High-salinity waste liquid electroflocculation hardness removal and electrodialysis resource treatment method and system

Abstract

The application relates to the technical field of electrochemical water treatment, and discloses a high-salinity waste liquid electroflocculation hardness removal and electrodialysis resource treatment method and system. The method comprises the following steps: collecting water quality parameters of high-salinity waste liquid and initial electrochemical impedance spectrum parameters of an electrode plate; calculating an initial current density according to hardness and conductivity to perform electroflocculation treatment, and identifying a fouling type and predicting a residual operation time of the electrode plate by monitoring impedance spectrum changes in real time; optimizing the current density according to the predicted time and calculating residual hardness; taking the residual hardness as a feedforward signal to adjust electrodialysis parameters to concentrate, and performing bipolar membrane electrodialysis on concentrated liquid to obtain acid and alkali liquid. The application solves the problems of blind adjustment of operation parameters caused by the fact that the state of the electrode plate cannot be monitored in real time in the electrochemical treatment process of high-salinity waste liquid, and high energy consumption and low resource utilization efficiency caused by the fact that parameters of pre-treatment and post-treatment units are not linked.

Description

Technical Field

[0001] This application relates to the field of electrochemical water treatment technology, and in particular to a method and system for the electrocoagulation and electrodialysis resource recovery treatment of high-salt waste liquid. Background Technology

[0002] High-salt wastewater generated during industrial production contains large amounts of calcium and magnesium ions, chlorides, sulfates, and organic pollutants, and direct discharge can cause serious environmental pollution. Electrocoagulation technology uses electrolysis to generate metal cations to form flocculants, effectively removing hardness ions and some organic matter from the wastewater. It offers advantages such as simple equipment, convenient operation, and no need for chemical additives. Electrodialysis technology utilizes the selective permeability of ion exchange membranes to separate and concentrate salts under an electric field, allowing for further desalination of the treated wastewater and recovery of high-concentration salt solutions. Bipolar membrane electrodialysis technology uses the water dissociation effect of bipolar membranes to convert concentrated brine into acidic and alkaline solutions, enabling the resource utilization of wastewater. Existing technologies already include process schemes combining electrocoagulation and electrodialysis for the treatment of high-salt wastewater.

[0003] However, existing technologies have the following shortcomings: First, scaling and passivation easily occur on the electrode surface during electrocoagulation, leading to decreased current efficiency and deterioration of treatment effect. However, existing technologies lack real-time monitoring methods for the electrode surface condition, and electrode failure can only be detected by observing changes in current or deterioration of effluent quality, making it impossible to provide early warning and optimize operating parameters. Second, electrocoagulation reactors typically operate with a fixed current density, without considering the impact of influent water quality fluctuations, electrode scaling degree, and remaining operating time, resulting in high energy consumption or unstable treatment effect. Third, during electrodialysis treatment, parameters are not adjusted according to the residual hardness of the electrocoagulated effluent. If the hardness removal effect in the first stage is poor, the subsequent electrodialysis membrane is easily impacted by high-hardness water, accelerating scaling. Finally, the concentration growth rates of acid and alkali solutions produced by bipolar membrane electrodialysis are asynchronous, resulting in low resource recovery efficiency. Summary of the Invention

[0004] This application provides a method and system for the electrocoagulation and electrodialysis resource recovery treatment of high-salt waste liquid, which solves the problems of blind adjustment of operating parameters due to the inability to monitor the electrode status in real time during the electrochemical treatment of high-salt waste liquid and the high energy consumption and low resource recovery efficiency caused by the lack of linkage between parameters of pre- and post-treatment units, thereby improving the intelligent level of system operation and overall treatment efficiency.

[0005] In a first aspect, this application provides a method for the electrocoagulation and electrodialysis resource recovery treatment of high-salt waste liquid, the method comprising:

[0006] Step S1: Collect the hardness, calcium ion concentration, average molecular weight of organic matter, and conductivity of the high-salt waste liquid; set an electrochemical impedance spectroscopy sensor on the electrode surface of the electrocoagulation reactor to measure the initial interfacial charge transfer resistance, initial double-layer capacitance, and initial mid-frequency slope.

[0007] Step S2: Calculate the initial current density based on the hardness and conductivity, and pump the high-salt waste liquid into the electrocoagulation reactor for electrocoagulation hardness removal treatment; measure the real-time interface charge transfer resistance, real-time double-layer capacitance, and real-time mid-frequency slope using the electrochemical impedance spectroscopy sensor, and calculate the interface resistance growth rate, double-layer capacitance decay rate, and mid-frequency slope change rate relative to the initial interface charge transfer resistance, initial double-layer capacitance, and initial mid-frequency slope, respectively; identify the electrode plate scaling type based on the interface resistance growth rate, double-layer capacitance decay rate, and mid-frequency slope change rate; input the interface resistance growth rate, double-layer capacitance decay rate, mid-frequency slope change rate, hardness, calcium ion concentration, average molecular weight of organic matter, and initial current density into the prediction model to obtain the remaining effective operating time of the electrode plate;

[0008] Step S3: Optimize the initial current density based on the remaining effective operating time of the electrode to obtain the operating current density, obtain the electrocoagulation effluent based on the operating current density, and calculate the residual hardness of the electrocoagulation effluent based on the operating current density;

[0009] Step S4: Using the residual hardness as a feedforward signal to adjust the electrodialysis treatment parameters, the electrocoagulated effluent is concentrated by electrodialysis to obtain a concentrate, and the concentrate is subjected to bipolar membrane electrodialysis to obtain an acid solution and an alkaline solution.

[0010] Secondly, this application provides a high-salt waste liquid electrocoagulation hardening and electrodialysis resource recovery treatment system, the high-salt waste liquid electrocoagulation hardening and electrodialysis resource recovery treatment system comprising:

[0011] The acquisition module is used to collect the hardness, calcium ion concentration, average molecular weight of organic matter, and conductivity of high-salt waste liquid; an electrochemical impedance spectroscopy sensor is set on the electrode surface of the electrocoagulation reactor to measure the initial interfacial charge transfer resistance, initial double-layer capacitance, and initial mid-frequency slope.

[0012] The identification module is used to calculate the initial current density based on the hardness and conductivity, and pump the high-salt waste liquid into the electrocoagulation reactor for electrocoagulation hardness removal treatment; measure the real-time interfacial charge transfer resistance, real-time double-layer capacitance, and real-time mid-frequency slope using the electrochemical impedance spectroscopy sensor, and calculate the interfacial resistance growth rate, double-layer capacitance decay rate, and mid-frequency slope change rate relative to the initial interfacial charge transfer resistance, the initial double-layer capacitance, and the initial mid-frequency slope, respectively; identify the scale type of the electrode plate based on the interfacial resistance growth rate, double-layer capacitance decay rate, and mid-frequency slope change rate; input the interfacial resistance growth rate, double-layer capacitance decay rate, mid-frequency slope change rate, hardness, calcium ion concentration, average molecular weight of organic matter, and initial current density into the prediction model to obtain the remaining effective operating time of the electrode plate;

[0013] The calculation module is used to optimize the initial current density based on the remaining effective operating time of the electrode to obtain the operating current density, obtain the electrocoagulation effluent based on the operating current density, and calculate the residual hardness of the electrocoagulation effluent based on the operating current density.

[0014] The adjustment module is used to adjust the electrodialysis treatment parameters by using the residual hardness as a feedforward signal, to concentrate the electrocoagulated effluent by electrodialysis to obtain a concentrate, and to treat the concentrate by bipolar membrane electrodialysis to obtain an acid solution and an alkaline solution.

[0015] The technical solution provided in this application establishes a baseline fingerprint of the electrochemical state of the electrode surface by setting an electrochemical impedance spectroscopy sensor on the electrode surface of the electrocoagulation reactor and measuring the initial interfacial charge transfer resistance, initial double-layer capacitance, and initial mid-frequency slope. This provides a comparative benchmark for subsequent dynamic monitoring. During the electrocoagulation hardening process, the changes in interfacial charge transfer resistance, double-layer capacitance, and mid-frequency slope are measured in real time, and the rate of increase of interfacial resistance, the rate of decrease of double-layer capacitance, and the rate of change of mid-frequency slope relative to the initial state are calculated, enabling continuous tracking of the scaling process on the electrode surface. The type of electrode scaling is identified based on the numerical combination characteristics of the change rates of the three impedance parameters, distinguishing between two different failure mechanisms: inorganic salt scale deposition and organic passivation, providing a basis for targeted cleaning measures. The impedance spectrum characteristic parameters, water quality characteristic parameters, and operating parameters are constructed into a nine-dimensional input feature vector and input into the prediction model. A nonlinear mapping relationship between impedance spectrum evolution and electrode failure time is established using a random forest regression algorithm, realizing the transformation from passively discovering failures to actively predicting failures, avoiding a sharp drop in treatment effect and frequent shutdowns caused by sudden electrode passivation. Based on the predicted remaining effective operating time of the electrodes, the current density was optimized, and a multi-objective optimization function incorporating energy consumption, operating time, and effluent quality was constructed. A genetic algorithm was used to find the optimal current density under constraints, achieving a balance between treatment effect, energy consumption, and equipment utilization. The residual hardness of the electrocoagulation effluent was calculated based on the optimized operating current density and used as a feedforward signal to adjust the electrodialysis treatment parameters. This allowed the electrodialysis current density and concentration / dilute chamber volume ratio to pre-adapt to fluctuations in the upstream treatment effect, avoiding the impact of high-hardness water on the membrane module and extending the membrane's lifespan. Attached Figure Description

[0016] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the following description of the embodiments will be briefly introduced. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0017] Figure 1 This is a schematic diagram of an embodiment of the high-salt waste liquid electrocoagulation dehardening and electrodialysis resource utilization treatment method in this application;

[0018] Figure 2 This is a schematic diagram showing the change of electrochemical parameters on the electrode surface with operating time in an embodiment of this application;

[0019] Figure 3 This is a schematic diagram comparing the energy consumption of the traditional method and the optimized method in the embodiments of this application. Detailed Implementation

[0020] This application provides a method and system for the electrocoagulation and electrodialysis resource recovery treatment of high-salt wastewater. The terms "first," "second," "third," "fourth," etc. (if present) in the specification, claims, and accompanying drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments described herein can be implemented in a sequence other than that illustrated or described herein. Furthermore, the terms "comprising" or "having" and any variations thereof are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0021] For ease of understanding, the specific process of the embodiments of this application is described below. Please refer to [link / reference]. Figure 1 One embodiment of the high-salt waste liquid electrocoagulation dehardening and electrodialysis resource recovery treatment method in this application includes:

[0022] Step S1: Collect the hardness, calcium ion concentration, average molecular weight of organic matter, and conductivity of the high-salt waste liquid; set an electrochemical impedance spectroscopy sensor on the electrode surface of the electrocoagulation reactor to measure the initial interfacial charge transfer resistance, initial double-layer capacitance, and initial mid-frequency slope.

[0023] Specifically, a comprehensive characterization system for high-salinity wastewater was established by constructing a seven-dimensional water quality feature vector. Hardness reflects the total calcium and magnesium content; calcium ion concentration quantifies easily scale-forming ions; average molecular weight of organic matter characterizes macromolecular pollutants; and conductivity reflects the total dissolved solids content. These four parameters collectively describe the chemical properties of the wastewater. After an electrochemical impedance spectroscopy sensor is embedded on the electrode surface, electrochemical interface characteristics are measured by applying an AC perturbation signal. The initial interfacial charge transfer resistance reflects the charge transfer resistance on the electrode surface; the initial double-layer capacitance reflects the charge storage capacity at the electrode-solution interface; and the initial mid-frequency slope reflects the impedance characteristics of the diffusion process. These three parameters constitute the electrochemical baseline fingerprint spectrum of the electrode surface, providing a comparative benchmark for subsequent dynamic monitoring.

[0024] Step S2: Calculate the initial current density based on hardness and conductivity, and pump the high-salt waste liquid into the electrocoagulation reactor for electrocoagulation hardness removal treatment; measure the real-time interfacial charge transfer resistance, real-time double-layer capacitance, and real-time mid-frequency slope using an electrochemical impedance spectroscopy sensor, and calculate the interfacial resistance growth rate, double-layer capacitance decay rate, and mid-frequency slope change rate relative to the initial interfacial charge transfer resistance, initial double-layer capacitance, and initial mid-frequency slope, respectively; identify the scale type of the electrode plate based on the interfacial resistance growth rate, double-layer capacitance decay rate, and mid-frequency slope change rate; input the interfacial resistance growth rate, double-layer capacitance decay rate, mid-frequency slope change rate, hardness, calcium ion concentration, average molecular weight of organic matter, and initial current density into the prediction model to obtain the remaining effective operating time of the electrode plate;

[0025] Specifically, the interfacial resistance growth rate quantifies the increase in electrode surface impedance by measuring the relative change in real-time interfacial charge transfer resistance compared to the initial value; the double-layer capacitance decay rate quantifies the reduction in active sites by measuring the relative decrease in real-time double-layer capacitance compared to the initial value; and the mid-frequency slope change rate quantifies the degree of obstruction in the diffusion process by measuring the relative shift of the real-time mid-frequency slope compared to the initial value. The numerical combination of these three parameters can distinguish scaling mechanisms. When the interfacial resistance increases significantly but the double-layer capacitance and mid-frequency slope change little, it indicates the formation of a non-conductive inorganic scale layer on the electrode surface, increasing charge transfer resistance but not altering the double-layer structure, thus identifying it as an inorganic scale deposition type. When the interfacial resistance increases while the double-layer capacitance decreases significantly and the mid-frequency slope changes significantly, it indicates that organic macromolecules cover active sites, leading to a loss of charge storage capacity and altering diffusion characteristics, thus identifying it as an organic passivation type. The prediction model, based on a nine-dimensional input feature vector, establishes a nonlinear mapping relationship between impedance spectrum characteristics and electrode failure time using a random forest regression algorithm, outputting the remaining effective operating time of the electrode, thus realizing the transformation from passively discovering failure to actively predicting failure.

[0026] Step S3: Optimize the initial current density based on the remaining effective operating time of the electrode to obtain the operating current density, obtain the electrocoagulation effluent based on the operating current density, and calculate the residual hardness of the electrocoagulation effluent based on the operating current density;

[0027] Specifically, the current density is dynamically optimized based on the predicted remaining effective operating time of the electrodes. When the remaining time is sufficient, the current density can be increased to enhance the treatment effect; when the remaining time is close to the threshold, the current density is reduced to extend the operating cycle and avoid frequent shutdowns. After the operating current density is determined, the residual hardness of the electrocoagulation effluent is calculated using the hardness removal rate formula. The hardness removal rate is positively correlated with the current density because the higher the current, the more flocculant is produced. It also shows a saturation growth relationship with the operating time because the removal rate is fast in the initial stage and tends to reach equilibrium in the later stage. The residual hardness is equal to the influent hardness multiplied by the unremoved proportion, which is one minus the hardness removal rate.

[0028] Step S4: Use residual hardness as a feedforward signal to adjust the electrodialysis treatment parameters, concentrate the electrocoagulated effluent by electrodialysis to obtain a concentrate, and then treat the concentrate by bipolar membrane electrodialysis to obtain an acid solution and an alkaline solution.

[0029] Specifically, the residual hardness of the electrocoagulated effluent is used as a feedforward compensation signal to pre-adjust the electrodialysis parameters, avoiding the impact of fluctuations in the front-end treatment effect on the back-end. The electrodialysis current density is negatively correlated with residual hardness. When residual hardness increases, the current density is reduced to slow ion migration and prevent rapid scaling on the membrane surface under high hardness conditions. The volume ratio of the concentration chamber decreases with increasing residual hardness, meaning the initial volume of the concentration chamber decreases to achieve a higher concentration factor within the same operating time to compensate for insufficient hardness removal in the front end. When the conductivity of the desalination chamber deviates from the set value, proportional-integral control is used to adjust the desalination water supply flow to stabilize the conductivity. When the conductivity change rate in the concentration chamber exceeds the threshold, the current density is reduced to prevent excessively rapid concentration leading to salting out. In bipolar membrane electrodialysis, the hydrogen ion transport number is greater than the hydroxide ion transport number. If the acid and alkali chambers have equal volumes, the acid concentration increases faster than the alkali concentration. By setting the volume ratio to the reciprocal of the transport number ratio, the acid and alkali concentrations reach their target values ​​simultaneously. The acid and alkali concentrations are calculated by dividing the conductivity of the acid chamber and the conductivity of the alkali chamber by their respective molar conductivity.

[0030] In one specific embodiment, step S1 includes:

[0031] The conductivity, hardness, calcium ion concentration, and average molecular weight of organic matter in the high-salt waste liquid were measured using a conductivity meter, hardness titrator, ion chromatograph, and gel permeation chromatograph, respectively.

[0032] Electrochemical impedance spectroscopy sensors with a three-electrode system are embedded at three positions on the surface of the aluminum electrode plate of the electrocoagulation reactor, at distances of 100 mm, 250 mm, and 400 mm from the bottom. The three-electrode system includes an aluminum disc working electrode, a silver-silver chloride reference electrode, and a platinum wire auxiliary electrode.

[0033] An AC perturbation signal with a frequency range of 0.01 Hz to 100 kHz and an amplitude of 10 mV was applied to the electrochemical impedance spectroscopy sensors at three locations using an electrochemical workstation.

[0034] The Nyquist plots at three locations were measured using an electrochemical workstation in a clean water environment. The semicircle diameter, mid-frequency slope, and low-frequency intercept of the Nyquist plots were extracted to obtain the initial interfacial charge transfer resistance, initial double-layer capacitance, and initial mid-frequency slope.

[0035] Specifically, water quality parameters were determined using standard analytical instruments to obtain key characteristic data of high-salt wastewater. A conductivity meter measured the solution resistance and converted the conductivity value to reflect the total ion concentration. A hardness titrator determined the total calcium and magnesium ions using complexometric titration, expressed as calcium carbonate equivalents. An ion chromatograph separated the molecules using an ion-exchange column and then quantitatively analyzed the calcium ion concentration using a conductivity detector. A gel permeation chromatograph separated organic molecules based on their permeation differences within the gel pores, calculated the molecular weight distribution based on retention time, and calculated the average molecular weight. The three-electrode system was embedded at different heights on the plates to monitor the spatial differences in vertical scale distribution. The aluminum disc working electrode was made of the same material as the plates to ensure the measurement results represented the actual plate condition. A silver-silver chloride reference electrode provided a stable potential reference, and a platinum wire auxiliary electrode formed the current loop.

[0036] The frequency range of the AC perturbation signal covers multiple timescales of the electrochemical process. The high-frequency band reflects solution resistance and electrode geometric capacitance, the mid-frequency band reflects charge transfer processes and double-layer charging and discharging, and the low-frequency band reflects diffusion processes and adsorption reactions. The amplitude is set to 10 mV to maintain a linear response and avoid significant perturbations that alter the electrode interface state. The Nyquist plot is drawn with the real part of impedance on the horizontal axis and the negative imaginary part of impedance on the vertical axis. The diameter of the semicircle corresponds to the charge transfer resistance value. The slope of the straight line in the mid-frequency region reflects the Weber impedance characteristics controlled by diffusion, and the intercept in the low-frequency region represents the limit value of the total impedance at zero frequency. The initial double-layer capacitance is calculated using the relationship between the frequency of the semicircular arc vertex and the charge transfer resistance. These three parameters together characterize the initial electrochemical state of the electrode surface under clean water conditions.

[0037] In one specific embodiment, step S2, calculating the initial current density based on hardness and conductivity, includes:

[0038] Normalize the hardness by dividing it by 1000 to obtain the normalized hardness value; raise the normalized hardness value to the power of 0.4 to obtain the hardness power term; normalize the conductivity by dividing it by 100 to obtain the conductivity normalized value; raise the conductivity normalized value to the power of 0.3 to obtain the conductivity power term.

[0039] Multiply the hardness power term by the conductivity power term and then multiply by a coefficient of 0.35 to obtain the initial current density, in amperes per square meter.

[0040] Specifically, hardness normalization converts the value from the milligrams per liter range to a dimensionless parameter by dividing by 1000, facilitating subsequent power-law calculations. The 0.4 power-law calculation establishes a non-linear relationship between hardness and current density, reflecting the influence of hardness on flocculant demand. A power exponent less than 1 indicates that the increase in current density demand with increasing hardness exhibits a diminishing marginal return. The value range of the hardness power term is typically between 0.5 and 1.5. Conductivity normalization converts the value from the millisieverts per centimeter range to a dimensionless parameter by dividing by 100. The 0.3 power-law calculation reflects the promoting effect of conductivity on the electrochemical reaction rate. A power exponent lower than the hardness power exponent indicates that the influence of conductivity is relatively small. The value range of the conductivity power term is typically between 0.9 and 1.2.

[0041] Multiplying the two power terms realizes the coupled influence of hardness and conductivity on the initial current density. The coefficient 0.35, derived from the regression fitting of experimental data in the literature, is used to convert the dimensionless product into a physically meaningful current density value. This coefficient comprehensively considers factors such as electrode material characteristics, electrode spacing, and reactor geometric parameters. The calculated initial current density directly determines the electric field strength applied during electrocoagulation startup. Too low a current density results in insufficient flocculant production rate, failing to effectively remove hardness ions; too high a current density accelerates electrode consumption and increases energy consumption. Adaptive calculation of the initial current density using water quality parameters avoids the blind operation of fixed parameters.

[0042] In one specific embodiment, step S2 calculates the rate of increase of interface resistance, the rate of decay of double-layer capacitance, and the rate of change of mid-frequency slope relative to the initial interface charge transfer resistance, the initial double-layer capacitance, and the initial mid-frequency slope, including:

[0043] Subtract the initial interface charge transfer resistance from the real-time interface charge transfer resistance, divide by the initial interface charge transfer resistance, and finally multiply by 100 to obtain the interface resistance growth rate, in percentage form.

[0044] Subtract the real-time electric double layer capacitance from the initial electric double layer capacitance, divide by the initial electric double layer capacitance, and finally multiply by 100 to obtain the electric double layer capacitance decay rate, in percentage.

[0045] Subtract the initial intermediate frequency slope from the real-time intermediate frequency slope, divide by the initial intermediate frequency slope, and finally multiply by 100 to obtain the intermediate frequency slope change rate, in percentage form.

[0046] Calculate the average growth rate of the interface resistance at the three locations to obtain the average interface resistance growth rate.

[0047] Calculate the average value of the double-layer capacitance decay rate corresponding to the three positions to obtain the average double-layer capacitance decay rate;

[0048] Calculate the average of the rate of change of the mid-frequency slope at the three positions to obtain the average rate of change of the mid-frequency slope.

[0049] Specifically, the interface resistance growth rate uses a relative change calculation method to eliminate the influence of differences in the initial states of different plates. The absolute increment obtained by subtracting the initial value from the real-time interface charge transfer resistance reflects the actual increase in the plate surface impedance. Dividing by the initial value and normalizing gives the relative increment, which is then multiplied by 100 to convert to a percentage for easy threshold setting. A positive value indicates the formation of a scale layer or passivation film on the plate surface that hinders charge transfer. The calculation order for the double-layer capacitance decay rate is the reverse of the interface resistance growth rate. The initial value is subtracted from the real-time value because a decrease in capacitance represents a deterioration in the plate state. The active sites being covered by contaminants weakens the double-layer charging and discharging capability. Dividing by the initial value and normalizing, then multiplying by 100 gives the decay percentage. A positive value indicates the degree of capacitance loss. The mid-frequency slope change rate also uses the relative change of the real-time value minus the initial value. The mid-frequency slope reflects the impedance characteristics of the diffusion process. An increased slope indicates increased diffusion resistance, while a decreased slope indicates a change in the diffusion path. The absolute value of the change rate reflects the degree of interference in the diffusion process.

[0050] The three locations correspond to local areas of the electrode plate: the bottom 100 mm, the middle 250 mm, and the top 400 mm, respectively. The bottom location is more prone to calcium and magnesium precipitation due to gravity settling and lower flow velocity. The middle location is a transitional zone with both settling and convection characteristics. The top location is more affected by aeration disturbance and the precipitates are less likely to remain. The average rate of change of interfacial resistance, the average rate of decrease of double-layer capacitance, and the average rate of change of mid-frequency slope at the three locations are calculated to obtain a comprehensive evaluation index of the surface state of the entire electrode plate. The average value eliminates the interference of local abnormal fluctuations. When the rate of change at the three locations differs greatly, it indicates that the scale distribution on the electrode plate surface is uneven. When the rate of change at the three locations is close, it indicates that the scaling process is relatively uniform. The average value serves as the input feature for subsequent scale type identification and remaining operating time prediction.

[0051] In one specific embodiment, step S2, which identifies the type of fouling on the electrode plate based on the interface resistance growth rate, the double-layer capacitance decay rate, and the intermediate frequency slope change rate, includes:

[0052] When the average interfacial resistance growth rate is greater than 30%, the average double-layer capacitance decay rate is less than 20%, and the average mid-frequency slope change rate is less than 10%, the electrode fouling type is identified as inorganic salt scale deposition; when the average interfacial resistance growth rate is greater than 20%, the average double-layer capacitance decay rate is greater than 40%, and the average mid-frequency slope change rate is greater than 25%, the electrode fouling type is identified as organic passivation.

[0053] The average interface resistance growth rate, average double-layer capacitance decay rate, average mid-frequency slope change rate, hardness, calcium ion concentration, average molecular weight of organic matter, initial current density, and running time are constructed into a nine-dimensional input feature vector.

[0054] The nine-dimensional input feature vector is input into the random forest regression model, which contains 200 decision trees, a maximum tree depth of 15, and a minimum number of leaf node samples of 5.

[0055] The remaining effective running time of the plates is output using a random forest regression model.

[0056] Specifically, the identification logic for inorganic salt scale deposition is based on the electrochemical characteristics of calcium and magnesium compounds forming a non-conductive scale layer on the electrode surface. The scale layer increases charge transfer resistance, leading to a significant increase in interfacial resistance exceeding 30%. However, inorganic salt crystals do not adsorb onto active sites, so the double-layer capacitance only decreases slightly, remaining below 20%. The dense structure of the scale layer has limited impact on the diffusion process, keeping the mid-frequency slope change rate below 10%. When all three threshold conditions are met, it is identified as inorganic salt scale. The identification logic for organic passivation is based on the electrochemical characteristics of macromolecular organic matter covering active sites. Although the organic matter adsorption layer increases charge transfer resistance, the degree is lower than that of inorganic scale, so the threshold for the interfacial resistance growth rate is set at 20%. Macromolecular coverage leads to the failure of a large number of active sites, causing a sharp decrease in double-layer capacitance exceeding 40%. Organic matter alters the diffusion path and interfacial microstructure, resulting in a significant shift in the mid-frequency slope exceeding 25%. When all three threshold conditions are met, it is identified as organic passivation. The threshold combination for the two types is derived from the statistical analysis of impedance spectral evolution patterns under different water quality conditions in the control experiment.

[0057] The nine-dimensional input feature vector integrates electrochemical monitoring data and water quality characteristic data. The average interfacial resistance growth rate, average double-layer capacitance decay rate, and average mid-frequency slope change rate characterize the current state of the electrode. Hardness and calcium ion concentration reflect the driving force of inorganic scale deposition, the average molecular weight of organic matter reflects the passivation risk of organic matter, the initial current density determines the flocculant production rate and the intensity of the electrode electrochemical reaction, and the accumulated operating time reflects the historical operating load. These nine dimensions describe the influencing factors of electrode failure from different perspectives. The random forest regression model establishes a nonlinear mapping relationship between input features and the remaining effective operating time of the electrode through ensemble learning. The model contains 200 decision trees, each trained independently. The overfitting risk is reduced by averaging the output value. The maximum tree depth is limited to 15 to prevent excessive complexity of a single tree, and the minimum number of leaf node samples is set to 5 to ensure that each leaf node has sufficient samples to support the prediction results.

[0058] The model training data comes from 50 electrocoagulation experiments under different water quality conditions. The impedance spectrum evolution trajectory and corresponding running time are recorded from start-up to complete passivation of the electrode. Complete passivation of the electrode is defined as the inability to maintain effective flocculation when the total current drops to less than 30% of the initial value. The training samples cover water quality ranges with hardness of 200 to 3500 mg / L and average molecular weight of organic matter of 5000 to 30000 Daltons. After the model inputs a nine-dimensional feature vector, it performs regression prediction through 200 decision trees. Each tree establishes a feature space segmentation rule based on the training data. Starting from the root node, it branches layer by layer according to the feature value until the maximum depth is reached or the number of leaf node samples is less than 5, and then stops the segmentation. After the test sample is input, it reaches the leaf node along the branch path of each tree to obtain the predicted value of that tree. The average of the 200 predicted values ​​is used to obtain the final output of the remaining effective running time of the electrode.

[0059] Figure 2 This is a schematic diagram illustrating the change of electrochemical parameters on the electrode surface with operating time in an embodiment of this application. Figure 2 As shown, the interfacial resistance growth rate and the double-layer capacitance decay rate exhibit different growth trends with the extension of the electrocoagulation reactor's operating time. The interfacial resistance growth rate, marked by solid circles, increases from 0 to 125% within 90 minutes of operation, showing a relatively rapid growth rate. The double-layer capacitance decay rate, marked by dashed boxes, increases from 0 to 85% within the same timeframe, showing a relatively gradual increase. The inorganic scale threshold line (30%) is marked in the figure. When the interfacial resistance growth rate exceeds this threshold while the double-layer capacitance decay rate is below it, the scale type on the electrode plate can be identified as inorganic scale deposition. This figure verifies the effectiveness of this application in real-time monitoring of electrode surface state changes using an electrochemical impedance spectroscopy sensor.

[0060] In one specific embodiment, step S3, which optimizes the initial current density based on the remaining effective operating time of the electrode to obtain the operating current density, includes:

[0061] The objective function is constructed as follows: energy consumption per unit volume multiplied by 0.5, plus the reciprocal of the remaining effective operating time of the electrode multiplied by 0.3, plus the square of the difference between the effluent chemical oxygen demand and 5000 mg / L multiplied by 0.2; the constraint conditions are set as follows: the remaining effective operating time of the electrode is greater than or equal to 60 minutes and the effluent chemical oxygen demand is less than or equal to 5500 mg / L.

[0062] A genetic algorithm was used to optimize the objective function in the range of 60 to 120 amperes per square meter. The genetic algorithm had a population size of 50, an iteration number of 30, a crossover probability of 0.8, and a mutation probability of 0.1 to obtain the operating current density.

[0063] Divide the operating current density by 100, raise it to the power of 0.6, multiply by 1, subtract the negative exponent of the already running time divided by 45, and then multiply by 0.82 to obtain the hardness removal rate.

[0064] Multiply the hardness by 1 and subtract the hardness removal rate to obtain the residual hardness of the electrocoagulation effluent.

[0065] Specifically, the objective function integrates three optimization objectives: energy consumption, operating time, and effluent water quality. Energy consumption per unit volume reflects economic efficiency; the reciprocal of the remaining effective operating time of the electrode reflects equipment utilization; and the square of the difference between the effluent chemical oxygen demand (COD) and the target value of 5000 mg / L reflects the degree of water quality compliance. Weighting coefficients of 0.5, 0.3, and 0.2 quantify the importance of each objective, with energy consumption having the highest weight reflecting the principle of energy conservation priority. The reciprocal form of the operating time means that the shorter the remaining time, the larger the objective function value, prompting the algorithm to select a current density that extends the operating cycle. The square term of the COD deviation causes the penalty for exceeding the standard to increase non-linearly with the degree of deviation. Constraints are set with a lower limit of 60 minutes for the remaining effective operating time of the electrode to ensure at least one hour of stable operation and avoid frequent shutdowns for cleaning; and an upper limit of 5500 mg / L for the effluent COD, leaving a 10% safety margin to prevent water quality fluctuations from exceeding the standard.

[0066] The genetic algorithm searches for the optimal solution within a current density search space of 60 to 120 amperes per square meter. A population size of 50 indicates that 50 candidate current density schemes are maintained per generation. The number of iterations (30) indicates termination after 30 rounds of evolution. A crossover probability of 0.8 indicates that 80% of individuals generate offspring through pairwise gene exchange. A mutation probability of 0.1 indicates that 10% of gene loci are randomly altered to increase population diversity. The algorithm outputs the operating current density that minimizes the objective function. In the hardness removal rate calculation formula, the operating current density is divided by 100 and then raised to the power of 0.6 to reflect the effect of current density on flocculant production. The running time is divided by 45, the negative number is taken, and the exponent is calculated to obtain the time decay factor. Subtracting the time decay factor from 1 yields the time correction factor, reflecting the saturation growth characteristic of the removal rate over time. Multiplying these two factors by a coefficient of 0.82 gives the hardness removal rate. Multiplying the hardness by 1 and subtracting the hardness removal rate gives the residual hardness value of the electrocoagulated water.

[0067] Figure 3 This is a schematic diagram comparing the energy consumption of the traditional method and the optimized method in the embodiments of this application. Figure 3 As shown, the energy consumption per unit volume of the traditional method and the optimized method in the three treatment stages of electrocoagulation, electrodialysis, and bipolar membrane electrodialysis, as well as the total energy consumption, are compared. The traditional method is represented by a bar chart with diagonally filled bars, while the optimized method is represented by a bar chart with reverse diagonally filled bars. In the electrocoagulation stage, the energy consumption of the traditional method is 3.2 kWh / ... The optimization method reduced it to 2.4 kWh / Energy savings of 25.0%; in the electrodialysis process, energy consumption decreased from 2.8 kWh / kWh to 2.1 kWh / kWh. Energy savings of 25.0%; in the bipolar membrane electrodialysis process, energy consumption decreased from 1.5 kWh / kWh to 1.2 kWh / kWh. Energy savings of 20.0%; total energy consumption reduced from 7.5 kWh / kWh. Overall energy savings of 24.0% were achieved. This figure demonstrates that this application significantly reduced system energy consumption through plate remaining operating time prediction and current density optimization.

[0068] In one specific embodiment, step S4 uses residual hardness as a feedforward signal to adjust the electrodialysis treatment parameters, including:

[0069] The electrodialysis current density and the concentration-to-dilute chamber volume ratio were calculated based on the residual hardness. The electrodialysis current density was negatively correlated with the residual hardness, and the concentration-to-dilute chamber volume ratio decreased as the residual hardness increased.

[0070] Monitor the conductivity of the desalination chamber and the concentration chamber. When the conductivity of the desalination chamber deviates from the set value, adjust the freshwater replenishment flow rate according to the deviation through proportional-integral control.

[0071] When the rate of change of conductivity in the concentration chamber exceeds the preset threshold, the electrodialysis current density is reduced and the operation continues until the conductivity in the concentration chamber reaches the target concentration value to obtain the concentrate.

[0072] The concentrate is pumped into the salt chamber of the bipolar membrane electrodialysis stack. The volume ratio of the acid chamber to the alkali chamber is set according to the migration number ratio of hydrogen ions to hydroxide ions. The acid concentration and alkali concentration are obtained by monitoring the conductivity of the acid chamber and the alkali chamber, respectively, and the acid solution and alkali solution are obtained.

[0073] Specifically, the calculation logic for the negative correlation between electrodialysis current density and residual hardness is as follows: divide the baseline hardness (206 mg / L) by the residual hardness, then raise the result to the power of 0.3, and multiply by the baseline current density (35 mA / cm²). When the residual hardness is higher than the baseline value, the quotient is less than 1, causing the power term to decrease, thus reducing the current density. Lowering the current density slows down the ion migration rate, prolongs the membrane cleaning cycle, and prevents the rapid deposition of calcium and magnesium ions on the membrane surface under high hardness conditions. The concentration-to-dilute chamber volume ratio is calculated by subtracting the difference between the residual hardness and the baseline hardness from 0.5 and dividing by 3000. When the residual hardness increases, the difference increases, leading to a decrease in the volume ratio, meaning the initial volume of the concentration chamber is smaller than that of the dilute chamber. The smaller concentration chamber volume allows the same amount of salt to be distributed in less liquid, accelerating the rate of concentration increase and achieving a higher concentration factor within the same operating time to compensate for the insufficient hardness removal in the upstream stage. In proportional-integral control, the proportional term multiplies the conductivity deviation of the desalination chamber by a coefficient of 0.15 liters per hour per millisecond per centimeter to generate an instantaneous response, while the integral term integrates the deviation over time and multiplies it by a coefficient of 0.02 liters per hour per millisecond per centimeter per minute to accumulate historical deviations and eliminate steady-state errors. The sum of the two terms is added to the baseline flow rate of 4.0 liters per hour to obtain the adjusted freshwater replenishment flow rate.

[0074] The rate of change of conductivity in the concentration chamber over time is calculated by dividing the difference between two adjacent measurements by the time interval. When the rate of change exceeds 0.5 mS / cm / min, it indicates that the concentration rate is too fast and there is a risk of salt precipitation. At this time, the electrodialysis current density is multiplied by 0.95 to achieve a 5% reduction and slow down ion migration. The process continues until the conductivity of the concentration chamber reaches 185 mS / cm, corresponding to a total dissolved solids of 110 g / L, at which point the concentration is stopped and the concentrate is obtained. In bipolar membrane electrodialysis, the hydrogen ion transport number is 0.82 and the hydroxide ion transport number is 0.17, with a transport number ratio of 4.82. To ensure that the acid and alkali concentrations increase synchronously, the volume ratio of the acid chamber to the alkali chamber needs to be set at 4.82:1, meaning the acid chamber volume is larger than the alkali chamber. The hydrogen ion migration rate is fast, but it is dispersed in a larger volume, so that the concentration increase rate matches the concentration increase rate of hydroxide ions in a smaller volume. The acid concentration is obtained by dividing the conductivity of the acid chamber by the molar conductivity of hydrochloric acid (42.6 mS / cm / mol / L), and the alkali concentration is obtained by dividing the conductivity of the alkali chamber by the molar conductivity of sodium hydroxide (24.8 mS / cm / mol / L).

[0075] The above describes the high-salt waste liquid electrocoagulation hardening and electrodialysis resource recovery treatment method in the embodiments of this application. The following describes the high-salt waste liquid electrocoagulation hardening and electrodialysis resource recovery treatment system in the embodiments of this application. One embodiment of the high-salt waste liquid electrocoagulation hardening and electrodialysis resource recovery treatment system in the embodiments of this application includes:

[0076] The acquisition module is used to collect the hardness, calcium ion concentration, average molecular weight of organic matter, and conductivity of high-salt waste liquid; an electrochemical impedance spectroscopy sensor is set on the electrode surface of the electrocoagulation reactor to measure the initial interfacial charge transfer resistance, initial double-layer capacitance, and initial mid-frequency slope.

[0077] The identification module is used to calculate the initial current density based on the hardness and conductivity, and pump the high-salt waste liquid into the electrocoagulation reactor for electrocoagulation hardness removal treatment; measure the real-time interfacial charge transfer resistance, real-time double-layer capacitance, and real-time mid-frequency slope using the electrochemical impedance spectroscopy sensor, and calculate the interfacial resistance growth rate, double-layer capacitance decay rate, and mid-frequency slope change rate relative to the initial interfacial charge transfer resistance, the initial double-layer capacitance, and the initial mid-frequency slope, respectively; identify the scale type of the electrode plate based on the interfacial resistance growth rate, double-layer capacitance decay rate, and mid-frequency slope change rate; input the interfacial resistance growth rate, double-layer capacitance decay rate, mid-frequency slope change rate, hardness, calcium ion concentration, average molecular weight of organic matter, and initial current density into the prediction model to obtain the remaining effective operating time of the electrode plate;

[0078] The calculation module is used to optimize the initial current density based on the remaining effective operating time of the electrode to obtain the operating current density, obtain the electrocoagulation effluent based on the operating current density, and calculate the residual hardness of the electrocoagulation effluent based on the operating current density.

[0079] The adjustment module is used to adjust the electrodialysis treatment parameters by using the residual hardness as a feedforward signal, to concentrate the electrocoagulated effluent by electrodialysis to obtain a concentrate, and to treat the concentrate by bipolar membrane electrodialysis to obtain an acid solution and an alkaline solution.

[0080] The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for hardening removal and electrodialysis resource treatment of high-salinity waste liquid by electroflocculation, characterized in that, The method includes: Step S1: Collect the hardness, calcium ion concentration, average molecular weight of organic matter, and conductivity of the high-salt waste liquid; set an electrochemical impedance spectroscopy sensor on the electrode surface of the electrocoagulation reactor to measure the initial interfacial charge transfer resistance, initial double-layer capacitance, and initial mid-frequency slope. Step S2: Calculate the initial current density based on the hardness and conductivity, and pump the high-salt waste liquid into the electrocoagulation reactor for electrocoagulation hardness removal treatment; measure the real-time interface charge transfer resistance, real-time double-layer capacitance, and real-time mid-frequency slope using the electrochemical impedance spectroscopy sensor, and calculate the interface resistance growth rate, double-layer capacitance decay rate, and mid-frequency slope change rate relative to the initial interface charge transfer resistance, initial double-layer capacitance, and initial mid-frequency slope, respectively; identify the electrode plate scaling type based on the interface resistance growth rate, double-layer capacitance decay rate, and mid-frequency slope change rate; input the interface resistance growth rate, double-layer capacitance decay rate, mid-frequency slope change rate, hardness, calcium ion concentration, average molecular weight of organic matter, and initial current density into the prediction model to obtain the remaining effective operating time of the electrode plate; Step S3: Optimize the initial current density based on the remaining effective operating time of the electrode to obtain the operating current density, obtain the electrocoagulation effluent based on the operating current density, and calculate the residual hardness of the electrocoagulation effluent based on the operating current density; Step S4: Using the residual hardness as a feedforward signal to adjust the electrodialysis treatment parameters, the electrocoagulated effluent is concentrated by electrodialysis to obtain a concentrate, and the concentrate is subjected to bipolar membrane electrodialysis to obtain an acid solution and an alkaline solution.

2. The high-salinity liquid waste electrocoagulation softening and electrodialysis resource recovery process of claim 1, wherein, Step S1 includes: The high-salt waste liquid was measured using a conductivity meter, a hardness titrator, an ion chromatograph, and a gel permeation chromatograph, respectively, to obtain the conductivity, hardness, calcium ion concentration, and average molecular weight of the organic matter. The electrochemical impedance spectroscopy sensor with a three-electrode system is embedded at three positions on the surface of the aluminum electrode plate of the electrocoagulation reactor, at 100 mm, 250 mm and 400 mm from the bottom, respectively. The three-electrode system includes an aluminum disc working electrode, a silver-silver chloride reference electrode and a platinum wire auxiliary electrode. An AC perturbation signal with a frequency range of 0.01 Hz to 100 kHz and an amplitude of 10 mV was applied to the electrochemical impedance spectroscopy sensors at the three locations using an electrochemical workstation. In a clean water environment, the Nyquist plots at the three locations are measured using the electrochemical workstation. The semicircle diameter, mid-frequency region slope, and low-frequency region intercept of the Nyquist plots are extracted to obtain the initial interface charge transfer resistance, the initial double-layer capacitance, and the initial mid-frequency region slope.

3. The high-salinity liquid waste electrocoagulation softening and electrodialysis resource recovery process of claim 2, wherein, Step S2, which calculates the initial current density based on the hardness and the conductivity, includes: The hardness is normalized by dividing it by 1000 to obtain a normalized hardness value; the normalized hardness value is then raised to the power of 0.4 to obtain a hardness power term; the conductivity is normalized by dividing it by 100 to obtain a conductivity normalized value; the normalized conductivity value is then raised to the power of 0.3 to obtain a conductivity power term. The initial current density is obtained by multiplying the hardness power term by the conductivity power term and then multiplying by a coefficient of 0.

35.

4. The high-salinity liquid waste electrocoagulation softening and electrodialysis resource recovery process of claim 3, wherein, Step S2 involves calculating the rate of increase of the interface resistance, the rate of decrease of the double-layer capacitance, and the rate of change of the mid-frequency slope relative to the initial interface charge transfer resistance, the initial double-layer capacitance, and the initial mid-frequency slope, including: Subtract the initial interface charge transfer resistance from the real-time interface charge transfer resistance, divide by the initial interface charge transfer resistance, and finally multiply by 100 to obtain the interface resistance growth rate, in percentage form. Subtract the real-time electric double layer capacitance from the initial electric double layer capacitance, divide by the initial electric double layer capacitance, and finally multiply by 100 to obtain the electric double layer capacitance decay rate, in percentage. Subtract the initial intermediate frequency slope from the real-time intermediate frequency slope, divide by the initial intermediate frequency slope, and finally multiply by 100 to obtain the rate of change of the intermediate frequency slope, in percentage form. Calculate the average value of the interface resistance growth rate corresponding to the three positions to obtain the average interface resistance growth rate; Calculate the average value of the double-layer capacitance decay rate corresponding to the three positions to obtain the average double-layer capacitance decay rate; Calculate the average value of the mid-frequency slope change rate corresponding to the three positions to obtain the average mid-frequency slope change rate.

5. The high-salinity liquid waste electrocoagulation softening and electrodialysis resource recovery process of claim 4, wherein, Step S2, which identifies the type of fouling on the electrode plate based on the interface resistance growth rate, the double-layer capacitance decay rate, and the mid-frequency slope change rate, includes: When the average interface resistance growth rate is greater than 30%, the average double-layer capacitance decay rate is less than 20%, and the average mid-frequency slope change rate is less than 10%, the electrode fouling type is identified as inorganic salt scale deposition; when the average interface resistance growth rate is greater than 20%, the average double-layer capacitance decay rate is greater than 40%, and the average mid-frequency slope change rate is greater than 25%, the electrode fouling type is identified as organic passivation. The average interface resistance growth rate, the average double-layer capacitance decay rate, the average mid-frequency slope change rate, the hardness, the calcium ion concentration, the average molecular weight of organic matter, the initial current density, and the running time are constructed into an eight-dimensional input feature vector. The eight-dimensional input feature vector is input into a random forest regression model, which contains 200 decision trees, a maximum tree depth of 15, and a minimum number of leaf node samples of 5. The remaining effective running time of the electrode is output through the random forest regression model.

6. The high-salinity liquid waste electrocoagulation softening and electrodialysis resource recovery process of claim 5, wherein, Step S3, which optimizes the initial current density based on the remaining effective operating time of the electrode to obtain the operating current density, includes: The objective function is constructed as follows: energy consumption per unit volume multiplied by 0.5, plus the reciprocal of the remaining effective operating time of the electrode plate multiplied by 0.3, plus the square of the difference between the chemical oxygen demand of the effluent and 5000 mg / L multiplied by 0.2; the constraint conditions are set as follows: the remaining effective operating time of the electrode plate is greater than or equal to 60 minutes and the chemical oxygen demand of the effluent is less than or equal to 5500 mg / L. The objective function was optimized using a genetic algorithm within the range of 60 to 120 amperes per square meter. The genetic algorithm had a population size of 50, an iteration number of 30, a crossover probability of 0.8, and a mutation probability of 0.1 to obtain the operating current density. The operating current density is divided by 100 and then raised to the power of 0.

6. This result is multiplied by 1, minus the exponent value of the operating time divided by 45 (which is the negative number), and then multiplied by 0.82 to obtain the hardness removal rate. In the formula for calculating the hardness removal rate, the operating current density divided by 100 and then raised to the power of 0.6 reflects the effect of current density on the amount of flocculant produced. The operating time is divided by 45, the negative number is taken, and then the exponent value is calculated to obtain the time decay factor. 1 is subtracted from the time decay factor to obtain the time correction factor, which reflects the saturation growth characteristics of the removal rate over time. The two factors are multiplied together and then multiplied by the coefficient 0.82 to obtain the hardness removal rate. The residual hardness of the electrocoagulated effluent is obtained by multiplying the hardness by 1 and subtracting the hardness removal rate.

7. The method for electrocoagulation and electrodialysis resource recovery of high-salt waste liquid according to claim 6, characterized in that, In step S4, the residual hardness is used as a feedforward signal to adjust the electrodialysis treatment parameters, including: The electrodialysis current density and concentration-to-dilute chamber volume ratio are calculated based on the residual hardness. The electrodialysis current density is negatively correlated with the residual hardness, and the concentration-to-dilute chamber volume ratio decreases as the residual hardness increases. The conductivity of the desalination chamber and the conductivity of the concentration chamber are monitored. When the conductivity of the desalination chamber deviates from the set value, the freshwater replenishment flow rate is adjusted according to the deviation through proportional-integral control. When the rate of change of conductivity in the concentration chamber exceeds a preset threshold, the electrodialysis current density is reduced, and the process continues until the conductivity in the concentration chamber reaches the target concentration value, thereby obtaining the concentrate. The concentrate is pumped into the salt chamber of the bipolar membrane electrodialysis stack. The volume ratio of the acid chamber to the alkali chamber is set according to the migration number ratio of hydrogen ions to hydroxide ions. The acid concentration and alkali concentration are obtained by monitoring the conductivity of the acid chamber and the conductivity of the alkali chamber, respectively, thus obtaining the acid solution and the alkali solution.

8. A high-salinity liquid waste electrocoagulation softening and electrodialysis resource recovery system, characterized in that, For implementing the high-salt waste liquid electrocoagulation hardening and electrodialysis resource recovery treatment method as described in any one of claims 1-7, the high-salt waste liquid electrocoagulation hardening and electrodialysis resource recovery treatment system comprises: The acquisition module is used to acquire the hardness, calcium ion concentration, average molecular weight of organic matter, and conductivity of high-salt waste liquid; an electrochemical impedance spectroscopy sensor is set on the electrode surface of the electrocoagulation reactor to measure the initial interfacial charge transfer resistance, initial double-layer capacitance, and initial mid-frequency slope. The identification module is used to calculate the initial current density based on the hardness and conductivity, and pump the high-salt waste liquid into the electrocoagulation reactor for electrocoagulation hardness removal treatment; measure the real-time interfacial charge transfer resistance, real-time double-layer capacitance, and real-time mid-frequency slope using the electrochemical impedance spectroscopy sensor, and calculate the interfacial resistance growth rate, double-layer capacitance decay rate, and mid-frequency slope change rate relative to the initial interfacial charge transfer resistance, the initial double-layer capacitance, and the initial mid-frequency slope, respectively; identify the scale type of the electrode plate based on the interfacial resistance growth rate, double-layer capacitance decay rate, and mid-frequency slope change rate; input the interfacial resistance growth rate, double-layer capacitance decay rate, mid-frequency slope change rate, hardness, calcium ion concentration, average molecular weight of organic matter, and initial current density into the prediction model to obtain the remaining effective operating time of the electrode plate; The calculation module is used to optimize the initial current density based on the remaining effective operating time of the electrode to obtain the operating current density, obtain the electrocoagulation effluent based on the operating current density, and calculate the residual hardness of the electrocoagulation effluent based on the operating current density. The adjustment module is used to adjust the electrodialysis treatment parameters by using the residual hardness as a feedforward signal, to concentrate the electrocoagulated effluent by electrodialysis to obtain a concentrate, and to treat the concentrate by bipolar membrane electrodialysis to obtain an acid solution and an alkaline solution.

9. The system of claim 8, wherein, The hardness, calcium ion concentration, average molecular weight of organic matter, and conductivity of the high-salt waste liquid were collected. An electrochemical impedance spectroscopy sensor was installed on the electrode surface of the electrocoagulation reactor to measure the initial interfacial charge transfer resistance, initial double-layer capacitance, and initial mid-frequency slope, including: The high-salt waste liquid was measured using a conductivity meter, a hardness titrator, an ion chromatograph, and a gel permeation chromatograph to obtain the conductivity, hardness, calcium ion concentration, and average molecular weight of the organic matter. The electrochemical impedance spectroscopy sensor with a three-electrode system is embedded at three positions on the surface of the aluminum electrode plate of the electrocoagulation reactor, at 100 mm, 250 mm and 400 mm from the bottom, respectively. The three-electrode system includes an aluminum disc working electrode, a silver-silver chloride reference electrode and a platinum wire auxiliary electrode. An AC perturbation signal with a frequency range of 0.01 Hz to 100 kHz and an amplitude of 10 mV was applied to the electrochemical impedance spectroscopy sensors at the three locations using an electrochemical workstation. In a clean water environment, the Nyquist plots at the three locations are measured using the electrochemical workstation. The semicircle diameter, mid-frequency region slope, and low-frequency region intercept of the Nyquist plots are extracted to obtain the initial interface charge transfer resistance, the initial double-layer capacitance, and the initial mid-frequency region slope.

10. The system of claim 9, wherein, Calculating the initial current density based on the hardness and conductivity includes: The hardness is normalized by dividing it by 1000 to obtain a normalized hardness value; the normalized hardness value is then raised to the power of 0.4 to obtain a hardness power term; the conductivity is normalized by dividing it by 100 to obtain a conductivity normalized value; the normalized conductivity value is then raised to the power of 0.3 to obtain a conductivity power term. The initial current density is obtained by multiplying the hardness power term by the conductivity power term and then multiplying by a coefficient of 0.35.

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