Carbon capture full-process intelligent regulation system and method based on multi-source heterogeneous data fusion

Abstract

The application discloses a multi-source heterogeneous data fusion carbon capture whole-process intelligent regulation and control system and method, relates to the technical field of carbon capture regulation and control, and is used for solving the problems of uneven distribution of tower internal humidity, liquid level height deviation, heat utilization efficiency reduction and shortened equipment operation life, taking the liquid level height of an absorption tower as a core regulation and control variable, setting multiple groups of liquid levels and sampling periods, collecting absorption heat content and gas-liquid humidity proportion in real time, calculating absorption heat efficiency based on import and export temperature difference and specific heat capacity, constructing a mass transfer efficiency evaluation factor in combination with image recognition results, screening an optimal liquid level height, subsequently collecting gas flow and temperature difference, calculating gas phase resistance coefficient, classifying tower operation states in combination with gas-liquid contact state, matching a pressure difference regulation mechanism to regulate gas-liquid balance, obtaining absorption residual time and calculating a load index, dynamically correcting operation load, improving mass transfer efficiency and heat utilization rate, prolonging equipment cycle and reducing system energy consumption.

Description

Technical Field

[0001] This invention relates to the field of carbon capture and control technology, and more specifically, to an intelligent control system and method for the entire carbon capture process based on the fusion of multi-source heterogeneous data. Background Technology

[0002] Carbon capture technology, as a crucial means to achieve industrial carbon reduction goals, is increasingly in demand in high-carbon-emission industries such as chemical, power, and steel. Current engineering applications widely employ chemical absorption methods to capture carbon dioxide from flue gas. A typical process includes gas pretreatment, mass transfer reaction in the absorption tower, liquid circulation, and regeneration. As the core equipment of the carbon capture system, the absorption tower's operational stability and mass transfer efficiency have a decisive impact on the overall capture rate and energy consumption level.

[0003] The existing technology has the following shortcomings:

[0004] Currently, the control of operating parameters of absorption towers is mostly based on local adjustments using feedback from a single variable (such as tower top temperature or liquid level). This lacks comprehensive perception and joint scheduling of gas-liquid contact behavior, mass transfer thermodynamic state, and system load. As a result, uneven moisture distribution within the tower leads to deviations in liquid level, decreased heat utilization efficiency, and shortened equipment lifespan. Therefore, a smart control system and method for the entire carbon capture process based on multi-source heterogeneous data fusion is proposed.

[0005] The information disclosed in the background section is only intended to enhance the understanding of the background of this disclosure, and therefore may include information that does not constitute prior art known to those skilled in the art. Summary of the Invention

[0006] To overcome the aforementioned deficiencies of the prior art, embodiments of the present invention provide an intelligent control system and method for the entire carbon capture process based on multi-source heterogeneous data fusion. This system addresses the problems mentioned in the background art by employing liquid level thermodynamic parameter calculation, image recognition analysis, and multivariable state modeling fusion techniques.

[0007] To achieve the above objectives, the present invention provides the following technical solution: a method for intelligent control of the entire carbon capture process based on multi-source heterogeneous data fusion, comprising the following steps:

[0008] Step S1: Adjust the liquid circulation flow rate of the absorption tower to set multiple sets of different liquid level heights, set the sampling time, and detect the absorption heat content and gas-liquid wettability ratio of the absorption tower at each set of liquid level heights within the sampling time.

[0009] Step S2: Calculate the absorption heat efficiency of each group using the absorption heat content of the absorption tower, evaluate the mass transfer efficiency change trend in combination with the gas-liquid wetting ratio, and use the mass transfer efficiency change trend to screen the target liquid level height.

[0010] Step S3: Detect the gas volume flow rate of the absorption tower based on the target liquid level height and calculate the gas phase resistance coefficient. Detect the gas temperature difference between the inlet and outlet of the absorption tower. Combine the gas phase resistance coefficient to classify the current gas-liquid contact state of the absorption tower. Select different differential pressure adjustment mechanisms based on the classification results.

[0011] Step S4: After selecting the differential pressure adjustment mechanism, call the emission monitoring platform to obtain the remaining emission time, use the remaining emission time to calculate the load index of the marker tower, and correct the current operating load of the absorption tower according to the load index.

[0012] In a preferred embodiment, in step S1, the liquid circulation flow rate of the absorption tower is adjusted to establish multiple different liquid level heights;

[0013] The heat content of absorption and the proportion of gas-liquid humidification in the absorption tower are collected within a preset sampling time period.

[0014] The heat content of the absorbed liquid is calculated by detecting the temperature difference between the inlet and outlet of the absorbent liquid and the specific heat capacity of the liquid.

[0015] The percentage of the wetted area is obtained by using an infrared image sensor to measure the proportion of the packing surface covered by the absorbent liquid.

[0016] In a preferred embodiment, in step S2, the heat absorption efficiency at each group of liquid level heights is calculated based on the heat absorption content.

[0017] The product of the heat absorption efficiency and the proportion of the wetted area is used as the mass transfer efficiency evaluation factor.

[0018] By calculating the mass transfer efficiency evaluation factor at each group of liquid level heights, the trend of mass transfer efficiency change under liquid level changes is obtained.

[0019] The liquid level height that maximizes the mass transfer efficiency evaluation factor is selected as the target liquid level height for the operation of the absorption tower.

[0020] In a preferred embodiment, in step S3, the liquid level of the absorption tower is adjusted to the target liquid level, the gas volume flow rate is detected by a differential pressure flow meter, and the gas flow channel cross-sectional area of ​​the gas outlet pipeline of the absorption tower is retrieved from the absorption tower archive database.

[0021] The ratio of gas volumetric flow rate to gas channel cross-sectional area is used as the average gas velocity.

[0022] Obtain the pressure values ​​of the gas at the inlet and outlet of the absorption tower, and take the absolute value of the difference as the gas pressure difference.

[0023] In a preferred embodiment, in step S3, the gas density inside the absorption tower is detected by an online gas density meter;

[0024] The gas phase drag coefficient is calculated using the average gas velocity, gas pressure difference, and gas density.

[0025] The gas temperature difference is obtained by measuring the gas temperature at the inlet and outlet of the absorption tower using temperature sensors and taking the absolute value of the difference.

[0026] In a preferred embodiment, in step S3, the gas temperature difference and the gas phase resistance coefficient are defined as input variables and divided into different fuzzy sets;

[0027] The gas-liquid contact state of the absorption tower is defined as the output variable, and it is divided into uniform distribution state, local aggregation state and uneven distribution state.

[0028] A set of fuzzy rules is formulated to describe the influence of different input variables on the output variable, and fuzzy inference is performed based on the fuzzy rules to obtain the output result.

[0029] In a preferred embodiment, in step S3, when the output result is a uniform distribution, the current pressure difference is maintained.

[0030] When the output result is a localized aggregation state, select the pulse-type differential pressure adjustment mechanism;

[0031] When the output result is unevenly distributed, a corrective differential pressure adjustment mechanism is selected.

[0032] In a preferred embodiment, in step S4, the total emission time, emission duration and emission rate of the emission monitoring platform are called, and the difference between the total emission time and emission duration is used to obtain the remaining emission time.

[0033] The load index of the absorption tower is calculated using the remaining emission time and emission rate.

[0034] The current operating load in the absorption tower's operation monitoring system is retrieved, and multiplied by the absorption tower's load index to obtain the corrected operating load.

[0035] The intelligent control system for the entire carbon capture process based on multi-source heterogeneous data fusion includes a liquid level and thermal parameter module, a mass transfer sieve optimization module, a gas resistance status identification module, and a load adjustment module. The functions of each module are as follows:

[0036] The liquid level thermal parameter module adjusts the liquid circulation flow rate of the absorption tower, sets multiple sets of different liquid level heights, sets the sampling time, and detects the absorbed heat content and gas-liquid wettability ratio of the absorption tower at each set of liquid level heights within the sampling time, and transmits the data to the mass transfer sieve optimization module.

[0037] The mass transfer screening module receives the absorbed heat content and gas-liquid wetting ratio from the liquid level thermal parameter module. It calculates the absorbed heat efficiency of each group using the absorbed heat content of the absorption tower, evaluates the mass transfer efficiency change trend in combination with the gas-liquid wetting ratio, and uses the mass transfer efficiency change trend to screen the target liquid level height and transmit it to the gas resistance status module.

[0038] The gas resistance status detection module detects the gas volume flow rate of the absorption tower based on the target liquid level height input from the mass transfer sieve optimization module and calculates the gas phase resistance coefficient. It also detects the gas temperature difference between the inlet and outlet of the absorption tower and classifies the current gas-liquid contact state of the absorption tower in combination with the gas phase resistance coefficient. Based on the classification results, different differential pressure adjustment mechanisms are selected.

[0039] After the load adjustment module selects the differential pressure adjustment mechanism, it calls the emission monitoring platform to obtain the remaining emission time, uses the remaining emission time to calculate the load index of the marker tower, and corrects the current operating load of the absorption tower according to the load index.

[0040] The technical effects and advantages of this invention are as follows:

[0041] This invention uses the absorber tower liquid level as the core control variable. By setting multiple liquid level heights and a complete sampling cycle, it collects the absorption heat content and gas-liquid wetting ratio under various operating conditions in real time. The absorption heat efficiency is calculated based on the liquid inlet / outlet temperature difference and the absorbent specific heat capacity. Combined with the wetting ratio obtained from image recognition, a mass transfer efficiency evaluation factor is constructed to screen out the optimal target liquid level height, achieving optimal control of mass transfer performance. After obtaining the target liquid level height, the gas volumetric flow rate and gas inlet / outlet temperature difference of the absorber tower are further collected to calculate the gas phase resistance coefficient. The tower's operating state is classified based on the gas-liquid contact characteristics, and different differential pressure adjustment mechanisms are matched to regulate the gas-liquid balance. The remaining absorption time is obtained, and the current load index of the marker tower is calculated accordingly. The absorber tower's operating load is dynamically corrected to ensure stable operation while achieving the carbon capture target, improving the mass transfer efficiency and heat utilization rate of the carbon capture process, extending the equipment's operating cycle, and reducing system energy consumption. Attached Figure Description

[0042] Figure 1 This is a flowchart of the intelligent control method for the entire carbon capture process based on multi-source heterogeneous data fusion, as described in this invention.

[0043] Figure 2 This is a schematic diagram of the modules of the intelligent control system for the entire carbon capture process based on multi-source heterogeneous data fusion of the present invention. Detailed Implementation

[0044] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0045] This invention uses the absorber tower liquid level as the core control variable. By setting multiple liquid level heights and a complete sampling cycle, it collects the absorption heat content and gas-liquid wetting ratio under various operating conditions in real time. The absorption heat efficiency is calculated based on the liquid inlet / outlet temperature difference and the absorbent specific heat capacity. Combined with the wetting ratio obtained from image recognition, a mass transfer efficiency evaluation factor is constructed to screen out the optimal target liquid level height, achieving optimal control of mass transfer performance. After obtaining the target liquid level height, the gas volume flow rate and gas inlet / outlet temperature difference of the absorber tower are further collected to calculate the gas phase resistance coefficient. The tower's operating state is then classified based on the gas-liquid contact characteristics, and different differential pressure adjustment mechanisms are matched to regulate the gas-liquid balance. The remaining absorption time is obtained, and the current load index of the marker tower is calculated accordingly. The operating load of the absorber tower is dynamically corrected to ensure stable operation while achieving the carbon capture target.

[0046] Example 1: A method for intelligent control of the entire carbon capture process based on multi-source heterogeneous data fusion, such as... Figure 1 As shown, it includes the following steps:

[0047] Step S1: Adjust the liquid circulation flow rate of the absorption tower to set multiple sets of different liquid level heights, set the sampling time, and detect the absorption heat content and gas-liquid wettability ratio of the absorption tower at each set of liquid level heights within the sampling time.

[0048] Step S2: Calculate the absorption heat efficiency of each group using the absorption heat content of the absorption tower, evaluate the mass transfer efficiency change trend in combination with the gas-liquid wetting ratio, and use the mass transfer efficiency change trend to screen the target liquid level height.

[0049] Step S3: Detect the gas volume flow rate of the absorption tower based on the target liquid level height and calculate the gas phase resistance coefficient. Detect the gas temperature difference between the inlet and outlet of the absorption tower. Combine the gas phase resistance coefficient to classify the current gas-liquid contact state of the absorption tower. Select different differential pressure adjustment mechanisms based on the classification results.

[0050] Step S4: After selecting the differential pressure adjustment mechanism, call the emission monitoring platform to obtain the remaining emission time, use the remaining emission time to calculate the load index of the marker tower, and correct the current operating load of the absorption tower according to the load index.

[0051] The specific implementation is as follows:

[0052] In step S1, the liquid circulation flow rate of the absorption tower is adjusted to establish multiple different liquid level heights. That is, different circulation flow rate values ​​are set in the absorption tower circulation pump flow control system so that the liquid in the absorption tower reaches multiple preset liquid level heights under steady-state conditions. The liquid level height is monitored and recorded in real time by the liquid level gauge in the tower.

[0053] It should be noted that the absorption tower circulating pump flow control system refers to an automated regulating device system used to adjust and control the circulating flow rate of the absorbent liquid in the absorption tower in real time. It adjusts the operating frequency or output pressure of the circulating pump according to externally set parameters to achieve precise control of the absorbent liquid mass flow rate. The tower level gauge refers to a sensor device installed in the liquid phase section of the absorption tower to monitor the absorbent liquid level in real time.

[0054] Set a sampling time period that covers the heat change process of absorption within a complete cycle. At each set of liquid level heights, the sampling period is determined based on the liquid residence time of the absorption tower and the circulation cycle of the absorbent liquid. Specifically, the sampling period should be greater than or equal to the maximum value of the liquid residence time of the absorption tower and the circulation cycle of the absorbent liquid, so as to ensure that at least one complete absorption process is covered.

[0055] The heat of absorption and the percentage of gas-liquid humidification in the absorption tower were collected during the sampling period.

[0056] The absorbed heat content is calculated by detecting the temperature difference between the inlet and outlet of the absorption liquid and the specific heat capacity of the liquid. The specific calculation formula is as follows:

[0057] ;

[0058] in, Let be the heat absorbed at the liquid level height of the i-th group; The mass flow rate of the absorbent liquid at the i-th liquid level height is collected in real time by the flow meter in the absorption tower circulating pump flow control system. The specific heat capacity of the absorbent is indicated by the absorbent property table. and The inlet and outlet temperatures of the liquid at the i-th liquid level are respectively collected by an online temperature sensor.

[0059] It should be noted that the absorbent property table refers to a standardized data table used to store and provide the physicochemical properties of the absorbent under different operating conditions, namely different temperatures, pressures, and concentrations; the online temperature sensor refers to a measuring component installed on the inlet and outlet pipelines of the absorbent liquid phase to continuously measure the temperature change of the absorbent and output the temperature signal in real time.

[0060] The gas-liquid wettability ratio refers to the proportion of the packing surface in the absorption tower that is covered by the absorbent liquid. This value is defined as follows: Real-time image analysis of the packing surface wettability is performed using an infrared image sensor, and the wetted area ratio is extracted using an image recognition algorithm.

[0061] ;

[0062] in, The percentage of gas-liquid wetting at the i-th liquid level is [value missing]. This represents the wetted area of ​​the packing surface at the i-th group of liquid level heights; This represents the total surface area of ​​the packing material.

[0063] It should be noted that the infrared image sensor refers to a non-contact photoelectric detection device used to collect infrared images of the surface of the packing material inside the absorption tower. Its main function is to capture the thermal radiation image of the packing area in real time under working conditions, thereby identifying the wetting coverage of the packing surface by the absorbent liquid. The image recognition algorithm refers to a set of calculation methods deployed in the image processing module for analyzing, recognizing and classifying the thermal radiation images collected by the infrared image sensor. In this embodiment, it is used to extract the liquid wetting area on the packing surface and calculate the gas-liquid wetting ratio.

[0064] In summary, at each liquid level, data on the absorbed heat content and the gas-liquid wetting ratio were collected through a set sampling time for subsequent analysis.

[0065] In step S2, based on the heat content of absorption and the gas-liquid wetting ratio corresponding to multiple sets of liquid level heights collected in step S1, the mass transfer performance of the absorption tower under different liquid level conditions is quantitatively analyzed, and the optimal target liquid level height is selected to improve carbon capture efficiency and reduce energy consumption.

[0066] First, the heat absorption efficiency at each liquid level height is calculated based on the absorbed heat content using the following formula:

[0067] ;

[0068] in, Let be the heat absorption efficiency at the i-th group of liquid level height; The absorbed heat content is collected at the liquid level height of the i-th group; Let be the mass flow rate of the absorbent at the i-th group of liquid levels.

[0069] The calculated heat absorption efficiency characterizes the amount of heat absorbed per unit mass of absorbent liquid during the absorption process, reflecting the heat absorption activity of the absorbent liquid in the mass transfer process. The larger the value, the greater the heat absorption activity, and the smaller the value, the smaller the heat absorption activity.

[0070] Subsequently, to comprehensively evaluate the mass transfer performance of the absorption tower at various liquid levels, a mass transfer efficiency evaluation factor was constructed, and the calculation formula is as follows:

[0071] ;

[0072] in, This is the mass transfer efficiency evaluation factor at the i-th group of liquid level heights; Let be the heat absorption efficiency at the i-th group of liquid level height; The percentage of gas-liquid humidification at the i-th liquid level height.

[0073] The heat absorption efficiency reflects the heat exchange capacity of the absorbent under operating conditions; the gas-liquid wettability ratio indicates the degree of effective gas-liquid contact area; and the mass transfer efficiency evaluation factor, as the product of the above two, can effectively reflect the synergy of heat and mass transfer and the overall absorption efficiency during carbon capture.

[0074] By calculating the mass transfer efficiency evaluation factor at each liquid level, the trend of mass transfer efficiency variation under liquid level changes was obtained. Combined with engineering analysis, insufficient coverage of the packing surface by the absorbent liquid leads to a reduction in the gas-liquid interface and mass transfer area, resulting in a simultaneous decrease in absorption heat efficiency and gas-liquid wetting ratio, and a significant reduction in carbon capture efficiency. While excessively high liquid levels increase the gas-liquid wetting ratio, the accumulation or supersaturation of liquid in the packing can cause blockage of gas phase channels and increased pressure drop, limiting gas phase diffusion and absorption reactions, leading to a decrease in absorption heat efficiency. Therefore, within the adjustable range of liquid level, the mass transfer efficiency evaluation factor exhibits a unimodal distribution, reaching a maximum value at a certain liquid level.

[0075] Among all the collected operating condition groups, the liquid level height that maximizes the mass transfer efficiency evaluation factor is selected as the target liquid level height for the operation of the absorber. This target liquid level height has the optimal combination of gas-liquid contact state and absorption heat efficiency, which effectively reduces the circulating pump load and operating energy consumption while ensuring that the carbon capture rate meets the standard.

[0076] In step S3, the liquid level of the absorption tower is adjusted to the target liquid level. The gas volume flow rate is detected by a differential pressure flow meter installed on the gas outlet pipeline of the absorption tower. The gas flow channel cross-sectional area of ​​the gas outlet pipeline of the absorption tower is called from the absorption tower archive database. The ratio of the gas volume flow rate to the gas flow channel cross-sectional area is used as the gas average flow velocity.

[0077] The pressure values ​​of gas at the inlet and outlet of the absorption tower are obtained by a pressure sensor installed at the gas outlet of the absorption tower, and the absolute value of the difference is taken as the gas pressure difference.

[0078] The gas density inside the absorption tower was detected using an online gas density meter.

[0079] Calculate the gas phase drag coefficient using the fluid dynamics drag formula: ,in, For gas pressure difference, For gas density, The average gas velocity, This is the gas phase drag coefficient;

[0080] The gas phase resistance coefficient is used to reflect the resistance level encountered by the gas when it flows in the absorption tower. The larger the gas phase resistance coefficient, the more likely there is uneven gas-liquid distribution or local accumulation in the operation.

[0081] The gas temperature difference is obtained by measuring the gas temperature at the inlet and outlet of the absorption tower using temperature sensors and taking the absolute value of the difference.

[0082] The gas temperature difference reflects the degree of sensible heat exchange between the gas and the absorbent in the absorption tower. The higher the gas temperature difference, the more complete the sensible heat exchange between the gas and the absorbent in the absorption tower.

[0083] Gas temperature difference and gas phase drag coefficient are defined as input variables and divided into different fuzzy sets. For example, gas temperature difference factors are divided into low temperature difference, medium temperature difference and high temperature difference, and gas phase drag coefficient factors are divided into slight drag region, medium drag region and drag surge region.

[0084] The gas-liquid contact state of the absorption tower is defined as the output variable, and it is divided into uniform distribution state, local aggregation state and uneven distribution state.

[0085] Develop a set of fuzzy rules to describe the impact of different input variables on the output variable. The rules can be defined based on professional knowledge or obtained through data analysis and experimentation, for example:

[0086] If the gas temperature difference is a low temperature difference and the gas phase resistance coefficient is in the region of slight resistance, then the gas-liquid contact state is judged to be a uniform distribution state.

[0087] If the gas temperature difference is a high temperature difference and the gas phase resistance coefficient is in the region of sudden increase in resistance, then the gas-liquid contact state is judged to be a local accumulation state.

[0088] If the gas temperature difference is medium and the gas phase resistance coefficient is in the medium resistance region, then the gas-liquid contact state is judged to be a uniform distribution state.

[0089] If the gas temperature difference is a low temperature difference and the gas phase resistance coefficient is in the region of sudden increase in resistance, then the gas-liquid contact state is judged to be a state of uneven distribution.

[0090] Fuzzy inference is performed based on fuzzy rules. When the output result is a uniform distribution, the current differential pressure is maintained; when the output result is a local clustering state, a pulse-type differential pressure adjustment mechanism is selected; and when the output result is an uneven distribution state, a corrective differential pressure adjustment mechanism is selected.

[0091] It should be explained that the fuzzy set division can be adjusted according to actual needs. Gas temperature difference and gas phase resistance coefficient can be divided into three or more sets to better classify them based on different conditions. Furthermore, the division of gas temperature difference and gas phase resistance coefficient can be set with thresholds based on actual operating experience and historical data. For example, when the gas temperature difference is less than 2℃, it is classified as a low temperature difference; when the gas temperature difference is between 2℃ and 5℃, it is classified as a medium temperature difference; and when the gas temperature difference is greater than 5℃, it is classified as a high temperature difference.

[0092] When the gas-liquid contact state is uniformly distributed, it indicates that the gas-liquid distribution in the absorption tower is balanced, and the current pressure difference is maintained. When the gas-liquid contact state is locally concentrated, it indicates that there is dense accumulation of gas and liquid in a local area in the absorption tower, and a pulse-type pressure difference adjustment mechanism is selected. When the gas-liquid contact state is unevenly distributed, it indicates that there are obvious regional differences in the gas-liquid contact, and a corrective pressure difference adjustment mechanism is selected.

[0093] It should be explained that the differential pressure adjustment mechanism is a preset control strategy library, which includes two types of modes: pulse-type differential pressure adjustment mechanism and correction-type differential pressure adjustment mechanism. The preset control strategy library is established based on the characteristics of the absorber equipment, operating experience, and experimental calibration data. After selecting the differential pressure adjustment mechanism, the corresponding operation is executed. The differential pressure adjustment mechanism is used to adjust the differential pressure distribution of the gas phase flow in the absorber, including the inlet and outlet differential pressure values ​​and the local pressure drop distribution in the tower. By controlling the opening of the inlet and outlet valves and the operating status of the flow guiding device in the tower, the differential pressure distribution of the gas phase flow is optimized. The pulse-type differential pressure adjustment mechanism adjusts the fan speed of the absorber or switches the opening of the inlet and outlet valves; the correction-type differential pressure adjustment mechanism fine-tunes the gas distribution path in conjunction with the flow guiding device in the absorber, and the specific settings are performed by professionals.

[0094] By classifying the gas-liquid contact state and implementing the corresponding differential pressure adjustment mechanism, the gas flow state of the absorption tower is changed. In subsequent steps, the load index needs to be recalculated and the operating load corrected based on emission monitoring data.

[0095] It should be noted that the absorption tower archive database is used to store the structural parameters and rated operating calibration data of the absorption tower. In this embodiment, it is used to obtain the cross-sectional area of ​​the gas flow channel in the gas outlet pipeline of the absorption tower. The differential pressure flow meter is an instrument that measures flow rate based on the functional relationship between the pressure difference generated when the fluid flows through the throttling element and the flow rate. In this embodiment, it is used to directly detect the gas volume flow rate. The online gas density meter is a detection device that can measure the gas density in the pipeline in real time. The fluid dynamics resistance formula is used to describe the relationship between pressure loss and flow kinetic energy caused by various factors when the fluid flows in the channel. The pressure sensor is a detection element that converts the pressure signal of the measured fluid into an electrical signal output. In this embodiment, it is used to collect the gas inlet and outlet pressures of the absorption tower in real time. The temperature sensor is a measurement element that converts the temperature signal of the fluid into a processable electrical signal. In this embodiment, the temperature sensor is installed at the inlet and outlet of the absorption tower to detect the gas temperature.

[0096] In step S4, the total emission time, emission duration, and emission rate of the emission monitoring platform are retrieved, and the remaining emission time is obtained by subtracting the total emission time and emission duration.

[0097] It needs to be explained that adjusting the absorption tower through the differential pressure adjustment mechanism changes the gas-liquid contact state of the absorption tower, thereby affecting the absorption capacity of the absorption tower. The load index is recalculated and the operating load of the absorption tower is corrected by discharging the remaining time.

[0098] Calculate the load index of the absorption tower using the remaining emission time and emission rate: ,in, For emission rate, For rated operating time, For rated processing capacity, For the remaining time of emission, The load index of the absorption tower;

[0099] It should be explained that the rated operating time and rated processing capacity of the absorption tower are obtained through the absorption tower archive database. The rated processing capacity refers to the amount of gas that the absorption tower can process per unit time under the designed operating conditions, and the rated operating time refers to the time required to complete one carbon capture under the rated processing capacity conditions.

[0100] Operating load refers to the ratio of the actual processing capacity of the absorption tower under current operating conditions to its rated processing capacity, reflecting the operating intensity of the absorption tower; the load index of the absorption tower refers to the ratio of the operating intensity required to complete the total amount of remaining carbon capture within the remaining emission time to its rated processing capacity.

[0101] When the load index of the absorption tower is greater than 1, it means that the carbon capture workload exceeds the rated processing capacity, and the operating load of the absorption tower needs to be increased; when the load index of the absorption tower is equal to 1, the absorption tower maintains the current operating load; when the load index of the absorption tower is less than 1, the carbon capture workload is lower than the rated processing capacity, and the operating load can be reduced to save energy.

[0102] The current operating load in the absorption tower's operation monitoring system is retrieved, and multiplied by the absorption tower's load index to obtain the corrected operating load; the absorption tower's operating load is then adjusted to the corrected operating load.

[0103] The adjustment of the operating load is carried out by professionals, including but not limited to the gas-liquid ratio, spray distribution mode and inlet / outlet pressure difference setting.

[0104] By calculating the load index of the absorption tower by emitting the remaining time and emission rate, and correcting it with the current operating load, the operating intensity of the absorption tower can be dynamically matched with the remaining carbon capture task, avoiding energy waste and equipment wear caused by over-operation, while improving the accuracy and response speed of absorption tower operation control.

[0105] It should be noted that the emission monitoring platform is used to collect real-time operational status data of upstream emission sources connected to the absorption tower, including emission rate, emission duration, and total emission time; the operation monitoring system is the process control and data acquisition platform for the absorption tower, used to monitor, calculate, and manage key parameters during the operation of the absorption tower in real time. In this embodiment, the operation monitoring system can directly output the current operating load.

[0106] Example 2: Intelligent control system for the entire carbon capture process based on multi-source heterogeneous data fusion, such as... Figure 2 As shown, the intelligent control method for the entire carbon capture process to achieve multi-source heterogeneous data fusion includes a liquid level thermal parameter module, a mass transfer sieve optimization module, a gas resistance status identification module, and a load adjustment module. The functions of each module are as follows:

[0107] The liquid level thermal parameter module adjusts the liquid circulation flow rate of the absorption tower, sets multiple sets of different liquid level heights, sets the sampling time, and detects the absorbed heat content and gas-liquid wettability ratio of the absorption tower at each set of liquid level heights within the sampling time, and transmits the data to the mass transfer sieve optimization module.

[0108] The mass transfer screening module receives the absorbed heat content and gas-liquid wetting ratio from the liquid level thermal parameter module. It calculates the absorbed heat efficiency of each group using the absorbed heat content of the absorption tower, evaluates the mass transfer efficiency change trend in combination with the gas-liquid wetting ratio, and uses the mass transfer efficiency change trend to screen the target liquid level height and transmit it to the gas resistance status module.

[0109] The gas resistance status detection module detects the gas volume flow rate of the absorption tower based on the target liquid level height input from the mass transfer sieve optimization module and calculates the gas phase resistance coefficient. It also detects the gas temperature difference between the inlet and outlet of the absorption tower and classifies the current gas-liquid contact state of the absorption tower in combination with the gas phase resistance coefficient. Based on the classification results, different differential pressure adjustment mechanisms are selected.

[0110] After the load adjustment module selects the differential pressure adjustment mechanism, it calls the emission monitoring platform to obtain the remaining emission time, uses the remaining emission time to calculate the load index of the marker tower, and corrects the current operating load of the absorption tower according to the load index.

[0111] The above formulas are all dimensionless calculations. The formulas are derived from software simulations based on a large amount of collected data to obtain the most recent real-world results. The preset parameters in the formulas are set by those skilled in the art according to the actual situation.

[0112] The above embodiments can be implemented, in whole or in part, by software, hardware, firmware, or any other combination thereof. When implemented using software, the above embodiments can be implemented, in whole or in part, in the form of a computer program product.

[0113] Those skilled in the art will recognize that the modules and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and inventive constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0114] In addition, the functional modules in the various embodiments of this application can be integrated into one processing module, or each module can exist physically separately, or two or more modules can be integrated into one module.

[0115] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

[0116] In conclusion, the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for intelligent control of the entire carbon capture process based on multi-source heterogeneous data fusion, characterized by: Includes the following steps: Step S1: Adjust the liquid circulation flow rate of the absorption tower to set multiple sets of different liquid level heights, set the sampling time, and detect the absorption heat content and gas-liquid wettability ratio of the absorption tower at each set of liquid level heights within the sampling time. In step S1, the liquid circulation flow rate of the absorption tower is adjusted to establish multiple different liquid level heights; The heat content of absorption and the proportion of gas-liquid humidification in the absorption tower are collected within a preset sampling time period. The heat content of the absorbed liquid is calculated by detecting the temperature difference between the inlet and outlet of the absorbent liquid and the specific heat capacity of the liquid. The percentage of the wetted area is obtained by using an infrared image sensor to acquire the proportion of the packing surface inside the absorption tower that is covered by the absorbent liquid. Step S2: Calculate the absorption heat efficiency of each group using the absorption heat content of the absorption tower, evaluate the mass transfer efficiency change trend in combination with the gas-liquid wetting ratio, and use the mass transfer efficiency change trend to screen the target liquid level height. In step S2, the heat absorption efficiency at each group of liquid level heights is calculated based on the heat absorption content; The product of the heat absorption efficiency and the proportion of the wetted area is used as the mass transfer efficiency evaluation factor. By calculating the mass transfer efficiency evaluation factor at each group of liquid level heights, the trend of mass transfer efficiency change under liquid level changes is obtained. The liquid level height that maximizes the mass transfer efficiency evaluation factor is selected as the target liquid level height for the operation of the absorption tower. Step S3: Detect the gas volume flow rate of the absorption tower based on the target liquid level height and calculate the gas phase resistance coefficient. Detect the gas temperature difference between the inlet and outlet of the absorption tower. Combine the gas phase resistance coefficient to classify the current gas-liquid contact state of the absorption tower. Select different differential pressure adjustment mechanisms based on the classification results. Step S4: After selecting the differential pressure adjustment mechanism, call the emission monitoring platform to obtain the remaining emission time, use the remaining emission time to calculate the load index of the marker tower, and correct the current operating load of the absorption tower according to the load index; In step S4, the total emission time, emission duration, and emission rate of the emission monitoring platform are retrieved, and the remaining emission time is obtained by subtracting the total emission time and emission duration. The load index of the absorption tower is calculated using the remaining emission time and emission rate. The current operating load in the absorption tower's operation monitoring system is retrieved, and multiplied by the absorption tower's load index to obtain the corrected operating load.

2. The intelligent control method for the entire carbon capture process based on multi-source heterogeneous data fusion according to claim 1, characterized in that: In step S3, the liquid level of the absorption tower is adjusted to the target liquid level, the gas volume flow rate is detected by a differential pressure flow meter, and the gas flow channel cross-sectional area of ​​the gas outlet pipeline of the absorption tower is retrieved from the absorption tower archive database. The ratio of gas volumetric flow rate to gas channel cross-sectional area is used as the average gas velocity. Obtain the pressure values ​​of the gas at the inlet and outlet of the absorption tower, and take the absolute value of the difference as the gas pressure difference.

3. The intelligent control method for the entire carbon capture process based on multi-source heterogeneous data fusion according to claim 2, characterized in that: In step S3, the gas density inside the absorption tower is detected by an online gas density meter; The gas phase drag coefficient is calculated using the average gas velocity, gas pressure difference, and gas density. The gas temperature difference is obtained by measuring the gas temperature at the inlet and outlet of the absorption tower using temperature sensors and taking the absolute value of the difference.

4. The intelligent control method for the entire carbon capture process based on multi-source heterogeneous data fusion according to claim 3, characterized in that: In step S3, the gas temperature difference and the gas phase resistance coefficient are defined as input variables and divided into different fuzzy sets; The gas-liquid contact state of the absorption tower is defined as the output variable, and it is divided into uniform distribution state, local aggregation state and uneven distribution state. A set of fuzzy rules is formulated to describe the influence of different input variables on the output variable, and fuzzy inference is performed based on the fuzzy rules to obtain the output result.

5. The intelligent control method for the entire carbon capture process based on multi-source heterogeneous data fusion according to claim 4, characterized in that: In step S3, when the output result is a uniform distribution, the current pressure difference is maintained. When the output result is a localized aggregation state, select the pulse-type differential pressure adjustment mechanism; When the output result is unevenly distributed, a corrective differential pressure adjustment mechanism is selected.

6. A multi-source heterogeneous data fusion-based intelligent control system for the entire carbon capture process, used to implement the multi-source heterogeneous data fusion-based intelligent control method for the entire carbon capture process as described in any one of claims 1-5, characterized in that: It includes a liquid level and thermal parameter module, a mass transfer sieve optimization module, a gas resistance status identification module, and a load adjustment module. The functions of each module are as follows: The liquid level thermal parameter module adjusts the liquid circulation flow rate of the absorption tower, sets multiple sets of different liquid level heights, sets the sampling time, and detects the absorbed heat content and gas-liquid wettability ratio of the absorption tower at each set of liquid level heights within the sampling time, and transmits the data to the mass transfer sieve optimization module. The mass transfer screening module receives the absorbed heat content and gas-liquid wetting ratio from the liquid level thermal parameter module. It calculates the absorbed heat efficiency of each group using the absorbed heat content of the absorption tower, evaluates the mass transfer efficiency change trend in combination with the gas-liquid wetting ratio, and uses the mass transfer efficiency change trend to screen the target liquid level height and transmit it to the gas resistance status module. The gas resistance status detection module detects the gas volume flow rate of the absorption tower based on the target liquid level height input from the mass transfer sieve optimization module and calculates the gas phase resistance coefficient. It also detects the gas temperature difference between the inlet and outlet of the absorption tower and classifies the current gas-liquid contact state of the absorption tower in combination with the gas phase resistance coefficient. Based on the classification results, different differential pressure adjustment mechanisms are selected. After the load adjustment module selects the differential pressure adjustment mechanism, it calls the emission monitoring platform to obtain the remaining emission time, uses the remaining emission time to calculate the load index of the marker tower, and corrects the current operating load of the absorption tower according to the load index.

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