Greenhouse gas intake pretreatment method and system

Abstract

The present invention relates to the field of gas processing technology, specifically to a greenhouse gas intake pretreatment method and system, comprising the following steps: collecting greenhouse gas temperature, pressure, flow rate and chemical composition data through sensors, cleaning and formatting the data, and integrating the data to generate basic information on the greenhouse gas state. In the present invention, by dynamically adjusting the valve opening and the intake path, the responsiveness to changing needs is significantly enhanced, ensuring the maximization of processing efficiency and energy utilization, using entropy theory to calculate and adjust the flow rate, optimizing the flow characteristics of greenhouse gases, reducing energy losses, and effectively matching the drying requirements of the permeable membrane by precisely controlling the pressure and temperature, further improving the greenhouse gas treatment quality and the environmental performance of the system, enhancing the overall performance and environmental benefits of greenhouse gas intake pretreatment, and greatly advancing the environmental protection and economic indicators of the technology compared to traditional technologies.

Description

Technical Field

[0001] The present invention relates to the technical field of gas processing, and in particular to a greenhouse gas intake preprocessing method and system. Background Art

[0002] The field of gas processing technology covers a series of methods and systems designed to treat, purify, separate and convert gases to meet specific environmental standards or industrial requirements, including but not limited to desulfurization, removal of harmful pollutants, gas sweetening (removal of hydrogen sulfide), CO2 capture and storage, and other greenhouse gas management. It has a wide range of applications. Gas processing technology not only focuses on improving processing efficiency and reducing costs, but also emphasizes the development of innovative methods, such as using biotechnology or advanced materials to improve gas separation and purification processes.

[0003] Among them, the greenhouse gas intake pretreatment method is a specific gas treatment technology that aims to carry out preliminary treatment of greenhouse gases entering the system through physical or chemical means. The key is to remove impurities and adjust the gas composition and concentration to ensure that the subsequent treatment process is more efficient and environmentally friendly. Its main uses include improving the reusability of greenhouse gases, reducing negative impacts on the environment, and optimizing energy efficiency in industrial processes. It is usually used in energy production, industrial emission control, and climate change mitigation technology to support environmental protection and sustainable development goals.

[0004] Existing technologies generally lack highly adjustable response mechanisms and predictive capabilities for greenhouse gas treatment, which results in insufficient efficiency and adaptability in the face of changing industrial demands. In particular, in terms of data processing and system response, traditional methods often cannot adjust process parameters in real time, which limits the optimization of treatment efficiency and energy use. In addition, advanced data analysis techniques are not fully utilized, making it impossible for the system to effectively predict and adapt to changes in intake demand, increasing energy waste and operating costs. This technical limitation may lead to unstable treatment quality in industrial applications and affect the achievement of environmental protection goals. For example, low efficiency may result in poor control of greenhouse gas emissions, which is contrary to the goal of reducing environmental impact. Summary of the invention

[0005] The purpose of the present invention is to solve the shortcomings of the prior art and to propose a greenhouse gas intake pretreatment method and system.

[0006] In order to achieve the above object, the present invention adopts the following technical solution: a greenhouse gas intake pretreatment method, comprising the following steps:

[0007] S1: Collect greenhouse gas temperature, pressure, flow rate and chemical composition data through sensors, clean and format the data, and integrate the data to generate basic information on greenhouse gas status;

[0008] S2: Based on the basic information of greenhouse gas status, data mining is used to extract key trends and patterns, and statistical analysis is used to determine the probability distribution of future air intake demand to obtain air intake demand forecast analysis results;

[0009] S3: compiling a valve operation sequence according to the intake demand prediction and analysis result, dynamically adjusting the valve opening to match the intake demand, and synchronously adjusting the intake path to generate an adjusted intake configuration;

[0010] S4: applying the adjusted intake configuration, comparing the target and actual data, calculating the entropy change characteristics of the greenhouse gas flow rate using entropy theory, adjusting the flow distribution, and generating entropy change analysis results;

[0011] S5: According to the entropy change analysis result, the pressure and temperature settings of the backwash gas are adjusted, the flow rate and direction of the greenhouse gas are adjusted in real time, the drying requirements of the permeable membrane are matched, and the dynamic regulation result of the greenhouse gas is generated;

[0012] S6: Based on the greenhouse gas dynamic control results, continuously monitor the greenhouse gas drying process, integrate and analyze all collected data, confirm that the greenhouse gas parameters meet the pretreatment standards, and obtain the greenhouse gas pretreatment results.

[0013] As a further scheme of the present invention, the basic information of the greenhouse gas status includes the record results of greenhouse gas temperature, pressure, flow rate and chemical composition, the intake demand forecast analysis results include key trend analysis results and future intake demand probability analysis results, the adjusted intake configuration includes valve operation sequence, valve opening and intake path, the entropy change analysis results include greenhouse gas flow entropy change characteristic records, the greenhouse gas dynamic control results include backwash gas pressure adjustment records, backwash gas temperature adjustment records, greenhouse gas flow rate adjustment records and greenhouse gas flow direction adjustment records, and the greenhouse gas pretreatment results include drying process monitoring records and parameter compliance confirmation results.

[0014] As a further solution of the present invention, the specific steps of S1 are:

[0015] S101: Collect temperature, pressure, flow rate and chemical composition data of greenhouse gases through sensors, perform initial screening of the data, exclude outliers and empty records, perform preliminary time alignment, and generate purified raw data;

[0016] S102: Based on the purified raw data, the data is standardized, the data storage structure is unified for batch processing, and the data is encoded and converted to ensure encoding consistency, so as to obtain data in a unified format;

[0017] S103: Based on the unified format data, separate sensor data records are merged, and the timestamp is used as the primary key to associate and fuse the different types of sensor data to obtain basic information on the greenhouse gas status.

[0018] As a further solution of the present invention, the specific steps of S2 are:

[0019] S201: Based on the basic information of the greenhouse gas status, perform time sorting, screen key nodes of the time series, identify data fluctuations at each key node, record data repetition patterns and abnormal fluctuations within each period, and generate time series analysis results;

[0020] S202: Based on the time series analysis result, extract data trend lines, analyze the increase and decrease relationship between data points, determine data trends and mark key change nodes, and generate key trend identification results;

[0021] S203: Based on the key trend identification result, the data fluctuation frequency of the different time periods is calculated, the data change trend of each period is counted, the probability distribution of the air intake demand is calculated, and the air intake demand prediction analysis result is obtained.

[0022] As a further solution of the present invention, the specific steps of S3 are:

[0023] S301: Based on the intake demand prediction and analysis results, an opening adjustment value of each valve within a target time period is marked, an opening strategy for each valve is planned, and a valve operation sequence is formulated and generated;

[0024] S302: Based on the valve operation sequence, program the real-time adjustment of the valve opening, set the automatic adjustment instruction of the valve opening over time, ensure that each valve operation matches the predicted demand in real time, and generate a dynamic valve adjustment plan;

[0025] S303: Based on the valve dynamic adjustment scheme, optimize the intake path configuration, adjust the flow direction and flow rate of the intake pipeline according to the real-time opening of the valve, and generate an adjusted intake configuration.

[0026] As a further solution of the present invention, the specific steps of S4 are:

[0027] S401: Based on the adjusted air intake configuration, collect greenhouse gas flow data after actual operation, compare with the predetermined target flow, record the difference between the actual and target flow in a time period, mark the key moment when the deviation exceeds the standard, and generate a flow comparison difference record;

[0028] S402: Based on the flow comparison difference record, calculate the greenhouse gas flow entropy change at the key moment, evaluate the entropy change characteristics of the flow, compare the correlation between the entropy change and the flow deviation in the time period, and generate a correlation analysis record;

[0029] S403: Based on the correlation analysis record, the flow distribution strategy is adjusted, the operating parameters of the corresponding valves, including the opening and the adjustment frequency, are modified, the greenhouse gas flow control is performed, and the entropy change analysis result is obtained.

[0030] As a further solution of the present invention, the greenhouse gas flow entropy change is according to the formula:

[0031] ;

[0032] Calculating the entropy change of greenhouse gas flows at critical moments ,in, is the heat element in the reversible process is the absolute temperature, is the pressure change, is the initial pressure, and is the weight coefficient, which is used to adjust the contribution of pressure change and mixing factor to the entropy change calculation. It is the mixing factor, which is used to measure the mixing degree of different types of greenhouse gases.

[0033] As a further solution of the present invention, the specific steps of S5 are:

[0034] S501: Based on the entropy change analysis result, real-time monitoring and adjustment of the pressure and temperature of the back-blowing gas are performed, and the back-blowing gas pressure and temperature are adjusted to predetermined optimal values ​​to match the gas flow requirements in the greenhouse, and the adjusted back-blowing gas control parameters are generated;

[0035] S502: Based on the adjusted backwash gas control parameters, adjusting the greenhouse gas flow rate and flow direction to match the permeable membrane requirements of the difference area, and generating an optimized greenhouse gas flow rate and direction configuration;

[0036] S503: Based on the optimized flow rate and direction configuration, dynamic regulation is implemented, actual operation effects are monitored, overall greenhouse gas flow distribution is optimized, and a greenhouse gas dynamic regulation result is obtained.

[0037] As a further solution of the present invention, the specific steps of S6 are:

[0038] S601: Based on the greenhouse gas dynamic control result, continuous monitoring is performed, greenhouse gas related parameters are recorded and synchronized and stored in real time through data collection, and real-time updates are performed to generate a real-time monitoring data set;

[0039] S602: Based on the real-time monitoring data set, perform core analysis on all monitoring data using data integration, confirm the compliance of greenhouse gas parameters with pre-processing standards, mark data that exceeds a preset range, and generate parameter verification records;

[0040] S603: Based on the parameter verification record, a final review is conducted to ensure that all monitoring data meet the predetermined processing standards, integrate all relevant data and obtain greenhouse gas preprocessing results.

[0041] A greenhouse gas intake pretreatment system, the system comprising:

[0042] The data acquisition and synchronization module collects temperature, pressure, flow rate and chemical composition data of greenhouse gases through sensors, performs preliminary time alignment, unifies the data storage structure and performs encoding conversion, performs data association and fusion, and obtains basic information on the status of greenhouse gases;

[0043] The data trend analysis module performs time sorting, screens key nodes of the time series, extracts data trend lines, determines data trends and marks key change nodes based on the basic information of the greenhouse gas status, and generates key trend identification results;

[0044] The air intake demand calculation module calculates the data fluctuation frequency of the different time periods based on the key trend identification results, calculates the probability distribution of the air intake demand, plans the opening strategy of each valve according to the calculation results, and formulates and generates the valve operation sequence;

[0045] The valve control programming module programs the real-time adjustment of the valve opening based on the valve operation sequence, sets the automatic adjustment instruction, adjusts the flow direction and flow rate of the intake duct, and generates the adjusted intake configuration;

[0046] The flow deviation management module records the difference between the actual and target flow rates within a time period based on the adjusted intake configuration, marks the critical moment when the deviation exceeds the standard, calculates the entropy change of the greenhouse gas flow rate at the critical moment, adjusts the flow distribution strategy and performs greenhouse gas flow control to obtain the entropy change analysis result;

[0047] The dynamic control optimization module monitors and adjusts the pressure and temperature of the backwash gas based on the entropy change analysis results to match the gas flow requirements in the greenhouse, synchronously adjusts the greenhouse gas flow rate and flow direction to match the permeable membrane requirements of the difference area, optimizes the greenhouse gas flow distribution, and obtains the dynamic control results of the greenhouse gas;

[0048] The monitoring and compliance analysis module monitors, synchronizes and stores greenhouse gas related parameters in real time based on the dynamic regulation results of greenhouse gases, performs core analysis on all monitoring data, marks data that exceeds the preset range, ensures that all monitoring data meets the predetermined processing standards, and obtains greenhouse gas preprocessing results.

[0049] Compared with the prior art, the advantages and positive effects of the present invention are:

[0050] In the present invention, by dynamically adjusting the valve opening and the air intake path, the responsiveness to changing demands is significantly enhanced, ensuring the maximization of processing efficiency and energy utilization, using entropy theory to calculate and adjust the flow rate, optimizing the flow characteristics of greenhouse gases, and reducing energy losses. By precisely controlling pressure and temperature, the drying requirements of the permeable membrane are effectively matched, further improving the treatment quality of greenhouse gases and the environmental performance of the system, and enhancing the overall performance and environmental benefits of greenhouse gas intake pretreatment. Compared with traditional technologies, the environmental protection and economic indicators of the technology are greatly advanced. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] Figure 1 It is a schematic diagram of the workflow of the present invention;

[0052] Figure 2 This is a flowchart of obtaining S1 of the present invention;

[0053] Figure 3 This is a flowchart of obtaining S2 of the present invention;

[0054] Figure 4 This is a flowchart of obtaining S3 of the present invention;

[0055] Figure 5 This is a flowchart of obtaining S4 of the present invention;

[0056] Figure 6 This is a flowchart of obtaining S5 of the present invention;

[0057] Figure 7 This is an acquisition flow chart of S6 of the present invention;

[0058] Figure 8 It is a system module diagram of the present invention. DETAILED DESCRIPTION

[0059] 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.

[0060] 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.

[0061] See also Figure 1 The present invention provides a technical solution: a greenhouse gas intake pretreatment method, comprising the following steps:

[0062] S1: Collect greenhouse gas temperature, pressure, flow rate and chemical composition data through sensors, clean and format the data, and integrate the data to generate basic information on greenhouse gas status;

[0063] S2: Based on the basic information of greenhouse gas status, data mining is used to extract key trends and patterns, and statistical analysis is used to determine the probability distribution of future air intake demand to obtain the air intake demand forecast analysis results;

[0064] S3: Based on the forecast and analysis results of the air intake demand, a valve operation sequence is compiled to dynamically adjust the valve opening to match the air intake demand, and the air intake path is adjusted synchronously to generate an adjusted air intake configuration;

[0065] S4: Apply the adjusted intake configuration, compare the target and actual data, use entropy theory to calculate the entropy change characteristics of the greenhouse gas flow, adjust the flow distribution, and generate entropy change analysis results;

[0066] S5: According to the entropy change analysis results, the pressure and temperature settings of the backwash gas are adjusted, the flow rate and direction of the greenhouse gas are adjusted in real time, the drying requirements of the permeable membrane are matched, and the dynamic regulation results of the greenhouse gas are generated;

[0067] S6: Based on the results of greenhouse gas dynamic control, continuously monitor the greenhouse gas drying process, integrate and analyze all collected data, confirm that the greenhouse gas parameters meet the pretreatment standards, and obtain the greenhouse gas pretreatment results.

[0068] The basic information on the greenhouse gas status includes the records of greenhouse gas temperature, pressure, flow rate and chemical composition. The results of the air intake demand forecast analysis include the key trend analysis results and the future air intake demand probability analysis results. The adjusted air intake configuration includes the valve operation sequence, valve opening and air intake path. The entropy change analysis results include the greenhouse gas flow entropy change characteristic records. The greenhouse gas dynamic control results include the backwash gas pressure adjustment records, the backwash gas temperature adjustment records, the greenhouse gas flow rate adjustment records and the greenhouse gas flow direction adjustment records. The greenhouse gas pretreatment results include the drying process monitoring records and the parameter compliance confirmation results.

[0069] See also Figure 2 , the specific steps of S1 are:

[0070] S101: Collect temperature, pressure, flow rate and chemical composition data of greenhouse gases through sensors, perform initial screening of the data, exclude outliers and empty records, perform preliminary time alignment, and generate purified raw data;

[0071] The temperature, pressure, flow rate and chemical composition data of greenhouse gases are collected through sensors, and the average value and standard deviation are calculated by the formula: , ,in represents the average value, represents the standard deviation, is each measured value, is the number of measurements. Compare each data point with the mean, remove outliers that exceed three times the standard deviation, and then delete all empty records to ensure data quality. Apply a time alignment algorithm to the remaining data, arrange them in order of measurement time, fill in time gaps, and generate purified raw data, which can exclude abnormal data and improve data reliability.

[0072] S102: Based on the purified original data, the data is standardized, the data storage structure is unified for batch processing, and the data is encoded and converted to ensure encoding consistency to obtain data in a unified format;

[0073] Based on the purification of raw data, data standardization is applied, and the minimum-maximum standardization method is used to convert each sensor data to the [0, 1] interval. The formula is: ,in represents the standardized data, is the original data, and are the maximum and minimum values ​​of the data set, respectively. After standardization, all data will have a uniform scale and magnitude, which is convenient for storage and subsequent processing. After that, the data is converted into a unified encoding format, such as ASCII encoding, to ensure error-free data transmission between different systems. The data is then stored in a database, and each record includes timestamp, temperature, pressure, flow rate and chemical composition, which is convenient for batch processing and access.

[0074] S103: Based on the unified format data, merge the individual sensor data records, use the timestamp as the primary key, associate and fuse the different types of sensor data, and obtain the basic information of greenhouse gas status;

[0075] Based on the processed unified format data, merge the data records from different sensors. First, All sensor data is sorted and indexed as the primary key so that the corresponding record can be found quickly. Next, the temperature, pressure, flow rate and chemical composition data are fused using an association algorithm to generate a record containing all relevant data. For example, if there is only temperature and pressure data at a certain time point, the system will search for data at adjacent time points to estimate the missing flow rate and chemical composition data. This is calculated by interpolation, and the formula is ,in represents the flow velocity value calculated by interpolation, and is the flow velocity value at adjacent time points, and is the corresponding timestamp. The final data set contains complete information on temperature, pressure, flow rate and chemical composition at each time point, providing an accurate data basis for subsequent analysis and monitoring.

[0076] See also Figure 3 , the specific steps of S2 are:

[0077] S201: Based on the basic information of greenhouse gas status, perform time sorting, screen the key nodes of the time series, identify the data fluctuations of each key node, record the data repetitive patterns and abnormal fluctuations in each cycle, and generate time series analysis results;

[0078] Based on the merged and integrated greenhouse gas status basic information, the data is first sorted by timestamp Sorting is done to ensure that the data is arranged in chronological order. Furthermore, data sampling technology is used to select key time nodes. The sampling method is to take points at equal intervals and select data as key nodes every hour. For each selected key node, its data fluctuation is calculated. The fluctuation calculation formula is: ,in, Represents the fluctuation difference between adjacent data points. and are the data values ​​of two consecutive time points. Next, the data repetition pattern in each cycle is identified, and the periodic repetition data and abnormal fluctuations are identified using the pattern recognition algorithm, and this information is recorded. Finally, the data repetition pattern and abnormal fluctuations of each cycle are integrated to generate the time series analysis results. This result can effectively indicate the behavioral characteristics of the data in the time dimension.

[0079] S202: Based on the time series analysis results, extract data trend lines, analyze the increase and decrease relationship between data points, determine data trends and mark key change nodes, and generate key trend identification results;

[0080] Based on the results of time series analysis, the trend line of the data is further extracted. The linear regression method is used to calculate the slope and intercept of the trend line. The formula is: ,in Represents the result of trend line calculation, is the time variable, is the slope, which represents the speed of increase or decrease of the data. is the intercept, which represents the baseline level of the data. By calculating the slope of the data change between every two consecutive key nodes, the overall data increase and decrease relationship can be analyzed. According to the positive and negative slope and its size, the main increase and decrease trend of the data is determined and the key change nodes, such as the slope mutation point, are marked. These marked nodes are recorded in the key trend identification results, providing an intuitive view of data changes, making subsequent decisions and analysis more targeted and effective.

[0081] S203: based on the key trend identification result, calculating the data fluctuation frequency of the different time periods, counting the data change trend of each period, calculating the probability distribution of the air intake demand, and obtaining the air intake demand prediction analysis result;

[0082] Based on the identified key trend results, the frequency of data fluctuations in different time periods is calculated using the frequency analysis formula ,in represents the fluctuation frequency, is the number of times a particular wave occurs, is the length of observation time. Combine the calculated fluctuation frequency with the data change trend to count the data change pattern of each cycle. Then use the probability distribution model, such as normal distribution, to calculate the probability distribution of air intake demand. The formula is: ,in represents the probability density of air intake demand, Represents the specific demand value, is the mean, is the standard deviation. In this way, the forecast analysis results of air intake demand are obtained, providing a scientific basis for adjusting and optimizing greenhouse gas management.

[0083] See also Figure 4 , the specific steps of S3 are:

[0084] S301: Based on the intake demand forecast analysis result, mark the opening adjustment value of each valve within the target time period, plan the opening strategy of each valve, and formulate and generate the valve operation sequence;

[0085] Based on the forecast analysis results of intake demand, detailed planning of each valve opening adjustment within the target time period is carried out. First, the demand in the forecast results is converted into valve opening percentage, using the conversion formula ,in Represents the target opening percentage of the valve, is the predicted demand, is the maximum flow capacity of the valve. Based on this calculation, a specific opening target value is set for each valve. Then, a detailed operation sequence is created, listing the opening adjustment of each valve in chronological order to ensure that the operation of each valve can accurately correspond to the predicted demand. These operation sequences contain the operation time point, target opening and expected adjustment range, forming a valve operation sequence file for subsequent automation control system use.

[0086] S302: Based on the valve operation sequence, program the real-time adjustment of the valve opening, set the automatic adjustment instruction of the valve opening over time, ensure that each valve operation matches the predicted demand in real time, and generate a dynamic valve adjustment plan;

[0087] Based on the generated valve operation sequence, the real-time adjustment programming of the valve opening is performed. The function of the valve opening changing with time is defined as ,in It's time The valve opening, is the initial opening, It is the opening change rate, which is dynamically adjusted according to the operation requirements in the time series. This function is programmed into the valve control system, and the opening is continuously adjusted through the automatic control software to ensure that the real-time operation of each valve matches the predicted demand in real time. This dynamic adjustment plan is concretized into a series of automatic adjustment instructions, each of which includes the execution time, target opening and adjustment rate, and is automatically executed by the control system to generate a dynamic adjustment plan for the valve.

[0088] S303: Based on the valve dynamic adjustment scheme, optimize the intake path configuration, adjust the flow direction and flow rate of the intake pipeline according to the real-time opening of the valve, and generate an adjusted intake configuration;

[0089] Based on the generated dynamic valve adjustment scheme, the intake path configuration is optimized. The specific method is to control the flow direction and flow rate of the intake duct by adjusting the valve opening in real time to ensure the efficient operation of the intake system. Use the flow rate adjustment formula ,in is the flow rate, It's traffic. is the cross-sectional area of ​​the pipe. The flow rate is adjusted according to the real-time opening of the valve. , and adjust the flow rate accordingly To adapt to different usage requirements. In this way, not only the intake path configuration is optimized, but also the best performance of the system under various operating conditions is ensured. The generated adjusted intake configuration records the adjustment of each valve, the changes in flow rate and flow rate in detail, and provides a detailed intake management plan.

[0090] See also Figure 5 , the specific steps of S4 are:

[0091] S401: Based on the adjusted air intake configuration, collect greenhouse gas flow data after actual operation, compare with the predetermined target flow, record the difference between the actual and target flow in the time period, mark the key moment when the deviation exceeds the standard, and generate a flow comparison difference record;

[0092] Based on the adjusted air intake configuration, first collect the greenhouse gas flow data after operation. Compare the measured flow with the predetermined target flow and calculate the difference using the formula ,in, Indicates the flow difference, is the actual flow rate, The target flow rate is recorded at each key time point during the entire observation period, and the key moments when the difference value exceeds the set threshold are marked. These marked moments are regarded as key moments when the deviation exceeds the standard, and these data are integrated into a flow comparison difference record. This record reflects the degree of deviation of system operation in detail, providing a basis for adjustment operations.

[0093] S402: Based on the flow comparison difference record, calculate the greenhouse gas flow entropy change at the key moment, evaluate the entropy change characteristics of the flow, compare the correlation between the entropy change and the flow deviation in the time period, and generate a correlation analysis record;

[0094] Greenhouse gas flow entropy change, according to the formula:

[0095] ;

[0096] Calculating the entropy change of greenhouse gas flows at critical moments ,in, is the heat element in the reversible process is the absolute temperature, is the pressure change, is the initial pressure, and is the weight coefficient, which is used to adjust the contribution of pressure change and mixing factor to the entropy change calculation. It is the mixing factor, which is used to measure the mixing degree of different types of greenhouse gases.

[0097] The execution process is as follows:

[0098] First, calculate the heat change at each time point and the corresponding temperature , and then consider the change in pressure With initial pressure ratio, which reflects the process of gas compression or expansion, adding a mixing factor , used to consider the impact of the change in the proportion of different greenhouse gases in the flow on the entropy change, the weight coefficient and Through data regression analysis, the contribution of pressure change and mixing factor to entropy change calculation is adjusted, and the relevant parameters are integrated and substituted into the formula to calculate the entropy change value of greenhouse gas flow at the critical moment.

[0099] S403: Based on the correlation analysis record, the flow distribution strategy is adjusted, the operating parameters of the corresponding valves, including the opening and the adjustment frequency, are modified, the greenhouse gas flow control is performed, and the entropy change analysis result is obtained;

[0100] Based on the obtained correlation analysis records, the flow distribution strategy is adjusted. The relationship between entropy change and flow deviation shown in the analysis records guides the modification of valve operating parameters, including opening and adjustment frequency. The adjustment formula is ),in is the adjusted valve opening, is the original opening, is the adjustment coefficient, which is set according to the difference in entropy change, It is the target entropy change value. Through precise control of valve opening and adjustment frequency, it is ensured that the greenhouse gas flow rate meets the predetermined entropy change analysis results in actual operation, thereby optimizing the efficiency and stability of the entire system.

[0101] See also Figure 6 , the specific steps of S5 are:

[0102] S501: Based on the entropy change analysis result, the pressure and temperature of the back-blowing gas are monitored and adjusted in real time, and the pressure and temperature of the back-blowing gas are adjusted to predetermined optimal values ​​to match the gas flow requirements in the greenhouse, and the adjusted back-blowing gas control parameters are generated;

[0103] Based on the results of the entropy change analysis, the pressure and temperature of the back-blowing gas are monitored and adjusted in real time. First, the current pressure and temperature parameters of the back-blowing gas are regularly detected. By comparing with the optimal values ​​recommended by the entropy change analysis, the pressure and temperature of the back-blowing gas are gradually adjusted to approach the ideal state. This adjustment adopts a progressive approach, and each adjustment is based on the latest monitoring data to ensure that each adjustment step is targeted and can immediately reflect the response of the system. Through this strategy, the control parameters of the back-blowing gas are optimized, and finally the adjusted parameter records are generated, which indicate the pressure and temperature settings at each stage.

[0104] S502: Based on the adjusted backwash gas control parameters, the greenhouse gas flow rate and flow direction are adjusted to match the permeable membrane requirements of the difference area, and an optimized greenhouse gas flow rate and direction configuration is generated;

[0105] Based on the adjusted backwash gas control parameters, continue to adjust the flow rate and direction of greenhouse gas to better match the permeable membrane requirements of different areas. The specific operation includes evaluating the specific requirements of the permeable membrane in each area for gas flow rate and direction, and fine-tuning the gas flow rate and direction according to the adjustment results of the backwash gas. By monitoring the distribution effect of gas in each area, dynamically adjust the gas distribution to ensure uniform and efficient gas supply. These operation results are recorded in the optimized configuration file, which lists the gas flow rate and flow direction settings for each area in detail.

[0106] S503: Based on the optimized flow rate and direction configuration, implement dynamic control, monitor the actual operation effect, optimize the overall greenhouse gas flow distribution, and obtain the dynamic control result of greenhouse gases;

[0107] After implementing the optimized flow rate and direction configuration, continue to perform dynamic control to monitor and optimize the overall greenhouse gas flow distribution. Through real-time monitoring system feedback, detect the actual operation effect and compare it with the predetermined gas flow configuration. If the flow or direction of any area is found to be deviated from the plan, make adjustments immediately. Dynamic control includes adjusting the opening of the valve and the frequency of adjustment to accurately control the flow and direction to ensure the stability of the greenhouse environment. Finally, a detailed dynamic control result report is generated, summarizing the key adjustments and optimization measures in the control process to ensure the effective and uniform distribution of greenhouse gases.

[0108] See also Figure 7 , the specific steps of S6 are:

[0109] S601: Based on the results of greenhouse gas dynamic control, continuous monitoring is performed, greenhouse gas related parameters are recorded and synchronized and stored in real time through data collection, and real-time updates are performed to generate real-time monitoring data sets;

[0110] Based on the results of greenhouse gas dynamic control, a continuous monitoring system is set up to record various parameters related to greenhouse gases in real time. This includes real-time monitoring of data such as temperature, pressure, flow rate, and chemical composition. The monitoring system collects data through sensors, automatically synchronizes and stores it in a central database to ensure real-time update and integrity of the data. Through such a configuration, a real-time monitoring data set is generated, which includes the timestamps and related parameters received from each sensor, providing detailed real-time data support for subsequent analysis.

[0111] S602: Based on the real-time monitoring data set, use data integration to conduct core analysis of all monitoring data, confirm the compliance of greenhouse gas parameters with pre-processing standards, mark data that exceeds the preset range, and generate parameter verification records;

[0112] Using real-time monitoring data sets, a series of data integration and core analysis operations are performed. In this process, the system first compares the collected data with the pre-processing standards to check whether each parameter meets the preset range and conditions. For those data points that are out of the preset range, the system will automatically mark and record them in the parameter verification record. This step ensures that any potential deviations or anomalies can be quickly identified and responded to for immediate adjustments or further detailed analysis.

[0113] S603: Based on the parameter verification records, conduct final review and confirmation to ensure that all monitoring data meet the predetermined processing standards, integrate all relevant data and obtain greenhouse gas preprocessing results;

[0114] Based on the parameter verification records, a final review confirmation process is carried out to ensure that all monitoring data meet the predetermined processing standards. This process involves a detailed review of the marked abnormal data, verifying the cause and background of each abnormal point, and whether the monitoring settings or processing procedures need to be adjusted. After completing these confirmations, all verified data are integrated to generate the final greenhouse gas preprocessing results. This result brings together all relevant data and provides a comprehensive and verified data view to guide subsequent greenhouse management and decision-making processes

[0115] See also Figure 8 , a greenhouse gas intake pretreatment system, comprising:

[0116] The data acquisition and synchronization module collects temperature, pressure, flow rate and chemical composition data of greenhouse gases through sensors, performs preliminary time alignment, unifies the data storage structure and performs encoding conversion, performs data association and fusion, and obtains basic information on the status of greenhouse gases;

[0117] The data trend analysis module performs time sorting, screens key nodes of the time series, extracts data trend lines, determines data trends, marks key change nodes, and generates key trend identification results based on the basic information of greenhouse gas status;

[0118] The air intake demand calculation module calculates the data fluctuation frequency in different time periods based on the key trend identification results, calculates the probability distribution of air intake demand, plans the opening strategy of each valve according to the calculation results, and formulates and generates the valve operation sequence;

[0119] The valve control programming module programs the real-time adjustment of the valve opening based on the valve operation sequence, sets the automatic adjustment instructions, adjusts the flow direction and flow rate of the intake duct, and generates the adjusted intake configuration;

[0120] The flow deviation management module records the difference between the actual and target flow rates within a time period based on the adjusted intake configuration, marks the critical moments when the deviation exceeds the standard, calculates the entropy change of greenhouse gas flow at the critical moments, adjusts the flow distribution strategy and performs greenhouse gas flow control to obtain the entropy change analysis results;

[0121] Based on the entropy change analysis results, the dynamic control optimization module monitors and adjusts the pressure and temperature of the backwash gas to match the gas flow requirements in the greenhouse, and simultaneously adjusts the greenhouse gas flow rate and flow direction to match the permeable membrane requirements of the difference area, optimizes the greenhouse gas flow distribution, and obtains the dynamic control results of the greenhouse gas;

[0122] The monitoring and compliance analysis module monitors, synchronizes and stores greenhouse gas related parameters in real time based on the results of dynamic greenhouse gas regulation, performs core analysis on all monitoring data, marks data that exceeds the preset range, ensures that all monitoring data meets the predetermined processing standards, and obtains greenhouse gas preprocessing results.

[0123] 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. A greenhouse gas inlet pretreatment method, characterized in that: The following steps are involved: Collect greenhouse gas temperature, pressure, flow rate and chemical composition data through sensors, clean and format the data, and integrate the data to generate basic information on the status of greenhouse gases; Based on the basic information of greenhouse gas status, data mining is used to extract key trends and patterns, and statistical analysis is used to determine the probability distribution of future air intake demand to obtain air intake demand forecast analysis results; According to the intake demand prediction and analysis results, a valve operation sequence is compiled to dynamically adjust the valve opening to match the intake demand, and the intake path is adjusted synchronously to generate an adjusted intake configuration; Applying the adjusted intake configuration, comparing the target and actual data, using entropy theory to calculate the entropy change characteristics of the greenhouse gas flow, adjusting the flow distribution, and generating entropy change analysis results; According to the entropy change analysis results, the pressure and temperature settings of the backwash gas are adjusted, the flow rate and direction of the greenhouse gas are adjusted in real time, the drying requirements of the permeable membrane are matched, and the dynamic regulation results of the greenhouse gas are generated; According to the greenhouse gas dynamic control results, continuously monitor the greenhouse gas drying process, integrate and analyze all collected data, confirm that the greenhouse gas parameters meet the pretreatment standards, and obtain the greenhouse gas pretreatment results; Based on the basic information of greenhouse gas status, data mining is used to extract key trends and patterns, and statistical analysis is used to determine the probability distribution of future air intake demand. The specific steps for obtaining the air intake demand forecast analysis results are as follows: Based on the basic information of the greenhouse gas status, time sorting is performed, key nodes of the time series are screened, data fluctuations of each key node are identified, data repetitive patterns and abnormal fluctuations within each period are recorded, and time series analysis results are generated; Based on the time series analysis results, extract data trend lines, analyze the increase and decrease relationship between data points, determine data trends and mark key change nodes, and generate key trend identification results; Based on the key trend identification results, the data fluctuation frequency of the different time periods is calculated, the data change trend of each cycle is counted, the probability distribution of the air intake demand is calculated, and the air intake demand prediction analysis results are obtained.

2. A greenhouse gas intake pretreatment method according to claim 1, characterized in that: The basic information on the greenhouse gas status includes the records of greenhouse gas temperature, pressure, flow rate and chemical composition; the intake demand forecast analysis results include key trend analysis results and future intake demand probability analysis results; the adjusted intake configuration includes valve operation sequence, valve opening and intake path; the entropy change analysis results include greenhouse gas flow entropy change characteristic records; the greenhouse gas dynamic control results include backwash gas pressure adjustment records, backwash gas temperature adjustment records, greenhouse gas flow rate adjustment records and greenhouse gas flow direction adjustment records; the greenhouse gas pretreatment results include drying process monitoring records and parameter compliance confirmation results.

3. A greenhouse gas intake pretreatment method according to claim 1, characterized in that: The specific steps of collecting greenhouse gas temperature, pressure, flow rate and chemical composition data through sensors, cleaning and formatting the data, and integrating the data to generate basic information on the status of greenhouse gases are as follows: Collect greenhouse gas temperature, pressure, flow rate and chemical composition data through sensors, perform initial screening of the data, exclude outliers and empty records, perform preliminary time alignment, and generate purified raw data; Based on the purified raw data, the data is standardized, the data storage structure is unified for batch processing, and the data is encoded and converted to ensure encoding consistency to obtain data in a unified format; Based on the unified format data, separate sensor data records are merged, and the timestamp is used as the primary key to associate and fuse the different types of sensor data to obtain basic information on the greenhouse gas status.

4. A greenhouse gas inlet pretreatment method according to claim 1, characterized in that: According to the intake demand prediction and analysis results, the valve operation sequence is compiled, the valve opening is dynamically adjusted to match the intake demand, and the intake path is adjusted synchronously to generate the adjusted intake configuration. The specific steps are: Based on the intake demand forecast analysis result, annotate the opening adjustment value of each valve within the target time period, plan the opening strategy of each valve, and formulate and generate a valve operation sequence; Based on the valve operation sequence, the real-time adjustment of the valve opening is programmed, and the automatic adjustment instructions of the valve opening over time are set to ensure that each valve operation matches the predicted demand in real time and generate a dynamic valve adjustment plan; Based on the valve dynamic adjustment scheme, the intake path configuration is optimized, the flow direction and flow rate of the intake pipeline are adjusted according to the real-time opening of the valve, and the adjusted intake configuration is generated.

5. A greenhouse gas inlet pretreatment method according to claim 1, characterized in that: The specific steps of applying the adjusted intake configuration, comparing the target and actual data, using entropy theory to calculate the entropy change characteristics of the greenhouse gas flow, adjusting the flow distribution, and generating the entropy change analysis results are as follows: Based on the adjusted air intake configuration, collect greenhouse gas flow data after actual operation, compare with the predetermined target flow, record the difference between the actual and target flow in the time period, mark the key moment when the deviation exceeds the standard, and generate a flow comparison difference record; Based on the flow comparison difference record, calculate the greenhouse gas flow entropy change at the key moment, evaluate the entropy change characteristics of the flow, compare the correlation between the entropy change and the flow deviation in the time period, and generate a correlation analysis record; Based on the correlation analysis records, the flow distribution strategy is adjusted, the operating parameters of the corresponding valves are modified, including the opening and the adjustment frequency, the greenhouse gas flow control is performed, and the entropy change analysis results are obtained.

6. A greenhouse gas inlet pretreatment method according to claim 5, characterized in that: The greenhouse gas flow entropy change is according to the formula: ； Calculating the entropy change of greenhouse gas flows at critical moments ,in, is the heat element in the reversible process, is the absolute temperature, is the pressure change, is the initial pressure, and is the weight coefficient, which is used to adjust the contribution of pressure change and mixing factor to the entropy change calculation. It is the mixing factor, which is used to measure the mixing degree of different types of greenhouse gases.

7. A greenhouse gas inlet pretreatment method according to claim 1, characterized in that: According to the entropy change analysis results, the pressure and temperature settings of the backwash gas are adjusted, the flow rate and direction of the greenhouse gas are adjusted in real time, and the drying requirements of the permeable membrane are matched. The specific steps for generating the dynamic control results of the greenhouse gas are as follows: Based on the entropy change analysis result, real-time monitoring and adjustment of the pressure and temperature of the back-blowing gas are performed, and the back-blowing gas pressure and temperature are adjusted to predetermined optimal values ​​to match the gas flow requirements in the greenhouse, and the adjusted back-blowing gas control parameters are generated; Based on the adjusted backflush gas control parameters, adjusting the greenhouse gas flow rate and flow direction to match the permeable membrane requirements of the difference area to generate an optimized greenhouse gas flow rate and direction configuration; Based on the optimized flow rate and direction configuration, dynamic regulation is implemented, the actual operation effect is monitored, the overall greenhouse gas flow distribution is optimized, and the dynamic regulation result of greenhouse gases is obtained.

8. A greenhouse gas inlet pretreatment method according to claim 1, characterized in that: According to the results of greenhouse gas dynamic control, the greenhouse gas drying process is continuously monitored, all collected data are integrated and analyzed, and it is confirmed that the greenhouse gas parameters meet the pretreatment standards. The specific steps to obtain the greenhouse gas pretreatment results are as follows: Based on the dynamic regulation results of greenhouse gases, continuous monitoring is performed, greenhouse gas related parameters are recorded, synchronized and stored in real time through data collection, and updated in real time to generate a real-time monitoring data set; Based on the real-time monitoring data set, use data integration to perform core analysis on all monitoring data, confirm the compliance of greenhouse gas parameters with pre-processing standards, mark data that exceeds the preset range, and generate parameter verification records; Based on the parameter verification records, a final review is conducted to ensure that all monitoring data meet the predetermined processing standards, integrate all relevant data and obtain greenhouse gas preprocessing results.

9. A greenhouse gas intake pretreatment system, characterized in that: According to a greenhouse gas intake pretreatment method according to any one of claims 1 to 8, the system comprises: The data acquisition and synchronization module collects temperature, pressure, flow rate and chemical composition data of greenhouse gases through sensors, performs preliminary time alignment, unifies the data storage structure and performs encoding conversion, performs data association and fusion, and obtains basic information on the status of greenhouse gases; The data trend analysis module performs time sorting, screens key nodes of the time series, extracts data trend lines, determines data trends and marks key change nodes based on the basic information of the greenhouse gas status, and generates key trend identification results; The air intake demand calculation module calculates the data fluctuation frequency of the different time periods based on the key trend identification results, calculates the probability distribution of the air intake demand, plans the opening strategy of each valve according to the calculation results, and formulates and generates the valve operation sequence; The valve control programming module programs the real-time adjustment of the valve opening based on the valve operation sequence, sets the automatic adjustment instruction, adjusts the flow direction and flow rate of the intake duct, and generates the adjusted intake configuration; The flow deviation management module records the difference between the actual and target flow rates within a time period based on the adjusted intake configuration, marks the critical moment when the deviation exceeds the standard, calculates the entropy change of the greenhouse gas flow rate at the critical moment, adjusts the flow distribution strategy and performs greenhouse gas flow control to obtain the entropy change analysis result; The dynamic control optimization module monitors and adjusts the pressure and temperature of the backwash gas based on the entropy change analysis results to match the gas flow requirements in the greenhouse, synchronously adjusts the greenhouse gas flow rate and flow direction to match the permeable membrane requirements of the difference area, optimizes the greenhouse gas flow distribution, and obtains the dynamic control results of the greenhouse gas; The monitoring and compliance analysis module monitors, synchronizes and stores greenhouse gas related parameters in real time based on the dynamic regulation results of greenhouse gases, performs core analysis on all monitoring data, marks data that exceeds the preset range, ensures that all monitoring data meets the predetermined processing standards, and obtains greenhouse gas preprocessing results.

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