehensively evaluating the effect of the bubble layer on oxygen exchange by comprehensively considering the thickness, coverage, density, oxygen permeability and local air pressure of the bubble layer. Each part of the formula is necessary and reasonable. First, and They represent the surface area coverage of the bubble layer and the thickness of the bubble layer respectively. Their product can reflect the overall coverage of the bubble layer - the greater the coverage, the more significant the effect of blocking oxygen. The density of the bubble layer is taken into account. The greater the density, the more bubbles there are, and the worse the oxygen permeability is. Therefore, this term is added to further reflect the enhancement of the barrier effect by the density of bubbles. is the oxygen permeability, which represents the amount of oxygen that passes through the bubble layer per unit time. This part directly affects the oxygen supply effect, so it is placed in the denominator to represent the offsetting effect of the permeability on the bubble layer. Represents the local air pressure. The higher the air pressure, the more difficult it is for oxygen to penetrate. Therefore, the square root is used to introduce the influence of air pressure to accurately reflect the resistance of air pressure to oxygen penetration. This formula can comprehensively and dynamically reflect the degree of resistance of the bubble layer to oxygen exchange through the weighted summation of multiple factors, thus providing an accurate basis for adjustments during the fermentation process.

[0034] Fermentation tank top There is a direct positive correlation between the size of the bubble coverage factor of each area and the predicted degree of oxygen obstruction by the bubble layer. The larger the bubble coverage factor, the thicker the bubble layer in the area, the wider the coverage area, and the higher the bubble density, which makes oxygen penetration more difficult. Specifically, the increase in the thickness and coverage of the bubble layer will cause oxygen to encounter greater resistance when penetrating the bubble layer, and the increase in bubble density will further reduce the speed of oxygen passing through the bubble layer. The reduction in local air pressure and oxygen permeability will also make it more difficult for oxygen to enter the fermentation liquid. Therefore, the larger the bubble coverage factor, the stronger the barrier effect of the bubble layer on oxygen, and it is more difficult for oxygen to effectively penetrate the bubble layer into the fermentation liquid, which may affect the metabolic efficiency and fermentation rate of yeast during fermentation.

[0035] The oxygen exchange information in the gas exchange information of each area on the top of the pretreated fermenter is extracted, including the oxygen concentration, gas exchange rate, oxygen demand, carbon dioxide concentration and temperature change rate of each area on the top of the fermenter at different times over a period of time, and calibrated as , , , and , Indicates the top of the fermentation tank area within a period of time The oxygen concentration at the time, Indicates the top of the fermentation tank area within a period of time The gas exchange rate at each moment, Indicates the top of the fermentation tank area within a period of time Oxygen demand at any time, Indicates the top of the fermentation tank area within a period of time The carbon dioxide concentration at the time, Indicates the top of the fermentation tank area within a period of time The temperature change rate at each moment; Extracting oxygen exchange information from each area on the top of the pretreated fermenter can be achieved through software combined with the analysis of multiple sensor network data. First, the oxygen concentration can be directly detected by oxygen sensors in each area. The sensor will measure the oxygen concentration regularly and transmit its data to the software system for analysis. The gas exchange rate is obtained through flow rate sensors or airflow monitoring equipment. These sensors can monitor the airflow dynamics at the top of the fermenter and measure the speed of gas passing through the bubble layer per unit time. The oxygen demand is calculated by the system combining the yeast metabolism model during the fermentation process and the real-time monitoring of fermentation temperature, yeast activity and other factors. The software will dynamically adjust the yeast oxygen demand based on these real-time data. The carbon dioxide concentration is measured in real time by the carbon dioxide sensor installed on the top of the fermenter. The software will regularly collect the carbon dioxide concentration in each area and analyze the effect of oxygen exchange in combination with the oxygen concentration. The temperature change rate is calculated by the temperature data measured by the temperature sensor at different time points. The system calculates the temperature change rate of each area by monitoring the temperature fluctuations in the fermenter. All these data will be transmitted to the central system in real time through the sensor network. The software will automatically clean and normalize these data and extract information related to oxygen exchange. Through these automated data extraction processes, the system can accurately grasp the oxygen exchange conditions in each area on the top of the fermentation tank, providing support for subsequent oxygen supply and regulation strategies.

[0036] Calculate the oxygen exchange index of each area on the top of the fermenter. The specific calculation formula is as follows: In the formula, The top of the fermenter Oxygen exchange index of a region.

[0037] Oxygen exchange index of each area at the top of the fermenter The calculation formula takes into account multiple factors such as oxygen concentration, gas exchange rate, carbon dioxide concentration, yeast oxygen demand, and temperature change rate to fully reflect whether oxygen can effectively penetrate and meet yeast needs during the fermentation process. First, the formula Represents oxygen concentration. The higher the concentration, the better the oxygen supply effect. is the gas exchange rate. The faster the gas exchange, the more efficient the oxygen supply. Therefore, multiplying the two can reflect the intensity of oxygen supply. Taking into account the concentration of carbon dioxide, the ratio of carbon dioxide to oxygen concentration will affect the efficiency of oxygen exchange. The higher the concentration of carbon dioxide, the more hindered the oxygen exchange is. Therefore, this item is used to deduct the negative impact of carbon dioxide on oxygen exchange. represents the oxygen demand of the yeast. The higher the demand, the greater the pressure on the oxygen supply, so it is placed in the denominator to represent the pressure on the oxygen supply caused by high demand. Finally, the temperature change rate Through the natural logarithm function The introduction reflects the effect of temperature on oxygen exchange. The greater the temperature gradient, the more obvious the impact on the solubility and fluidity of oxygen may be. Therefore, the logarithmic function is used to make the effect nonlinear. Through the calculation of these steps, the oxygen exchange index can reflect whether the oxygen supply in each area is sufficient and whether oxygen can effectively penetrate the bubble layer to support the oxygen demand during the fermentation process.

[0038] Fermentation tank top The size of the oxygen exchange index of each area is inversely related to the degree of oxygen obstruction by the bubble layer. The larger the oxygen exchange index, the higher the oxygen concentration in the area, the faster the gas exchange rate, the lower the carbon dioxide concentration, the smaller the effect of temperature changes on oxygen, and the yeast's oxygen demand is better met, indicating that the oxygen supply in the area is relatively sufficient. Therefore, the larger the oxygen exchange index, the smaller the oxygen obstruction by the bubble layer. On the contrary, if the oxygen exchange index is small, it means that oxygen permeation is poor, the carbon dioxide concentration is high, the temperature changes are large, and oxygen cannot effectively penetrate the bubble layer into the fermentation liquid, which means that the bubble layer has a strong degree of oxygen obstruction. Therefore, the oxygen exchange index can intuitively reflect the obstruction effect of the bubble layer on oxygen permeation. The smaller the index, the greater the degree of obstruction.

[0039] In this embodiment, the bubble coverage factor of each area on the top of the fermentation tank is generated. and oxygen exchange index Construct an obstacle prediction model and generate the obstacle coefficients of each area on the top of the fermenter by weighted summation , and the resulting resistance coefficients of each area on the top of the fermenter The threshold interval of the obstacle coefficient is set in advance The comparison is carried out, and the degree of oxygen obstruction of the bubble layer formed in each area on the top of the fermentation tank is predicted according to the comparison results. According to the prediction results, each area on the top of the fermentation tank is divided into a high barrier area, a medium barrier area and a low barrier area. The specific comparison analysis and division process is as follows: like , the bubble layer formed in this area has a low barrier to oxygen, so this area is divided into a low barrier area; This area is classified as a low-barrier zone, which means that the bubble layer formed in this area has a weaker barrier effect on oxygen, and oxygen can pass through the bubble layer more smoothly to fully exchange with the fermentation liquid. In this case, the yeast can get enough oxygen supply, the fermentation efficiency is higher, and the accumulation of carbon dioxide is less. The bubble layer with less impact will not significantly interfere with the fermentation process. By obtaining data such as the bubble layer thickness and oxygen permeability through sensors, combined with the sensor network and real-time data analysis inside the fermentation tank, the system can automatically identify areas with lower barrier coefficients as low-barrier zones. The specific division method is based on the system settings. Threshold, through real-time monitoring and comparison of the obstruction coefficients of various areas by the algorithm, automatically divides the areas below this threshold into low-obstruction areas.

[0040] like , the bubble layer formed in this area has a medium degree of barrier to oxygen, so this area is divided into a medium barrier area; This area is classified as a medium barrier zone, which means that the bubble layer in this area has a moderate degree of oxygen barrier. Oxygen can pass through the bubble layer but may be affected to a certain extent. In this case, the oxygen penetration efficiency is reduced, the yeast metabolism rate is slowed down, but the fermentation process can still remain relatively stable. The accumulation of carbon dioxide begins to increase, but it will not significantly affect the fermentation process. By real-time monitoring of bubble layer thickness, oxygen permeability, air pressure and other parameters, the system can automatically analyze and calculate whether the barrier coefficient of this area is within the preset range. and The division method relies on the continuous data collection of the sensor and the automatic comparison function of the software, and the area falling into this interval is automatically identified as a medium barrier area.

[0041] like , the bubble layer formed in this area has a high barrier degree to oxygen, so this area is divided into a high barrier area.

[0042] This area is classified as a high-barrier zone, which means that the bubble layer in this area has a very obvious barrier effect on oxygen, and oxygen can hardly effectively pass through the bubble layer to fully exchange with the fermentation liquid. At this time, the yeast's metabolic rate may decrease due to lack of oxygen, the fermentation efficiency will be significantly reduced, the accumulation of carbon dioxide will also increase significantly, and the fermentation process will be greatly affected. In order to avoid insufficient oxygen supply, the system needs to take regulatory measures in time, such as increasing the stirring intensity of the area or adjusting the oxygen supply. The system will automatically calculate the barrier coefficient of the area through the oxygen concentration, bubble layer thickness and other data obtained by the sensor, and compare it with the preset For comparison, areas exceeding the threshold will be classified as high-barrier areas. The specific process of classification depends on the continuous monitoring of sensor data and the real-time feedback mechanism of the system to ensure that high-barrier areas can be identified in time and corresponding countermeasures can be taken.

[0043] The bubble coverage factor of each area on the top of the fermenter is generated and oxygen exchange index Constructing an obstruction prediction model, the obstruction coefficient of each area can be generated by weighted summation Specifically, the system considers both coefficients for each zone, combining their respective effects on oxygen barrier. Since a larger bubble coverage coefficient means a stronger barrier to oxygen from the bubble layer, and a smaller oxygen exchange index means poor oxygen permeability, the weights of these two parameters need to be adjusted according to their relative importance to oxygen barrier. In general, the bubble coverage coefficient may have a greater impact, so the weight will be larger, while the oxygen exchange index, while equally important, may be more important under certain fermentation conditions. will be slightly smaller. The weighted summation formula is as follows: ;in, and is the weight coefficient, usually To reflect the greater impact of bubble coverage on oxygen barrier. Through this weighted summation method, the system will comprehensively consider the impact of bubble coverage and oxygen exchange on oxygen permeation to generate a comprehensive barrier coefficient. This obstruction coefficient directly reflects the degree of oxygen obstruction of the bubble layer in each area. The larger the value, the stronger the obstruction. The system can further classify and adjust the area accordingly.

[0044] Based on the division results of each area, a bubble suppression and oxygen regulation mechanism is constructed to make different oxygen supply and bubble dissipation adjustments for high barrier area, medium barrier area and low barrier area respectively; In this embodiment, based on the division results of each area, a bubble suppression and oxygen adjustment mechanism is constructed, specifically including: according to the division results of the high barrier area, the medium barrier area and the low barrier area, different oxygen supply and bubble dissipation parameters are set respectively to form a bubble suppression and oxygen adjustment mechanism; the adjustment mechanism is based on the obstruction coefficient of each area and the current oxygen exchange state, and the adjustment range and method of the oxygen supply and bubble dissipation are automatically determined through pre-set rules; First, the system divides the area on the top of the fermentation tank into high barrier area, medium barrier area and low barrier area by real-time monitoring of parameters such as the thickness of the bubble layer, gas exchange rate and oxygen concentration. After the division of each area is completed, the system will set the corresponding oxygen supply and bubble dissipation parameters according to the obstruction coefficient of each area. In the high barrier area, due to the thick bubble layer, the system needs to increase the oxygen supply and increase the stirring intensity to accelerate the dissipation of bubbles. Therefore, the software automatically sets high oxygen supply parameters and higher stirring frequency. In the medium barrier area, the oxygen obstruction is moderate, and the system will maintain the standard oxygen supply parameters to ensure that the bubble layer has little effect on oxygen exchange. In the low barrier area, due to the thin bubble layer, oxygen can penetrate smoothly, so the system will reduce the oxygen supply and reduce the stirring intensity to save resources. In this way, the system automatically matches the most suitable oxygen supply and bubble dissipation parameters according to the specific obstruction level of each area, forming an intelligent adjustment mechanism.

[0045] This adjustment mechanism is implemented through pre-set rules and algorithms. The software automatically determines the adjustment range of oxygen supply and bubble dissipation based on the obstruction coefficient of each area (generated by bubble coverage coefficient and oxygen exchange index) and the current oxygen exchange status. First, the system determines whether the oxygen exchange in the area is significantly affected based on the size of the obstruction coefficient. If the obstruction coefficient of a certain area exceeds the set threshold, the software will automatically increase the oxygen supply and increase the stirring intensity to dissipate the bubble layer as soon as possible and restore the normal supply of oxygen. For areas with lower obstruction coefficients, the system will automatically reduce the oxygen supply according to the oxygen exchange status and reduce the stirring frequency to avoid oversupply. The whole process is achieved through the automatic feedback system in the software. The system dynamically adjusts the supply parameters based on the real-time collected data (such as oxygen concentration, carbon dioxide concentration, bubble layer thickness, etc.) to ensure that the oxygen exchange efficiency during the fermentation process is always maintained at the best state.

[0046] This adjustment mechanism is set up to deal with the problem of uneven oxygen supply caused by the obstruction of the bubble layer during the fermentation process. During the fermentation of high-concentration wort, the degree of oxygen obstruction by the bubble layer will directly affect the metabolic efficiency of the yeast, and the traditional optimization control technology has failed to solve the technical problem of uneven distribution of oxygen in different areas. Therefore, based on the obstruction coefficient and oxygen exchange state of each area, the mechanism of automatically adjusting the oxygen supply and bubble dissipation parameters can ensure that each area inside the fermentation tank can get proper oxygen supply and avoid the problem of insufficient local oxygen supply due to excessively thick bubble layer. This adjustment mechanism can accurately and real-time respond to changes in the fermentation process, improve the activity of yeast, avoid the problems of decreased fermentation efficiency and excessive accumulation of carbon dioxide, thereby improving the overall fermentation stability and product quality.

[0047] Different oxygen supply and bubble dissipation adjustments are made to the high barrier zone, medium barrier zone and low barrier zone respectively, specifically including: in the high barrier zone, high oxygen supply parameters in the adjustment mechanism are used, and the stirring intensity is increased to accelerate the dissipation of the bubble layer; in the medium barrier zone, the standard oxygen supply parameters in the adjustment mechanism are maintained to maintain the current oxygen supply and bubble dissipation rate; in the low barrier zone, low oxygen supply parameters in the adjustment mechanism are used to reduce the oxygen supply and reduce the stirring intensity for the dissipation of the bubble layer.

[0048] In the high barrier area, the bubble layer has a very strong barrier effect on oxygen, and the system needs to adopt a more aggressive control strategy. The software can automatically activate the high oxygen supply mode based on the real-time monitoring of the bubble coverage coefficient and oxygen exchange index. In this case, the oxygen supply parameter is set to a higher value, and the system will increase the oxygen supply by automatically controlling the oxygen supply equipment (such as the oxygen injection system or blower). At the same time, the system will detect the dissipation of bubbles in the fermenter, and increase the stirring intensity as needed, using the built-in stirring controller to increase the speed or power of the agitator to accelerate the dissipation of the bubble layer. This adjustment can be dynamically adjusted by the algorithm, and the adjustment range of the stirring intensity and oxygen supply is determined according to the size of the barrier coefficient and the thickness of the bubble layer. This is done to quickly break the barrier of the bubble layer so that oxygen can enter the fermentation liquid in time, ensuring the normal metabolism of the yeast and the smooth progress of the fermentation process.

[0049] In the medium barrier zone, the barrier effect of the bubble layer on oxygen is moderate, so no major adjustments are required. The software maintains standard oxygen supply parameters based on the barrier coefficient of the area and the current oxygen exchange status. The system will maintain the operation of the existing oxygen supply equipment through a timed feedback mechanism based on the preset oxygen supply and bubble layer thickness without making too many adjustments. The stirring intensity is also maintained at a normal level to ensure that the bubble layer does not accumulate excessively and does not cause too much disturbance. The advantage of this adjustment method is that it can save energy and oxygen supply resources while ensuring the stability of the fermentation process. Since the barrier effect of the bubble layer is relatively small, the oxygen supply can meet the metabolic needs of the yeast, and the fermentation efficiency can be maintained in a good state without additional operational intervention.

[0050] In the low-barrier area, the bubble layer's barrier to oxygen is almost negligible, so the system automatically reduces the oxygen supply. The software uses sensor data to determine the oxygen exchange in the area, and automatically adjusts the oxygen supply to a lower level based on oxygen concentration, bubble layer thickness, and oxygen exchange index to avoid waste. At the same time, the stirring intensity will also be reduced. The software will reduce the operating time of the agitator or reduce the stirring power according to the state of the bubble layer to reduce interference with the fermentation liquid. This adjustment method can maximize energy and oxygen savings while ensuring that the fermentation process is not subject to additional interference. Since the bubble layer has little barrier to oxygen, yeast can continue to metabolize normally with the existing oxygen supply, so reducing the oxygen supply will not affect the fermentation efficiency, but will optimize resource utilization and improve the overall efficiency of the system.

[0051] In the process of adjusting each area by the bubble suppression and oxygen regulation mechanism, the gas exchange feedback information of each area is obtained in real time, and analyzed after acquisition to evaluate whether the adjustment effect of the mechanism in each area can meet the requirements of oxygen penetrating the bubble layer and exchanging with the fermentation liquid normally, and the adjustment mechanism is optimized according to the evaluation results; In this embodiment, during the process of adjusting each area by the bubble suppression and oxygen regulation mechanism, the gas exchange feedback information of each area is obtained in real time, and analyzed after acquisition to evaluate whether the adjustment effect of the mechanism in each area can meet the requirements of oxygen penetrating the bubble layer and exchanging with the fermentation liquid normally, and the adjustment mechanism is optimized according to the evaluation results, which specifically includes the following steps: In the process of adjusting each area by bubble suppression and oxygen regulation mechanism, gas exchange feedback information of each area is obtained in real time and pre-processed after acquisition; Real-time gas exchange feedback information in each area can be obtained through a sensor network. Sensors are deployed in different areas on the top of the fermenter to monitor key parameters related to gas exchange. These sensors include oxygen concentration sensors, carbon dioxide concentration sensors, bubble layer thickness sensors, and temperature sensors. Each sensor will send data to the central control system regularly through wireless transmission technology, and the software will process and analyze the data in real time. Specific gas exchange feedback information includes changes in oxygen concentration, carbon dioxide concentration, dynamic changes in the thickness of the bubble layer, and temperature changes in the fermenter. These data can fully reflect the exchange of gases in different areas and are a direct reflection of the adjustment effect of the regulation mechanism. The software will collect sensor data regularly according to the preset collection frequency and summarize it to ensure that the gas exchange dynamics in each area are fed back in real time.

[0052] The purpose of preprocessing is to ensure the accuracy and consistency of the data, because the data collected by the sensor may contain noise, missing values ​​or transient anomalies, which may affect subsequent analysis. Preprocessing first includes data cleaning, and the system automatically identifies and removes outliers, such as extreme values ​​caused by sensor errors or environmental interference. Next is data smoothing, which uses moving averages or filters to eliminate short-term fluctuations in the data, making the data smoother and reflecting the true gas exchange trend. Finally, data standardization is performed to convert different types of data (such as oxygen concentration, carbon dioxide concentration, and temperature changes) to the same dimension so that they can be compared and calculated during subsequent analysis. Through these preprocessing steps, the system is able to obtain clean and reliable gas exchange feedback data, thereby providing more accurate input for the evaluation of regulatory effects.

[0053] Extracting oxygen exchange dynamic information and oxygen penetration resistance dynamic information from the pre-processed gas exchange feedback information of each region, and analyzing them after extraction to generate gas exchange efficiency variation coefficient and oxygen penetration resistance variation coefficient of each region respectively; Extracting the "dynamic information of oxygen exchange" and "dynamic information of oxygen penetration resistance" from the pre-processed gas exchange feedback information of each area can be achieved by classifying and calculating the sensor data through the software system. First, the system will group the pre-processed data, classify the parameters related to oxygen concentration, gas exchange rate, bubble layer thickness, etc. as "dynamic information of oxygen exchange"; and classify the parameters related to oxygen concentration gradient, carbon dioxide concentration and bubble layer density as "dynamic information of oxygen penetration resistance". The software performs trend analysis and change rate calculation on these parameters in different areas through the set data analysis model. For example, the system will dynamically calculate the oxygen exchange rate and change rate based on the collected oxygen concentration and bubble layer thickness change data, thereby extracting the "dynamic information of oxygen exchange"; at the same time, combined with the changes in carbon dioxide concentration and bubble layer density, the system automatically calculates the changes in oxygen penetration resistance, thereby extracting the "dynamic information of oxygen penetration resistance". This extraction method relies on the automatic analysis and allocation of real-time data. The software can perform targeted extraction and classification based on the gas exchange feedback information of different areas to ensure that the data can accurately reflect the oxygen exchange status of each area.

[0054] The generated gas exchange efficiency variation coefficient and oxygen penetration resistance variation coefficient of each area are used to construct an adjustment effect evaluation model to generate an adjustment coefficient for each area. The generated adjustment coefficient for each area is compared with a preset adjustment coefficient threshold. Based on the comparison results, it is evaluated whether the adjustment effect of the mechanism in each area can meet the requirements of oxygen penetrating the bubble layer and exchanging normally with the fermentation liquid, and the adjustment mechanism is optimized based on the evaluation results.

[0055] The pre-set adjustment coefficient threshold can be determined by the software system in combination with historical data analysis, experimental results and dynamic optimization algorithms. First, the system collects a large amount of gas exchange feedback data from historical fermentation processes, including information such as bubble layer thickness, oxygen concentration, and gas exchange efficiency in different regions. By analyzing these historical data, the software can identify which adjustment measures (such as oxygen supply, stirring intensity, etc.) can most effectively improve oxygen penetration and exchange efficiency under different bubble layer obstruction conditions, and thus preliminarily determine a range of adjustment coefficients. Next, the system will combine experimental verification to simulate the oxygen exchange and bubble layer dissipation process in different regions to further optimize these thresholds. By providing feedback on the adjustment effect under different fermentation conditions, the software can dynamically adjust the coefficient threshold. In order to ensure flexible response to changes in different batches of fermentation, the system can also continuously learn and update the threshold through machine learning algorithms to ensure that the adjustment coefficient matches the actual fermentation state, thereby improving the accuracy and effectiveness of the adjustment mechanism.

[0056] In this embodiment, the logic for obtaining the gas exchange efficiency variation coefficient and the oxygen penetration resistance variation coefficient of each region is as follows: Extract the oxygen exchange dynamic information from the gas exchange feedback information of each area after preprocessing, specifically including the oxygen exchange rate, bubble layer thickness, oxygen permeability and corresponding time points at different times during a period of time in the process of bubble suppression and oxygen regulation mechanism adjusting each area, and use function to calculate the oxygen exchange rate, bubble layer thickness and oxygen permeability at different times during a period of time in the process of bubble suppression and oxygen regulation mechanism adjusting each area according to the time series. , and To express, For time point, Indicates the role of bubble suppression and oxygen regulation mechanisms in During the period of adjustment of the region The oxygen exchange rate at each moment, Indicates the role of bubble suppression and oxygen regulation mechanisms in During the period of adjustment of the region The thickness of the bubble layer at the time, Indicates the role of bubble suppression and oxygen regulation mechanisms in During the period of adjustment of the region The oxygen permeability at the moment, , is a positive integer, defining the time period as ; Extracting the dynamic information of oxygen exchange in each pre-treated area can be achieved through software combined with sensor network automation. First, oxygen exchange rate sensors, bubble layer thickness sensors, and oxygen permeability sensors are deployed in different areas on the top of the fermenter. These sensors will monitor the key parameters of each area in real time during the fermentation process and send these data to the central control system in a time series. After receiving these sensor data, the software first calculates the oxygen exchange rate of each area. , bubble layer thickness , and oxygen permeability Carry out preliminary sorting and labeling to ensure that each piece of data is consistent with the time. Closely correspond. Through specific analysis algorithms, the software extracts data from different time points to form a series of time series data, and ensures the accuracy and consistency of the data according to preprocessing standards (such as denoising and data smoothing). The source of these data can be real-time data monitored by sensors, or combined with historical data, the current trend of change can be predicted and supplemented through data fusion algorithms. In this way, the software system can simultaneously obtain and extract dynamic information on oxygen exchange involved in the fermentation process from multiple areas, thereby providing key feedback information for the regulation mechanism.

[0057] Calculate the coefficient of variation of gas exchange efficiency in each area. The specific calculation formula is as follows: In the formula, For the The coefficient of variation of gas exchange efficiency in each region is Indicates the rate of change of oxygen exchange rate, represents the change rate of the bubble layer thickness, Indicates the rate of change of oxygen permeability; The following is a detailed explanation of the calculation formula for the coefficient of change of gas exchange efficiency in each area: This formula combines the dynamic change rate of gas exchange rate, oxygen permeability and bubble layer thickness in the form of time integral to quantify the change of gas exchange efficiency in each area within a specific time period. The core idea of ​​the formula design is that in the process of bubble suppression and oxygen regulation mechanism adjusting each area, the changes in these three parameters directly reflect the dynamic adjustment of gas exchange efficiency. Oxygen exchange rate Indicates the change in the rate at which oxygen enters the fermentation liquid through the bubble layer. It is an important indicator for directly measuring the efficiency of oxygen supply. Oxygen permeability Indicates the ability of oxygen to penetrate the bubble layer. If the permeability changes rapidly, it means that the oxygen supply is effectively guaranteed. The thickness of the bubble layer The rate of change indicates the degree of obstruction of the bubble layer to oxygen transmission. The thicker the bubble layer, the more difficult it is for oxygen to pass through. Therefore, the change in thickness determines the fluctuation of oxygen exchange efficiency. By calculating in integral form, the cumulative effect of these three dynamic factors over a time period can be captured. In this way, the formula can accurately reflect the complex interactive effects of bubble layer thickness, oxygen permeability, and oxygen exchange rate during the oxygen supply process, help evaluate the gas exchange efficiency of each area in real time, and provide data support for the adjustment strategy.

[0058] Change rate of oxygen exchange rate :This expression means Area in time The rate of change of oxygen exchange rate on the fermentation liquid. The oxygen exchange rate is a measure of the rate at which oxygen passes through the bubble layer and enters the fermentation liquid. The rate of change captures how the oxygen exchange rate changes over time. A larger rate of change means that oxygen can pass through the bubble layer faster, which means that the oxygen supply is smooth; a smaller rate of change may indicate that oxygen transmission is blocked. Therefore, this expression helps to measure the dynamic changes in oxygen penetrating the bubble layer and entering the fermentation liquid during the fermentation process.

[0059] Change rate of oxygen permeability :This expression means The rate of change of regional oxygen permeability over time. Oxygen permeability indicates the ability of oxygen to penetrate the bubble layer into the fermentation liquid. As fermentation progresses, the bubble layer may become thicker or thinner over time, which affects the oxygen permeability. A larger permeability change indicates that the resistance of the bubble layer is reduced and the oxygen permeability is improved; conversely, a smaller permeability change means that the bubble layer has become more difficult to penetrate.

[0060] Change rate of bubble layer thickness :This expression means The rate of change of the regional bubble layer thickness over time. The thicker the bubble layer, the more difficult it is for oxygen to penetrate, so changes in thickness have a direct impact on oxygen transmission. By calculating the rate of change of thickness, it is possible to capture the dynamic changes of the bubble layer, especially the process of bubble dissipation or accumulation. A large thickness change rate means that the bubble layer is accumulating or dissipating rapidly, resulting in a significant change in the barrier to oxygen transmission.

[0061] No. The size of the coefficient of change of gas exchange efficiency in each region directly reflects the permeability of oxygen in the bubble layer and the overall gas exchange dynamics. If the coefficient is large, it means that the dynamic changes of oxygen exchange rate, bubble layer thickness and oxygen permeability are relatively ideal, indicating that oxygen can quickly penetrate the bubble layer and effectively exchange with the fermentation liquid, thereby ensuring the normal metabolic activity of yeast. On the contrary, if the coefficient is small, it means that the gas exchange efficiency is low, and there may be a phenomenon that oxygen is blocked by the bubble layer and carbon dioxide is not discharged smoothly, resulting in oxygen being unable to effectively reach the fermentation liquid. By evaluating this coefficient, it can be judged whether the current bubble suppression and oxygen regulation mechanism has achieved the expected effect during the adjustment process. If the coefficient does not reach the expected value, the bubble suppression mechanism or oxygen supply parameters need to be further optimized to ensure sufficient oxygen supply during the fermentation process, meet the metabolic needs of yeast and avoid a decrease in fermentation efficiency.

[0062] Extract the dynamic information of oxygen penetration resistance from the gas exchange feedback information of each area after preprocessing, specifically including the oxygen concentration, carbon dioxide concentration, bubble layer density and corresponding time points at different times during a period of time when the bubble suppression and oxygen regulation mechanism adjusts each area, and use the function to calculate the oxygen concentration, carbon dioxide concentration and bubble layer density at different times during a period of time when the bubble suppression and oxygen regulation mechanism adjusts each area according to the time series. , and To express, Indicates the role of bubble suppression and oxygen regulation mechanisms in During the period of adjustment of the region The oxygen concentration at the time, Indicates the role of bubble suppression and oxygen regulation mechanisms in During the period of adjustment of the region The carbon dioxide concentration at the time, Indicates the role of bubble suppression and oxygen regulation mechanisms in During the period of adjustment of the region The density of the bubble layer at the moment, is a time point, and the time period is defined as ; Extracting dynamic information about oxygen penetration resistance in each pre-treated area can be achieved by combining sensor data and software analysis. Oxygen concentration sensors, carbon dioxide concentration sensors, and bubble layer density sensors are deployed in different areas of the fermentation tank to monitor the changes in these data in real time. Each sensor will collect oxygen concentration in the corresponding area at regular intervals during the fermentation process. , CO2 concentration and the density of the bubble layer The data is transmitted to the central software control system by wireless or wired means. After receiving the data, the system first organizes the data at different time points into corresponding time series and performs preprocessing, such as eliminating noise, filling missing data, and processing outliers to ensure the accuracy of the data. The software uses the time stamp function to associate the oxygen concentration, carbon dioxide concentration, and bubble layer density data with the corresponding time points. Precisely match, thus forming a complete time series. The software can also combine historical data for comparative analysis, and predict the trend of oxygen concentration and carbon dioxide concentration in each area at future moments through the model. Based on the pre-processed data, the software can automatically extract the dynamic information of oxygen penetration resistance at different times in each area, providing accurate data support for subsequent adjustment and optimization.

[0063] Calculate the oxygen penetration resistance variation coefficient of each area. The specific calculation formula is as follows: In the formula, For the The oxygen penetration resistance variation coefficient of each region is represents the rate of change of oxygen concentration, represents the rate of change of carbon dioxide concentration, Indicates the rate of change of the bubble layer density.

[0064] The formula The purpose of the design is to evaluate the changes in the resistance of the bubble layer to oxygen transmission in various areas of the fermenter. and the rate of change of carbon dioxide concentration , the formula can reflect the impact of dynamic changes in oxygen and carbon dioxide concentrations on gas exchange efficiency during fermentation. The product of the two shows the combined effect of oxygen and carbon dioxide changes. The bubble layer density change rate in the denominator It is used to represent the impact of the dynamic changes of the bubble layer on the resistance to oxygen transmission. When the density of the bubble layer increases, the oxygen penetration resistance increases, so the overall value of the formula decreases, reflecting that the bubble layer's resistance to oxygen penetration has increased. The formula integrates and calculates the cumulative effect of these change rates over a period of time, comprehensively evaluates the resistance of the bubble layer to oxygen transmission, and then provides a basis for adjusting the oxygen supply strategy during the fermentation process.

[0065] Rate of change of oxygen concentration : Indicates the rate of change of oxygen concentration in a certain area over time during the process of bubble suppression and oxygen regulation mechanism adjustment. The larger the value, the faster the oxygen concentration rises, indicating that oxygen can penetrate the bubble layer more effectively. If the rate of change is very small, it means that the oxygen permeability is poor and oxygen is blocked by bubbles on the surface of the fermentation liquid.

[0066] The rate of change of carbon dioxide concentration : Reflects the accumulation or discharge rate of carbon dioxide in a certain area. A rapid increase in carbon dioxide concentration usually means insufficient oxygen exchange, resulting in reduced gas exchange efficiency during fermentation. Therefore, this value helps analyze the effect of carbon dioxide on oxygen penetration resistance, especially when oxygen is blocked by the bubble layer.

[0067] The rate of change of the density of the bubble layer : reflects the density change of the bubble layer per unit time. If this change rate is high, it means that the density of the bubble layer increases rapidly, making it more difficult for oxygen to penetrate, hindering the exchange of oxygen and fermentation liquid. By monitoring the changes in the density of the bubble layer, we can better evaluate the degree of obstruction of bubbles to oxygen exchange and make timely adjustments to optimize the fermentation effect.

[0068] No. The size of the oxygen penetration resistance variation coefficient of each region reflects the change in resistance encountered by oxygen when penetrating the bubble layer. If the coefficient is large, it means that the resistance is large during the process of oxygen penetrating the bubble layer. It may be due to the increase in the density of the bubble layer or the increase in the carbon dioxide concentration, which makes it difficult for oxygen to penetrate into the fermentation liquid, thereby hindering the oxygen supply during the fermentation process and affecting the metabolic efficiency of the yeast. If the coefficient is small, it means that the bubble layer has a reduced barrier effect on oxygen, and oxygen is more likely to penetrate the bubble layer and fully exchange with the fermentation liquid to meet the oxygen demand of the yeast during the fermentation process. By evaluating the size of this coefficient, it can be judged whether the adjustment of the bubble suppression and oxygen regulation mechanism is effective. If the coefficient does not reach the expected low value, it means that the oxygen penetration effect is not good, and the adjustment mechanism fails to effectively dissipate the resistance of the bubble layer. At this time, it is necessary to further optimize the stirring intensity or oxygen supply strategy to reduce the resistance, ensure that oxygen enters the fermentation liquid smoothly, and improve the fermentation efficiency.

[0069] In this embodiment, the gas exchange efficiency variation coefficient of each region is generated and oxygen penetration resistance variation coefficient Construct an adjustment effect evaluation model and generate adjustment coefficients for each region through weighted summation , the adjustment coefficients for each region generated With the preset adjustment factor threshold Compare and evaluate whether the adjustment effect of the mechanism in each area can meet the requirements of oxygen penetrating the bubble layer and exchanging with the fermentation liquid normally according to the comparison results, and optimize the adjustment mechanism according to the evaluation results. The specific comparison analysis is as follows: like , the adjustment effect of the bubble suppression and oxygen regulation mechanism in this area cannot meet the requirements of oxygen penetrating the bubble layer and exchanging with the fermentation liquid normally. The adjustment mechanism needs to be optimized, including increasing the oxygen supply, increasing the stirring intensity and extending the adjustment time; like , which means that in a certain area, the effect of the bubble suppression and oxygen regulation mechanism has not met expectations. This may result in the inability of oxygen to fully penetrate the bubble layer and effectively exchange with the fermentation liquid, thus affecting the fermentation efficiency. In this case, it is necessary to adjust the bubble layer and oxygen supply through an optimization mechanism to make the oxygen exchange more sufficient. The optimization method includes increasing the supply of oxygen, dynamically adjusting the output power of the oxygen supply system by real-time monitoring of the oxygen concentration and the changes in oxygen demand in the fermentation liquid, and ensuring that the increased oxygen is transmitted to the fermentation liquid in time. Increasing the stirring intensity can be achieved by controlling the speed of the agitator, and adjusting the stirring speed in real time according to the changes in the thickness and density of the bubble layer to accelerate the dissipation of bubbles. In addition, extending the adjustment time can automatically set the adjustment cycle through the software, extend the duration of oxygen supply and stirring, ensure that the bubble layer is fully dissipated, and oxygen can fully penetrate the bubble layer into the fermentation liquid.

[0070] like , the adjustment effect of the bubble suppression and oxygen regulation mechanism in this area can meet the requirements of oxygen penetrating the bubble layer and exchanging normally with the fermentation liquid. There is no need to optimize the adjustment mechanism and maintain the current adjustment parameters.

[0071] like , indicating that in this area, the bubble suppression and oxygen regulation mechanisms have been able to meet the requirements of oxygen permeation through the bubble layer, the oxygen exchange process is normal, and the yeast fermentation reaction efficiency remains stable. In this case, there is no need to further optimize the adjustment mechanism, just maintain the existing adjustment parameters. In software implementation, this means maintaining the current set values ​​of oxygen supply and stirring parameters without real-time adjustment. This can be achieved by comparing and analyzing the monitoring data of each area through the software system. When the monitoring results are within the set range, the system will maintain the current adjustment settings and will not actively make adjustments, avoiding waste of system resources while ensuring the stability of the fermentation process.

[0072] To calculate the gas exchange efficiency variation coefficient of each area and oxygen penetration resistance variation coefficient To build an adjustment effect evaluation model, we first need to combine the two and perform a weighted sum to generate the final adjustment coefficient. . In this process, the weight coefficients of the gas exchange efficiency variation coefficient and the oxygen penetration resistance variation coefficient should be set according to their influence on oxygen exchange during the fermentation process. Usually, the gas exchange efficiency variation coefficient can be set with a higher weight because it directly reflects the dynamic exchange of oxygen and fermentation liquid, and is usually a key indicator of whether oxygen can penetrate the bubble layer. The oxygen penetration resistance variation coefficient reflects the resistance of the bubble layer to oxygen penetration, so its weight can be slightly lower, but it is still an important evaluation indicator. When calculating specifically, the adjustment coefficient The calculation formula is: ;in, and are the weight coefficients of the gas exchange efficiency variation coefficient and the oxygen penetration resistance variation coefficient. The values ​​of these two weight coefficients can be determined by experimental data or historical fermentation data. For example, in the critical stage of gas exchange dynamics, can be set to 0.6, while It can be set to 0.4, which reflects the priority of gas exchange efficiency over adjustment effect. In the case where resistance significantly affects oxygen penetration, the weight can be dynamically adjusted to and When the software is implemented, it can obtain the real-time and The data is used to calculate the adjustment coefficient of each area based on the weight. This adjustment coefficient is ultimately used to determine whether the oxygen supply and bubble suppression effect of each area meet the fermentation requirements. If it meets the preset threshold range, it means that the oxygen supply and regulation mechanism are effective. Otherwise, the system's oxygen supply and bubble dissipation parameters need to be further adjusted.

[0073] The gas exchange data, adjustment records and fermentation effects during the entire fermentation process are recorded and comprehensively analyzed in real time, the oxygen supply and bubble suppression strategies are continuously improved, and the adjustment mechanism is improved in real time.

[0074] To achieve real-time recording of gas exchange data and adjustment records, it is first necessary to deploy a sensor network during the fermentation process to monitor key parameters such as oxygen exchange rate, oxygen concentration, carbon dioxide concentration, bubble layer thickness, fermentation liquid temperature, etc. in real time. The sensor will collect data regularly and record these values ​​at each time point through the software system. The software will automatically store all gas exchange dynamic information and corresponding adjustment records (such as oxygen supply, stirring intensity and duration, etc.) in the database for subsequent analysis and optimization. The software system will trigger data recording operations according to predetermined time intervals or according to the dynamic changes in gas exchange to ensure the real-time and continuity of information.

[0075] During the fermentation process, in addition to real-time recording, real-time analysis of the collected data is also required. The software system can analyze the changing trends of oxygen exchange efficiency and oxygen penetration resistance through data processing algorithms. By building a model, the gas exchange efficiency variation coefficient and oxygen penetration resistance variation coefficient of different regions are comprehensively evaluated to predict and evaluate whether the fermentation effect of each region meets the requirements. This step uses a big data analysis algorithm, combined with historical data and current real-time data, to determine whether the current fermentation effect meets expectations. If the gas exchange efficiency in certain areas is found to be unsatisfactory, the system will automatically mark the area and trigger further adjustments.

[0076] Based on the above analysis, the software system will automatically give optimization suggestions for different areas. These suggestions are adjusted based on real-time feedback data. For example, if the resistance of the bubble layer in a certain area is too large, resulting in the inability of oxygen to effectively enter the fermentation liquid, the system will adjust the oxygen supply strategy and stirring parameters of the area according to real-time data. By adjusting the parameter model, the software will dynamically optimize the oxygen supply, adjust the stirring intensity and stirring time to increase the bubble dissipation speed and oxygen penetration efficiency in the area. The optimization strategy can be further improved through machine learning algorithms. The system will continuously learn historical data and actual operation results in order to gradually optimize parameter settings and control processes.

[0077] Based on all data analysis and strategy optimization, the software will dynamically adjust the adjustment mechanism of each area. The system will build an adaptive adjustment mechanism model based on previous operation records, feedback information and real-time fermentation results. If it is found that the fermentation effect in some areas does not meet expectations, the software will readjust the oxygen supply and stirring parameters based on feedback. The parameters in the adjustment mechanism can be continuously optimized and self-adjusted according to different fermentation stages to ensure that each step in the fermentation process is optimized in real time. Through this continuous optimization and feedback closed loop, the adjustment mechanism can maintain dynamic flexibility and adapt to different fermentation conditions and environments.

[0078] The purpose of achieving real-time recording, analysis and optimization through the above methods is to improve the efficiency and quality of the fermentation process and ensure that the metabolic rate of yeast is always in the best state. The effective supply of oxygen is the key to the fermentation process. Any insufficient oxygen supply will affect the fermentation efficiency and the final quality of the beer. The bubble layer will hinder oxygen penetration, so it is particularly important to optimize the bubble suppression and oxygen supply strategy. Real-time data analysis can help to detect problems in time and make adjustments in the shortest time to ensure that the fermentation process is always in the best control state in a dynamically changing environment, avoiding fermentation failure or quality decline.

[0079] like Figure 2An optimization control system for beer fermentation shown includes a fermentation area division and sensor monitoring module, a gas exchange information prediction and analysis module, a bubble suppression and oxygen regulation optimization module, a feedback and adjustment optimization module, and a fermentation process comprehensive recording and strategy improvement module; The fermentation area division and sensor monitoring module divides the top of the fermentation tank into several areas evenly during the fermentation of high-concentration wort, and evenly distributes the fermentation liquid in each area. A sensor network is deployed in each area to obtain gas exchange information in real time. The gas exchange information prediction and analysis module obtains the gas exchange information of each area on the top of the fermenter in real time, analyzes it after acquisition, predicts the degree of oxygen obstruction of the bubble layer formed in each area on the top of the fermenter, and divides each area on the top of the fermenter into a high-barrier area, a medium-barrier area and a low-barrier area according to the prediction results; The bubble suppression and oxygen regulation optimization module builds a bubble suppression and oxygen regulation mechanism based on the division results of each area, and makes different oxygen supply and bubble dissipation adjustments for high barrier area, medium barrier area and low barrier area respectively; Feedback and adjustment optimization module, in the process of adjusting each area by the bubble suppression and oxygen regulation mechanism, obtains gas exchange feedback information of each area in real time, analyzes it after obtaining, evaluates whether the adjustment effect of the mechanism in each area can meet the requirements of oxygen penetrating the bubble layer and exchanging with the fermentation liquid normally, and optimizes the adjustment mechanism according to the evaluation results; The comprehensive record and strategy improvement module of the fermentation process records and conducts real-time and comprehensive analysis of the gas exchange data, adjustment records and fermentation effects during the entire fermentation process, continuously improves the oxygen supply and bubble suppression strategies, and improves the adjustment mechanism in real time.

[0080] The above formulas are all dimensionless and numerical calculations. The formula is a formula for the most recent real situation obtained by collecting a large amount of data and performing software simulation. The preset parameters in the formula are set by technicians in this field according to actual conditions.

[0081] The above embodiments can be implemented in whole or in part by software, hardware, firmware or any other combination. When implemented by software, the above embodiments can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from one website, computer, server or data center to another website, computer, server or data center by wired or wireless (such as infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server or data center that contains one or more available media sets. The available medium can be a magnetic medium (for example, a floppy disk, a hard disk, a tape), an optical medium (for example, a DVD), or a semiconductor medium. The semiconductor medium can be a solid-state hard disk.

[0082] It should be understood that in the various embodiments of the present application, the size of the serial numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0083] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0084] In the several embodiments provided in the present application, it should be understood that the disclosed systems and methods can be implemented in other ways. For example, the embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interfaces, devices or units, which can be electrical, mechanical or other forms.

[0085] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0086] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0087] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. An optimization control method for beer fermentation, characterized in that: The specific steps include: During the fermentation of high-concentration wort, the top of the fermentation tank is evenly divided into several areas, and the fermentation liquid is evenly distributed in each area. A sensor network is deployed in each area to obtain gas exchange information in real time. The gas exchange information of each area on the top of the fermenter is obtained in real time, and analyzed after acquisition to predict the degree of oxygen obstruction of the bubble layer formed in each area on the top of the fermenter, and the areas on the top of the fermenter are divided into high-barrier area, medium-barrier area and low-barrier area according to the prediction results; Based on the division results of each area, a bubble suppression and oxygen regulation mechanism is constructed to make different oxygen supply and bubble dissipation adjustments for high barrier area, medium barrier area and low barrier area respectively; In the process of adjusting each area by the bubble suppression and oxygen regulation mechanism, the gas exchange feedback information of each area is obtained in real time, and analyzed after acquisition to evaluate whether the adjustment effect of the mechanism in each area can meet the requirements of oxygen penetrating the bubble layer and exchanging with the fermentation liquid normally, and the adjustment mechanism is optimized according to the evaluation results; The gas exchange data, adjustment records and fermentation effects during the entire fermentation process are recorded and comprehensively analyzed in real time, the oxygen supply and bubble suppression strategies are continuously improved, and the adjustment mechanism is improved in real time.

2. The optimization control method for beer fermentation according to claim 1, characterized in that: The gas exchange information of each area on the top of the fermenter is obtained in real time, and analyzed after acquisition to predict the degree of oxygen obstruction of the bubble layer formed in each area on the top of the fermenter, and the areas on the top of the fermenter are divided into high barrier area, medium barrier area and low barrier area according to the prediction results, which specifically includes the following steps: Obtain gas exchange information in various areas of the top of the fermenter in real time and perform preprocessing after acquisition; Extracting the bubble obstruction information and the oxygen exchange information from the gas exchange information of each area on the top of the pretreated fermenter, and analyzing them after extraction to generate the bubble coverage factor and the oxygen exchange index of each area on the top of the fermenter respectively; The bubble coverage coefficient and oxygen exchange index of each area on the top of the fermenter are used to construct an obstacle prediction model, and the obstacle coefficient of each area on the top of the fermenter is generated. The generated obstacle coefficient of each area on the top of the fermenter is compared with the preset obstacle coefficient threshold range. The obstacle degree of oxygen formed by the bubble layer in each area on the top of the fermenter is predicted according to the comparison result, and the various areas on the top of the fermenter are divided into high barrier area, medium barrier area and low barrier area according to the prediction result.

3. The optimization control method for beer fermentation according to claim 2, characterized in that: The logic for obtaining the bubble coverage factor and oxygen exchange index of each area on the top of the fermenter is as follows: The bubble barrier information in the gas exchange information of each area on the top of the pretreated fermenter was extracted, including the average thickness of the bubble layer, the surface area coverage of the bubble layer, the oxygen permeability, the bubble layer density and the average air pressure of each area on the top of the fermenter at different times within a period of time, and calibrated as , , , and , Indicates the top of the fermentation tank Regions within a period of time The average thickness of the bubble layer at the time, Indicates the top of the fermentation tank Regions within a period of time The surface area coverage of the bubble layer at the moment, Indicates the top of the fermentation tank area within a period of time The oxygen permeability at the moment, Indicates the top of the fermentation tank Regions within a period of time The density of the bubble layer at the moment, Indicates the top of the fermentation tank Regions within a period of time The average air pressure at the time, , , and All are positive integers; Calculate the bubble coverage factor of each area on the top of the fermentation tank. The specific calculation formula is as follows: In the formula, The top of the fermenter The bubble coverage factor of each area; The oxygen exchange information in the gas exchange information of each area on the top of the pretreated fermenter is extracted, including the oxygen concentration, gas exchange rate, oxygen demand, carbon dioxide concentration and temperature change rate of each area on the top of the fermenter at different times over a period of time, and calibrated as , , , and , Indicates the top of the fermentation tank Regions within a period of time The oxygen concentration at the time, Indicates the top of the fermentation tank Regions within a period of time The gas exchange rate at each moment, Indicates the top of the fermentation tank Regions within a period of time Oxygen demand at any time, Indicates the top of the fermentation tank Regions within a period of time The carbon dioxide concentration at the time, Indicates the top of the fermentation tank Regions within a period of time The temperature change rate at each moment; Calculate the oxygen exchange index of each area on the top of the fermenter. The specific calculation formula is as follows: In the formula, The top of the fermenter Oxygen exchange index of a region.

4. The optimization control method for beer fermentation according to claim 3, characterized in that: The bubble coverage factor of each area on the top of the fermenter is generated and oxygen exchange index Construct an obstacle prediction model and generate the obstacle coefficients of each area on the top of the fermenter by weighted summation , and the resulting resistance coefficients of each area on the top of the fermenter The threshold interval of the obstacle coefficient is set in advance The comparison is carried out, and the degree of oxygen obstruction of the bubble layer formed in each area on the top of the fermentation tank is predicted according to the comparison results. According to the prediction results, each area on the top of the fermentation tank is divided into a high barrier area, a medium barrier area and a low barrier area. The specific comparison analysis and division process are as follows: like , the bubble layer formed in this area has a low barrier to oxygen, so this area is divided into a low barrier area; like , the bubble layer formed in this area has a medium degree of barrier to oxygen, so this area is divided into a medium barrier area; like , the bubble layer formed in this area has a high barrier degree to oxygen, so this area is divided into a high barrier area.

5. The optimization control method for beer fermentation according to claim 4, characterized in that: Based on the division results of each area, a bubble suppression and oxygen adjustment mechanism is constructed, specifically including: according to the division results of the high barrier area, the medium barrier area and the low barrier area, different oxygen supply and bubble dissipation parameters are set respectively to form a bubble suppression and oxygen adjustment mechanism; the adjustment mechanism is based on the obstruction coefficient of each area and the current oxygen exchange state, and the adjustment range and method of the oxygen supply and bubble dissipation are automatically determined through pre-set rules; Different oxygen supply and bubble dissipation adjustments are made to the high barrier zone, medium barrier zone and low barrier zone respectively, specifically including: in the high barrier zone, high oxygen supply parameters in the adjustment mechanism are used, and the stirring intensity is increased to accelerate the dissipation of the bubble layer; in the medium barrier zone, the standard oxygen supply parameters in the adjustment mechanism are maintained to maintain the current oxygen supply and bubble dissipation rate; in the low barrier zone, low oxygen supply parameters in the adjustment mechanism are used to reduce the oxygen supply and reduce the stirring intensity for the dissipation of the bubble layer.

6. The optimization control method for beer fermentation according to claim 5, characterized in that: In the process of adjusting each area by the bubble suppression and oxygen regulation mechanism, the gas exchange feedback information of each area is obtained in real time, and analyzed after acquisition to evaluate whether the adjustment effect of the mechanism in each area can meet the requirements of oxygen penetrating the bubble layer and exchanging with the fermentation liquid normally, and optimize the adjustment mechanism according to the evaluation results, which specifically includes the following steps: In the process of adjusting each area by bubble suppression and oxygen regulation mechanism, the gas exchange feedback information of each area is obtained in real time and pre-processed after acquisition; Extracting oxygen exchange dynamic information and oxygen penetration resistance dynamic information from the pre-processed gas exchange feedback information of each region, and analyzing them after extraction to generate gas exchange efficiency variation coefficient and oxygen penetration resistance variation coefficient of each region respectively; The generated gas exchange efficiency variation coefficient and oxygen penetration resistance variation coefficient of each area are used to construct an adjustment effect evaluation model to generate an adjustment coefficient for each area. The generated adjustment coefficient for each area is compared with a preset adjustment coefficient threshold. Based on the comparison results, it is evaluated whether the adjustment effect of the mechanism in each area can meet the requirements of oxygen penetrating the bubble layer and exchanging normally with the fermentation liquid, and the adjustment mechanism is optimized based on the evaluation results.

7. The optimization control method for beer fermentation according to claim 6, characterized in that: The logic for obtaining the gas exchange efficiency variation coefficient and oxygen penetration resistance variation coefficient of each region is as follows: Extract the oxygen exchange dynamic information from the gas exchange feedback information of each area after preprocessing, specifically including the oxygen exchange rate, bubble layer thickness, oxygen permeability and corresponding time points at different times during a period of time in the process of bubble suppression and oxygen regulation mechanism adjusting each area, and use function to calculate the oxygen exchange rate, bubble layer thickness and oxygen permeability at different times during a period of time in the process of bubble suppression and oxygen regulation mechanism adjusting each area according to the time series. , and To express, For time point, Indicates the role of bubble suppression and oxygen regulation mechanisms in During the period of adjustment of the region The oxygen exchange rate at each moment, Indicates the role of bubble suppression and oxygen regulation mechanisms in During the period of adjustment of the region The thickness of the bubble layer at the time, Indicates the role of bubble suppression and oxygen regulation mechanisms in During the period of adjustment of the region The oxygen permeability at the moment, , is a positive integer, defining the time period as ; Calculate the coefficient of variation of gas exchange efficiency in each area. The specific calculation formula is as follows: In the formula, For the The coefficient of variation of gas exchange efficiency in each region is Indicates the rate of change of oxygen exchange rate, represents the change rate of the bubble layer thickness, Indicates the rate of change of oxygen permeability; Extract the dynamic information of oxygen penetration resistance from the gas exchange feedback information of each area after preprocessing, specifically including the oxygen concentration, carbon dioxide concentration, bubble layer density and corresponding time points at different times during a period of time when the bubble suppression and oxygen regulation mechanism adjusts each area, and use the function to calculate the oxygen concentration, carbon dioxide concentration and bubble layer density at different times during a period of time when the bubble suppression and oxygen regulation mechanism adjusts each area according to the time series. , and To express, Indicates the role of bubble suppression and oxygen regulation mechanisms in During the period of adjustment of the region The oxygen concentration at the time, Indicates the role of bubble suppression and oxygen regulation mechanisms in During the period of adjustment of the region The carbon dioxide concentration at the time, Indicates the role of bubble suppression and oxygen regulation mechanisms in During the period of adjustment of the region The density of the bubble layer at the moment, is a time point, and the time period is defined as ; Calculate the oxygen penetration resistance variation coefficient of each area. The specific calculation formula is as follows: In the formula, For the The oxygen penetration resistance variation coefficient of each region is represents the rate of change of oxygen concentration, represents the rate of change of carbon dioxide concentration, Indicates the rate of change of the bubble layer density.

8. The optimization control method for beer fermentation according to claim 7, characterized in that: The gas exchange efficiency variation coefficient of each region generated and oxygen penetration resistance variation coefficient Construct an adjustment effect evaluation model and generate adjustment coefficients for each region through weighted summation , the adjustment coefficients for each region generated With the preset adjustment factor threshold Compare and evaluate whether the adjustment effect of the mechanism in each area can meet the requirements of oxygen penetrating the bubble layer and exchanging with the fermentation liquid normally according to the comparison results, and optimize the adjustment mechanism according to the evaluation results. The specific comparison analysis is as follows: like , the adjustment effect of the bubble suppression and oxygen regulation mechanism in this area cannot meet the requirements of oxygen penetrating the bubble layer and exchanging with the fermentation liquid normally. The adjustment mechanism needs to be optimized, including increasing the oxygen supply, increasing the stirring intensity and extending the adjustment time; like , the adjustment effect of the bubble suppression and oxygen regulation mechanism in this area can meet the requirements of oxygen penetrating the bubble layer and exchanging normally with the fermentation liquid. There is no need to optimize the adjustment mechanism and maintain the current adjustment parameters.

9. An optimization control system for beer fermentation, used to implement an optimization control method for beer fermentation as described in any one of claims 1 to 8, characterized in that: It includes fermentation area division and sensor monitoring module, gas exchange information prediction and analysis module, bubble suppression and oxygen regulation optimization module, feedback and adjustment optimization module, and fermentation process comprehensive recording and strategy improvement module; The fermentation area division and sensor monitoring module divides the top of the fermentation tank into several areas evenly during the fermentation of high-concentration wort, and evenly distributes the fermentation liquid in each area. A sensor network is deployed in each area to obtain gas exchange information in real time. The gas exchange information prediction and analysis module obtains the gas exchange information of each area on the top of the fermenter in real time, analyzes it after acquisition, predicts the degree of oxygen obstruction of the bubble layer formed in each area on the top of the fermenter, and divides each area on the top of the fermenter into a high-barrier area, a medium-barrier area and a low-barrier area according to the prediction results; The bubble suppression and oxygen regulation optimization module builds a bubble suppression and oxygen regulation mechanism based on the division results of each area, and makes different oxygen supply and bubble dissipation adjustments for high barrier area, medium barrier area and low barrier area respectively; Feedback and adjustment optimization module, in the process of adjusting each area by the bubble suppression and oxygen regulation mechanism, obtains gas exchange feedback information of each area in real time, analyzes it after obtaining, evaluates whether the adjustment effect of the mechanism in each area can meet the requirements of oxygen penetrating the bubble layer and exchanging with the fermentation liquid normally, and optimizes the adjustment mechanism according to the evaluation results; The comprehensive record and strategy improvement module of the fermentation process records and conducts real-time and comprehensive analysis of the gas exchange data, adjustment records and fermentation effects during the entire fermentation process, continuously improves the oxygen supply and bubble suppression strategies, and improves the adjustment mechanism in real time.

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