A fermentation parameter intelligent control method, system, terminal and medium

Abstract

The present application relates to a method, system, terminal and medium for intelligent control of fermentation parameters, and belongs to the technical field of enzyme fermentation. The method for intelligent control of fermentation parameters includes: determining the current fermentation stage of the fermentation process; determining the dissolved oxygen target value and the pH target value according to the fermentation stage; obtaining monitoring data, the monitoring data including the actual dissolved oxygen value, the dissolved oxygen change rate, the actual pH value, the pH change rate, the bacterial concentration and the fermentation volume; if the dissolved oxygen change rate is negative, then predicting the pH predicted value for the next n minutes based on the actual dissolved oxygen value and the bacterial concentration; judging whether the error between the pH predicted value and the pH target value is not greater than the error threshold; if so, performing parameter intervention, the parameters including ventilation volume, stirring speed and alkali supplementation amount. The present application has the beneficial effect of being able to accurately control the fermentation parameters to accurately improve the quality of the fermentation product.

Description

Technical Field

[0001] The present application relates to the technical field of enzyme fermentation, and in particular to a method, system, terminal and medium for intelligently controlling fermentation parameters. Background Art

[0002] With the continuous development and application of biotechnology, the fermentation industry continues to expand, encompassing diverse sectors such as food, medicine, and chemicals. Fermentation is a biochemical process that utilizes the metabolic activity of microorganisms under specific conditions to convert organic matter into target products. With the continued development of the fermentation industry, the requirements for fermentation efficiency and product quality are becoming increasingly stringent. To improve fermentation efficiency and product quality, more precise regulation of the fermentation process is necessary. Precisely controlling fermentation parameters can provide a more suitable growth environment for microorganisms, promote their growth and metabolism, and increase the yield and quality of fermentation products. Furthermore, precise regulation can reduce energy and raw material consumption during the fermentation process, lowering production costs and improving the economic benefits of the enterprise.

[0003] Traditional fermentation process control usually relies on manual experience and simple feedback control, which makes it difficult to achieve precise regulation of the fermentation process. The control of dissolved oxygen and pH values is often based on fixed parameter settings, and cannot be adjusted in real time according to the dynamic changes of the fermentation process, thus affecting the quality of the fermentation product. For example, in aerobic fermentation, the control of dissolved oxygen concentration is usually achieved through fixed ventilation volume and stirring speed, but the demand for dissolved oxygen by microorganisms is different in different growth stages. Fixed parameter settings may lead to insufficient or excessive dissolved oxygen supply, affecting the growth and metabolism of microorganisms. Similarly, pH value control is often maintained within a relatively stable range by regularly adding acid-base regulators, but this method cannot respond to rapid changes in pH value in a timely manner, which can easily lead to excessive fluctuations in pH value and affect the fermentation effect. Summary of the Invention

[0004] In order to accurately control fermentation parameters and precisely improve the quality of fermentation products, the present application provides a fermentation parameter intelligent control method, system, terminal and medium.

[0005] In the first aspect, the present application provides a method for intelligently controlling fermentation parameters, which adopts the following technical solutions:

[0006] A method for intelligently controlling fermentation parameters, comprising:

[0007] Determine the current fermentation stage of the fermentation process;

[0008] Determining a target dissolved oxygen value and a target pH value according to the fermentation stage;

[0009] Acquiring monitoring data, including actual dissolved oxygen value, dissolved oxygen change rate, actual pH value, pH change rate, bacterial concentration, and fermentation volume;

[0010] If the dissolved oxygen change rate is negative, the pH condition in the next n minutes is predicted based on the actual dissolved oxygen value and the bacterial cell concentration to obtain a predicted pH value;

[0011] Determining whether an error between the predicted pH value and the target pH value is less than an error threshold;

[0012] If so, parameter intervention is performed, including ventilation volume, stirring speed and alkali supplementation amount.

[0013] By employing the above technical solution, microorganisms have different growth and metabolic characteristics at different fermentation stages, resulting in varying requirements for dissolved oxygen and pH. By determining the current fermentation stage and, in turn, the corresponding dissolved oxygen and pH target values, a suitable growth environment can be provided for the microorganisms, promoting their growth and metabolism, and improving fermentation efficiency and product yield. Clarifying parameter target values for each fermentation stage makes fermentation process control more targeted and operational. Acquiring monitoring data such as the actual dissolved oxygen value, dissolved oxygen change rate, actual pH value, pH change rate, cell concentration, and fermentation volume comprehensively reflects the state of the fermentation process. These parameters are interrelated and influence each other, and comprehensive analysis of them allows for a more accurate understanding of the dynamics of the fermentation process. When the dissolved oxygen change rate is negative, the predicted pH value for the next n minutes is predicted based on the actual dissolved oxygen value and cell concentration, enabling early detection of potential pH trends. Determining whether the error between the predicted pH value and the target pH value is within an acceptable error threshold provides a clear basis for parameter intervention. Parameter intervention is only performed when the error is within an acceptable range, avoiding unnecessary adjustments and minimizing disruption to the fermentation process. At the same time, it can promptly detect abnormal pH changes, ensuring that the fermentation process remains within the target parameter range. Parameter intervention based on the judgment results, adjusting parameters such as ventilation volume, stirring speed, and alkali supplementation, can effectively control dissolved oxygen and pH values, bringing them close to or even reaching target values. Adjusting ventilation volume and stirring speed can affect the supply of dissolved oxygen, while adjusting alkali supplementation can adjust pH. By flexibly adjusting these parameters, precise control can be achieved based on the actual conditions of the fermentation process, improving fermentation efficiency and product quality.

[0014] Optionally, the step of predicting the pH condition in the next n minutes based on the actual dissolved oxygen value and the bacterial cell concentration to obtain a predicted pH value includes:

[0015] The actual dissolved oxygen value and the bacterial cell concentration are input into a pre-built prediction model to obtain the pH change value. The prediction model is: , is the pH change value, To adjust the parameters, is the actual value of dissolved oxygen, is the target value of dissolved oxygen, is the bacterial concentration;

[0016] According to the pH change value, a pH prediction value is obtained, and the pH prediction value .

[0017] Optionally, the specific steps of performing parameter intervention include:

[0018] Obtain dissolved oxygen error value and pH error value, the dissolved oxygen error value , the pH error value ;

[0019] Obtaining a synergistic value according to the dissolved oxygen error value and the pH error value;

[0020] If the synergy value is positive, intervention is performed according to a first regulation rule;

[0021] If the synergy value is negative, an intervention is performed according to a second control rule.

[0022] By adopting the above technical solution, the dissolved oxygen error value and the pH error value are obtained and comprehensively analyzed, which can more comprehensively and accurately reflect the actual state of the fermentation process. During the fermentation process, dissolved oxygen and pH values are key factors affecting microbial growth and metabolism, and the two are interrelated and influence each other. The error of a single parameter may not accurately reflect the actual situation of the fermentation process. However, by comprehensively considering the error values of the two parameters, it is possible to more accurately judge whether the fermentation process deviates from expectations, thereby providing a more reliable basis for subsequent parameter intervention and avoiding the misleading effect of intervention based solely on a single parameter error. The synergistic value can intuitively reflect the combined impact of dissolved oxygen and pH errors, providing a clear judgment standard for subsequent parameter intervention. When the synergistic value is positive or negative, it represents different parameter error combinations. Targeted intervention measures can be taken according to the positive or negative synergistic value, thereby improving the accuracy and effectiveness of parameter intervention. Different positive and negative synergistic values represent different parameter error combinations and interaction patterns. The use of different adjustment rules can make targeted parameter adjustments based on specific situations and improve the effect of parameter intervention. By adopting different adjustment rules according to the positive or negative synergy value, parameter deviations in the fermentation process can be corrected in a timely manner, reducing the problems of microbial growth inhibition and low product synthesis efficiency caused by parameter abnormalities, and ultimately improving the yield and quality of fermentation products.

[0023] Optionally, the step of obtaining a synergistic value according to the dissolved oxygen error value and the pH error value includes:

[0024] The dissolved oxygen error value and the pH error value are input into a pre-trained synergy model to obtain a synergy value; the synergy model is is the synergy value, is the adjustment parameter of the current fermentation stage, is the adjustment weight of the relevant parameters, is the dissolved oxygen change rate, is the rate of pH change.

[0025] Optionally, the first adjustment rule is:

[0026] According to the synergistic value, the stirring speed is increased, the ventilation volume is increased, and the alkali supplementation is suspended;

[0027] New stirring speed is the current stirring speed, is the stirring gain coefficient, The maximum increase allowed in the current fermentation stage;

[0028] New ventilation volume , To initially increase ventilation, is the current ventilation volume, is the ventilation gain coefficient, is the maximum ventilation allowed in the current fermentation stage, MAI is the metabolic activity index, OUR is the oxygen uptake rate, and CER is the carbon dioxide release rate.

[0029] Optionally, the second adjustment rule step includes:

[0030] Determining whether the dissolved oxygen change rate is greater than a set rate threshold;

[0031] If so, calculate the amount of alkali to be added and inject it according to the preset time interval. , V is the fermentation volume;

[0032] Mapping the dissolved oxygen error value and the pH error value to the interval [-1, 1] respectively to obtain a dissolved oxygen mapping value and a pH mapping value;

[0033] Determining an adjustment parameter of a current stirring speed and an adjustment parameter of a current ventilation volume according to the dissolved oxygen mapping value and the pH mapping value;

[0034] adjusting the stirring speed according to the current stirring speed adjustment parameter and adjusting the ventilation volume according to the current ventilation volume adjustment parameter;

[0035] If not, then according to the emergency alkali replenishment model, the alkali replenishment experience value is obtained, and the emergency alkali replenishment model is is the alkali supplement concentration coefficient;

[0036] The alkali supplementation empirical value is injected by a gradient injection method, wherein the gradient injection method is: injecting in m times, each time 80% of the alkali solution is injected through the ejector at the bottom of the fermentation tank, and 20% is dispersedly injected through the nozzle on the inner wall of the fermentation tank.

[0037] By employing this technical solution, when the dissolved oxygen change rate exceeds a set threshold, and considering that rapid changes in dissolved oxygen during fermentation may indicate the production of acidic substances by microbial metabolism, timely and appropriate alkali addition is required to maintain a suitable pH environment. The dissolved oxygen error and pH error values are mapped to the interval [-1, 1] to generate the dissolved oxygen and pH mapping values, respectively. This mapping operation unifies error values of varying magnitudes and ranges into a standardized interval, facilitating subsequent calculations and comparisons. The current stirring speed and aeration adjustment parameters are determined based on the dissolved oxygen and pH mapping values, and the stirring speed and aeration adjustment parameters are adjusted accordingly. This approach comprehensively considers the impact of two key factors, dissolved oxygen and pH, on the fermentation process, achieving precise adjustment of the stirring speed and aeration volume. For example, if the dissolved oxygen mapping value indicates insufficient dissolved oxygen and the pH mapping value indicates excessive acidity, the stirring speed and aeration volume can be appropriately increased, while alkali addition is combined to quickly improve the fermentation environment and promote microbial growth and metabolism. The entire technical solution effectively maintains stable dissolved oxygen and pH levels during fermentation by determining the rate of change in dissolved oxygen, flexibly applying alkali supplementation strategies, and precisely adjusting agitation speed and ventilation volume. A stable environment promotes optimal microbial growth and metabolism, reduces fermentation anomalies caused by environmental fluctuations, and improves fermentation success rates and product quality.

[0038] Optionally, the fermentation parameter intelligent control method further includes:

[0039] If the dissolved oxygen change rate is a positive value, the current ventilation volume is obtained;

[0040] The dissolved oxygen change rate and the current ventilation volume are input into the oxygen reduction empirical model to obtain the ventilation volume change value. The oxygen reduction empirical model is: is the ventilation change value, is the time constant, is the attenuation coefficient;

[0041] According to the ventilation change value, a new ventilation volume is obtained. ;

[0042] The dissolved oxygen change rate and the actual dissolved oxygen value are input into the stirring empirical model to obtain the stirring speed change value. The stirring empirical model is: , is the stirring speed change value, is the dissolved oxygen attenuation factor;

[0043] According to the stirring speed change value, a new stirring speed is obtained. .

[0044] By adopting the above technical solution, during the fermentation process, if the dissolved oxygen change rate is positive, it means that the dissolved oxygen content is increasing. This may be due to changes in microbial metabolic activities, such as transitions in growth stages, substrate consumption and other factors. By obtaining the current ventilation volume and inputting the dissolved oxygen change rate and the current ventilation volume into the oxygen reduction empirical model, the ventilation volume can be accurately adjusted according to actual conditions to adapt to the dissolved oxygen needs of microorganisms at different stages. An appropriate dissolved oxygen level is essential for the growth and metabolism of microorganisms. By accurately adjusting the ventilation volume and stirring speed, a stable and suitable dissolved oxygen environment can be provided for microorganisms, promoting the growth of microorganisms and product synthesis, thereby improving fermentation efficiency and product quality.

[0045] In a second aspect, the present application provides a fermentation parameter intelligent control system, which adopts the following technical solutions:

[0046] A fermentation parameter intelligent control system, comprising:

[0047] A fermentation stage determination module is used to determine the current fermentation stage of the fermentation process;

[0048] a target value determination module, configured to determine a dissolved oxygen target value and a pH target value according to the fermentation stage;

[0049] A production data acquisition module is used to acquire monitoring data, including actual dissolved oxygen value, dissolved oxygen change rate, actual pH value, pH change rate, bacterial concentration, and fermentation volume;

[0050] A judgment module, used to judge whether the dissolved oxygen change rate is a positive value or a negative value;

[0051] a data processing module for predicting the pH condition in the next n minutes based on the actual dissolved oxygen value and the bacterial cell concentration when the dissolved oxygen change rate is negative, so as to obtain a pH prediction value;

[0052] The judgment module is further configured to judge whether the error between the pH prediction value and the pH target value is not greater than an error threshold;

[0053] The parameter adjustment module is used to perform parameter intervention when the judgment module judges that the result is yes. The parameters include ventilation volume, stirring speed and alkali supplementation amount.

[0054] In a third aspect, the present application provides a terminal that adopts the following technical solution:

[0055] A terminal, comprising:

[0056] A memory storing a fermentation parameter intelligent control program;

[0057] The processor is used to execute the program stored in the memory to implement the steps of the above-mentioned fermentation parameter intelligent control method.

[0058] In a fourth aspect, the present application provides a computer-readable storage medium, which adopts the following technical solution:

[0059] A computer-readable storage medium stores a computer program that can be loaded by a processor and execute the above-mentioned fermentation parameter intelligent control method.

[0060] In summary, this application has at least the following beneficial effects:

[0061] Microorganisms have different growth and metabolic characteristics at different fermentation stages, resulting in varying requirements for dissolved oxygen and pH. By determining the current fermentation stage and, in turn, the corresponding dissolved oxygen and pH target values, we can provide a suitable growth environment for microorganisms, promote their growth and metabolism, and improve fermentation efficiency and product yield. Clearly defining parameter target values for each fermentation stage makes fermentation process control more targeted and actionable. Acquiring monitoring data such as the actual dissolved oxygen value, dissolved oxygen change rate, actual pH value, pH change rate, cell concentration, and fermentation volume comprehensively reflects the state of the fermentation process. These parameters are interrelated and influence each other, and comprehensive analysis of them can more accurately grasp the dynamics of the fermentation process. When the dissolved oxygen change rate is negative, predicting the pH value for the next n minutes based on the actual dissolved oxygen value and cell concentration can identify potential pH trends in advance. Determining whether the error between the predicted pH value and the target pH value is within an acceptable error threshold provides a clear basis for parameter intervention. Parameter intervention is only performed when the error is within an acceptable range, avoiding unnecessary adjustments and minimizing disruption to the fermentation process. At the same time, it can promptly detect abnormal pH changes, ensuring that the fermentation process remains within the target parameter range. Parameter intervention based on the judgment results, adjusting parameters such as ventilation volume, stirring speed, and alkali supplementation, can effectively control dissolved oxygen and pH values, bringing them close to or even reaching target values. Adjusting ventilation volume and stirring speed can affect the supply of dissolved oxygen, while adjusting alkali supplementation can adjust pH. By flexibly adjusting these parameters, precise control can be achieved based on the actual conditions of the fermentation process, improving fermentation efficiency and product quality. BRIEF DESCRIPTION OF THE DRAWINGS

[0062] Figure 1 This is a first flow chart of an embodiment of the method of the present application;

[0063] Figure 2 This is a second flow chart of the method embodiment of the present application;

[0064] Figure 3 This is a third flow chart of the method embodiment of the present application;

[0065] Figure 4 This is the fourth flow chart of the method embodiment of the present application. DETAILED DESCRIPTION

[0066] To make the purpose, technical solutions and advantages of the embodiments of the present application clearer, the following will be combined with the appended drawings of the embodiments of the present invention. Figure 1 -Attached Figure 4The technical solutions in the embodiments of the present invention are clearly and completely described. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of them. All other embodiments derived by persons of ordinary skill in the art based on the embodiments of the present invention without inventive effort are within the scope of protection of the present invention.

[0067] The first embodiment of the present application discloses a method for intelligently controlling fermentation parameters. Figure 1 As an embodiment of the fermentation parameter intelligent control method, the fermentation parameter intelligent control method may include S110-S160:

[0068] S110, determining the current fermentation stage of the fermentation process;

[0069] S120, determining a target dissolved oxygen value and a target pH value according to the fermentation stage;

[0070] S130, acquiring monitoring data, including actual dissolved oxygen value, dissolved oxygen change rate, actual pH value, pH change rate, bacterial concentration, and fermentation volume;

[0071] S140, if the dissolved oxygen change rate is negative, predicting the pH in the next n minutes based on the actual dissolved oxygen value and the bacterial cell concentration to obtain a predicted pH value;

[0072] S150, determining whether the error between the pH prediction value and the pH target value is not greater than an error threshold;

[0073] S160: If yes, perform parameter intervention, the parameters including ventilation volume, stirring speed and alkali supplementation amount.

[0074] Specifically, the fermentation process can be divided into three stages: bacterial growth (I), enzyme induction (II), and product synthesis (III). The current fermentation stage can be determined based on fermentation time or changes in physiological indicators. Furthermore, the target dissolved oxygen and pH values for that fermentation stage can be determined based on production processes or historical production data. Monitoring data for each fermentation stage is then acquired using a sensor assembly. The actual dissolved oxygen value can be measured online using a composite membrane oxygen electrode. The rate of change of dissolved oxygen can be calculated by sampling sensor data every second and calculating the DO gradient per unit time (e.g., per minute). The actual pH value can be monitored in real time using a composite glass electrode. The rate of change of pH can be calculated by recording the pH fluctuation per minute and calculating the pH difference between adjacent time points. Bacterial concentration can be measured using a turbidity sensor or capacitance probe. Fermentation volume can be acquired in real time using a load cell (for tank weight monitoring) or an ultrasonic level meter.

[0075] The actual dissolved oxygen value and bacterial concentration are input into the pre-built prediction model to obtain the pH change value. The prediction model is: is the pH change value, To adjust the parameters, is the actual value of dissolved oxygen, is the target value of dissolved oxygen, is the bacterial concentration; then according to the pH change value, the pH predicted value is obtained, the pH predicted value .

[0076] When the error between the pH prediction value and the pH target value is less than or equal to the error threshold, parameter intervention is performed. Figure 2 The parameter intervention steps may include S210-S250:

[0077] S210, obtaining a dissolved oxygen error value and a pH error value;

[0078] S220, obtaining a synergistic value according to the dissolved oxygen error value and the pH error value;

[0079] S230, determining whether the synergy value is a positive value;

[0080] S240, if yes, then intervene according to the first adjustment rule;

[0081] S250: If not, intervene according to the second regulation rule.

[0082] Specifically, the dissolved oxygen error value , pH error value The dissolved oxygen error value and pH error value are input into the pre-trained synergy model to obtain the synergy value; the synergy model is is the synergy value, is the adjustment parameter of the current fermentation stage, is the adjustment weight of the relevant parameters, is the dissolved oxygen change rate, is the rate of pH change.

[0083] The first adjustment rule is:

[0084] According to the synergistic value, increase the stirring speed, increase the ventilation volume and suspend the alkali addition;

[0085] New stirring speed is the current stirring speed, is the stirring gain coefficient, The maximum increase allowed in the current fermentation stage; It means taking the minimum value of the two;

[0086] New ventilation volume , To initially increase ventilation, is the current ventilation volume, is the ventilation gain coefficient, is the maximum ventilation allowed in the current fermentation stage, MAI is the metabolic activity index, OUR is the oxygen uptake rate, and CER is the carbon dioxide release rate.

[0087] Reference Figure 3 If the synergy value is not a positive value, it means that the synergy value is a negative value. Therefore, the specific steps of the second adjustment rule include S310-S370:

[0088] S310, determining whether the dissolved oxygen change rate is greater than a set rate threshold;

[0089] S320, if yes, calculate the amount of alkali supplement and inject it according to the preset time interval;

[0090] S330, mapping the dissolved oxygen error value and the pH error value to the interval [-1, 1] to obtain a dissolved oxygen mapping value and a pH mapping value;

[0091] S340, determining an adjustment parameter of a current stirring speed and an adjustment parameter of a current ventilation volume according to the dissolved oxygen mapping value and the pH mapping value;

[0092] S350, adjusting the stirring speed according to the current stirring speed adjustment parameter and adjusting the ventilation volume according to the current ventilation volume adjustment parameter;

[0093] S360, if not, obtain the alkali replenishment experience value according to the emergency alkali replenishment model;

[0094] S370, adopt gradient injection method to inject alkali supplementation experience value.

[0095] Specifically, the calculation method of the amount of alkali supplement can be: , V is the fermentation volume.

[0096] The error value can be mapped to the [-1,1] interval using linear mapping. Assume that the maximum absolute value of the dissolved oxygen error value is The maximum absolute value of the pH error is , then the dissolved oxygen mapping value and pH mapping values The calculation formula is as follows:

[0097]

[0098] Stirring speed adjustment parameters ; Ventilation adjustment parameters They are all adjustment coefficients of corresponding parameters, which can be determined according to specific fermentation processes, experimental data, historical intervention data, etc.; for example, through multiple fermentation experiments, the adjustment amounts of stirring speed and ventilation volume required to make dissolved oxygen and pH values reach target values are recorded under different dissolved oxygen mapping values and pH mapping values, and then the weight coefficients are fitted using methods such as the least squares method.

[0099] Assume that the current stirring speed is is the adjustment step of stirring speed.

[0100] Assume that the current ventilation volume is is the adjustment step of ventilation volume.

[0101] The emergency alkali replenishment model is is the alkali concentration coefficient.

[0102] The gradient injection method is: inject m times, each time 80% of the alkali solution is injected through the injector at the bottom of the fermentation tank, and 20% is dispersedly injected through the nozzle on the inner wall of the fermentation tank.

[0103] Reference Figure 4 The fermentation parameter intelligent control method also includes S410-S450:

[0104] S410, if the dissolved oxygen change rate is positive, obtain the current ventilation volume;

[0105] S420, inputting the dissolved oxygen change rate and the current ventilation volume into the oxygen reduction empirical model to obtain a ventilation volume change value;

[0106] S430, obtaining a new ventilation volume according to the ventilation volume change value;

[0107] S440, inputting the dissolved oxygen change rate and the actual dissolved oxygen value into the stirring empirical model to obtain a stirring speed change value;

[0108] S450: Obtain a new stirring speed according to the stirring speed change value.

[0109] Specifically, the new ventilation volume The empirical model for oxygen reduction is is the attenuation coefficient.

[0110] New stirring speed The empirical model of stirring is is the stirring speed change value, is the dissolved oxygen attenuation factor.

[0111] The implementation of a scenario in this embodiment is as follows:

[0112] Before adjusting the fermentation parameters, it is necessary to first determine the current fermentation stage of the fermentation process, and then determine the dissolved oxygen target value and pH target value in the fermentation stage; after determination, obtain the monitoring data, and determine whether the dissolved oxygen change rate is positive or negative. If it is negative, the pH in the next n minutes can be predicted based on the actual dissolved oxygen value and the bacterial concentration to obtain the pH prediction value; then determine whether the error between the pH prediction value and the pH target value is not greater than the error threshold. If so, perform parameter intervention; when performing parameter intervention, it is necessary to obtain the dissolved oxygen error value and the pH error value, and then obtain the synergy value according to the synergy model to further determine whether the synergy value is positive or negative. If it is a negative value, if it is a positive value, the stirring speed and ventilation volume are increased according to the synergy value, and the alkali supplementation is suspended; if it is a negative value, it is necessary to further determine whether the dissolved oxygen change rate is greater than the rate threshold. If so, the alkali supplementation amount is calculated and then injected according to the preset time interval; at the same time, the dissolved oxygen error value and the pH error value are respectively mapped to the [-1, 1] interval to obtain the dissolved oxygen mapping value and the pH mapping value, and then the adjustment parameters of the current stirring speed and the current ventilation volume are determined through the dissolved oxygen mapping value and the pH mapping value, so as to adjust the stirring speed according to the adjustment parameters of the current stirring speed and adjust the ventilation volume according to the adjustment parameters of the current ventilation volume.

[0113] Based on the above method embodiment, the second embodiment of the present application discloses a fermentation parameter intelligent control system. As an embodiment of the fermentation parameter intelligent control system, the fermentation parameter intelligent control system may include:

[0114] A fermentation stage determination module is used to determine the current fermentation stage of the fermentation process;

[0115] A target value determination module is used to determine a dissolved oxygen target value and a pH target value according to the fermentation stage;

[0116] The production data acquisition module is used to obtain monitoring data, including the actual value of dissolved oxygen, the rate of change of dissolved oxygen, the actual value of pH, the rate of change of pH, the concentration of bacteria, and the fermentation volume;

[0117] A judgment module is used to judge whether the dissolved oxygen change rate is positive or negative;

[0118] The data processing module is used to predict the pH value in the next n minutes based on the actual dissolved oxygen value and bacterial concentration when the dissolved oxygen change rate is negative;

[0119] The judgment module is further used to judge whether the error between the pH prediction value and the pH target value is not greater than the error threshold;

[0120] The parameter adjustment module is used to perform parameter intervention when the judgment module determines that the result is yes. The parameters include ventilation volume, stirring speed and alkali supplementation amount.

[0121] The modules of the fermentation parameter intelligent control system correspond to the fermentation parameter intelligent control method one by one, and will not be described in detail here.

[0122] The third embodiment of the present application provides a terminal. As an implementation of the terminal, the terminal may include: a memory and a processor; wherein,

[0123] The memory is used to store the fermentation parameter intelligent control program;

[0124] The processor is used to execute the program stored in the memory to implement the steps of the above-mentioned fermentation parameter intelligent control method.

[0125] The memory may be communicatively connected to the processor via a communication bus, and the communication bus may be an address bus, a data bus, a control bus, or the like.

[0126] In addition, the memory may include a random access memory (RAM) and may also include a non-volatile memory (NVM), such as at least one disk storage.

[0127] The processor can be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it can also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc.

[0128] The fourth embodiment of the present application provides a computer-readable storage medium storing a computer program that can be loaded by a processor and execute the above-mentioned fermentation parameter intelligent control method.

[0129] Computer-readable storage media 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 includes one or more available media. Available media can include magnetic media (e.g., floppy disks, hard disks, magnetic tapes), optical media (e.g., DVDs), or semiconductor media (e.g., solid-state drives).

[0130] The above are all preferred embodiments of the present application and are not intended to limit the scope of protection of the present application. Unless otherwise specified, any feature disclosed in this specification (including the abstract and drawings) may be replaced by other equivalent or similar features. In other words, unless otherwise specified, each feature is merely an example of a series of equivalent or similar features.

Claims

1. A method for intelligently controlling fermentation parameters, characterized in that: include: Determine the current fermentation stage of the fermentation process; Determining a target dissolved oxygen value and a target pH value according to the fermentation stage; Acquiring monitoring data, including actual dissolved oxygen value, dissolved oxygen change rate, actual pH value, pH change rate, bacterial concentration, and fermentation volume; If the dissolved oxygen change rate is negative, the pH condition in the next n minutes is predicted based on the actual dissolved oxygen value and the bacterial cell concentration to obtain a predicted pH value; Determining whether an error between the predicted pH value and the target pH value is less than an error threshold; If yes, parameter intervention is performed, including ventilation volume, stirring speed and alkali supplementation amount; The specific steps of performing parameter intervention include: Obtain dissolved oxygen error value and pH error value, the dissolved oxygen error value , the pH error value ; Obtaining a synergistic value according to the dissolved oxygen error value and the pH error value; If the synergy value is positive, intervention is performed according to a first regulation rule; If the synergy value is negative, intervention is performed according to the second regulation rule; The step of obtaining a synergistic value according to the dissolved oxygen error value and the pH error value comprises: The dissolved oxygen error value and the pH error value are input into a pre-trained synergy model to obtain a synergy value; the synergy model is , is the synergy value, is the adjustment parameter of the current fermentation stage, is the adjustment weight of the relevant parameters, is the dissolved oxygen change rate, is the rate of pH change.

2. A fermentation parameter intelligent control method according to claim 1, characterized in that: The step of predicting the pH condition in the next n minutes based on the actual dissolved oxygen value and the bacterial cell concentration to obtain a predicted pH value includes: The actual dissolved oxygen value and the bacterial cell concentration are input into a pre-built prediction model to obtain the pH change value. The prediction model is: is the pH change value, To adjust the parameters, is the actual value of dissolved oxygen, is the target value of dissolved oxygen, is the bacterial concentration; According to the pH change value, a pH prediction value is obtained, and the pH prediction value .

3. A fermentation parameter intelligent control method according to claim 1, characterized in that: The first adjustment rule is: According to the synergistic value, the stirring speed is increased, the ventilation volume is increased, and the alkali supplementation is suspended; New stirring speed , is the current stirring speed, is the stirring gain coefficient, The maximum increase allowed in the current fermentation stage; New ventilation volume , To initially increase ventilation, is the current ventilation volume, is the ventilation gain coefficient, is the maximum ventilation allowed in the current fermentation stage, MAI is the metabolic activity index, OUR is the oxygen uptake rate, and CER is the carbon dioxide release rate.

4. A fermentation parameter intelligent control method according to claim 1, characterized in that: The steps of the second adjustment rule include: Determining whether the dissolved oxygen change rate is greater than a set rate threshold; If yes, calculate the amount of alkali to be added and inject it according to the preset time interval. , V is the fermentation volume; Mapping the dissolved oxygen error value and the pH error value to the interval [-1, 1] respectively to obtain a dissolved oxygen mapping value and a pH mapping value; Determining an adjustment parameter of a current stirring speed and an adjustment parameter of a current ventilation volume according to the dissolved oxygen mapping value and the pH mapping value; adjusting the stirring speed according to the current stirring speed adjustment parameter and adjusting the ventilation volume according to the current ventilation volume adjustment parameter; If not, then according to the emergency alkali replenishment model, the alkali replenishment experience value is obtained, and the emergency alkali replenishment model is is the alkali supplement concentration coefficient; The alkali supplementation empirical value is injected by a gradient injection method, wherein the gradient injection method is: injecting in m times, each time 80% of the alkali solution is injected through the ejector at the bottom of the fermentation tank, and 20% is dispersedly injected through the nozzle on the inner wall of the fermentation tank.

5. The method for intelligently controlling fermentation parameters according to claim 1, wherein: The fermentation parameter intelligent control method further includes: If the dissolved oxygen change rate is a positive value, the current ventilation volume is obtained; The dissolved oxygen change rate and the current ventilation volume are input into the oxygen reduction empirical model to obtain the ventilation volume change value. The oxygen reduction empirical model is: is the ventilation change value, is the time constant, is the attenuation coefficient; According to the ventilation change value, a new ventilation volume is obtained. ; The dissolved oxygen change rate and the actual dissolved oxygen value are input into the stirring empirical model to obtain the stirring speed change value. The stirring empirical model is: is the stirring speed change value, is the dissolved oxygen attenuation factor; According to the stirring speed change value, a new stirring speed is obtained. .

6. A fermentation parameter intelligent control system, characterized in that: The method for intelligently controlling fermentation parameters according to any one of claims 1 to 5 comprises: A fermentation stage determination module is used to determine the current fermentation stage of the fermentation process; a target value determination module, configured to determine a dissolved oxygen target value and a pH target value according to the fermentation stage; A production data acquisition module is used to acquire monitoring data, including actual dissolved oxygen value, dissolved oxygen change rate, actual pH value, pH change rate, bacterial concentration, and fermentation volume; A judgment module, used to judge whether the dissolved oxygen change rate is a positive value or a negative value; a data processing module for predicting the pH condition in the next n minutes based on the actual dissolved oxygen value and the bacterial cell concentration when the dissolved oxygen change rate is negative, so as to obtain a pH prediction value; The judgment module is further configured to judge whether the error between the pH prediction value and the pH target value is not greater than an error threshold; The parameter adjustment module is used to perform parameter intervention when the judgment module judges that the result is yes. The parameters include ventilation volume, stirring speed and alkali supplementation amount.

7. A terminal, characterized in that: include: A memory storing a fermentation parameter intelligent control program; A processor is used to execute the program stored in the memory to implement the steps of the fermentation parameter intelligent control method as described in any one of claims 1 to 5.

8. A computer-readable storage medium, characterized in that The device stores a computer program that can be loaded by a processor and execute the method for intelligently controlling fermentation parameters as described in any one of claims 1 to 5.

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