Automatic pretreatment method and system for industrial wastewater

Abstract

The invention relates to the technical field of wastewater treatment, in particular to an automatic pretreatment method and system.The method comprises the steps that firstly, according to the pH value of the current hour and related index data, the pH value of the next hour is predicted, and an initial pH predicted value is obtained; then analyzing the change similarity of the pH value in the known time period of the today and the corresponding time period of any historical day, and correcting the initial predicted pH value once to obtain a corrected predicted pH value; performing secondary correction on the pH correction predicted value by analyzing the influence of the adjacent filter grids on the change of the pH value of the wastewater in the current filter grid to obtain a pH predicted value; and finally, according to the pH predicted value, an agent is put into each filtering grid through an automatic agent adding system. According to the method and the system, the future pH value is predicted, so that the timeliness of pH regulation and control is improved, and the wastewater treatment effect is ensured.

Description

Technical Field

[0001] The invention relates to the technical field of wastewater treatment, and in particular to an automated pretreatment method and system for industrial wastewater. Background Art

[0002] With the development of science and technology, by utilizing new generation information technologies such as artificial intelligence, cloud computing and big data, combined with intelligent hardware, all-round real-time perception of wastewater treatment processes can be achieved. The regulation of pH value is crucial in the process of wastewater treatment. Most wastewater treatment systems are equipped with automatic dosing systems for pH value regulation. The system is equipped with online pH monitoring instruments that can detect the pH value of wastewater in real time. Once the pH value exceeds the preset control range, the system will automatically trigger the dosing device for adjustment.

[0003] However, in the current automatic dosing system, the pH value will only be adjusted when it exceeds the preset control range. After dosing, it cannot be guaranteed that the pH value of all wastewater will return to the normal range in a short period of time. The pH value of the wastewater will be in an abnormal range during the intermediate period, which may cause some wastewater to fail to achieve the expected treatment effect. Summary of the invention

[0004] In order to solve the above technical problems, the object of the present invention is to provide an automated pretreatment method and system for industrial wastewater.

[0005] According to a first aspect of an embodiment of the present invention, an automated pretreatment method for industrial wastewater is provided, and the technical solution adopted is specifically as follows: Collect the pH value and related index data of wastewater in each filter cell; According to the pH value, a pH value variation curve of the wastewater in each filter grid is obtained every day; According to the pH value of the current hour and related index data, the pH value of the next hour is predicted to obtain the initial predicted pH value of the wastewater in each filter cell; Based on the pH value change curve, the similarity of the pH value change of the wastewater in each filter cell in the known time period today and the corresponding time period of any historical day is analyzed, and the initial pH prediction value is corrected once to obtain the pH correction prediction value of the wastewater in each filter cell; Analyze the influence of all adjacent filter cells on the change of pH value of wastewater in the current filter cell, perform secondary correction on the pH correction prediction value, and obtain the pH prediction value of wastewater in each filter cell; According to the predicted pH value, the agent is added into each filter grid through the automatic dosing system.

[0006] In some embodiments of the present invention, the pH value for the next hour is predicted based on the pH value of the current hour and related indicator data to obtain an initial predicted pH value of the wastewater in each filter cell, including: According to the current relevant indicator data and the relevant indicator data of the previous hour, the change range of the relevant indicator data is obtained; According to the variation range and in combination with the pH value of the current hour, the pH value for the next hour is predicted to obtain an initial predicted pH value of the wastewater in each filter cell.

[0007] In some embodiments of the present invention, based on the pH value change curve, the similarity of the pH value change of the wastewater in each filter cell in the known time period today and the corresponding time period of any historical day is analyzed, and the initial pH prediction value is corrected once to obtain the pH correction prediction value of the wastewater in each filter cell, including: Analyze the DTW distance between the pH value change curve of the wastewater in each filter cell during a known period today and a corresponding period of any day in history to obtain the similarity of the pH value change curve; Analyze the difference between the change range of the relevant indicator data in the known time period of the wastewater in each filter cell today and the corresponding time period of any day in history, and obtain the consistency of the change range of the relevant indicator data; According to the similarity of the pH value change curve and the consistency of the change amplitude, the similarity of the pH value change between today and any day in history is obtained; According to the similarity of the pH value change, the initial pH prediction value is corrected once to obtain the pH correction prediction value of the wastewater in each filter cell.

[0008] In some embodiments of the present invention, the initial predicted pH value is corrected once according to the similarity of the pH value change to obtain the pH corrected predicted value of the wastewater in each filter cell, including: For each filter grid, according to all the pH value change similarities, determine the date corresponding to the maximum value of the pH value change similarity as the similar day; Obtain the historical pH value change range between the current hour and the next hour corresponding to the similar day, and obtain the predicted pH value change range between the pH value of the current hour and the initial predicted pH value of the next hour; According to the historical pH value change range and the predicted pH value change range, combined with the pH value change similarity between today and the similar day, a correction factor for the predicted pH value change range is obtained; According to the correction factor and the predicted pH value change range, combined with the pH value of the current hour, the pH correction predicted value of the wastewater in each filter cell is obtained.

[0009] In some embodiments of the present invention, the influence of all adjacent filter cells on the change of pH value of wastewater in the current filter cell is analyzed, and the pH correction prediction value is corrected twice to obtain the pH prediction value of wastewater in each filter cell, including: Analyze the correlation between the pH value changes of the current filter grid and all adjacent filter grids; Based on the pH value change correlation, analyzing the pH values ​​of all adjacent filter grids corresponding to the next hour; According to the correlation of pH value changes between the current filter grid and the four neighboring filter grids, the correlation gradient direction of the current filter grid is obtained; Analyze the relationship between the current filter grid and the adjacent filter grid Diffusion, get the pH gradient direction of the current filter grid; Analyzing the cosine similarity between the correlation gradient direction and the pH gradient direction to obtain the predicted value weight affected by adjacent filter grids; Obtaining the comprehensive prediction value weights corresponding to all adjacent filter grids according to all the pH value change correlations and the prediction value weights; According to the predicted value weight, the comprehensive predicted value weight and the pH value in the next hour, the pH corrected predicted value is corrected twice to obtain the pH predicted value of the wastewater in each filter cell.

[0010] In some embodiments of the present invention, analyzing the correlation between the pH value changes of the current filter grid and all adjacent filter grids includes: Analyze the similarity between the pH value change curve corresponding to the current filter grid and the pH value change curve corresponding to the adjacent filter grid that is shifted to the right by t time units, and take the maximum value of the similarity as the maximum similarity; According to the maximum similarity, the pH value change correlation between the current filter grid and all adjacent filter grids is obtained in combination with the connected areas between the current filter grid and the adjacent filter grids.

[0011] In some embodiments of the present invention, based on the pH value change correlation, analyzing the pH values ​​of all adjacent filter grids corresponding to the next hour includes: The t corresponding to the maximum similarity is obtained as the lag time; Based on the current hour, shift the delay time forward to obtain the associated time of the current hour; The pH values ​​of all the adjacent filter grids in the next hour after the association time are obtained as the pH values ​​of all the adjacent filter grids in the next hour.

[0012] In some embodiments of the present invention, the correlation gradient direction of the current filter grid is obtained according to the correlation of pH value changes between the current filter grid and the four neighboring filter grids, including: Calculate the lateral difference between the correlations of the two pH value changes between the current filter grid and the two lateral neighboring filter grids to obtain the magnitude and direction of the lateral correlation gradient; Calculate the longitudinal difference between the correlations of the two pH value changes between the current filter grid and the two longitudinal neighboring filter grids to obtain the magnitude and direction of the longitudinal correlation gradient; The magnitude and direction of the horizontal correlation gradient and the magnitude and direction of the vertical correlation gradient are combined to obtain the correlation gradient direction of the current filter grid.

[0013] According to a second aspect of an embodiment of the present invention, an automated pretreatment system for industrial wastewater is provided, comprising: a memory and a processor, wherein: The memory is used to store program code; The processor is used to read the program code stored in the memory and execute the method described in the first aspect of the embodiment of the present invention.

[0014] In some embodiments of the present invention, the processor comprises: The index data collection module is used to collect the pH value and related index data of the wastewater in each filter cell; A pH value change curve acquisition module, used to obtain the pH value change curve of the wastewater in each filter grid every day according to the pH value; The pH value prediction module is first used to predict the pH value for the next hour based on the pH value of the current hour and related indicator data to obtain the initial pH prediction value of the wastewater in each filter cell; then used to analyze the similarity of the pH value change of the wastewater in each filter cell in the known time period today and the corresponding time period of any historical day, and to correct the initial pH prediction value once to obtain the pH correction prediction value of the wastewater in each filter cell; finally, used to analyze the influence of all adjacent filter cells on the pH value change of the wastewater in the current filter cell, and to correct the pH correction prediction value twice to obtain the pH prediction value of the wastewater in each filter cell; The pH value control module is used to add medicine into each filter grid through an automatic dosing system according to the predicted pH value.

[0015] Compared with the prior art, the present invention provides an automated pretreatment method and system for industrial wastewater, which have the following beneficial effects: the present invention first analyzes the changing trend of the pH value according to the pH value and related index data of the current hour, and makes a preliminary prediction of the pH value in the next hour; then analyzes the similarity between the pH value change curves of different historical days and the pH value change curves of today, determines the different historical days with similar overall changes to today, and combines the changes in related index data between today and different historical days to determine the similar historical days with similar overall changes to today and with the same reasons for the changes, corrects the changing trend of the pH value today based on the known pH value changes of similar days, and further predicts the pH value in the next hour; finally, the influence of adjacent filter grids on the pH value changes of the wastewater in the current filter grid is considered, and the pH correction prediction value is corrected again to obtain the pH prediction value of the wastewater in each filter grid. The method and system of the present invention improve the timeliness of pH regulation and ensure the effect of wastewater treatment by predicting future pH values; and by comparing the data of different historical days with today and the influence of pH value changes between adjacent filter cells, the pH prediction value is corrected twice, so that the final pH prediction value is more accurate, providing a more reliable data basis for subsequent pH regulation and ensuring the accuracy and efficiency of regulation. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the drawings required for use in the embodiments or the prior art descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0017] Figure 1 A basic flow diagram of an automated pretreatment method for industrial wastewater provided by one embodiment of the present invention; Figure 2 A schematic diagram of the basic components of a pH prediction value analysis method provided by one embodiment of the present invention; Figure 3 A schematic diagram of the basic components of an automated pretreatment system for industrial wastewater provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0018] In order to further explain the technical means and effects adopted by the present invention to achieve the predetermined invention purpose, the following is a detailed description of the automatic pretreatment method and system of industrial wastewater proposed by the present invention, its specific implementation method, structure, characteristics and effects, in combination with the accompanying drawings and preferred embodiments. In the following description, different "one embodiment" or "another embodiment" does not necessarily refer to the same embodiment. In addition, specific features, structures or characteristics in one or more embodiments may be combined in any suitable form.

[0019] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those generally understood by those skilled in the art of the present invention. Terms such as "comprises", "comprising" or any other variant thereof are intended to cover non-exclusive inclusions, so that a circuit structure, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such articles or devices. In the absence of further restrictions, there are elements defined by the statement "comprising one...", and it is not excluded that there are other identical elements in the articles or devices including the elements. Relational terms such as the terms "first" and "second" are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations.

[0020] The scenario targeted by the present invention is: in the wastewater pretreatment system, the pH value of the wastewater needs to be monitored. A pH value monitor is installed in each filter grid of the filter pool, and a DO value measuring instrument and a thermometer are installed. There is also an automatic dosing system that can add reagents to different filter grids. When the pH concentration of a filter grid exceeds a reasonable range, it can be individually dosed. Therefore, the purpose of the present invention is: in the process of wastewater filtration, the pH value of the next stage is predicted by analyzing the monitoring data, and when the pH value is monitored to have a risk of exceeding the limit, it is adjusted in time by adding a reagent, so as to avoid the failure to adjust the pH value of the wastewater in time after adding the reagent, resulting in unsatisfactory treatment effect of some wastewater. Adjustment in advance can make the pH value always within the ideal range.

[0021] Based on the above scenarios and purposes, the present invention monitors the main parameters that may affect the pH value in real time, obtains the predicted value of the pH value in the next stage according to the current pH value level combined with the monitoring results of other main parameters, and then corrects the obtained pH value prediction results in combination with the mutual influence between different filter grids, and judges whether it is necessary to administer the agent based on the prediction results, and adjusts the pH value in advance to ensure that the pH value continues to be maintained within a reasonable range.

[0022] The specific scheme of the automated pretreatment method for industrial wastewater provided by the present invention is described in detail below in conjunction with the accompanying drawings.

[0023] See also Figure 1 , which shows the basic process of an automated pretreatment method for industrial wastewater provided by an embodiment of the present invention.

[0024] like Figure 1 As shown, an automatic pretreatment method for industrial wastewater provided by one embodiment of the present invention specifically includes: S100: Collect the pH value and related index data of the wastewater in each filter cell.

[0025] Establish a special database to store the pH value and related index data of wastewater in each filter grid collected by the system, including dissolved oxygen content (DO value) and temperature data. Connect the database to the pH value monitors of different wastewater filter grids and record their readings to obtain the pH value of wastewater in each filter grid; and obtain the reading records of the DO value (dissolved oxygen content) measuring instrument in the same way, and also obtain the daily temperature changes recorded by hour.

[0026] The acquired pH value and related indicator data are cleaned, and the missing values ​​and outliers in the data are processed to provide reliable and practical data for the subsequent data analysis process.

[0027] S200: According to the pH value, a pH value variation curve of the wastewater in each filter cell is obtained every day.

[0028] According to the real-time monitoring results of the pH value, the pH value change curve of the wastewater in each filter grid is obtained every day, and the curve chart is further divided into hours. The hourly monitoring average value of the pH value is recorded as the pH representative value at the end of the hour. For example, the pH value monitoring average value from 9:00 to 10:00 is recorded as the pH representative value at 10:00, and the hourly average pH value change curve within a day is further obtained. The hourly average pH value change curve obtained is stored in the database. It should be noted that the pH value change curves used in subsequent analysis are all hourly average pH value change curves after division.

[0029] S300: Based on the pH value of the current hour and related indicator data, the pH value of the next hour is predicted to obtain an initial predicted pH value of the wastewater in each filter cell.

[0030] For wastewater treatment systems, temperature changes generally affect the pH value of wastewater. Temperature changes affect the ionization balance of water, which in turn affects the pH value. Usually, an increase in temperature will increase the H+ concentration in water, which may reduce the pH value. Therefore, the higher the monitored ambient temperature, the more likely it is that the pH value of the wastewater will decrease.

[0031] At the same time, photosynthesis and respiration will affect the pH value of wastewater. In natural water bodies, photosynthesis consumes carbon dioxide, resulting in an increase in pH value; while the respiration of aquatic organisms produces carbon dioxide, resulting in a decrease in pH value. The photosynthesis process will increase the dissolved oxygen content (DO value) in the water body, and respiration will reduce the dissolved oxygen in the water body. Therefore, a dissolved oxygen meter is used to monitor the dissolved oxygen concentration in real time to determine the effects of photosynthetic activity and respiration on dissolved oxygen. A lower DO value level may indicate strong biological respiration or weak photosynthesis. The lower the monitored DO value, the more likely it is that the pH value of the wastewater will be lower in the future.

[0032] Based on the above analysis, this embodiment predicts the pH value for the next hour based on the pH value of the current hour and the relevant index data, and obtains the initial predicted pH value of the wastewater in each filter grid. Further, based on the current relevant index data and the relevant index data of the previous hour, the change range of the relevant index data is obtained; based on the change range, combined with the pH value of the current hour, the pH value for the next hour is predicted to obtain the initial predicted pH value of the wastewater in each filter grid.

[0033] The calculation formula for constructing the initial predicted pH value is: In the formula, It represents the initial predicted pH value of the wastewater in the mth filter cell in the next hour; It represents the change of the average temperature of the wastewater in the mth filter cell in the current hour compared with the average temperature in the previous hour, and when the value is 0, it is replaced by 0.1 for calculation, where, , It represents the average temperature of the wastewater in the mth filter cell in the last hour. Indicates the average temperature of the wastewater in the mth filter cell in the current hour; Indicates the change in the average DO level of the wastewater in the mth filter cell in the current hour compared to the average DO level in the previous hour, where: , It represents the average DO level of the wastewater in the mth filter cell in the last hour. It indicates the average DO level of the wastewater in the mth filter cell in the current hour; It represents the pH value of the wastewater in the mth filter cell in the current hour. It should be noted that the pH value at this time is the average pH value in the current hour, that is, the pH representative value. The prediction of the pH value in the next hour is also the prediction of the pH representative value. Therefore, the subsequent pH values ​​(including pH initial prediction value, pH revised prediction value, pH prediction value, etc.) all represent the average pH value in a certain hour unless otherwise specified.

[0034] The change in average temperature The larger the value, the higher the temperature, and the corresponding pH value will decrease; the change range of the average DO level The larger it is, the higher the dissolved oxygen content in the water body, and the corresponding pH value will increase.

[0035] S400: Based on the pH value change curve, analyze the similarity of the pH value change of the wastewater in each filter cell in the known time period today and the corresponding time period of any historical day, correct the initial pH prediction value once, and obtain the pH correction prediction value of the wastewater in each filter cell.

[0036] Combine the pH value change curve of any day in history with today's pH value change curve and the temperature and DO level changes of the two days to jointly correct the above pH value change trend, and further predict the pH value in the next hour. The higher the similarity between today's known pH value change curve and the pH value change curve of the corresponding time period of a previous day, and the higher the similarity between the temperature and DO monitoring value change curves in the corresponding time period, the more similar the overall pH value changes in the two days are.

[0037] Based on the above analysis, this embodiment analyzes the similarity of the pH value change of the wastewater in each filter cell between the known time period today and the corresponding time period of any day in history based on the pH value change curve, and corrects the initial pH prediction value to obtain the pH correction prediction value of the wastewater in each filter cell. Further including: First, the DTW distance between the pH value change curve of the wastewater in each filter grid in the known time period today and the corresponding time period of any historical day is analyzed to obtain the similarity of the pH value change curve. A specific example is: for each filter grid, the pH value change curve in the corresponding time period of any historical day is obtained corresponding to the known time period today. For example, if the current time is 15:00, the currently known pH value change curve is the change curve from 0:00 to 15:00, and the curve in the corresponding time period is the change curve from 0:00 to 15:00 on any historical day; the DTW algorithm is used to analyze the DTW distance between the pH value change curve in the known time period today and the corresponding time period of any historical day, which is recorded as the similarity of the pH value change curve today and any historical day.

[0038] Then, since the DTW distance represents the overall similarity between the two curves, it cannot be determined whether the reasons for their overall similarity are the same. When the reasons for their overall similarity are the same, it means that the pH value changes in two days should be more similar, and then the similarity of the pH value change curve is corrected according to the corresponding temperature and DO level change data of the corresponding day in the historical records. Therefore, this embodiment obtains the consistency of the change amplitude of the relevant indicator data by analyzing the difference in the change amplitude of the relevant indicator data in the known time period of the wastewater in each filter grid today and the corresponding time period of any historical day. And, based on the similarity of the pH value change curve and the consistency of the change amplitude, the similarity of the pH value change between today and any historical day is obtained.

[0039] The calculation formula for the similarity of pH value changes between today and any day in history is: In the formula, Indicates the similarity of pH value change between today and the xth day in history for the mth filter; Indicates the similarity of the pH value change curve of the mth filter grid today and the xth day in history; Indicates the change in the average temperature of the mth filter grid in the i-th hour today compared to the average temperature of the previous hour; Indicates the change in the average temperature of the ith hour on the xth day of the mth filter compared to the average temperature of the previous hour; Indicates the change in the average DO level of the mth filter grid in the i-th hour today compared to the average DO level of the previous hour; It indicates the change of the average DO level in the ith hour on the xth day of the mth filter compared with the average DO level in the previous hour; L indicates the number of hours between 0:00 and the current hour; exp indicates an exponential function with the natural constant e as the base; norm indicates a linear normalization function.

[0040] It represents the absolute value of the difference between the average temperature of the ith hour of the mth filter grid today and the xth day in history compared with the average temperature of the previous hour. The larger the value, the greater the difference in temperature change between today and the xth day in history, indicating that the possibility that the temperature change is the same is smaller, and the corresponding pH value change is smaller. It indicates the absolute value of the difference between the average temperature of the ith hour of the mth filter grid today and the xth day in history compared to the change range of the DO average level in the previous hour. The larger the value, the greater the difference in DO value change between today and the xth day in history, indicating that the reason for their overall similarity is that the possibility of the same DO value change is smaller, and the corresponding pH value change similarity is smaller. By comparing the change range of the corresponding average temperature between today and the xth day in history and the change range of the DO average level, the similarity of the pH value change curve is corrected.

[0041] Similarly, the similarity of pH value changes between today and all historical days is obtained.

[0042] Finally, according to the similarity of pH value changes, the initial pH prediction value is corrected to obtain the pH correction prediction value of the wastewater in each filter cell. Specifically, it includes: First, for each filter grid, based on the similarity of pH value changes between today and all historical days, the date corresponding to the maximum pH value change similarity is determined as the similar day, which is expressed as ; and obtain the historical pH value change range between the current hour and the next hour corresponding to the similar day. For example, if the current hour is 15:00, then obtain the historical pH value change range between 15:00 and 16:00 corresponding to the similar day. The pH value change range is the ratio of the pH difference between 16:00 and 15:00 to the pH value at 15:00; and obtain the predicted pH value change range between the pH value of the current hour and the initial predicted pH value for the next hour. The predicted pH value change range is calculated in the same way as above.

[0043] Second, based on the historical pH value change range and the predicted pH value change range, combined with the similarity of pH value changes between today and similar days, the correction factor of the predicted pH value change range is obtained. The calculation formula of the correction factor is: In the formula, The correction factor representing the pH value change of the mth filter in the next hour; Indicates the similarity of pH value changes between the current day and similar days for m filter grids; Indicates the historical pH value change between the current hour and the next hour corresponding to the mth filter grid similar day; It represents the predicted pH value change between the pH value of the mth filter in the current hour and the initial predicted pH value in the next hour, that is, ; norm represents the linear normalization function.

[0044] It means that if the change rate of the pH value change curve of the mth filter grid on a similar day is greater than that of today, it will be adjusted larger, and if it is smaller than that of today, it will be adjusted smaller; and the higher the similarity of the pH value change, the greater the adjustment amplitude according to the similar curve.

[0045] Third, based on the correction factor and the predicted pH change, combined with the current hourly pH value, the pH correction prediction value of the wastewater in each filter cell is obtained. The calculation formula for the pH correction prediction value is: In the formula, It represents the pH correction prediction value of the wastewater in the mth filter cell; The correction factor representing the pH value change of the mth filter in the next hour; Indicates the predicted pH value change between the pH value of the mth filter cell in the current hour and the initial predicted pH value in the next hour; Indicates the pH value of the wastewater in the mth filter cell at the current hour.

[0046] Correction factor by pH value variation The predicted pH value variation is corrected to obtain a pH corrected predicted value.

[0047] S500: Analyze the influence of all adjacent filter cells on the change of pH value of wastewater in the current filter cell, perform secondary correction on the pH correction prediction value, and obtain the pH prediction value of wastewater in each filter cell.

[0048] Most wastewater treatment systems divide the filter pool into multiple filter grids. Different monitoring points can be set in different filter grids to track water quality changes in real time and make targeted adjustments. Due to this special structure, during the treatment process, the pH value of the filter grid may be affected by the pH value of the adjacent filter grid due to the fluidity of the water. When the water in filter grid A flows into filter grid B, the change trend of the pH value in filter grid B will generally be similar to that of filter grid A. The higher the similarity, the greater the influence.

[0049] Based on the above analysis, this embodiment performs a secondary correction on the pH correction prediction value by analyzing the influence of all adjacent filter cells on the pH value change of the wastewater in the current filter cell, and obtains the pH prediction value of the wastewater in each filter cell.

[0050] See also Figure 2 , which shows the basic process of a pH prediction value analysis method provided by an embodiment of the present invention.

[0051] like Figure 2 As shown, the influence of all adjacent filter cells on the pH value change of the wastewater in the current filter cell is analyzed, and the pH correction prediction value is corrected twice to obtain the pH prediction value of the wastewater in each filter cell, including: S501: Analyze the correlation between the pH value changes of the current filter grid and all adjacent filter grids.

[0052] The influence between two filter grids usually has a lag, so the correlation of pH value changes of the two filter grids can be obtained by translating the pH value change curve. Therefore, the correlation of pH value changes between the current filter grid and all adjacent filter grids is analyzed, specifically including: analyzing the similarity between the pH value change curve corresponding to the current filter grid and the pH value change curve corresponding to the adjacent filter grid translated to the right by t time units, and taking the maximum value of the similarity as the maximum similarity; according to the maximum similarity, combined with the connected area between the current filter grid and the adjacent filter grid, the correlation of pH value changes between the current filter grid and all adjacent filter grids is obtained. The calculation formula for constructing the correlation of pH value changes between the current filter grid and all adjacent filter grids is: In the formula, Indicates the correlation of pH value changes between the mth filter grid and its adjacent nth filter grid; Indicates the similarity between the pH value change curve of the mth filter grid within two hours and the pH value change curve of the nth filter grid adjacent to it after being shifted to the right by t time units. Here, the similarity of the two curves can also be expressed by the DTW distance value between the two curves; represents the connected area between the mth filter grid and its adjacent nth filter grid; a represents the total number of rightward translations is a; represents the maximum similarity among all a times of rightward translation; norm represents the linear normalization function.

[0053] By shifting rightward for t time units multiple times, multiple similarities are obtained, and the maximum similarity is taken to represent the influence between the mth filter grid and its adjacent nth filter grid; and because the larger the connected area of ​​the two filter grids, the greater the influence between the corresponding two filter grids, therefore, the similarity is corrected by the connected area of ​​the two filter grids to obtain the correlation of pH value changes between the two filter grids.

[0054] S502: Based on the correlation of pH value changes, analyze the pH values ​​of all adjacent filter grids corresponding to the next hour.

[0055] Due to the hysteresis of the influence, if you want to analyze the influence of the adjacent filter grid on the current filter grid to determine the pH prediction value for the next hour, you need to refer to the pH value of the corresponding moment when the adjacent filter grid can affect the pH value for the next hour. Therefore, based on the correlation of pH value changes, analyze the pH value of the next hour corresponding to all adjacent filter grids. The specific method is as follows: obtain t corresponding to the maximum similarity, which is the lag time; based on the current hour, move the length of the lag time forward to obtain the association time of the current hour; obtain the pH value of all adjacent filter grids in the next hour of the association time as the pH value of all adjacent filter grids in the next hour.

[0056] S503: Obtaining the correlation gradient direction of the current filter grid according to the correlation of pH value changes between the current filter grid and the four neighboring filter grids.

[0057] According to the correlation of pH value changes between the current filter grid and the four neighboring filter grids, the correlation gradient of the current filter grid is obtained. The specific method is: calculate the lateral difference of the two pH value change correlations between the current filter grid and the two lateral neighboring filter grids to obtain the size and direction of the lateral correlation gradient, where the size is the size of the lateral difference, and the direction is the side with the larger lateral difference; calculate the longitudinal difference of the two pH value change correlations between the current filter grid and the two longitudinal neighboring filter grids to obtain the size and direction of the longitudinal correlation gradient, where the size is the size of the longitudinal difference, and the direction is the side with the larger longitudinal difference; combine the size and direction of the lateral correlation gradient with the size and direction of the longitudinal correlation gradient to obtain the correlation gradient direction of the current filter grid, that is, sum the vectors of the two correlation gradients to determine the correlation gradient direction.

[0058] S504: Analyze the relationship between the current filter grid and the adjacent filter grid Diffusion, get the pH gradient direction of the current filter grid.

[0059] Since pH and Content related, so high The area with the highest concentration of PH value will diffuse, causing the pH value of the wastewater in the surrounding filter grids to decrease. Based on the current pH value of the wastewater in each filter grid, the pH value of the wastewater in the filter grid is determined. The direction of diffusion is obtained, thereby obtaining the direction of pH value decrease, and then obtaining the gradient direction and magnitude of pH value, where the gradient direction of pH value is The pH gradient in the opposite direction of the diffusion direction is the pH difference. The pH gradient direction of the current filter grid is obtained by combining the horizontal and vertical gradients.

[0060] S505: Analyze the cosine similarity between the correlation gradient direction and the pH gradient direction to obtain the prediction value weight affected by the adjacent filter grids.

[0061] The more similar the pH gradient direction is to the correlation gradient direction, the higher the accuracy of predicting future pH changes based on the correlation of pH value changes in adjacent filter grids, which has a maximum weight of 0.7. Therefore, by analyzing the cosine similarity between the correlation gradient direction and the pH gradient direction, the weight of the predicted value affected by the adjacent filter grid is obtained. The calculation formula for the weight of the predicted value affected by the adjacent filter grid is: In the formula, It represents the weight of the predicted value of the mth filter grid affected by the adjacent filter grid; A represents the correlation gradient direction; B represents the pH gradient direction; cossim represents the cosine similarity function.

[0062] S506: Obtaining the comprehensive prediction value weights corresponding to all adjacent filter grids according to all pH value change correlations and prediction value weights.

[0063] The pH value of the current filter in the next hour is predicted based on the correlation of pH value changes between the filter cells. The greater the correlation of pH value changes, the greater the weight of the related data in the pH value prediction. Therefore, this embodiment obtains the comprehensive prediction value weights corresponding to all adjacent filter grids according to the correlation of all pH value changes and the prediction value weights, and the calculation formula is: In the formula, Indicates the weight of the data related to the nth filter grid adjacent to the mth filter grid when calculating the pH prediction value; Indicates the weight of the predicted value of the mth filter grid affected by the adjacent filter grid; represents the correlation of pH value changes between the m-th filter grid and its adjacent n-th filter grid; N represents the number of filter grids adjacent to the m-th filter grid.

[0064] The greater the correlation between the pH value changes of the mth filter grid and its adjacent nth filter grid, the greater the weight of the corresponding filter grid related data in calculating the pH prediction value; and through Limit its maximum weight.

[0065] S507: According to the predicted value weight, the comprehensive predicted value weight and the pH value in the next hour, the pH corrected predicted value is corrected twice to obtain the pH predicted value of the wastewater in each filter cell.

[0066] According to the predicted value weight, the comprehensive predicted value weight and the pH value in the next hour, the pH correction predicted value is corrected twice to obtain the pH predicted value of the wastewater in each filter grid. The calculation formula for constructing the pH predicted value of the wastewater in each filter grid is: In the formula, It represents the predicted pH value of the wastewater in the mth filter cell in the next hour; Indicates the weight of the data related to the nth filter grid adjacent to the mth filter grid when calculating the pH prediction value; Indicates the weight of the predicted value of the mth filter grid affected by the adjacent filter grid; It represents the pH correction prediction value of the wastewater in the mth filter cell; represents the pH value of the next hour corresponding to the nth filter grid adjacent to the mth filter grid; N represents the number of filter grids adjacent to the mth filter grid.

[0067] S600: According to the predicted pH value, the reagent is added into each filter cell through the automatic dosing system.

[0068] When the predicted pH value for the next hour exceeds the preset pH value range, for example, the preset pH value is [6, 8], the automatic dosing system calculates the dosage of the agent according to the extent that the predicted pH value exceeds the range. The automatic dosing system accurately doses the acid and alkali agents according to the calculated dosage (acidic agents are dosed if the value is greater than 8, and alkaline agents are dosed if the value is less than 6), and activates the stirring device to ensure uniform mixing of the agents. The entire dosing process monitors pH changes in real time through the control system. Once the preset target value is reached, the system automatically stops dosing to ensure that the pH of the wastewater is maintained within a safe and appropriate range. The recording and monitoring of pH data during the dosing process can provide a basis for subsequent optimization and ensure the accuracy and efficiency of the adjustment.

[0069] Based on the same inventive concept as the above method, this embodiment also provides an automated pretreatment system for industrial wastewater.

[0070] See also Figure 3 , which shows the basic composition of an automated pretreatment system for industrial wastewater provided by an embodiment of the present invention.

[0071] like Figure 3 As shown, an automated pretreatment system for industrial wastewater includes: a memory 10 and a processor 20, wherein: A memory 10, used for storing program codes; The processor 20 is used to read the program code stored in the memory 10, and execute the collection of the pH value and related index data of the wastewater in each filter grid; according to the pH value, obtain the pH value change curve of the wastewater in each filter grid every day; according to the pH value and related index data of the current hour, predict the pH value in the next hour, and obtain the initial pH prediction value of the wastewater in each filter grid; based on the pH value change curve, analyze the similarity of the pH value change of the wastewater in each filter grid in the known time period today and the corresponding time period of any historical day, correct the initial pH prediction value once, and obtain the pH correction prediction value of the wastewater in each filter grid; analyze the influence of all adjacent filter grids on the pH value change of the wastewater in the current filter grid, correct the pH correction prediction value twice, and obtain the pH prediction value of the wastewater in each filter grid; according to the pH prediction value, add a medicine to each filter grid through the automatic dosing system.

[0072] Furthermore, the processor 20 includes an index data acquisition module 21, a pH value change curve acquisition module 22, a pH value prediction module 23 and a pH value control module 24. Among them: The index data collection module 21 is used to collect the pH value and related index data of the wastewater in each filter cell; A pH value variation curve acquisition module 22, for obtaining a pH value variation curve of wastewater in each filter cell every day according to the pH value; The pH value prediction module 23 is first used to predict the pH value for the next hour based on the pH value of the current hour and related indicator data, and obtain the initial pH prediction value of the wastewater in each filter cell; then used to analyze the similarity of the pH value change of the wastewater in each filter cell in the known time period today and the corresponding time period of any historical day, and perform a correction on the initial pH prediction value to obtain the pH correction prediction value of the wastewater in each filter cell; finally, used to analyze the influence of all adjacent filter cells on the pH value change of the wastewater in the current filter cell, perform a second correction on the pH correction prediction value, and obtain the pH prediction value of the wastewater in each filter cell; The pH value control module 24 is used to add a drug into each filter cell through an automatic drug adding system according to the predicted pH value.

[0073] It should be noted that the sequence of the above embodiments of the present invention is for description only and does not represent the advantages and disadvantages of the embodiments. The processes depicted in the accompanying drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0074] The various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referenced to each other, and each embodiment focuses on the differences from other embodiments.

Claims

1. An automated pretreatment method for industrial wastewater, characterized in that: The method comprises: Collect the pH value and related index data of wastewater in each filter cell; According to the pH value, a pH value variation curve of the wastewater in each filter grid is obtained every day; According to the pH value of the current hour and related index data, the pH value of the next hour is predicted to obtain the initial predicted pH value of the wastewater in each filter cell; Based on the pH value change curve, the similarity of the pH value change of the wastewater in each filter cell in the known time period today and the corresponding time period of any historical day is analyzed, and the initial pH prediction value is corrected once to obtain the pH correction prediction value of the wastewater in each filter cell; Analyze the influence of all adjacent filter cells on the change of pH value of wastewater in the current filter cell, perform secondary correction on the pH correction prediction value, and obtain the pH prediction value of wastewater in each filter cell; According to the predicted pH value, the agent is added into each filter grid through the automatic dosing system.

2. The automated pretreatment method for industrial wastewater according to claim 1, characterized in that: Based on the current hour's pH value and related indicator data, the pH value for the next hour is predicted to obtain the initial predicted pH value of the wastewater in each filter cell, including: According to the current relevant indicator data and the relevant indicator data of the previous hour, the change range of the relevant indicator data is obtained; According to the variation range and in combination with the pH value of the current hour, the pH value for the next hour is predicted to obtain an initial predicted pH value of the wastewater in each filter cell.

3. The automated pretreatment method for industrial wastewater according to claim 1, characterized in that: Based on the pH value change curve, the similarity of the pH value change of the wastewater in each filter cell in the known time period today and the corresponding time period of any historical day is analyzed, and the initial pH prediction value is corrected once to obtain the pH correction prediction value of the wastewater in each filter cell, including: Analyze the DTW distance between the pH value change curve of the wastewater in each filter cell during a known period today and a corresponding period of any day in history to obtain the similarity of the pH value change curve; Analyze the difference between the change range of the relevant indicator data in the known time period of the wastewater in each filter cell today and the corresponding time period of any day in history, and obtain the consistency of the change range of the relevant indicator data; According to the similarity of the pH value change curve and the consistency of the change amplitude, the similarity of the pH value change between today and any day in history is obtained; According to the similarity of the pH value change, the initial pH prediction value is corrected once to obtain the pH correction prediction value of the wastewater in each filter cell.

4. The automated pretreatment method for industrial wastewater according to claim 3, characterized in that: According to the similarity of the pH value change, the initial pH prediction value is corrected once to obtain the pH correction prediction value of the wastewater in each filter cell, including: For each filter grid, according to all the pH value change similarities, determine the date corresponding to the maximum value of the pH value change similarity as the similar day; Obtain the historical pH value change range between the current hour and the next hour corresponding to the similar day, and obtain the predicted pH value change range between the pH value of the current hour and the initial predicted pH value of the next hour; According to the historical pH value change range and the predicted pH value change range, combined with the pH value change similarity between today and the similar day, a correction factor for the predicted pH value change range is obtained; According to the correction factor and the predicted pH value change range, combined with the pH value of the current hour, the pH correction predicted value of the wastewater in each filter cell is obtained.

5. The automated pretreatment method for industrial wastewater according to claim 1, characterized in that: Analyze the influence of all adjacent filter cells on the change of pH value of wastewater in the current filter cell, perform secondary correction on the pH correction prediction value, and obtain the pH prediction value of wastewater in each filter cell, including: Analyze the correlation between the pH value changes of the current filter grid and all adjacent filter grids; Based on the pH value change correlation, analyzing the pH values ​​of all adjacent filter grids corresponding to the next hour; According to the correlation of pH value changes between the current filter grid and the four neighboring filter grids, the correlation gradient direction of the current filter grid is obtained; Analyze the relationship between the current filter grid and the adjacent filter grid Diffusion, get the pH gradient direction of the current filter grid; Analyzing the cosine similarity between the correlation gradient direction and the pH gradient direction to obtain the predicted value weight affected by adjacent filter grids; Obtaining the comprehensive prediction value weights corresponding to all adjacent filter grids according to all the pH value change correlations and the prediction value weights; According to the predicted value weight, the comprehensive predicted value weight and the pH value in the next hour, the pH corrected predicted value is corrected twice to obtain the pH predicted value of the wastewater in each filter cell.

6. The automated pretreatment method for industrial wastewater according to claim 5, characterized in that: Analyze the correlation between the pH value changes of the current filter grid and all adjacent filter grids, including: Analyze the similarity between the pH value change curve corresponding to the current filter grid and the pH value change curve corresponding to the adjacent filter grid that is shifted to the right by t time units, and take the maximum value of the similarity as the maximum similarity; According to the maximum similarity, the pH value change correlation between the current filter grid and all adjacent filter grids is obtained in combination with the connected areas between the current filter grid and the adjacent filter grids.

7. The automated pretreatment method for industrial wastewater according to claim 6, characterized in that: Based on the pH value change correlation, the pH values ​​of all adjacent filter grids corresponding to the next hour are analyzed, including: The t corresponding to the maximum similarity is obtained as the lag time; Based on the current hour, shift the delay time forward to obtain the associated time of the current hour; The pH values ​​of all the adjacent filter grids in the next hour after the association time are obtained as the pH values ​​of all the adjacent filter grids in the next hour.

8. The automated pretreatment method for industrial wastewater according to claim 1, characterized in that: According to the correlation of pH value changes between the current filter grid and the four neighboring filter grids, the correlation gradient direction of the current filter grid is obtained, including: Calculate the lateral difference between the correlations of the two pH value changes between the current filter grid and the two lateral neighboring filter grids to obtain the magnitude and direction of the lateral correlation gradient; Calculate the longitudinal difference between the correlations of the two pH value changes between the current filter grid and the two longitudinal neighboring filter grids to obtain the magnitude and direction of the longitudinal correlation gradient; The magnitude and direction of the horizontal correlation gradient and the magnitude and direction of the vertical correlation gradient are combined to obtain the correlation gradient direction of the current filter grid.

9. An automated pretreatment system for industrial wastewater, characterized in that: The system comprises: a memory and a processor, wherein: The memory is used to store program code; The processor is configured to read the program code stored in the memory and execute the method according to any one of claims 1 to 8.

10. The automated pretreatment system for industrial wastewater according to claim 9, characterized in that: The processor comprises: The index data collection module is used to collect the pH value and related index data of the wastewater in each filter cell; A pH value change curve acquisition module, used to obtain the pH value change curve of the wastewater in each filter grid every day according to the pH value; The pH value prediction module is first used to predict the pH value for the next hour based on the pH value of the current hour and related indicator data to obtain the initial pH prediction value of the wastewater in each filter cell; then used to analyze the similarity of the pH value change of the wastewater in each filter cell in the known time period today and the corresponding time period of any historical day, and to correct the initial pH prediction value once to obtain the pH correction prediction value of the wastewater in each filter cell; finally, used to analyze the influence of all adjacent filter cells on the pH value change of the wastewater in the current filter cell, and to correct the pH correction prediction value twice to obtain the pH prediction value of the wastewater in each filter cell; The pH value control module is used to add medicine into each filter grid through an automatic dosing system according to the predicted pH value.

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