Integrated separation decision-making method and system for volatile organic compounds

Abstract

The invention discloses an integrated separation decision-making method and system for volatile organic compounds, and relates to the technical field of waste gas separation.The method comprises the steps that volatile organic compounds are separated according to VOCs production process element information, a VOCs production component system is generated, and then the VOCs production component system is classified and marked based on a VOCs attribute classifier; determining a VOCs production attribute feature information set; according to the VOCs separation processing strategy, a VOCs separation processing data space is constructed in a data driving mode, then parameter analysis is carried out on the VOCs production attribute characteristic information set, and VOCs separation processing parameters are output; and carrying out separation treatment and waste gas separation decision on the VOCs production component system based on the VOCs separation treatment parameters. The technical effects that intelligent and efficient waste gas separation treatment is achieved, the separation treatment efficiency and the treatment decision accuracy are improved, and then the waste gas separation treatment effect is ensured are achieved.

Description

Technical Field

[0001] This invention relates to the field of waste gas separation technology, and in particular to an integrated separation decision method and system for volatile organic compounds. Background Technology

[0002] With the acceleration of industrialization and urbanization, the pollution problem of volatile organic compounds (VOCs) is becoming increasingly serious. VOCs not only negatively impact human health and the environment but can also lead to environmental problems such as photochemical smog and ozone layer depletion. Therefore, how to effectively treat and remove VOCs from waste gas has become an urgent problem to be solved. Existing VOCs separation and treatment methods mainly include adsorption, condensation, precipitation, filtration, membrane separation, direct combustion, and catalytic combustion. However, the complex gas composition of existing technologies leads to low separation and treatment efficiency. Summary of the Invention

[0003] This application provides an integrated separation decision-making method and system for volatile organic compounds, which solves the technical problem of low separation efficiency caused by complex gas composition in existing technologies. It achieves intelligent and efficient waste gas separation and treatment, improves separation and treatment efficiency and treatment decision accuracy, and thus ensures the effectiveness of waste gas separation and treatment.

[0004] In view of the above problems, the present invention provides an integrated separation decision method and system for volatile organic compounds.

[0005] Firstly, this application provides an integrated separation decision-making method for volatile organic compounds (VOCs). The method includes: acquiring VOCs production process information; extracting elements from the VOCs production process information to obtain VOCs production process element information; separating VOCs according to the VOCs production process element information to generate a VOCs production component system; constructing a VOCs attribute classifier, which includes production source, chemical structure, physical properties, and generation concentration; classifying and labeling each VOCs information in the VOCs production component system based on the VOCs attribute classifier to determine a VOCs production attribute feature information set; setting a VOCs separation and treatment strategy, which includes separation and treatment method, separation and treatment sequence, and separation and treatment level; constructing a VOCs separation and treatment data space based on the VOCs separation and treatment strategy using a data-driven approach; performing parameter analysis on the VOCs production attribute feature information set based on the VOCs separation and treatment data space to output VOCs separation and treatment parameters; and making separation and treatment decisions for the VOCs production component system based on the VOCs separation and treatment parameters.

[0006] On the other hand, this application also provides an integrated separation decision system for volatile organic compounds (VOCs), the system comprising: a process element extraction module for acquiring VOCs production process information and extracting elements from the VOCs production process information to obtain VOCs production process element information; a VOCs separation module for separating VOCs according to the VOCs production process element information to generate a VOCs production component system; an attribute classifier construction module for constructing a VOCs attribute classifier, the VOCs attribute classifier including production source, chemical structure, physical properties, and generation concentration; and a system classification labeling module for classifying each component in the VOCs production component system based on the VOCs attribute classifier. The system classifies and labels VOCs information to determine the set of VOCs production attribute characteristic information; a separation and treatment strategy setting module is used to set VOCs separation and treatment strategies, which include separation and treatment methods, separation and treatment order, and separation and treatment levels; a separation and treatment parameter output module is used to construct a VOCs separation and treatment data space based on the VOCs separation and treatment strategy in a data-driven manner, perform parameter analysis on the set of VOCs production attribute characteristic information based on the VOCs separation and treatment data space, and output VOCs separation and treatment parameters; and a waste gas separation and treatment decision module is used to make separation and treatment decisions for the VOCs production component system and waste gas separation based on the VOCs separation and treatment parameters.

[0007] One or more technical solutions provided in this application have at least the following technical effects or advantages: This technical solution employs a method that extracts elements from VOCs production process information, separates volatile organic compounds (VOCs) based on the extracted VOCs production process elements, and generates a VOCs production component system. A VOCs attribute classifier is used to classify and label each VOCs information in the VOCs production component system, determining a set of VOCs production attribute feature information. Simultaneously, a VOCs separation and treatment strategy is set, including separation and treatment methods, separation and treatment order, and separation and treatment levels. Based on the VOCs separation and treatment strategy, a VOCs separation and treatment data space is constructed using a data-driven approach. This space is then used to perform parameter analysis on the VOCs production attribute feature information set, outputting VOCs separation and treatment parameters. Based on these parameters, separation and treatment decisions are made for the VOCs production component system. This achieves the technical effect of intelligent and efficient waste gas separation and treatment, improving separation and treatment efficiency and the accuracy of treatment decisions, thereby ensuring the effectiveness of waste gas separation and treatment.

[0008] The above description is only an overview of the technical solution of this application. In order to better understand the technical means of this application and to implement it in accordance with the contents of the specification, and to make the above and other objects, features and advantages of this application more obvious and understandable, the following are specific embodiments of this application. Attached Figure Description

[0009] Figure 1 This is a flowchart illustrating the integrated separation decision method for volatile organic compounds used in this application. Figure 2 This is a schematic diagram of the process for generating VOCs production components in the integrated separation decision method for volatile organic compounds used in this application; Figure 3 This is a schematic diagram of the integrated separation decision system for volatile organic compounds used in this application.

[0010] Figure labeling: Module 11 for process element extraction, Module 12 for volatile organic compound separation, Module 13 for attribute classifier construction, Module 14 for system classification labeling, Module 15 for separation treatment strategy setting, Module 16 for separation treatment parameter output, and Module 17 for waste gas separation treatment decision. Detailed Implementation

[0011] This application provides an integrated separation decision-making method and system for volatile organic compounds, which solves the technical problem of low separation efficiency caused by complex gas composition in existing technologies. It achieves intelligent and efficient waste gas separation and treatment, improves separation and treatment efficiency and treatment decision accuracy, and thus ensures the effectiveness of waste gas separation and treatment.

[0012] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0013] This application will now be described with reference to the accompanying drawings.

[0014] Example 1 like Figure 1 As shown, this application provides an integrated separation decision method for volatile organic compounds, the method being applied to an integrated separation decision system for volatile organic compounds, the method comprising: Step S1: Obtain VOCs production process information, and extract elements from the VOCs production process information to obtain VOCs production process element information; Specifically, with the acceleration of industrialization and urbanization, the pollution problem of volatile organic compounds (VOCs) is becoming increasingly serious. VOCs not only have negative impacts on human health and the environment, but may also lead to environmental problems such as photochemical smog and ozone layer depletion. Therefore, how to effectively treat and remove VOCs from waste gas has become an urgent problem to be solved. Existing VOCs separation and treatment methods mainly include adsorption, condensation, precipitation, filtration, membrane separation, direct combustion, and catalytic combustion.

[0015] VOCs are generated in various industrial production processes. To achieve intelligent and efficient waste gas treatment, the first step is to obtain the production process information of the VOCs to be treated. For example, the production process of polycrystalline silicon cells in the photovoltaic industry includes processes such as cutting, bonding, cleaning, printing, and sintering, all of which generate VOCs. Next, the VOCs production process information is analyzed by extracting relevant parameters, specifically the volatile organic compound (VOC) correlation parameters. This yields corresponding VOCs production process element information, including production process nodes, reactants, and related parameters of the production environment. This provides production data for subsequent VOCs separation and treatment.

[0016] Step S2: Separate volatile organic compounds according to the VOCs production process element information to generate a VOCs production component system; like Figure 2 As shown, furthermore, the step of generating the VOCs production component system in this application also includes: Based on the VOCs production process element information, the production process nodes, node reactant parameters, node reaction mechanisms, and node environmental parameters are determined. Digital twin technology is used to create a three-dimensional model of the production process nodes, node reactant parameters, node reaction mechanisms, and node environmental parameters, generating a VOCs production process twin model. The VOCs production process twin model is divided into N spatial units, each corresponding one-to-one with a production process node. Spatial reaction traversal simulation is performed based on the N spatial units to generate a VOCs production component information set, and the VOCs production component system is formed based on this VOCs production component information set.

[0017] Furthermore, the step of generating the VOCs production component information set in this application also includes: A time-reaction node is set, and the N spatial units sequentially perform spatial reaction simulations according to the time-reaction node to obtain a time-node production component information set for the N spatial units; based on the VOCs component changes in the time-node production component information set, N VOCs component change curves are obtained; based on the N VOCs component change curves, a conversion analysis is performed to construct N spatial VOCs component conversion models; based on the N spatial VOCs component conversion models, production prediction is performed to determine the VOCs production component information set.

[0018] Furthermore, the construction of N spatial VOCs component conversion models, as described in this application, further includes the following steps: Rate analysis is performed on the N VOCs component change curves to obtain N VOCs component change rate curves; information on the change rate of components at turning points is extracted from the N VOCs component change rate curves; continuity analysis is performed on the change rate information of components at turning points to obtain N VOCs component change rate coefficients; weighted fitting is performed on the N VOCs component change rate coefficients according to the proportion of organic matter components to construct the N spatial VOCs component conversion models.

[0019] Specifically, volatile organic compound (VOC) separation is performed based on the VOCs production process element information. First, the main production-related parameters are determined based on this information, including: production process nodes (node ​​type, node sequence, etc.); node reactant parameters (reactant type, reactant production quantity, and concentration at each node); node reaction mechanisms (reaction conversion equations and VOCs generation types at each node); and node environmental parameters (temperature, humidity, and air pressure at each node). Using digital twin technology combined with historical production data, a three-dimensional model, data-driven correlation, and multi-scale coupling are performed on the production process nodes, reactant parameters, reaction mechanisms, and environmental parameters to generate a VOCs production process twin model. This model simulates the VOCs generation at each production process node. The VOCs production process twin model is then divided into N spatial units, each corresponding to a production process node, with different VOCs generation conditions in each unit.

[0020] Based on the aforementioned N spatial units, a spatial reaction ergonomic simulation is performed. This involves using the finite volume method or smoothed particle fluid dynamics to sequentially simulate the VOCs production process in each spatial unit, independently solving the mass / energy conservation equations for each unit. Specifically, time-based reaction nodes are set, which are time intervals separating the reaction time, for example, 1 minute. The production components are simulated at minute intervals. The N spatial units are sequentially simulated at multiple time points according to these time-based reaction nodes, thereby obtaining the corresponding time-point production component information sets for the N spatial units, i.e., the exhaust gas component content information for each time point. Based on the changes in the concentration of each type of VOCs in the time-point production component information sets, N VOCs component change curves are plotted for each time point to illustrate the relationship between the concentration of each type of VOCs component and time.

[0021] A conversion analysis is performed based on the N VOCs component change curves, specifically analyzing the concentration conversion of VOCs components in each spatial unit. First, a rate analysis is conducted on the N VOCs component change curves. By differentiating the VOCs component change curves, corresponding N VOCs component change rate curves are obtained, indicating the speed of change in the production reaction rate of VOCs components. Next, information on the rate of change of components at turning points is extracted from the N VOCs component change rate curves, marking the rate increase inflection points in the curves. Then, a continuity analysis is performed on the rate of change of components at these turning points. This involves taking the second derivative of the VOCs component change curves to obtain N VOCs component change rate coefficients that represent the trend of VOCs component changes. Larger coefficients indicate a stronger trend in the VOCs component conversion rate. The N VOCs component change rate coefficients are then weighted and fitted according to the proportion of each type of volatile organic compound in each spatial unit, constructing N spatial VOCs component conversion models. These spatial VOCs component conversion models are used to simulate the conversion relationship of each type of VOCs component over time.

[0022] Based on the N spatial VOCs component conversion models, production predictions are performed to calculate and determine the VOCs production component information set at the preset VOCs treatment time point. This set includes the VOCs production component types and concentrations of each type across N spatial units. A VOCs production component system is then constructed based on this information set, indicating the composition parameters of the VOCs to be treated in the production process. This enables personalized intelligent analysis of VOCs components, improving the comprehensiveness and accuracy of component analysis, thereby ensuring separation and treatment efficiency and the precision of treatment decisions.

[0023] Step S3: Construct a VOCs attribute classifier, which includes production source, chemical structure, physical properties, and concentration of generated VOCs. Step S4: Based on the VOCs attribute classifier, classify and label the VOCs information in the VOCs production component system to determine the VOCs production attribute feature information set; Step S5: Set the VOCs separation and treatment strategy, which includes separation and treatment method, separation and treatment sequence, and separation and treatment level; Specifically, to improve the accuracy of separation and processing, a VOCs attribute classifier is constructed. This classifier categorizes each volatile organic compound by its attributes. Classification indicators include: production source (e.g., oil industry sources, adhesive industry sources, dry cleaning industry sources, etc.); chemical structure (e.g., alkanes, aromatics, esters, aldehydes, etc.); physical properties (e.g., volatility, water solubility, density, etc.); and generation concentration (i.e., the VOCs generation concentration at the time point to be processed). Based on this VOCs attribute classifier, the information of each VOC in the VOCs production component system is classified and labeled to determine the attribute characteristics of the VOCs to be processed. These attribute characteristics are then fused and labeled to form a VOCs production attribute characteristic information set, which serves as the basis for separation and processing features. A VOCs separation and treatment strategy is established, which refers to the methods for separating and treating VOCs. The strategy indicators include: separation and treatment methods, such as adsorption, condensation, membrane separation, and biological treatment; separation and treatment sequence, i.e., the order in which different types of VOCs are separated and treated; and separation and treatment levels, including parameters such as the separation and treatment time and degree for each type of VOC. This aims to achieve comprehensive and rational VOCs separation and treatment, thereby improving separation and treatment efficiency.

[0024] Step S6: Based on the VOCs separation and processing strategy, construct a VOCs separation and processing data space using a data-driven approach. Based on the VOCs separation and processing data space, perform parameter analysis on the VOCs production attribute feature information set and output VOCs separation and processing parameters. Furthermore, regarding the output VOCs separation and processing parameters, the steps in this application also include: According to the VOCs separation and processing strategy, separation and processing feature dimension information is set; based on the separation and processing feature dimension information, the VOCs production attribute feature information set is arranged and integrated to obtain the VOCs production attribute feature dimension information set; a similarity algorithm is used to calculate the similarity between the VOCs production attribute feature dimension information set and the VOCs separation and processing data space to determine the separation and processing strategy similarity set; based on the separation and processing strategy similarity set, the separation and processing parameters are optimized, and the VOCs separation and processing parameters are output.

[0025] Furthermore, the step of optimizing the separation processing parameters based on the similarity set of the separation processing strategy in this application also includes: Based on the similarity set of the separation and treatment strategies, the similarity is sorted in descending order, and a separation and treatment strategy parameter memory is constructed by proportional screening. Indicators are extracted from the volatile organic compound (VOC) separation standards to obtain organic compound separation effect evaluation indicators, including treatment efficiency, recovery rate, and separation energy consumption. Based on the organic compound separation effect evaluation indicators, a separation effect fitness function is constructed. The separation effect fitness function is used to perform a global search and optimization within the separation and treatment strategy parameter memory until a preset number of iterations are reached, and the VOCs separation and treatment parameters are output.

[0026] Specifically, based on the VOCs separation and processing strategy, a VOCs separation and processing data space is constructed using a data-driven approach. Data-driven processing is a method that uses data as the primary driving force, employing data analysis and utilization to make decisions or optimize processes. This involves collecting and searching various processing data related to the VOCs separation and processing strategy to form the VOCs separation and processing data space. This data space includes VOCs attribute feature data, processing strategy data, and separation and processing effect data. Based on this VOCs separation and processing data space, parameter analysis is performed on the VOCs production attribute feature information set. To ensure standardized and efficient parameter optimization analysis, separation and processing feature dimension information is first set according to the VOCs separation and processing strategy. This separation and processing feature dimension information corresponds to the feature types in the VOCs separation and processing strategy, including separation and processing methods, separation and processing order, and separation and processing level feature dimensions. Based on this separation and processing feature dimension information, the VOCs production attribute feature information set is arranged and integrated, that is, the VOCs production attribute feature information set is classified and arranged according to the separation and processing feature dimension information, and then integrated to obtain a VOCs production attribute feature dimension information set arranged according to feature dimensions.

[0027] A similarity algorithm is used to calculate the similarity between the VOCs production attribute feature dimension information set and the VOCs separation processing data space. Commonly used similarity algorithms include Jaccard similarity, cosine similarity, and Pearson similarity algorithms. The data in the VOCs separation processing data space is also arranged according to the separation processing feature dimension information. The similarity set between the production attribute feature dimension information of the VOCs to be processed and the separation processing strategies of each strategy parameter in the space is quickly calculated and determined. Based on the separation processing strategy similarity set, the separation processing parameters are optimized. First, the similarity of the separation processing strategies is sorted in descending order, placing the separation processing strategy data with higher similarity at the top, thus achieving sequential arrangement of similarity data. Then, a similarity ratio is empirically preset, for example, the top 10% of similar strategy data is selected and integrated to construct a separation processing strategy parameter memory, serving as the range for strategy parameter optimization. This enables specific applicability analysis of the separation processing strategy parameters, thereby improving parameter optimization efficiency.

[0028] The separation standards for volatile organic compounds (VOCs) can be extracted based on actual VOCs separation experience to obtain evaluation indicators for the separation effect. These evaluation indicators are assessment metrics strongly correlated with VOCs separation effectiveness, including treatment efficiency, recovery rate, and separation energy consumption. Based on these evaluation indicators, a separation effect fitness function is constructed. This fitness function is an evaluation function for VOCs separation effectiveness, obtained by fitting historical separation effect data from the VOCs separation treatment data space associated with the evaluation indicators. A higher fitness indicates a better separation effect. A particle swarm optimization algorithm can be used to perform a global search and optimization within the separation treatment strategy parameter memory using the fitness function. The search strategy parameters in the memory are evaluated and compared using the fitness function until a preset number of iterations is reached. This preset number of iterations can be set according to the optimization accuracy and speed requirements. The strategy parameter with the highest fitness is selected as the output VOCs separation treatment parameter. By optimizing intelligent strategy parameters, VOCs can be separated and treated efficiently, improving separation efficiency and accuracy, thereby ensuring the effectiveness of waste gas separation and treatment.

[0029] Step S7: Based on the VOCs separation and treatment parameters, perform separation treatment and waste gas separation decisions on the VOCs production component system.

[0030] Furthermore, the steps in this application also include: Hazard factor analysis is performed on the VOCs production attribute characteristic information set to generate VOCs hazard factor information; the VOCs production component system is monitored for separation treatment based on the VOCs separation treatment parameters to obtain separation treatment feedback parameter information; separation effect loss analysis is performed through the separation treatment feedback parameter information to obtain the separation effect loss coefficient; and the VOCs separation treatment parameters are optimized and adjusted based on the separation effect loss coefficient.

[0031] Specifically, based on the VOCs separation and treatment parameters, the VOCs production component system is separated and waste gas separation decisions are made to achieve efficient and environmentally friendly VOCs treatment and avoid secondary pollution to the environment. To ensure the effectiveness of VOCs separation and treatment, a hazard factor analysis is first performed on the VOCs production attribute characteristic information set. This can be achieved through multi-dimensional hazard level assessment using historical VOCs hazard data, including hazard type and hazard range. The assessed hazard levels are then weighted and fused to generate VOCs hazard factor information; the larger the factor, the greater the hazard level of the VOCs to be treated. The separation and treatment of the VOCs production component system is monitored based on the VOCs separation and treatment parameters. This involves real-time monitoring of the VOCs separation and treatment status using a sensor array to obtain corresponding separation and treatment feedback parameter information, including VOCs treatment efficiency, recovery content, and energy consumption parameters. Finally, a separation effect loss analysis is performed using the separation and treatment feedback parameter information, comparing it with a preset separation effect standard, and using the difference in separation effect as a separation effect loss coefficient. A larger coefficient indicates a greater gap in VOCs separation efficiency, requiring a greater degree of optimization in the separation process. Based on the separation efficiency loss coefficient, the VOCs separation parameters can be optimized and adjusted. This can be achieved through methods such as simulated annealing algorithms, for example, increasing the separation time parameter. Improving the timeliness of waste gas separation and treatment decisions enhances separation efficiency and decision-making accuracy, ensuring effective waste gas separation and treatment.

[0032] In summary, the integrated separation and decision-making method and system for volatile organic compounds provided in this application have the following technical advantages: This technical solution employs a method that extracts elements from VOCs production process information, separates volatile organic compounds (VOCs) based on the extracted VOCs production process elements, and generates a VOCs production component system. A VOCs attribute classifier is used to classify and label each VOCs information in the VOCs production component system, determining a set of VOCs production attribute feature information. Simultaneously, a VOCs separation and treatment strategy is set, including separation and treatment methods, separation and treatment order, and separation and treatment levels. Based on the VOCs separation and treatment strategy, a VOCs separation and treatment data space is constructed using a data-driven approach. This space is then used to perform parameter analysis on the VOCs production attribute feature information set, outputting VOCs separation and treatment parameters. Based on these parameters, separation and treatment decisions are made for the VOCs production component system. This achieves the technical effect of intelligent and efficient waste gas separation and treatment, improving separation and treatment efficiency and the accuracy of treatment decisions, thereby ensuring the effectiveness of waste gas separation and treatment.

[0033] Example 2 Based on the same inventive concept as the integrated separation decision-making method for volatile organic compounds in the foregoing embodiments, the present invention also provides an integrated separation decision-making system for volatile organic compounds, such as... Figure 3 As shown, the system includes: The process element extraction module 11 is used to acquire VOCs production process information, extract elements from the VOCs production process information, and obtain VOCs production process element information. The volatile organic compound separation module 12 is used to separate volatile organic compounds according to the VOCs production process element information to generate a VOCs production component system. The attribute classifier construction module 13 is used to construct a VOCs attribute classifier, which includes the production source, chemical structure, physical properties, and concentration of the generated VOCs. The system classification and labeling module 14 is used to classify and label each VOCs information in the VOCs production component system based on the VOCs attribute classifier, and determine the set of VOCs production attribute feature information; The separation and processing strategy setting module 15 is used to set the VOCs separation and processing strategy, which includes separation and processing method, separation and processing sequence, and separation and processing level. The separation processing parameter output module 16 is used to construct a VOCs separation processing data space in a data-driven manner according to the VOCs separation processing strategy, perform parameter analysis on the VOCs production attribute feature information set based on the VOCs separation processing data space, and output VOCs separation processing parameters. The waste gas separation and treatment decision module 17 is used to perform separation and treatment of the VOCs production component system and make waste gas separation decisions based on the VOCs separation and treatment parameters.

[0034] Furthermore, the system also includes: The element parameter determination unit is used to determine the production process nodes, node reactant parameters, node reaction mechanisms, and node environmental parameters based on the VOCs production process element information. A parameter modeling unit is generated to perform three-dimensional modeling of the production process nodes, node reactant parameters, node reaction mechanisms, and node environmental parameters using digital twin technology, thereby generating a VOCs production process twin model. The twin model segmentation unit is used to segment the VOCs production process twin model into N spatial units, and the N spatial units correspond one-to-one with the production process nodes. The reaction traversal simulation unit is used to perform spatial reaction traversal simulation based on the N spatial units, generate a set of VOCs production component information, and form the VOCs production component system based on the set of VOCs production component information.

[0035] Furthermore, the system also includes: A spatial reaction simulation unit is used to set time reaction nodes. The N spatial units sequentially perform spatial reaction simulations according to the time reaction nodes to obtain a set of production component information for the N spatial units at the time nodes. The component change curve acquisition unit is used to acquire N VOCs component change curves based on the VOCs component changes in the production component information set at the time node. The curve conversion analysis unit is used to perform conversion analysis based on the N VOCs component change curves and construct N spatial VOCs component conversion models. The production forecasting unit is used to perform production forecasting based on the N spatial VOCs component conversion models and to determine the set of VOCs production component information.

[0036] Furthermore, the system also includes: The rate of change analysis unit is used to perform rate analysis on the change curves of the N VOCs components to obtain the change rate curves of the N VOCs components. The transition node extraction unit is used to extract the transition node component change rate information based on the N VOCs component change rate curves. A continuity analysis unit is used to perform continuity analysis on the component change rate information at the turning point to obtain N VOCs component change rate coefficients. The coefficient weighted fitting unit is used to perform weighted fitting on the change rate coefficients of the N VOCs components according to the proportion of organic matter components, and to construct the spatial VOCs component conversion model.

[0037] Furthermore, the system also includes: The feature dimension setting unit is used to set the separation processing feature dimension information according to the VOCs separation processing strategy. The feature arrangement and integration unit is used to arrange and integrate the VOCs production attribute feature information set based on the separated processing feature dimension information to obtain the VOCs production attribute feature dimension information set. The similarity calculation unit is used to perform similarity calculation on the VOCs production attribute feature dimension information set and the VOCs separation processing data space using a similarity algorithm, and to determine the separation processing strategy similarity set; The separation processing parameter optimization unit is used to optimize the separation processing parameters based on the similarity set of the separation processing strategies and output the VOCs separation processing parameters.

[0038] Furthermore, the system also includes: The parameter ratio filtering unit is used to sort the similarity in descending order based on the similarity set of the separation processing strategy, and the ratio filtering constructs a separation processing strategy parameter memory library; The evaluation index extraction unit is used to extract indicators from the volatile organic compound separation standard to obtain organic compound separation effect evaluation indicators, which include processing efficiency, recovery rate and separation energy consumption. The fitness function construction unit is used to construct a separation effect fitness function based on the organic matter separation effect evaluation index. The global search optimization unit is used to perform a global search optimization in the separation processing strategy parameter memory using the separation effect fitness function until a preset number of iterations are reached, and then outputs the VOCs separation processing parameters.

[0039] Furthermore, the system also includes: The hazard factor analysis unit is used to perform hazard factor analysis on the set of VOCs production attribute characteristic information to generate VOCs hazard factor information. The separation and treatment monitoring unit is used to monitor the separation and treatment of the VOCs production component system based on the VOCs separation and treatment parameters, and to obtain separation and treatment feedback parameter information. The separation effect loss analysis unit is used to perform separation effect loss analysis based on the separation process feedback parameter information to obtain the separation effect loss coefficient. The parameter optimization and adjustment unit is used to optimize and adjust the VOCs separation and processing parameters based on the separation effect loss coefficient.

[0040] The foregoing Figure 1 The various variations and specific examples of the integrated separation decision method for volatile organic compounds in Example 1 are also applicable to the integrated separation decision system for volatile organic compounds in this embodiment. Through the foregoing detailed description of the integrated separation decision method for volatile organic compounds, those skilled in the art can clearly understand the implementation method of the integrated separation decision system for volatile organic compounds in this embodiment. Therefore, for the sake of brevity, it will not be described in detail here.

[0041] This specification and accompanying drawings are merely illustrative examples of this application, but the scope of protection of this application is not limited thereto. It should be noted that any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. In some cases, the actions or steps described in this application can be performed in a different order than that shown in the embodiments and still achieve the desired results. Furthermore, the processes depicted in the accompanying drawings do not necessarily require the specific order or sequential order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

Claims

1. An integrated separation decision method for volatile organic compounds, characterized in that, The method is applied to an integrated separation decision system for volatile organic compounds, and the method comprises: Obtaining VOCs production process information, performing element extraction on the VOCs production process information to obtain VOCs production process element information; According to the VOCs production process element information, generating a VOCs production component system; Building a VOCs attribute classifier, which includes production source, chemical structure, physical property, and generation concentration; Based on the VOCs attribute classifier, classifying and labeling each VOCs information in the VOCs production component system to determine a VOCs production attribute feature information set; Setting a VOCs separation processing strategy, which includes separation processing mode, separation processing sequence, and separation processing level; According to the VOCs separation processing strategy, building a VOCs separation processing data space through data-driven method, and based on the VOCs separation processing data space, performing parameter analysis on the VOCs production attribute feature information set to output VOCs separation processing parameters; Based on the VOCs separation processing parameters, performing separation processing and waste gas separation decision on the VOCs production component system.

2. The integrated separation decision method for volatile organic compounds as claimed in claim 1, wherein, The generation of the VOCs production component system comprises: According to the VOCs production process element information, determining production process nodes, node reactant parameters, node reaction mechanisms, and node environmental parameters; Using digital twin technology to perform three-dimensional modeling on the production process nodes, node reactant parameters, node reaction mechanisms, and node environmental parameters to generate a VOCs production process twin model; Dividing the VOCs production process twin model into N spatial units, which correspond one-to-one to the production process nodes; According to the N spatial units, performing spatial reaction traversal simulation to generate a VOCs production component information set, and based on the VOCs production component information set, forming the VOCs production component system.

3. The integrated separation decision method for volatile organic compounds as claimed in claim 2, wherein, The generation of the VOCs production component information set comprises: Setting a time reaction node, and the N spatial units perform spatial reaction simulation according to the time reaction node to obtain a time node production component information set of the N spatial units; According to the VOCs component change of the time node production component information set, obtaining N VOCs component change curves; Based on the N VOCs component change curves, performing conversion analysis to build N spatial VOCs component conversion models; Based on the N spatial VOCs component conversion models, performing production prediction to determine the VOCs production component information set.

4. The integrated separation decision method for volatile organic compounds as claimed in claim 3, wherein, The construction of the N spatial VOCs component conversion models comprises: Performing rate analysis on the N VOCs component change curves to obtain N VOCs component change rate curves; According to the turning node component change rate information extraction in the N VOCs component change rate curves; Performing continuity analysis on the turning node component change rate information to obtain N VOCs component change rate coefficients; The N VOCs component conversion model is constructed by weighting fitting the change rate coefficients of the N VOCs components according to the proportion of the organic matter components.

5. The integrated separation decision method for volatile organic compounds as claimed in claim 1, wherein, The output VOCs separation processing parameters include: According to the VOCs separation processing strategy, separation processing characteristic dimension information is set; Based on the separation processing characteristic dimension information, a VOCs production attribute characteristic dimension information set is arranged and integrated to obtain a VOCs production attribute characteristic dimension information set; The VOCs production attribute characteristic dimension information set and the VOCs separation processing data space are calculated by a similarity algorithm to determine a separation processing strategy similarity set; Based on the separation processing strategy similarity set, separation processing parameter optimization is performed to output the VOCs separation processing parameters.

6. The integrated separation decision method for volatile organic compounds as claimed in claim 5, wherein, The separation processing parameter optimization based on the separation processing strategy similarity set includes: Based on the separation processing strategy similarity set, a similarity descending order sorting is performed to proportionally screen and construct a separation processing strategy parameter memory bank; The volatile organic compound separation standard is used to extract indicators to obtain organic compound separation effect evaluation indicators, including processing efficiency, recovery rate, and separation energy consumption; Based on the organic compound separation effect evaluation indicators, a separation effect fitness function is constructed; The separation effect fitness function is used for global search optimization in the separation processing strategy parameter memory bank until a preset iteration number is reached, and the VOCs separation processing parameters are output.

7. The integrated separation decision method for volatile organic compounds as claimed in claim 1, wherein, The method further includes: The VOCs production attribute characteristic information set is analyzed for hazard factors to generate VOCs hazard factor information; Based on the VOCs separation processing parameters, the VOCs production component system is monitored for separation processing to obtain separation processing feedback parameter information; The separation effect loss coefficient is obtained by analyzing the separation effect loss based on the separation processing feedback parameter information; Based on the separation effect loss coefficient, the VOCs separation processing parameters are optimized and adjusted.

8. An integrated separation decision system for volatile organic compounds, characterized by, The system for implementing the integrated separation decision-making method for volatile organic compounds according to any one of claims 1-7, the system comprising: A process element extraction module for obtaining VOCs production process information and extracting elements from the VOCs production process information to obtain VOCs production process element information; A volatile organic compound separation module for separating volatile organic compounds according to the VOCs production process element information to generate a VOCs production component system; An attribute classifier construction module for constructing a VOCs attribute classifier, the VOCs attribute classifier including production source, chemical structure, physical properties, and generation concentration; A system classification marker module for classifying and marking each VOCs information in the VOCs production component system based on the VOCs attribute classifier to determine a VOCs production attribute characteristic information set; A separation processing strategy setting module for setting a VOCs separation processing strategy, the VOCs separation processing strategy including separation processing mode, separation processing order, and separation processing level; The separation processing parameter output module is configured to construct a VOCs separation processing data space by a data-driven manner according to the VOCs separation processing strategy, perform parameter analysis on the VOCs production attribute feature information set based on the VOCs separation processing data space, and output VOCs separation processing parameters. The waste gas separation processing decision module is configured to perform separation processing and waste gas separation decision on the VOCs production component system based on the VOCs separation processing parameters.

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