Wine cross-flow filtration flow rate control method and system

Abstract

The invention provides a wine cross-flow filtration flow rate control method and system, a fixed terminal turbidity target value is determined according to product standards and downstream process requirements, an initial circulation flow rate reference value and an initial operation pressure are determined according to initial characteristic parameters and preset membrane module process parameters, and then cross-flow filtration is started. The real-time turbidity, the transmembrane pressure difference and the permeate flux of the filtrate are monitored synchronously, the membrane pollution development index is determined based on the rising rate of the transmembrane pressure difference and the falling rate of the permeate flux, and then the circulation flow rate is adjusted according to the comparison result of the membrane pollution development index and the preset membrane pollution threshold value. And when the real-time turbidity is continuously lower than the terminal turbidity target value and the transmembrane pressure difference and the permeate flux are in a reasonable working condition range, judging that the wine filtration is completed. By adopting the scheme of the invention, intelligent flow velocity control can be performed on wine cross-flow filtration based on the predicted pollution trend at the initial stage of filtration.

Description

Technical Field

[0001] This application relates to the field of filtration flow rate control technology, and in particular to a method and system for controlling the flow rate of wine cross-flow filtration. Background Technology

[0002] Cross-flow filtration is a key process in wine production for clarifying and sterilizing wine. It achieves solid-liquid separation through membrane modules driven by pressure, which plays a decisive role in ensuring the clarity, biological stability, and sensory quality of the final product. In this process, the circulation flow rate is one of the core operating parameters, and its magnitude directly affects the shear force on the membrane surface, thereby affecting the rate of membrane fouling and the stability of filtration flux.

[0003] Currently, industrial control of cross-flow filtration circulation rate mainly relies on operator experience and simple program control. However, wine production exhibits significant batch-to-batch variability. Different batches of raw grapes and pretreatment processes can lead to large fluctuations in parameters such as initial turbidity, particulate matter characteristics, colloid content, and viscosity of the wine. Existing fixed or programmed flow rate control methods cannot detect or adapt to these batch-to-batch variations. For batches with a high tendency to contamination, setting the initial flow rate too low can cause membrane fouling too quickly, resulting in a sharp increase in transmembrane pressure and a rapid decline in filtration flux. This not only shortens the single filtration cycle and increases the cleaning frequency but may also affect downstream process scheduling due to excessively long filtration times. For batches with a low tendency to contamination, setting the initial flow rate too high can lead to unnecessary energy waste, and excessive shear force may affect the wine's flavor. Therefore, how to intelligently control the flow rate of cross-flow wine filtration based on predicted contamination trends in the early stages of filtration has become a challenge for the industry. Summary of the Invention

[0004] Based on this, this application provides a wine cross-flow filtration flow rate control method and system for intelligent flow rate control of wine cross-flow filtration based on predicted contamination trends in the initial stage of filtration.

[0005] In a first aspect, this application provides a method for controlling the flow rate of wine cross-flow filtration, comprising the following steps: Obtain the initial characteristic parameters of the current batch of wine; A fixed target value for terminal turbidity is determined based on product standards and downstream process requirements; The initial circulation flow rate reference value and the initial operating pressure are determined based on the initial characteristic parameters and the preset membrane module process parameters. Then, cross-flow filtration is started with the initial circulation flow rate reference value and the initial operating pressure, and the real-time turbidity, transmembrane pressure difference and permeate flux of the filtrate are monitored simultaneously. In the initial stage of filtration, based on the rate of increase of the transmembrane pressure difference and the rate of decrease of the permeate flux, a membrane fouling development index is determined to characterize the speed of fouling development. Then, the circulation flow rate is adjusted according to the comparison result between the membrane fouling development index and the preset membrane fouling threshold. During the main filtration stage, when the real-time turbidity is consistently lower than the terminal turbidity target value, and the transmembrane pressure difference and the permeate flux are within a reasonable operating range, the wine filtration is deemed complete, and qualified wine filtrate is output.

[0006] In some embodiments, determining a fixed target value for terminal turbidity based on product standards and downstream process requirements specifically includes: Determine the clarity standard parameters corresponding to the type of wine in the current batch; Determine the maximum permissible limit parameters for the turbidity of the feed liquid at the equipment interface of the cold stabilization treatment; By comparing the clarity standard parameter with the maximum permissible limit parameter, the more stringent value is selected as the fixed terminal turbidity target value that must be achieved in this filtration process.

[0007] In some embodiments, determining the initial circulation flow rate reference value and the initial operating pressure based on the initial characteristic parameters and preset membrane module process parameters specifically includes: The basic range of values ​​for the initial circulation flow rate and the initial operating pressure is determined based on the preset membrane module process parameters. Based on the initial turbidity and viscosity characteristics in the initial characteristic parameters, joint interpolation calculations are performed within the basic value range to obtain the initial circulation flow rate and initial operating pressure values. The initial circulation flow rate and the initial operating pressure are verified for process safety. The values ​​that pass the verification are ultimately determined as the initial circulation flow rate reference value and the initial operating pressure for starting the filter.

[0008] In some embodiments, initiating cross-flow filtration with the initial circulation flow rate reference value and the initial operating pressure, and simultaneously monitoring the real-time turbidity of the filtrate, transmembrane pressure difference, and permeate flux specifically includes: The initial circulating flow rate reference value and the initial operating pressure are used as setpoint commands and sent to the circulating pump and pressure regulating valve. Drive the circulating pump and the pressure regulating valve to stabilize the circulating flow rate and operating pressure at the control set point, so as to start cross-flow filtration; Simultaneously with the start of filtration, the online sensor group installed on the filtrate pipeline and membrane module is activated to continuously collect the raw turbidity signal of the filtrate, the raw pressure signals at the inlet and outlet of the membrane module, and the raw filtrate flow rate signal. The acquired raw signals are conditioned, converted from analog to digital and converted to engineering units to generate and output real-time turbidity, transmembrane pressure difference and permeate flux in digital form.

[0009] In some embodiments, during the initial stage of filtration, determining a membrane fouling development index, characterizing the rate of fouling development, based on the rate of increase of the transmembrane pressure difference and the rate of decrease of the permeate flux, specifically includes: During the initial filtration time window, time-series data of the transmembrane pressure difference and the permeate flux are acquired; Linear fitting is performed on the time series data of the transmembrane pressure difference, and the absolute value of its slope is used as the rate of increase of the transmembrane pressure difference. Similarly, linear fitting is performed on the time series data of the permeate flux, and the absolute value of its slope is used as the rate of decrease of the permeate flux. The rising rate and the falling rate are normalized and weighted and summed to output a membrane fouling development index that characterizes the speed of fouling development.

[0010] In some embodiments, adjusting the circulation flow rate based on a comparison between the membrane fouling development index and a preset membrane fouling threshold specifically includes: Obtain the preset membrane fouling threshold; The membrane fouling development index is compared with the membrane fouling threshold to determine the current level of fouling development. Determine the circulation velocity adjustment amount corresponding to the grade range; Based on the circulating flow rate adjustment amount, a setpoint modification command is sent to the circulating flow rate control loop to adjust the circulating flow rate to the target value.

[0011] In some embodiments, the method further includes: when the real-time turbidity is consistently higher than the terminal turbidity target value, triggering a diagnostic process to check membrane integrity or adjust pretreatment process parameters.

[0012] Secondly, this application provides a wine cross-flow filtration flow rate control system, the system comprising: The acquisition module is used to acquire the initial characteristic parameters of the current batch of wine; The processing module is used to determine a fixed target value for terminal turbidity based on product standards and downstream process requirements; The processing module is also used to determine the initial circulation flow rate reference value and the initial operating pressure based on the initial characteristic parameters and the preset membrane module process parameters, and then start cross-flow filtration with the initial circulation flow rate reference value and the initial operating pressure, and simultaneously monitor the real-time turbidity of the filtrate, the transmembrane pressure difference and the permeate flux. The processing module is also used to determine the membrane fouling development index, which characterizes the speed of fouling development, based on the rising rate of the transmembrane pressure difference and the decreasing rate of the permeate flux in the initial stage of filtration, and then adjust the circulation flow rate according to the comparison result of the membrane fouling development index and the preset membrane fouling threshold. The execution module is used to determine that the wine filtration is complete and output qualified wine filtrate when the real-time turbidity is consistently lower than the terminal turbidity target value and the transmembrane pressure difference and the permeate flux are within a reasonable operating range during the main filtration stage.

[0013] Thirdly, this application provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps of the above-described wine cross-flow filtration flow rate control method.

[0014] Fourthly, this application provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps of the above-described wine cross-flow filtration flow rate control method.

[0015] The technical solutions provided by the embodiments disclosed in this application have the following beneficial effects: The wine cross-flow filtration flow rate control method and system provided in this application firstly acquires the initial characteristic parameters of the current batch of wine and determines a fixed terminal turbidity target value based on product standards and downstream process requirements. This step can be based on personalized process starting point settings for batch differences and the establishment of fixed quality targets that integrate enterprise internal control and downstream needs, thereby improving the scientific nature of the initial filtration conditions and the authority of quality standards. Secondly, based on the initial characteristic parameters and preset membrane module process parameters, the initial circulation flow rate reference value and initial operating pressure are determined, and then cross-flow filtration is started with the initial circulation flow rate reference value and the initial operating pressure, while simultaneously monitoring the real-time turbidity of the filtrate, the transmembrane pressure difference, and the permeate flux. This step can be based on the safety and adaptive initial operating condition settings of characteristic parameters and membrane safety boundaries, as well as the synchronous digitization of key parameters throughout the filtration process, thereby improving the safety of system startup and the observability of process status. Then, in the initial stage of filtration, based on the rate of increase of the transmembrane pressure difference and the decrease of the permeate flux... The process involves several steps. First, a membrane fouling development index is determined to characterize the rate of fouling development. Then, the circulation flow rate is adjusted based on a comparison between this index and a preset membrane fouling threshold. This step allows for a quantitative assessment of the initial physical trends—namely, pressure gradient increases and flux decreases—to preventative adaptive flow rate adjustments. This improves the ability to predict batch fouling tendencies and the timeliness of intervention, optimizing fluid conditions before fouling intensifies. Finally, in the main filtration stage, when the real-time turbidity remains below the target terminal turbidity value, and the transmembrane pressure gradient and permeate flux are within reasonable operating ranges, the wine filtration is considered complete, and qualified wine filtrate is output. This step allows for precise endpoint determination and automatic output based on the combined effects of real-time turbidity, transmembrane pressure gradient, and permeate flux, improving the accuracy of filtration endpoint determination and achieving a fully automated closed-loop process from quality monitoring to product output. In summary, the solution proposed in this application enables intelligent flow rate control for cross-flow wine filtration in the initial stage of filtration based on predicted fouling trends. Attached Figure Description

[0016] Figure 1 This is an exemplary flowchart of a wine cross-flow filtration flow rate control method according to some embodiments of this application; Figure 2 This is a schematic diagram illustrating an application scenario of a cross-flow filtering flow rate control data processing system according to some embodiments of this application; Figure 3 This is a schematic flowchart illustrating the process of determining the membrane fouling development index according to some embodiments of this application; Figure 4 This is a schematic diagram of the structure of a wine cross-flow filtration flow rate control system according to some embodiments of this application; Figure 5This is a schematic diagram of the structure of a computer device for implementing a cross-flow filtration flow rate control method for wine, according to some embodiments of this application. Detailed Implementation

[0017] To better understand the above technical solutions, the following will provide a detailed explanation of the technical solutions in conjunction with the accompanying drawings and specific implementation methods.

[0018] refer to Figure 1 The figure is an exemplary flowchart of a wine cross-flow filtration flow rate control method according to some embodiments of this application. The wine cross-flow filtration flow rate control method mainly includes the following steps: In step 101, the initial characteristic parameters of the current batch of wine are obtained.

[0019] In practice, the initial characteristic parameters of the current batch of wine can be obtained in the following way: A set of calibrated online process analysis instruments is integrated and installed at the outlet of the feed tank containing the current batch of wine. This allows for automated measurement of a representative sample of the current batch of wine before the filtration process begins, thereby obtaining complete initial characteristic parameters. These initial characteristic parameters include initial turbidity and viscosity characteristics. The initial turbidity is measured continuously in real-time using an online turbidimeter based on the principle of scattered light measurement, and the average value is recorded after the reading stabilizes. The unit is the national standard unit NTU. The viscosity characteristics can be obtained in two ways: one is to connect an online process viscometer based on the principle of vibration, such as the Anton Paar L-Vis, in series on the outlet pipe of the feed tank. The 510 model viscometer features a measuring unit matched to the viscosity range of wine. During measurement, the wine flows through the viscometer at a constant low flow rate. The instrument's internal processor directly calculates and outputs the real-time viscosity value in millipascals per second based on the vibration attenuation rate. This real-time viscosity value is transmitted to the control system via a communication interface as the viscosity characteristic. Alternatively, when an online viscometer is unavailable, model estimation is used. The control system has a pre-stored "wine viscosity-component-temperature relationship empirical database," established through the following method: collecting hundreds of historical batch sample data covering major types such as dry red and dry white wines. Each data set includes alcohol content, residual sugar, temperature, and corresponding viscosity measured using standard laboratory methods. Multiple regression analysis is used to fit an empirical formula, for example: η = 1.15 + 0.048A + 0.0018S - 0.012T +0.0001A·S, where η is the estimated viscosity in mPa·s, A is the alcohol content in %vol, S is the residual sugar in g / L, and T is the temperature in ℃. When obtaining the initial characteristic parameters, the alcohol content and residual sugar measured by the online near-infrared spectrometer and the temperature measured by the platinum resistance thermometer are substituted into this formula to calculate the viscosity characteristics. Other methods can also be used in other embodiments, and this application does not limit them.

[0020] It should be noted that the initial characteristic parameters in this application are the basic parameters characterizing the initial physicochemical state of the current batch of wine to be filtered.

[0021] In some embodiments, reference Figure 2As shown in the figure, this figure is a schematic diagram of the application scenario of the cross-flow filtration flow rate control data processing system according to some embodiments of this application. The figure includes three main components: a data acquisition device, a server, and a data storage device. The data acquisition device is responsible for collecting the initial characteristic parameters of the current batch of wine and sending the collected initial characteristic parameters of the current batch of wine to the server through a communication network. The cross-flow filtration flow rate control data processing system runs on the server. The server stores the processing results in the data storage device and visualizes them.

[0022] In step 102, a fixed target value for terminal turbidity is determined based on product standards and downstream process requirements.

[0023] In some embodiments, determining a fixed target value for terminal turbidity based on product standards and downstream process requirements can be achieved through the following steps: Determine the clarity standard parameters corresponding to the type of wine in the current batch; Determine the maximum permissible limit parameters for the turbidity of the feed liquid at the equipment interface of the cold stabilization treatment; By comparing the clarity standard parameter with the maximum permissible limit parameter, the more stringent value is selected as the fixed terminal turbidity target value that must be achieved in this filtration process.

[0024] It should be noted that the terminal turbidity target value in this application refers to the unique end-point standard of filtrate quality that must be achieved throughout the entire cross-flow filtration process. Its function is to provide a fixed and unchanging quality pass line for the filtration process, serving as the core quality criterion for ultimately determining whether filtration is complete. The clarity standard parameter refers to the inherent quality requirements for clarity of different types of wine products specified by the enterprise's product quality standards. Its function is to set an internal constraint on the terminal turbidity target value from the perspective of final product quality. The maximum permissible limit parameter refers to the mandatory upper limit requirement for the turbidity of the filtrate received by the downstream process equipment. Its function is to set an external constraint on the terminal turbidity target value from the perspective of production process connection and safe equipment operation.

[0025] In specific implementation, determining the clarity standard parameter corresponding to the current batch of wine can be achieved in the following way: A wine quality specification database is pre-established and maintained in the filtration control system or the connected manufacturing execution system. This database uses wine type, such as dry red, dry white, and rosé, as key indexes and stores the clarity standards corresponding to various products, confirmed by process documents. These standards are manifested as specific turbidity numerical parameters. When it is necessary to determine the clarity standard parameter, the current batch of wine type information input from the production order or operation interface is received and used as a query condition to initiate a request to the quality specification database. Based on the query condition, the quality specification database retrieves and returns a specific turbidity limit value. This turbidity limit value is the clarity standard parameter strictly corresponding to the current batch of wine type. For example, ≤1.5 NTU is returned for bottled dry red. Other methods can also be used in other embodiments, and this application does not limit this.

[0026] In practice, determining the maximum permissible limit parameter for feed liquid turbidity at the equipment interface of the cold stabilization process can be achieved in the following way: In the production line, the cold stabilization process, located downstream of the cross-flow filtration process, or other key downstream processes such as fine filtration and filling, typically has pre-set process parameters within its equipment control system to ensure its safe and stable operation. The maximum permissible limit parameter is one of these parameters, specifying the highest permissible turbidity of the filtrate entering the equipment. When determining this maximum permissible limit parameter, the filtration control system establishes a communication connection with the programmable logic controller (PLC) of the downstream cold stabilization equipment through a workshop-level industrial network and calls a predefined data interface service to read the feed turbidity upper limit parameter value stored in the equipment configuration file or control program. Alternatively, the feed turbidity upper limit parameter value can be pre-entered into the configuration table of the filtration control system by the engineer according to the equipment manual. The turbidity value obtained through any of the above methods is the maximum permissible limit parameter from the hard constraints of the downstream process, for example, ≤1.0 NTU. The workshop-level industrial network is such as Ethernet / IP or Profinet, and the data interface service is such as OPC. The UA read service can be implemented using other methods in other embodiments, and this application does not limit it.

[0027] In specific implementation, comparing the clarity standard parameter and the maximum allowable limit parameter, and selecting the more stringent value as the fixed terminal turbidity target value that must be achieved in this filtration process can be achieved in the following way: comparing the numerical values ​​of the clarity standard parameter and the maximum allowable limit parameter, where the "more stringent value" refers to the smaller value of the two turbidity parameters, because a smaller turbidity value represents a higher requirement for liquid clarity. Therefore, if the value of the clarity standard parameter is less than the maximum allowable limit parameter, the clarity standard parameter is selected as the output; otherwise, the maximum allowable limit parameter is selected as the output. The result of this selection is set as the unique and fixed terminal turbidity target value for this filtration process and written into the process variable storage area for this production process, for direct use in subsequent steps. Other methods can also be used in other embodiments, and this application does not limit them.

[0028] It should be noted that the above steps can be based on the personalized process starting point setting based on batch differences, and the establishment of fixed quality targets that integrate enterprise internal control and downstream needs, thereby improving the scientific nature of the initial filtration conditions and the authority of the quality standards.

[0029] In step 103, the initial circulation flow rate reference value and the initial operating pressure are determined according to the initial characteristic parameters and the preset membrane module process parameters. Then, cross-flow filtration is started with the initial circulation flow rate reference value and the initial operating pressure, and the real-time turbidity of the filtrate, the transmembrane pressure difference and the permeate flux are monitored simultaneously.

[0030] In some embodiments, determining the initial circulation flow rate reference value and the initial operating pressure based on the initial characteristic parameters and preset membrane module process parameters can be achieved by the following steps: The basic range of values ​​for the initial circulation flow rate and the initial operating pressure is determined based on the preset membrane module process parameters. Based on the initial turbidity and viscosity characteristics in the initial characteristic parameters, joint interpolation calculations are performed within the basic value range to obtain the initial circulation flow rate and initial operating pressure values. The initial circulation flow rate and the initial operating pressure are verified for process safety. The values ​​that pass the verification are ultimately determined as the initial circulation flow rate reference value and the initial operating pressure for starting the filter.

[0031] It should be noted that the initial circulation velocity reference value in this application refers to the first stable operating speed value set for the circulation pump during the filtration start-up phase. Its function is to provide an initial fluid dynamic condition that balances anti-fouling and energy consumption for the initial stage of filtration, taking into account the characteristics of the current batch and membrane safety. The initial operating pressure refers to the first stable transmembrane drive pressure value set during the filtration start-up phase. Its function is to provide the initial separation driving force for filtration, while ensuring the safety of the membrane module and the initial quality of the filtrate.

[0032] In specific implementation, determining the basic value range of the initial circulation flow rate and the initial operating pressure based on the preset membrane module process parameters can be achieved in the following way: In the configuration file of the filtration control system, the preset membrane module process parameters extracted from the technical specifications provided by the membrane module supplier are stored in advance. These membrane module process parameters include at least: the maximum transmembrane pressure difference that the membrane module can safely operate for a long time, the recommended circulation flow rate (cross-flow velocity) range for obtaining the best antifouling effect, and the recommended initial low pressure value for wine filtration scenarios. When determining the basic value range, these preset values ​​are directly called: the lower limit and upper limit of the recommended circulation flow rate range are set as the minimum and maximum values ​​of the basic value range of the initial circulation flow rate, respectively. At the same time, the zero value, i.e., the gauge pressure, and the conservative pressure value set according to engineering experience that is lower than the maximum transmembrane pressure difference, for example, 25% of the maximum transmembrane pressure difference value, are set together as the lower limit and upper limit of the basic value range of the initial operating pressure, thereby constructing a safe initial operating window. Other methods can also be used in other embodiments, and this application does not limit them.

[0033] In specific implementation, the initial circulation velocity and initial operating pressure values ​​are obtained by joint interpolation calculation based on the initial turbidity and viscosity characteristics in the initial characteristic parameters within the basic value range. This can be achieved in the following way: First, a two-dimensional interpolation lookup table is pre-stored. This table uses the initial turbidity gradient (<10 NTU, 10-20 NTU, 20-30 NTU, >30 NTU) as rows and the viscosity characteristic gradient (<1.5 mPa·s, 1.5-2.0 mPa·s, >2.0 mPa·s) as columns. Each cell stores a set of recommended initial values ​​verified by the process: circulation velocity V_rec and operating pressure P_rec. After obtaining the specific initial turbidity T0 and viscosity η0, the turbidity and viscosity ranges to which T0 and η0 belong are first located. Then, bilinear interpolation is performed on the recommended values ​​in four adjacent cells. The formula for the initial circulation velocity value V0 is as follows: V0 = V_rec(low turbidity, low viscosity) * (1-u)(1-v) + V_rec(high turbidity, low viscosity) * u*(1-v) + V_rec(low turbidity, high viscosity) * (1-u)*v + V_rec(high turbidity, high viscosity) * u*v, where u and v are normalized position coefficients. The calculation formula for the initial operating pressure value P0 is similar. Other methods can also be used in other embodiments, and this application does not limit them.

[0034] In specific implementation, the initial circulation flow rate value and the initial operating pressure value are subjected to process safety verification. The values ​​that pass the verification are ultimately determined as the initial circulation flow rate reference value and initial operating pressure value for starting the filter. This can be achieved in the following way: a built-in verification logic unit is used to perform process safety verification on the interpolated initial circulation flow rate value and the initial operating pressure value. The verification includes: range compliance check, correlation constraint check, and historical deviation check. The range compliance check confirms that V0 ∈ [V_min, V_max] and P0 ∈ [P_min, P_max], where [V_min, V_max] is the basic value range of the initial circulation flow rate, [P_min, P_max] is the basic value range of the initial operating pressure value, and P_max is the maximum allowable transmembrane pressure difference of the membrane module. The correlation constraint check requires that if the terminal turbidity target value is lower than a preset strict standard (e.g., ≤0.8 NTU), then P0 ≤ 0.6 * P_max is used to ensure membrane safety under high clarification requirements. The historical deviation check compares V0 and P0 with the average initial values ​​of the most recent 10 successful batches. If any parameter deviates by more than 20%, a prompt message is triggered, requesting the operator to confirm or enable a backup parameter. Only when all checks pass can V0 and P0 be finally determined as the initial circulation flow rate reference value and the initial operating pressure. Other methods can also be used in other embodiments, and this application does not limit them.

[0035] In some embodiments, initiating cross-flow filtration with the initial circulation flow rate reference value and the initial operating pressure, and simultaneously monitoring the real-time turbidity of the filtrate, the transmembrane pressure difference, and the permeate flux, can be achieved by the following steps: The initial circulating flow rate reference value and the initial operating pressure are used as setpoint commands and sent to the circulating pump and pressure regulating valve. Drive the circulating pump and the pressure regulating valve to stabilize the circulating flow rate and operating pressure at the control set point, so as to start cross-flow filtration; Simultaneously with the start of filtration, the online sensor group installed on the filtrate pipeline and membrane module is activated to continuously collect the raw turbidity signal of the filtrate, the raw pressure signals at the inlet and outlet of the membrane module, and the raw filtrate flow rate signal. The acquired raw signals are conditioned, converted from analog to digital and converted to engineering units to generate and output real-time turbidity, transmembrane pressure difference and permeate flux in digital form.

[0036] It should be noted that, in this application, real-time turbidity refers to the instantaneous turbidity value of the filtrate obtained online and continuously during the filtration process. Its function is to provide a continuous quality feedback signal for the process, to monitor the filtrate quality in real time, and to serve as a direct input for endpoint determination and anomaly diagnosis. The transmembrane pressure difference refers to the pressure difference required to drive the wine through the membrane during the filtration process. Its function is to reflect the resistance status of the membrane filtration channel in real time and is a key process variable characterizing the degree of membrane fouling and the system operating load. The permeate flux refers to the volume of filtrate that permeates per unit time and per unit membrane area. Its function is to reflect the production efficiency of the filtration system, i.e., the separation rate, and is a key process variable for measuring the process economy and membrane performance status.

[0037] In practical implementation, the initial circulation flow rate reference value and the initial operating pressure are used as setpoint commands and sent to the circulation pump and pressure regulating valve. This can be achieved in the following way: the main controller of the filtration control system converts the determined initial circulation flow rate reference value and the initial operating pressure into specific, executable commands. More specifically, for the variable frequency centrifugal pump driving the wine circulation, i.e., the circulation pump, the controller outputs the commands through an analog output channel (e.g., 4-20mA) or through PROFINET, Modbus, etc. The controller uses fieldbus protocols such as TCP / IP to send a target frequency setpoint proportional to the initial circulation velocity reference value to the frequency converter attached to the circulating pump. For the pressure regulating valve controlling the back pressure of the membrane system, which is typically a pneumatic diaphragm regulating valve or an electric regulating valve, the controller sends a target opening percentage signal corresponding to the initial operating pressure to the electric valve positioner attached to the pressure regulating valve through another independent analog output channel or the same fieldbus network. It should be noted that the unit of the initial circulation velocity reference value in this application is cubic meters per hour, and the unit of the initial operating pressure is megapascals. Other methods can also be used in other embodiments, and this application does not limit them.

[0038] In specific implementation, driving the circulating pump and the pressure regulating valve to stabilize the circulating flow rate and operating pressure at the control setpoint to initiate cross-flow filtration can be achieved in the following way: After the setpoint command is issued, the frequency converter of the circulating pump adjusts the motor speed according to the received target frequency, thereby changing the pump output and driving the wine to start flowing in the membrane filtration circulation pipeline. The actual circulating flow rate is detected in real time by an electromagnetic flowmeter installed on the main circulation pipeline, and this detected value is fed back to the flow rate PID control loop of the controller as a process variable. This flow rate PID control loop dynamically adjusts the command sent to the frequency converter to make the actual flow rate... The circulating flow rate rapidly approaches and eventually stabilizes within the allowable error range of the initial circulating flow rate reference value, for example, ±5%. Simultaneously, the positioner of the pressure regulating valve moves the valve core according to the received opening command, changing the pipeline resistance to regulate the system pressure. The actual operating pressure is detected in real time by a pressure sensor installed at the inlet of the membrane module, and this detected value is fed back to the pressure PID control loop of the controller as a process variable. The pressure PID control loop dynamically adjusts the command sent to the valve positioner to make the actual operating pressure rapidly approach and eventually stabilize within the allowable error range of the initial operating pressure, for example, ±0.02 MPa. When both independent closed-loop control loops reach a stable state and maintain it for more than a preset stable time, such as 30 seconds, the control system determines that the cross-flow filtration process has started correctly and smoothly, and enters an operating state where process monitoring and adjustment can be performed. Other methods can also be used in other embodiments, and this application does not limit them.

[0039] In practice, upon starting the filtration process, an online sensor group installed on the filtrate pipeline and membrane module is activated to continuously collect the raw turbidity signal of the filtrate, the raw pressure signals at the inlet and outlet of the membrane module, and the raw filtrate flow rate signal. This can be achieved in the following way: Synchronously with the start-up command of the drive equipment, the main controller sends a digital command to the online sensor group to power on or begin measurement. The online sensor group specifically includes: an online turbidity sensor installed on the filtrate pipeline of the cross-flow filtration system, which uses the principle of scattered light measurement and continuously outputs raw turbidity signals characterizing the degree of liquid turbidity, typically a 4-20mA analog current signal; and sensors rigidly connected to the feed inlet flange and concentrate outlet flange of the membrane module, respectively. Two high-precision pressure transmitters on the device begin to continuously measure and output raw pressure signals representing the absolute pressure at the two points, which are also standard analog current signals. A mass flow meter or a turbine flow meter with pulse output installed on the filtrate branch begins to continuously measure and output raw filtrate flow signals representing the instantaneous volumetric flow rate of the filtrate, which are in the form of pulse frequency signals or another 4-20mA analog signal. The data acquisition unit of the control system synchronously scans the output channels of all these sensors at a constant high frequency, such as 10 Hz, converting the continuous physical signals into discrete raw data snapshots with precise timestamps and storing them in a temporary buffer. Other methods may be used in other embodiments, and this application does not limit them.

[0040] In practical implementation, the acquired raw signals undergo signal conditioning, analog-to-digital conversion, and engineering unit conversion to generate and output real-time turbidity, transmembrane pressure difference, and permeate flux in digital form. This can be achieved as follows: First, signal conditioning is performed, including impedance matching and low-pass filtering of the analog current signal to remove high-frequency noise, and shaping and counting of the pulse frequency signal. Next, analog-to-digital conversion is performed: for analog signals, a high-resolution analog-to-digital converter quantizes them into digital quantities; for pulse signals, a counter converts them into digital quantities representing cumulative flow. Finally, the crucial engineering unit conversion is performed: based on the factory calibration curve of the online turbidity sensor, the corresponding digital quantities are converted into real-time turbidity values ​​in NTUs (turbidity units). The digital quantities converted from the two pressure transmitter signals are then... Based on their respective ranges and zero-point parameters, the inlet pressure and outlet pressure values ​​in megapascals are calculated respectively. The difference between the two values ​​yields the transmembrane pressure difference. The digital value of the original flow signal is converted and the instantaneous filtrate flow rate in liters per hour is calculated based on the flow meter's instrument coefficient. This flow rate value is then divided by the effective filtration area of ​​the membrane module preset in the control system parameters. The effective filtration area of ​​the membrane module is in square meters. Finally, the permeate flux value in liters per square meter per hour is obtained. After this complete processing flow, a set of timestamp-aligned, directly physically meaningful real-time digital parameters of turbidity, transmembrane pressure difference, and permeate flux are updated in real time to the process database and provided as standard interface data for subsequent steps. Other methods can also be used in other embodiments, and this application does not limit them.

[0041] It should be noted that the above steps can be based on the safety and adaptive initial operating condition settings of characteristic parameters and membrane safety boundaries, as well as the synchronous digitization of key parameters throughout the filtration process, thereby improving the safety of system startup and the observability of process status.

[0042] In step 104, at the initial stage of filtration, a membrane fouling development index, which characterizes the rate of fouling development, is determined based on the rate of increase of the transmembrane pressure difference and the rate of decrease of the permeate flux. Then, the circulation flow rate is adjusted according to the comparison result between the membrane fouling development index and a preset membrane fouling threshold.

[0043] In some embodiments, reference Figure 3 As shown in the figure, this is a schematic flowchart of the process for determining the membrane fouling development index in some embodiments of this application. In this embodiment, in the initial stage of filtration, the membrane fouling development index, which characterizes the rate of fouling development, is determined based on the rate of increase of the transmembrane pressure difference and the rate of decrease of the permeate flux. This can be achieved by the following steps: In step 1031, within the initial filtration time window, time-series data of the transmembrane pressure difference and the permeate flux are acquired; In step 1032, the time series data of the transmembrane pressure difference is linearly fitted, and the absolute value of its slope is used as the rate of increase of the transmembrane pressure difference; the time series data of the permeate flux is linearly fitted, and the absolute value of its slope is used as the rate of decrease of the permeate flux. In step 1033, the rising rate and the falling rate are normalized and weighted and summed to output the membrane fouling development index, which characterizes the speed of fouling development.

[0044] It should be noted that the membrane fouling development index in this application is a comprehensive quantitative indicator that characterizes the rate of membrane fouling development in the current batch. In the early stage of filtration, it integrates information on the rate of increase in transmembrane pressure difference and the rate of decrease in permeate flux. Its function is to provide a basis for decision-making to predict the fouling situation in advance and then implement preventive flow rate adjustment.

[0045] In specific implementation, the acquisition of the time-series data of the transmembrane pressure difference and the permeate flux within the initial filtration time window can be achieved in the following way: based on the signal of successful filtration startup, timing begins and the initial filtration time window is entered. The duration of this initial filtration time window is a preset fixed value, such as 10 minutes, or a value dynamically calculated based on the initial turbidity in the acquired initial characteristic parameters. For example, the higher the initial turbidity, the longer the initial window time is set to capture a more complete initial contamination trend. Within this initial filtration time window, data acquisition is performed at constant time intervals, such as every 2 seconds, accessing the process database continuously generated and updated by step 103. According to the timestamp order, the numerical sequence of the transmembrane pressure difference and the numerical sequence of the permeate flux are read and cached respectively, thereby forming two columns of raw data sequences that are strictly aligned with time and have equal time intervals. This completes the acquisition of the time-series data of the transmembrane pressure difference and the permeate flux. Other methods can also be used in other embodiments, and this application does not limit them.

[0046] In specific implementation, linear fitting is performed on the time-series data of the transmembrane pressure difference, and the absolute value of its slope is taken as the rate of increase of the transmembrane pressure difference. Similarly, linear fitting is performed on the time-series data of the permeate flux, and the absolute value of its slope is taken as the rate of decrease of the permeate flux. This can be achieved as follows: An embedded mathematical calculation engine is invoked to process the acquired time-series data of the transmembrane pressure difference. The mathematical calculation engine uses a least squares linear regression algorithm, taking time as the independent variable and the corresponding transmembrane pressure difference value as the dependent variable, to perform linear fitting, obtaining an optimal fitted line. The slope of this fitted line is calculated, and its absolute value is defined as the characteristic line. The rate of increase of the transmembrane pressure difference, which is the intensity of the pressure difference increase within a given time period, is expressed in megapascals per minute. Simultaneously, the same processing procedure is performed on the time-series data of the permeate flux: a least-squares linear fit is performed with time as the independent variable and the corresponding permeate flux value as the dependent variable to obtain the slope of the fitted line. Since the flux usually decreases in the initial stage of filtration, this slope is negative. Taking its absolute value, it is defined as the rate of decrease of the permeate flux, which characterizes the intensity of flux decay per unit time, and is expressed in liters per square meter per hour per minute. The above fitting calculation can be performed in a rolling manner within a time window to obtain an updated rate. Other methods can also be used in other embodiments, and this application does not limit this.

[0047] In practice, the normalization and weighted summation of the rise rate and fall rate to output the membrane fouling development index, which characterizes the rate of fouling development, can be achieved in the following way: First, a pre-stored normalized baseline value is called. This baseline value is derived from historical data analysis: from the initial filtration data of no less than 50 normal batches in the past, the transmembrane pressure difference rise rate (ΔP_rate) and the permeate flux fall rate (J_rate) are statistically calculated respectively. The median of the two is taken as the normalized baseline value, denoted as ΔP_ref and J_ref. For example, ΔP_ref = 0.005 MPa / min, J_ref = 0.25 L / (m 2·h·min); then, normalization calculations are performed: normalized differential pressure rise rate N_ΔP = ΔP_rate / ΔP_ref, normalized flux decline rate N_J = J_rate / J_ref; finally, weighted summation is performed, the weighting coefficients (w1, w2) are determined through process experiment optimization, the goal is to make the membrane fouling development index have the highest correlation with the total flux decay rate during the filtration cycle, a typical set of values ​​is w1=0.6, w2=0.4, and w1 + w2 = 1, the membrane fouling development index (MPI) is calculated as: MPI = w1 * N_ΔP + w2 * N_J, the MPI is a dimensionless number, its value is greater than 1 usually indicates that the fouling development trend is faster than the historical average level, other methods can also be used in other embodiments, this application does not limit it.

[0048] In some embodiments, adjusting the circulation flow rate based on a comparison between the membrane fouling development index and a preset membrane fouling threshold can be achieved using the following steps: Obtain the preset membrane fouling threshold; The membrane fouling development index is compared with the membrane fouling threshold to determine the current level of fouling development. Determine the circulation velocity adjustment amount corresponding to the grade range; Based on the circulating flow rate adjustment amount, a setpoint modification command is sent to the circulating flow rate control loop to adjust the circulating flow rate to the target value.

[0049] It should be noted that the membrane fouling threshold in this application is a predefined boundary value used to divide the numerical range of the membrane fouling development index. Its function is to quantify the continuous fouling trend into discrete "high, medium, and low" fouling development levels, providing a judgment benchmark for selecting different regulation strategies. The circulation flow rate regulation amount refers to the adjustment range required for the current circulation flow rate setpoint, determined based on the fouling development level, usually expressed as a percentage. Its function is to directly transform the diagnostic conclusion of the fouling trend into specific and executable circulation flow rate control instructions.

[0050] In specific implementation, the membrane fouling threshold can be preset in the following way: the preset membrane fouling threshold is based on statistical analysis of historical production batch data. Specifically, firstly, the membrane fouling development index calculated in the initial stage of filtration for a large number of typical batches of wine is collected to form a historical index dataset; then, by performing statistical analysis on the historical index dataset, such as calculating its mean and standard deviation, and combining the experience judgment of process experts on the degree of membrane fouling, boundary values ​​for classifying different levels of fouling development are determined. Typically, two thresholds are preset: one is a high fouling trend threshold, which can be set as the mean of the historical index dataset plus one standard deviation, used to identify batches with rapid fouling development; the other is a low fouling trend threshold, which can be set as the mean of the historical index dataset minus one standard deviation, used to identify batches with slow fouling development. The high fouling trend threshold and the low fouling trend threshold are pre-stored in the process parameter configuration file of the control system and are loaded when the system is initialized for a specific product or membrane component. Other methods can also be used in other embodiments, and this application does not limit them.

[0051] In specific implementation, the membrane fouling development index is compared with the membrane fouling threshold to determine the current level of fouling. This can be achieved by executing a three-stage numerical comparison logic: First, determine whether the membrane fouling development index is greater than the high fouling trend threshold. If so, the current level of fouling is determined to be in the "high" level range. If not, further determine whether the membrane fouling development index is less than the low fouling trend threshold. If so, it is determined to be in the "low" level range. If neither of the above conditions is met, it means that the membrane fouling development index is between the low fouling trend threshold and the high fouling trend threshold, and is determined to be in the "medium" level range. Other methods can also be used in other embodiments, and this application does not limit them.

[0052] In specific implementation, the circulation flow rate adjustment corresponding to the aforementioned level interval can be determined as follows: Maintain a "Pollution Level - Adjustment Strategy" lookup table. This table is based on process test data under different pollution trends. The pollution level intervals are divided according to the Membrane Fouling Development Index (MPI), for example: low pollution level (MPI < 0.8), medium pollution level (0.8 ≤ MPI < 1.5), and high pollution level (MPI ≥ 1.5). Each level corresponds to a specific flow rate adjustment percentage, as shown below: the circulation flow rate adjustment (ΔV%) for low pollution level is -8%, for medium pollution level it is 0% (maintained), and for high pollution level it is +15%. The circulation flow rate adjustment represents the adjustment range of the current circulation flow rate setpoint. After obtaining ΔV% from the table, the new target flow rate setpoint V_target = V_current × (1 + ΔV% / 100), where V_current is the original circulation flow rate. Other methods can also be used in other embodiments, and this application does not limit this.

[0053] In practice, based on the circulating flow rate adjustment amount, a setpoint modification command is sent to the circulating flow rate control loop to adjust the circulating flow rate to the target value. This can be achieved in the following way: First, a new target flow rate value is calculated based on the circulating flow rate adjustment amount obtained from the query and the current circulating flow rate set value. In the initial stage of filtration, this circulating flow rate set value is the initial circulating flow rate reference value. The calculation method is as follows: New target flow velocity value = Current circulating flow velocity setpoint × (1 + Circulating flow velocity adjustment amount / 100). After the calculation is completed, the new target flow velocity value is sent as a new setpoint command to the circulating flow velocity control loop that has been established and is running in step S103. The circulating flow velocity control loop is a closed-loop PID control loop with the circulating pump frequency converter as the actuator and the measured value of the electromagnetic flowmeter on the pipeline as feedback. After receiving the new setpoint command, the PID algorithm of the circulating flow velocity control loop will calculate the corresponding control output, drive the circulating pump frequency converter to change the motor speed, so that the actual circulating flow velocity changes smoothly and finally stabilizes at the new target flow velocity value, thus completing the adaptive adjustment of circulating flow velocity based on the initial pollution trend assessment. Other methods can also be used in other embodiments, and this application does not limit them.

[0054] It should be noted that the initial filtration phase in this application is a dynamic time period based on the process status. The end criteria are: from the start of filtration until the permeate flux decreases from the initial value to 10% or lasts for 15 minutes, whichever comes first, the main filtration phase begins. In addition, if the circulation flow rate is increased according to the membrane fouling development index during the main filtration phase, and the index continues to rise by more than 10% within 10 minutes in the next calculation cycle, it is determined that the fouling has intensified. An upgraded control strategy is automatically executed, that is, the circulation flow rate is further increased to 85% of the equipment's safe limit, and a warning is issued simultaneously, suggesting that the cleaning procedure be performed in advance after the filtration of this batch is completed.

[0055] In addition, it should be noted that the above steps can be based on the initial physical trends, namely the quantitative assessment of the rate of membrane fouling caused by pressure rise and flux drop, and preventive adaptive flow rate adjustment can be carried out accordingly, thereby improving the ability to predict batch fouling tendencies and the timeliness of intervention, and optimizing fluid conditions before fouling intensifies.

[0056] In step 105, during the main filtration stage, when the real-time turbidity is consistently lower than the terminal turbidity target value, and the transmembrane pressure difference and the permeate flux are within a reasonable operating range, the wine filtration is determined to be complete, and qualified wine filtrate is output.

[0057] In specific implementation, during the main filtration stage, when the real-time turbidity is consistently lower than the terminal turbidity target value, and the transmembrane pressure difference and the permeate flux are within reasonable operating ranges, the wine filtration is deemed complete, and qualified wine filtrate is output. This can be achieved in the following way: The reasonable operating range can be predefined based on membrane module safety and process economy. The reasonable range for transmembrane pressure difference is: the current transmembrane pressure difference TMP must be less than 75% of the maximum permissible transmembrane pressure difference TMP_max specified by the membrane module manufacturer. That is, the judgment condition is: TMP < 0.75 × TMP_max. The reasonable range for permeate flux is: the current permeate flux J must be greater than 30% of the initial flux J_initial of this batch of filtration. That is, the judgment condition is: J > 0.30 × J_initial. The final logical judgment condition for filtration completion must simultaneously meet the following three points and last for at least 5 minutes: real-time turbidity < terminal turbidity target value, TMP < 0.75 × TMP_max, J > 0.30 × TMP_max. J_initial: When the above three conditions are met simultaneously, the current batch of wine is determined to be filtered. Then, the completion sequence is automatically executed: First, a smooth stop command is sent to the circulation pump and pressure regulating valve to stop the filtration action. Then, the control pipeline switching valve directs all the filtrate that meets the quality standards in the membrane system and related pipelines to the designated qualified wine filtrate receiving tank. Finally, the completion time, final parameters and production report are recorded, thus completing the fully automatic closed-loop control process from online monitoring to endpoint determination and product output. If the system running time exceeds the preset maximum process time and the completion conditions are not met, an automatic alarm will be triggered to prompt manual intervention. Other methods can also be used in other embodiments, and this application does not limit them.

[0058] In addition, in some embodiments, during the main filtration stage, when the real-time turbidity is consistently higher than the terminal turbidity target value, a diagnostic process is triggered to check membrane integrity or adjust pretreatment process parameters.

[0059] In practice, during the main filtration stage, when the real-time turbidity consistently exceeds the terminal turbidity target value, a diagnostic process is triggered to check membrane integrity or adjust pretreatment process parameters. This can be achieved as follows: During the main filtration stage, if the real-time turbidity value is consistently and stably higher than the terminal turbidity target value for more than a preset anomaly judgment time window (e.g., for 10 consecutive minutes), and the possibility of momentary sensor malfunction is ruled out, an anomaly diagnostic process is automatically triggered. This anomaly diagnostic process first locks the current filtration state and records a snapshot of all process parameters. The first step in the diagnosis is a membrane integrity check: a built-in membrane integrity test program is automatically started. Specifically, while maintaining circulation, the filtrate-side valve is temporarily closed, and clean compressed air or nitrogen below the membrane bubble point pressure is applied to the membrane system. The pressure decay rate is monitored over a specific time period. If the pressure decay rate exceeds the allowable threshold for this type of membrane module, then... If membrane element damage or sealing leakage is detected, an alarm is generated to prompt replacement or repair. If the membrane integrity check passes, the second step of diagnosis is initiated: pretreatment process parameter adaptability analysis. The initial characteristic parameters of the current batch of wine are retrieved, especially the initial turbidity and viscosity characteristics, and compared with historical batch data of successful filtration. At the same time, the membrane fouling development index and its changing trend calculated in the early stage of filtration are analyzed. Based on these data, the reasons for possible pretreatment deficiencies are inferred through the built-in rule base or model, such as unsuitable particle size distribution or excessive colloidal substances. Specific suggestions for adjusting pretreatment process parameters are given through the human-machine interface. For example, it is suggested that the remaining wine from the same batch that has not yet been filtered be returned to the previous process, the amount of fining agent such as bentonite be added, the settling time be extended, or the separation factor of the centrifuge be adjusted. Other methods can also be used in other embodiments, and this application does not limit them.

[0060] It should be noted that the above steps can be based on the precise endpoint determination and automatic output of three conditions: real-time turbidity, transmembrane pressure difference and permeate flux, thereby improving the accuracy of filtration endpoint determination and realizing a fully automated closed loop from quality monitoring to product output.

[0061] In another aspect, in some embodiments, this application provides a wine cross-flow filtration flow rate control system, with reference to... Figure 4 The figure is a schematic diagram of the structure of a wine cross-flow filtration flow rate control system according to some embodiments of this application. The wine cross-flow filtration flow rate control system includes: an acquisition module 401, a processing module 402, and an execution module 403, which are described below: The acquisition module 401 in this application is mainly used to acquire the initial characteristic parameters of the current batch of wine; Processing module 402, in this application, is mainly used to determine a fixed terminal turbidity target value based on product standards and downstream process requirements; The processing module 402 described in this application is further configured to determine the initial circulation flow rate reference value and the initial operating pressure based on the initial characteristic parameters and the preset membrane module process parameters, and then start cross-flow filtration with the initial circulation flow rate reference value and the initial operating pressure, and simultaneously monitor the real-time turbidity, transmembrane pressure difference and permeate flux of the filtrate. The processing module 402 described in this application is also used to determine the membrane fouling development index, which characterizes the speed of fouling development, based on the rising rate of the transmembrane pressure difference and the decreasing rate of the permeate flux in the initial stage of filtration, and then adjust the circulation flow rate according to the comparison result of the membrane fouling development index and the preset membrane fouling threshold. The execution module 403 in this application is mainly used to determine that the wine filtration is completed and output qualified wine filtrate when the real-time turbidity is continuously lower than the terminal turbidity target value and the transmembrane pressure difference and the permeate flux are within a reasonable operating range during the main filtration stage.

[0062] The various modules in the aforementioned cross-flow filtration rate control system for wine can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device, or stored in the computer device's memory as software, so that the processor can call and execute the corresponding operations of each module.

[0063] In another embodiment, this application provides a computer device, which may be a server, and its internal structure diagram may be as follows. Figure 5 As shown, the computer device includes a processor, memory, and a network interface connected via a system bus. The processor provides computational and control capabilities. The memory includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores an operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage medium. The database stores wine cross-flow filtration rate control data. The network interface communicates with external terminals via a network connection. When executed by the processor, the computer program implements a wine cross-flow filtration rate control method.

[0064] Those skilled in the art will understand that Figure 5The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0065] In one embodiment, a computer device is also provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps in the above embodiment of the wine cross-flow filtration flow rate control method.

[0066] In one embodiment, a computer-readable storage medium is provided storing a computer program that, when executed by a processor, implements the steps in the above-described wine cross-flow filtration flow rate control method embodiment.

[0067] In one embodiment, a computer program product or computer program is provided, comprising computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the computer device to perform the steps described in the wine cross-flow filtration flow rate control method embodiment.

[0068] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the methods described above. Any references to memory, storage, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, or optical storage, etc. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM), etc.

[0069] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0070] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the invention patent. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this patent application should be determined by the appended claims.

Claims

1. A method for controlling the flow rate in cross-flow filtration of wine, characterized in that, Includes the following steps: Obtain the initial characteristic parameters of the current batch of wine; A fixed target value for terminal turbidity is determined based on product standards and downstream process requirements; The initial circulation flow rate reference value and the initial operating pressure are determined based on the initial characteristic parameters and the preset membrane module process parameters. Then, cross-flow filtration is started with the initial circulation flow rate reference value and the initial operating pressure, and the real-time turbidity, transmembrane pressure difference and permeate flux of the filtrate are monitored simultaneously. In the initial stage of filtration, based on the rate of increase of the transmembrane pressure difference and the rate of decrease of the permeate flux, a membrane fouling development index is determined to characterize the speed of fouling development. Then, the circulation flow rate is adjusted according to the comparison result between the membrane fouling development index and the preset membrane fouling threshold. During the main filtration stage, when the real-time turbidity is consistently lower than the terminal turbidity target value, and the transmembrane pressure difference and the permeate flux are within a reasonable operating range, the wine filtration is deemed complete, and qualified wine filtrate is output.

2. The method as described in claim 1, characterized in that, Determining fixed target values ​​for terminal turbidity based on product standards and downstream process requirements specifically includes: Determine the clarity standard parameters corresponding to the type of wine in the current batch; Determine the maximum permissible limit parameters for the turbidity of the feed liquid at the equipment interface of the cold stabilization treatment; By comparing the clarity standard parameter with the maximum permissible limit parameter, the more stringent value is selected as the fixed terminal turbidity target value that must be achieved in this filtration process.

3. The method as described in claim 1, characterized in that, Determining the initial circulation flow rate baseline and initial operating pressure based on the initial characteristic parameters and preset membrane module process parameters specifically includes: The basic range of values ​​for the initial circulation flow rate and the initial operating pressure is determined based on the preset membrane module process parameters. Based on the initial turbidity and viscosity characteristics in the initial characteristic parameters, joint interpolation calculations are performed within the basic value range to obtain the initial circulation flow rate and initial operating pressure values. The initial circulation flow rate and the initial operating pressure are verified for process safety. The values ​​that pass the verification are ultimately determined as the initial circulation flow rate reference value and the initial operating pressure for starting the filter.

4. The method as described in claim 1, characterized in that, The process of initiating cross-flow filtration based on the initial circulation flow rate and the initial operating pressure, and simultaneously monitoring the real-time turbidity of the filtrate, transmembrane pressure differential, and permeate flux, specifically includes: The initial circulating flow rate reference value and the initial operating pressure are used as setpoint commands and sent to the circulating pump and pressure regulating valve. Drive the circulating pump and the pressure regulating valve to stabilize the circulating flow rate and operating pressure at the control set point, so as to start cross-flow filtration; Simultaneously with the start of filtration, the online sensor group installed on the filtrate pipeline and membrane module is activated to continuously collect the raw turbidity signal of the filtrate, the raw pressure signals at the inlet and outlet of the membrane module, and the raw filtrate flow rate signal. The acquired raw signals are conditioned, converted from analog to digital and converted to engineering units to generate and output real-time turbidity, transmembrane pressure difference and permeate flux in digital form.

5. The method as described in claim 1, characterized in that, In the initial stage of filtration, based on the rate of increase of the transmembrane pressure difference and the rate of decrease of the permeate flux, the membrane fouling development index, which characterizes the rate of fouling development, is determined, specifically including: During the initial filtration time window, time-series data of the transmembrane pressure difference and the permeate flux are acquired; Linear fitting is performed on the time series data of the transmembrane pressure difference, and the absolute value of its slope is used as the rate of increase of the transmembrane pressure difference. Similarly, linear fitting is performed on the time series data of the permeate flux, and the absolute value of its slope is used as the rate of decrease of the permeate flux. The rising rate and the falling rate are normalized and weighted and summed to output a membrane fouling development index that characterizes the speed of fouling development.

6. The method as described in claim 1, characterized in that, Adjusting the circulation flow rate based on the comparison between the membrane fouling development index and the preset membrane fouling threshold specifically includes: Obtain the preset membrane fouling threshold; The membrane fouling development index is compared with the membrane fouling threshold to determine the current level of fouling development. Determine the circulation velocity adjustment amount corresponding to the grade range; Based on the circulating flow rate adjustment amount, a setpoint modification command is sent to the circulating flow rate control loop to adjust the circulating flow rate to the target value.

7. The method as described in claim 1, characterized in that, Also includes: When the real-time turbidity is consistently higher than the terminal turbidity target value, a diagnostic process is triggered to check membrane integrity or adjust pretreatment process parameters.

8. A wine cross-flow filtration flow rate control system, characterized in that, The system includes: The acquisition module is used to acquire the initial characteristic parameters of the current batch of wine; The processing module is used to determine a fixed target value for terminal turbidity based on product standards and downstream process requirements; The processing module is also used to determine the initial circulation flow rate reference value and the initial operating pressure based on the initial characteristic parameters and the preset membrane module process parameters, and then start cross-flow filtration with the initial circulation flow rate reference value and the initial operating pressure, and simultaneously monitor the real-time turbidity of the filtrate, the transmembrane pressure difference and the permeate flux. The processing module is also used to determine the membrane fouling development index, which characterizes the speed of fouling development, based on the rising rate of the transmembrane pressure difference and the decreasing rate of the permeate flux in the initial stage of filtration, and then adjust the circulation flow rate according to the comparison result of the membrane fouling development index and the preset membrane fouling threshold. The execution module is used to determine that the wine filtration is complete and output qualified wine filtrate when the real-time turbidity is consistently lower than the terminal turbidity target value and the transmembrane pressure difference and the permeate flux are within a reasonable operating range during the main filtration stage.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the wine cross-flow filtration flow rate control method according to any one of claims 1 to 7.

10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the steps of the wine cross-flow filtration flow rate control method as described in any one of claims 1 to 7.

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