Microbial fermentation enzyme system and practical application method thereof

Abstract

The present application relates to the technical field of biomass conversion materials, and discloses a microbial fermentation enzyme production system and a practical application method thereof, which comprises the following steps: collecting the load torque and the dissolved oxygen dissipation rate of a biomass substrate fermentation system; determining the local viscous resistance coefficient of each spatial unit inside a fermentation tank by using a mass transfer distribution field model; identifying a fluid stagnation shielding boundary and calculating a mass transfer metabolic barrier index based on the local viscous resistance coefficient; outputting an adjustment instruction when the index exceeds a preset threshold; and controlling the stirring mechanism to change the stirring speed in a pulse mode to destroy the fluid stagnation shielding boundary. Through accurate identification of the spatial heterogeneity of the flow field, the present application cooperatively regulates energy input and metabolic oxygen distribution, thereby improving substrate conversion efficiency and enzyme protein synthesis capacity under the premise of ensuring the integrity of the enzyme-producing microbial mycelium structure.

Description

Technical Field

[0001] This invention belongs to the field of biomass conversion materials technology, and in particular relates to a microbial fermentation enzyme production system and its practical application method. Background Technology

[0002] Currently, the large-scale production of industrial enzyme preparations typically utilizes the biotransformation of biomass materials by microorganisms. By adding biomass substrates such as agricultural waste to the fermentation system, the target protein is synthesized through the metabolic mechanisms of microorganisms, which is the core production method in the field of biomass conversion. As the demand for increased single-batch enzyme production increases, the increase in the initial biomass substrate concentration causes the fermentation broth system to exhibit strong non-Newtonian fluid characteristics. Its apparent viscosity fluctuates with substrate degradation and generates obvious local flow dead zones inside the reactor, leading to a decrease in the gas-liquid mass transfer coefficient.

[0003] Under these conditions, because the microbial cells are in a hypoxic microenvironment, carbon metabolism shifts from target enzyme synthesis to primary metabolism. Measures such as increasing stirring speed or feeding at a fixed rate fail to recognize the spatial heterogeneity of the fermentation broth, leading to a misalignment between energy injection and actual spatial resistance distribution. This not only fails to improve mass transfer in dead zones but also causes mechanical damage to the enzyme-producing mycelium due to excessive shear force. Regarding hardware improvements and control logic, for example, Chinese invention patent application CN117535119A discloses a fermenter and its method of use that can precisely control high-viscosity fermentation processes. Liquid addition components and concentration sensors are installed at the segmented sections of the tank. Combined with mechanical adjustment of the stirring blade tilt angle, feeding intervention is used to intervene in the fermentation microenvironment. Discrete point monitoring and a passive feedback mechanism for steady-state mechanical compensation are employed. However, in the highly spatially heterogeneous environment of the high-solids biomass system, the sensors are affected by local concentration polarization or material encapsulation, and the feedback signal cannot characterize the evolution of the overall rheological field inside the tank. Due to the lack of quantitative identification capability of the three-dimensional topological morphology of the mass transfer metabolic barrier inside the tank, local mechanical adjustment cannot penetrate the high-viscosity shielding layer formed by uneven material degradation. Therefore, while ensuring the integrity of the mycelial structure, it cannot decouple the substrate conversion efficiency and energy input.

[0004] Therefore, the technical problem to be solved by this invention is how to match the spatiotemporal coupling of substrate degradation rheological evolution and cellular metabolic oxygen demand in a high solids biomass system, eliminate mass transfer dead zones by utilizing physical spatial feature feedback, and maintain hyphal structural stability. Summary of the Invention

[0005] To address the problems mentioned in the background art, the technical solution of the present invention is as follows: A practical application method of a microbial fermentation enzyme production system, comprising the following steps:

[0006] Step 101: Real-time acquisition of driving load torque data and dissolved oxygen dissipation rate data of fermentation system containing biomass conversion material substrate and enzyme-producing microorganisms.

[0007] Step 102: Map the load torque and dissolved oxygen dissipation rate to the preset in-tank mass transfer distribution field model to determine the local viscous drag coefficient of each spatial unit in the fermentation system; wherein, the spatial unit is obtained by meshing the three-dimensional space inside the fermenter, and the in-tank mass transfer distribution field model is used to quantitatively describe the non-Newtonian fluid rheological properties, dissolved oxygen osmotic pressure gradient and multiphase flow field spatial heterogeneity distribution caused by biomass conversion materials in the fermentation system;

[0008] Step 103: Based on the local fluid damping coefficient of each grid point, identify the high viscosity mass transfer shielding boundary in the non-Newtonian fluid stagnation state inside the fermentation system, and calculate the volume ratio of the high viscosity mass transfer shielding boundary in the mass transfer distribution field model inside the tank, so as to construct the mass transfer metabolic barrier index characterizing the substrate degradation resistance.

[0009] Step 104: Determine whether the mass transfer metabolic barrier index exceeds the preset threshold. If it does, output a flow field shear distribution correction command for the fermentation system based on the geometric center coordinates and evolution trend of the high viscosity mass transfer shield boundary. The physical integrity of the high viscosity mass transfer shield boundary is destroyed by adjusting the stirring frequency in a pulse manner, thereby achieving a forced reset of the microenvironment concentration gradient.

[0010] Preferably, the establishment of the local fluid damping coefficient of each grid point in the fermentation system in step 102 includes: extracting the real-time change slope of the driving load torque data and the decay fluctuation rate of the dissolved oxygen dissipation rate data; defining the real-time change slope as the rheological physical damping component and the decay fluctuation rate as the respiratory metabolic damping component; and updating the state vector of each grid point in the corresponding spatial coordinate in the mass transfer distribution field model in the tank by using the nonlinear correlation weight between the rheological physical damping component and the respiratory metabolic damping component.

[0011] Preferably, step 104, which involves forcibly resetting the concentration gradient of the microenvironment, includes: obtaining the biomass substrate feed rate of the fermentation system at the current fermentation stage; and simultaneously adjusting the biomass substrate feed rate and the pulse response frequency of the stirring mechanism according to the rate of change of the mass transfer metabolic barrier index, so that the newly added substrate stream can penetrate the viscous layer of the high-viscosity mass transfer shield boundary.

[0012] Preferably, step 101 further includes obtaining the exhaust gas from the fermentation system. Concentration data; Step 103 involves constructing the mass transfer metabolic barrier index, including based on exhaust gas... The cell-specific enzyme production rate was calculated from the concentration data; the cell-specific enzyme production rate was then used to calibrate and correct the volume ratio of the high-viscosity mass transfer shield boundary.

[0013] Preferably, step 103, identifying the high-viscosity mass transfer shielding boundary in the non-Newtonian fluid stagnation state inside the fermentation system, includes: identifying continuous grid regions in the mass transfer distribution field model inside the tank where the local fluid damping coefficient is greater than a preset critical viscosity value; calculating the ratio of surface area to volume of the continuous grid regions, and defining the ratio of surface area to volume as the morphological complexity of the shielding layer.

[0014] Preferably, in step 104, the frequency increment of the pulse-type adjustment of the stirring frequency is... Satisfy the following formula: Where β is the rheological correction factor. For the volume of the high-viscosity mass transfer shielding boundary envelope, The total volume of the fermentation system. The preset maximum shear strength threshold that the mycelium can withstand. This represents the real-time average shear strength in the mass transfer distribution field model inside the tank.

[0015] Preferably, after step 104, the method further includes: monitoring the ablation rate of the high-viscosity mass transfer shield boundary after implementing pulsed adjustment of the stirring frequency; if the ablation rate is lower than a preset threshold, adjusting the axial tilt angle of the stirring blades inside the fermentation system, and physically stripping the high-viscosity mass transfer shield boundary by changing the momentum distribution ratio of the axial flow and the radial flow.

[0016] Preferably, determining whether the mass transfer metabolic barrier index exceeds a preset threshold in step 104 includes: dynamically setting a preset threshold based on the average length of the mycelium of enzyme-producing microorganisms in the fermentation system; synchronously reducing the preset threshold when the average length of the mycelium increases, so as to trigger the flow field shear distribution correction command in advance; and outputting the flow field shear distribution correction command for the fermentation system in step 104 includes: resolving the radial coordinates of the high-viscosity mass transfer shield boundary in the fermentation system; and adjusting the power output of the stirring layers at different heights in the fermentation system based on the radial coordinates.

[0017] Preferably, the method is used for the enzymatic hydrolysis process of high solids content biomass conversion materials. Through closed-loop feedback of the mass transfer metabolic barrier index, the dissolved oxygen osmotic pressure of the fermentation system is maintained while the instantaneous shear force generated by the pulsed adjustment of the stirring frequency is limited, thus ensuring the integrity of the mycelial structure of the enzyme-producing microorganisms.

[0018] A microbial fermentation enzyme production system, and a practical application method for the microbial fermentation enzyme production system.

[0019] Compared with existing technologies, the microbial fermentation enzyme production system and its practical application method of the present invention have the following advantages:

[0020] 1. In microbial fermentation enzyme production systems, this method addresses the spatial mass transfer heterogeneity constraint commonly found in high-solids fermentation systems. By using real-time acquired torque data and dissolved oxygen dissipation rate as boundary constraints and parsing them into a pre-set three-dimensional geometric mesh model, discrete global one-dimensional physical parameters are converted into node feature vectors characterizing the spatial state within the tank. This mechanism enables dynamic modeling of the geometric evolution of the mass transfer metabolic barrier within the fermenter, identifying the spatial dead zone envelope surface formed by uneven material degradation. Compared to traditional feedback logic that relies solely on a single scalar threshold, this method provides accurate identification capabilities for spatial topological distortions, ensuring a high degree of matching between energy injection actions and the physical resistance distribution of the three-dimensional viscous boundary within the tank.

[0021] 2. Establish a cell protection system based on physical topological state recognition and metabolic parameter interlocking. The system integrates the temporal characteristics of torque variation, dissolved oxygen variation slope, and exhaust carbon dioxide concentration. It constructs a collaborative judgment path driven by physical resistance and physiological metabolic indicators. By calculating the volume ratio of the isolation envelope surface in the grid model, it achieves an objective characterization of the degree of mass transfer deterioration. This logic avoids the accidental triggering of high shear action due to a simple surge in oxygen demand during the vigorous growth period of microorganisms. It prevents brittle mycelia from being mechanically torn at the mechanism level. While maintaining the dissolved oxygen penetration of the fermentation broth, it ensures the integrity of the cell structure of the microbial community and keeps the metabolic flow stable on the synthesis pathway of the target enzyme.

[0022] 3. To achieve spatiotemporal coupling between the rheological evolution of biomass substrate degradation and the oxygen demand of cell metabolism, this method utilizes the hindrance deformation weights of grid nodes to guide the synchronous operation of the feed mechanism and the stirring mechanism, so that the substrate replenishment sequence precisely corresponds to the rheological phase transition nodes of the system. Through dynamic monitoring of the geometric features of the isolation envelope, the system automatically triggers deformation countermeasures when it determines that there is a risk of topological collapse in the grid model. Through pulsed rotation speed adjustment, it penetrates the high-viscosity boundary layer and resets the concentration gradient of the microenvironment in conjunction with the underlying physical stripping mechanism. This shift in thinking from point control to spatial geometric morphology repair eliminates the mass transfer dead zone in high solids content systems and improves substrate conversion efficiency. Attached Figure Description

[0023] Figure 1 This is a flowchart of the mass transfer state identification and adaptive pulse regulation of the microbial fermentation enzyme production system of the present invention;

[0024] Figure 2 This is a logic diagram of the construction and calibration of the mass transfer metabolic barrier index based on multidimensional parameter mapping in this invention. Detailed Implementation

[0025] The technical solutions of the embodiments of this application will be clearly described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of this application are within the scope of protection of this application.

[0026] A practical application method for a microbial fermentation enzyme production system includes the following steps:

[0027] Step 101: Real-time acquisition of driving load torque data and dissolved oxygen dissipation rate data of fermentation system containing biomass conversion material substrate and enzyme-producing microorganisms.

[0028] Step 102: Map the load torque and dissolved oxygen dissipation rate to the preset in-tank mass transfer distribution field model to determine the local viscous drag coefficient of each spatial unit in the fermentation system; wherein, the spatial unit is obtained by meshing the three-dimensional space inside the fermenter, and the in-tank mass transfer distribution field model is used to quantitatively describe the non-Newtonian fluid rheological properties, dissolved oxygen osmotic pressure gradient and multiphase flow field spatial heterogeneity distribution caused by biomass conversion materials in the fermentation system;

[0029] Step 103: Based on the local fluid damping coefficient of each grid point, identify the high viscosity mass transfer shielding boundary in the non-Newtonian fluid stagnation state inside the fermentation system, and calculate the volume ratio of the high viscosity mass transfer shielding boundary in the mass transfer distribution field model inside the tank, so as to construct the mass transfer metabolic barrier index characterizing the substrate degradation resistance.

[0030] Step 104: Determine whether the mass transfer metabolic barrier index exceeds the preset threshold. If it does, output a flow field shear distribution correction command for the fermentation system based on the geometric center coordinates and evolution trend of the high viscosity mass transfer shield boundary. The physical integrity of the high viscosity mass transfer shield boundary is destroyed by adjusting the stirring frequency in a pulse manner, thereby achieving a forced reset of the microenvironment concentration gradient.

[0031] Preferably, the establishment of the local fluid damping coefficient of each grid point in the fermentation system in step 102 includes: extracting the real-time change slope of the driving load torque data and the decay fluctuation rate of the dissolved oxygen dissipation rate data; defining the real-time change slope as the rheological physical damping component and the decay fluctuation rate as the respiratory metabolic damping component; and updating the state vector of each grid point in the corresponding spatial coordinate in the mass transfer distribution field model in the tank by using the nonlinear correlation weight between the rheological physical damping component and the respiratory metabolic damping component.

[0032] Preferably, step 104, which involves forcibly resetting the concentration gradient of the microenvironment, includes: obtaining the biomass substrate feed rate of the fermentation system at the current fermentation stage; and simultaneously adjusting the biomass substrate feed rate and the pulse response frequency of the stirring mechanism according to the rate of change of the mass transfer metabolic barrier index, so that the newly added substrate stream can penetrate the viscous layer of the high-viscosity mass transfer shield boundary.

[0033] Preferably, step 101 further includes obtaining the exhaust gas from the fermentation system. Concentration data; Step 103 involves constructing the mass transfer metabolic barrier index, including based on exhaust gas... The cell-specific enzyme production rate was calculated from the concentration data; the cell-specific enzyme production rate was then used to calibrate and correct the volume ratio of the high-viscosity mass transfer shield boundary.

[0034] Preferably, step 103, identifying the high-viscosity mass transfer shielding boundary in the non-Newtonian fluid stagnation state inside the fermentation system, includes: identifying continuous grid regions in the mass transfer distribution field model inside the tank where the local fluid damping coefficient is greater than a preset critical viscosity value; calculating the ratio of surface area to volume of the continuous grid regions, and defining the ratio of surface area to volume as the morphological complexity of the shielding layer.

[0035] Preferably, in step 104, the frequency increment of the pulse-type adjustment of the stirring frequency is... Satisfy the following formula: Where β is the rheological correction factor. For the volume of the high-viscosity mass transfer shielding boundary envelope, The total volume of the fermentation system. The preset maximum shear strength threshold that the mycelium can withstand. This represents the real-time average shear strength in the mass transfer distribution field model inside the tank.

[0036] Preferably, after step 104, the method further includes: monitoring the ablation rate of the high-viscosity mass transfer shield boundary after implementing pulsed adjustment of the stirring frequency; if the ablation rate is lower than a preset threshold, adjusting the axial tilt angle of the stirring blades inside the fermentation system, and physically stripping the high-viscosity mass transfer shield boundary by changing the momentum distribution ratio of the axial flow and the radial flow.

[0037] Preferably, determining whether the mass transfer metabolic barrier index exceeds a preset threshold in step 104 includes: dynamically setting a preset threshold based on the average length of the mycelium of enzyme-producing microorganisms in the fermentation system; synchronously reducing the preset threshold when the average length of the mycelium increases, so as to trigger the flow field shear distribution correction command in advance; and outputting the flow field shear distribution correction command for the fermentation system in step 104 includes: resolving the radial coordinates of the high-viscosity mass transfer shield boundary in the fermentation system; and adjusting the power output of the stirring layers at different heights in the fermentation system based on the radial coordinates.

[0038] Preferably, the method is used for the enzymatic hydrolysis process of high solids content biomass conversion materials. Through closed-loop feedback of the mass transfer metabolic barrier index, the dissolved oxygen osmotic pressure of the fermentation system is maintained while the instantaneous shear force generated by the pulsed adjustment of the stirring frequency is limited, thus ensuring the integrity of the mycelial structure of the enzyme-producing microorganisms.

[0039] A microbial fermentation enzyme production system, and a practical application method for the microbial fermentation enzyme production system.

[0040] Example 1: In the continuous operation of industrial-grade fermentation to produce enzyme preparations using agricultural waste as a high-solids biomass conversion substrate, as the concentration of biomass substrate in the fermentation system increases, the fermentation broth system exhibits non-Newtonian fluid characteristics, the apparent viscosity increases and forms a spatial heterogeneous distribution inside the reactor, and the high-viscosity fluid constructs a local flow field dead zone in the outer region of the reactor that hinders the mass transfer of the gas-liquid-solid three phases; conventional control logic relies on the acquisition of global one-dimensional physical quantities to trigger whole-reactor mechanical feedback. This control method leads to energy concentration in the central flow domain, and the outer viscous boundary layer is in a microenvironment of oxygen starvation. The continuously output high shear force causes mechanical breakage of the enzyme-producing microfilament cells in a fragile state of logarithmic growth phase, resulting in a physical conflict between the rheological evolution of substrate degradation and the oxygen demand of cell metabolism.

[0041] To resolve the physical contradiction between the mass transfer barrier and the maintenance of hyphal structure integrity in a multiphase flow system, the processor reads a pre-set in-tank mass transfer distribution field model from memory, acquires real-time driving load torque data and dissolved oxygen dissipation rate data of the fermentation system containing biomass conversion substrates and enzyme-producing microorganisms, and parses the acquired driving load torque data and dissolved oxygen dissipation rate data into a boundary constraint data sequence. Based on this boundary constraint data sequence, the processor executes a node topology reconstruction algorithm in the in-tank mass transfer distribution field model to determine the local viscous drag coefficient of each spatial unit. The specific mapping execution logic is as follows: the system sampling frequency of the driving load torque data and dissolved oxygen dissipation rate data is set to 50Hz, and the processor calculates the real-time change slope of the driving load torque data and the decay fluctuation rate of the dissolved oxygen dissipation rate data every 2000ms, which are respectively used as the rheological physical damping component and the respiratory metabolic damping component. A data array lookup table is set up. The horizontal addressing index of this data array lookup table is a discretized rheological physical damping component, and the vertical addressing index is a discretized respiratory metabolic damping component. The values ​​stored in the table are the local viscous resistance benchmark values ​​obtained by offline rheometer gradient testing before production. The processor inputs these two damping components acquired in real time into the data array lookup table, and uses the nearest neighbor node addressing logic to output the corresponding values ​​directly as the nonlinear correlation weights, which are then assigned to the local viscous resistance coefficients of each spatial unit. This avoids complex partial differential equation calculations and identifies the high-viscosity mass transfer shielding boundary in the non-Newtonian fluid stagnation state inside the fermentation system based on the local viscous resistance coefficient. The volume proportion of the high-viscosity mass transfer shielding boundary in the in-tank mass transfer distribution field model is calculated to construct a mass transfer metabolic barrier index characterizing the substrate degradation resistance. The calculation logic of this mass transfer metabolic barrier index includes a strain scalar mapped from the basic parameters. The mapping constraint relationship is ,in, For strain scalar, The driving load torque data represents the driving resistance at the current moment. The reference torque for sterile water under no-load conditions. The value is the derivative of the real-time dissolved oxygen concentration with respect to time, α is a geometrical proportionality constant, and ϵ is a compensation value to prevent the denominator from being zero; the processor determines whether the mass transfer metabolic barrier index exceeds the preset threshold.

[0042] When the mass transfer metabolic barrier index does not exceed the preset threshold, the processor controls the feed mechanism to maintain the injection signal of the biomass conversion material substrate and maintain the initial stirring frequency. When uneven material degradation leads to mass transfer deterioration and the cell-specific enzyme production rate calculated by the processor from the carbon dioxide concentration data of the fermentation system shows a downward trend, the processor determines that the mass transfer metabolic barrier index exceeds the preset threshold. Based on the geometric center coordinates and evolution trend of the high-viscosity mass transfer shield boundary, the processor outputs a flow field shear distribution correction command for the fermentation system. The flow field shear distribution correction command drives the bottom actuator to disrupt the physical integrity of the high-viscosity mass transfer shield boundary by adjusting the stirring frequency in a pulse manner, thereby forcibly resetting the microenvironment concentration gradient. By synchronously adjusting the biomass substrate feed rate and the pulse response frequency of the stirring mechanism, the new substrate stream penetrates the viscous layer of the high-viscosity mass transfer shield boundary, enabling the energy injection path to achieve the desired effect. Spatial matching restores the rheological stability of the fermentation system, guiding the internal carbon metabolism flux to stabilize within the target enzyme protein synthesis pathway. Addressing the technical deficiency of lacking quantitative definitions for physiological metabolic indicators in the fermentation control logic, the fermentation control system initiates a metabolic baseline mapping procedure before introducing gas-phase active parameters. The operating terminal acquires seed culture homologous to the target enzyme-producing strain and inoculates it into a test reactor equipped with a tail gas chromatography-mass spectrometer (GC-MS). The strain is cultured to the logarithmic growth phase under constant dissolved oxygen conditions without mass transfer limitations. The GC-MS continuously samples and outputs a carbon dioxide concentration sequence. The processor extracts the highest slope segment of this sequence during the logarithmic growth phase as the baseline metabolic flux parameter. The control bus gradually reduces the aeration flow rate of the test reactor according to a predetermined decay step size to approach the anoxic critical point of the enzyme-producing microorganism. Simultaneously, the inflection point slope of the nonlinear decay of the carbon dioxide release rate caused by anoxic stress in the enzyme-producing microorganism is extracted. The processor will calculate the slope of the inflection point. The product of the coefficient λ, which is the compensation coefficient for the inherent measurement error of the characterization system, is locked as the preset gas phase active threshold. This parameter calibration step transforms the physiological metabolic transition state into a physical constant based on objective fluid dynamics and the intrinsic metabolic properties of the strain. It establishes a quantitative benchmark for logical comparison of the change rate of characteristic components of exhaust carbon dioxide concentration, eliminating the risk of misjudgment of metabolic interlocking actions caused by batch differences of strains.

[0043] Example 2: Addressing the spatial dead zone problem caused by non-Newtonian fluid characteristics in the later stages of fermentation of high-solids biomass conversion materials, a verification platform based on a standard industrial-grade fermenter was constructed. This platform is equipped with a dynamic torque sensor with a measurement resolution of 0.1 N·m and an optical dissolved oxygen probe with a response delay of less than 5 s. To reproduce the physical interference of the industrial environment, Gaussian white noise with a signal-to-noise ratio of 20 dB was actively superimposed on the experimental signal source to simulate the power frequency vibration interference of mechanical transmission components. Simultaneously, a high-frequency pulsating disturbance signal caused by bubble bursting was injected into the dissolved oxygen signal acquisition channel. The control group used a single global torque feedback control method to increase the constant stirring frequency, while the experimental group used the control method of this invention, which uses pulse-based adjustment of the flow field shear distribution based on the mass transfer metabolic barrier index. All raw acquired data were directly used as the bottom layer input without smoothing, and the mass transfer metabolic barrier index was preset to a threshold. The logic for determining the threshold is based on the balance between the tensile yield strength of the enzyme-producing mycelium and the oxygen demand for substrate degradation. If the threshold is lower than the set lower limit, it will frequently trigger high-shear stirring commands, tearing apart the enzyme-producing mycelium in the logarithmic growth phase. If the threshold is higher than the set upper limit, it will cause the outer area of ​​the reactor to fall into an oxygen-starved state, causing a shift in the carbon metabolism pathway. The processor establishes a function mapping relationship based on the critical shear tolerance scalar of the fermentation strain and the thixotropic recovery time constant of the non-Newtonian fluid boundary layer. When the carbon dioxide release rate characteristic component obtained by the exhaust gas analyzer is in the rising phase, the preset threshold shifts towards the upper limit of the value range to prioritize maintaining the integrity of the mycelial structure. To verify the adaptability of this logic, an experimental system with three initial biomass substrate mass concentration gradients of 15%, 25%, and 35% was constructed to characterize the fluid viscosity and mass transfer resistance intensity under mild, moderate, and extreme conditions, respectively.

[0044] During the experimental process at a substrate concentration of 25%, the apparent viscosity of the fermentation system increased, and the raw drive load torque data output by the dynamic torque sensor exhibited wide-frequency oscillations. The processor read the preset in-tank mass transfer distribution field model from the memory, received the raw signal, and removed high-frequency white noise using a moving average difference algorithm, outputting the drive load torque data at the current moment. The derivative of real-time dissolved oxygen concentration with respect to time The processor uses the aforementioned formula structure to calculate the strain scalar. By combining the local viscous drag coefficients of each spatial unit to extract the high-viscosity mass transfer shielding boundary, the continuously collected data showed nonlinear evolution characteristics. When fermentation lasted for 72.4 hours, the volume ratio of the high-viscosity mass transfer shielding boundary showed a nonlinear jump, and the synchronous real-time dissolved oxygen dissipation rate data showed an exponential decay, indicating that the spatial mass transfer dead zone was substantially formed. At this time, the calculated mass transfer metabolic barrier index crossed the preset threshold, confirming the model's ability to capture the topological distortion of the bottom local dead zone.

[0045] When the mass transfer metabolic barrier index exceeds a preset threshold, the processor outputs a flow field shear distribution correction command, driving the underlying mechanism to start pulse stirring and speed up according to a preset frequency and duty cycle, resetting the microenvironment concentration gradient. The measured data of the final fermentation under different substrate concentration gradients show the quantitative correlation between the technical effect and the mass transfer resistance intensity. Under the 15% concentration condition, the target enzyme protein specific productivity of both the experimental group and the control group remained at the baseline level. Under the 25% concentration condition, the target enzyme protein specific productivity of the experimental group reached 124.6 U / mg, while the measured value of the control group was 105.1 U / mg. When the substrate concentration reached the extreme boundary condition of 35%, the batch synthesis of the control group was interrupted due to cell autolysis caused by local oxygen depletion. The measured enzyme protein specific productivity of the experimental group remained at 102.7 U / mg. The gradient verification results confirm that the pulse shear correction intervention mechanism based on the mass transfer metabolic barrier index overcomes the technical problem of mass transfer deterioration in non-Newtonian fluid systems and achieves synergy between substrate conversion efficiency and microbial physiological activity.

[0046] Example 3: In an industrial-grade fermentation scenario using agricultural waste as a substrate for high-solids biomass conversion, the apparent viscosity of the fermentation broth increases with increasing substrate concentration, forming local dead zones in the flow field that hinder multiphase mass transfer. The processor receives real-time drive load torque data and real-time dissolved oxygen concentration data characterizing the state of the fermentation system. The Kriging space interpolation algorithm is used to map the above-mentioned sensing data to a preset three-dimensional geometric mesh model. The preset in-tank mass transfer distribution field model includes a flow field reference empirical matrix built into the memory, which is generated during the calibration stage before the equipment is put into production. The calibration procedure includes injecting a substrate that simulates a non-Newtonian fluid with a viscosity gradient covering the entire fermentation cycle into the reactor and traversing all stirring speed levels within the rated range. The computational fluid dynamics simulation and offline multi-dimensional array test sensors output three-dimensional spatial node feature parameters under each given working condition are extracted. A deterministic mapping lookup table is constructed, consisting of drive load torque, macroscopic scalar features, dissolved oxygen state at measuring points, and local viscous resistance reference values ​​of each three-dimensional spatial unit of the reactor.

[0047] When the fermentation enzyme production system is operating online, the processor combines the real-time acquired drive load torque data with the dissolved oxygen dissipation rate data collected by the fixedly installed optical dissolved oxygen probe into a real-time addressing feature vector. This vector is then traversed and searched within the flow field baseline empirical matrix. The processor uses the multidimensional Euclidean distance minimum baseline operating condition matching term as the current preset baseline distribution field, extracts the actual measured coordinate points, and calculates the variation residual between the real-time data and the theoretical values ​​of the corresponding physical coordinate nodes in the preset baseline distribution field. Using the actual spatial coordinates of the physical sensors as divergence anchors, the processor employs a Kriging spatial interpolation algorithm, combined with the physical coordinate distance between adjacent nodes and the set rheological variance attribute, to calculate and generate a three-dimensional deviation compensation matrix covering the entire grid of the fermenter. This matrix is ​​then algebraically superimposed point-by-point with the feature vectors of each node in the preset baseline distribution field, outputting the local viscous drag coefficient of each spatial unit within the fermentation system at the current moment. For each spatial node in this model, the processor calculates the drag deformation weight, characterizing the local viscous properties, by combining the spatial coordinate distance between adjacent nodes and the data variation gradient. The specific calculation formula is as follows: ,in, To impede deformation weights, Let be the gradient vector of the torque variation at this spatial node. Let β be the dissolved oxygen concentration gradient vector, β be the rheological correction constant, and γ be the minimum constant to prevent the denominator from being zero. Based on the distribution of the resistance deformation weights of all spatial nodes, the processor defines the three-dimensional geometric contour of the high-viscosity mass transfer shielding boundary.

[0048] To determine the control parameters required to break the high-viscosity mass transfer barrier, an offline engineering verification platform consisting of three independent test reactors was constructed. Fermentation broth samples in the logarithmic growth phase with a biomass substrate concentration of 25% were injected into each reactor. The base stirring frequency of the reactors was set to 150 rpm, and the pulse acceleration amplitude was set to 1.5 times the base stirring frequency. The pulse duty cycles for the first, second, and third reactors were set to 10%, 20%, and 30%, respectively. The three reactors were run continuously for 4 hours. At the end of the run, a laser particle size analyzer was used to measure the average length of enzyme-producing microfilaments in each fermentation broth sample to quantify the hyphal breakage rate. Simultaneously, the dissolved oxygen concentration rise curve output by the optical dissolved oxygen probe after pulse excitation was extracted, and the dissolved oxygen concentration was measured. The dissolved oxygen recovery slope was measured, and the measured data showed a quantitative response pattern across gradients. Under a 10% duty cycle, the dissolved oxygen recovery slope was less than 0.5 mg / (L·min), indicating insufficient disruption of mass transfer resistance. Under a 30% duty cycle, the hyphal breakage rate reached 15.2%, exceeding the physiological tolerance limit for normal microbial metabolism. Under a 20% duty cycle, the dissolved oxygen recovery slope reached 1.8 mg / (L·min), and the hyphal breakage rate remained within the lower limit range of 4.1%. Based on this calibration test data, the processor established a preferred duty cycle of 20% for pulsed stirring acceleration and wrote this duty cycle value into the flow field shear distribution correction command. This command triggered the stirring mechanism to operate in a pulsed manner at a 20% duty cycle, which maintained the physiological metabolic activity of the fermentation microbial community while disrupting the non-Newtonian fluid stagnation shield boundary.

[0049] Example 4: In the pre-commissioning scenario of deploying a microbial fermentation enzyme production system in a brand-new industrial fermenter, the fermentation control system initiates the flow field benchmark extraction and geometric mesh registration procedure, injects a quantitative amount of pure water matrix into the fermenter and maintains it at the initial temperature, the bottom mechanism drives the stirring device to operate at the rated speed, the dynamic torque sensor collects the no-load torque sequence, the processor uses digital filtering to filter out transmission mechanical disturbances, and sets the converged steady-state torque average as the sterile water no-load benchmark torque. Meanwhile, the processor reads the physical configuration space data of the fermenter and scales the geometric topology of the preset in-tank mass transfer distribution field model according to the absolute coordinates of the internal components, so that the grid nodes in the three-dimensional geometric grid model are aligned and mapped with the actual flow field boundary.

[0050] With the spatial grid mapping established, the feed mechanism injects a biomass conversion material substrate suspension into the pure water matrix according to a predetermined concentration gradient, simulating the evolution of rheological properties. During each concentration step period, the dynamic torque sensor and the optical dissolved oxygen probe synchronously collect data on the driving load torque and dissolved oxygen dissipation rate. The processor imports the measured data into the three-dimensional geometric grid model and solves the inverse interpolation. By comparing the measured retardation deformation weights... The deviation from the model's expected value is iteratively corrected using the gradient descent algorithm, adjusting the geometric proportionality constant α and the rheological correction constant β within the model. When the deviation converges to the set tolerance limit, parameter correction is stopped. This calibration procedure establishes the algorithm parameters as engineering setpoints under a specific hardware architecture. The fermentation control system outputs the material inoculation ready status parameters.

[0051] Example 5: When the fermentation system faces high-throughput aeration causing bubble blockage and local phase change in the optical dissolved oxygen probe, the signal sequence output by the optical dissolved oxygen probe is mixed with non-Gaussian transient noise, resulting in numerical deviations in the dissolved oxygen dissipation rate calculation. To suppress the calculation deviation caused by abnormal measurement boundaries, the system initiates a procedure for constructing a historical baseline envelope model based on an undisturbed environment before formal operation. Under the set standard aeration and pure water matrix conditions without substrate viscosity interference, the processor extracts a sliding time window containing a predetermined number of continuous data points according to the set sampling frequency. The specific underlying data acquisition logic is as follows: The independent... A hardware timer is used to set the hardware sampling frequency of the optical dissolved oxygen probe to 20Hz. A first-in-first-out (FIFO) circular buffer with a capacity of 100 floating-point data points is allocated in memory. The sliding time window corresponds to a time span of 5 seconds. The processor advances the memory write pointer in increments of 20 oldest data points, ensuring that the overlap between adjacent sliding time windows on the time axis reaches 80%. The processor performs bubble sorting on the valid data in the circular buffer and extracts the median value sequence of dissolved oxygen concentration data within the window. Based on this median value sequence, the time correlation difference is calculated to obtain the dissolved oxygen evolution slope under the standard baseline state. , The calculation formula is as follows: ,in, The derivative of real-time dissolved oxygen concentration with respect to reference state time , This represents the median dissolved oxygen concentration within the current sliding time window. Δt is the median dissolved oxygen concentration of the previous adjacent period, and Δt is the scalar of the center time interval between the two sliding time windows. The processor traverses all standard test data of the preset duration, extracts the maximum deviation amplitude of the dissolved oxygen evolution slope, establishes the historical baseline envelope extreme value of the system health status reference and stores it in memory.

[0052] During the online operation phase of actual feeding and fermentation, the processor continuously acquires the real-time dissolved oxygen concentration sequence containing multiphase interference and simultaneously calculates the absolute value of the real-time dissolved oxygen evolution slope. This real-time dissolved oxygen evolution slope absolute value is compared with the historical baseline envelope extreme value. If the real-time dissolved oxygen evolution slope absolute value is greater than the historical baseline envelope extreme value, the processor determines that the optical dissolved oxygen probe in the current window has experienced a gas-liquid phase physical occlusion fault. The data bus blocks the transmission channel of the current outlier data and calls the historical baseline envelope extreme value as a substitute parameter input into the in-tank mass transfer distribution field model. If the real-time dissolved oxygen evolution slope absolute value is not greater than the historical baseline envelope extreme value, the data bus maintains the transmission of the currently calculated value. The historical baseline reference system establishment and online data reconstruction procedure transform the original measurement signal into a stable gradient input parameter, suppressing operator overflow caused by local gas-liquid phase changes, and maintaining the numerical continuity and data reliability of the mass transfer metabolic barrier index calculation under extreme aeration environments.

[0053] The embodiments of this application have been described above with reference to the accompanying drawings. Unless otherwise specified, the embodiments and features in the embodiments of this application can be combined with each other. This application is not limited to the specific embodiments described above. The specific embodiments described above are merely illustrative and not restrictive. Those skilled in the art can make many other forms under the guidance of this application without departing from the spirit of this application and the scope of protection of this invention, and all of these forms are within the protection scope of this application.

Claims

1. A practical application method for a microbial fermentation enzyme production system, characterized in that, Includes the following steps: Step 101: Real-time acquisition of driving load torque data and dissolved oxygen dissipation rate data of fermentation system containing biomass conversion material substrate and enzyme-producing microorganisms. Step 102: Map the load torque and dissolved oxygen dissipation rate to the preset in-tank mass transfer distribution field model to determine the local viscous drag coefficient of each spatial unit in the fermentation system; wherein, the spatial unit is obtained by meshing the three-dimensional space inside the fermenter, and the in-tank mass transfer distribution field model is used to quantitatively describe the non-Newtonian fluid rheological properties, dissolved oxygen osmotic pressure gradient and multiphase flow field spatial heterogeneity distribution caused by biomass conversion materials in the fermentation system; Step 103: Based on the local fluid damping coefficient of each grid point, identify the high viscosity mass transfer shielding boundary in the non-Newtonian fluid stagnation state inside the fermentation system, and calculate the volume ratio of the high viscosity mass transfer shielding boundary in the mass transfer distribution field model inside the tank, so as to construct the mass transfer metabolic barrier index characterizing the substrate degradation resistance. Step 104: Determine whether the mass transfer metabolic barrier index exceeds the preset threshold. If it does, output a flow field shear distribution correction command for the fermentation system based on the geometric center coordinates and evolution trend of the high viscosity mass transfer shield boundary. The physical integrity of the high viscosity mass transfer shield boundary is destroyed by adjusting the stirring frequency in a pulse manner, thereby achieving a forced reset of the microenvironment concentration gradient.

2. The practical application method of the microbial fermentation enzyme production system according to claim 1, characterized in that, Step 102 establishes the local fluid damping coefficients of each grid point in the fermentation system by: extracting the real-time change slope of the driving load torque data and the decay fluctuation rate of the dissolved oxygen dissipation rate data; defining the real-time change slope as the rheological physical damping component and the decay fluctuation rate as the respiratory metabolic damping component; and using the nonlinear correlation weights of the rheological physical damping component and the respiratory metabolic damping component to update the state vectors of each grid point in the corresponding spatial coordinates in the in-tank mass transfer distribution field model.

3. The practical application method of the microbial fermentation enzyme production system according to claim 1, characterized in that, Step 104, which involves forcibly resetting the concentration gradient of the microenvironment, includes: obtaining the biomass substrate feed rate of the fermentation system at the current fermentation stage; and simultaneously adjusting the biomass substrate feed rate and the pulse response frequency of the stirring mechanism according to the rate of change of the mass transfer metabolic barrier index, so that the newly added substrate stream can penetrate the viscous layer of the high-viscosity mass transfer shield boundary.

4. A practical application method of the microbial fermentation enzyme production system according to claim 1, characterized in that, Step 101 also includes obtaining the exhaust gas from the fermentation system. Concentration data; Step 103, constructing the mass transfer metabolic barrier index, includes: based on exhaust gas The cell-specific enzyme production rate was calculated from the concentration data; the cell-specific enzyme production rate was then used to calibrate and correct the volume ratio of the high-viscosity mass transfer shield boundary.

5. A practical application method of the microbial fermentation enzyme production system according to claim 1, characterized in that, Step 103 involves identifying the high-viscosity mass transfer shielding boundary within the fermentation system that is in a non-Newtonian fluid stagnation state. This includes identifying continuous grid regions in the mass transfer distribution field model inside the tank where the local fluid damping coefficient is greater than a preset critical viscosity value; calculating the ratio of the surface area to the volume of the continuous grid regions; and defining the ratio of the surface area to the volume as the morphological complexity of the shielding layer.

6. A practical application method of the microbial fermentation enzyme production system according to claim 1, characterized in that, In step 104, the frequency increment Δf of the pulsed stirring frequency adjustment satisfies the following formula: Where β is the rheological correction factor. For the volume of the high-viscosity mass transfer shielding boundary envelope, The total volume of the fermentation system. The preset maximum shear strength threshold that the mycelium can withstand. This represents the real-time average shear strength in the mass transfer distribution field model inside the tank.

7. A practical application method of the microbial fermentation enzyme production system according to claim 1, characterized in that, Step 104 is followed by: monitoring the ablation rate of the high-viscosity mass transfer shielding boundary after implementing pulsed adjustment of the stirring frequency; if the ablation rate is lower than a preset threshold, adjusting the axial tilt angle of the stirring blades inside the fermentation system, and physically stripping the high-viscosity mass transfer shielding boundary by changing the momentum distribution ratio of the axial flow and the radial flow.

8. A practical application method of the microbial fermentation enzyme production system according to claim 1, characterized in that, Step 104, determining whether the mass transfer metabolic barrier index exceeds the preset threshold, includes: dynamically setting the preset threshold based on the average length of the mycelium of enzyme-producing microorganisms in the fermentation system; simultaneously reducing the preset threshold as the average length of the mycelium increases to trigger the flow field shear distribution correction command in advance; and outputting the flow field shear distribution correction command for the fermentation system in step 104, including: resolving the radial coordinates of the high-viscosity mass transfer shield boundary within the fermentation system; and adjusting the power output of the stirring layers at different heights in the fermentation system based on the radial coordinates.

9. A practical application method of the microbial fermentation enzyme production system according to claim 1, characterized in that, The method is used for the enzymatic hydrolysis process of high solids biomass conversion materials. Through closed-loop feedback of the mass transfer metabolic barrier index, the method maintains the dissolved oxygen osmotic pressure of the fermentation system while limiting the instantaneous shear force generated by pulsed adjustment of stirring frequency, thus ensuring the integrity of the mycelial structure of enzyme-producing microorganisms.

10. A microbial fermentation enzyme production system, characterized in that, The microbial fermentation enzyme production system is used to realize the practical application method of the microbial fermentation enzyme production system described in claim 1.

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