Foaming machine flow self-adaptive regulation and control system and method based on accurate control of metering pump

Abstract

The invention discloses a foaming machine flow self-adaptive regulation and control system and method based on accurate control of a metering pump, relates to the field of flow regulation and control, and aims at enabling flow data of a foaming machine regulated and controlled by the metering pump to meet the requirements of a foaming process from the angle of adjusting related parameters of the metering pump. Therefore, the foaming process can be carried out smoothly; according to the method, a final foaming machine flow regulation and control mapping equation is constructed, so that corresponding foaming machine flow data can be obtained based on an equation mapping mode every time, actual operation is not needed, and the regulation efficiency is greatly improved; a manta ray optimization algorithm is adopted to carry out multiple times of iterative adjustment on the multiple flow influence parameters of the calibrated metering pump, and the error between the corresponding adjusted flow data of the foaming machine and the upper and lower limits of the corresponding foaming process flow requirement range serves as a fitness function; and the adjusted flow data of the foaming machine finally meets the flow requirement of the foaming process.

Description

Technical Field

[0001] The present invention belongs to the field of flow regulation, and more particularly, to a flow self-adaptive regulation system and method for a foaming machine based on precise control of a metering pump. Background Art

[0002] In the foaming process, the flow data of the foaming machine needs to meet the process requirements to ensure the smooth progress of the process; the metering pump has a regulating effect on the flow of the foaming machine. In the existing traditional operations, a mapping relationship reflecting the parameters of the metering pump and the flow of the foaming machine has not been constructed. Therefore, the traditional method of relying on actual operations to adjust the parameters of the metering pump to obtain appropriate flow data is inefficient. Summary of the Invention

[0003] In view of the problems in the related art, the present invention provides a flow self-adaptive regulation system and method for a foaming machine based on precise control of a metering pump to overcome the above-mentioned technical problems existing in the existing related art.

[0004] To solve the above technical problems, the present invention is achieved through the following technical solutions: The present invention provides a flow self-adaptive regulation method for a foaming machine based on precise control of a metering pump, including the following steps: S1. Set a metering pump and several types of parameters that affect the flow of the foaming machine other than the metering pump, and perform a calibration adjustment operation on the metering pump to be calibrated to obtain a calibrated metering pump; S2. In cooperation with the parameter types set in S1, collect several groups of historical foaming machine flow data after regulating the flow of the foaming machine using the calibrated metering pump, and the parameter data of various types of metering pumps that affect the flow of the foaming machine, and construct a final foaming machine flow regulation mapping equation; S3. Use the calibrated metering pump to regulate the flow of the currently used foaming machine. After the regulation is completed, obtain the current foaming machine flow data; determine whether the current foaming machine flow data is within the current flow target value range of the foaming machine. If not, input the parameters of the calibrated metering pump obtained each time into the final foaming machine flow regulation mapping equation to obtain an adjustment result until the adjustment result is within the current flow target value range of the foaming machine; This solution makes the flow data of the foaming machine after being regulated by the metering pump meet the requirements of the foaming process from the perspective of adjusting the relevant parameters of the metering pump, thus ensuring the smooth progress of the foaming process; among them, by constructing the final foaming machine flow regulation mapping equation, after each adjustment of the parameters of the metering pump, the corresponding foaming machine flow data can be obtained based on the equation mapping method, without the need for actual operations, greatly increasing the adjustment efficiency.

[0005] Preferably, several types of parameters to be adjusted during the maintenance of the metering pump are set to obtain a set of metering pump maintenance parameter types, and a calibration adjustment operation is performed on the metering pump to be calibrated to obtain a calibrated metering pump. By performing a calibration adjustment operation on the metering pump to be calibrated, the measurement results obtained by subsequently measuring the flow rate of the foaming machine using it are accurate; furthermore, the flow rate of the foaming machine can be correctly adjusted using the metering pump according to the correct measurement results, ensuring the efficiency and accuracy of the adjustment.

[0006] Preferably, the calibration adjustment operation on the metering pump to be calibrated in conjunction with the set of metering pump maintenance parameter types in S12 includes the following steps: S121. Set several calibration points of the metering pump to be calibrated to obtain a set of metering pump points to be calibrated; traverse the set of metering pump points to be calibrated and record the currently traversed calibration point as the current metering pump point to be calibrated; then set the calibration times threshold for a single calibration point. S122. Accurately place the stroke adjustment mechanism of the metering pump to be calibrated at the position of the current metering pump point to be calibrated; set the fluid medium to be added; when the temperature, pressure, and flow rate of the fluid medium to be added are stable, inject the fluid medium to be added into the standard metal measuring vessel from the filling port of the metering pump to be calibrated; and start timing with a stopwatch simultaneously when starting the injection. When the injection process has been running for a period of time (not less than 1 min), stop the injection operation and stop the stopwatch timing simultaneously to obtain the current injection time a 1; After the injection is completed, use a thermometer to record the temperature of the fluid medium to be added in the standard metal measuring vessel to obtain the temperature data of the fluid medium to be added in the measuring vessel a 2; Then read the volume reading of the liquid in the standard metal measuring vessel to obtain the volume data of the fluid medium to be added in the measuring vessel a 3; Correct the volume data of the fluid medium to be added in the measuring vessel to obtain the corrected volume data of the fluid medium to be added in the measuring vessel a 4; The calculation formula is as follows, ; In the formula, represents the coefficient of thermal expansion of the fluid medium to be added; Calculate the actual value of the liquid flow rate discharged by the metering pump to be calibrated according to the corrected volume data of the fluid medium to be added in the measuring vessel, denoted as the actual discharged liquid flow rate a 5; As follows, ; S123. Set a measurement error threshold; use the metering pump to be calibrated to discharge the fluid medium to be added, and after the discharge is completed, read the flow rate reading of the metering pump to be calibrated to obtain the measured discharged liquid flow rate a6; When the absolute value of the difference between the actual value and the measured value of the discharge liquid flow rate is greater than or equal to the measurement error threshold, perform a calibration adjustment operation on the metering pump to be calibrated according to the set of metering pump maintenance parameter types; otherwise, no calibration adjustment operation is required; Repeat S122 and S123. When the number of repetitions is greater than or equal to the single calibration point calibration number threshold, stop repeating; S124. After stopping the repetition, use the next metering pump calibration point in the metering pump calibration point set to be calibrated as the current metering pump calibration point; and repeat S122 and S123 until the current metering pump calibration point is the last metering pump calibration point in the metering pump calibration point set; By performing multiple calibration tests and adjustments on each calibration point of the metering pump to be calibrated respectively, the data occasionality brought by a single calibration process is reduced, and the accuracy of the measurement result of the metering pump to be calibrated after calibration is further ensured.

[0007] Preferably, S2 includes the following steps: S21. Collect several groups of data on the flow rate of the foaming machine after the calibrated metering pump is used historically to control the flow rate of the foaming machine, the parameter data of various types of metering pumps that affect the flow rate of the foaming machine, and various types of parameters other than the metering pump parameters that affect the flow rate of the foaming machine, obtain the historical metering pump flow rate influence parameter matrix, the historical non-metering pump flow rate influence parameter matrix, and the historical regulated foaming machine flow rate data set, and construct the final foaming machine flow rate regulation mapping equation; By constructing the final foaming machine flow rate regulation mapping equation, it is used to realize the mapping between the parameter data of various types of metering pumps that affect the flow rate of the foaming machine and the flow rate of the foaming machine. When adjusting the parameters of the metering pump that affect the flow rate of the foaming machine subsequently, the corresponding adjustment effect can be obtained in a timely manner, making the adjustment process more efficient; among them, by collecting several groups of data on the flow rate of the foaming machine after the calibrated metering pump is used historically to control the flow rate of the foaming machine and the corresponding parameter data of various types of metering pumps that affect the flow rate of the foaming machine, it provides data support for constructing the final foaming machine flow rate regulation mapping equation.

[0008] Preferably, constructing the final foaming machine flow rate regulation mapping equation in S21 includes the following steps: S221. Construct the initial foaming machine flow rate regulation mapping equation; S222. Substitute each row of data in the historical metering pump flow rate influence parameter matrix into the initial foaming machine flow rate regulation mapping equation for mapping to obtain the historical regulated foaming machine flow rate mapping data set; S223. Adjust the initial foam machine flow regulation mapping equation according to the historical foam machine flow mapping dataset after regulation to obtain the final foam machine flow regulation mapping equation; Based on the method of assigning parameter coefficients, a mapping relationship is established between the parameter data of various types of metering pumps that affect the foam machine flow and the flow data of the regulated foam machine, providing a mapping tool for obtaining the corresponding foam machine flow data in a timely manner when adjusting the parameter data of various types of current metering pumps that affect the foam machine flow in the future; in addition, by substituting the collected historical data into the initial foam machine flow regulation mapping equation for preliminary mapping and calculating the error between the mapped data and the actual data, it is possible to know whether the mapping accuracy rate of the initial foam machine flow regulation mapping equation meets the requirements and then determine whether it is necessary to adjust the initial foam machine flow regulation mapping equation, so as to ensure that the mapping accuracy rate of the obtained final foam machine flow regulation mapping equation meets the requirements.

[0009] Preferably, in S223, the bat optimization algorithm is used to adjust the initial foam machine flow regulation mapping equation.

[0010] Preferably, S3 includes the following steps: S31. Set the currently used foam machine and the corresponding flow target value interval to obtain the current foam machine flow target value interval; when the flow of the currently used foam machine is regulated according to the calibrated metering pump, obtain the current foam machine flow data; S32. When the current foam machine flow data is within the current foam machine flow target value interval, perform S33; otherwise, adjust the parameters of the calibrated metering pump in cooperation with the final foam machine flow regulation mapping; S33. Collect several groups of real-time flow data of the currently used foam machine and predict the flow data of the currently used foam machine at future time points to obtain the current foam machine future flow dataset; when there is flow data in the current foam machine future flow dataset that is not within the current foam machine flow target value interval, adjust the parameters of the calibrated metering pump in cooperation with the final foam machine flow regulation mapping equation; To prevent the flow of the foam machine from fluctuating over time, therefore, by predicting the flow data of the currently used foam machine at future time points and then adjusting the parameters of the calibrated metering pump according to the prediction results, the working stability of the metering pump and the foam machine in the future period is ensured.

[0011] Preferably, in S33, the SVM model is used to predict the flow data of the currently used foam machine at future time points; The SVM model determines the optimal hyperplane by maximizing the margin, rather than solving it through the gradient descent method like neural networks. Therefore, it can avoid falling into local optimal solutions. Its final decision function is only determined by a few support vectors, and the computational complexity depends on the number of support vectors rather than the dimension of the sample space, avoiding the "curse of dimensionality"; it will automatically select features that have an important impact on classification or regression during the training process, thus simplifying the feature engineering process; it has a certain robustness to noise and outliers in the data; based on the above, the SVM model is used in this solution to predict the flow data of the current foam machine at future time points, ensuring the correctness of the prediction.

[0012] Preferably, the adjustment of the parameters of the calibrated metering pump in S32 and S33 includes the following steps: S321. Set the value range of each parameter of the calibrated metering pump and randomly set the initial position of each manta ray in the manta ray population that affects the parameter adjustment of the calibrated metering pump flow to obtain the second initial position matrix; S322. Construct the fitness function of the manta ray population that affects the parameter adjustment of the calibrated metering pump flow; S323. Iteratively update the second initial position matrix in cooperation with the fitness function of the manta ray population that affects the parameter adjustment of the calibrated metering pump flow; S324. When the maximum number of iterations is reached, stop the iteration to obtain the second final global best fitness and the second final global best position; when the second final global best fitness is within the current flow target value range of the foam machine, set each position component of the second final global best position to the calibrated metering pump, and the adjustment is completed; The manta ray optimization algorithm simulates the foraging behavior of manta rays and adopts three foraging methods: chain, spiral, and tumbling, enabling the algorithm to cover a wider search space during the search process, increasing the possibility of finding the global optimal solution; by continuously adjusting the search direction and strategy during the search process, it can avoid falling into local optimal solutions to a certain extent; based on the above advantages, this solution uses the manta ray optimization algorithm to iteratively adjust multiple flow influence parameters of the calibrated metering pump, and uses the error between the flow data of the corresponding adjusted foam machine and the upper and lower limits of the corresponding foam process flow requirement range as the fitness function; therefore, as the iteration progresses, the flow data of the adjusted foam machine finally meets the foam process flow requirements.

[0013] The foam machine flow adaptive control system based on precise control of the metering pump includes a foam flow influence parameter type setting module, a metering pump measurement and calibration module, a foam machine flow control mapping equation construction module, a current foam machine flow control module, and a calibrated metering pump parameter adjustment module.

[0014] The present invention has the following beneficial effects: 1. In the present invention, from the perspective of adjusting the relevant parameters of the metering pump, the flow rate data of the foam machine after being regulated by the metering pump meet the requirements of the foaming process, thus ensuring the smooth progress of the foaming process. Among them, by constructing the final flow rate regulation mapping equation of the foam machine, after each adjustment of the parameters of the metering pump, the corresponding flow rate data of the foam machine can be obtained based on the equation mapping method, without the need for actual operation, greatly increasing the adjustment efficiency.

[0015] 2. In the present invention, by conducting multiple calibration tests and adjustments on each calibration point of the metering pump to be calibrated respectively, the data occasionality brought by a single calibration process is reduced, further ensuring the accuracy of the measurement results of the metering pump to be calibrated after calibration.

[0016] 3. In the present invention, the bat optimization algorithm is used to perform multiple iterative adjustments on multiple flow rate influence parameters of the calibrated metering pump, and the error between the flow rate data of the corresponding adjusted foam machine and the upper and lower limits of the flow rate requirement range of the corresponding foaming process is used as the fitness function; the flow rate data of the adjusted foam machine finally meet the flow rate requirements of the foaming process.

[0017] 4. In the present invention, by using the bat optimization algorithm, as the iteration progresses, the coefficient of each independent variable and the bias parameter of the initial flow rate regulation mapping equation of the foam machine are adjusted, so that the mapping accuracy rate of the initial flow rate regulation mapping equation of the foam machine reaches the optimal, meeting the mapping requirements; it ensures the accuracy of obtaining the corresponding flow rate data of the foam machine based on the metering pump and several parameters that have an impact on the flow rate of the foam machine other than the metering pump parameters, and further ensures the accuracy of the direction of adjusting the parameters that have an impact on the flow rate of the foam machine of the metering pump according to the flow rate data of the foam machine.

[0018] Of course, it is not necessary for any product implementing the present invention to achieve all the above-mentioned advantages simultaneously. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the technical solutions of the embodiments of the invention, the drawings required for describing the embodiments will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments of the invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0020] Figure 1 It is the overall flow chart of the self-adaptive regulation method for the flow rate of the foam machine based on the precise control of the metering pump of the present invention; Figure 2 It is the flow chart of the self-adaptive regulation method for the flow rate of the foam machine based on the precise control of the metering pump of the present invention Figure 3Flow schematic diagram for constructing the final foaming machine flow regulation mapping equation of the present invention; Figure 4 Flow schematic diagram for adjusting multiple flow influence parameters of the calibrated metering pump of the present invention; Figure 5 Module schematic diagram of the foaming machine flow adaptive regulation system based on precise control of the metering pump of the present invention. Detailed implementation manners

[0021] The following will clearly and completely describe the technical solutions in the embodiments of the invention with reference to the accompanying drawings in the embodiments of the invention. Obviously, the described embodiments are only a part of the embodiments of the invention, rather than all the embodiments. Based on the embodiments of the invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the invention.

[0022] Embodiment 1

[0023] Please refer to Figures 1-4 , this embodiment is a foaming machine flow adaptive regulation method based on precise control of the metering pump, including the following steps: S1. Set several parameter types of the metering pump and other types of parameters that affect the flow of the foaming machine to obtain the first foaming machine flow influence parameter type set and the second foaming machine flow influence parameter type set; perform calibration adjustment operations on the metering pump to be calibrated to obtain the calibrated metering pump; The said S1 includes the following steps: S11. Set several parameter types of the metering pump that affect the flow of the foaming machine to obtain the first foaming machine flow influence parameter type set; the first foaming machine flow influence parameter type set includes stroke length and rotational speed, etc.; then set several parameter types of the parameters other than the metering pump parameters that affect the flow of the foaming machine to obtain the second foaming machine flow influence parameter type set; the second foaming machine flow influence parameter type set includes the viscosity, temperature of the foaming agent, and the internal pressure of the foaming machine, etc. Among them, the viscosity, temperature of the foaming agent, and the internal pressure data of the foaming machine can be obtained by collecting through the rotational viscometer method, temperature sensor, and pressure sensor respectively; S12. Set several parameter types that need to be adjusted during the maintenance of the metering pump to obtain the metering pump maintenance parameter type set; then set the metering pump to be calibrated and perform calibration adjustment operations on the metering pump to be calibrated in combination with the metering pump maintenance parameter type set to obtain the calibrated metering pump; the metering pump maintenance parameter type set includes the position parameters of components such as the plunger, piston, and diaphragm, and the position and tension parameters of the diaphragm after replacing the diaphragm, etc.; The calibration adjustment operation of the metering pump to be calibrated in combination with the metering pump maintenance parameter type set in S12 includes the following steps: S121. Set several calibration points for the metering pump to be calibrated to obtain a set of calibration points for the metering pump to be calibrated; traverse the set of calibration points for the metering pump and record the currently traversed calibration point as the current calibration point for the metering pump to be calibrated; then set the threshold for the number of calibrations for a single calibration point. S122. Accurately position the stroke adjustment mechanism of the metering pump to be calibrated at the position of the current calibration point for the metering pump to be calibrated; set the fluid medium to be added; when the temperature, pressure, and flow rate of the fluid medium to be added are stable, inject the fluid medium to be added into the standard metal measuring device from the filling port of the metering pump to be calibrated; and start timing with a stopwatch at the same time as starting the injection. After the injection process has been running for a period of time (not less than 1 minute), stop the injection operation and stop the stopwatch timing simultaneously to obtain the current injection time a 1; After the injection is completed, use a thermometer to record the temperature of the fluid medium to be added in the standard metal measuring device to obtain the temperature data of the fluid medium to be added in the measuring device. a 2; Then read the volume reading of the liquid in the standard metal measuring device to obtain the volume data of the fluid medium to be added in the measuring device. a 3. Correct the volume data of the fluid medium to be added in the measuring device to obtain the corrected volume data of the fluid medium to be added in the measuring device. a 4. The calculation formula is as follows. ; In the formula, represents the coefficient of thermal expansion of the fluid medium to be added. Calculate the actual value of the liquid flow rate discharged by the metering pump to be calibrated based on the corrected volume data of the fluid medium to be added in the measuring device, and record it as the actual value of the discharged liquid flow rate. a 5. As follows. ; S123. Set the measurement error threshold; use the metering pump to be calibrated to discharge the fluid medium to be added, and after the discharge is completed, read the flow rate reading of the metering pump to be calibrated to obtain the measured value of the discharged liquid flow rate. a 6. When the absolute value of the difference between the actual value of the discharged liquid flow rate and the measured value of the discharged liquid flow rate is greater than or equal to the measurement error threshold, perform a calibration adjustment operation on the metering pump to be calibrated according to the set of metering pump maintenance parameter types; otherwise, no calibration adjustment operation is required. Repeat S122 and S123. When the number of repetitions is greater than or equal to the threshold for the number of calibrations for a single calibration point, stop repeating. S124. After stopping the repetition, use the next metering pump calibration point to be calibrated in the set of metering pump calibration points to be calibrated as the current metering pump calibration point; and repeat S122 and S123 until the current metering pump calibration point is the last metering pump calibration point in the set of metering pump calibration points to be calibrated; S2. Construct the final foaming machine flow regulation mapping equation by collecting several groups of historical foaming machine flow data after regulating the foaming machine flow with calibrated metering pumps and the corresponding parameter data of various types of metering pumps that affect the foaming machine flow; The S2 includes the following steps: S21. In cooperation with the first set of foaming machine flow influence parameter types, collect several groups of historical foaming machine flow data after regulating the foaming machine flow with calibrated metering pumps, the corresponding parameter data of various types of metering pumps that affect the foaming machine flow, and the corresponding parameters of various types that affect the foaming machine flow other than metering pump parameters, to obtain the historical metering pump flow influence parameter matrix , the historical non-metering pump flow influence parameter matrix and the historical regulated foaming machine flow data set , denotes the i th group of historical foaming machine flow data after regulating the foaming machine flow with calibrated metering pumps, denotes the total number of groups of historical data of regulating the foaming machine flow with calibrated metering pumps collected; S22. Use the historical metering pump flow influence parameter matrix and the historical regulated foaming machine flow data set to construct the final foaming machine flow regulation mapping equation; The S22 includes the following steps: S221. In cooperation with the historical metering pump flow influence parameter matrix and the historical regulated foaming machine flow data set, construct the initial foaming machine flow regulation mapping equation; as follows, ; Wherein, is the dependent variable of the initial foaming machine flow regulation mapping equation, representing the foaming machine flow data after regulating the foaming machine flow with calibrated metering pumps; , are the j th and th independent variables of the initial foaming machine flow regulation mapping equation respectively, representing the j th type of metering pump and the parameter data of the parameters other than the metering pump that affect the foaming machine flow respectively, , are respectively , The corresponding independent variable coefficient; Indicates the bias parameter; 、 respectively represent the total number of the set metering pumps and the types of parameters that affect the flow rate of the foaming machine other than the metering pumps; S222. Substitute each row of data in the historical metering pump flow rate influence parameter matrix into the initial foaming machine flow rate regulation mapping equation for mapping to obtain the historical regulated foaming machine flow rate mapping data set , b i Indicates the mapping data obtained by substituting the i th row of data in the historical metering pump flow rate influence parameter matrix into the initial foaming machine flow rate regulation mapping equation for mapping; Calculate the error data between the historical regulated foaming machine flow rate mapping data set and the historical regulated foaming machine flow rate data set to obtain the historical regulated foaming machine flow rate mapping error data ; as follows, ; S223. Set the foaming machine flow rate mapping error threshold; when the historical regulated foaming machine flow rate mapping error data is greater than or equal to the foaming machine flow rate mapping error threshold, adjust the initial foaming machine flow rate regulation mapping equation until the historical regulated foaming machine flow rate mapping error data is less than the foaming machine flow rate mapping error threshold, and obtain the final foaming machine flow rate regulation mapping equation; otherwise, there is no need to adjust the initial foaming machine flow rate regulation mapping equation, and use the initial foaming machine flow rate regulation mapping equation as the final foaming machine flow rate regulation mapping equation; The adjustment of the initial foaming machine flow rate regulation mapping equation in S223 includes the following steps: S2231. Set the value range of each independent variable coefficient and bias parameter in the initial foaming machine flow rate regulation mapping equation to obtain the foaming machine flow rate mapping independent variable coefficient value range set and the foaming machine flow rate mapping bias parameter value range , 、 respectively represent the lower limit and upper limit of the value of the bias parameter of the initial foaming machine flow rate regulation mapping equation; ; Among them, 、 respectively represent the lower limit and upper limit of the value of the i th independent variable coefficient of the initial foaming machine flow rate regulation mapping equation; Construct the flow regulation mapping of the foaming machine to adjust the manta ray population; set the maximum number of iterations for the flow regulation mapping of the foaming machine to adjust the manta ray population to be and the current number of iterations to be , which respectively represent the maximum number of iterations of the flow mapping adjustment and the current number of iterations of the flow mapping adjustment; the number of search space dimensions of the flow regulation mapping of the foaming machine to adjust the manta ray population is ; S2232. Generate the initial position matrix of each manta ray in the flow regulation mapping of the foaming machine to adjust the manta ray population according to the set of independent variable coefficient value ranges of the foaming machine flow mapping and the value range of the foaming machine flow mapping bias parameter, and obtain the first set of initial position matrices , c j represents the initial position matrix of the j th manta ray in the flow regulation mapping of the foaming machine to adjust the manta ray population, represents the scale of the flow regulation mapping of the foaming machine to adjust the manta ray population; The generation formula is as follows, ; ; In the formula, , respectively represent random numbers between 0 and 1 generated for c j1i and c j2 ; c j1i represents c j 's position component in the i th independent variable coefficient dimension of the initial flow regulation mapping equation of the foaming machine, c j2 represents c j 's position component in the bias parameter dimension of the initial flow regulation mapping equation of the foaming machine; S2233. Construct the fitness function of the flow regulation mapping of the foaming machine to adjust the manta ray population ; as follows, ; Among them, represents the error between the mapped data and the corresponding actual data obtained by substituting a set of independent variable coefficients and bias parameters obtained in each iteration into the initial flow regulation mapping equation of the foaming machine and then substituting each row of data in the historical metering pump flow influence parameter matrix in S222 into the initial flow regulation mapping equation for mapping; is a positive number, representing the first correction parameter, used to prevent The denominator is 0; S2234. Start iteration. Before iteration, set the current iteration number of the flow mapping adjustment to 1. During the first-round iteration, use the flow control mapping of the foaming machine to adjust the fitness function of the manta ray population Calculate the fitness values of the initial position matrices of each manta ray in the first initial position matrix set to obtain the first fitness value set. Take the maximum fitness value in the first fitness value set and the corresponding initial position matrix of the manta ray as the first global best fitness and the first global best position respectively. Update the initial position matrices of each manta ray in the first initial position matrix set according to the first global best fitness and the first global best position. After the update is completed, increment the current iteration number of the flow mapping adjustment by 1 and enter the next round of iteration; During each other round of iteration, use the flow control mapping of the foaming machine to adjust the fitness function of the manta ray population Calculate the fitness values of the position matrices of each manta ray in the manta ray population adjusted by the flow control mapping of the foaming machine updated during the previous round of iteration to obtain the second fitness value set. Take the maximum fitness value in the second fitness value set and the corresponding position matrix of the manta ray as the second global best fitness and the second global best position respectively. Update the position matrices of each manta ray in the manta ray population adjusted by the flow control mapping of the foaming machine updated during the previous round of iteration according to the second global best fitness and the second global best position. After the update is completed, increment the current iteration number of the flow mapping adjustment by 1 and enter the next round of iteration; S2235. When Stop iteration to obtain the first final global best fitness and the first final global best position; otherwise, continue iteration until At this time. Take the first final global best fitness as the historical optimized foaming machine flow mapping error data. When the historical optimized foaming machine flow mapping error data is less than the foaming machine flow mapping error threshold, substitute each position component of the first final global best position into the initial foaming machine flow control mapping equation to obtain the final foaming machine flow control mapping equation; otherwise, return to S2234 to continue iteration until the historical optimized foaming machine flow mapping error data is less than the foaming machine flow mapping error threshold; By using the manta ray optimization algorithm for each independent variable coefficient and bias parameter of the initial foaming machine flow regulation mapping equation, and taking the mapping accuracy rate of the initial foaming machine flow regulation mapping equation as the fitness function; Therefore, as the iteration progresses, a set of appropriate independent variable coefficients and bias parameters will be obtained, making the mapping accuracy rate of the initial foaming machine flow regulation mapping equation reach the optimal and meeting the mapping requirements; It ensures the accuracy of obtaining the corresponding foaming machine flow data based on the metering pump and several parameters that affect the foaming machine flow other than the metering pump parameters, and further ensures the accuracy of the direction of adjusting the parameters that affect the foaming machine flow of the metering pump according to the foaming machine flow data; S3. Use the calibrated metering pump to regulate the flow of the currently used foaming machine. After the regulation is completed, obtain the current foaming machine flow data; According to whether the current foaming machine flow data is within the current flow target value range of the foaming machine, input the parameters of the calibrated metering pump obtained by each adjustment into the final foaming machine flow regulation mapping equation to obtain the adjustment result until the adjustment result is within the current flow target value range of the foaming machine; The S3 includes the following steps: S31. Set the currently used foaming machine; Set the current flow target value range of the currently used foaming machine according to the actual foaming process requirements to obtain the current foaming machine flow target value range; When regulating the flow of the currently used foaming machine according to the calibrated metering pump, obtain the current foaming machine flow data; S32. When the current foaming machine flow data is within the current flow target value range of the foaming machine, perform S33; Otherwise, adjust the parameters of the calibrated metering pump in combination with the final foaming machine flow regulation mapping equation, the first foaming machine flow influence parameter type set, and the second foaming machine flow influence parameter type set until the current foaming machine flow data is within the current flow target value range of the foaming machine; S33. Collect several groups of real-time flow data of the currently used foaming machine to obtain the current foaming machine real-time flow data set; Set several future time points to obtain the future time point set; Predict the flow data of the currently used foaming machine at future time points according to the future time point set and the current foaming machine real-time flow data set to obtain the current foaming machine future flow data set; When there is flow data in the current foaming machine future flow data set that is not within the current flow target value range of the foaming machine, adjust the parameters of the calibrated metering pump in combination with the final foaming machine flow regulation mapping equation and the first foaming machine flow influence parameter type set until there is no flow data in the current foaming machine future flow data set that is not within the current flow target value range of the foaming machine; Otherwise, there is no need to adjust the parameters of the calibrated metering pump; In S33, an SVM model is used to predict the flow rate data of the currently used foam machine at future time points; The adjustment of the parameters of the calibrated metering pump in S32 and S33 includes the following steps: S321. Collect the parameters corresponding to the currently used foam machine according to the second type set of foam machine flow rate influence parameters to obtain the current non-metering pump flow rate influence parameter set; set the value range of each parameter of the calibrated metering pump in cooperation with the first type set of foam machine flow rate influence parameters to obtain the calibrated metering pump flow rate influence parameter value range set As follows, ; Among them, , respectively represent the lower limit and upper limit of the value of the i th type of parameter that affects the flow rate of the foam machine for the calibrated metering pump; Construct the adjusted manta ray population of the calibrated metering pump flow rate influence parameters; set the maximum number of iterations of the adjusted manta ray population of the calibrated metering pump flow rate influence parameters to be and the current number of iterations to be , which are respectively recorded as the maximum number of iterations of flow parameter adjustment and the current number of iterations of flow parameter adjustment; the search space dimension of the adjusted manta ray population of the calibrated metering pump flow rate influence parameters is the same as that of ; S322. Generate the initial position of each manta ray in the adjusted manta ray population of the calibrated metering pump flow rate influence parameters according to the calibrated metering pump flow rate influence parameter value range set to obtain the second initial position matrix; The generation formula is as follows, ; In the formula, respectively represent random numbers between 0 and 1 generated for d ji ; d ji represents the position component of the initial position of the j th manta ray in the adjusted manta ray population of the calibrated metering pump flow rate influence parameters on the i th type of parameter dimension that affects the flow rate of the foam machine for the calibrated metering pump S323. Construct the fitness function of the adjusted manta ray population of the calibrated metering pump flow rate influence parameters ; As follows, ; Among them, It represents the current foaming machine flow data obtained by substituting a set of parameters that affect the foaming machine flow and the current non-metering pump flow influence parameter set obtained in each iteration process into the final foaming machine flow regulation mapping equation for mapping. It represents the number of flow data in the future moment's foaming machine flow dataset that is not within the current flow target value range of the foaming machine, which is obtained by substituting a set of parameters that affect the foaming machine flow and the current non-metering pump flow influence parameter set obtained in each iteration process into the calibrated metering pump and regulating the flow of the currently used foaming machine, and then collecting and predicting the flow of the foaming machine in real time. 、 They respectively represent the lower limit value and the upper limit value of the current flow target value range of the foaming machine. 、 Both are positive numbers, representing the second correction parameter and the third correction parameter respectively, which are used to prevent the denominators of the two partial fractions of S324. Start iteration. Before iteration, set the current iteration number of the flow parameter adjustment to 1. In the first round of iteration, use the flow influence parameter of the calibrated metering pump to adjust the fitness function of the manta ray population Calculate the fitness values of the initial positions of each manta ray in the second initial position matrix to obtain the third fitness value set. Take the maximum fitness value in the third fitness value set and the corresponding initial position of the manta ray as the third global best fitness and the third global best position respectively. Update the initial positions of each manta ray in the second initial position matrix according to the third global best fitness and the third global best position. After the update is completed, increment the current iteration number of the flow parameter adjustment by 1 and enter the next round of iteration. In each subsequent round of iteration, use the flow influence parameter of the calibrated metering pump to adjust the fitness function of the manta ray population Calculate the fitness values of the positions of each manta ray in the manta ray population adjusted by the flow influence parameter of the calibrated metering pump updated in the previous round of iteration to obtain the fourth fitness value set. Take the maximum fitness value in the fourth fitness value set and the corresponding position of the manta ray as the fourth global best fitness and the fourth global best position respectively. Update the positions of each manta ray in the manta ray population adjusted by the flow influence parameter of the calibrated metering pump updated in the previous round of iteration according to the fourth global best fitness and the fourth global best position. After the update is completed, increment the current iteration number of the flow parameter adjustment by 1 and enter the next round of iteration. S325. When is satisfied, stop iteration to obtain the second final global best fitness and the second final global best position; otherwise, continue iteration until until; use the second final global best fitness as the current optimized flow data of the foaming machine; when the current optimized flow data of the foaming machine is within the current flow target value range of the foaming machine, set each position component of the second final global best position to the calibrated metering pump, and the adjustment is completed; otherwise, return to S324 to continue the iteration until the current optimized flow data of the foaming machine is within the current flow target value range of the foaming machine.

[0024] Embodiment 2 Please refer to Figure 5 , this embodiment discloses a self-adaptive regulation system for the flow rate of a foaming machine based on precise control of a metering pump. The system can implement the method of the above embodiment, including a foaming flow influence parameter type setting module, a metering pump measurement and calibration module, a foaming machine flow regulation mapping equation construction module, a current foaming machine flow regulation module, and a calibrated metering pump parameter adjustment module; The foaming flow influence parameter type setting module sets the types of parameters that affect the flow rate of the foaming machine for the metering pump and several other parameters except the metering pump, and obtains a first set of foaming machine flow influence parameter types and a second set of foaming machine flow influence parameter types; The metering pump measurement and calibration module performs calibration adjustment operations on the metering pump to be calibrated to obtain a calibrated metering pump; The foaming machine flow regulation mapping equation construction module constructs a final foaming machine flow regulation mapping equation by collecting several sets of foaming machine flow data after regulating the flow rate of the foaming machine using the calibrated metering pump in the past and the parameter data of various types of metering pumps that affect the flow rate of the foaming machine; The current foaming machine flow regulation module uses the calibrated metering pump to regulate the flow rate of the currently used foaming machine. After the regulation is completed, the current foaming machine flow data is obtained; The calibrated metering pump parameter adjustment module determines whether the current foaming machine flow data is within the current flow target value range of the foaming machine. By inputting the parameters of the calibrated metering pump obtained from each adjustment into the final foaming machine flow regulation mapping equation, the adjustment result is obtained until the adjustment result is within the current flow target value range of the foaming machine.

[0025] In the description of this specification, the descriptions referring to terms such as "one embodiment", "example", "specific example", etc. mean that the specific features, structures, materials, or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the invention. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described can be combined in a suitable manner in any one or more embodiments or examples.

[0026] The preferred embodiments of the invention disclosed above are only used to help explain the invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to the specific embodiments described. Obviously, many modifications and variations can be made according to the content of this specification. These embodiments are selected and specifically described in this specification to better explain the principle and practical application of the invention, so that those skilled in the art can well understand and utilize the invention.

Claims

1. A method for adaptively regulating the flow rate of a foaming machine based on precise control of a metering pump, characterized in that, The following steps are involved: S1, setting a metering pump and several parameter types other than the metering pump that have an impact on the flow rate of the foaming machine, and performing calibration and adjustment operations on the metering pump to be calibrated to obtain a calibrated metering pump; S2. According to the parameter type set in S1, several groups of historical foaming machine flow data after the foaming machine flow is regulated by the calibrated metering pump, as well as corresponding parameter data of various types of metering pumps that have an impact on the foaming machine flow, are collected, and the final foaming machine flow control mapping equation is constructed; S3, using the calibrated metering pump to regulate the flow of the foaming machine currently in use, and after the regulation is completed, obtaining the current flow data of the foaming machine; Determine whether the current foaming machine flow data is within the current foaming machine flow target value range. If not, input the parameters of the calibrated metering pump obtained from each adjustment into the final foaming machine flow control mapping equation to obtain the adjustment result until the adjustment result is within the current foaming machine flow target value range.

2. The flow rate self-adaptive regulation method of the foaming machine based on precise control of the metering pump according to claim 1, characterized in that: Several parameter types that need to be adjusted when maintaining the metering pump are set, a metering pump maintenance parameter type set is obtained, and a calibration adjustment operation is performed on the metering pump to be calibrated to obtain a calibrated metering pump.

3. The flow rate adaptive regulation method of the foaming machine based on precise control of the metering pump according to claim 2, characterized in that The S2 comprises the following steps: S21. Collect several groups of historical foaming machine flow data after using a calibrated metering pump to regulate the foaming machine flow, corresponding parameter data of various types of metering pumps that have an impact on the foaming machine flow, and corresponding various types of parameters that have an impact on the foaming machine flow except the metering pump parameters, obtain the historical metering pump flow influencing parameter matrix, the historical non-metering pump flow influencing parameter matrix, and the historical foaming machine flow data set after regulation, and construct the final foaming machine flow control mapping equation.

4. The flow rate adaptive regulation method of the foaming machine based on precise control of the metering pump according to claim 3, wherein, The construction of the final foaming machine flow control mapping equation in S21 includes the following steps: S221, constructing an initial foaming machine flow control mapping equation; S222, substituting each row of data in the historical metering pump flow influencing parameter matrix into the initial foaming machine flow control mapping equation for mapping, to obtain a foaming machine flow mapping data set after historical control; S223, adjusting the initial foaming machine flow control mapping equation according to the foaming machine flow control mapping data set after historical control to obtain a final foaming machine flow control mapping equation.

5. The flow rate adaptive regulation method of the foaming machine based on the precise control of the metering pump according to claim 4, wherein: In S223, the manta ray optimization algorithm is used to adjust the initial foaming machine flow control mapping equation.

6. The flow rate adaptive regulation method of the foaming machine based on precise control of the metering pump according to claim 5, characterized in that The S3 comprises the following steps: S31, setting the foaming machine currently in use and the corresponding flow target value interval to obtain the current flow target value interval of the foaming machine; after the flow of the foaming machine currently in use is regulated by the calibrated metering pump, the current flow data of the foaming machine is obtained; S32, when the current foaming machine flow rate data is within the current foaming machine flow rate target value interval, proceed to S33; otherwise, adjust the parameters of the calibrated metering pump in conjunction with the final foaming machine flow rate control mapping; S33. Collect several groups of real-time flow data of the currently used foaming machine and predict the flow data of the currently used foaming machine at future time points to obtain the future flow data set of the current foaming machine; when there is flow data in the future flow data set of the current foaming machine that is not within the current flow target value range of the foaming machine, adjust the parameters of the calibrated metering pump in cooperation with the final foaming machine flow regulation mapping equation.

7. The flow rate adaptive regulation method of the foaming machine based on precise control of the metering pump according to claim 6, characterized in that: In S33, an SVM model is used to predict the flow data of the currently used foaming machine at future time points.

8. The flow rate self-adaptive regulation method of the foaming machine based on precise control of the metering pump according to claim 7, characterized in that, The adjustment of the parameters of the calibrated metering pump in S32 and S33 includes the following steps: S321. Set the value range of each parameter of the calibrated metering pump and randomly set the initial positions of each manta ray in the manta ray population for adjusting the flow influence parameters of the calibrated metering pump to obtain the second initial position matrix. S322. Construct the fitness function of the manta ray population for adjusting the flow influence parameters of the calibrated metering pump. S323. Iteratively update the second initial position matrix in cooperation with the fitness function of the manta ray population for adjusting the flow influence parameters of the calibrated metering pump. S324. When the maximum number of iterations is reached, stop the iteration to obtain the second final global best fitness and the second final global best position; when the second final global best fitness is within the current flow target value range of the foaming machine, set each position component of the second final global best position to the calibrated metering pump, and the adjustment is completed.

9. A system for implementing the method for self-adaptive regulation of the flow rate of a foaming machine based on precise control of a metering pump according to any one of claims 1-8.

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