Batch production process of hydrogel oxygen-releasing materials for water ecological restoration

Abstract

The present invention discloses a batch production process for hydrogel oxygen-releasing materials for water ecological restoration, belonging to the technical field of water ecological restoration. The present invention solves the problem that existing processes cannot adjust the oxygen-releasing performance of materials in real time according to changes in the water environment. The neural network model is trained through water environment parameters and hydrogel material formula parameters in historical production, so that the neural network model can predict the oxygen-releasing performance index of the hydrogel based on the water environment parameters and the current provisional hydrogel material formula parameters during the real-time production process; and the correlation coefficient between the water environment parameters and the predicted oxygen-releasing performance index is calculated in combination with the correlation analysis method, thereby judging the adaptability of the current provisional hydrogel formula parameters to the water environment parameters; and the hydrogel formula parameters are dynamically adjusted based on the judgment results, thereby optimizing the production process of the hydrogel oxygen-releasing material.

Description

Technical Field

[0001] The present invention relates to the technical field of water body ecological restoration, in particular to a batch production process of a water body ecological restoration hydrogel oxygen-releasing material. Background Art

[0002] Hydrogel oxygen-releasing materials for water ecological restoration are used for water pollution control and ecological restoration. They slowly release oxygen and absorb pollutants. They are primarily composed of a uniform combination of polyvinyl alcohol (PVA) and oxygen-releasing functional materials such as calcium peroxide, urea peroxide, sodium perborate, and sodium percarbonate, along with pollutant-absorbing materials such as granular activated carbon, zeolite, silica gel, and alumina. With the rapid development of industrialization and urbanization, water pollution is becoming increasingly serious, and water ecological restoration has become an urgent environmental issue. As a new type of water restoration material, hydrogel oxygen-releasing materials can slowly release oxygen, improve dissolved oxygen levels in water, and promote the recovery of aquatic ecosystems.

[0003] However, in traditional production processes, there is a lack of dynamic optimization capabilities for material properties, and it is impossible to adjust the oxygen release performance of the material in real time according to changes in the water environment.

[0004] Therefore, it does not meet the existing needs, so we proposed a batch production process of hydrogel oxygen-releasing materials for water ecological restoration. Summary of the Invention

[0005] The purpose of the present invention is to provide a batch production process of hydrogel oxygen-releasing materials for water body ecological restoration. The neural network model is trained by water environment parameters and hydrogel material formula parameters in historical production, so that the neural network model can predict the oxygen release performance index of the hydrogel based on the water environment parameters and the current tentative hydrogel material formula parameters during the real-time production process; and the correlation coefficient between the water environment parameters and the predicted oxygen release performance index is calculated in combination with the correlation analysis method, thereby judging the adaptability of the current tentative hydrogel formula parameters to the water environment parameters; and the formula parameters of the hydrogel are dynamically adjusted based on the judgment results, thereby optimizing the production process of the hydrogel oxygen-releasing material, solving the problems raised in the above-mentioned background technology.

[0006] To achieve the above object, the present invention provides the following technical solutions:

[0007] A batch production process for hydrogel oxygen-releasing materials for water ecological restoration, the production process being based on the influence of water environment parameters and hydrogel material formulation parameters on the oxygen-releasing performance index of the hydrogel, wherein the oxygen-releasing performance index of the hydrogel is constructed by a neural network model; the production process comprising:

[0008] The water environment parameters and hydrogel formulation parameters in historical production were processed based on Min-Max normalization and Z-score standardization;

[0009] Water environment parameters and hydrogel formulation parameters are predicted based on a neural network model, and the output is the oxygen release performance index of the hydrogel;

[0010] The correlation coefficient between the water environment parameters and the predicted oxygen release performance index is calculated based on the correlation analysis method to determine the compatibility of the hydrogel formula parameters with the water environment parameters; and based on the calculation results, the formula parameters of the hydrogel oxygen-releasing material are dynamically adjusted;

[0011] Based on the K-means clustering method, the water environment parameters in historical production and the adjusted hydrogel formula parameters were clustered and analyzed to obtain the clustering results of the water environment parameters and the corresponding hydrogel formula parameters, which were used as reference samples for real-time production processes.

[0012] Furthermore, it also includes:

[0013] Compare the current water environment parameters with the historical water environment parameters in each cluster in the clustering results to find the most similar cluster; obtain the corresponding hydrogel formula parameters from the most similar cluster;

[0014] Based on the neural network model, the current water environment parameters and hydrogel formula parameters are predicted, and the oxygen release performance index of the current hydrogel is output;

[0015] Based on the correlation analysis method, the compatibility of the currently obtained hydrogel formula parameters and the water environment parameters is judged;

[0016] If it is not suitable, the hydrogel formulation parameters are dynamically adjusted based on the calculation results;

[0017] If suitable, the hydrogel oxygen-releasing material is prepared based on the current hydrogel formula parameters in combination with the freeze-thaw-crosslinking method, and the granular material is made through granulation and drying processes.

[0018] Furthermore, the water environment parameters and hydrogel formulation parameters in historical production are processed based on Min-Max normalization, which specifically includes the following steps:

[0019] Collect water environment parameters and hydrogel formula parameters from historical production, including dissolved oxygen concentration, water temperature, pollutant concentration, pH value, water transparency and water flow rate, as well as polyvinyl alcohol concentration, cross-linking agent type and dosage, and oxygen release agent dosage;

[0020] Collect oxygen release performance indicators of hydrogel oxygen-releasing materials with different formulations in historical production, including: oxygen release rate, oxygen release duration, mechanical strength, particle size distribution, and environmental stability;

[0021] Obtain a data set of water environment parameters and oxygen release performance indicators in historical data, and obtain the maximum value and minimum value of the data in the data set;

[0022] Based on the maximum and minimum values ​​of the data, the data set is scaled to the interval [0, 1], and the calculation formula is as follows:

[0023]

[0024] Among them, T norm is represented as a normalized data set; T is represented as a data set; T max Expressed as the maximum value of the data; T min Represents the minimum value of the data.

[0025] Furthermore, the water environment parameters and hydrogel formulation parameters in historical production were processed based on Z-score standardization, which specifically includes the following steps:

[0026] Get the normalized data set, combine it with the standard deviation, and standardize the current data set to convert the data into a distribution with a mean of 0 and a standard deviation of 1. The calculation formula is as follows:

[0027]

[0028] Among them, T norm It represents the normalized data set; T represents the data set; μ represents the mean of the data; σ represents the standard deviation.

[0029] Furthermore, the water environment parameters and hydrogel formulation parameters are predicted based on the neural network model, which specifically includes the following steps:

[0030] The treated water environment parameters and hydrogel formulation parameters are used as historical data and divided into training set, validation set and test set;

[0031] Determine the model structure, initialize the model weights and bias parameters, select a suitable activation function, introduce nonlinear characteristics, and select the mean square error as the model loss function based on the oxygen release performance index;

[0032] The training set is used as the model input for model training. During the training process, the gradient of the loss function is calculated through the back-propagation algorithm.

[0033] Use the validation set to evaluate model performance and adjust hyperparameters to optimize model performance;

[0034] Use the test set to validate and evaluate the model, and use the mean square error to measure the difference between the predicted value and the true value;

[0035] The trained neural network model is applied to the production process of hydrogel oxygen-releasing materials.

[0036] Furthermore, the correlation coefficient between the water environment parameters and the predicted oxygen release performance index is calculated based on the correlation analysis method, which specifically includes the following steps:

[0037] Obtain water body environmental parameters and output oxygen release performance indicators, sort the water body environmental parameters and oxygen release performance indicators from small to large, and calculate the corresponding grade difference of each data point; based on the grade difference of each data point, calculate the square of the grade difference of each data point; if there are identical values, take the average grade.

[0038] Furthermore, based on the square of the calculated grade difference, the correlation coefficient between the water environment parameters and the predicted oxygen release performance index is calculated to determine the compatibility of the hydrogel formula parameters with the water environment parameters, which specifically includes the following steps:

[0039] The correlation coefficient between the water environment parameters and the predicted oxygen release performance index was calculated based on the Spearman rank correlation coefficient. The calculation formula is as follows:

[0040]

[0041] Where ρ represents the strength and direction of the correlation between water environment parameters and oxygen release performance indicators; n Expressed as the sum of water body environmental parameters and predicted oxygen release performance indicators; Expressed as the sum of squared rank differences; 6 and n 2 -1 represents a constant factor in the derivation process;

[0042] If the correlation coefficient ρ is close to 1 or -1, it means that there is a significant monotonic relationship between the hydrogel formulation parameters and the water environment parameters, and the adaptability is good;

[0043] If the correlation coefficient ρ is close to 0, it means that there is no obvious correlation between the hydrogel formulation parameters and the water environment parameters, and the hydrogel formulation parameters need to be adjusted.

[0044] Furthermore, based on the calculation results, the formulation parameters of the hydrogel are dynamically adjusted, specifically including the following steps:

[0045] The correlation between water environment parameters and oxygen release performance indicators was evaluated based on the calculated Spearman rank correlation coefficient;

[0046] Analyze the effects of hydrogel formulation parameters on oxygen release performance and identify the formulation parameters with the most significant impact;

[0047] Dynamically adjust hydrogel formulation parameters based on correlation analysis results and formulation parameter impact analysis;

[0048] The adjusted hydrogel formula parameters are experimentally verified to test whether the oxygen release performance indicators meet the expected targets; if the expected targets are not met, the formula parameters are further adjusted until the requirements are met.

[0049] Furthermore, based on the water environment parameters in current production, the hydrogel formula parameters corresponding to similar historical water environment parameters are obtained, which specifically includes the following steps:

[0050] Compare the current water environment parameters with the cluster centers in the clustering results to find the most similar cluster;

[0051] From the most similar cluster, the corresponding hydrogel formulation parameters are obtained;

[0052] Based on the obtained formula parameters, the formula parameters of the hydrogel currently in production are determined, and the production process is implemented.

[0053] Furthermore, the effects of hydrogel formulation parameters on oxygen release performance were analyzed, and the formulation parameters with significant impact were identified, including:

[0054] Extract hydrogel formulation parameters;

[0055] Determining oxygen release performance metrics, wherein the metrics include oxygen release rate, duration, and total oxygen release;

[0056] Setting the parameter value of each formula substance in the hydrogel formula parameters to form three sets of values ​​corresponding to each formula substance, wherein the three sets of values ​​include the original parameter value of each formula substance in the hydrogel formula parameters and two experimental values ​​set based on the original parameter value;

[0057] Normalizing the three sets of values ​​corresponding to each formula substance to generate standardized data values ​​corresponding to the formula substance;

[0058] Taking each formula substance as a variable, and keeping the original parameter values ​​of other formula substances unchanged, the oxygen release performance test is carried out on the three sets of values ​​of each formula substance to obtain the oxygen release rate, duration and total oxygen release amount corresponding to the three sets of values ​​of each formula substance;

[0059] The differences in the measurement indicators of the three groups of values ​​for each formula substance are obtained based on the experimental results;

[0060] The influence coefficient of each formula substance on oxygen release performance is obtained by using the difference in the measurement indicators of the three groups of values ​​of each formula substance;

[0061] The influence coefficient of each formula substance on oxygen release performance is obtained by the following formula:

[0062]

[0063] Where W represents the influence coefficient of each formula substance on oxygen release performance; n represents the number of measurement indicators corresponding to oxygen release performance; X mini and X maxi represents the minimum and maximum values ​​of the i-th measurement index during the oxygen release performance experiment of the three sets of values ​​of each formula substance; w represents the preset adjustment coefficient, and its value range is 0.3-0.6; X yi Indicates the value of the measurement index corresponding to the original parameter value of each formula substance; Y b represents the standard deviation of the three sets of values ​​corresponding to each formula substance; Y represents the original parameter value of each formula substance; y represents the weight value corresponding to each formula substance;

[0064] Comparing the influence coefficient with a preset first coefficient threshold and a second coefficient threshold;

[0065] When the influence coefficient exceeds a preset first coefficient threshold, the formula substance whose influence coefficient exceeds the preset first coefficient threshold is determined to be a priority adjustment substance;

[0066] When the influence coefficient does not exceed the preset first coefficient threshold but exceeds the preset second coefficient threshold, the formula substance whose influence coefficient does not exceed the preset first coefficient threshold but exceeds the preset second coefficient threshold is determined to be a secondary adjustment substance;

[0067] When the influence coefficient does not exceed the preset second coefficient threshold, it is determined that the formula substance is a substance that does not require adjustment.

[0068] Furthermore, the process of setting the two experimental values ​​corresponding to each formula substance includes:

[0069] Extract the correlation coefficients between water environment parameters and predicted oxygen release performance indicators;

[0070] Extracting the original parameter value of each formula substance in the hydrogel formula parameters;

[0071] Determine the difference between the correlation coefficient and values ​​close to 1 or -1;

[0072] Obtaining a parameter adjustment coefficient using a difference between the correlation coefficient and a value close to 1 or -1;

[0073] The parameter adjustment coefficient is obtained by the following formula:

[0074]

[0075] Where S represents the parameter adjustment coefficient; G represents the difference between the correlation coefficient and close to 1 or -1;

[0076] Using the parameter adjustment coefficient, two experimental values ​​corresponding to each formula substance are set;

[0077] The two experimental values ​​corresponding to each formula substance are obtained by the following formula:

[0078]

[0079] Among them, Y 01 and Y 02 Represent the two experimental values ​​corresponding to each formula substance; Y represents the original parameter value of each formula substance; S represents the parameter adjustment coefficient.

[0080] Compared with the prior art, the present invention has the following beneficial effects:

[0081] In the present invention, the neural network model is trained by using the water environment parameters and hydrogel material formula parameters in historical production, so that it can more accurately predict the oxygen release performance index of the hydrogel during the real-time production process, thereby providing a scientific basis for the production process; and the correlation coefficient between the water environment parameters and the predicted oxygen release performance index is calculated in combination with the correlation analysis method, thereby judging the adaptability of the current tentative hydrogel formula parameters to the water environment parameters; and the hydrogel formula parameters are dynamically adjusted based on the judgment results, thereby improving the performance and adaptability of the hydrogel; enabling it to quickly respond to changes in the water environment and improve the flexibility and adaptability of production; at the same time, under the premise of ensuring the stable quality of the hydrogel oxygen-releasing material, the formula and production process are optimized, the waste of raw materials is reduced, the production cost is reduced, and the needs of different water environments are met. BRIEF DESCRIPTION OF THE DRAWINGS

[0082] Figure 1 This is a flow chart of the batch production process of the water body ecological restoration hydrogel oxygen-releasing material of the present invention. DETAILED DESCRIPTION

[0083] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0084] In order to solve the technical problem of the traditional production process lacking the ability to dynamically optimize material properties and unable to adjust the material's oxygen release performance in real time according to changes in the water environment, please refer to Figure 1 , this embodiment provides the following technical solutions:

[0085] The batch production process of hydrogel oxygen-releasing materials for water ecological restoration is based on the influence of water environment parameters and hydrogel material formula parameters on the oxygen-releasing performance index of the hydrogel. The oxygen-releasing performance index of the hydrogel is constructed by a neural network model. The production process includes:

[0086] The water environment parameters and hydrogel formulation parameters in historical production are processed based on Min-Max normalization and Z-score standardization; specifically, the following steps are included:

[0087] The water environment parameters and hydrogel formula parameters in historical production were collected, including dissolved oxygen concentration, water temperature, pollutant concentration, pH value, water transparency and water flow rate, as well as polyvinyl alcohol concentration, cross-linking agent type and dosage, oxygen release agent dosage; pollutant concentrations such as chemical oxygen demand COD, ammonia nitrogen, total phosphorus TP, etc.; oxygen release performance indicators of hydrogel oxygen-releasing materials with different formulas in historical production were collected, including oxygen release rate, oxygen release duration, mechanical strength, particle size distribution and environmental stability; mechanical strength such as compressive strength and tensile strength, environmental stability such as performance changes under different temperature and pH conditions; and the collected water environment parameters and hydrogel formula parameters were cleaned to eliminate abnormal values ​​and ensure data accuracy.

[0088] Since the dimensions and numerical ranges of different parameters vary greatly, in order to improve the training efficiency and stability of the model, the data needs to be normalized. Specifically, the data set of water environment parameters and oxygen release performance indicators in the historical data is obtained, and the maximum and minimum values ​​of the data set are obtained;

[0089] Based on the maximum and minimum values ​​of the data, the data set is scaled to the interval [0, 1], and the calculation formula is as follows:

[0090]

[0091] Among them, T norm is represented as a normalized data set; T is represented as a data set; T max Expressed as the maximum value of the data; T min Represents the minimum value of the data.

[0092] In one embodiment, assume a set of water environment parameter data, including measured values ​​of water temperature T and dissolved oxygen DO, as follows:

[0093] Table 1: Water environment parameter data table

[0094]

[0095] Among them, the maximum value of water temperature (T) is 30°C and the minimum value is 15°C; the maximum value of dissolved oxygen (DO) is 9mg / L and the minimum value is 5mg / L;

[0096] Based on the above normalization formula, we can get:

[0097] Table 2: Water environment parameter data after normalization

[0098]

[0099] Secondly, obtain the normalized data set, combine it with the standard deviation, and standardize the current data set to convert the data into a distribution with a mean of 0 and a standard deviation of 1. The calculation formula is as follows:

[0100]

[0101] Among them, T norm Represents the normalized data set; T represents the data set; μ represents the mean of the data; σ represents the standard deviation;

[0102] Based on the above calculation formula, the data in Table 2 are calculated to obtain the water environment parameter data after standardization. This converts the original data into normalized and standardized data for use in the neural network model, which helps to improve the training efficiency and prediction accuracy of the model.

[0103] The water environment parameters and hydrogel formulation parameters are predicted based on the neural network model, and the output is the oxygen release performance index of the hydrogel. The specific steps include:

[0104] The treated water environment parameters and hydrogel formulation parameters are used as historical data and divided into training, validation, and test sets, with the proportions usually being 70%, 15%, and 15%; the training set is used for model training, the validation set is used for hyperparameter adjustment, and the test set is used to evaluate the final performance of the model;

[0105] Determine the model structure, specifically: Input layer: The model input consists of two parts: water environment parameters and hydrogel material formula parameters. Hidden layer: A recurrent neural network structure is used to capture long-term dependencies in time series data. Output layer: The output of the model is the oxygen release performance index of the hydrogel, such as oxygen release rate and duration. Initialize the model weights and bias parameters, such as initializing the bias parameters to zero; select an appropriate activation function and introduce nonlinear characteristics. Based on the oxygen release performance index, select the mean square error as the model loss function; and calculate the gradient by randomly selecting a portion of the data to update the model parameters.

[0106] The training set is used as model input for model training. During the training process, the gradient of the loss function is calculated through the backpropagation algorithm, and the model parameters are updated. The validation set is used to evaluate model performance, and hyperparameters are adjusted to optimize model performance. The test set is used to verify and evaluate the model, and the mean square error is used to measure the difference between the predicted value and the true value. The trained neural network model is applied to the production process of hydrogel oxygen-releasing materials. Based on real-time water environment parameters and material formulation parameters, the model is used to predict the oxygen release performance indicators of the hydrogel, and the material formulation and production process parameters are dynamically adjusted to optimize material performance. At the same time, the hydrogel performance data collected during actual production is fed back to the model to further optimize the model parameters and structure. Through continuous feedback and optimization, the model can better adapt to changes in the water environment and improve the performance and production efficiency of hydrogel oxygen-releasing materials.

[0107] The beneficial effects achieved by the above content are: the dynamic adjustment strategy based on neural network reduces the trial and error cost, improves the stability and efficiency of the production process, and reduces production time.

[0108] The correlation coefficient between the water environment parameters and the predicted oxygen release performance index is calculated based on the correlation analysis method to determine the compatibility of the hydrogel formula parameters with the water environment parameters; and based on the calculation results, the formula parameters of the hydrogel oxygen-releasing material are dynamically adjusted. Specifically, the following steps are included:

[0109] The water environment parameters and the output oxygen release performance index are obtained, and the water environment parameters and the oxygen release performance index are sorted from small to large, and the corresponding grade difference of each data point is calculated; based on the grade difference of each data point, the square of the grade difference of each data point is calculated; if there are identical values, the average grade is taken; based on the square of the calculated grade difference, the correlation coefficient between the water environment parameters and the predicted oxygen release performance index is calculated to judge the compatibility of the hydrogel formula parameters with the water environment parameters, which specifically includes the following steps:

[0110] The correlation coefficient between the water environment parameters and the predicted oxygen release performance index was calculated based on the Spearman rank correlation coefficient. The calculation formula is as follows:

[0111]

[0112] Where ρ represents the strength and direction of the correlation between water environment parameters and oxygen release performance indicators; n Expressed as the sum of water body environmental parameters and predicted oxygen release performance indicators; Expressed as the sum of squared rank differences; 6 and n 2 -1 represents a constant factor in the derivation process;

[0113] If the correlation coefficient ρ is close to 1 or -1, it means that there is a significant monotonic relationship between the hydrogel formulation parameters and the water environment parameters, and the adaptability is good;

[0114] If the correlation coefficient ρ is close to 0, it means that there is no obvious correlation between the hydrogel formulation parameters and the water environment parameters, and the hydrogel formulation parameters need to be adjusted.

[0115] Based on the calculated Spearman rank correlation coefficient, the correlation between water environment parameters and oxygen release performance indicators was evaluated; the influence of hydrogel formula parameters on oxygen release performance was analyzed, and the formula parameters with significant impact were identified; based on the correlation analysis results and formula parameter impact analysis, the hydrogel formula parameters were dynamically adjusted; the adjusted hydrogel formula parameters were experimentally verified to test whether the oxygen release performance indicators met the expected targets; if the expected targets were not met, the formula parameters were further adjusted until the requirements were met.

[0116] In one embodiment, assume that there is sample data of the following water environment parameter X and oxygen release performance index Y. X and Y are sorted from small to large, and each data point is assigned a corresponding rank. The data is as follows:

[0117] Table 3: Data point level table

[0118]

[0119] Calculate the rank difference of each pair of data, , and calculate its square d i 2 ; According to the Spearman rank correlation coefficient formula, we can get:

[0120]

[0121] X i Indicates the i Water body environmental parameters X, Y i Indicates the i A water body environmental parameter Y.

[0122] Based on the interpretation range of the above correlation coefficient, it can be seen that: in this embodiment, ρ=-1, which means that there is a completely negative correlation between the water environment parameters and the oxygen release performance index, which means that there is a significant monotonic relationship between the hydrogel formula parameters and the water environment parameters, and the adaptability is good, and there is no need to adjust the hydrogel formula parameters.

[0123] Beneficial effects of the above content: Through the above process, the compatibility between the hydrogel formula parameters and the water environment parameters can be scientifically determined, thereby improving the reliability of the produced hydrogel oxygen-releasing material.

[0124] Based on the K-means clustering method, the water environment parameters in historical production and the adjusted hydrogel formula parameters are clustered and analyzed to obtain the clustering results of the water environment parameters and the corresponding hydrogel formula parameters, which are used as reference samples for the real-time production process. Specifically, through cluster analysis, historical data similar to the current water environment parameters can be quickly identified in real-time production, thereby providing optimized formula parameters for real-time production, reducing trial and error time, and improving production efficiency. Secondly, the hydrogel formula parameters that perform best in a specific water environment can be identified, thereby guiding the adjustment of the formula in real-time production to obtain better oxygen release performance.

[0125] The current water environment parameters are compared with the historical water environment parameters in each cluster in the clustering results to find the most similar cluster; the corresponding hydrogel formula parameters are obtained from the most similar cluster; the current water environment parameters and the hydrogel formula parameters are predicted based on the neural network model, and the oxygen release performance index of the current hydrogel is output; the compatibility of the currently obtained hydrogel formula parameters and the water environment parameters is judged based on the correlation analysis method; if they are not compatible, the hydrogel formula parameters are dynamically adjusted based on the calculation results; if they are compatible, the hydrogel oxygen-releasing material is prepared based on the current hydrogel formula parameters in combination with the freeze-thaw-crosslinking method, and the granular material is prepared through granulation and drying processes, which specifically includes the following steps:

[0126] Prepare hydrogel raw materials, including: polyvinyl alcohol as a hydrogel substrate, which has good gelation and biocompatibility; oxygen-releasing functional materials for providing oxygen, such as calcium peroxide and urea peroxide, and additives; add polyvinyl alcohol to deionized water, heat until completely dissolved, and form a uniform polyvinyl alcohol aqueous solution; after evenly mixing the oxygen-releasing functional material and the additive, add them to the polyvinyl alcohol aqueous solution, stir until completely dispersed, and form a paste-like mixed aqueous dispersion; pour the mixed aqueous dispersion into a mold and perform a freeze-thaw-crosslinking treatment; specifically: freeze the dispersion to -25°C and keep it for 30 minutes; then thaw it to 35°C and keep it for 30 minutes. The freeze-thaw cycle is repeated five times; after freeze-thaw-crosslinking treatment, the mixed aqueous dispersion is transformed into a plastic hydrogel; the hydrogel is removed from the mold and granulated using an extrusion granulation process; the hydrogel is made into a rod-shaped continuous material using a granulator, and then evenly cut into granules using a rotating tool; the granulated hydrogel particles are dried to further solidify the structure and appearance, thereby obtaining solid hydrogel oxygen-releasing material particles that are easy to store and use.

[0127] The beneficial effects achieved by the above-mentioned process include: This process enables rapid response to changes in the aquatic environment, improving production flexibility and adaptability; while also ensuring the stable quality of the hydrogel oxygen-releasing material, optimizing the formulation and production process, reducing raw material waste, lowering production costs, and meeting the needs of diverse aquatic environments. The cement glue formed based on this production process slowly releases oxygen in water, helping to improve dissolved oxygen levels; it also absorbs pollutants in the water, reducing water pollution; and exhibits excellent biocompatibility and is environmentally friendly, thereby promoting the recovery and health of aquatic ecosystems.

[0128] Working principle: The neural network model is trained through the water environment parameters and hydrogel material formula parameters in historical production, so that it can more accurately predict the oxygen release performance index of the hydrogel based on the water environment parameters and the current tentative hydrogel material formula parameters during the real-time production process, thereby providing a scientific basis for the production process; and combined with the correlation analysis method to calculate the correlation coefficient between the water environment parameters and the predicted oxygen release performance index, thereby judging the adaptability of the current tentative hydrogel formula parameters to the water environment parameters; and dynamically adjust the hydrogel formula parameters based on the judgment results, thereby improving the performance and adaptability of the hydrogel.

[0129] Specifically, the effects of hydrogel formulation parameters on oxygen release performance were analyzed, and the formulation parameters with significant impact were identified, including:

[0130] Extract hydrogel formulation parameters;

[0131] Determining oxygen release performance metrics, wherein the metrics include oxygen release rate, duration, and total oxygen release;

[0132] Setting the parameter value of each formula substance in the hydrogel formula parameters to form three sets of values ​​corresponding to each formula substance, wherein the three sets of values ​​include the original parameter value of each formula substance in the hydrogel formula parameters and two experimental values ​​set based on the original parameter value;

[0133] Normalizing the three sets of values ​​corresponding to each formula substance to generate standardized data values ​​corresponding to the formula substance;

[0134] Taking each formula substance as a variable, and keeping the original parameter values ​​of other formula substances unchanged, the oxygen release performance test is carried out on the three sets of values ​​of each formula substance to obtain the oxygen release rate, duration and total oxygen release amount corresponding to the three sets of values ​​of each formula substance;

[0135] The differences in the measurement indicators of the three groups of values ​​for each formula substance are obtained based on the experimental results;

[0136] The influence coefficient of each formula substance on oxygen release performance is obtained by using the difference in the measurement indicators of the three groups of values ​​of each formula substance;

[0137] The influence coefficient of each formula substance on oxygen release performance is obtained by the following formula:

[0138]

[0139] Where W represents the influence coefficient of each formula substance on oxygen release performance; n represents the number of measurement indicators corresponding to oxygen release performance; X mini and X maxi represents the minimum and maximum values ​​of the i-th measurement index during the oxygen release performance experiment of the three sets of values ​​of each formula substance; w represents the preset adjustment coefficient, and its value range is 0.3-0.6; X yi Indicates the value of the measurement index corresponding to the original parameter value of each formula substance; Y b represents the standard deviation of the three sets of values ​​corresponding to each formula substance; Y represents the original parameter value of each formula substance; y represents the weight value corresponding to each formula substance;

[0140] Comparing the influence coefficient with a preset first coefficient threshold and a second coefficient threshold;

[0141] When the influence coefficient exceeds a preset first coefficient threshold, the formula substance whose influence coefficient exceeds the preset first coefficient threshold is determined to be a priority adjustment substance;

[0142] When the influence coefficient does not exceed the preset first coefficient threshold but exceeds the preset second coefficient threshold, the formula substance whose influence coefficient does not exceed the preset first coefficient threshold but exceeds the preset second coefficient threshold is determined to be a secondary adjustment substance;

[0143] When the influence coefficient does not exceed the preset second coefficient threshold, it is determined that the formula substance is a substance that does not require adjustment.

[0144] The technical effect of the above technical solution is as follows: by systematically extracting the hydrogel formula parameters and setting and experimenting with each parameter, it is possible to accurately identify the formula parameters that significantly affect the oxygen release performance, providing a clear direction for optimizing the oxygen release performance of the hydrogel. Based on the comparison of the influence coefficient with the preset threshold, the formula substances are divided into priority adjustment substances, secondary adjustment substances, and substances that do not require adjustment. This facilitates targeted adjustment of the formula in actual production or research, improves efficiency, and reduces costs. The above formula is used to calculate the influence coefficient of each formula substance on oxygen release performance, comprehensively considering multiple factors, making the measurement of the influence of the formula substances more scientific and comprehensive.

[0145] This calculation reflects the relative relationship between the extreme values ​​of each formula's metrics and the values ​​at the original parameter values ​​under different experimental values. w, a preset adjustment factor (ranging from 0.3 to 0.6), adjusts the weight of the maximum value in the calculation, reflecting the varying degree of emphasis on extreme values.

[0146] This calculation comprehensively considers the fluctuations in the values ​​of the formulation ingredients and their respective weights to reflect the sensitivity of each formulation parameter to the metric. By adding the two components, weighted at 0.6 and 0.4, the formula comprehensively calculates the influence coefficient of each formulation ingredient on oxygen release performance, taking into account the extreme values ​​of the metric, the fluctuations in the values, and the weight of the formulation ingredients themselves.

[0147] Furthermore, this technical solution systematically analyzes the impact of hydrogel formulation parameters on oxygen release performance (oxygen release rate, duration, and total oxygen release) through detailed experimental procedures. This systematic analysis helps fully understand the role of each formulation parameter in the oxygen release process, providing a foundation for subsequent optimization and improvement. By normalizing experimental data and calculating the influence coefficient of each formulation component on oxygen release performance using a specific formula, this technical solution accurately quantifies the impact of each formulation parameter on oxygen release performance. This precise quantification helps identify formulation parameters with significant impact, providing a direct basis for subsequent optimization. By comparing the influence coefficient with pre-set first and second coefficient thresholds, this technical solution effectively identifies formulation components with significant impact (priority adjustment), formulation components with less significant impact (secondary adjustment), and formulation components with minimal impact (no need for adjustment). This classification helps optimize resource allocation, prioritizing the formulation parameters with the greatest impact. By setting three sets of values ​​for each formulation component (including the original parameter value and two experimental values) and conducting oxygen release performance experiments, this technical solution provides a more comprehensive assessment of the impact of each formulation parameter on oxygen release performance. Furthermore, normalization and influence coefficient calculation improve the accuracy and comparability of experimental results, helping to more accurately identify key formulation parameters. Based on these analysis results, technicians can more specifically adjust and optimize the hydrogel formulation to improve its oxygen release performance. This guided optimization approach helps develop hydrogel products with better performance to meet specific application requirements.

[0148] Specifically, the process of setting the two experimental values ​​corresponding to each formula substance includes:

[0149] Extract the correlation coefficients between water environment parameters and predicted oxygen release performance indicators;

[0150] Extracting the original parameter value of each formula substance in the hydrogel formula parameters;

[0151] Determine the difference between the correlation coefficient and values ​​close to 1 or -1;

[0152] Obtaining a parameter adjustment coefficient using a difference between the correlation coefficient and a value close to 1 or -1;

[0153] The parameter adjustment coefficient is obtained by the following formula:

[0154]

[0155] Where S represents the parameter adjustment coefficient; G represents the difference between the correlation coefficient and close to 1 or -1;

[0156] Using the parameter adjustment coefficient, two experimental values ​​corresponding to each formula substance are set;

[0157] The two experimental values ​​corresponding to each formula substance are obtained by the following formula:

[0158]

[0159] Among them, Y 01 and Y 02 Represent the two experimental values ​​corresponding to each formula substance; Y represents the original parameter value of each formula substance; S represents the parameter adjustment coefficient.

[0160] The technical effect of the above technical solution is: by extracting the correlation coefficient between the water environment parameters and the predicted oxygen release performance index, and calculating the parameter adjustment coefficient based on this to set the experimental value of each formula substance, the setting of the experimental value is made more scientific and targeted, and the influence of the formula substance on the oxygen release performance can be explored more accurately. This solution takes into account the correlation between the water environment parameters and the oxygen release performance index, and incorporates environmental factors into the process of setting the experimental value of the formula substance, which helps to better optimize the oxygen release performance of the hydrogel in the actual water environment and improve the effect of the hydrogel in practical applications. The parameter adjustment coefficient is calculated using the difference between the correlation coefficient and a value close to 1 or -1, which provides a quantitative basis for the adjustment of the experimental value, avoids the blindness of the experimental value setting, and facilitates the standardization and repeatability of the experiment.

[0161] The value of G is mapped to a parameter adjustment coefficient S within a certain range (determined by the value range of G). This allows the appropriate adjustment coefficient to be determined based on the strength of the correlation. When the correlation is stronger (the smaller G is), the value of S will also change accordingly within the appropriate range, which can be used to adjust the experimental values ​​later.

[0162] Furthermore, by extracting correlation coefficients between water environmental parameters and predicted oxygen release performance indicators, this technical solution provides a scientific basis for experimental design. Correlation coefficients reflect the relationship between water environmental parameters and oxygen release performance, guiding the appropriate setting of experimental values. The difference between the correlation coefficient and values ​​close to 1 or -1 is used to determine the parameter adjustment factor. This factor is then used to set two experimental values ​​for each formulation, improving the accuracy of experimental value settings. The parameter adjustment factor quantifies the difference between the correlation coefficient and the ideal value (1 or -1), guiding the appropriate adjustment of experimental values ​​based on the original parameter values. By precisely setting experimental values, this technical solution enables a more comprehensive assessment of the impact of each formulation component on oxygen release performance within a limited number of experiments. This helps reduce unnecessary experiments and improves experimental efficiency. Because the experimental value setting is based on scientific methods and precise calculations, the experimental results are more reliable. This helps more accurately assess the impact of each formulation component on oxygen release performance, providing strong support for subsequent optimization efforts. Based on the experimental results, technicians can more specifically adjust and optimize the hydrogel formulation. By comparing the changes in oxygen release performance under different experimental values, the formula substances that have a significant impact on the oxygen release performance can be identified, thereby guiding the formulation optimization work and improving the oxygen release performance of the hydrogel.

[0163] It should be noted that, in this document, relational terms such as first and second, etc., are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "including," "having," or any other variations thereof are intended to cover non-exclusive possessors, such that a process, method, article, or apparatus that includes a list of elements includes not only those elements but also other elements not explicitly listed, or includes elements that are inherent to such process, method, article, or apparatus.

[0164] While embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that changes, modifications, substitutions, and alterations may be made to the embodiments without departing from the principles and spirit of the invention, and that the scope of the invention is defined by the appended claims and their equivalents.

Claims

1. A batch production process of hydrogel oxygen-releasing materials for water body ecological restoration, characterized in that: The production process is based on the influence of water environment parameters and hydrogel formula parameters on the oxygen release performance index of the hydrogel, and the oxygen release performance index of the hydrogel is constructed by a neural network model; the production process includes: The water environment parameters and hydrogel formulation parameters in historical production were processed based on Min-Max normalization and Z-score standardization; The oxygen release performance index of hydrogel is predicted using neural network model based on water environment parameters and hydrogel formula parameters; The correlation coefficient between the water environment parameters and the predicted oxygen release performance index is calculated based on the correlation analysis method to determine the compatibility of the hydrogel formula parameters with the water environment parameters; and based on the calculation results, the formula parameters of the hydrogel oxygen-releasing material are dynamically adjusted; Based on the K-means clustering method, the water environment parameters in historical production and the adjusted hydrogel formula parameters were clustered and analyzed to obtain the clustering results of the water environment parameters and the corresponding hydrogel formula parameters, which were used as reference samples for the real-time production process. Based on the calculation results, the formulation parameters of the hydrogel are dynamically adjusted, specifically including the following steps: The correlation between water environment parameters and oxygen release performance indicators was evaluated based on the calculated Spearman rank correlation coefficient; Analyze the effects of hydrogel formulation parameters on oxygen release performance and identify the formulation parameters with the most significant impact; Dynamically adjust hydrogel formulation parameters based on correlation analysis results and formulation parameter impact analysis; The adjusted hydrogel formula parameters are experimentally verified to test whether the oxygen release performance indicators meet the expected targets; if the expected targets are not met, the formula parameters are further adjusted until the requirements are met.

2. The batch production process of the water body ecological restoration hydrogel oxygen-releasing material according to claim 1 is characterized in that: Also includes: Compare the current water environment parameters with the historical water environment parameters in each cluster in the clustering results to find the most similar cluster; From the most similar cluster, the corresponding hydrogel formulation parameters are obtained; Based on the neural network model, the current water environment parameters and hydrogel formula parameters are predicted, and the oxygen release performance index of the current hydrogel is output; Based on the correlation analysis method, the compatibility of the currently obtained hydrogel formula parameters and the water environment parameters is judged; If it is not suitable, the hydrogel formulation parameters are dynamically adjusted based on the calculation results; If suitable, the hydrogel oxygen-releasing material is prepared based on the current hydrogel formula parameters in combination with the freeze-thaw-crosslinking method, and the granular material is made through granulation and drying processes.

3. The batch production process of the water body ecological restoration hydrogel oxygen-releasing material according to claim 1 is characterized in that: The water environment parameters and hydrogel formulation parameters in historical production are processed based on Min-Max normalization, which specifically includes the following steps: Collect water environment parameters and hydrogel formula parameters from historical production, including dissolved oxygen concentration, water temperature, pollutant concentration, pH value, water transparency and water flow rate, as well as polyvinyl alcohol concentration, cross-linking agent type and dosage, and oxygen release agent dosage; Collect oxygen release performance indicators of hydrogel oxygen-releasing materials with different formulations in historical production, including: oxygen release rate, oxygen release duration, mechanical strength, particle size distribution, and environmental stability; Obtain a data set of water environment parameters and oxygen release performance indicators in historical data, and obtain the maximum value and minimum value of the data in the data set; Based on the maximum and minimum values ​​of the data, the data set is scaled to the interval [0, 1], and the calculation formula is as follows: ； Among them, T norm is represented as a normalized data set; T is represented as a data set; T max Expressed as the maximum value of the data; T min Represents the minimum value of the data.

4. The batch production process of the water body ecological restoration hydrogel oxygen-releasing material according to claim 3 is characterized by: The water environment parameters and hydrogel formulation parameters in historical production were processed based on Z-score standardization, which specifically includes the following steps: Get the normalized data set, combine it with the standard deviation, and standardize the current data set to convert the data into a distribution with a mean of 0 and a standard deviation of 1. The calculation formula is as follows: ； Among them, T norm It represents the normalized data set; T represents the data set; μ represents the mean of the data; σ represents the standard deviation.

5. The batch production process of the water body ecological restoration hydrogel oxygen-releasing material according to claim 1 is characterized in that: The water environment parameters and hydrogel formulation parameters are predicted based on the neural network model, which specifically includes the following steps: The treated water environment parameters and hydrogel formulation parameters are used as historical data and divided into training set, validation set and test set; Determine the model structure, initialize the model weights and bias parameters, select a suitable activation function, introduce nonlinear characteristics, and select the mean square error as the model loss function based on the oxygen release performance index; The training set is used as the model input for model training. During the training process, the gradient of the loss function is calculated through the back-propagation algorithm. Use the validation set to evaluate model performance and adjust hyperparameters to optimize model performance; Use the test set to validate and evaluate the model, and use the mean square error to measure the difference between the predicted value and the true value; The trained neural network model is applied to the production process of hydrogel oxygen-releasing materials.

6. The batch production process of the water body ecological restoration hydrogel oxygen-releasing material according to claim 1 is characterized in that: The correlation coefficient between the water environment parameters and the predicted oxygen release performance index is calculated based on the correlation analysis method, which specifically includes the following steps: Obtain water environment parameters and output oxygen release performance indicators, sort the water environment parameters and oxygen release performance indicators from small to large, and calculate the corresponding grade difference of each data point; if there are identical values, take the average grade; Based on the rank difference of each data point, calculate the square of the rank difference of each data point.

7. The batch production process of the water body ecological restoration hydrogel oxygen-releasing material according to claim 6 is characterized in that: Based on the square of the calculated grade difference, the correlation coefficient between the water environment parameters and the predicted oxygen release performance index is calculated to determine the compatibility of the hydrogel formula parameters with the water environment parameters, which specifically includes the following steps: The correlation coefficient between the water environment parameters and the predicted oxygen release performance index was calculated based on the Spearman rank correlation coefficient. The calculation formula is as follows: ； Where, ρ represents the strength and direction of the correlation between water environment parameters and oxygen release performance indicators; n Expressed as the sum of water environment parameters and predicted oxygen release performance indicators; Σd i 2 Expressed as the sum of squared rank differences; 6 and n 2 -1 represents a constant factor in the derivation process; If the correlation coefficient ρ is close to 1 or -1, it means that there is a significant monotonic relationship between the hydrogel formulation parameters and the water environment parameters, and the adaptability is good; If the correlation coefficient ρ is close to 0, it means that there is no obvious correlation between the hydrogel formulation parameters and the water environment parameters, and the hydrogel formulation parameters need to be adjusted.

8. The batch production process of the water body ecological restoration hydrogel oxygen-releasing material according to claim 1 is characterized by: Analyze the effects of hydrogel formulation parameters on oxygen release performance and identify the formulation parameters with significant impact, including: Extract hydrogel formulation parameters; Determining oxygen release performance metrics, wherein the metrics include oxygen release rate, duration, and total oxygen release; Setting the parameter value of each formula substance in the hydrogel formula parameters to form three sets of values ​​corresponding to each formula substance, wherein the three sets of values ​​include the original parameter value of each formula substance in the hydrogel formula parameters and two experimental values ​​set based on the original parameter value; Normalizing the three sets of values ​​corresponding to each formula substance to generate standardized data values ​​corresponding to the formula substance; Taking each formula substance as a variable, and keeping the original parameter values ​​of other formula substances unchanged, the oxygen release performance test is carried out on the three sets of values ​​of each formula substance to obtain the oxygen release rate, duration and total oxygen release amount corresponding to the three sets of values ​​of each formula substance; The differences in the measurement indicators of the three groups of values ​​for each formula substance are obtained based on the experimental results; The influence coefficient of each formula substance on oxygen release performance is obtained by using the difference in the measurement indicators of the three groups of values ​​of each formula substance; Comparing the influence coefficient with a preset first coefficient threshold and a second coefficient threshold; When the influence coefficient exceeds a preset first coefficient threshold, the formula substance whose influence coefficient exceeds the preset first coefficient threshold is determined to be a priority adjustment substance; When the influence coefficient does not exceed the preset first coefficient threshold but exceeds the preset second coefficient threshold, the formula substance whose influence coefficient does not exceed the preset first coefficient threshold but exceeds the preset second coefficient threshold is determined to be a secondary adjustment substance; When the influence coefficient does not exceed the preset second coefficient threshold, it is determined that the formula substance is a substance that does not require adjustment.

9. The batch production process of the water body ecological restoration hydrogel oxygen-releasing material according to claim 8, characterized in that: The process of setting the two experimental values ​​corresponding to each formula substance includes: Extract the correlation coefficients between water environment parameters and predicted oxygen release performance indicators; Extracting the original parameter value of each formula substance in the hydrogel formula parameters; Determine the difference between the correlation coefficient and values ​​close to 1 or -1; Obtaining a parameter adjustment coefficient using a difference between the correlation coefficient and a value close to 1 or -1; The parameter adjustment coefficient is used to set two experimental values ​​corresponding to each formula substance.

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