Degradable plastic production method and system based on isotope determination degradation rate
By using isotopes to determine the degradation rate during the plastic production process, real-time monitoring and optimization of production parameters, the problem of inconsistent degradation performance in traditional plastic production process is solved, and efficient and environmentally friendly degraded plastic production is achieved.
Patent Information
- Application Number
- CN202411692984.4
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-11-25
- Publication Date
- 2025-03-21
- Estimated Expiration
- Not applicable · inactive patent
AI Technical Summary
The traditional plastic production process lacks real-time monitoring and optimization of degradation performance, resulting in inconsistent degradation performance and affecting the quality of plastics.
Degradation rate detection method based on isotope determination is adopted, and degradation experiments are carried out through plastic samples labeled isotopes, real-time production data is collected and analyzed, and real-time production parameters are optimized using the preset degradation plastic production model to determine the optimal production parameters.
It realizes precise control of the production process of degraded plastics, ensures that the product has higher degradation efficiency and consistent quality, reduces resource waste, improves production efficiency, reduces costs, and meets environmental protection needs.
Smart Images
Figure CN119671305A_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to the field of plastic processing, and in particular to a method and system for producing degradable plastics based on isotope-based degradation rate determination. Background Art
[0002] The widespread use of plastic products has brought great convenience and economic wealth to human life. However, along with these benefits comes the problem of plastic waste, which has now become a major factor threatening the ecological environment. In the soil, large amounts of plastic waste residues can cause soil compaction, and long-term accumulation can interfere with the absorption of nutrients and water by crops, ultimately affecting crop yields. Plastic waste on land and in water is often mistakenly eaten by animals, which can lead to their death. Although these wastes are usually disposed of by landfill, this is not an effective solution in the long run because plastics degrade slowly.
[0003] With the improvement of public environmental awareness and increasing attention to food safety, the development of environmentally friendly degradable food packaging materials has become urgent and important. Among them, starch-based packaging materials show great development prospects due to their wide sources and biodegradability. This type of degradable food packaging material mainly uses edible and renewable materials such as starch, fiber, protein and fat as raw materials, combined with industrial manufacturing equipment and professional manufacturing processes to produce novel and practical food packaging solutions. They can be widely used in food packaging films, edible coatings, tableware and other fields. In the natural environment, these materials can degrade more easily, which is of great significance to promoting the development of sustainable development strategies and low-carbon industries. At present, in the production of degradable plastics, the traditional plastic production process often lacks real-time monitoring and optimization of degradation performance, which will make it impossible to effectively control the degradation rate of degradable plastics during production, which will lead to inconsistent degradation performance and affect the quality of plastics.
[0004] Currently, no effective solution has been proposed for the problems in the related technologies. Summary of the invention
[0005] In view of this, and in response to the problems in the related art, the present invention provides a method and system for producing degradable plastics based on isotope determination of degradation rate, so as to solve the above-mentioned problem that the traditional plastic production process often lacks real-time monitoring and optimization of degradation performance.
[0006] In order to solve the above problems, the specific technical solutions adopted by the present invention are as follows: A method and system for producing degradable plastics based on isotope-based degradation rate determination, the method for producing degradable plastics based on isotope-based degradation rate determination comprises the following steps: S1. Selecting polymers with degradable properties as raw materials for the production of degradable plastics; S2. Collect real-time production data during the production of degradable plastics, including raw material parameters, processing conditions and environmental parameters; S3, optimizing production parameters in real time based on real-time production data and through a preset degradable plastic production model to determine the optimal production parameters; S4. Transmit the optimal production parameters to the degradable plastic production system to produce the degradable plastic.
[0007] Preferably, optimizing production parameters according to real-time production data and using a preset degradable plastic production model to determine the optimal real-time production parameters includes the following steps: S31. Degrading the plastic sample labeled with isotopes under preset control conditions, including temperature, humidity and microbial environment; S32. Collect historical production parameters of plastic samples and their isotope contents at different time points during the degradation process, and calculate the degradation rate of degraded plastics; S33, determining a change trend of the plastic sample in a preset time period according to the degradation rate of the degradable plastic; S34, calculating the degradation trend value of the plastic sample according to the historical production parameters of the plastic sample and the change trend of the plastic sample in a preset time period; S35. Conduct correlation analysis on the historical production parameters of plastic samples and their degradation trend values; S36. Based on the results of correlation analysis, a multivariate stepwise regression method is used to establish a degradable plastic production model, and real-time production data is used as model input to obtain the optimal real-time production parameters.
[0008] Preferably, collecting historical production parameters of plastic samples and isotope contents at different time points during the degradation process, and calculating the degradation rate of the degraded plastics comprises the following steps: S321. Collect historical production parameters of plastic samples, and perform data cleaning and classification on the historical production parameters; S322. Collect plastic samples regularly and measure the isotope content in the plastic samples by mass spectrometry; S323, using the collected isotope content data and combining it with the initial content, calculating the degradation rate at different time points; S324, integrating the obtained degradation rate data with historical production parameters.
[0009] Preferably, the calculation formula for calculating the degradation trend value of the plastic sample according to the historical production parameters of the plastic sample and the change trend of the plastic sample in a preset time period is: ; Where N represents the degradation trend value of the i-th production parameter of the plastic sample; S i represents the i-th production parameter value of the plastic sample; R i and R j All represent dimension conversion coefficients; B i Indicates the change trend of the i-th production parameter value of the plastic sample in the preset time period; S j The jth production parameter value of the plastic sample; B j Indicates the change trend of the jth production parameter value of the plastic sample in the preset time period; n represents the number of production parameters of the plastic sample.
[0010] Preferably, the correlation analysis between the historical production parameters of the plastic sample and its degradation status value comprises the following steps: S351. Based on the historical production parameters of the plastic sample and its degradation status value, a parameter status matrix is established, and a minimum support threshold and a minimum confidence threshold are set; S352, using the Apriori algorithm, generating frequent item sets from the parameter situation matrix; S353, establishing association rules between historical production parameters and degradation trend values based on frequent item sets; S354. Analyze the correlation between the historical production parameters and the degradation situation value according to the correlation rules between the historical production parameters and the degradation situation value.
[0011] Preferably, using the Apriori algorithm, generating frequent item sets from the parameter situation matrix includes the following steps: S3521. Scan the parameter situation matrix using the Apriori algorithm and identify candidate items of frequent item sets; S3522, filter out candidates that do not meet the conditions according to the minimum support threshold, and perform pruning operations; S3523. Count the frequencies of the remaining candidate items in the transaction item matrix and determine their support; S3524, based on the support, perform pruning operation again and exclude candidate items that do not meet the minimum support to generate secondary frequent itemsets; S3525. Repeat steps S3521 to S3524 until no new frequent itemsets can be generated, and obtain the final frequent itemsets.
[0012] Preferably, establishing association rules between historical production parameters and degradation status values based on frequent item sets includes the following steps: S3531. Extract all association rules from the final frequent item set; S3532. Calculate the support and confidence of each association rule; S3533. Filter out the most relevant association rules according to the preset minimum support threshold and minimum confidence threshold.
[0013] Preferably, based on the correlation analysis results, a multivariate stepwise regression method is used to establish a degradable plastic production model, and real-time production data is used as model input to obtain the optimal real-time production parameters, including the following steps: S361. According to the correlation analysis results, historical production parameters whose correlation meets the preset threshold are selected as independent variables, and the degradation trend value is used as the dependent variable; S362. Use the multivariate stepwise regression method to construct a degradable plastic production model, and gradually eliminate independent variables to obtain the final degradable plastic production model; S363. Based on the constructed degradable plastic production model, real-time parameter optimization is performed using real-time production data to obtain optimal real-time generation parameters.
[0014] Preferably, constructing a degradable plastic production model using a multivariate stepwise regression method and gradually eliminating independent variables comprises the following steps: S3621. Gradually introduce the preset initial model for each independent variable and evaluate its impact on the initial model; S3622. Based on the introduced independent variables, gradually eliminate the independent variables with the smallest impact on the initial model; S3623. After introducing or removing independent variables at each step, evaluate the fit and statistical significance of the initial model; S3624. When the pre-set termination conditions are met, stop introducing or eliminating independent variables to obtain the final degradable plastic production model.
[0015] According to another aspect of the present invention, a degradable plastic production system based on isotope determination of degradation rate is provided, the degradable plastic production system based on isotope determination of degradation rate comprises: a raw material selection module, a data collection module, a parameter determination module and a plastic production module, and the raw material selection module, the data collection module, the parameter determination module and the plastic production module are connected in sequence; A raw material selection module is used to select polymers with degradable properties as raw materials for the production of degradable plastics; Data collection module, used to collect real-time production data during the production process of degradable plastics, including raw material parameters, processing conditions and environmental parameters; A parameter determination module is used to optimize the production parameters in real time according to the real-time production data and through a preset degradable plastic production model to determine the optimal production parameters; The plastic production module is used to transmit the optimal production parameters to the degradable plastic production system for the production of degradable plastics.
[0016] Compared with the prior art, the present invention provides a method and system for producing degradable plastics based on isotope-based degradation rate determination, which has the following beneficial effects: (1) The present invention can more accurately control the production process of degradable plastics by selecting appropriate degradable polymer raw materials and combining the collection and analysis of real-time production data, which helps to ensure that the produced degradable plastics have higher degradation efficiency and consistent quality. The real-time data can be analyzed by a preset production model to help determine the optimal production parameters, which can reduce resource waste, improve production efficiency, and reduce costs. By real-time monitoring and optimization of production parameters, it can ensure that the produced degradable plastics maintain consistent high quality between different batches, and can improve production efficiency and product quality while ensuring environmental protection and degradation effects, thereby meeting the growing environmental protection needs.
[0017] (2) The present invention can more accurately determine the key production parameters in the plastic degradation process through a combination of experimental and data analysis methods, which helps to produce higher quality and more environmentally friendly plastic products. By optimizing the degradation process of plastics, environmental pollution can be reduced and sustainable development can be promoted. Accurate prediction and control of plastic degradation rates can help improve waste management and recycling. The Apriori algorithm and multivariate stepwise regression method can be used to discover the deep correlation between production parameters and degradation efficiency, thereby providing data support for production decisions and helping to continuously explore and innovate more efficient production methods. BRIEF DESCRIPTION OF THE DRAWINGS
[0018] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work. In the drawings: Figure 1 is a flow chart of a method for producing degradable plastics based on isotope-based degradation rate determination according to an embodiment of the present invention; Figure 2 It is a principle block diagram of a degradable plastic production system based on isotope determination of degradation rate according to an embodiment of the present invention.
[0019] In the figure: 1. Raw material selection module; 2. Data collection module; 3. Parameter determination module; 4. Plastic production module. DETAILED DESCRIPTION
[0020] In order to enable those skilled in the art to better understand the technical solutions in this application, the technical solutions in the embodiments of this application will be clearly and completely described below in conjunction with the drawings in the embodiments of this application. Obviously, the described embodiments are only part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of this application.
[0021] According to an embodiment of the present invention, a method and system for producing degradable plastics based on isotope-based degradation rate determination are provided.
[0022] The present invention is further described with reference to the accompanying drawings and specific embodiments. Figure 1 As shown, according to one embodiment of the present invention, a method for producing degradable plastics based on isotope determination of degradation rate is provided, and the method for producing degradable plastics based on isotope determination of degradation rate comprises the following steps: S1. Selecting polymers with degradable properties as raw materials for the production of degradable plastics; It should be noted that the characteristics and properties of the polymer with degradation properties, such as biodegradability, degradation time, etc., are first determined, polymers that meet the degradation requirements are screened, and their controllable degradability is ensured during the production process.
[0023] S2. Collect real-time production data during the production of degradable plastics, including raw material parameters, processing conditions, environmental parameters, etc.; It should be noted that sensors, monitoring instruments and other real-time monitoring equipment are installed in the degradable plastic production system to collect various production data in real time. Raw material parameters include but are not limited to raw material quality, composition, moisture content, particle size and other related parameters, processing condition monitoring includes temperature, pressure, flow and other processing condition parameters, environmental parameter measurement includes temperature, humidity, gas concentration, etc. These factors may have an impact on the production process of degradable plastics.
[0024] S3, optimizing production parameters in real time based on real-time production data and through a preset degradable plastic production model to determine the optimal production parameters; As a preferred embodiment, according to the real-time production data and through the preset degradable plastic production model, the production parameters are optimized, and the optimal real-time production parameters are determined, including the following steps: S31. Degrading the plastic sample labeled with isotopes under preset control conditions, including temperature, humidity and microbial environment; Specifically, first prepare plastic samples labeled with specific isotopes, set control conditions according to the experimental purpose, conduct experiments under the set conditions, place the labeled plastic samples in the experimental environment, and regularly monitor and record the degradation process.
[0025] The experimental control conditions include: setting a constant temperature, such as the common room temperature of 20-25°C, setting a constant relative humidity, such as the relative humidity of the indoor environment is set between 30%-50%, and the relative humidity of the rainforest environment is set at 80%-100%. The microbial environment is natural soil.
[0026] S32. Collect historical production parameters of plastic samples and their isotope contents at different time points during the degradation process, and calculate the degradation rate of degraded plastics; As a preferred embodiment, collecting the historical production parameters of the plastic sample and its isotope content at different time points during the degradation process, and calculating the degradation rate of the degradable plastic includes the following steps: S321. Collect historical production parameters of plastic samples, and perform data cleaning and classification on the historical production parameters; It should be noted that data cleaning includes deleting duplicate data, correcting errors and outliers, and filling missing values, and then classifying historical production parameters according to production batches, types of raw materials and production process parameters.
[0027] S322. Collect plastic samples regularly and measure the isotope content in the plastic samples by mass spectrometry; It should be noted that mass spectrometers can perform measurements based on different principles and technologies. Common ones include mass spectrometers and isotope ratio mass spectrometers. Mass spectrometers can measure the relative abundance and isotope ratio of different isotopes in a sample. By measuring the isotope ratio, the content of different isotopes in the sample can be determined.
[0028] S323, using the collected isotope content data and combining it with the initial content, calculating the degradation rate at different time points; It should be noted that by collecting isotope content data and initial content data, the isotope content data should include measurement results at different time points, and the initial content data refers to the content value at the initial moment. For the isotope content data at each time point, the relative degradation rate is calculated, and the relative degradation rate refers to the degree of degradation relative to the initial content.
[0029] S324, integrating the obtained degradation rate data with historical production parameters.
[0030] It should be noted that the degradation rate data and historical production parameter data can be integrated and stored and managed in the form of data tables or databases, and the integrated data can be used for statistics and analysis. Statistical indicators such as the average degradation rate, maximum degradation rate, and minimum degradation rate under different historical production parameter conditions can be calculated to understand the overall impact of historical production parameters on the degradation rate.
[0031] S33, determining a change trend of the plastic sample in a preset time period according to the degradation rate of the degradable plastic; It should be noted that according to the characteristics of degradable plastics, the preset time period is divided into multiple stages, such as early, middle and late stages. The early stage is set at two weeks, the middle stage is set at three to six weeks, and the late stage is set after seven weeks.
[0032] S34, calculating the degradation trend value of the plastic sample according to the historical production parameters of the plastic sample and the change trend of the plastic sample in a preset time period; Specifically, the calculation formula for calculating the degradation trend value of the plastic sample according to the historical production parameters of the plastic sample and the change trend of the plastic sample in a preset time period is: ; Where N represents the degradation trend value of the i-th production parameter of the plastic sample; S i represents the i-th production parameter value of the plastic sample; R i and R j All represent dimension conversion coefficients; B i Indicates the change trend of the i-th production parameter value of the plastic sample in the preset time period; S j The jth production parameter value of the plastic sample; B j Indicates the change trend of the jth production parameter value of the plastic sample in the preset time period; n represents the number of production parameters of the plastic sample.
[0033] Specifically, by calculating the degradation trend value of the plastic sample, the historical production parameters and the changing trends of the preset time period can be comprehensively considered to evaluate the degradation degree and degradation trend of the plastic sample, which can help evaluate the degradable performance of the plastic sample.
[0034] S35. Conduct correlation analysis on the historical production parameters of plastic samples and their degradation trend values; As a preferred embodiment, the correlation analysis between the historical production parameters of the plastic sample and its degradation status value includes the following steps: S351. Based on the historical production parameters of the plastic sample and its degradation status value, a parameter status matrix is established, and a minimum support threshold and a minimum confidence threshold are set; It should be noted that the historical production parameters of the plastic samples are taken as columns of the matrix, and the corresponding degradation trend values are taken as columns of the matrix or as category labels of the matrix. Each row represents a sample, which contains the historical production parameters and the corresponding degradation trend values.
[0035] Among them, the minimum support refers to the proportion of all samples that simultaneously contain a certain historical production parameter or degradation trend value, and the minimum confidence refers to the proportion of samples that contain a certain historical production parameter and simultaneously contain another historical production parameter or degradation trend value.
[0036] S352, using the Apriori algorithm, generating frequent item sets from the parameter situation matrix; It should be noted that the Apriori algorithm is a classic algorithm for association rule mining, which is usually used to discover the association between item sets from large-scale data sets. The main goal of this algorithm is to find frequent item sets, that is, item sets that often appear together in the data set. These frequent item sets can be used to generate association rules to describe the association relationship between item sets.
[0037] As a preferred implementation, using the Apriori algorithm, generating frequent item sets from the parameter situation matrix includes the following steps: S3521. Scan the parameter situation matrix using the Apriori algorithm and identify candidate items of frequent item sets; It should be noted that the candidate items of frequent itemsets are generated in the iterative process of the Apriori algorithm. In each iteration, the algorithm generates candidate item sets, and then counts their support by scanning the data set, filtering out item sets with support below the set threshold, and finally obtaining frequent item sets. These frequent item sets are combinations of items that frequently appear in the data set.
[0038] S3522, filter out candidates that do not meet the conditions according to the minimum support threshold, and perform pruning operations; It should be noted that in the Apriori algorithm, the pruning operation is mainly based on the Apriori property to remove candidate item sets that cannot be frequent item sets. By excluding candidate item sets that cannot be frequent item sets, the efficiency of the algorithm is improved, making the mining process more efficient and feasible.
[0039] S3523. Count the frequencies of the remaining candidate items in the transaction item matrix and determine their support; S3524, based on the support, perform pruning operation again and exclude candidate items that do not meet the minimum support to generate secondary frequent itemsets; S3525. Repeat steps S3521 to S3524 until no new frequent itemsets can be generated, and obtain the final frequent itemsets.
[0040] S353, establishing association rules between historical production parameters and degradation trend values based on frequent item sets; As a preferred implementation, establishing association rules between historical production parameters and degradation status values based on frequent item sets includes the following steps: S3531. Extract all association rules from the final frequent item set; It should be noted that for each frequent item set, all possible non-empty subsets are generated as conditions, and the difference between these subsets and the frequent item set is calculated as the conclusion, so as to obtain all possible association rules, and the generated rules are used to obtain the set of all possible association rules.
[0041] S3532. Calculate the support and confidence of each association rule; S3533. Filter out the most relevant association rules according to the preset minimum support threshold and minimum confidence threshold.
[0042] S354. Analyze the correlation between the historical production parameters and the degradation situation value according to the correlation rules between the historical production parameters and the degradation situation value.
[0043] S36. Based on the results of correlation analysis, a multivariate stepwise regression method is used to establish a degradable plastic production model, and real-time production data is used as model input to obtain the optimal real-time production parameters.
[0044] As a preferred implementation, based on the correlation analysis results, a multivariate stepwise regression method is used to establish a degradable plastic production model, and real-time production data is used as model input to obtain the optimal real-time production parameters, including the following steps: S361. According to the correlation analysis results, historical production parameters whose correlation meets the preset threshold are selected as independent variables, and the degradation trend value is used as the dependent variable; S362. Use the multivariate stepwise regression method to construct a degradable plastic production model, and gradually eliminate independent variables to obtain the final degradable plastic production model; Specifically, multivariate stepwise regression is a regression analysis method used to explore the relationship between a dependent variable (target variable) and multiple independent variables (explanatory variables). This method builds a model by gradually adding and deleting independent variables to find the combination of independent variables that has the most significant impact on the dependent variable.
[0045] As a preferred embodiment, the multivariate stepwise regression method is used to construct a degradable plastic production model, and the independent variables are gradually eliminated, including the following steps: S3621. Gradually introduce the preset initial model for each independent variable and evaluate its impact on the initial model; It should be noted that, according to the preset initial model, a group of independent variables are selected as the independent variable set of the initial model, and the remaining independent variables are gradually introduced into the initial model, one independent variable at a time. After each step of introducing the independent variable, the performance and goodness of fit of the model are evaluated. Indicators such as adjusted R-square, AIC, BIC, etc. can be used to evaluate the degree of fit of the model.
[0046] S3622. Based on the introduced independent variables, gradually eliminate the independent variables with the smallest impact on the initial model; S3623. After introducing or removing independent variables at each step, evaluate the fit and statistical significance of the initial model; It should be noted that after introducing independent variables at each step, the impact of each independent variable is evaluated. It is possible to identify the independent variables with the smallest impact on the model and eliminate them by checking indicators such as the coefficient size and significance level. This can be done by setting a threshold, for example, eliminating independent variables with smaller absolute coefficient values.
[0047] S3624. When the pre-set termination conditions are met, stop introducing or eliminating independent variables to obtain the final degradable plastic production model.
[0048] It should be noted that the termination condition is that when the statistical significance index of the degradable plastic production model no longer changes after introducing new independent variables or eliminating existing independent variables, the introduction or elimination of independent variables will be stopped.
[0049] S363. Based on the constructed degradable plastic production model, real-time parameter optimization is performed using real-time production data to obtain optimal real-time generation parameters.
[0050] It should be noted that real-time data is imported into the constructed degradable plastic production model to predict or simulate the real-time data. According to the prediction results of the model, the production parameters that need to be adjusted are determined, including adjusting the temperature, pressure, flow and other production parameters to optimize the production process.
[0051] S4. Transmit the optimal production parameters to the degradable plastic production system to produce the degradable plastic.
[0052] It should be noted that the biodegradable plastic production system consists of raw material processing, reactors, catalyst and additive adding equipment, product separation and post-processing equipment, etc.
[0053] Among them, after the biodegradable plastic production model determines the optimal production parameter combination, the optimal production parameters are transmitted to the biodegradable plastic production system. According to the characteristics and requirements of the biodegradable plastic production system, the relevant equipment, control systems and process flows are adjusted to monitor the production process to ensure that the actual application of the production parameters is consistent with expectations. The performance and results of the production process are continuously monitored and evaluated. According to the actual situation, continuous optimization and improvement are carried out to further improve the production efficiency and quality of biodegradable plastics.
[0054] Specifically, after the biodegradable plastic production model determines the optimal combination of production parameters, it is a crucial step to effectively transfer these parameters to the biodegradable plastic production system. The following is a detailed description of how to do this and a specific example: Obtain the optimal combination of production parameters from the degradable plastic production model, including reaction temperature, pressure, catalyst dosage, reaction time, additive ratio, etc.; Input the confirmed optimal production parameters into the central control system of the biodegradable plastic production system. This is usually done through a dedicated software interface or control system operation panel; Adjust each part of the production system according to the optimal parameters, including raw material processing, reactor configuration, product separation and post-processing, and calibrate the production system to ensure that all equipment operates according to the set parameters and the production system as a whole is in the best condition.
[0055] Start the production system and monitor the key parameters of the production process in real time to ensure that they are consistent with the optimal parameters. If necessary, fine-tune the parameters of the production process to cope with any possible fluctuations or deviations.
[0056] For example, suppose that the optimal production parameter combination determined by the degradable plastic production model is: reaction temperature 200°C, reaction pressure 1.5MPa, catalyst dosage 5%, reaction time 4 hours, additive A ratio 2%, additive B ratio 1%.
[0057] Log in to the central control software of the biodegradable plastic production system, find options such as reaction temperature, reaction pressure, catalyst dosage, reaction time, additive ratio, etc. in the "Production Parameter Settings" or similar menu, enter the above optimal parameters into the corresponding options, and save the settings.
[0058] Adjust the temperature controller of the reactor to ensure that the reaction temperature can be stabilized at 200°C; adjust the pressure control system of the reactor to ensure that the reaction pressure can be maintained at 1.5MPa; check the catalyst feeder and additive feeder to ensure that they can accurately add materials according to the set ratio (5% and 2%, 1%); set the reaction time to 4 hours and configure the corresponding timer or control system; calibrate the entire system to ensure that all equipment operates according to the set parameters.
[0059] Start the production system and begin the production process of degradable plastics; monitor key parameters such as reaction temperature, reaction pressure, catalyst dosage, reaction time, etc. in real time to ensure that they are consistent with the optimal parameters; if any deviation or abnormality is found, make adjustments immediately or take corrective measures.
[0060] like Figure 2 As shown, according to another embodiment of the present invention, a degradable plastic production system based on isotope determination of degradation rate is provided, and the degradable plastic production system based on isotope determination of degradation rate comprises: a raw material selection module 1, a data collection module 2, a parameter determination module 3 and a plastic production module 4, and the raw material selection module 1, the data collection module 2, the parameter determination module 3 and the plastic production module 4 are connected in sequence; A raw material selection module 1 is used to select a polymer with a degradable property as a raw material for the production of degradable plastics; Data collection module 2, used to collect real-time production data during the production process of degradable plastics, including raw material parameters, processing conditions and environmental parameters; Parameter determination module 3, used to optimize the production parameters in real time according to the real-time production data and through the preset degradable plastic production model, and determine the optimal production parameters; The plastic production module 4 is used to transmit the optimal production parameters to the degradable plastic production system for producing degradable plastic.
[0061] In summary, with the help of the above technical scheme of the present invention, the present invention can more accurately control the production process of degradable plastics by selecting appropriate degradable polymer raw materials and combining the collection and analysis of real-time production data, which helps to ensure that the produced degradable plastics have higher degradation efficiency and consistent quality. The real-time data is analyzed by a preset production model, which helps to determine the optimal production parameters, which can reduce resource waste, improve production efficiency, and reduce costs. By real-time monitoring and optimizing production parameters, it can ensure that the produced degradable plastics maintain consistent high quality between different batches, and can improve production efficiency and product quality while ensuring environmental protection and degradation effects, and meet the growing environmental protection needs; the present invention can more accurately determine the key production parameters in the plastic degradation process through a method combining experiments and data analysis, which helps to produce higher quality and more environmentally friendly plastic products. By optimizing the degradation process of plastics, environmental pollution can be reduced and sustainable development can be promoted. Accurate prediction and control of plastic degradation rate helps to improve waste management and recycling. The Apriori algorithm and multivariate stepwise regression method can be used to find the deep correlation between production parameters and degradation efficiency, thereby providing data support for production decisions and helping to continuously explore and innovate more efficient production methods.
[0062] It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, optical storage, etc.) containing computer-usable program code.
[0063] The specific embodiments described above further illustrate the objectives, technical solutions and beneficial effects of the present invention in detail. It should be understood that the above description is only a specific embodiment of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.
Claims
1. A method for producing degradable plastics based on isotope-based degradation rate determination, characterized in that: The method for producing degradable plastics based on isotope-based degradation rate determination comprises the following steps: S1. Selecting polymers with degradable properties as raw materials for the production of degradable plastics; S2. Collect real-time production data during the production of degradable plastics, including raw material parameters, processing conditions and environmental parameters; S3, optimizing production parameters in real time based on real-time production data and through a preset degradable plastic production model to determine the optimal production parameters; S4. Transmit the optimal production parameters to the degradable plastic production system to produce the degradable plastic.
2. The method for producing degradable plastics based on isotope-based degradation rate determination according to claim 1, characterized in that: The method of optimizing production parameters according to real-time production data and using a preset degradable plastic production model to determine the optimal real-time production parameters includes the following steps: S31, subjecting the plastic sample labeled with the isotope to plastic degradation under preset control conditions, wherein the control conditions include temperature, humidity and microbial environment; S32. Collect historical production parameters of plastic samples and their isotope contents at different time points during the degradation process, and calculate the degradation rate of degraded plastics; S33, determining a change trend of the plastic sample in a preset time period according to the degradation rate of the degradable plastic; S34, calculating the degradation trend value of the plastic sample according to the historical production parameters of the plastic sample and the change trend of the plastic sample in a preset time period; S35. Conduct correlation analysis on the historical production parameters of plastic samples and their degradation trend values; S36. Based on the results of correlation analysis, a multivariate stepwise regression method is used to establish a degradable plastic production model, and real-time production data is used as model input to obtain the optimal real-time production parameters.
3. The method for producing degradable plastics based on isotope-based degradation rate determination according to claim 2, characterized in that: The process of collecting the historical production parameters of the plastic sample and its isotope content at different time points during the degradation process and calculating the degradation rate of the degraded plastic comprises the following steps: S321. Collect historical production parameters of plastic samples, and perform data cleaning and classification on the historical production parameters; S322. Collect plastic samples regularly and measure the isotope content in the plastic samples by mass spectrometry; S323, using the collected isotope content data and combining it with the initial content, calculating the degradation rate at different time points; S324, integrating the obtained degradation rate data with historical production parameters.
4. The method for producing degradable plastics based on isotope-based degradation rate determination according to claim 2, characterized in that: The calculation formula for calculating the degradation trend value of the plastic sample based on the historical production parameters of the plastic sample and the change trend of the plastic sample in a preset time period is: ； Where N represents the degradation trend value of the i-th production parameter of the plastic sample; S i represents the i-th production parameter value of the plastic sample; R i and R j All represent dimension conversion coefficients; B i Indicates the change trend of the i-th production parameter value of the plastic sample in the preset time period; S j The jth production parameter value of the plastic sample; B j Indicates the change trend of the jth production parameter value of the plastic sample in the preset time period; n represents the number of production parameters of the plastic sample.
5. The method for producing degradable plastics based on isotope-based degradation rate determination according to claim 2, characterized in that: The correlation analysis between the historical production parameters of the plastic sample and its degradation status value comprises the following steps: S351. Based on the historical production parameters of the plastic sample and its degradation status value, a parameter status matrix is established, and a minimum support threshold and a minimum confidence threshold are set; S352, using the Apriori algorithm, generating frequent item sets from the parameter situation matrix; S353, establishing association rules between historical production parameters and degradation trend values based on frequent item sets; S354. Analyze the correlation between the historical production parameters and the degradation situation value according to the correlation rules between the historical production parameters and the degradation situation value.
6. The method for producing degradable plastics based on isotope-based degradation rate determination according to claim 5, characterized in that: The method of generating frequent item sets from the parameter situation matrix using the Apriori algorithm includes the following steps: S3521. Scan the parameter situation matrix using the Apriori algorithm and identify candidate items of frequent item sets; S3522, filter out candidates that do not meet the conditions according to the minimum support threshold, and perform pruning operations; S3523. Count the frequencies of the remaining candidate items in the transaction item matrix and determine their support; S3524, based on the support, perform pruning operation again and exclude candidate items that do not meet the minimum support to generate secondary frequent itemsets; S3525. Repeat steps S3521 to S3524 until no new frequent itemsets can be generated, and obtain the final frequent itemsets.
7. The method for producing degradable plastics based on isotope-based degradation rate determination according to claim 5, characterized in that: The establishment of association rules between historical production parameters and degradation status values based on frequent item sets includes the following steps: S3531. Extract all association rules from the final frequent item set; S3532. Calculate the support and confidence of each association rule; S3533. Filter out the most relevant association rules according to the preset minimum support threshold and minimum confidence threshold.
8. The method for producing degradable plastics based on isotope-based degradation rate determination according to claim 2, characterized in that: The method of establishing a degradable plastic production model based on the correlation analysis results by using a multivariate stepwise regression method and using real-time production data as model input to obtain the optimal real-time production parameters includes the following steps: S361. According to the correlation analysis results, historical production parameters whose correlation meets the preset threshold are selected as independent variables, and the degradation trend value is used as the dependent variable; S362. Use the multivariate stepwise regression method to construct a degradable plastic production model, and gradually eliminate independent variables to obtain the final degradable plastic production model; S363. Based on the constructed degradable plastic production model, real-time parameter optimization is performed using real-time production data to obtain optimal real-time generation parameters.
9. The method for producing degradable plastics based on isotope-based degradation rate determination according to claim 8, characterized in that: The method of constructing a degradable plastic production model by using a multivariate stepwise regression method and gradually eliminating independent variables includes the following steps: S3621. Gradually introduce the preset initial model for each independent variable and evaluate its impact on the initial model; S3622. Based on the introduced independent variables, gradually eliminate the independent variables with the smallest impact on the initial model; S3623. After introducing or removing independent variables at each step, evaluate the fit and statistical significance of the initial model; S3624. When the pre-set termination conditions are met, stop introducing or eliminating independent variables to obtain the final degradable plastic production model.
10. A system for producing degradable plastics based on isotope measurement of degradation rate, used to implement the method for producing degradable plastics based on isotope measurement of degradation rate according to any one of claims 1 to 9, characterized in that: The degradable plastic production system based on isotope-based degradation rate determination comprises: a raw material selection module, a data collection module, a parameter determination module and a plastic production module, and the raw material selection module, the data collection module, the parameter determination module and the plastic production module are connected in sequence; The raw material selection module is used to select polymers with degradable properties as raw materials for the production of degradable plastics; The data collection module is used to collect real-time production data during the production process of degradable plastics, including raw material parameters, processing conditions and environmental parameters; The parameter determination module is used to optimize the production parameters in real time according to the real-time production data and through a preset degradable plastic production model to determine the optimal production parameters; The plastic production module is used to transmit the optimal production parameters to the degradable plastic production system to produce degradable plastics.