Operation control method of adsorption system and adsorption system

Abstract

The embodiment of the invention provides an operation control method of an adsorption system and the adsorption system, and relates to the technical field of wastewater treatment. According to the method, operation parameters of a target adsorption column are obtained in real time, the operation parameters comprise the inlet concentration and the outlet concentration of target pollutants, the liquid flow and the accumulative treatment liquid volume, based on the operation parameters obtained in real time, parameters of an adsorption penetration prediction model are dynamically updated through online data fitting, and based on the parameters of the adsorption penetration prediction model, the adsorption penetration prediction model is obtained. According to the preset penetration concentration, the inlet concentration and the liquid flow, calculating the residual effective operation time of the target adsorption column, and when the residual effective operation time is smaller than a first preset time threshold value, prompting to prepare for regeneration and / or start a preparation program of a standby adsorption column. Therefore, dynamic and accurate prediction of the penetration time of the adsorption column can be realized, and the problem of prediction deviation caused by neglecting of resin performance attenuation and working condition fluctuation in a traditional fixed period or threshold value control method is solved.

Description

Technical Field

[0001] This invention relates to the field of wastewater treatment technology, and more specifically, to an operation control method for an adsorption system and an adsorption system. Background Technology

[0002] Fixed-bed adsorption technology is widely used in hydrometallurgy, chemical separation, and advanced wastewater treatment due to its selective removal capabilities for target metal ions. Particularly in the production of lithium iron phosphate battery precursors, trace amounts of copper ions present in the raw material ferric phosphate solution, if not effectively removed, will introduce impurities into the final product, significantly affecting the electrochemical performance and thermal stability of the cathode material. Therefore, developing efficient adsorption processes to achieve deep removal of copper ions is of significant engineering importance.

[0003] Currently, chelating resins rely on their ability to chelate Cu²⁺ + Its high selectivity and large partition coefficient characteristics have made it a major technical means for copper removal in industry. However, in practical engineering applications, especially for copper with high viscosity and rich in Fe³⁺, [further challenges exist]. + With PO4³ - Furthermore, traditional adsorption processes for phosphorus-iron liquid systems, which are prone to hydrolysis, exhibit significant technical limitations. They lack dynamic prediction capabilities and rely solely on manual intervention or simple interlocking control based on preset fixed operating cycles or outlet concentration thresholds. They fail to establish breakthrough prediction models based on real-time operating conditions, making it impossible to adaptively adjust to resin performance degradation and fluid property changes (such as increased viscosity). This technical deficiency leads to the accumulation of prediction errors as the operating cycle lengthens, ultimately rendering the prediction results worthless for engineering guidance. Summary of the Invention

[0004] In view of this, the object of the present invention is to provide an operation control method for an adsorption system and an adsorption system to at least partially improve the above-mentioned problems.

[0005] To achieve the above objectives, the technical solutions adopted in the embodiments of the present invention are as follows: In a first aspect, embodiments of the present invention provide an operation control method for an adsorption system, the adsorption system comprising at least two adsorption columns, the method comprising: The operating parameters of the target adsorption column are acquired in real time. The operating parameters include the inlet and outlet concentrations of the target pollutant, the liquid flow rate, and the cumulative volume of liquid treated. The target adsorption column is the adsorption column that is currently in adsorption operation. Based on the real-time acquired operating parameters, the parameters of the adsorption penetration prediction model are dynamically updated through online data fitting. Based on the parameters of the adsorption breakthrough prediction model, the remaining effective operating time of the target adsorption column is calculated according to the preset breakthrough concentration, the inlet concentration, and the liquid flow rate. When the remaining effective operating time is less than the first preset time threshold, a prompt is made to prepare for regeneration and / or to start the preparatory procedure for the backup adsorption column.

[0006] Optionally, the step of obtaining the outlet concentration includes: The liquid flowing out of the target adsorption column is sampled and pretreated online to obtain a pretreated sample. The sample is analyzed using a first spectral analysis technique to obtain a first concentration value of the target pollutant; When the first concentration value reaches the preset concentration, the sample is detected using a second spectral analysis technique to obtain a second concentration value of the target pollutant; the monitoring accuracy of the second spectral analysis technique is higher than that of the first spectral analysis technique. The outlet concentration is determined based on the first concentration value and the second concentration value.

[0007] Optionally, the adsorption breakthrough prediction model is a linear model obtained by linearizing the Thomas adsorption kinetics model; the linear model is:

[0008] Where A and B are parameters that are dynamically updated through fitting. The cumulative volume of liquid processed. The aforementioned inlet concentration, The outlet concentration is mentioned.

[0009] Optionally, the step of dynamically updating the parameters of the adsorption penetration prediction model based on the real-time acquired operating parameters through online data fitting includes: At preset fixed time intervals, data points that meet the effective concentration range conditions are selected from historical operating data; each data point includes inlet concentration, outlet concentration, and cumulative treated liquid volume; the effective concentration range condition is that the ratio of the outlet concentration to the inlet concentration is between a first ratio threshold and a second ratio threshold. The selected data points are fitted using a linear regression method to update the parameters A and B of the adsorption penetration prediction model.

[0010] Optionally, the calculation of the remaining effective operating time of the target adsorption column based on the parameters of the adsorption breakthrough prediction model, according to the preset breakthrough concentration, the inlet concentration, and the liquid flow rate, includes: Substitute the preset breakthrough concentration and the inlet concentration into the adsorption breakthrough prediction model to calculate the volume of liquid that has been treated when the preset breakthrough concentration is reached. The remaining liquid volume is obtained by subtracting the current cumulative liquid volume processed from the volume of liquid that has been penetrated. The remaining effective operating time of the target adsorption column is obtained by dividing the remaining treatment liquid volume by the liquid flow rate.

[0011] Optionally, the adsorption system further includes a pulse backflush device and a stirring device; the method further includes: When the outlet concentration is between a first preset concentration threshold and a second preset concentration threshold, the pulse backflush device and / or the stirring device are activated. When the outlet concentration is greater than the second preset concentration threshold or the remaining effective operating time is less than the second preset time threshold, the feed valve of the target adsorption column is closed, the standby adsorption column is switched, and the target adsorption column is regenerated.

[0012] Optionally, after the step of regenerating the target adsorption column, the method further includes: Record the actual total amount of target pollutants removed by the target adsorption column during this adsorption cycle; Based on the actual total adsorption amount of the current and at least one historical adsorption cycle, an effective adsorption capacity decay model for the target adsorption column is constructed, and the corresponding capacity decay coefficient is calculated; the capacity decay coefficient is used to characterize the degradation trend of the adsorption performance of the adsorption material with the number of uses.

[0013] Optionally, the regeneration process of the target adsorption column includes: The amount of regenerant is dynamically adjusted according to the capacity decay coefficient. The target adsorption column was regenerated using an adjusted regeneration dose.

[0014] Optionally, the method further includes: Real-time monitoring of the bed pressure drop of the target adsorption column; When the pressure drop in the bed exceeds a preset differential pressure threshold, the pulse backflush device is activated.

[0015] Secondly, embodiments of the present invention provide an adsorption system, comprising: At least two switchable adsorption columns are used to adsorb and treat the target pollutants. A pulse backflush device located at the bottom of the adsorption column is used to agitate the adsorption bed by intermittent upward fluid pulses. A low-speed stirring device located inside the adsorption column is used to generate gentle shear force during the adsorption process to promote uniform distribution of the adsorbent material. Multiple sensors, including flow meters, pressure sensors, and an online heavy metal detection unit, are used to collect liquid flow rate, bed pressure drop, and target pollutant concentration in real time, respectively. The control unit is communicatively connected to all of the aforementioned sensors and actuators for performing the method as described in any of the first aspects.

[0016] The present invention provides an operation control method and adsorption system for an adsorption system. By collecting operating parameters in real time and dynamically fitting and updating the adsorption breakthrough prediction model, it achieves adaptive and accurate prediction of the remaining effective operating time of the adsorption column. This overcomes the shortcomings of traditional control strategies, such as prediction lag and inappropriate regeneration timing under complex operating conditions. It can provide timely warning and initiate switching or regeneration preparation before the adsorbent material approaches breakthrough, significantly improving the continuity, stability and automation level of system operation, and enhancing processing efficiency and adsorbent material utilization.

[0017] To make the above-mentioned objectives, features and advantages of this application more apparent and understandable, preferred embodiments are described below in detail with reference to the accompanying drawings. Attached Figure Description

[0018] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of the present invention and should not be regarded as a limitation on the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0019] Figure 1 A schematic structural block diagram of an electronic device provided in an embodiment of the present invention; Figure 2 A schematic flowchart illustrating an operation control method for an adsorption system provided in an embodiment of the present invention; Figure 3 This is a schematic diagram of an adsorption system provided in an embodiment of the present invention; Figure 4 This is another schematic flowchart of an operation control method for an adsorption system provided in an embodiment of the present invention; Figure 5 This is another schematic flowchart of an operation control method for an adsorption system provided in an embodiment of the present invention.

[0020] Icons: 100 - Electronic device; 101 - Memory; 102 - Communication interface; 103 - Processor; 104 - Communication bus; 30 - Adsorption system; 31 - Adsorption column; 32 - Feed valve. Detailed Implementation

[0021] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, 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. The components of the embodiments of the present invention described and shown in the accompanying drawings can generally be arranged and designed in various different configurations.

[0022] Therefore, the following detailed description of the embodiments of the invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely to illustrate selected embodiments of the invention. All other embodiments obtained by those skilled in the art based on the embodiments of the invention without inventive effort are within the scope of protection of the invention.

[0023] It should be noted that similar reference numerals and letters in the following figures indicate similar items; therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures. Furthermore, in the description of this invention, terms such as "first," "second," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0024] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0025] In existing technologies, for high-viscosity, easily hydrolyzed phosphorus-iron liquid systems, traditional adsorption systems generally rely on fixed operating cycles or simple outlet concentration thresholds to trigger regeneration. They lack the ability to dynamically perceive and respond to changes in actual operating conditions, resulting in inaccurate breakthrough prediction, premature or delayed regeneration, low resin utilization, high risk of effluent water quality, increased operating costs, and difficulty in achieving continuous and stable production.

[0026] Based on the above, embodiments of the present invention provide an operation control method and an adsorption system for an adsorption system. By acquiring key parameters such as the inlet concentration, outlet concentration, liquid flow rate, and cumulative treatment volume of the target adsorption column in real time, and combining online data fitting to dynamically update the adsorption breakthrough prediction model, the remaining effective operating time is accurately calculated. When a preset warning threshold is reached, the system automatically prompts for regeneration preparation or starts a backup adsorption column, thereby achieving a leap from "experience-driven" to "model-driven" and significantly improving the system's intelligence level and operational reliability.

[0027] To implement the process steps and functions of the various examples of this invention, please refer to [link / reference]. Figure 1 , Figure 1 This is a schematic structural block diagram of an electronic device provided in an embodiment of the present invention. The electronic device 100 includes a memory 101 and a processor 103, which are electrically connected directly or indirectly to each other to achieve data transmission or interaction. For example, these components can be electrically connected to each other through one or more communication buses 104 or signal lines. The memory 101 can be used to store software programs and modules, and the processor 103 executes the software programs and modules stored in the memory 101, thereby performing various functional applications and data processing.

[0028] Electronic device 100 can be, but is not limited to, a personal computer (PC), a server, a distributed computer, etc. It is understood that electronic device 100 is not limited to a physical server, but can also be a virtual machine on a physical server, a virtual machine built on a cloud platform, or any other computer that can provide the same functionality as the server or virtual machine. The operating system of electronic device 100 can be, but is not limited to, Windows, Linux, etc.

[0029] The memory 101 may be, but is not limited to, random access memory (RAM), read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), etc.

[0030] The communication connection between the electronic device 100 and external devices is achieved through at least one communication interface 102 (which can be wired or wireless).

[0031] Processor 103 may be an integrated circuit chip with signal processing capabilities. In implementation, the steps of this embodiment can be completed by integrated logic circuits in the hardware of processor 103 or by instructions in software form. Processor 103 may be a general-purpose processor, including a Central Processing Unit (CPU), a Network Processor (NP), etc.; it may also be a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field-Programmable Gate Array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components.

[0032] Understandable. Figure 1 The structure shown is for illustrative purposes only; the electronic device 100 may also include components that are more advanced than those shown. Figure 1 The more or fewer components shown, or having the same Figure 1 The different configurations shown. Figure 1 The components shown can be implemented using hardware, software, or a combination thereof.

[0033] The following is an exemplary description of the operation control method for the adsorption system provided by the present invention. See also... Figure 2 The subject executing this method can be one of the above. Figure 1 The electronic device 100 shown is described in the following document. Figure 3 The adsorption system 30 includes at least two adsorption columns 31. Each adsorption column can be switched via valves to operate in series or in parallel, supporting alternating operation under multiple working conditions during continuous production, including adsorption by the main column, standby column, and regeneration of the failed column. At any given time, one or a group of adsorption columns serves as the target adsorption column and undertakes the main adsorption task.

[0034] The method includes, for example Figure 2 The following steps are described: S210: Real-time acquisition of the operating parameters of the target adsorption column; wherein, the operating parameters include the inlet and outlet concentrations of the target pollutant, the liquid flow rate and the cumulative treated liquid volume, and the target adsorption column is the adsorption column currently in adsorption operation.

[0035] S220: Based on real-time acquired operating parameters, the parameters of the adsorption penetration prediction model are dynamically updated through online data fitting.

[0036] S230: Based on the parameters of the adsorption breakthrough prediction model, and according to the preset breakthrough concentration, inlet concentration and liquid flow rate, calculate the remaining effective operating time of the target adsorption column.

[0037] S240: When the remaining effective running time is less than the first preset time threshold, prompt the user to prepare for regeneration and / or start the preparatory procedure for the backup adsorption column.

[0038] By integrating various sensors into the system pipelines and adsorption columns, key operating parameters of the target adsorption column during its current adsorption operation are continuously collected. These operating parameters include at least: the inlet and outlet concentrations of the target pollutant, the liquid flow rate, and the cumulative treated liquid volume. This data is uploaded to the central controller periodically or in real-time via a signal transmission module, forming a dynamically updated data stream that provides the input basis for subsequent model calculations.

[0039] The built-in adsorption kinetics model is invoked, and using actual operating data from the current and historical time periods, the key parameters of the model are fitted and corrected online using the least squares method or other regression algorithms. This process is executed periodically (e.g., every 10–30 minutes) to ensure that the model always reflects the true situation of the current resin performance, fluid state, and mass transfer conditions, and has good adaptability.

[0040] After the model parameters are updated, the preset breakthrough concentration standard (e.g., the effluent copper ion concentration does not exceed 3 mg / L) is substituted into the model. Combined with the current inlet concentration and liquid flow rate, the time required to reach the breakthrough point is calculated. Subtracting the already running time, the remaining effective time for the target adsorption column to operate safely is obtained. This value is dynamically updated, intuitively reflecting the risk level of the equipment approaching breakthrough.

[0041] When the remaining effective operating time is determined to be less than the set safety margin (e.g., 2 hours), an early warning mechanism is automatically triggered. On the one hand, it sends audible and visual or text message prompts to the operators, reminding them to prepare for resin regeneration; on the other hand, it can pre-activate the pre-start preparation procedures such as flushing and venting of the backup adsorption column, ensuring a seamless switchover before the main column fails, and guaranteeing the continuous and stable operation of the entire system.

[0042] This method achieves intelligent management of the adsorption process by constructing a closed-loop control logic of "real-time perception - dynamic modeling - accurate prediction - pre-response", which significantly improves the reliability and processing efficiency of the system operation. It is especially suitable for deep purification scenarios with complex composition, easy hydrolysis and precipitation, high viscosity and other harsh working conditions.

[0043] In this embodiment, the liquid to be treated is ferric phosphorus solution, the target pollutant is copper ions, and the adsorption material is resin.

[0044] The concentration of the target pollutant at the point of entry can be detected, or the concentration of the target pollutant in the liquid to be treated can be used directly.

[0045] To further improve the accuracy and reliability of target pollutant outlet concentration detection, especially in the critical stage near the breakthrough point in the later stage of the adsorption process, this invention provides a dual-mode synergistic online detection method. Accordingly, the steps for obtaining the outlet concentration may include: S211: Perform online sampling and pretreatment of the liquid flowing out of the target adsorption column to obtain the pretreated sample.

[0046] A sampling port is set on the outlet pipeline of the target adsorption column, which is connected to the bypass line and integrates an automatic precision dilution device and a high-temperature and high-pressure self-cleaning filter. The filter can remove solid suspended matter in the phosphorus iron solution that may interfere with the detection. An online complexing agent addition device can also be configured to add 0.1-1.0 g / L of EDTA or citric acid complexing agent to prevent copper ion hydrolysis and precipitation, and ensure detection accuracy.

[0047] S212: The first spectral analysis technique is used to detect the sample and obtain the first concentration value of the target pollutant.

[0048] The pretreated sample flows through the first spectroscopic analysis device, which can be a UV-Vis spectrometer with a wavelength range of 200-800 nm, a detection limit ≤0.05 mg / L, and a response time ≤30 s. The copper ion concentration is calculated in real time using the absorbance value at a specific wavelength (250-300 nm), achieving high-frequency continuous monitoring. The detection result serves as the main signal source for the outlet concentration, used for model input and trend tracking under normal operating conditions.

[0049] S213: When the first concentration value reaches the preset concentration, the second spectral analysis technology is used to detect the sample to obtain the second concentration value of the target pollutant; the monitoring accuracy of the second spectral analysis technology is higher than that of the first spectral analysis technology.

[0050] When the monitored concentration value rises to a certain critical threshold (e.g., 80% of the preset breakthrough concentration, such as 2.4 mg / L), it is determined that the adsorption process has entered the breakthrough warning period, at which point a higher-precision auxiliary detection mechanism is automatically triggered. A second spectroscopic analysis device is then activated; this device can be a laser-induced breakdown spectrometer (LIBS), which performs re-analysis on the same or simultaneously acquired sample. LIBS technology, based on elemental atomic emission spectral line recognition, possesses advantages such as extremely low detection limits (down to 0.01 mg / L), strong resistance to matrix interference, and no need for complex standard calibration, making it suitable for the precise quantification of trace metals.

[0051] S214: Determine the outlet concentration based on the first and second concentration values.

[0052] The control system integrates the two detection results and uses weighted fusion, deviation correction, or master / slave switching strategies to ultimately determine the current outlet concentration value. For example, during normal operation, the UV-Vis detection value is the primary value; when the LIBS detection is activated, its result is used to correct the UV-Vis reading; if the difference between the two exceeds the set tolerance, a sensor malfunction alarm is issued, and the LIBS data is prioritized as the reliable input.

[0053] The above-mentioned dual-technology integration solution not only ensures the continuity and economy of daily monitoring, but also enhances the authority and decision reliability of the detection results during critical risk periods, providing high-quality input data for subsequent penetration prediction models and significantly enhancing the robustness and security of the entire control system.

[0054] The adsorption breakthrough prediction model in this embodiment of the invention can be a linear model obtained by linearizing the Thomas adsorption kinetics model.

[0055] The Thomas adsorption kinetic model is as follows:

[0056] in, Let t be the outlet concentration, in mg / L. The concentration at the inlet is mg / L; k is the Thomas rate constant (L / (mg·h)). M represents the saturated adsorption capacity of the resin, in mg / g; M represents the mass of the resin, in g. Let L be the cumulative volume of liquid processed up to time t.

[0057] Linearizing the Thomas adsorption kinetics model, we obtain:

[0058] Let A = B= Therefore, the final linear model is:

[0059] Where A and B are parameters that are dynamically updated through fitting. To accumulate the volume of liquid processed, This is the imported concentration. This refers to the export concentration.

[0060] By adopting this linearized model, not only is the computational burden on the embedded controller significantly reduced and real-time performance improved, but convergence failures that may arise from nonlinear fitting are also avoided, enhancing the system's stability and engineering practicality. At the same time, this model retains the physical foundation of the Thomas model, giving its predictions clear physical interpretation and long-term reliability.

[0061] To further improve the fitting accuracy and stability of the adsorption breakthrough prediction model and avoid interference from invalid or noisy data in parameter estimation, this invention provides a data processing method based on effective concentration range screening to optimize the online update process of model parameters. See also... Figure 4 Step S220 includes: S221: Select data points that meet the effective concentration range conditions from historical operating data at preset fixed time intervals; each data point includes inlet concentration, outlet concentration and cumulative treated liquid volume; the effective concentration range condition is: the ratio of outlet concentration to inlet concentration is between a first proportional threshold and a second proportional threshold.

[0062] S222: Use linear regression to fit the selected data points to update the parameters A and B of the adsorption penetration prediction model.

[0063] The control system triggers a model parameter update process at a fixed interval (e.g., every 15 minutes). During each execution, the system retrieves historical operational data from the most recent period, forming the dataset to be analyzed. To ensure the quality of the fit, only data points within the linear response region of the adsorption curve are selected for calculation.

[0064] Optionally, the first ratio threshold is set to 0.05, and the second ratio threshold is set to 0.95, meaning that only data points that meet the following conditions are retained: This interval excludes two unstable regions, when When approaching 0, It will be very big, when near hour, It is negative infinity.

[0065] Each valid data point is converted to the coordinates (x, y) required for linear fitting, where: .

[0066] The least squares method is used to perform linear regression on the transformed set of coordinate points {(x1,y2), (x2,y2),...} to obtain a fit of the form y=A B The optimal straight line for x is found, thus determining the latest model parameters A (intercept) and B (slope).

[0067] To transform the calculation results of the adsorption breakthrough prediction model into time parameters with direct operational guidance, this invention provides a calculation method that maps from the volume domain to the time domain, for accurately assessing the remaining effective operating time of the target adsorption column. See also... Figure 5 Step S230 may include the following sub-steps: S231: Substitute the preset breakthrough concentration and the inlet concentration into the adsorption breakthrough prediction model to calculate the volume of liquid that is treated when the preset breakthrough concentration is reached.

[0068] S232: Subtract the current cumulative processed liquid volume from the volume of liquid that has been processed to obtain the remaining processed liquid volume.

[0069] S233: Divide the remaining treatment liquid volume by the liquid flow rate to obtain the remaining effective operating time of the target adsorption column.

[0070] For example, the preset penetration concentration C 穿透 The concentration is 3 mg / L, and C t =C 穿透 Substituting into the Thomas model and rearranging the terms of the above model formula, the volume of liquid undergoing penetration treatment is obtained. V 穿透 The calculation formula:

[0071] Get the cumulative liquid volume V processed by the system at the current moment. 已处理 The remaining safe-to-handle liquid volume V 剩余 =V 穿透 -V 已处理 .

[0072] Obtain the current real-time flow rate Q of the liquid. The remaining effective operating time T of the target adsorption column. 剩余 = V 剩余 / Q.

[0073] To improve the operational stability of the adsorption system and prevent abnormal operating conditions such as resin bed caking, channeling, or short circuits caused by high-viscosity fluids, the adsorption system provided in this embodiment of the invention may also include a pulse backflush device and a stirring device, and combine a multi-parameter collaborative control strategy to achieve proactive intervention and preventive maintenance.

[0074] The pulse backflushing device is connected to the bottom of the target adsorption column. It controls the periodic introduction of reverse fluid impact through a pneumatic diaphragm valve, generating a brief but powerful upward water flow that disturbs the bottom resin, breaks the initially formed gel-like deposition structure, and restores the bed porosity.

[0075] The stirring device can be a low-speed anchor or propeller-type mechanical stirrer installed in the upper part of the adsorption column. Its speed is extremely low (e.g., 10–30 rpm) and it is only used to apply gentle shear force to promote the slow up and down circulation of resin particles, avoid the formation of static dead zones, and at the same time, not damage the resin particles.

[0076] Based on this, the method may further include: When the outlet concentration is between the first preset concentration threshold and the second preset concentration threshold, the pulse backflush device and / or stirring device are activated.

[0077] When the outlet concentration is greater than the second preset concentration threshold or the remaining effective operating time is less than the second preset time threshold, the feed valve 32 of the target adsorption column is closed, the standby adsorption column is switched, and the target adsorption column is regenerated.

[0078] When the outlet concentration is detected to rise above the first preset concentration threshold but not exceed the second preset concentration threshold (e.g., 2.0 mg / L), <C t If the concentration is ≤ 2.5 mg / L, the adsorption process is considered to have entered the mid-term warning stage, indicating a potential increase in local mass transfer resistance or a decrease in flowability. At this point, the control system automatically activates the pulse backflush device and / or stirring device to perform one or more rounds of enhanced perturbation operations. The pulse backflush frequency is 1–2 times / hour, with each pulse lasting 10–20 seconds. The backflush flow rate is 1.2–1.5 times the normal feed flow rate. The backflush fluid can be heated to 35–45℃ through a heat exchanger to reduce viscosity and improve the backflush effect.

[0079] The agitator is started and run for 1–2 minutes, then turned off, allowing the resin to settle naturally and return to a uniform distribution.

[0080] When the outlet concentration is greater than the second preset concentration threshold (e.g., C) t >2.5 mg / L); or the remaining effective running time is less than the second preset time threshold (e.g., T). 剩余 If the target adsorption column is nearing failure (less than 30 minutes), immediately execute a high-level response action: The feed valve of the adsorption column is automatically closed.

[0081] Switch the feed flow to the backup adsorption column to ensure continuous processing.

[0082] The regeneration process of the current column is started simultaneously, including steps such as evacuation, backwashing, acid regeneration, and rinsing.

[0083] In addition, to enhance system security redundancy, the method also includes: Real-time monitoring of bed pressure drop in the target adsorption column.

[0084] When the bed pressure drop exceeds the preset differential pressure threshold, the pulse backflush device is activated.

[0085] By installing high-precision pressure sensors at the top and bottom of the adsorption column, the pressure difference between the two ends is continuously collected to reflect the flow resistance state of the resin bed. As the operating time increases, if the resin surface adsorbs gel-like substances, hydrolysis products, or undergoes compression, the pressure drop of the bed will gradually increase.

[0086] When the bed pressure drop exceeds the preset differential pressure threshold (e.g., 0.6 MPa), the system automatically triggers the pulse backflushing device to perform a cleaning operation, regardless of whether the outlet concentration is abnormal. This mechanism is independent of the concentration detection path and forms a "physical state-driven" preventive protection layer, which is particularly suitable for dealing with sudden blockages or early caking problems.

[0087] Based on the above embodiments, in order to achieve refined management of the entire life cycle of adsorption materials and optimize regeneration process parameters, this invention provides a method for constructing an effective adsorption capacity decay model based on historical operating data, and a technical solution for dynamically adjusting the amount of regenerator accordingly.

[0088] After the step of regenerating the target adsorption column, the method may further include: Record the actual total amount of target pollutants removed by the target adsorption column during this adsorption cycle.

[0089] Based on the actual total adsorption capacity of the current adsorption cycle and at least one historical adsorption cycle, an effective adsorption capacity decay model for the target adsorption column is constructed, and the corresponding capacity decay coefficient is calculated. The capacity decay coefficient is used to characterize the degradation trend of the adsorption performance of the adsorption material with the number of uses.

[0090] After a complete adsorption-regeneration cycle, the total amount of target pollutants actually removed by the resin in this cycle is accurately calculated using the discrete integral method, based on the accumulated inlet and outlet concentrations, liquid flow rate, and operating time data collected during the cycle. :

[0091] in, The sampling time interval for the i-th data point. This is the actual total adsorption amount. As the core real data characterizing the resin's performance in this cycle, it is stored in the system's historical database.

[0092] Extract the actual total adsorption data of the current period and at least the most recent complete historical period from the database to form a sequence {M1, M2, ..., M}. N Based on this sequence, a decay model of the effective adsorption capacity is constructed using a data fitting method.

[0093] The attenuation model can be selected as a linear model. or exponential model The form is given by the system, where n is the period number and a, b, M0, k are fitting parameters. Through fitting, the system calculates a capacity decay coefficient used to quantify the performance decline trend. α (For example, the slope b in a linear model, or the decay constant k in an exponential model).

[0094] Traditional regeneration processes use a fixed amount of regenerant, which cannot adapt to dynamic changes in resin properties. Based on the real-time capacity decay coefficient... α By using a preset mapping relationship or optimization algorithm, the optimal amount of regenerant required for the next regeneration cycle is dynamically calculated and adjusted. Therefore, the steps for regenerating the target adsorption column can include: The amount of regenerant used is dynamically adjusted based on the capacity decay coefficient.

[0095] The target adsorption column was regenerated using an adjusted regeneration dose.

[0096] The dosage of regenerant is adjusted according to a preset regenerant dosage adjustment strategy. For example, the standard regenerant dosage is defined as follows: V std (In this example, 5.5 mol / L dilute sulfuric acid is selected, and the flow rate is 0.5 BV / h), so the adjusted dosage is... V adj According to α Value determined: like α<α1 (Slight performance degradation), then V adj =0.8 × V std .

[0097] like α1≤α<α2 (Performance degradation is normal), then V adj =V std .

[0098] like α≥α2 (Performance degradation is normal), then V adj =1.1 × V std .

[0099] in, α1、α2 These are empirical thresholds set based on the resin characteristics. The dosage can be adjusted by controlling the metering pump to change the volume, concentration, or injection flow rate of the regenerated liquid.

[0100] When the target adsorption column re-enters the regeneration phase, the control system will use the calculated optimized regenerant dosage. V adj It automatically executes the regeneration process.

[0101] Furthermore, embodiments of the present invention also provide an adsorption system, comprising: At least two switchable adsorption columns are used to adsorb and treat target pollutants.

[0102] A pulse backflush device located at the bottom of the adsorption column is used to agitate the adsorption bed by intermittent upward fluid pulses.

[0103] A low-speed stirring device located inside the adsorption column is used to generate gentle shear force during the adsorption process to promote uniform distribution of the adsorbent material.

[0104] Multiple sensors, including flow meters, pressure sensors, and an online heavy metal detection unit, are used to collect liquid flow rate, bed pressure drop, and target pollutant concentration in real time.

[0105] The control unit communicates with all sensors and actuators to execute the above-mentioned operation control method of the adsorption system.

[0106] In summary, the adsorption system and its operation control method provided by this invention integrate real-time operating parameter acquisition, dynamic model updating, and multi-level collaborative control strategies to achieve intelligent management of the entire lifecycle of the adsorption process. Compared to traditional fixed-cycle or threshold-triggered control methods, this solution can accurately calculate the remaining effective operating time of the target adsorption column by using online data fitting to dynamically update the adsorption breakthrough prediction model (such as a linearized Thomas model) based on key parameters such as the inlet concentration, outlet concentration, liquid flow rate, and cumulative treatment volume of the target pollutant. It also provides early warning and initiates a backup column preparation procedure when the time falls below a first preset time threshold, significantly improving the continuity and stability of system operation. Furthermore, the synergistic use of dual-spectral detection technologies (such as UV-Vis and LIBS) ensures the accuracy and reliability of outlet concentration measurement, especially achieving high-precision verification during the breakthrough critical stage.

[0107] In the embodiments provided by this invention, it should be understood that the disclosed apparatus and methods can also be implemented in other ways. The apparatus embodiments described above are merely illustrative; for example, the flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of apparatus, methods, and computer program products according to various embodiments of the present invention. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code, which contains one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions marked in the blocks may occur in a different order than those marked in the drawings. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram and / or flowchart, and combinations of blocks in block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or action, or using a combination of dedicated hardware and computer instructions.

[0108] In addition, the functional modules in the various embodiments of the present invention can be integrated together to form an independent part, or each module can exist independently, or two or more modules can be integrated to form an independent part.

[0109] If the functionality is implemented as a software module and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a computer-readable storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0110] The above are merely preferred embodiments of the present invention and are not intended to limit the present invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

[0111] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the invention can be implemented in other specific forms without departing from its spirit or essential characteristics. Therefore, the embodiments should be considered in all respects as exemplary and non-limiting, and the scope of the invention is defined by the appended claims rather than the foregoing description. Thus, all variations falling within the meaning and scope of equivalents of the claims are intended to be included within the present invention. No reference numerals in the claims should be construed as limiting the scope of the claims.

Claims

1. A method for controlling the operation of an adsorption system, characterized in that, The adsorption system includes at least two adsorption columns, and the method includes: The operating parameters of the target adsorption column are acquired in real time. The operating parameters include the inlet and outlet concentrations of the target pollutant, the liquid flow rate, and the cumulative volume of liquid treated. The target adsorption column is the adsorption column that is currently in adsorption operation. Based on the real-time acquired operating parameters, the parameters of the adsorption penetration prediction model are dynamically updated through online data fitting. Based on the parameters of the adsorption breakthrough prediction model, the remaining effective operating time of the target adsorption column is calculated according to the preset breakthrough concentration, the inlet concentration, and the liquid flow rate. When the remaining effective operating time is less than the first preset time threshold, a prompt is made to prepare for regeneration and / or to start the preparatory procedure for the backup adsorption column.

2. The method according to claim 1, characterized in that, The steps for obtaining the outlet concentration include: The liquid flowing out of the target adsorption column is sampled and pretreated online to obtain a pretreated sample. The sample is analyzed using a first spectral analysis technique to obtain a first concentration value of the target pollutant; When the first concentration value reaches the preset concentration, the sample is detected using a second spectral analysis technique to obtain a second concentration value of the target pollutant; the monitoring accuracy of the second spectral analysis technique is higher than that of the first spectral analysis technique. The outlet concentration is determined based on the first concentration value and the second concentration value.

3. The method according to claim 1, characterized in that, The adsorption breakthrough prediction model is a linear model obtained by linearizing the Thomas adsorption kinetics model; the linear model is as follows: Where A and B are parameters that are dynamically updated through fitting. The cumulative volume of liquid processed. The aforementioned inlet concentration, The outlet concentration is mentioned.

4. The method according to claim 3, characterized in that, The method of dynamically updating the parameters of the adsorption penetration prediction model based on the real-time acquired operating parameters through online data fitting includes: At preset fixed time intervals, data points that meet the effective concentration range conditions are selected from historical operating data; each data point includes inlet concentration, outlet concentration, and cumulative treated liquid volume; the effective concentration range condition is that the ratio of the outlet concentration to the inlet concentration is between a first ratio threshold and a second ratio threshold. The selected data points are fitted using a linear regression method to update the parameters A and B of the adsorption penetration prediction model.

5. The method according to claim 1, characterized in that, The remaining effective operating time of the target adsorption column is calculated based on the parameters of the adsorption breakthrough prediction model, according to the preset breakthrough concentration, the inlet concentration, and the liquid flow rate, including: Substitute the preset breakthrough concentration and the inlet concentration into the adsorption breakthrough prediction model to calculate the volume of liquid that has been treated when the preset breakthrough concentration is reached. The remaining liquid volume is obtained by subtracting the current cumulative liquid volume processed from the volume of liquid that has been penetrated. The remaining effective operating time of the target adsorption column is obtained by dividing the remaining treatment liquid volume by the liquid flow rate.

6. The method according to claim 1, characterized in that, The adsorption system further includes a pulse backflush device and a stirring device; the method further includes: When the outlet concentration is between a first preset concentration threshold and a second preset concentration threshold, the pulse backflush device and / or the stirring device are activated. When the outlet concentration is greater than the second preset concentration threshold or the remaining effective operating time is less than the second preset time threshold, the feed valve of the target adsorption column is closed, the standby adsorption column is switched, and the target adsorption column is regenerated.

7. The method according to claim 6, characterized in that, After the step of regenerating the target adsorption column, the method further includes: Record the actual total amount of target pollutants removed by the target adsorption column during this adsorption cycle; Based on the actual total adsorption amount of the current and at least one historical adsorption cycle, an effective adsorption capacity decay model for the target adsorption column is constructed, and the corresponding capacity decay coefficient is calculated; the capacity decay coefficient is used to characterize the degradation trend of the adsorption performance of the adsorption material with the number of uses.

8. The method according to claim 7, characterized in that, The regeneration process of the target adsorption column includes: The amount of regenerant is dynamically adjusted according to the capacity decay coefficient. The target adsorption column was regenerated using an adjusted regeneration dose.

9. The method according to claim 6, characterized in that, The method further includes: Real-time monitoring of the bed pressure drop of the target adsorption column; When the pressure drop in the bed exceeds a preset differential pressure threshold, the pulse backflush device is activated.

10. An adsorption system, characterized in that, include: At least two switchable adsorption columns are used to adsorb and treat the target pollutants. A pulse backflush device located at the bottom of the adsorption column is used to agitate the adsorption bed by intermittent upward fluid pulses. A low-speed stirring device located inside the adsorption column is used to generate gentle shear force during the adsorption process to promote uniform distribution of the adsorbent material. Multiple sensors, including flow meters, pressure sensors, and an online heavy metal detection unit, are used to collect liquid flow rate, bed pressure drop, and target pollutant concentration in real time, respectively. The control unit is communicatively connected to all of the said sensors and actuators for performing the method as described in any one of claims 1 to 9.

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