Ozone oxidation micro-electrolysis method and system for RO concentrated water treatment

Abstract

The invention belongs to the technical field of RO (reverse osmosis) concentrated water pretreatment, and provides an ozone oxidation micro-electrolysis method and system for RO concentrated water treatment, in a plurality of historical treatment cycles, the ozone demand quantity during RO concentrated water ozone oxidation in each historical treatment cycle is obtained, and the ozone consumption range is obtained through treatment and output; the method is beneficial for avoiding substandard pollutant degradation caused by abnormal ozone consumption and guaranteeing the stability of the pretreatment process, and by obtaining ozone consumption in a plurality of historical treatment periods and excess content in a Fe-C micro-electrolysis coupling stage, correlation analysis is carried out to obtain a consumption correlation coefficient, and the consumption correlation coefficient is used for analyzing the ozone consumption in the plurality of historical treatment periods and the excess content in the Fe-C micro-electrolysis coupling stage. According to the method, the incidence relation between the ozone consumption and the excessive content under different working conditions is reflected, and the RO concentrated water pretreatment quality is improved, so that excessive supply and invalid consumption of ozone are avoided, the use amount of the ozone is reduced, and the adaptability of the pretreatment process to different working conditions is enhanced.

Description

Technical Field

[0001] This invention belongs to the field of RO concentrate pretreatment technology, specifically an ozone oxidation micro-electrolysis method and system for RO concentrate treatment. Background Technology

[0002] In the field of industrial wastewater treatment, the treatment of RO (reverse osmosis) concentrate has always been a challenge. RO concentrate contains high concentrations of pollutants such as organic matter and inorganic salts. Direct discharge of such concentrate would cause serious environmental pollution. Therefore, effective pretreatment methods are needed to reduce its pollutant content in order to meet subsequent treatment or discharge requirements.

[0003] In existing technologies, on the one hand, the differences in the required pollutant content for degradation in RO concentrate over different historical treatment cycles are not fully considered. Because the composition and concentration of pollutants in different batches of RO concentrate vary, a fixed ozone supply is insufficient to meet actual needs. This leads to either insufficient ozone supply during actual treatment, resulting in substandard pollutant degradation and impacting subsequent treatment processes and water quality safety; or excessive ozone supply, leading to ozone waste. On the other hand, there is a lack of in-depth research on the relationship between the Fe-C micro-electrolysis coupling stage and the ozone oxidation stage. Existing technologies do not analyze the relationship between ozone consumption during the ozone oxidation stage and excess ozone content during the Fe-C micro-electrolysis coupling stage, failing to reflect the correlation between the two under different operating conditions. This makes it prone to excessive ozone supply and ineffective consumption. Furthermore, in the RO concentrate pretreatment process, no excess warning model based on the ozone consumption range and correlation has been constructed, making it impossible to provide early warning of ozone levels in the subsequent ozone oxidation stage. Moreover, the location range of the fastest time period has not been determined, making it impossible to adjust the generation rate in a timely manner based on the content within the current target time period.

[0004] Therefore, the present invention provides an ozone oxidation micro-electrolysis method and system for RO concentrate treatment. Summary of the Invention

[0005] In order to overcome the shortcomings of the prior art, at least one technical problem raised in the background art is solved.

[0006] The technical solution adopted by this invention to solve its technical problem is: In a first aspect, an ozone oxidation micro-electrolysis method for treating RO concentrate includes the following steps: The ozone demand during RO concentrate ozone oxidation in multiple historical treatment cycles is processed to output the ozone consumption range. Based on the ozone consumption during the ozone oxidation stage of RO concentrate in multiple historical treatment cycles, and the excess ozone during the Fe-C micro-electrolysis coupling stage... Content, construct correlation analysis curves, and perform correlation degree analysis to obtain the consumption correlation coefficient: Linear analysis is performed on the constructed correlation curves. If a positive linear correlation is found, the consumption correlation coefficient and the ozone depletion range are combined to construct... Excessive warning model; In the Fe-C micro-electrolysis coupling stage, the generation rate of each historical processing period within the historical processing cycle is obtained and analyzed to determine the fastest generation rate, thus obtaining the corresponding fastest historical period. Stability analysis of these periods is then performed across multiple historical cycles to determine the location interval of the fastest period. Within this fastest period location interval, based on… The over-prevention model yielded the following results: Rate adjustment amount.

[0007] A preferred embodiment of the present invention is as follows: the method for obtaining the ozone depletion range is: Within a historical treatment cycle, the required pollutant content in the RO concentrate is obtained. Combined with the oxidation reaction equation with ozone, the ozone demand is calculated. The ozone demand corresponding to each historical treatment cycle and the corresponding actual ozone supply are extracted and subtracted to output the actual ozone consumption. The actual ozone consumption corresponding to each historical treatment cycle is compared, and the maximum and minimum actual ozone consumption are analyzed and selected as the ozone consumption range.

[0008] A preferred embodiment of the present invention is: excess Fe-C micro-electrolysis coupling stage The content is obtained by: Obtain the ozone demand corresponding to the historical processing cycle and the corresponding actual ozone supply, calculate the difference, and then calculate the ratio with the ozone consumption range length to output the ozone consumption. The concentrated RO aqueous solution was divided into three layers: top, middle, and bottom. In the content monitoring area, the top layer of the concentrated RO aqueous solution was obtained separately. Content monitoring area, middle layer Content monitoring area and bottom layer Content monitoring area Content, to obtain the top layer Content, middle layer Content and bottom layer The content is calculated and averaged to output the solution. Average content; If solution The average content is greater than that of the solution. The content threshold will then be used to determine the solution. Average content and solution After subtracting the content threshold, and then comparing it with the solution... The content threshold is used to calculate the ratio, and the output is the excess. content.

[0009] As a preferred embodiment of the present invention, the correlation analysis process is as follows: Extracting data from each historical processing cycle Excessive ozone emission levels and corresponding excess levels Content, construct content correlation analysis curves, and extract the X-axis and Y-axis coordinates of all coordinate points respectively. Sort them from front to back according to their positions on the content correlation analysis curves, and construct X-axis coordinate sequences and Y-axis coordinate sequences respectively. By combining the X-axis coordinates and Y-axis coordinates of adjacent positions within the X-axis coordinate sequence and the Y-axis coordinate sequence respectively, multiple X-coordinate combinations and multiple Y-coordinate combinations can be obtained. Using the position of the coordinates on the content correlation analysis curve as the secondary combination rule, the X coordinate combination and Y coordinate combination with the same position are combined in a secondary combination to obtain multiple XY coordinate analysis groups. The adjacent change values ​​of the X-axis and the adjacent change values ​​of the Y-axis in the XY coordinate analysis group are obtained respectively, the ratio is calculated, and the unit change coefficient is output. Extract the element variation coefficients corresponding to each XY coordinate analysis group, calculate the standard deviation, and output the element coefficient standard deviation. The mean values ​​of the X-coordinates and Y-coordinates within the X-axis coordinate sequence are calculated and averaged respectively, and the mean values ​​of the X-coordinates and Y-coordinates are output. The mean values ​​of the X-coordinates and Y-coordinates are then calculated and averaged again, and the XY-coordinate coefficients are output. Input the XY coordinate coefficients and the standard deviation of the unit coefficients into the coefficient of variation formula to obtain the content correlation assessment value; If the content correlation assessment value is less than or equal to the content correlation assessment threshold, then the content correlation is strong.

[0010] A preferred embodiment of the present invention is as follows: the consumption correlation coefficient is obtained in the following way: If a signal with a close correlation to the content is generated, the average value of the unit change coefficients corresponding to all XY coordinate analysis groups is calculated, and the consumption correlation coefficient is output.

[0011] The preferred embodiment of the present invention is as follows: The overload warning model is constructed as follows: If the linear analysis value is less than or equal to the linear analysis threshold, then the two endpoint values ​​within the ozone depletion range, along with the depletion correlation coefficient, are extracted as the model slope to construct the model. The over-exploitation warning model, wherein the warning model formula is: ,in, Represented as the model slope, It is represented as a constant.

[0012] As a preferred embodiment of the present invention, the linear analysis value is obtained as follows: Extract the endpoint coordinates on the content correlation analysis curve and connect them to fit a fitting analysis line. Extract all coordinate points on the correlation analysis curve and use each coordinate point on the correlation analysis curve as a reference point to draw a unit vertical line perpendicular to the fitting analysis line. Obtain the proportion of the unit vertical line length to the fitting analysis line length to get the unit residual value. The mean value of the unit residuals is calculated by averaging all the unit residuals and output as the mean value of the unit residuals. Calculate the standard deviation of all unit residuals and output the standard deviation of the unit residuals. Input the mean and standard deviation of the unit residuals into the coefficient of variation formula to obtain the linear analysis value.

[0013] A preferred embodiment of the present invention is as follows: the method for obtaining the location interval of the fastest time period is: The historical processing cycle is divided into several historical processing periods, and the data within each historical processing period is obtained. The content of the time period is calculated and the ratio of the ratio to the duration of the historical processing period is used to output the generation rate of the time period. Within the historical processing cycle, the generation rate of each historical processing period is compared to select the fastest generation rate, and the historical processing period corresponding to the fastest generation rate is extracted and marked as the fastest rate historical period. Extract the fastest generation rate within each historical processing cycle and obtain the temporal position of the historical processing cycle in which the fastest rate historical period is located, and use it as the sorting of the fastest rate period in the cycle; Extract the period with the fastest rate within each historical processing cycle, and obtain the position range of the fastest period based on the position before and after the historical processing period within the historical processing cycle.

[0014] The preferred embodiment of the present invention is as follows: The process of obtaining the rate adjustment amount is as follows: The average generation rate of all key monitoring periods within the fastest time period location interval is calculated and output as the key generation rate. extract The formula for the over-exposure warning model is as follows: It extracts the maximum and minimum actual ozone consumption within the ozone consumption range, calculates the ratio of each to the consumption correlation coefficient, and outputs the maximum ozone consumption. Excess and Minimum Excess, and build Excess range; Obtain the current key monitoring starting point time period For the content, arbitrarily select a key monitoring period within the current fastest time interval as the current target time period; If the current target time period is within The content was not at If the amount is excessive, then... Minimum within the excess range Excessive levels are warning values, and are within the current key monitoring period. The difference between the content is calculated to obtain the early warning adjustment difference, and the ratio with the key generation rate is calculated to output the adjustment duration. If the adjustment time is less than the time required to proceed to the ozone oxidation stage, the difference between the adjustment time and the ozone oxidation stage time will be used to obtain the remaining adjustment time. The ratio of the early warning adjustment difference to the remaining adjustment time is calculated and output as follows: Rate adjustment amount.

[0015] Secondly, an ozone oxidation micro-electrolysis system for RO concentrate treatment includes the following modules: Ozone Consumption Range Analysis Module: Processes the ozone demand during RO concentrate ozone oxidation in multiple historical treatment cycles and outputs the ozone consumption range. Consumption correlation analysis module: Based on the ozone consumption during the ozone oxidation stage of RO concentrate in multiple historical treatment cycles, and the excess ozone during the Fe-C micro-electrolysis coupling stage. The content was determined, a correlation analysis curve was constructed, and the correlation degree was analyzed to obtain the consumption correlation coefficient. Excessive ozone emission warning module: Performs linear analysis on the constructed correlation curve. If a positive linear correlation is found, the consumption correlation coefficient and ozone consumption range are combined to construct... Excessive warning model Rate warning and adjustment module: During the Fe-C micro-electrolysis coupling stage, it acquires the generation rate of each historical processing period after the historical processing cycle is divided, analyzes it, determines the fastest generation rate, obtains the corresponding fastest historical period, and performs period stability analysis over multiple historical cycles to determine the location interval of the fastest period. Within the location interval of the fastest period, it adjusts the rate based on... The over-prevention model yielded the following results: Rate adjustment amount.

[0016] The beneficial effects of this invention are as follows: 1. This invention obtains the ozone demand during RO concentrate ozone oxidation in each historical treatment cycle, processes it, and outputs the ozone consumption range. This helps to avoid substandard pollutant degradation due to abnormal ozone consumption, ensuring the stability of the pretreatment process. By obtaining the ozone consumption in multiple historical treatment cycles, and the excess ozone during the Fe-C micro-electrolysis coupling stage... By analyzing the content and correlation, the consumption correlation coefficient is obtained. This not only reflects the relationship between ozone consumption and excess content under different operating conditions, but also helps to improve the quality of RO concentrate pretreatment, thereby avoiding excessive ozone supply and ineffective consumption, reducing ozone usage, and enhancing the adaptability of the pretreatment process to different operating conditions. 2. This invention combines the consumption correlation coefficient and the ozone consumption range to construct... The overload warning model, through its construction The over-ozone warning model helps to provide early warnings about the ozone content during the subsequent ozone oxidation stage, allowing for timely adjustments to the RO concentrate pretreatment under different operating conditions. This improves fault tolerance and also predicts the required ozone content for the subsequent ozone oxidation stage. Furthermore, it can further obtain data on the Fe-C micro-electrolysis coupling stage in each historical treatment cycle. The generation rate is used to obtain the location interval of the fastest time period, and based on the... The over-prevention model yielded the following results: The rate adjustment not only helps to adjust the generation rate in a timely manner according to the content in the current target period, so that the reaction reaches the optimal state at the right time, reducing the ineffective consumption of ozone due to excessive generation of substances, and allowing more ozone to be used for pollutant degradation, avoiding abnormal ozone consumption, but also further ensures that ozone can fully react with pollutants, thereby improving the degradation rate of pollutants in RO concentrate and improving the quality of effluent. Attached Figure Description

[0017] The invention will now be further described with reference to the accompanying drawings.

[0018] Figure 1 This is a flowchart of the steps of an ozone oxidation micro-electrolysis method for RO concentrate treatment according to the present invention; Figure 2 This is a flowchart of the judgment process in the ozone oxidation micro-electrolysis method for RO concentrate treatment according to the present invention; Figure 3 This is a schematic diagram of an ozone oxidation micro-electrolysis method and system for RO concentrate treatment according to the present invention. Detailed Implementation

[0019] To make the technical means, creative features, objectives and effects of this invention easier to understand, the invention will be further described below in conjunction with specific embodiments.

[0020] Example 1 An ozone oxidation micro-electrolysis method for RO concentrate treatment includes the following specific steps: S1, In the Fe-C micro-electrolysis coupling stage, the mass ratio of iron to carbon is 1:1 for Fe-C micro-electrolysis coupling pretreatment; S2, hydraulic retention time 15-60 min, influent COD 87 mg / L, effluent COD 62 mg / L, COD removal rate 28.7%, ozone dosage 65 mg / L; S3, when the dissolution time is less than 1 minute, and after the ozone is mixed with water and saturated, it is preferable to transfer the ozone in 10-30 seconds; S4 introduces ozone-saturated RO concentrate into a reactor containing fluidized bed activated carbon particles, allowing the RO concentrate to contact the activated carbon particles. Fluidized bed activated carbon particles with a particle size of 300μm-1500μm and a density greater than 0.45 are used to improve the contact efficiency between activated carbon and pollutants, while reducing the loss of activated carbon particles.

[0021] Example 2 Please see Figures 1-2 As shown in the embodiment of the present invention, an ozone oxidation micro-electrolysis method for RO concentrate treatment includes the following steps: Step 1: Within multiple historical treatment cycles, obtain the ozone demand during RO concentrate ozone oxidation in each historical treatment cycle, process it, and output the ozone consumption range. It should be noted that the time required for each pretreatment of RO concentrate in history corresponds to one historical treatment cycle. In some embodiments, the process of obtaining ozone demand is as follows: During the historical treatment cycle, the required concentration of pollutants to be degraded in the RO concentrate is obtained, and combined with the oxidation reaction equation with ozone, the ozone requirement is obtained. It should be noted that the required pollutant content in the RO concentrate is set by those skilled in the art when degrading the RO concentrate; The process for obtaining the ozone depletion range is as follows: Extract the ozone demand and the actual ozone supply for each historical processing cycle. Calculate the difference between the actual ozone supply and the ozone demand to output the actual ozone consumption. The actual ozone consumption corresponding to each historical treatment cycle is compared, and the maximum and minimum actual ozone consumption are analyzed and selected as the ozone consumption range. It should be noted that the ozone consumption range refers to the range of ozone consumption actually utilized under different operating conditions, constructed based on the maximum and minimum values ​​of actual ozone consumption during historical treatment cycles. This range includes both the effective consumption required for pollutant degradation and the consumption caused by other factors. Ineffective consumption caused by excessive or other interfering factors; specifically, the purpose of obtaining the ozone depletion range is: Objective 1: From the perspective of process stability, the Fe-C micro-electrolysis stage generates... If in excess, it will compete with pollutants for ozone ( Oxidized by ozone This leads to increased ineffective ozone depletion; fluctuations in pollutant concentrations also cause changes in effective ozone depletion. Therefore, the ozone depletion range is defined by historical data as a "normal depletion interval"—when the actual ozone depletion in the current treatment cycle exceeds this range, it can be quickly determined that there may be a problem. Abnormalities such as excessive ozone supply (leading to high consumption) or insufficient ozone supply (leading to low consumption) require timely intervention and regulation (such as adjustment). (Generation rate or ozone supply) to avoid substandard pollutant degradation due to abnormal ozone depletion and to ensure the stability of the pretreatment process; Objective 2: The core of Fe-C micro-electrolysis is to generate through the Fe and C electrode reaction. (As a catalyst or reducing agent for subsequent ozone oxidation), but Excessive ozone consumption can become a competitor to ozone; therefore, the range of ozone depletion reflects the historical effective utilization (degradation of pollutants) and ineffective depletion (waste) of ozone. The overall fluctuation of consumption; Step 2: Obtain ozone consumption over multiple historical treatment cycles, as well as excess ozone during the Fe-C micro-electrolysis coupling stage. The content was analyzed to obtain the consumption correlation coefficient; In some embodiments, the ozone consumption during the ozone oxidation stage and the excess ozone during the Fe-C micro-electrocoupling stage are extracted separately within a historical processing cycle. content; Specifically, the process for obtaining ozone consumption during the ozone oxidation stage is as follows: Obtain the ozone demand corresponding to the historical processing cycle and the corresponding actual ozone supply. Calculate the difference between the actual ozone supply and the ozone demand, and then calculate the ratio with the length of the ozone consumption range to output the ozone consumption. The ozone depletion range length is obtained by subtracting the maximum ozone depletion and the minimum ozone depletion within the ozone depletion range. Specifically, excess Fe-C micro-electrolysis coupling stage The process for obtaining the content is as follows: The concentrated RO aqueous solution was divided into three layers: top, middle, and bottom. Content monitoring area, including the top, middle and bottom layers. The volume of concentrated RO solution within the content monitoring area is the same in all local areas. Obtain the top layer of concentrated RO aqueous solution Content monitoring area Content, as the top layer content; Obtain the middle layer of concentrated RO aqueous solution Content monitoring area Content, as a middle layer content; Obtain the bottom layer of concentrated RO aqueous solution Content monitoring area Content, as the bottom layer content; Top layer Content, middle layer Content and bottom layer The content is summed and the mean is calculated to output the solution. Average content; If solution Average content and solution The content thresholds were compared, and the process is as follows: If solution The average content of the solution is less than or equal to The content threshold indicates the concentration of the solution during the Fe-C micro-electrolysis coupling stage. The content was within the ideal range, and no excess was produced. ; If solution The average content is greater than that of the solution. The content threshold indicates the concentration of the solution during the Fe-C micro-electrolysis coupling stage. When the content is in excess, it will be displayed as... Excess signal, solution Average content and solution After subtracting the content threshold, and then comparing it with the solution... The content threshold is used to calculate the ratio, and the output is the excess. content; Extracting data from each historical processing cycle Excessive ozone emission levels and corresponding excess levels Content, construct content correlation analysis curves, where the X-axis represents excess. Content, with ozone consumption on the Y-axis; It should be noted that within each historical processing cycle Excessive ozone emission levels and corresponding excess levels The content was imported into the two-dimensional coordinate system in order of increasing ozone consumption; Extract the X-axis and Y-axis coordinates of all coordinate points on the content correlation analysis curve, and sort the X-axis coordinates of all coordinate points from front to back according to their positions on the content correlation analysis curve to construct an X-axis coordinate sequence; Similarly, the Y-axis coordinates of all coordinate points are sorted from front to back on the content correlation analysis curve to construct a Y-axis coordinate sequence; By combining the X-axis coordinates of adjacent positions within the X-axis coordinate sequence, multiple X-axis coordinate combinations can be obtained. By combining the Y-axis coordinates of adjacent positions within the Y-axis coordinate sequence, multiple Y-axis coordinate combinations can be obtained. To help understand this, for example, the X-axis coordinate sequence includes... , , , and The Y-coordinate sequence includes , , , and ; Within the X-axis coordinate sequence, adjacent positions are... and By combining them, we obtain a set of X-coordinate combinations; Within the X-axis coordinate sequence, adjacent positions are... and By combining them, we obtain a set of X-coordinate combinations; Within the X-axis coordinate sequence, adjacent positions are... and By combining them, we obtain a set of X-coordinate combinations; Within the X-axis coordinate sequence, adjacent positions are... and By combining them, we obtain a set of X-coordinate combinations; Similarly, within the Y-axis coordinate sequence, adjacent positions are... and By combining them, we obtain a set of Y-coordinate combinations; Within the Y-axis coordinate sequence, adjacent positions are... and By combining them, we obtain a set of Y-coordinate combinations; Within the Y-axis coordinate sequence, adjacent positions are... and By combining them, we obtain a set of Y-coordinate combinations; Within the Y-axis coordinate sequence, adjacent positions are... and By combining them, we obtain a set of Y-coordinate combinations; Using the position of the coordinates on the content correlation analysis curve as the secondary combination rule, the X coordinate combination and Y coordinate combination with the same position are combined in a secondary combination to obtain multiple XY coordinate analysis groups. To aid understanding, extracting from adjacent positions and The combination of X coordinates, and the combination of adjacent positions and The Y-coordinates of the combination are combined and then combined again to obtain a set of XY coordinate analysis groups; Extract from adjacent positions respectively and The combination of X coordinates, and the combination of adjacent positions and The Y-coordinates of the combination are combined and then combined again to obtain a set of XY coordinate analysis groups; Extract from adjacent positions respectively and The combination of X coordinates, and the combination of adjacent positions and The Y-coordinates of the combination are combined and then combined again to obtain a set of XY coordinate analysis groups; Extract from adjacent positions respectively and The combination of X coordinates, and the combination of adjacent positions and The Y-coordinates are combined and then combined again to obtain a set of XY coordinate analysis groups; Within the XY coordinate analysis group, the difference between adjacent X coordinates within the X coordinate combination is used to obtain the adjacent change value of the X axis, and the difference between adjacent Y coordinates within the Y coordinate combination is used to obtain the adjacent change value of the Y axis. The ratio of adjacent changes on the Y-axis to adjacent changes on the X-axis is calculated, and the unit change coefficient is output. Extract the element variation coefficients corresponding to each XY coordinate analysis group, calculate the standard deviation, and output the element coefficient standard deviation. The mean value of the X-coordinates within the X-axis coordinate sequence is calculated and output as the mean value of the X-coordinates. Similarly, the mean value of the Y coordinates within the Y-axis coordinate sequence is calculated and output as the mean value of the Y coordinates. The mean values ​​of the X and Y coordinates are averaged to calculate the X and Y coordinate coefficients. Input the XY coordinate coefficients and the standard deviation of the unit coefficients into the coefficient of variation formula to obtain the content correlation assessment value. ; Specifically, the formula for the coefficient of variation is: ,in, Expressed as the standard deviation of the unit coefficients, Represented as XY coordinate coefficients; It is understandable that the meaning of the content correlation assessment value is: by combining the XY coordinate coefficients with the standard deviation of the unit coefficients using the coefficient of variation formula, a comprehensive index is obtained that reflects the degree of correlation and change characteristics between ozone consumption and excess content. Specifically, the purpose of obtaining the content correlation assessment value is: Objective 1: By analyzing the evaluation values, we can reflect the correlation between ozone consumption and excess content under different operating conditions, providing a reference for adjusting process parameters, such as the reaction conditions of Fe-C micro-electrolysis and the ozone supply, so that the process can operate under optimal conditions and improve treatment efficiency. Objective 2: By ensuring a reasonable correlation between ozone consumption and the content of substances generated in the Fe-C micro-electrolysis stage, it is possible to ensure that pollutants are fully degraded in the ozone oxidation stage, while avoiding poor treatment results due to insufficient or excessive ozone supply, thus helping to improve the quality of RO concentrate pretreatment. Objective 3: By accurately analyzing the correlation between ozone consumption and excess content, excessive ozone supply and ineffective consumption are avoided, ozone usage is reduced, and the adaptability of the pretreatment process to different operating conditions is enhanced. The content association assessment value is compared with the content association assessment threshold, as follows: If the content correlation assessment value is greater than the content correlation assessment threshold, it indicates that there is an excess of Fe-C in the micro-electrolysis coupling stage. There is a close correlation between the content and the ozone consumption during ozone oxidation, indicating a non-close correlation signal. If the content correlation assessment value is less than or equal to the content correlation assessment threshold, it indicates that there is an excess of Fe-C in the micro-electrolysis coupling stage. There is a non-close correlation between the content and the ozone consumption in ozone oxidation, but the content shows a close correlation signal. The average value of the unit change coefficients corresponding to all XY coordinate analysis groups is calculated to output the consumption correlation coefficient. The specific solution in this embodiment is as follows: Within multiple historical treatment cycles, the ozone demand during RO concentrate ozone oxidation in each historical treatment cycle is obtained and processed to output the ozone consumption range. This helps to avoid substandard pollutant degradation due to abnormal ozone consumption, ensuring the stability of the pretreatment process. By obtaining the ozone consumption within multiple historical treatment cycles, and the excess ozone during the Fe-C micro-electrolysis coupling stage... By analyzing the content and correlation, the consumption correlation coefficient is obtained. This not only reflects the relationship between ozone consumption and excess content under different operating conditions, but also helps to improve the quality of RO concentrate pretreatment, thereby avoiding excessive ozone supply and ineffective consumption, reducing ozone usage, and enhancing the adaptability of the pretreatment process to different operating conditions.

[0022] Example 3 Please see Figures 1-2 As shown in the embodiment of the present invention, an ozone oxidation micro-electrolysis method for RO concentrate treatment further includes the following steps: Step 3: Combine the consumption correlation coefficient and the ozone depletion range to construct... Excessive warning model; In some embodiments, the endpoint coordinates on the content correlation analysis curve are extracted and connected to fit a fitting analysis line; It should be noted that the endpoint coordinates on the content correlation analysis curve are the starting coordinates and ending coordinates on the content correlation analysis curve, respectively. Among them, the two endpoint values ​​within the ozone depletion range correspond to the Y coordinates within the starting coordinates and the Y coordinates within the ending coordinates on the content correlation analysis curve, respectively. Extract all coordinate points on the correlation analysis curve, and take each coordinate point on the correlation analysis curve as a reference point to draw a unit vertical line perpendicular to the fitting analysis line. Obtain the proportion of the unit vertical line length to the fitting analysis line length to get the unit residual value. The mean value of the unit residuals is calculated by averaging all the unit residuals and output as the mean value of the unit residuals. Calculate the standard deviation of all unit residuals and output the standard deviation of the unit residuals. Input the mean and standard deviation of the unit residuals into the coefficient of variation formula to obtain the linear analysis value. ; Specifically: Coefficient of variation formula: ,in, Expressed as the standard deviation of the unit residuals, Represented as the mean of the unit residuals; It should be noted that the significance of using the coefficient of variation formula is as follows: The calculated linear analysis value represents the vertical distance between each coordinate point on the correlation analysis curve and the fitted analysis line, thus reflecting the overall matching degree between the content correlation curve and the fitted analysis line, and indicating excess content in the Fe-C micro-electrolysis coupling stage. Based on the close correlation between the content and ozone consumption during ozone oxidation, further exploration was conducted to uncover the excess content within the Fe-C micro-electrolysis coupling stage. Is there a linear positive correlation between ozone content and ozone consumption during ozone oxidation, thus providing a basis for constructing... The over-exposure warning model provides data support; The linear analysis value is compared with the linear analysis threshold, as follows: If the linear analysis value is greater than the linear analysis threshold, it indicates that the overall matching degree between the content correlation curve and the fitted analysis line is low, and it is a non-linear positive correlation. If the linear analysis value is less than or equal to the linear analysis threshold, it indicates a high overall match between the content correlation curve and the fitted analysis line, suggesting a positive linear correlation. The two endpoints within the ozone depletion range, along with the depletion correlation coefficient, are extracted as the model slope to construct the model. The over-exploitation warning model, wherein the warning model formula is: ,in, Represented as the model slope, Represented as a constant; The purpose of constructing the over-exposure warning model is: Objective 1: To construct an early warning model to extract the effects of generated [elements] during the Fe-C micro-electrolysis coupling stage. Monitoring helps to provide early warning of ozone levels during the subsequent ozone oxidation stage, and allows for timely adjustments to the RO concentrate pretreatment under different operating conditions. This improves the tolerance for errors and also enables the prediction of the required ozone levels during the subsequent ozone oxidation stage. Objective 2: If the substances generated during the Fe-C micro-electrolysis stage are excessive, they will not only compete with pollutants for ozone, but may also cause secondary pollution. Therefore, by monitoring the relationship between the excess content and ozone consumption, it is possible to promptly identify substances that may affect the degradation effect of pollutants. Step 4: Obtain the Fe-C micro-electrocoupling stage data for each historical processing cycle. The generation rate is used to obtain the location interval of the fastest time period, and based on the... The over-prevention model yielded the following results: Rate adjustment amount to complete the Fe-C micro-electrolysis coupling stage The generation rate was adjusted. In some embodiments, the process of obtaining the fastest time period location interval is as follows: The historical processing cycle is divided into several historical processing periods, and the data within each historical processing period is obtained. The content of the time period is calculated and the ratio of the ratio to the duration of the historical processing period is used to output the generation rate of the time period. Among them, the duration of the historical processing periods divided into historical processing cycles is equal, and the method of dividing the historical processing periods within each historical processing cycle is consistent, and the number of historical processing periods after the division of each historical processing cycle is the same. Within the historical processing cycle, the generation rate of each historical processing period is compared to select the fastest generation rate, and the historical processing period corresponding to the fastest generation rate is extracted and marked as the fastest rate historical period. Similarly, the fastest generation rate within each historical processing cycle and the corresponding historical period of the fastest rate are obtained. For example, the fastest generation rate in each historical processing cycle and the corresponding historical period of the fastest rate are extracted, and the temporal position of the historical period of the fastest rate in the historical processing cycle is obtained as the sorting of the period of the fastest rate. Extract the period with the fastest rate within each historical processing cycle, and obtain the position range of the fastest period based on the position before and after the historical processing period within the historical processing cycle. It should be noted that the purpose of obtaining the fastest time period location range is: Objective 1: From a time perspective, by determining the location range of the fastest time period, we can identify the specific time period that needs to be focused on in the entire historical processing cycle. This helps to determine the scope of key monitoring periods, enable timely detection of such rhythm changes, provide a basis for subsequent adjustment of processing parameters, and ensure that the response reaches the optimal state at the appropriate time. Objective 2: The fastest time period includes multiple historical periods with the fastest generation rate, and the fastest generation rate can serve as an important benchmark for rate adjustment. The rate adjustment value obtained based on the over-prevention model is an adjustment made for the generation rate within this critical period. By adjusting this benchmark rate, the reaction speed of the entire Fe-C micro-electrolysis coupling stage can be controlled, avoiding poor processing effect or waste of resources due to the generation rate being too fast or too slow. Objective 3: By accurately obtaining the location range of the fastest time period and adjusting the generation rate of the time period within the fastest time period location range, it is possible to ensure that pollutants can be effectively removed in the critical reaction stage, and further provide data support for determining the time period for rate adjustment; The process of obtaining the rate adjustment amount is as follows: The average generation rate of all key monitoring periods within the fastest time period location interval is calculated and output as the key generation rate. extract The formula for the over-exposure warning model is as follows: It extracts the maximum and minimum actual ozone consumption within the ozone consumption range, calculates the ratio of each to the consumption correlation coefficient, and outputs the maximum ozone consumption. Excess and Minimum Excess, and build Excess range; Obtain the current key monitoring starting point within the time period content; For example, arbitrarily select a key monitoring period within the current fastest time period range as the current target time period; If the current target time period is within The content was not at If the amount is excessive, then... Minimum within the excess range Excessive levels are warning values, and are within the current key monitoring period. The difference between the content is calculated to obtain the early warning adjustment difference, and the ratio with the key generation rate is calculated to output the adjustment duration. If the adjustment period is greater than or equal to the time to enter the ozone oxidation stage, then no rate adjustment operation is required; If the adjustment time is less than the time required to proceed to the ozone oxidation stage, the difference between the adjustment time and the ozone oxidation stage time will be used to obtain the remaining adjustment time. The time required to reach the ozone oxidation stage is calculated by averaging the time required for multiple Fe-C micro-electrolysis coupling stages to obtain the total micro-electrolysis time, and then the difference between the total micro-electrolysis time and the current micro-electrolysis time is output. The ratio of the early warning adjustment difference to the remaining adjustment time is calculated and output as follows: Rate adjustment amount; It should be noted that, The purpose of obtaining the rate adjustment is: Objective 1: To help adjust the generation rate in a timely manner based on the concentration in the current target period, so that the reaction reaches the optimal state at the appropriate time, reduce the ineffective consumption of ozone due to excessive generation of substances, and enable more ozone to be used for pollutant degradation, thereby avoiding abnormal ozone consumption. Objective 2: By accurately adjusting the generation rate of Fe-C micro-electrolysis coupling, excessive generation of substances is prevented from competing with pollutants for ozone, ensuring that ozone can fully react with pollutants, thereby improving the degradation rate of pollutants in RO concentrate and improving the quality of effluent. Objective 3: It can also provide a suitable reaction environment for subsequent ozone catalytic oxidation (such as...) As a catalyst, ozone oxidation can further degrade intermediate products generated by iron-carbon micro-electrolysis, thereby improving the overall treatment efficiency. The specific solution in this embodiment is as follows: The consumption correlation coefficient and the ozone consumption range are combined to construct... The overload warning model, through its construction The over-ozone warning model helps to provide early warnings about the ozone content during the subsequent ozone oxidation stage, allowing for timely adjustments to the RO concentrate pretreatment under different operating conditions. This improves fault tolerance and also predicts the required ozone content for the subsequent ozone oxidation stage. Furthermore, it can further obtain data on the Fe-C micro-electrolysis coupling stage in each historical treatment cycle. The generation rate is used to obtain the location interval of the fastest time period, and based on the... The over-prevention model yielded the following results: The rate adjustment not only helps to adjust the generation rate in a timely manner according to the content in the current target period, so that the reaction reaches the optimal state at the right time, reducing the ineffective consumption of ozone due to excessive generation of substances, and allowing more ozone to be used for pollutant degradation, avoiding abnormal ozone consumption, but also further ensures that ozone can fully react with pollutants, thereby improving the degradation rate of pollutants in RO concentrate and improving the quality of effluent.

[0023] Example 4 Please see Figure 3 As shown in the embodiment of the present invention, an ozone oxidation micro-electrolysis system for RO concentrate treatment includes the following modules: Ozone Consumption Range Analysis Module: Processes the ozone demand during RO concentrate ozone oxidation in multiple historical treatment cycles and outputs the ozone consumption range. Consumption correlation analysis module: Based on the ozone consumption during the ozone oxidation stage of RO concentrate in multiple historical treatment cycles, and the excess ozone during the Fe-C micro-electrolysis coupling stage. The content was determined, a correlation analysis curve was constructed, and the correlation degree was analyzed to obtain the consumption correlation coefficient. Excessive ozone emission warning module: Performs linear analysis on the constructed correlation curve. If a positive linear correlation is found, the consumption correlation coefficient and ozone consumption range are combined to construct... Excessive warning model Rate warning and adjustment module: During the Fe-C micro-electrolysis coupling stage, it acquires the generation rate of each historical processing period after the historical processing cycle is divided, analyzes it, determines the fastest generation rate, obtains the corresponding fastest historical period, and performs period stability analysis over multiple historical cycles to determine the location interval of the fastest period. Within the location interval of the fastest period, it adjusts the rate based on... The over-prevention model yielded the following results: Rate adjustment amount.

[0024] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely illustrative of the principles of the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the present invention as claimed. The scope of protection of the present invention is defined by the appended claims and their equivalents.

Claims

1. A micro-electrolysis method for ozone oxidation in RO concentrate treatment, characterized in that: include: The ozone demand during RO concentrate ozone oxidation in multiple historical treatment cycles is processed to output the ozone consumption range. Based on the ozone consumption during the ozone oxidation stage of RO concentrate in multiple historical treatment cycles, and the excess ozone during the Fe-C micro-electrolysis coupling stage... Content, construct correlation analysis curves, and perform correlation degree analysis to obtain the consumption correlation coefficient: Linear analysis is performed on the constructed correlation curves. If a positive linear correlation is found, the consumption correlation coefficient and the ozone depletion range are combined to construct... Excessive warning model; In the Fe-C micro-electrolysis coupling stage, the generation rate of each historical processing period within the historical processing cycle is obtained and analyzed to determine the fastest generation rate, thus obtaining the corresponding fastest historical period. Stability analysis of these periods is then performed across multiple historical cycles to determine the location interval of the fastest period. Within this fastest period location interval, based on… The over-prevention model yielded the following results: Rate adjustment amount.

2. The ozone oxidation micro-electrolysis method for RO concentrate treatment according to claim 1, characterized in that: The method for obtaining the ozone depletion range is as follows: Within a historical treatment cycle, the required pollutant content in the RO concentrate is obtained. Combined with the oxidation reaction equation with ozone, the ozone demand is calculated. The ozone demand corresponding to each historical treatment cycle and the corresponding actual ozone supply are extracted and subtracted to output the actual ozone consumption. The actual ozone consumption corresponding to each historical treatment cycle is compared, and the maximum and minimum actual ozone consumption are analyzed and selected as the ozone consumption range.

3. The ozone oxidation micro-electrolysis method for RO concentrate treatment according to claim 1, characterized in that: Excess Fe-C microelectrolysis coupling stage The content is obtained by: Obtain the ozone demand corresponding to the historical processing cycle and the corresponding actual ozone supply, calculate the difference, and then calculate the ratio with the ozone consumption range length to output the ozone consumption. The concentrated RO aqueous solution was divided into three layers: top, middle, and bottom. In the content monitoring area, the top layer of the concentrated RO aqueous solution was obtained separately. Content monitoring area, middle layer Content monitoring area and bottom layer Content monitoring area Content, to obtain the top layer Content, middle layer Content and bottom layer The content is calculated and averaged to output the solution. Average content; If solution The average content is greater than that of the solution. The content threshold will then be used to determine the solution. Average content and solution After subtracting the content threshold, and then comparing it with the solution... The content threshold is used to calculate the ratio, and the output is the excess. content.

4. The ozone oxidation micro-electrolysis method for RO concentrate treatment according to claim 1, characterized in that: The process of correlation analysis is as follows: Construct content correlation analysis curves, and extract the X-axis and Y-axis coordinates of all coordinate points respectively, and construct X-axis coordinate sequences and Y-axis coordinate sequences respectively; The X-coordinate combinations and Y-coordinate combinations with the same position are combined twice to obtain multiple XY coordinate analysis groups. The adjacent change values ​​of the X-axis and the adjacent change values ​​of the Y-axis are obtained respectively, the ratio is calculated, the unit change coefficient is output, and the standard deviation is calculated to output the unit coefficient standard deviation. The mean values ​​of the X-coordinates and Y-coordinates within the X-axis coordinate sequence are calculated and averaged respectively, and the mean values ​​of the X-coordinates and Y-coordinates are output. The mean values ​​of the X-coordinates and Y-coordinates are then calculated and averaged again, and the XY-coordinate coefficients are output. Input the XY coordinate coefficients and the standard deviation of the unit coefficients into the coefficient of variation formula to obtain the content correlation assessment value. If it is less than or equal to the content correlation assessment threshold, then the content correlation is strong.

5. The ozone oxidation micro-electrolysis method for RO concentrate treatment according to claim 4, characterized in that: The consumption correlation coefficient is obtained as follows: If a signal with a close correlation to the content is generated, the average value of the unit change coefficients corresponding to all XY coordinate analysis groups is calculated, and the consumption correlation coefficient is output.

6. The ozone oxidation micro-electrolysis method for RO concentrate treatment according to claim 1, characterized in that: The overload warning model is constructed as follows: If the linear analysis value is less than or equal to the linear analysis threshold, then the two endpoint values ​​within the ozone depletion range, along with the depletion correlation coefficient, are extracted as the model slope to construct the model. The over-exploitation warning model, wherein the warning model formula is: ,in, Represented as the model slope, It is represented as a constant.

7. The ozone oxidation micro-electrolysis method for RO concentrate treatment according to claim 1, characterized in that: The linear analysis values ​​are obtained as follows: Extract the endpoint coordinates on the content correlation analysis curve and connect them to fit a fitting analysis line. Extract all coordinate points on the correlation analysis curve and use each coordinate point on the correlation analysis curve as a reference point to draw a unit vertical line perpendicular to the fitting analysis line. Obtain the proportion of the unit vertical line length to the fitting analysis line length to get the unit residual value. The mean value of the unit residuals is calculated by averaging all the unit residuals and output as the mean value of the unit residuals. Calculate the standard deviation of all unit residuals and output the standard deviation of the unit residuals. Input the mean and standard deviation of the unit residuals into the coefficient of variation formula to obtain the linear analysis value.

8. The ozone oxidation micro-electrolysis method for RO concentrate treatment according to claim 1, characterized in that: The fastest time period location range is obtained as follows: The historical processing cycle is divided into several historical processing periods, and the data within each historical processing period is obtained. The content of the time period is calculated and the ratio of the ratio to the duration of the historical processing period is used to output the generation rate of the time period. Within the historical processing cycle, the generation rate of each historical processing period is compared to select the fastest generation rate, and the historical processing period corresponding to the fastest generation rate is extracted and marked as the fastest rate historical period. Extract the fastest generation rate within each historical processing cycle and obtain the temporal position of the historical processing cycle in which the fastest rate historical period is located, and use it as the sorting of the fastest rate period in the cycle; Extract the period with the fastest rate within each historical processing cycle, and obtain the position range of the fastest period based on the position of the historical processing period within the historical processing cycle.

9. The ozone oxidation micro-electrolysis method for RO concentrate treatment according to claim 1, characterized in that: The process of obtaining the rate adjustment amount is as follows: The average generation rate of the time period within the fastest time period location interval is calculated to output the key generation rate. Based on the early warning model formula: Extract the maximum and minimum actual ozone consumption within the ozone depletion range, calculate the ratio of each to the consumption correlation coefficient, and output the maximum ozone consumption. Excess and Minimum Excess, and build Excess range; Arbitrarily select a key monitoring period within the current fastest time interval as the current target time interval; If the current target time period is within The content was not at If the amount is excessive, then... Minimum within the excess range Excessive levels are warning values, and are within the current key monitoring starting time period. The difference between the content is calculated to obtain the early warning adjustment difference, and the ratio with the key generation rate is calculated to output the adjustment duration. If the adjustment time is less than the time required to proceed to the ozone oxidation stage, the difference between the adjustment time and the ozone oxidation stage time will be used to obtain the remaining adjustment time. The ratio of the early warning adjustment difference to the remaining adjustment time is calculated and output as follows: Rate adjustment amount.

10. An ozone oxidation micro-electrolysis system for RO concentrate treatment, characterized in that: include: Ozone Consumption Range Analysis Module: Processes the ozone demand during RO concentrate ozone oxidation in multiple historical treatment cycles and outputs the ozone consumption range. Consumption correlation analysis module: Based on the ozone consumption during the ozone oxidation stage of RO concentrate in multiple historical treatment cycles, and the excess ozone during the Fe-C micro-electrolysis coupling stage. Content, construct correlation analysis curves, and perform correlation degree analysis to obtain the consumption correlation coefficient: Excessive ozone emission warning module: Performs linear analysis on the constructed correlation curve. If a positive linear correlation is found, the consumption correlation coefficient and ozone consumption range are combined to construct... Excessive warning model; Rate warning and adjustment module: During the Fe-C micro-electrolysis coupling stage, it acquires the generation rate of each historical processing period after the historical processing cycle is divided, analyzes it, determines the fastest generation rate, obtains the corresponding fastest historical period, and performs period stability analysis over multiple historical cycles to determine the location interval of the fastest period. Within the location interval of the fastest period, it adjusts the rate based on... The over-prevention model yielded the following results: Rate adjustment amount.

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