Waste gas filtering treatment system and method for intelligent shoemaking production line

Abstract

The invention relates to the technical field of waste gas treatment, in particular to an intelligent shoemaking production line waste gas filtering treatment system and method, and the system comprises a waste gas component analysis module, a pollution trend prediction module, an operation parameter setting module, a waste gas treatment execution module, a treatment effect monitoring module and an environmental protection compliance evaluation module. According to the invention, by monitoring the waste gas components of the intelligent shoemaking production line in real time and adjusting the treatment configuration, the environmental adaptability and the response capability are remarkably improved, and by accurately analyzing the concentration of waste gas pollutants and timely adjusting treatment parameters such as reaction time and temperature, the real-time change of the waste gas components is adapted; the method allows optimization of selection of a catalyst and a filter medium, ensures that a waste gas treatment system always operates in an optimal state, continuously meets environmental protection standards, reduces environmental risks, enhances compliance and transparency of a treatment process through real-time comparison with requirements of environmental protection laws and regulations, assists in timely correction of deviations, and reduces illegal risks.

Description

Technical Field

[0001] The present invention relates to the technical field of waste gas treatment, and in particular to a waste gas filtering and treatment system and method for an intelligent shoe production line. Background Art

[0002] The field of waste gas treatment technology focuses on reducing the pollution of the environment caused by harmful gases generated in industrial production, chemical manufacturing and emission processes through physical, chemical or biological methods, including gas absorption, adsorption, catalytic decomposition and other treatment methods. It is applied to smart shoe production, petrochemical, metallurgy, electronic manufacturing and other industries. By setting up filtering equipment, catalytic devices and related control systems, it can reduce the emission of pollutants such as volatile organic compounds (VOCs), particulate matter and harmful gases, thereby protecting air quality and achieving strict environmental emission standards.

[0003] Among them, the intelligent shoemaking production line waste gas filtration and treatment system is specially designed for waste gas treatment in shoemaking production lines. It combines intelligent control with multiple filtration and treatment technologies to remove harmful substances from the waste gas generated in the shoemaking process, including volatile organic compounds produced by adhesives and dyes, thereby reducing the impact of waste gas emissions on the environment. The system realizes real-time monitoring and effective filtration of waste gas through precise control of automated equipment to ensure the environmental compliance of production line operations.

[0004] Exhaust gas treatment methods in existing technologies lack sufficient flexibility and cannot adapt to the rapid and irregular changes that occur in production lines during operation. For example, traditional exhaust gas treatment sets fixed operating parameters, which in actual operation leads to a mismatch between the treatment effect and the actual exhaust gas composition, including in a production environment where the exhaust gas composition changes frequently. The system lacks an effective real-time monitoring mechanism, making it difficult to immediately evaluate and adjust the treatment process. This operating mode that lacks real-time feedback not only increases environmental compliance risks, but also leads to excessive or insufficient use of filter materials and catalysts, thereby reducing treatment efficiency and increasing operating costs. Existing technologies face obvious limitations in achieving environmental protection goals. Summary of the invention

[0005] The purpose of the present invention is to solve the shortcomings of the prior art and to propose an intelligent shoe production line exhaust gas filtration treatment system and method.

[0006] In order to achieve the above-mentioned purpose, the present invention adopts the following technical scheme: the exhaust gas filtration and treatment system of the intelligent shoe production line comprises: The exhaust gas composition analysis module deploys an air pump to the smart shoe production line to capture exhaust gas samples, measure the concentration of exhaust gas pollution components, conduct quantitative analysis on each component, and generate classification results of key exhaust gas pollution components; The pollution trend prediction module evaluates the change trend of waste gas pollutants based on the data obtained from the classification results of the key polluting components, predicts the waste gas pollution level of the intelligent shoe production line in the future time period, and generates the future pollution level prediction results; The operating parameter setting module adjusts the operating parameters of the exhaust gas treatment configuration of the intelligent shoe production line according to the future pollution level prediction result, and obtains the adjusted operating parameters; The exhaust gas treatment execution module uses the adjusted operating parameters to perform exhaust gas treatment on the intelligent shoe production line, selects an appropriate catalyst and filter medium, performs exhaust gas conversion and filtration operations, and obtains an exhaust gas treatment operation effect; The treatment effect monitoring module monitors the exhaust gas treatment operation effect, detects the composition and concentration of the treated exhaust gas in real time, and obtains real-time monitoring data; The environmental compliance assessment module evaluates the real-time monitoring data, reviews the waste gas treatment of the intelligent shoe production line, compares the operating procedures with the requirements of current environmental regulations, and forms a compliance waste gas treatment assessment result.

[0007] As a further scheme of the present invention, the classification results of key exhaust gas pollution components include component identification, concentration level, and pollution indicators; the future pollution level prediction results include predicted pollution level, expected change pattern, and impact time period; the adjusted operating parameters include set reaction time parameters and adjusted reaction temperature parameters; the exhaust gas treatment operation effect includes chemical conversion rate and physical filtration efficiency; the real-time monitoring data includes exhaust gas composition after monitoring and exhaust gas concentration after monitoring; the compliance exhaust gas treatment assessment results include regulatory compliance and environmental impact level.

[0008] As a further solution of the present invention, the exhaust gas composition analysis module includes: The vacuum pump submodule deploys the vacuum pump to the smart shoe production line, adjusts the vacuum rate and periodic interval operation to match the needs of differentiated production areas and time, captures exhaust gas samples, and obtains vacuum sample data; The component determination submodule calibrates the infrared sensor according to the gas extraction sample data, optimizes the sensitivity and response speed to the target chemical components, adjusts the infrared sensor parameters through continuous monitoring, records the concentration of the pollutant components, and generates component concentration results; The pollution analysis submodule uses the component concentration results to analyze and classify the hazard level and frequency of occurrence of pollutants, classify the data and mark key pollutants, and establish classification results for key exhaust gas pollution components.

[0009] As a further solution of the present invention, the pollution trend prediction module includes: The data classification submodule assigns data labels and classifies the pollutants based on the classification results of the key exhaust gas pollutants and the information of the exhaust gas pollutants, and refines the classification operation of the data set by applying statistical distribution to obtain the pollutant component data set; The trend analysis submodule extracts time series data from the pollution component data set, performs seasonal adjustments based on environmental factors, applies statistical methods to identify trends and anomalies, and constructs a trend change model; The prediction model submodule integrates prediction related parameters according to the trend change model, performs time series analysis, adjusts the prediction model parameters, simulates the changing trend of the exhaust gas pollution level in the future time period, and obtains the prediction result of the future pollution level.

[0010] As a further solution of the present invention, the operation parameter setting module includes: The prediction data analysis submodule analyzes the future pollution level prediction results, applies a linear regression algorithm, evaluates the expected changes and trends of differential pollutant concentrations, and adjusts the data collection frequency to match the predicted volatility to obtain pollution trend assessment results; The parameter adjustment submodule uses the pollution trend assessment results to adjust the exhaust gas treatment configuration in the production line, including setting the reaction time and adjusting the reaction temperature values ​​to match the changing pollution level, recording the adjustment value of each parameter, and generating an adjustment parameter record; The result verification submodule uses the adjustment parameter records to conduct field tests to verify the effectiveness of the new parameter settings, including simulating the exhaust gas treatment effects of various pollution levels in a controlled environment, verifying the settings of the operating parameters, and obtaining the adjusted operating parameters.

[0011] As a further solution of the present invention, the formula of the linear regression algorithm is as follows:

[0012] in, represents the predicted filtration efficiency, Represents the basic filtration efficiency, The weight coefficient representing the amount of organic solvent used, Represents the total amount of organic solvents used in the production line, The weight coefficient representing the efficiency of the filter medium, Represents the type and quality of filter media used in filtration. represents the adjustment factor of the ambient temperature, represents the average temperature of the location where the shoe factory is located. represents the adjustment factor of work intensity, Represents the working shift of the production line.

[0013] As a further solution of the present invention, the exhaust gas treatment execution module includes: The catalyst selection submodule analyzes the exhaust gas composition based on the adjusted operating parameters, selects the corresponding catalyst and matches the exhaust gas with differentiated chemical properties, adjusts the ratio and dosage of the catalyst, and builds a catalyst configuration list in combination with the exhaust gas flow rate and temperature parameter adjustment; The filter medium adjustment submodule determines the matching filter medium type and layout according to the catalyst configuration list, adjusts the layer and density of the filter medium, configures the physical properties of the filter medium, and generates an optimized filtration scheme; The pollution level matching submodule uses the optimized filtering scheme to adjust the operating parameters of the exhaust gas treatment configuration, including flow rate and reaction time, according to the real-time pollution monitoring data to match the current pollution level and obtain the exhaust gas treatment operation effect.

[0014] As a further solution of the present invention, the processing effect monitoring module includes: The real-time component analysis submodule recaptures the exhaust gas sample based on the exhaust gas treatment operation effect, uses an infrared sensor to detect the gas composition in real time, adjusts the sensitivity of the infrared sensor for each detected chemical substance, synchronizes the sampling frequency and sampling volume and matches the changes in the exhaust gas composition to obtain component analysis data; The concentration detection submodule uses the component analysis data to set the detection parameters of the spectrometer for each chemical component, performs continuous measurement to capture the dynamic changes of concentration, records the data at each time point, and obtains real-time concentration records; The data summary submodule organizes and analyzes the data based on the real-time concentration records, detects trends and abnormal values ​​in the data, compares the data with the original measurement data, and obtains real-time monitoring data.

[0015] As a further solution of the present invention, the environmental compliance assessment module includes: The real-time data review submodule performs format and integrity checks on the real-time monitoring data, verifies data consistency through data comparison and analysis, and generates monitoring data verification results; The regulation comparison submodule uses the monitoring data verification results to perform regulation comparison, check the consistency of the production line exhaust gas treatment steps with environmental protection regulations, and obtain the regulatory compliance analysis results by quantitatively analyzing the coverage of regulations and the matching degree of operation execution; The impact analysis submodule evaluates the environmental impact of waste gas treatment based on the regulatory compliance analysis results, analyzes the emission and treatment efficiency of waste gas pollutants during the treatment process, calculates the relationship between emissions and environmental carrying capacity through a model, and forms a compliance waste gas treatment assessment result.

[0016] An intelligent shoe production line waste gas filtration treatment method, the intelligent shoe production line waste gas filtration treatment method is performed based on the above-mentioned intelligent shoe production line waste gas filtration treatment system, comprising the following steps: S1: Deploy a vacuum pump to capture exhaust gas samples in the smart shoe production line, monitor the exhaust gas flow and pollutant concentration in real time, continuously monitor each pollutant component in the exhaust gas sample, record the data, and obtain the classification results of key exhaust gas pollutant components; S2: Based on the classification results of the key exhaust gas pollution components, the seasonal change trend of the exhaust gas pollutant concentration is analyzed by comparing the original data, and the trend prediction model is calibrated using the change data to predict the level of exhaust gas pollution of the production line in the future time period to obtain the prediction result of the future pollution level; S3: adjusting the parameters of the exhaust gas treatment configuration according to the future pollution level prediction result, optimizing the exhaust gas treatment cycle and temperature setting, and entering the adjusted parameters into a database according to the predicted exhaust gas composition change to obtain the adjusted operating parameters; S4: using the adjusted operating parameters, selecting a new catalyst and filter medium that matches the predicted exhaust gas pollution level, adjusting the exhaust gas treatment configuration, and continuously monitoring the exhaust gas treatment effect, recording the data of each exhaust gas treatment, and obtaining the exhaust gas treatment operation effect; S5: monitor the effect of the waste gas treatment operation in real time, use analytical instruments to determine the composition and concentration of the treated waste gas, compare the monitoring data with environmental protection regulations and standards, evaluate the compliance of the waste gas treatment of the smart shoe production line, and generate compliance waste gas treatment evaluation results.

[0017] Compared with the prior art, the advantages and positive effects of the present invention are: In the present invention, by real-time monitoring of exhaust gas composition and adjusting the exhaust gas treatment configuration, the environmental adaptability and responsiveness of the intelligent shoemaking production line are effectively improved. By carefully analyzing the concentrations of various pollutants in the exhaust gas, the treatment parameters, such as reaction time and temperature, can be adjusted in time to adapt to the real-time changes in the exhaust gas composition during the production process, allowing instant optimization of the selection of catalysts and filter media to ensure that the exhaust gas treatment always operates in the best state. The intelligent shoemaking production line can continue to meet strict environmental protection standards and reduce environmental risks caused by improper exhaust gas treatment. By real-time monitoring of the treatment effect and comparing it with environmental protection regulations, the compliance and transparency of the exhaust gas treatment process are enhanced, which helps to timely discover and correct any deviations, thereby reducing potential environmental violations. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 is a system flow chart of the present invention; Figure 2 It is a schematic diagram of the system framework of the present invention; Figure 3This is a flow chart of the exhaust gas composition analysis module in the present invention; Figure 4 This is a flow chart of the pollution trend prediction module in the present invention; Figure 5 It is a flow chart of the operating parameter setting module in the present invention; Figure 6 It is a flow chart of the exhaust gas treatment execution module in the present invention; Figure 7 This is a flow chart of the processing effect monitoring module in the present invention; Figure 8 It is a flow chart of the environmental compliance assessment module in the present invention; Fig. 9 It is a schematic diagram of the method steps of the present invention. DETAILED DESCRIPTION

[0019] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0020] In the description of the present invention, it should be understood that the terms "length", "width", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside" and the like indicate positions or positional relationships based on the positions or positional relationships shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as limiting the present invention. In addition, in the description of the present invention, "multiple" means two or more, unless otherwise clearly and specifically defined.

[0021] Embodiment 1 See also Figure 1 to Figure 2 The present invention provides a technical solution: the exhaust gas filtration and treatment system of the intelligent shoe production line includes: The exhaust gas composition analysis module deploys an air pump to the smart shoe production line to capture exhaust gas samples, uses sensor technology to measure the concentration of exhaust gas pollution components, conducts quantitative analysis on each component, and generates classification results of key exhaust gas pollution components; The pollution trend prediction module evaluates the changing trend of waste gas pollutants based on the data obtained from the classification results of key pollutant components, analyzes the changes through statistical methods, predicts the waste gas pollution level of the smart shoe production line in the future time period, and generates the prediction results of future pollution levels; The operating parameter setting module adjusts the operating parameters of the exhaust gas treatment configuration of the intelligent shoe production line according to the future pollution level prediction results, including setting the reaction time and adjusting the reaction temperature, responding to the predicted exhaust gas pollution changes, and obtaining the adjusted operating parameters; The exhaust gas treatment execution module uses the adjusted operating parameters to treat the exhaust gas on the intelligent shoe production line, selects the appropriate catalyst and adjusts the filter medium, matches the predicted pollution level, performs exhaust gas purification and filtration operations, and obtains the exhaust gas treatment operation effect; The treatment effect monitoring module monitors the effect of waste gas treatment operation, detects the composition and concentration of the treated waste gas in real time, and obtains real-time monitoring data; The environmental compliance assessment module evaluates real-time monitoring data, reviews the waste gas treatment of the smart shoe production line, compares the operating procedures with the requirements of current environmental regulations, analyzes the impact of the treatment process on the environment, and forms a compliance waste gas treatment assessment result.

[0022] The classification results of key exhaust gas pollution components include component identification, concentration level, and pollution indicators. The future pollution level prediction results include predicted pollution level, expected change pattern, and impact time period. The adjusted operating parameters include set reaction time parameters and adjusted reaction temperature parameters. The exhaust gas treatment operation effects include chemical conversion rate and physical filtration efficiency. The real-time monitoring data include exhaust gas composition after monitoring and exhaust gas concentration after monitoring. The compliance exhaust gas treatment assessment results include regulatory compliance and environmental impact level.

[0023] Specifically, if Figure 2 , 3 As shown, the exhaust gas composition analysis module includes: The vacuum pump submodule deploys the vacuum pump to the smart shoe production line, and adjusts the vacuum rate and periodic interval operation to match the needs of differentiated production areas and time, captures exhaust gas samples, and obtains the execution process of vacuum sample data as follows; Vacuum pumps are deployed in the intelligent shoemaking production line. By adjusting the vacuum rate and periodic interval, timely capture of waste gas samples in each production area is achieved. The vacuum rate is precisely adjusted according to the differentiated needs of differentiated production periods. The vacuum pump submodule first determines the type of waste gas and its concentration distribution in each area, and adjusts the vacuum cycle through real-time data feedback to ensure that the operating efficiency of the vacuum pump is maximized. The vacuum pump in each area automatically adjusts its operating parameters, such as the vacuum rate and time interval, based on real-time monitoring data to adapt to the cyclically changing working environment on the production line, thereby effectively improving the accuracy and representativeness of the waste gas sample data. Finally, the vacuum sample data is obtained through this method.

[0024] The component determination submodule calibrates the infrared sensor based on the gas extraction sample data, optimizes the sensitivity and response speed to the target chemical components, adjusts the infrared sensor parameters through continuous monitoring, records the concentration of the pollutant components, and generates the component concentration results. The execution process is as follows; Optimize the sensitivity and response speed of the target chemical composition according to the formula:

[0025] Calculate the percentage increase in sensitivity, where Represents the percentage of sensitivity increase, Represents the detected concentration of the target chemical component, represents the baseline concentration; In a practical case, if the concentration of the target chemical component is 50 units, while the baseline concentration The sensitivity is 40 units, and the percentage of sensitivity increase is calculated according to the above formula. for: ; This represents a 25% improvement in the infrared sensor's sensitivity relative to the baseline state.

[0026] The pollution analysis submodule uses the component concentration results to analyze and classify the hazard level and frequency of pollutants, classify the data and mark key pollutants, and establish the execution process of the classification results of key exhaust gas pollution components as follows; The component concentration results are used to analyze and classify the hazard level and frequency of occurrence of pollutants. During the implementation process, data on each chemical component is collected, and the average concentration and coefficient of variation of each component are calculated using statistical methods. The hazard level of pollutants is evaluated, and they are ranked based on their concentration and hazard level. Key pollutants are classified and their hazard level is marked to ensure that various types of pollutants are effectively managed according to their hazard level. The classification results of key exhaust gas pollution components are established to provide data support for the formulation of further pollution control and governance strategies.

[0027] Specifically, if Figure 2 , 4 As shown, the pollution trend prediction module includes: The data classification submodule assigns data labels and classifies the pollutants based on the classification results of key exhaust gas pollutants and the information of exhaust gas pollutants. It applies statistical distribution to refine the classification operation of the data set and obtains the execution process of the pollutant component data set as follows; Based on the classification results of key exhaust gas pollution components, operations are performed by analyzing the characteristics of exhaust gas pollutants, assigning labels to the pollution components, and further refining and classifying the data. The data set construction process includes the identification and recording of various types of pollutants. Statistical methods such as cluster analysis are applied to the study of the relationship and similarity between differentiated pollution components. The classification operation of the refined data set involves the distribution statistics and pattern recognition of exhaust gas components. This process ensures that the data set can reflect the actual situation and characteristics of the pollution components, so as to facilitate subsequent data processing and analysis. The final pollution component data set is used for further analysis and research, providing a scientific basis for pollution control and governance.

[0028] The trend analysis submodule extracts time series data from the pollution component dataset, performs seasonal adjustments based on environmental factors, and applies statistical methods to identify trends and outliers. The execution process of building a trend change model is as follows; Apply statistical methods to identify trends and outliers, according to the formula:

[0029] Calculate the trend smoothing value, where Represents the current trend smoothing value, represents the smoothing coefficient, Represents the actual monitoring value at the current time point, and Represent the trend and seasonal components of the previous time point respectively; Referring to a specific example, if at time Monitoring value is 200 units, the trend at the previous point 180 units, seasonal components Set the smoothing coefficient to 20 units is 0.3, and the trend smoothing value is calculated according to the formula for: ; This calculation process shows that through the weighted average of historical data, the trend analysis model can effectively smooth out the fluctuations caused by environmental factors and provide accurate basic data for building a trend change model.

[0030] The prediction model submodule integrates prediction related parameters based on the trend change model, performs time series analysis, adjusts the prediction model parameters, simulates the changing trend of exhaust gas pollution level in the future time period, and obtains the execution process of the future pollution level prediction result as follows; By utilizing the established trend change model, integrating key prediction-related parameters such as historical trend data, seasonal adjustment factors and external environmental influencing factors, performing time series analysis, and adjusting various parameters of the prediction model, we can ensure the accuracy and reliability of the prediction. The optimization and adjustment of parameters are based on the results of historical data analysis. The method of minimizing prediction errors is used to select the optimal parameters and simulate the changing trend of exhaust gas pollution levels in future time periods. The prediction results can provide decision-making support for environmental management and ensure the scientificity and foresight of future pollution control strategies. The final prediction results of future pollution levels provide a basis for policy formulation and resource allocation.

[0031] Specifically, if Figure 2 , 5 As shown, the operation parameter setting module includes: The prediction data analysis submodule analyzes the future pollution level prediction results, applies the linear regression algorithm, evaluates the expected changes and trends of the concentrations of differentiated pollutants, and adjusts the data collection frequency to match the predicted volatility. The execution process of obtaining the pollution trend assessment results is as follows; The formula for the linear regression algorithm is as follows:

[0032] in, represents the predicted filtration efficiency, Represents the basic filtration efficiency, The weight coefficient representing the amount of organic solvent used, Represents the total amount of organic solvents used in the production line, The weight coefficient representing the efficiency of the filter medium, Represents the type and quality of filter media used in filtration. represents the adjustment factor of the ambient temperature, represents the average temperature of the location where the shoe factory is located. represents the adjustment factor of work intensity, Represents the working shift of the production line.

[0033] Detailed explanation of the formula and the process of formula calculation and derivation: This formula is used to predict the effect of exhaust gas filtration in a shoe production line, which includes consideration of various environmental and operating parameters; (Basic Filtration Efficiency): This is a constant term that represents the baseline for pollution treatment under standard operating conditions. This value is obtained by conducting a series of filtration experiments under standard conditions. The difference in pollutant content between untreated exhaust gas and filtered exhaust gas is measured in the experiment. ; (Weight coefficient of organic solvent usage): The relationship between organic solvent usage and total pollutants is analyzed through historical data, and regression analysis is used to determine , which indicates that for every 1 unit increase in the use of organic solvents, the concentration of pollutants in the exhaust gas increases by 0.05 units; (Total amount of organic solvents): This is directly measured by the real-time monitoring system of the production line, in tons / day. The data measured on a certain day is set as ton; (Weight coefficient of filter medium efficiency): obtained through standardized processing based on the filter efficiency performance of different types of filter materials in the experiment ; (Filter material type and quality): According to the type and quality of the filter material used, it is obtained from the technical data sheet provided by the supplier and after quantitative standardization. The value of is 3, which represents medium quality; (Adjustment coefficient of ambient temperature): Determined through experiments based on the effect of ambient temperature on the volatilization rate of VOCs ; (Average temperature): Provided in real time by the weather station in the factory area, the average temperature of the day is set to ; (Adjustment coefficient of work intensity): Based on the production data of differentiated work shifts, determine ; (Work shift): Obtain the number of work shifts for the day through the production scheduling system. ; Substitute the specific values ​​into the formula to calculate :

[0034]

[0035]

[0036]

[0037] The results show that under the given conditions, the expected filtration efficiency is 22.958, which means that the exhaust gas filtration system of the production line can effectively reduce about 23% of pollutants, taking into account the amount of organic solvent used, the type and quality of filter materials, the ambient temperature and the intensity of work. This value has important guiding significance for further optimizing the filtration system and adjusting production operation parameters.

[0038] The parameter adjustment submodule uses the pollution trend assessment results to adjust the exhaust gas treatment configuration in the production line, including setting the reaction time and adjusting the reaction temperature value to match the changing pollution level, recording the adjustment value of each parameter, and generating the execution process of the adjustment parameter record as follows; According to the results of the pollution trend assessment, the changes in the exhaust gas composition on the production line are analyzed in detail. Based on the assessment results, the key operating parameters in the exhaust gas treatment device are accurately adjusted. First, the increase or decrease ratio of pollutants is calculated to determine the increase or decrease of the reaction time. For example, if the assessment results show that the pollutants increase by 10%, the reaction time is increased by 5% accordingly. The reaction temperature is adjusted according to the volatility and reactivity of the pollutants to ensure the completeness and efficiency of the chemical reaction. For example, for increased organic volatile pollutants, the reaction temperature is increased to speed up the processing speed. After each adjustment, the set reaction time and temperature are automatically recorded, and the specific adjustment value of each parameter is saved to generate an adjustment parameter record. The record will include the initial value of the parameter, the adjustment value and its corresponding pollutant concentration for subsequent analysis and verification. The adjustment value of each parameter is recorded.

[0039] The result verification submodule uses the adjusted parameter records to conduct field tests to verify the effectiveness of the new parameter settings, including simulating the exhaust gas treatment effects of various pollution levels in a controlled environment, verifying the settings of the operating parameters, and obtaining the execution flow of the adjusted operating parameters as follows; The effectiveness of the adjustment is verified through actual operation tests. Field tests include simulating differentiated pollution levels under controlled environmental conditions and monitoring the performance of waste gas treatment under various conditions. For example, a simulated environment is set up in the laboratory to simulate high and low pollution scenarios, and the treatment efficiency and by-product yield of the waste gas treatment device under differentiated parameter settings are recorded. Through data, the suitability and effect of various operating parameters such as reaction time and temperature adjustments are analyzed to ensure the optimization of parameters. During the verification process, each test will record the operating parameter settings, test conditions, and treatment effects in detail, so as to obtain a set of verified and reliable operating parameters to guide the daily operation of the production line and verify the setting of operating parameters.

[0040] Specifically, if Figure 2 , 6 As shown, the exhaust gas treatment execution module includes: The catalyst selection submodule analyzes the exhaust gas composition based on the adjusted operating parameters, selects the corresponding catalyst and matches the exhaust gas with differentiated chemical properties, adjusts the catalyst ratio and dosage, and combines the exhaust gas flow rate and temperature parameter adjustments to build the catalyst configuration list. The execution process is as follows; Based on the adjusted operating parameters, the exhaust gas composition is accurately analyzed and the most suitable catalyst is selected to match the chemical properties of the exhaust gas. This process involves the identification of the exhaust gas composition and the comparison of the catalyst characteristics. The catalyst ratio and dosage are adjusted according to the exhaust gas flow rate and temperature parameters. Such operations ensure that the catalyst can function under optimal conditions and increase the treatment efficiency. Constructing a catalyst configuration list is a key step in the entire process. The list records in detail the use conditions and ratios of various catalysts, as well as the expected reaction effects, providing an important basis for the optimization of the entire exhaust gas treatment system.

[0041] The filter medium adjustment submodule determines the matching filter medium type and layout according to the catalyst configuration list, adjusts the layer and density of the filter medium, configures the physical properties of the filter medium, and generates the execution process of the optimized filtration plan as follows; Adjust the level and density of the filter media according to the formula:

[0042] Calculate the overall density of the filter media, where represents the total density of the filter medium, represents the density of a single-layer medium, represents the filtration volume, represents the filtration area; Assume the density of the single-layer medium is The filtration volume is The filter area is , the total density of the filter medium can be calculated as follows: ; The results show that by adjusting the density and layering of the filter media, the overall density of the filtration system can be effectively controlled, thereby optimizing the filtration effect.

[0043] The pollution level matching submodule uses the optimized filtering scheme to adjust the operating parameters of the exhaust gas treatment configuration, including flow rate and reaction time, according to the real-time pollution monitoring data to match the current pollution level. The execution process of obtaining the exhaust gas treatment operation effect is as follows; By optimizing the filtration solution, the operating parameters of the exhaust gas treatment configuration are adjusted according to the real-time pollution monitoring data, including real-time monitoring of pollution levels and key operations of adjusting exhaust gas flow rate and reaction time. In this way, it can be ensured that the exhaust gas treatment system is perfectly matched to the current pollution level, thereby improving the treatment efficiency and effect. The effect of the exhaust gas treatment operation is obtained through real-time data analysis. The implementation strategy is to maximize the exhaust gas treatment efficiency and ensure environmental safety. The final exhaust gas treatment operation effect reflects the system's responsiveness and treatment capabilities to the actual pollution conditions.

[0044] Specifically, if Figure 2 ,7 As shown, the processing effect monitoring module includes: The real-time component analysis submodule recaptures the exhaust gas sample based on the exhaust gas treatment operation effect, uses infrared sensors to detect the gas composition in real time, adjusts the sensitivity of the infrared sensor for each detected chemical substance, synchronizes the sampling frequency and sampling volume and matches the changes in the exhaust gas composition, and obtains the component analysis data. The execution process is as follows; Adjust the sensitivity of the infrared sensor for each chemical detected, according to the formula:

[0045] Calculate the sensitivity adjustment value, where Represents the sensitivity adjustment value, represents the maximum detection intensity, represents the minimum detection intensity, represents the reference intensity; As a specific example, if the maximum detection intensity The minimum detection intensity is 120 units. The reference intensity is 20 units. is 100 units, and the sensitivity adjustment value is calculated according to the formula for:

[0046] This means that the sensitivity of the infrared sensor needs to be adjusted to 100% of the ratio of the difference between the maximum and minimum detected intensity to the reference intensity to match the changes in the exhaust gas composition.

[0047] The concentration detection submodule uses the component analysis data to set the detection parameters of the spectrometer for each chemical component, conducts continuous measurements to capture the dynamic changes in concentration, and records the data at each time point. The execution process for obtaining real-time concentration records is as follows; Use the component analysis data to set the detection parameters of the spectrometer, and continuously measure each chemical component, including adjusting the sensitivity of the spectrometer and setting the detection range, as well as capturing real-time operations of dynamic changes in concentration. By setting specific detection parameters, the spectrometer can accurately record the concentration of chemical components at each time point, thereby generating real-time concentration records. The records will be used for further data analysis and environmental monitoring to ensure the accuracy and real-time nature of the data, providing key data support for environmental protection and monitoring.

[0048] The data aggregation submodule organizes and analyzes the data based on the real-time concentration records, detects trends and outliers in the data, compares with the original measurement data, and obtains the execution process of real-time monitoring data as follows; Based on the real-time concentration records, data is collated and analyzed to detect trends and outliers in the data, including time series analysis of continuous measurement data and comparison with the original measurement data. In this way, environmental risks or pollution events can be quickly identified. The acquisition of real-time monitoring data is the core of the entire exhaust gas treatment system. It not only provides feedback on operational efficiency, but also provides a data basis for environmental management decisions. The real-time monitoring data finally obtained is a key indicator for evaluating the performance of the entire system.

[0049] Specifically, if Figure 2 , 8 As shown, the environmental compliance assessment module includes: The real-time data review submodule performs format and integrity checks on the real-time monitoring data, verifies data consistency through data comparison and analysis, and generates the monitoring data verification results. The execution process is as follows; Format and integrity checks are performed based on real-time monitoring data. This process covers the initial review of the data, such as format consistency and integrity verification, and verifies data consistency through data comparison and analysis. This refinement process ensures the accuracy and availability of the data, providing a reliable basis for subsequent analysis and decision-making. The generation of monitoring data verification results is a summary of the entire data review work. The results reflect the rigor and efficiency of the data processing process, and provide key guarantees for ensuring the quality and security of information.

[0050] The regulation comparison submodule uses the monitoring data verification results to compare regulations and check the consistency between the production line exhaust gas treatment steps and environmental protection regulations. By quantitatively analyzing the matching degree between the regulation coverage and the operation execution, the execution process of obtaining the regulatory compliance analysis results is as follows; Compare regulations and check the consistency of waste gas treatment steps with environmental regulations according to the formula:

[0051] Calculate regulatory compliance, where Represents regulatory compliance, Represents the operation execution value, Represents the regulatory requirement value, Represents the total number of items checked; If there are 5 regulations that need to be checked, the operation execution values ​​are 100, 105, 95, 100, 90, and the regulatory requirement values ​​are 100, 100, 100, 100, 100, and the regulatory compliance is calculated according to the formula for:

[0052]

[0053]

[0054] This means that during the inspection, the average value of the sum of squared deviations of the consistency between the exhaust gas treatment steps and environmental regulations was 30. This result shows that the overall compliance with regulations needs to be further improved to meet environmental protection requirements.

[0055] The impact analysis submodule evaluates the environmental impact of waste gas treatment based on the regulatory compliance analysis results, analyzes the emission and treatment efficiency of waste gas pollutants during the treatment process, calculates the relationship between emissions and environmental carrying capacity through the model, and forms the compliance waste gas treatment evaluation results. The execution process is as follows; The environmental impact of waste gas treatment is evaluated using the results of regulatory compliance analysis. The process includes a detailed analysis of the emission of waste gas pollutants and the treatment efficiency. The relationship between emissions and environmental carrying capacity is calculated through models, including the aggregation and model analysis of emission data of various pollutants to determine their potential impact on the environment. The formation of compliance waste gas treatment assessment results is a comprehensive judgment on the efficiency and effectiveness of the entire waste gas treatment system. The results are of great reference value for environmental management and policy making.

[0056] See also Fig. 9 , a method for filtering and treating waste gas from an intelligent shoemaking production line, the method for filtering and treating waste gas from an intelligent shoemaking production line is performed based on the above-mentioned waste gas filtering and treating system of the intelligent shoemaking production line, and comprises the following steps: S1: Deploy a vacuum pump to capture exhaust gas samples in the smart shoe production line, monitor the exhaust gas flow and pollutant concentration in real time, continuously monitor each pollutant component in the exhaust gas sample, record the data, and obtain the classification results of key exhaust gas pollutant components; S2: Based on the classification results of key exhaust gas pollution components, the seasonal change trend of exhaust gas pollutant concentration is analyzed by comparing the original data, and the trend prediction model is calibrated using the change data to predict the level of exhaust gas pollution of the production line in the future time period to obtain the prediction results of future pollution levels; S3: According to the prediction results of future pollution levels, the parameters of the exhaust gas treatment configuration are adjusted to optimize the exhaust gas treatment cycle and temperature settings. According to the predicted changes in exhaust gas composition, the adjusted parameters are entered into the database to obtain the adjusted operating parameters; S4: Use the adjusted operating parameters to select new catalysts and filter media that match the predicted exhaust gas pollution level, adjust the exhaust gas treatment configuration, and continuously monitor the exhaust gas treatment effect, record the data of each exhaust gas treatment, and obtain the exhaust gas treatment operation effect; S5: Monitor the effect of waste gas treatment operation in real time, use analytical instruments to determine the composition and concentration of the treated waste gas, compare the monitoring data with environmental protection regulations and standards, evaluate the compliance of waste gas treatment of the smart shoe production line, and generate compliance waste gas treatment evaluation results.

[0057] The above are only preferred embodiments of the present invention and are not intended to limit the present invention in other forms. Any technician familiar with the profession may use the technical contents disclosed above to change or modify them into equivalent embodiments with equivalent changes and apply them to other fields. However, any simple modification, equivalent change and modification made to the above embodiments based on the technical essence of the present invention without departing from the technical solution of the present invention still falls within the protection scope of the technical solution of the present invention.

Claims

1. Intelligent shoe production line exhaust gas filtration treatment system, characterized in that: The system comprises: The exhaust gas composition analysis module deploys an air pump to the smart shoe production line to capture exhaust gas samples, measure the concentration of exhaust gas pollution components, conduct quantitative analysis on each component, and generate classification results of key exhaust gas pollution components; The pollution trend prediction module evaluates the change trend of waste gas pollutants based on the data obtained from the classification results of the key polluting components, predicts the waste gas pollution level of the intelligent shoe production line in the future time period, and generates the future pollution level prediction results; The operating parameter setting module adjusts the operating parameters of the exhaust gas treatment configuration of the intelligent shoe production line according to the future pollution level prediction result, and obtains the adjusted operating parameters; The exhaust gas treatment execution module uses the adjusted operating parameters to perform exhaust gas treatment on the intelligent shoe production line, selects an appropriate catalyst and filter medium, performs exhaust gas conversion and filtration operations, and obtains an exhaust gas treatment operation effect; The treatment effect monitoring module monitors the exhaust gas treatment operation effect, detects the composition and concentration of the treated exhaust gas in real time, and obtains real-time monitoring data; The environmental compliance assessment module evaluates the real-time monitoring data, reviews the waste gas treatment of the intelligent shoe production line, compares the operating procedures with the requirements of current environmental regulations, and forms a compliance waste gas treatment assessment result.

2. The intelligent shoe production line exhaust gas filtration treatment system according to claim 1 is characterized by: The classification results of key exhaust gas pollution components include component identification, concentration level, and pollution indicators. The future pollution level prediction results include predicted pollution level, expected change pattern, and impact time period. The adjusted operating parameters include set reaction time parameters and adjusted reaction temperature parameters. The exhaust gas treatment operation effect includes chemical conversion rate and physical filtration efficiency. The real-time monitoring data includes exhaust gas composition after monitoring and exhaust gas concentration after monitoring. The compliance exhaust gas treatment assessment results include regulatory compliance and environmental impact level.

3. The intelligent shoe production line exhaust gas filtration treatment system according to claim 1 is characterized by: The exhaust gas composition analysis module comprises: The vacuum pump submodule deploys the vacuum pump to the smart shoe production line, adjusts the vacuum rate and periodic interval operation to match the needs of differentiated production areas and time, captures exhaust gas samples, and obtains vacuum sample data; The component determination submodule calibrates the infrared sensor according to the gas extraction sample data, optimizes the sensitivity and response speed to the target chemical components, adjusts the infrared sensor parameters through continuous monitoring, records the concentration of the pollutant components, and generates component concentration results; The pollution analysis submodule uses the component concentration results to analyze and classify the hazard level and frequency of occurrence of pollutants, classify the data and mark key pollutants, and establish classification results for key exhaust gas pollution components.

4. The intelligent shoe production line exhaust gas filtration treatment system according to claim 1 is characterized by: The pollution trend prediction module includes: The data classification submodule assigns data labels and classifies the pollutants based on the classification results of the key exhaust gas pollutants and the information of the exhaust gas pollutants, and refines the classification operation of the data set by applying statistical distribution to obtain the pollutant component data set; The trend analysis submodule extracts time series data from the pollution component data set, performs seasonal adjustments based on environmental factors, applies statistical methods to identify trends and anomalies, and constructs a trend change model; The prediction model submodule integrates prediction related parameters according to the trend change model, performs time series analysis, adjusts the prediction model parameters, simulates the changing trend of the exhaust gas pollution level in the future time period, and obtains the prediction result of the future pollution level.

5. The intelligent shoe production line exhaust gas filtration treatment system according to claim 1 is characterized by: The operation parameter setting module includes: The prediction data analysis submodule analyzes the future pollution level prediction results, applies a linear regression algorithm, evaluates the expected changes and trends of differential pollutant concentrations, and adjusts the data collection frequency to match the predicted volatility to obtain pollution trend assessment results; The parameter adjustment submodule uses the pollution trend assessment results to adjust the exhaust gas treatment configuration in the production line, including setting the reaction time and adjusting the reaction temperature value to match the changing pollution level, recording the adjustment value of each parameter, and generating an adjustment parameter record; The result verification submodule uses the adjustment parameter records to conduct field tests to verify the effectiveness of the new parameter settings, including simulating the exhaust gas treatment effects of various pollution levels in a controlled environment, verifying the settings of the operating parameters, and obtaining the adjusted operating parameters.

6. The intelligent shoe production line exhaust gas filtration treatment system according to claim 5 is characterized by: The formula for the linear regression algorithm is as follows: in, represents the predicted filtration efficiency, Represents the basic filtration efficiency, The weight coefficient representing the amount of organic solvent used, Represents the total amount of organic solvents used in the production line, The weight coefficient representing the efficiency of the filter medium, Represents the type and quality of filter media used in filtration. represents the adjustment factor of the ambient temperature, represents the average temperature of the location where the shoe factory is located. represents the adjustment factor of work intensity, Represents the working shift of the production line.

7. The intelligent shoe production line exhaust gas filtration treatment system according to claim 1 is characterized by: The exhaust gas treatment execution module comprises: The catalyst selection submodule analyzes the exhaust gas composition based on the adjusted operating parameters, selects the corresponding catalyst and matches the exhaust gas with differentiated chemical properties, adjusts the ratio and dosage of the catalyst, and builds a catalyst configuration list in combination with the exhaust gas flow rate and temperature parameter adjustment; The filter medium adjustment submodule determines the matching filter medium type and layout according to the catalyst configuration list, adjusts the layer and density of the filter medium, configures the physical properties of the filter medium, and generates an optimized filtration scheme; The pollution level matching submodule uses the optimized filtering scheme to adjust the operating parameters of the exhaust gas treatment configuration, including flow rate and reaction time, according to the real-time pollution monitoring data to match the current pollution level and obtain the exhaust gas treatment operation effect.

8. The intelligent shoe production line exhaust gas filtration treatment system according to claim 1 is characterized by: The processing effect monitoring module includes: The real-time component analysis submodule recaptures the exhaust gas sample based on the exhaust gas treatment operation effect, uses an infrared sensor to detect the gas composition in real time, adjusts the sensitivity of the infrared sensor for each detected chemical substance, synchronizes the sampling frequency and sampling volume and matches the changes in the exhaust gas composition to obtain component analysis data; The concentration detection submodule uses the component analysis data to set the detection parameters of the spectrometer for each chemical component, performs continuous measurement to capture the dynamic changes of concentration, records the data at each time point, and obtains real-time concentration records; The data summary submodule organizes and analyzes the data based on the real-time concentration records, detects trends and abnormal values ​​in the data, compares the data with the original measurement data, and obtains real-time monitoring data.

9. The intelligent shoe production line exhaust gas filtration treatment system according to claim 1 is characterized by: The environmental compliance assessment module includes: The real-time data review submodule performs format and integrity checks on the real-time monitoring data, verifies data consistency through data comparison and analysis, and generates monitoring data verification results; The regulation comparison submodule uses the monitoring data verification results to perform regulation comparison, check the consistency of the production line exhaust gas treatment steps with environmental protection regulations, and obtain the regulatory compliance analysis results by quantitatively analyzing the coverage of regulations and the matching degree of operation execution; The impact analysis submodule evaluates the environmental impact of waste gas treatment based on the regulatory compliance analysis results, analyzes the emission and treatment efficiency of waste gas pollutants during the treatment process, calculates the relationship between emissions and environmental carrying capacity through a model, and forms a compliance waste gas treatment assessment result.

10. Intelligent shoe production line waste gas filtration treatment method, characterized in that: According to any one of claims 1 to 9, the intelligent shoe production line exhaust gas filtration treatment system is implemented, comprising the following steps: Deploy a vacuum pump to capture exhaust gas samples in the smart shoe production line, monitor the exhaust gas flow and pollutant concentration in real time, continuously monitor each pollutant component in the exhaust gas sample, record the data, and obtain the classification results of key exhaust gas pollutant components; According to the classification results of the key exhaust gas pollution components, the seasonal change trend of the exhaust gas pollutant concentration is analyzed by comparing the original data, and the trend prediction model is calibrated using the change data to predict the level of exhaust gas pollution of the production line in the future time period, and the future pollution level prediction results are obtained; According to the predicted results of the future pollution level, the parameters of the exhaust gas treatment configuration are adjusted to optimize the exhaust gas treatment cycle and temperature settings, and according to the predicted changes in the exhaust gas composition, the adjusted parameters are entered into a database to obtain the adjusted operating parameters; Using the adjusted operating parameters, selecting new catalysts and filter media that match the predicted exhaust gas pollution level, adjusting the exhaust gas treatment configuration, and continuously monitoring the exhaust gas treatment effect, recording the data of each exhaust gas treatment, and obtaining the exhaust gas treatment operation effect; The effect of the waste gas treatment operation is monitored in real time, the composition and concentration of the treated waste gas are determined using analytical instruments, the monitoring data are compared with environmental protection regulations and standards, the compliance of the waste gas treatment of the smart shoe production line is evaluated, and compliance waste gas treatment evaluation results are generated.

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