Amine liquid degradation rate online monitoring method and system, electronic equipment and storage medium

Abstract

The invention discloses an amine liquid degradation rate online monitoring method and system, electronic equipment and a storage medium, a barren solution after rich solution desorption is sampled and analyzed to obtain target parameters, and the target parameters comprise conductivity, nitramine substance concentration and acid radical ion concentration; environmental parameters and liquid parameters of barren liquor are obtained, the environmental parameters comprise the temperature and pressure of the current environment, and the liquid parameters comprise the CO2 concentration and the liquid flow rate; determining a current temperature and pressure compensation coefficient according to the environmental parameters; inputting the environmental parameters and the liquid parameters into a trained algorithm model to obtain a weight coefficient corresponding to each type of target parameters; and executing an amine liquid concentration control strategy according to the amine liquid degradation rate. Compared with a fixedly set weight coefficient, the weight coefficient of the target parameter is dynamically adjusted according to the current environment parameter and the liquid parameter, and the weight coefficient can be obtained more accurately; the amine liquid degradation rate can be quickly calculated according to the temperature and pressure compensation coefficient, the target parameter and the weight coefficient.

Description

Technical Field

[0001] This invention relates to the field of flue gas carbon capture technology, and in particular to an online monitoring method, system, electronic device, and storage medium for amine liquid degradation rate. Background Technology

[0002] Currently, the abnormal climate change caused by excessive CO2 emissions has become a global environmental problem threatening human survival and development. Therefore, CO2 capture and storage (CCS) is one of the important technologies for countries around the world to address excessive CO2 emissions. Chemical absorption, as the closest to commercially viable CO2 removal technology, has broad market prospects for capturing CO2 from power plant flue gas. Among these methods, absorption using amines as absorbents has been demonstrated and applied on a small scale in many locations, offering advantages such as fast gas absorption rate, good removal effect, and good chemical stability. However, amine absorbents have poor thermal stability and are prone to thermal degradation under certain temperature conditions (especially during desorption). In experiments, the loss of monoethanolamine (MEA) reached 1.4 kg per ton of CO2, and in some cases even higher. These inherent defects of amine absorbents seriously hinder their application in carbon capture. Amine degradation leads to a decrease in solution concentration, affecting subsequent absorption efficiency, and the degradation products of amines are corrosive, affecting the service life of the reactor. Therefore, studying the degradation of amines during carbon capture is crucial for improving carbon capture technology and reducing capture costs.

[0003] In existing technologies, when detecting the degradation rate of amine liquid, traditional offline detection methods (such as ion chromatography) are mainly used, which have long cycles (greater than 24 hours) and cannot guide process adjustments in real time. Alternatively, traditional detection methods rely on a single parameter, resulting in a large detection error rate. Summary of the Invention

[0004] This invention provides an online monitoring method for amine degradation rate, which solves the problems of long detection cycle and large error in the existing technology for detecting amine degradation rate.

[0005] In a first aspect, the present invention provides a method for online monitoring of amine degradation rate, applied to an online monitoring system for amine degradation rate, the method comprising:

[0006] The lean liquid after desorption of the rich liquid was sampled and analyzed to obtain target parameters, including conductivity, concentration of nitramines and concentration of acid anions;

[0007] The environmental parameters and the liquid parameters of the lean solution are obtained. The environmental parameters include the current ambient temperature and pressure, and the liquid parameters include CO2 concentration and liquid flow rate.

[0008] Determine the current temperature and pressure compensation coefficient based on the environmental parameters;

[0009] The environmental parameters and the liquid parameters are input into the trained algorithm model to obtain the weight coefficients corresponding to the target parameters of each type;

[0010] The amine degradation rate of the current lean solution is calculated based on the temperature and pressure compensation coefficient, the target parameter, and the weighting coefficient corresponding to the target parameter for each type.

[0011] An amine concentration control strategy is implemented based on the amine degradation rate.

[0012] Secondly, the present invention provides an online monitoring system for amine liquid degradation rate, comprising:

[0013] The sampling and analysis module is used to sample and analyze the lean liquid after the rich liquid is desorbed to obtain target parameters, including conductivity, concentration of nitramines and concentration of acid radicals.

[0014] The parameter acquisition module is used to acquire environmental parameters and liquid parameters of the lean solution. The environmental parameters include the current ambient temperature and pressure, and the liquid parameters include CO2 concentration and liquid flow rate.

[0015] The temperature and pressure compensation coefficient determination module is used to determine the current temperature and pressure compensation coefficient based on the environmental parameters.

[0016] The weight coefficient determination module is used to input the environmental parameters and the liquid parameters into the trained algorithm model to obtain the weight coefficients corresponding to each type of target parameter;

[0017] The amine degradation rate calculation module is used to calculate the current amine degradation rate of the lean solution based on the temperature and pressure compensation coefficient, the target parameter, and the weighting coefficient corresponding to each type of the target parameter.

[0018] An execution module is used to execute an amine concentration control strategy based on the amine degradation rate.

[0019] Thirdly, the present invention provides an electronic device, the electronic device comprising:

[0020] At least one processor; and

[0021] A memory communicatively connected to the at least one processor; wherein,

[0022] The memory stores a computer program that can be executed by the at least one processor, which enables the at least one processor to perform the online monitoring method for amine degradation rate as described in the first aspect of the present invention.

[0023] Fourthly, the present invention provides a computer-readable storage medium storing computer instructions that, when executed by a processor, implement the online monitoring method for amine degradation rate described in the first aspect of the present invention.

[0024] This invention provides an online monitoring method for amine degradation rate. First, the lean liquid after desorption from the rich liquid is sampled and analyzed to obtain target parameters, including conductivity, nitramine concentration, and acid anion concentration. Environmental parameters and liquid parameters of the lean liquid are then acquired. Environmental parameters include current temperature and pressure, while liquid parameters include CO2 concentration and flow rate. A temperature and pressure compensation coefficient is determined based on the environmental parameters. The environmental and liquid parameters are input into a trained algorithm model to obtain weight coefficients corresponding to each type of target parameter. The amine degradation rate of the lean liquid is calculated based on the temperature and pressure compensation coefficient, the target parameters, and the weight coefficients for each type of target parameter. Finally, an amine concentration control strategy is implemented based on the amine degradation rate. First, this scheme takes into account the errors caused by temperature and pressure changes when calculating the amine degradation rate, and therefore sets a temperature and pressure compensation coefficient, which can improve the detection accuracy. Second, compared with a fixed weighting coefficient, dynamically adjusting the weighting coefficient of the target parameter according to the current environmental and liquid parameters can obtain a more accurate weighting coefficient. Third, calculating the amine degradation rate by using the weighting coefficient and the corresponding detection data can quickly obtain the final result, which greatly shortens the detection cycle and is conducive to providing real-time guidance for the carbon capture process.

[0025] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of the present invention, nor is it intended to limit the scope of the invention. Other features of the invention will become readily apparent from the following description. Attached Figure Description

[0026] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0027] Figure 1 This is a flowchart of an online monitoring method for amine degradation rate provided in an embodiment of the present invention;

[0028] Figure 2 This is a schematic diagram of the structure of an online monitoring system for amine degradation rate provided in an embodiment of the present invention;

[0029] Figure 3 This is a schematic diagram of the structure of the electronic device provided in an embodiment of the present invention. Detailed Implementation

[0030] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. 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 should fall within the scope of protection of the present invention.

[0031] To better understand this scheme, the general steps and principles of carbon capture are described below:

[0032] Rich liquid formation: In the carbon capture stage, flue gas or gas stream containing CO2 passes through an absorption tower and comes into contact with an aqueous amine solution inside the tower. CO2 dissolves into the solution and reacts with the amine to form carbonates or carbamates. The final amine solution is called "rich liquid" and will be transported to the desorption tower.

[0033] Lean liquor formation: Inside the desorption tower, energy is provided to the rich liquor through heating or other means, causing the previously captured CO2 to be released from the solution. In addition, the amine solution will undergo oxidation, thermal degradation, and reactions with impurities. After desorption, the CO2 content in the amine solution is greatly reduced, and the remaining solution is the "lean liquor".

[0034] Figure 1 This is a flowchart illustrating an online monitoring method for amine degradation rate according to an embodiment of the present invention. This embodiment is applicable to situations involving online monitoring of amine degradation rate. The method can be executed by an online amine degradation rate monitoring system, which can be implemented in hardware and / or software and can be configured in an electronic device. Figure 1 As shown, the online monitoring method for amine degradation rate includes:

[0035] S101. Sample and analyze the lean liquid after desorption of the rich liquid to obtain the target parameters.

[0036] The target parameters include conductivity, concentration of nitrosamines, and concentration of acid radicals. Among them, the acid radicals mainly include formate and acetate ions.

[0037] Sampling of the lean solution can be accomplished through an online amine degradation rate monitoring system, which includes three stages: sampling, filtration, and sensing detection. The online amine degradation rate monitoring system includes an ultraviolet spectroscopy module, an online micro ion chromatography module, and an online conductivity module. Of course, it can also include temperature and pressure sensors.

[0038] The following describes the three stages: sampling, filtering, and sensing detection:

[0039] 1. Sampling stage: Sampling is carried out in the lean solution pipeline before the new amine solution replenishment tube after desorption and cooling. The pipeline needs to be kept warm, but no additional heating is required.

[0040] 2. Filtration Stage: Pre-filter: 316L stainless steel sintered filter element with silicon carbide coating → Self-cleaning centrifugal degassing module → Replaceable online ion exchange column (adsorbing Fe) 3+ Cr 3+ (e.g., metal ions).

[0041] 3. Sensor detection:

[0042] (1) The online ultraviolet spectroscopy module (used for detecting the concentration of nitrosamines) includes:

[0043] Light source: deuterium lamp (wavelength 200-400nm), power fluctuation compensation algorithm (ΔI / I<0.5%).

[0044] Detector: CMOS linear array sensor (1nm resolution), detecting characteristic peaks of nitrosamines (220-280nm).

[0045] Wavelength accuracy: ±0.3nm;

[0046] (2) Online micro ion chromatography module (for detecting acid radical ion concentration):

[0047] The microfluidic chip (channel width 200μm) integrates an online enrichment column with a detection limit ≤0.1ppm (formate / acetate) and a microfluidic chip calibration solution consumption ≤1mL / time.

[0048] Anti-Cl⁻ interference: Selective filtration via anion exchange membrane.

[0049] Analysis cycle: ≤5 minutes / time.

[0050] (3) Online conductivity module (used for detecting conductivity):

[0051] PTFE coated electrode, measuring range 0-200mS / cm, resistant to high temperature of 120℃.

[0052] Corrosion resistance: Lifespan ≥ 2 years in 40% MEA solution.

[0053] All of the above sensors require regular calibration and verification.

[0054] This embodiment employs an online ultraviolet (UV) spectroscopy module to detect nitrosamines, based on their characteristic absorption properties in the UV band. Nitroamine molecules contain chromophores such as nitro groups (-NO2), which undergo electronic transitions under UV light irradiation at specific wavelengths (e.g., 200-400 nm), resulting in light absorption. When nitrosamines in a sample absorb light energy at a specific wavelength, the transmitted light intensity decreases. A detector (e.g., a photodiode or photomultiplier tube) measures this change in light intensity. Since absorbance is proportional to concentration and optical path length, the concentration of the nitrosamine can be calculated. Compared to infrared, UV spectroscopy offers higher sensitivity for nitrosamines with conjugated systems or strong chromophores, thus providing higher detection accuracy.

[0055] After obtaining front-end data through sensor detection, analysis of this data yields conductivity, nitrosamine concentration, and anion concentration. Specifically, sampling and analysis of the lean solution after desorption from the rich solution are performed to obtain target parameters, including:

[0056] The UV absorbance of the lean solution was detected by a UV spectroscopy module; the ion chromatographic values ​​of the lean solution were detected by an online micro ion chromatography module; the conductivity of the lean solution was detected by an online conductivity module; the concentration of nitramines was determined based on the UV absorbance, and the concentration of acid radicals was determined based on the ion chromatographic values.

[0057] In an optional embodiment, after detecting the conductivity of the lean solution using the linear conductivity module, the method further includes: determining whether there is abnormal data based on the correlation between ultraviolet absorbance, ion chromatography values, and conductivity; if so, deleting the current abnormal data.

[0058] Performing abnormal data cleaning can prevent incorrect amine degradation rate calculations due to sensing errors. Once abnormal data is detected and deleted, the target parameters in the lean solution can be re-acquired and analyzed.

[0059] Determining the presence of abnormal data based on the correlation between UV absorbance, ion chromatography values, and conductivity involves: acquiring historical data including multiple data points, each containing conductivity, UV absorbance, and ion chromatography values; performing spatial clustering on the data points to obtain cluster centers and cluster radii; determining the current spatial location of the current conductivity, UV absorbance, and ion chromatography values; calculating whether the distance between the current location and the cluster center is greater than the cluster radius; if so, then the current conductivity, UV absorbance, and ion chromatography values ​​are determined to be abnormal data.

[0060] In addition, a triangular correlation matrix of conductivity-UV absorbance-ion chromatography values ​​can be established, and data exceeding the confidence interval are discarded. This invention does not limit the method of data cleaning.

[0061] S102. Obtain environmental parameters and liquid parameters of the lean solution.

[0062] Environmental parameters include the current ambient temperature and pressure, while liquid parameters include CO2 concentration and liquid flow rate.

[0063] S103. Determine the current temperature and pressure compensation coefficient based on environmental parameters.

[0064] The temperature and pressure compensation coefficient is used to compensate for deviations in the amine degradation rate under certain specific temperature and pressure conditions. Amine degradation is affected by temperature and pressure; higher temperatures accelerate the thermal degradation of amines. Pressure primarily affects the amine degradation rate by altering the solubility of CO2 in the liquid phase; higher pressure increases the amount of CO2 that can be dissolved. Therefore, this embodiment also determines the current temperature and pressure compensation coefficient based on the current ambient temperature and pressure, which can improve the accuracy of the amine degradation rate calculation.

[0065] Specifically, the impact of temperature and pressure on the degradation rate of amine liquid can be determined based on historical data, and then the temperature and pressure compensation coefficient corresponding to each temperature and pressure data set can be determined. Finally, the corresponding temperature and pressure compensation coefficient can be determined based on the current ambient temperature and pressure.

[0066] Optionally, the temperature and pressure compensation coefficient is calculated using the following formula:

[0067] δ(T,P)=k1×(TT base )+k2×(PP base )+k3×(TT base (PP) base );

[0068] Where δ(T,P) is the temperature and pressure compensation coefficient, T base P base These represent the preset reference temperature and reference pressure, respectively; T and P represent the current ambient temperature and pressure, respectively; and k1, k2, and k3 are preset compensation coefficients. The preset compensation coefficients are calibrated through accelerated aging experiments in the laboratory, but also require continuous monitoring and adjustment based on actual application data. Reference temperature T base It can be set to 25℃, with a reference pressure P. base It can be set to 1.0 bar.

[0069] It should also be noted that the temperature and pressure compensation coefficient is the compensation data given relative to the ambient reference temperature and reference pressure. In other words, when the actual ambient temperature and pressure are the ambient reference temperature and reference pressure respectively, there is no need to consider the adjustment effect of the temperature and pressure compensation coefficient, that is, the temperature and pressure compensation coefficient is 0.

[0070] S104. Input the environmental parameters and liquid parameters into the trained algorithm model to obtain the weight coefficients corresponding to each type of target parameter.

[0071] Environmental parameters include temperature and pressure, while liquid parameters include CO2 concentration and liquid flow rate.

[0072] Optionally, the algorithm model is a Long Short-Term Memory network, and the training process of the algorithm model is as follows:

[0073] Acquire training data including multiple data points. Each data point includes target parameters, concentration differences corresponding to the target parameters, environmental parameters, and liquid parameters of the lean solution. The concentration difference is the difference between the concentration of the effective component in the initial amine solution and the concentration of the effective component in the current amine solution.

[0074] The actual amine solution degradation rate was calculated based on the concentration difference and the concentration of effective components in the initial amine solution.

[0075] Initialize the model parameters of the algorithm model;

[0076] The environmental parameters and the liquid parameters of the lean solution from the data points are input into the algorithm model in sequence to obtain the prediction weight coefficients corresponding to each target parameter.

[0077] The predicted amine degradation rate is calculated based on the predicted weighting coefficients and target parameters.

[0078] The prediction error is determined based on the preset amine liquid degradation rate and the actual amine liquid degradation rate.

[0079] Determine whether the prediction error is within the preset error range;

[0080] If so, then the algorithm model training is complete;

[0081] If not, adjust the model parameters of the algorithm model based on the prediction error, and return to the steps of sequentially inputting the environmental parameters and the liquid parameters of the low-lying solution from the data points into the algorithm model.

[0082] Through the training process described above, the algorithm model learns the correlation between the weight coefficients of each type of target parameter and environmental and liquid parameters in order to obtain the correct amine degradation rate. Based on this, the weight coefficients are predicted by the machine learning model and can be automatically adjusted according to changes in environmental or liquid parameters, avoiding the static limitations of traditional manual weight setting and thus improving computational accuracy.

[0083] S105. Calculate the current amine degradation rate of the lean solution based on the temperature and pressure compensation coefficient, the target parameters, and the weighting coefficients corresponding to each type of target parameter.

[0084] The amine degradation rate represents the total percentage of loss of active ingredients in the amine solution [such as monoethanolamine (MEA) and piperazine (PZ)] due to oxidation, thermal degradation, and reaction with impurities.

[0085] Since nitrosamines and anions are substances generated after amine degradation, and conductivity is positively correlated with their concentrations, the amine degradation rate is positively correlated with conductivity and the concentrations of nitrosamines and anions. After obtaining the target parameters, the amine degradation rate of the current lean solution can be calculated based on the temperature and pressure compensation coefficient, the target parameters, and the weighting coefficients corresponding to each type of target parameter.

[0086] Optionally, the amine degradation rate can be calculated using the following formula:

[0087] D = α × σ + β × A UV +γ×C HCOO- +δ(T,P);

[0088] Where D is the amine degradation rate, σ is the conductivity, and A UV C represents the concentration of nitrosamines. HCOO- denoted as α, β, and γ, respectively, and δ(T,P) is the temperature and pressure compensation coefficient.

[0089] S106. Implement an amine concentration control strategy based on the amine degradation rate.

[0090] Specifically, the process includes: if the amine degradation rate is higher than a preset first alarm threshold, a amine purification command is generated; if the amine degradation rate is higher than a preset second alarm threshold, the rate of increase of the amine degradation rate relative to the initial concentration is calculated; when the rate of increase is greater than a preset increase threshold, an interlock shutdown is initiated and a amine replacement command is generated.

[0091] The first alarm threshold can be set to 10%~15%. When the degradation rate of amine solution is higher than the preset first alarm threshold, the amine solution purification system will be started. The second alarm threshold can be set to 20%~25%. The rising threshold is set to 20%. When the concentration increases by 20% relative to the initial value, the system will be interlocked and shut down, and the amine solution of the entire system will be replaced.

[0092] This invention provides an online monitoring method for amine degradation rate. First, the lean liquid after desorption from the rich liquid is sampled and analyzed to obtain target parameters, including conductivity, nitramine concentration, and acid anion concentration. Environmental parameters and liquid parameters of the lean liquid are then acquired. Environmental parameters include current temperature and pressure, while liquid parameters include CO2 concentration and flow rate. A temperature and pressure compensation coefficient is determined based on the environmental parameters. The environmental and liquid parameters are input into a trained algorithm model to obtain weight coefficients corresponding to each type of target parameter. The amine degradation rate of the lean liquid is calculated based on the temperature and pressure compensation coefficient, the target parameters, and the weight coefficients for each type of target parameter. Finally, an amine concentration control strategy is implemented based on the amine degradation rate. First, this scheme takes into account the errors caused by temperature and pressure changes when calculating the amine degradation rate, and therefore sets a temperature and pressure compensation coefficient, which can improve the detection accuracy. Second, compared with a fixed weighting coefficient, dynamically adjusting the weighting coefficient of the target parameter according to the current environmental and liquid parameters can obtain a more accurate weighting coefficient. Third, calculating the amine degradation rate by using the weighting coefficient and the corresponding detection data can quickly obtain the final result, which greatly shortens the detection cycle and is conducive to real-time guidance of the carbon capture process.

[0093] Figure 2 This is a schematic diagram of an online monitoring system for amine degradation rate provided in an embodiment of the present invention. Figure 2 As shown, the online monitoring system for amine liquid degradation rate includes:

[0094] The sampling and analysis module 201 is used to sample and analyze the lean liquid after the rich liquid is desorbed to obtain target parameters, including conductivity, concentration of nitramines and concentration of acid radicals.

[0095] The parameter acquisition module 202 is used to acquire environmental parameters and liquid parameters of the lean solution. The environmental parameters include the current temperature and pressure, and the liquid parameters include CO2 concentration and liquid flow rate.

[0096] Temperature and pressure compensation coefficient determination module 203 is used to determine the current temperature and pressure compensation coefficient based on the environmental parameters;

[0097] The weight coefficient determination module 204 is used to input the environmental parameters and the liquid parameters into the trained algorithm model to obtain the weight coefficients corresponding to each type of target parameter;

[0098] The amine degradation rate calculation module 205 is used to calculate the current amine degradation rate of the lean solution based on the temperature and pressure compensation coefficient, the target parameter, and the weighting coefficient corresponding to each type of the target parameter.

[0099] The execution module 206 is used to execute an amine concentration control strategy based on the amine degradation rate.

[0100] Optionally, the sampling and analysis module 201 includes an online ultraviolet spectroscopy module, an online micro ion chromatography module, and an online conductivity module.

[0101] The online ultraviolet spectroscopy module is used to detect the ultraviolet absorbance of the low-supply solution;

[0102] The online micro ion chromatography module is used to detect ion chromatography values ​​in the lean solution;

[0103] The linear conductivity module is used to detect the conductivity of the low-conductivity solution;

[0104] The sampling analysis module 201 further includes:

[0105] The concentration detection submodule is used to determine the concentration of nitramines based on the ultraviolet absorbance and to determine the concentration of acid radicals based on the ion chromatography values.

[0106] Optionally, the sampling analysis module 201 further includes:

[0107] The abnormal data judgment submodule is used to determine whether there is abnormal data based on the correlation between the ultraviolet absorbance, the ion chromatography value and the conductivity; if so, the contents of the abnormal data deletion submodule are executed.

[0108] The abnormal data deletion submodule is used to delete the current abnormal data.

[0109] Optionally, the abnormal data judgment submodule includes:

[0110] The historical data acquisition unit is used to acquire historical data including multiple data points, each of which includes conductivity, ultraviolet absorbance and ion chromatography values.

[0111] Clustering unit, used to perform spatial clustering of the data points to obtain cluster center and cluster radius;

[0112] A point determination unit is used to determine the current point in space of the current conductivity, the ultraviolet absorbance, and the ion chromatography values;

[0113] The point distance judgment unit is used to calculate whether the distance between the current point and the cluster center is greater than the cluster radius; if so, the contents of the abnormal data determination unit are executed.

[0114] An abnormal data determination unit is used to determine that the current conductivity, ultraviolet absorbance, and ion chromatography values ​​are abnormal data.

[0115] Optionally, the temperature and pressure compensation coefficient is calculated using the following formula:

[0116] δ(T,P)=k1×(TT base )+k2×(PP base )+k3×(TT base (PP) base );

[0117] Where δ(T,P) is the temperature and pressure compensation coefficient, T base P base These are the preset reference temperature and reference pressure, respectively; T and P are the current ambient temperature and pressure, respectively; and k1, k2, and k3 are the preset compensation coefficients.

[0118] Optionally, the amine degradation rate is calculated using the following formula:

[0119] D = α × σ + β × A UV +γ×C HCOO- +δ(T,P);

[0120] Where D is the amine degradation rate, σ is the conductivity, and A UV C represents the concentration of nitrosamines. HCOO- denoted as α, β, and γ, respectively, and δ(T,P) is the temperature and pressure compensation coefficient.

[0121] Optionally, the execution module 206 includes:

[0122] The first execution submodule is used to generate a purification command for amine liquid if the degradation rate of the amine liquid is higher than a preset first alarm threshold.

[0123] The rate of increase monitoring submodule is used to calculate the rate of increase of the amine degradation rate relative to the initial concentration if the amine degradation rate is higher than a preset second alarm threshold.

[0124] The second execution submodule is used to interlock and stop the machine and generate a command to replace the amine solution when the rise rate is greater than a preset rise threshold.

[0125] The online monitoring system for amine degradation rate provided in this embodiment of the invention can execute the online monitoring method for amine degradation rate provided in any embodiment of the invention, and has the corresponding functional modules and beneficial effects of the method.

[0126] Figure 3A schematic diagram of an electronic device 40 that can be used to implement embodiments of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the invention described and / or claimed herein.

[0127] like Figure 3 As shown, the electronic device 40 includes at least one processor 41 and a memory, such as a read-only memory (ROM) 42 or a random access memory (RAM) 43, communicatively connected to the at least one processor 41. The memory stores computer programs executable by the at least one processor. The processor 41 can perform various appropriate actions and processes based on the computer program stored in the ROM 42 or loaded from storage unit 48 into the RAM 43. The RAM 43 may also store various programs and data required for the operation of the electronic device 40. The processor 41, ROM 42, and RAM 43 are interconnected via a bus 44. An input / output (I / O) interface 45 is also connected to the bus 44.

[0128] Multiple components in electronic device 40 are connected to I / O interface 45, including: input unit 46, such as keyboard, mouse, etc.; output unit 47, such as various types of monitors, speakers, etc.; storage unit 48, such as disk, optical disk, etc.; and communication unit 49, such as network card, modem, wireless transceiver, etc. Communication unit 49 allows electronic device 40 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0129] Processor 41 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 41 include, but are not limited to, central processing unit (CPU), graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, digital signal processors (DSPs), and any suitable processor, controller, microcontroller, etc. Processor 41 performs the various methods and processes described above, such as the online monitoring method for amine degradation rate.

[0130] In some embodiments, the online monitoring method for amine degradation rate can be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 48. In some embodiments, part or all of the computer program can be loaded and / or installed on electronic device 40 via ROM 42 and / or communication unit 49. When the computer program is loaded into RAM 43 and executed by processor 41, one or more steps of the online monitoring method for amine degradation rate described above can be performed. Alternatively, in other embodiments, processor 41 can be configured to perform the online monitoring method for amine degradation rate by any other suitable means (e.g., by means of firmware).

[0131] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), complex programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations may include: implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0132] Computer programs used to implement the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when executed by the processor, the computer programs cause the functions / operations specified in the flowcharts and / or block diagrams to be performed. The computer programs may be executed entirely on a machine, partially on a machine, or as a standalone software package, partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0133] In the context of this invention, a computer-readable storage medium can be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination thereof. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0134] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0135] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or middleware components (e.g., application servers), or frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include local area networks (LANs), wide area networks (WANs), blockchain networks, and the Internet.

[0136] A computing system can include clients and servers. Clients and servers are generally located far apart and typically interact through communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a hosting product within the cloud computing service system to address the shortcomings of traditional physical hosts and VPS services, such as high management difficulty and weak business scalability.

[0137] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this invention can be achieved, and this is not limited herein.

[0138] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. A method for online monitoring of amine degradation rate, characterized in that, The method, applied to an online monitoring system for amine degradation rate, includes: The lean liquid after desorption of the rich liquid was sampled and analyzed to obtain target parameters, including conductivity, concentration of nitramines and concentration of acid anions; The environmental parameters and the liquid parameters of the lean solution are obtained. The environmental parameters include the current ambient temperature and pressure, and the liquid parameters include CO2 concentration and liquid flow rate. Determine the current temperature and pressure compensation coefficient based on the environmental parameters; The environmental parameters and the liquid parameters are input into the trained algorithm model to obtain the weight coefficients corresponding to the target parameters of each type; The amine degradation rate of the current lean solution is calculated based on the temperature and pressure compensation coefficient, the target parameter, and the weighting coefficient corresponding to the target parameter for each type. An amine concentration control strategy is implemented based on the amine degradation rate.

2. The method as described in claim 1, characterized in that, The online monitoring system for amine degradation rate includes an online ultraviolet spectroscopy module, an online micro ion chromatography module, and an online conductivity module. The sampling and analysis of the lean liquid after desorption of the rich liquid to obtain target parameters includes: The UV absorbance of the low-energy solution was detected using the online UV spectroscopy module. The ion chromatographic values ​​of the lean solution were detected using the online micro ion chromatography module. The conductivity of the lean solution is detected by the linear conductivity module. The concentration of nitramines is determined based on the ultraviolet absorbance, and the concentration of acid radicals is determined based on the ion chromatography values.

3. The method as described in claim 2, characterized in that, After detecting the conductivity of the lean solution using the linear conductivity module, the method further includes: The presence of abnormal data is determined based on the correlation between the ultraviolet absorbance, the ion chromatography values, and the conductivity. If so, delete the current abnormal data.

4. The method as described in claim 3, characterized in that, The step of determining whether there is abnormal data based on the correlation between the ultraviolet absorbance, the ion chromatography value, and the conductivity includes: Acquire historical data including multiple data points, each of which includes conductivity, ultraviolet absorbance, and ion chromatography values; Spatial clustering is performed on the data points to obtain cluster centers and cluster radii; Determine the current position of the current conductivity, ultraviolet absorbance, and ion chromatography values ​​in space; Calculate whether the distance between the current point and the cluster center is greater than the cluster radius; If so, then the current conductivity, ultraviolet absorbance, and ion chromatography values ​​are determined to be abnormal data.

5. The method as described in claim 1, characterized in that, The temperature and pressure compensation coefficient is calculated using the following formula: δ(T,P)=k1×(T-T base )+k2×(P-P base )+k3×(T-T base )(P-P base ); Where δ(T,P) is the temperature and pressure compensation coefficient, T base P base These are the preset reference temperature and reference pressure, respectively; T and P are the current ambient temperature and pressure, respectively; and k1, k2, and k3 are the preset compensation coefficients.

6. The method as described in claim 1, characterized in that, The amine degradation rate is calculated using the following formula: D=α×σ+β×A UV +γ×C HCOO- +δ(T,P); Where D is the amine degradation rate, σ is the conductivity, and A UV C represents the concentration of nitrosamines. HCOO- denoted as α, β, and γ, respectively, and δ(T,P) is the temperature and pressure compensation coefficient.

7. The method according to any one of claims 1-6, characterized in that, The step of implementing an amine concentration control strategy based on the amine degradation rate includes: If the degradation rate of the amine liquid is higher than the preset first alarm threshold, a purification command for the amine liquid is generated. If the amine degradation rate is higher than the preset second alarm threshold, then the rate of increase of the amine degradation rate relative to the initial concentration is calculated; When the rate of increase exceeds a preset threshold, the system is interlocked and shut down, and a command to replace the amine solution is generated.

8. An online monitoring system for amine liquid degradation rate, characterized in that, include: The sampling and analysis module is used to sample and analyze the lean liquid after the rich liquid is desorbed to obtain target parameters, including conductivity, concentration of nitramines and concentration of acid radicals. The parameter acquisition module is used to acquire environmental parameters and liquid parameters of the lean solution. The environmental parameters include the current ambient temperature and pressure, and the liquid parameters include CO2 concentration and liquid flow rate. The temperature and pressure compensation coefficient determination module is used to determine the current temperature and pressure compensation coefficient based on the environmental parameters. The weight coefficient determination module is used to input the environmental parameters and the liquid parameters into the trained algorithm model to obtain the weight coefficients corresponding to each type of target parameter; The amine degradation rate calculation module is used to calculate the current amine degradation rate of the lean solution based on the temperature and pressure compensation coefficient, the target parameter, and the weighting coefficient corresponding to each type of the target parameter. An execution module is used to execute an amine concentration control strategy based on the amine degradation rate.

9. An electronic device, characterized in that, The electronic device includes: At least one processor; and A memory communicatively connected to the at least one processor; wherein, The memory stores a computer program that can be executed by the at least one processor, the computer program being executed by the at least one processor to enable the at least one processor to perform the online monitoring method for amine liquid degradation rate according to any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions that cause a processor to execute the online monitoring method for amine degradation rate according to any one of claims 1-7.

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