Automatic control system for selective salt separation by capacitive deionization

Abstract

The present invention provides a capacitive deionization selective salt separation automatic control system, comprising: a liquid to be treated unit, a capacitive deionization device, a purified water storage unit, an uncertainty and sensitivity analysis model, a multi-physical field coupling mathematical model, and a parameter quantitative influence database, wherein the uncertainty and sensitivity analysis model, the multi-physical field coupling mathematical model, and the parameter quantitative influence database achieve precise control of the capacitive deionization desalination operation with the goal of processing the expected effect. The capacitive deionization selective salt separation automatic control system of the present invention can provide parameter setting guidance without time-consuming multi-physical field coupling mathematical model analysis when treating different liquids to be treated, facilitate quick switching of application scenarios, and can easily achieve automatic control. It can be applied to water softening, heavy metal removal, nutrients, and combined with the chemical precipitation method, avoiding the investment and operation of expensive membrane systems, and achieving near-zero discharge of industrial wastewater such as mine water.

Description

Technical Field

[0001] The present invention relates to the field of efficient desalination of sewage treatment, and particularly to a capacitive deionization selective salt separation automatic control system. Background Art

[0002] The salts in sewage will inhibit the growth of microorganisms in natural water bodies or biological treatment systems, making desalination an important issue in the field of water treatment after the removal of COD, nitrogen, phosphorus and heavy metals, and also a major problem in the domestic and foreign environmental protection fields. For most industries, due to the complex salt content of wastewater, it is energy-consuming and difficult to achieve "zero solid waste" external discharge by simple evaporation alone. According to the new relevant environmental protection regulations and requirements, the water quality factors of sewage discharge, especially mine water discharge, should meet or be better than the corresponding values of surface water environmental quality specified in the environmental function zoning of the receiving water body, that is, the salt content shall not exceed 1000 mg / L. If the salts are not separated, it will be very difficult to desalinate at low cost and efficiently. The finally obtained solid miscellaneous salts should basically be treated as solid hazardous wastes. At present, the treatment cost of solid hazardous wastes in China is expensive, and its cost is higher than the sum of the costs of the previous processes of membrane concentration, evaporation concentration and evaporation crystallization.

[0003] Capacitive deionization (CDI), as an emerging desalination technology, applies a voltage to a porous electrode, resulting in the enrichment of charges at the electrode / aqueous solution interface. At the same time, the salt ions in the water are adsorbed in the region between the electrode and the aqueous solution to form an electric double layer, thereby achieving the purpose of desalination and having the effect of energy storage. It has the advantages of low energy consumption, high efficiency, easy regeneration, easy maintenance, and no secondary pollution, and has broad application prospects in sewage desalination. In addition, CDI has the characteristic of selective removal, that is, it shows selectivity and preferentially removes specific ions during electro-adsorption in a multi-ion system. This characteristic can be used to achieve the separation and removal of target ions in raw water, and has important application values in aspects such as water quality softening, removal of heavy metal ions, and fractional salt recovery of nutrients. However, the multi-ion competitive adsorption process in a multi-salt coexistence system is relatively complex. In addition to being related to the structure and material configuration of CDI, the selection of operating parameters depends on the ion system and concentration of the solution to be treated, which makes the regulation of operating parameters extremely complex. In the actual operation process, strict control of operating parameters is required, and there are common problems such as inaccurate manual control. Moreover, the influent water quality changes greatly during the treatment process, and the impact load is strong. It is difficult to achieve effective removal by presetting constant operating parameters. If the model prediction is used to adjust the operating parameters, there are key problems such as long standby time and control lag, which seriously limit the in-depth application of CDI technology in selective separation. There is an urgent need for a capacitive deionization system that can automatically and intelligently adjust operating parameters to achieve efficient selective desalination. Summary of the Invention

[0004] In view of the above deficiencies in the prior art, the present invention provides an automatic control system for capacitive deionization selective salt separation, which only needs to artificially set the possible concentration range of influent ions. On this basis, the system automatically performs uncertainty analysis and global sensitivity model analysis, generates and memorizes the isolated and coupled influence degrees of parameters such as inlet flow rate, ion concentrations, operating current, etc. on the effluent water quality, enabling the system to have the ability to operate autonomously and adjust the operating conditions for the wastewater to be treated, and intelligently and autonomously and precisely adjust the operating conditions according to the current situation and requirements of the effluent water quality, and finally achieve the goal of efficient separation of target ions.

[0005] To achieve the above object, the present invention provides an automatic control system for capacitive deionization selective salt separation, comprising:

[0006] A liquid to be treated unit for temporarily storing the liquid to be treated and having the function of real-time monitoring of the water quality of the liquid to be treated;

[0007] A capacitive deionization device for driving the migration of salt ions by positive and negative electrode voltages to achieve the separation of salts and the removal of total salts from the liquid to be treated and produce purified water;

[0008] A purified water storage unit for storing the treated purified water. If the purified water needs to be further treated, the purified water is returned to the capacitive deionization device; the liquid to be treated unit, the capacitive deionization device and the purified water storage unit are connected in sequence;

[0009] An uncertainty and sensitivity analysis model for automatically generating a series of operating parameter arrays based on the ion species automatically obtained by the liquid to be treated unit, the structural characteristics of the porous electrode of the capacitive deionization device set artificially, and the ion concentration range in the liquid to be treated set artificially, and using the results returned by the multi-physical field coupling mathematical model to form a quantitative functional relationship between the parameter group and the water quality treatment effect;

[0010] A multi-physical field coupling mathematical model for simulating and calculating the treatment effect data of the capacitive deionization device based on the operating parameter arrays and returning the treatment effect data to the uncertainty and sensitivity analysis model;

[0011] The uncertainty and sensitivity analysis model is also used for statistical analysis of the simulation result data groups, evaluating the accuracy of the quantitative functional relationship between the parameter group and the water quality treatment effect, and forming the data content of the parameter quantitative influence database;

[0012] The parameter quantitative influence database is used for storing a large amount of data generated during the analysis process of the uncertainty and sensitivity model and the high-precision operating parameter and effect data relationship polynomial function generated, and performing intelligent automatic control on the capacitive deionization device based on the effect data relationship polynomial function.

[0013] Preferably, based on the electrode structure features input manually and the possible range of the concentration of the liquid to be processed based on historical data, model analysis is carried out before the formal operation of the entire capacitive deionization device to generate the parameter quantitative influence database for real-time control during the formal operation of the capacitive deionization device; when the capacitive deionization device is formally operating, based on the parameter quantitative influence database within the full parameter range, the operating parameters are automatically adjusted according to the treatment target and the current water quality status.

[0014] Preferably, in the uncertainty and sensitivity analysis model, the built-in efficient algorithm automatically generates multiple groups of the operating parameter arrays according to the evaluation results of the data calculated by the multi-physical field coupling mathematical model for further simulation calculation of the multi-physical field coupling mathematical model.

[0015] Preferably, the variable site and variable target operate directly and have strong resistance to water quality shock load. Although the process of the uncertainty and sensitivity model analysis before the formal operation of the capacitive deionization device is the most time-consuming, as long as the electrode structure of the capacitive deionization device remains unchanged and the ionic components in the liquid to be processed remain unchanged, even if the system usage location and scenario are changed, and the ionic concentration and operation target are changed, the analysis process of the uncertainty and sensitivity model directly uses the existing parameter quantitative influence database and realizes intelligent automatic control, and is equipped with a majority library storage and selection function, and can freely switch the stored application environments.

[0016] Preferably, the setting ranges of the concentrations of the respective ionic components in the uncertainty and sensitivity model analysis before the formal operation can be manually changed after the formal operation of the capacitive deionization device, without discarding the calculation results within the previous concentration ranges, without model restart and simulation recalculation, which is convenient for remedying the waiting time caused by human errors in the previous concentration setting and greatly reduces the waiting time when manually analyzing the water quality treatment results.

[0017] Preferably, the prediction process of the multi-physical field coupling mathematical model is allowed to be carried out simultaneously with the salt separation process of the capacitive deionization device.

[0018] Preferably, multi-mode switching is allowed, and the modes include full desalination, separation of low-valence ions, and separation of high-valence ions.

[0019] Preferably, according to the preset output parameters during the current situation assessment or prediction, multiple data forms such as data tables, concentration distribution contour maps, or animations are automatically generated, and a human intervention output function is provided.

[0020] Since the present invention adopts the above technical solutions, it has the following beneficial effects:

[0021] (1) Based on the electrode structure features input by humans and the possible range of the concentration of the liquid to be processed based on historical data, the system of the present invention performs model analysis before the formal operation of the entire CDI to generate a database of quantitative influence of parameters for real-time control during the formal operation of CDI; based on the database of quantitative influence of all parameter ranges, there is no need to control the operating parameters after time-consuming physical model prediction during the formal operation of CDI, avoiding the waiting of the device and the lag of control parameters;

[0022] (2) In the uncertainty and sensitivity analysis model adopted by the present invention, an efficient algorithm is built in to calculate the evaluation results of data according to the multi-physical-field coupling mathematical model, and automatically generate multiple groups of parameter arrays for further simulation calculation of the multi-physical-field coupling mathematical model. The generation of multiple groups of parameter arrays facilitates the parallel calculation of the mathematical model and greatly reduces the generation time of the database of quantitative influence of parameters;

[0023] (3) The system adopted by the present invention can run directly with variable sites and variable targets. Although the uncertainty and sensitivity model analysis before the formal operation of CDI is the most time-consuming stage, as long as the CDI electrode structure remains unchanged and the ionic components in the liquid to be processed remain unchanged, even if the system usage location and scenario are changed and the ion concentration and operation target change, the system does not require a time-consuming uncertainty and sensitivity model analysis process and can be directly used to achieve intelligent automatic control;

[0024] (4) The concentration setting ranges of each ionic component in the uncertainty and sensitivity model analysis before the formal operation of the system adopted by the present invention can be manually changed during the subsequent operation process, without having to discard the calculation results after the previous concentration range setting, and without the need for model restart and recalculation processes, which is convenient for remedying the waiting time caused by human errors in the previous concentration setting;

[0025] (5) The system adopted by the present invention allows the prediction process of the multi-physical-field coupling mathematical model and the desalting process of capacitive deionization to be carried out simultaneously. Since the model prediction process does not participate in the automatic control of operating parameters and only provides the function of current situation evaluation and prediction, although the simulation time is relatively time-consuming, it does not affect the process of the core process of capacitive deionization desalting, greatly saving time;

[0026] (6) The system adopted by the present invention allows multi-mode switching and can freely switch between multiple target functions such as full desalination, separation of low-valence ions, and separation of high-valence ions;

[0027] (7) When evaluating the current situation or making predictions, the system adopted by the present invention can automatically generate various data forms such as data tables, concentration distribution cloud maps, or animations according to the pre-set output parameters, and can also be manually intervened in the output function, which is convenient for the analysis, evaluation, summary, and display of the current operation situation;

[0028] (8) The system adopted by the present invention is small in scale. Except for the influent and effluent storage unit and the capacitive deionization device, only a relatively small microprocessor is required, which is convenient for transportation and use. Description of the Drawings

[0029] Figure 1 It is a schematic structural diagram of the automatic control system for selective salt separation by capacitive deionization according to an embodiment of the present invention;

[0030] Figure 2 It is a comparison chart of the current density sampling point data and the corresponding removal rate data automatically generated according to the results of the efficient algorithm of the uncertainty and sensitivity model according to an embodiment of the present invention. Detailed Embodiments

[0031] The following is based on the drawings Figure 1 and Figure 2 , and the preferred embodiments of the present invention are given and described in detail to better understand the functions and characteristics of the present invention.

[0032] Please refer to Figure 1 and Figure 2 , an automatic control system for selective salt separation by capacitive deionization according to an embodiment of the present invention includes:

[0033] A liquid to be treated unit 1, which is used to temporarily store the liquid to be treated and has the function of real-time monitoring of the water quality of the liquid to be treated, and can monitor the types of ions and their respective concentrations in the solution;

[0034] A capacitive deionization device 2, which is used to drive the migration of salt ions by positive and negative voltages to realize the separation of salts and the removal of all salts from the liquid to be treated and produce purified water; this device is the core device for the selective separation of salts in the solution, and the system operation target (total component desalination, separation of high-valence ions, separation of low-valence ions) can be set artificially, and the system automatically adjusts the operation parameters to accurately achieve the operation target;

[0035] A purified water storage unit 3, which is used to store the treated purified water. If the purified water needs to be further treated, the purified water is returned to the capacitive deionization device 2; the liquid to be treated unit 1, the capacitive deionization device 2 and the purified water storage unit 3 are connected in sequence;

[0036] An uncertainty and sensitivity analysis model 4, which is used to automatically generate a series of operation parameter arrays based on the types of ions automatically obtained by the liquid to be treated unit 1, the structural characteristics of the porous electrode of the capacitive deionization device 2 set artificially, and the range of ion concentrations in the liquid to be treated set artificially, and use the multi-physical field coupling mathematical model to return the results to form a quantitative functional relationship between the parameter group and the water quality treatment effect;

[0037] A multi-physical field coupling mathematical model 5 simulates and calculates the treatment effect data of the capacitive deionization device 2 based on the operating parameter array, and returns the treatment effect data to the uncertainty and sensitivity analysis model 4;

[0038] The uncertainty and sensitivity analysis model 4 statistically analyzes the simulated result groups, evaluates the accuracy of the quantitative functional relationship between the parameter group and the water quality treatment effect, and forms the data content of the parameter quantitative influence database 6;

[0039] The parameter quantitative influence database 6 is used to store a large amount of data generated during the uncertainty and sensitivity model analysis process and the polynomial function of the relationship between the generated high-precision operating parameters and the effect data, and performs intelligent automatic control on the capacitive deionization device 2 based on the effect data relationship polynomial function.

[0040] In this embodiment, based on the artificially input electrode structure characteristics and the possible range of the concentration of the liquid to be treated based on historical data, model analysis is performed before the capacitive deionization device 2 is officially operated to generate the parameter quantitative influence database 6 for real-time control during the official operation of the capacitive deionization device 2; when the capacitive deionization device 2 is officially operating, based on the parameter quantitative influence database 6 with the full parameter range, the operating parameters are automatically adjusted according to the treatment target and the current water quality status, without the need for time-consuming physical model prediction before the capacitive deionization device 2 is officially operating and then controlling the operation, avoiding the waiting of the device and the lag of the control parameters.

[0041] In the uncertainty and sensitivity analysis model 4, an efficient algorithm automatically generates multiple groups of operating parameter arrays for further simulation calculation of the multi-physical field coupling mathematical model 5 according to the evaluation results of the data calculated by the multi-physical field coupling mathematical model 5. The generation of multiple groups of parameter arrays facilitates the parallel calculation of the mathematical model and greatly reduces the generation time of the parameter quantitative influence database 6.

[0042] It can operate directly with variable sites and variable targets, and has strong resistance to water quality shock loads. Although the uncertainty and sensitivity model analysis process before the capacitive deionization device 2 is officially operated is the most time-consuming, as long as the electrode structure of the capacitive deionization device 2 remains unchanged and the ion components in the liquid to be treated remain unchanged, even if the system usage location and scenario are changed, and the ion concentration and operation target change, the analysis process of the uncertainty and sensitivity model directly uses the existing parameter quantitative influence database 6 and realizes intelligent automatic control, and is equipped with a majority library storage and selection function, and can freely switch the stored application environment (the composition of the liquid to be treated changes).

[0043] Before the formal operation, the concentration setting ranges of various ionic components in the uncertainty and sensitivity model analysis can be artificially changed after the capacitive deionization device 2 is formally put into operation. There is no need to discard the calculation results within the previous concentration range, and there is no need to restart the model and recalculate the simulation, which is convenient for remedying the waiting time caused by artificial errors in the previous concentration setting and greatly reduces the waiting time when manually analyzing the water quality treatment results.

[0044] It is allowed that the prediction process of the multi-physical-field coupling mathematical model 5 is carried out simultaneously with the salt separation process of the capacitive deionization device 2. Since the model prediction process does not participate in the automatic control of the operating parameters and only provides the status assessment and prediction functions, although the simulation time is relatively time-consuming, it does not affect the process of the core process of capacitive deionization salt separation, saving a large amount of time.

[0045] It is allowed to switch between multiple modes, including total desalination, separation of low-valence ions, and separation of high-valence ions, to realize the multi-functional use of the whole system.

[0046] When conducting the status assessment or prediction, according to the preset output parameters, various data forms such as data tables, concentration distribution contour maps, or animations are automatically generated, and it has the function of manual intervention output, which is convenient for the analysis, assessment, summary, and display of the operation status.

[0047] This model includes all physical processes in the capacitive deionization device 2, improving the accuracy of model calculation. Specifically, it includes three physical fields: the flow field of fluid flow in the capacitive deionization device 2, the concentration field of multi-component ion migration, and the electric field of the electric potential distribution in the capacitive deionization device 2. The concentration field includes multiple ion mass transfer processes such as the convective diffusion process in the flow channel between the electrodes, the pure diffusion process driven by the concentration difference and potential difference in the porous electrode, and the sieving process of micropores for salt ions. In addition to considering the common Ohmic resistance, the electric field also additionally considers the consumption of current by the Faraday side reaction on the electrode surface.

[0048] An automatic control system for capacitive deionization selective salt separation according to an embodiment of the present invention selectively adsorbs target ions, can maximize the adsorption capacity of the porous electrode of the capacitive deionization device 2, and can flexibly switch between the separation and extraction of monovalent and high-valence ions by adjusting parameters such as the operating current and hydraulic retention time according to the water outlet requirements. It can be applied to water quality softening, heavy metal removal, nutrients. In addition, by switching to the extraction mode of monovalent ions, it can be combined with the chemical precipitation method to avoid investing in and operating expensive membrane systems and achieve near-zero discharge of industrial wastewater such as mine water.

[0049] In addition to being used for the above-mentioned uncertainty and sensitivity model analysis, the multi-physical field coupling mathematical model 5 can also simulate and predict the current or possible influent conditions. The simulation and prediction results can be customized into various visual data forms (such as data tables, concentration distribution contour maps, or animations). The simulation results of the current influent conditions can automatically generate and save various data forms according to the preset output frequency, or can be manually interfered to generate them in one key in real time.

[0050] The entire control system is small in scale. Except for the influent and effluent storage units and the capacitive deionization device, only a relatively small microprocessor is required, which is convenient for transportation and use. Based on the electrode structure characteristics input by humans and the possible range of the concentration of the liquid to be treated based on historical data, model analysis is carried out before the capacitive deionization device 2 operates formally, and a quantitative influence database 6 of parameters is generated for real-time control during the formal operation of the capacitive deionization device 2. Based on the quantitative influence database of the full parameter range, there is no need to wait for time-consuming physical model prediction during the formal operation of the capacitive deionization device 2 and then control, avoiding the waiting of the device and the lag of control parameters. The control system can provide a model prediction function, and can automatically generate various data forms such as data tables, concentration distribution contour maps, or animations according to the preset output parameters, or the output function can be manually intervened.

[0051] The system of the present invention is mainly an automatic control system for realizing selective separation or total salt removal of a multi-salt ion system based on CDI. Among them, the liquid to be treated unit 1, the capacitive deionization device 2, and the treated purified water storage unit 3 are the main process lines for target salt ion separation or total salt efficient removal. The uncertainty and sensitivity analysis model 4, the multi-physical field coupling mathematical model 5, and the quantitative influence database 6 of parameters realize the precise control of CDI operation with the expected treatment effect as the goal.

[0052] Specifically, the liquid to be treated unit 1, the capacitive deionization device 2, and the treated purified water storage unit 3 are the main process lines for target salt ion separation or total salt efficient removal. Among them, the operating parameters of the capacitive deionization device 2 are autonomously controlled by a subsystem composed of the uncertainty and sensitivity analysis model 4, the multi-physical field coupling mathematical model 5, and the quantitative influence database 6 of parameters.

[0053] Before the capacitive deionization device 2 is turned on, the types of ions in the liquid to be treated are manually input or automatically monitored in the liquid to be treated. The structural characteristics of the input electrode (porosity) are set, the possible concentration ranges of various types of ions and the operating parameter ranges (the flow rate range of the pump and the current density range) are set. The uncertainty and sensitivity analysis model 4 automatically generates an array of parameters for the multi-physical field coupling mathematical model 5 to perform computational simulations. The calculation results are returned to the uncertainty and sensitivity analysis model 4 for analysis and evaluation. If the analysis does not converge, a new array of parameters is formed for simulation calculations. If it converges, statistical analysis is automatically performed and fitted into a polynomial function with the salt separation and desalination effect as the objective function and multiple operating parameters as variables. A large amount of simulation data and fitting functions are stored to form a database of quantitative parameter impacts 6;

[0054] When the capacitive deionization device 2 is turned on, the ion concentration in the liquid to be treated is automatically monitored by a sensor and input into the database of quantitative parameter impacts 6. The database of quantitative parameter impacts 6 then obtains the set operating target (i.e., the salt separation and desalination effect). On this basis, the corresponding control parameters are instantaneously generated directly through the fitting function in the database, and the capacitive deionization device 2 is controlled in real time to ultimately achieve the operating target;

[0055] After the capacitive deionization device 2 is turned on, according to the real-time operating parameters, the output is controlled according to the preset output parameters or manually by the operator. The multi-physical field coupling mathematical model 5 generates and stores personalized customized visualization data forms (data tables, concentration distribution cloud maps, animations, etc.) for subsequent analysis, evaluation, and display, etc.

[0056] For example:

[0057] Taking simulated wastewater containing 50 mmol / L NaCl and 50 mmol / L CaCl 2 as an example, the macropore porosity of the electrode is 0.38, the micropore porosity is 0.25. The possible concentration ranges of the two preset influent ions are both 1 - 200 mmol / L, and the controllable range of the current density applied on both sides of the CDI device electrode is 1 - 20 A / m 2 . Through the intelligent automatic precise control of this system, the concentration ratio of NaCl to CaCl 2 in the effluent reaches 0.15, and the energy consumption is 25.13 kWh / kg, achieving a relatively ideal analysis effect.

[0058] The present invention has been described in detail above in conjunction with the embodiments with reference to the drawings. Those of ordinary skill in the art can make various variations to the present invention according to the above description. Therefore, certain details in the embodiments should not constitute a limitation to the present invention, and the protection scope of the present invention will be defined by the scope of the appended claims.

Claims

1. A capacitive deionization selective salt separation automatic control system, characterized in that, it includes: A liquid to be treated unit for temporarily storing the liquid to be treated and having the function of real-time monitoring of the water quality of the liquid to be treated; A capacitive deionization device for driving the migration of salt ions by positive and negative voltages to achieve salt separation and total salt removal of the liquid to be treated and produce purified water; A purified water storage unit for storing the treated purified water. If the purified water needs to be further treated, the purified water is returned to the capacitive deionization device; The liquid to be treated unit, the capacitive deionization device and the purified water storage unit are connected in sequence; An uncertainty and sensitivity analysis model for automatically generating a series of operation parameter arrays based on the ion types automatically obtained by the liquid to be treated unit, the structural characteristics of the porous electrodes of the capacitive deionization device set by humans, and the ion concentration range in the liquid to be treated set by humans, and using the results returned by the multi-physical field coupling mathematical model to form a quantitative functional relationship between the parameter group and the water quality treatment effect; A multi-physical field coupling mathematical model for simulating and calculating the treatment effect data of the capacitive deionization device based on the operation parameter array and returning the treatment effect data to the uncertainty and sensitivity analysis model; The uncertainty and sensitivity analysis model is also used to statistically analyze the simulation result data groups, evaluate the accuracy of the quantitative functional relationship between the parameter group and the water quality treatment effect, and form the data content of the parameter quantitative influence database; The parameter quantitative influence database is used to store a large amount of data generated during the analysis process of the uncertainty and sensitivity model and the polynomial function of the relationship between the generated high-precision operation parameters and effect data, and perform intelligent automatic control on the capacitive deionization device based on the polynomial function of the effect data relationship.

2. The capacitive deionization selective salt separation automatic control system according to claim 1, characterized in that, Based on the electrode structure characteristics input by humans and the possible range of the concentration of the liquid to be treated based on historical data, model analysis is carried out before the formal operation of the entire capacitive deionization device to generate the parameter quantitative influence database for real-time control during the formal operation of the capacitive deionization device; when the capacitive deionization device is formally operating, based on the parameter quantitative influence database within the full parameter range, the operation parameters are automatically adjusted according to the treatment target and the current water quality situation.

3. The capacitive deionization selective salt separation automatic control system according to claim 1, characterized in that, In the uncertainty and sensitivity analysis model, an efficient algorithm is built-in to automatically generate multiple groups of the operation parameter arrays for further simulation calculation by the multi-physical field coupling mathematical model according to the evaluation results of the data calculated by the multi-physical field coupling mathematical model.

4. The capacitive deionization selective salt separation automatic control system according to claim 1, characterized in that, The variable site and variable target operate directly and are highly resistant to water quality shock loads. Although the analysis process of the uncertainty and sensitivity model before the formal operation of the capacitive deionization device is the most time-consuming, as long as the electrode structure of the capacitive deionization device remains unchanged and the ionic components in the liquid to be treated remain unchanged, even if the system usage location and scenario are changed, and the ion concentration and operation target are changed, the analysis process of the uncertainty and sensitivity model directly uses the existing parameter quantitative influence database and realizes intelligent automatic control, and is equipped with a majority library storage and selection function, and can freely switch the stored application environment.

5. The capacitive deionization selective salt separation automatic control system according to claim 1, characterized in that the concentration setting ranges of the respective ionic components in the uncertainty and sensitivity model analysis before formal operation can be artificially changed after the formal operation of the capacitive deionization device, without discarding the calculation results within the previous concentration range, without restarting the model and recalculating the simulation, which is convenient for remedying the waiting time caused by human errors in the previous concentration setting.

6. The capacitive deionization selective salt separation automatic control system according to claim 1, characterized in that it allows the prediction process of the multi-physical field coupling mathematical model to be carried out simultaneously with the salt separation process of the capacitive deionization device, greatly reducing the waiting time when manually analyzing the water quality treatment results.

7. The capacitive deionization selective salt separation automatic control system according to claim 1, characterized in that it allows multi-mode switching, and the modes include full desalination, separation of low-valence ions, and separation of high-valence ions.

8. The capacitive deionization selective salt separation automatic control system according to claim 1, characterized in that when evaluating or predicting the current situation, according to the preset output parameters, it automatically generates various data forms such as data tables, concentration distribution contour maps or animations, and has a function of manual intervention output.

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