Intelligent ozone adding regulation and control system and method based on water quality purification

Abstract

The invention belongs to the technical field of water quality purification, and particularly relates to an intelligent ozone adding regulation and control system and method based on water quality purification. According to the method, multiple water quality indexes are weighted and synthesized into a comprehensive value, misleading of a feeding decision by a single index is avoided, the actual treatment load can be reflected more accurately, so that a more appropriate ozone feeding amount is obtained, a historical evaluation and compensation mechanism is introduced, the recent pollution change trend can be identified and corrected in the feeding amount, and the accuracy of ozone feeding is improved. The treatment failure or resource waste caused by sudden water quality fluctuation is reduced, the target index can be continuously corrected and approached, the standard reaching stability and response speed are improved, the excessive use of ozone is reduced through precise addition, the chemical and energy consumption cost is saved, the ozone residue and possible secondary pollution risk are reduced, and the environmental safety is improved. And by adopting table look-up mapping, field parameter maintenance, step-by-step optimization and expert experience introduction are facilitated.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of water quality purification, and particularly relates to an ozone dosing intelligent regulation and control system and method based on water quality purification. BACKGROUND

[0002] With the rapid development of China's economy and society, water pollution problems are becoming increasingly prominent. In particular, the water quality of large rivers represented by the Yangtze River is influenced by many factors such as seasonal changes, industrial emissions, agricultural non-point source pollution, and algae outbreaks, and presents complex and variable characteristics. Most water treatment plants in East China take the Yangtze River as the water source. The traditional water treatment process (such as coagulation, sedimentation, and filtration) has limited removal capacity for refractory organic matter, trace pollutants, odor substances, and microplastics, and it is difficult to stably meet the requirements of the drinking water health standard, let alone achieve the quality target of direct drinking water.

[0003] The ozone-activated carbon advanced treatment process adopted in the prior art has been widely used internationally due to its high removal capacity for organic matter, color, odor, and the like. However, this process still has significant technical bottlenecks in actual operation, especially the control of ozone dosage. Most water plants currently use fixed proportion or experience-based dosing methods, which are difficult to respond to dynamic changes in water quality in real time, resulting in insufficient ozone dosage, substandard treatment effect, excessive ozone dosage, increased operating costs, increased risk of byproduct generation, and even biological activity inhibition of subsequent activated carbon filters. SUMMARY

[0004] The purpose of the present application is to provide an ozone dosing intelligent regulation and control system and method based on water quality purification, which can optimize the intelligent regulation and control of ozone dosage in real time according to water quality changes, and improve the operation efficiency of water plants and guarantee the water quality.

[0005] The technical solutions adopted by the present application are as follows: An ozone dosing intelligent regulation and control method based on water quality purification, comprising: obtaining real-time water quality data of the water body to be treated, and obtaining comprehensive information of pollutant concentration based on the water quality data; constructing a historical evaluation period based on the comprehensive information of pollutant concentration, obtaining historical comprehensive information of pollutant concentration in the historical evaluation period, and obtaining historical compensation based on the historical comprehensive information of pollutant concentration; obtaining an ozone dosing control amount of the water body to be treated based on the comprehensive information of pollutant concentration and the historical compensation, and executing the ozone dosing control amount; constructing a feedback period, obtaining the comprehensive information of pollutant concentration after executing the ozone dosing control amount based on the feedback period, obtaining a comprehensive deviation of pollutant concentration, and obtaining an ozone dosing optimization strategy based on the comprehensive deviation of pollutant concentration; Reconstruct the historical evaluation period based on the ozone dosage optimization strategy, and reacquire the ozone dosage control quantity until the standard purification index requirement is met.

[0006] In a preferred scheme, real-time water quality data of the water body to be treated is acquired, and the step of acquiring comprehensive information of pollutant concentration based on the water quality data comprises: Acquiring real-time water quality data of the water body to be treated, wherein the water quality data comprises turbidity, organic matter concentration, algae content, odor substance concentration and water temperature; Acquiring turbidity value, organic matter concentration value, algae content value, odor substance concentration value and water temperature value based on the water quality data; Acquiring water quality weight, wherein the water quality weight comprises turbidity weight, organic matter weight, algae weight, odor weight and water temperature weight; Acquiring comprehensive value of pollutant concentration based on the turbidity value, organic matter concentration value, algae content value, odor substance concentration value, water temperature value and water quality weight, and marking it as comprehensive information of pollutant concentration.

[0007] In a preferred scheme, the step of constructing a historical evaluation period based on the comprehensive information of pollutant concentration, acquiring historical comprehensive information of pollutant concentration in the historical evaluation period, and acquiring historical compensation based on the historical comprehensive information of pollutant concentration comprises: Constructing a historical evaluation period based on the comprehensive information of pollutant concentration; Dividing the historical evaluation period into multiple historical evaluation data collection time points; Acquiring historical comprehensive information of pollutant concentration in each historical evaluation data collection time point, and acquiring historical comprehensive value of pollutant concentration based on the historical comprehensive information of pollutant concentration; Acquiring corresponding historical evaluation duration based on the historical evaluation period; Acquiring historical pollutant change value based on the multiple historical comprehensive values of pollutant concentration and the historical evaluation duration; Acquiring a compensation table, wherein the compensation table comprises multiple historical pollutant change value intervals and historical compensation corresponding to each historical pollutant change value interval; Acquiring corresponding historical compensation from the compensation table based on the historical pollutant change value interval corresponding to the historical pollutant change value.

[0008] In a preferred scheme, the step of constructing a historical evaluation period based on the comprehensive information of pollutant concentration comprises: Acquiring comprehensive value of pollutant concentration based on the comprehensive information of pollutant concentration; Acquiring reference duration and reference comprehensive value of pollutant concentration; Acquiring a duration optimization table, wherein the duration optimization table comprises multiple pollutant concentration comprehensive value intervals and duration optimization values corresponding to each pollutant concentration comprehensive value interval; acquire the corresponding time length optimization value from the time length optimization table based on the pollutant concentration comprehensive value interval corresponding to the pollutant concentration comprehensive value; acquire a historical evaluation time length based on the reference time length, the reference pollutant concentration comprehensive value, the pollutant concentration comprehensive value and the time length optimization value; acquire a starting time based on the historical evaluation time length and the ending time, and construct a historical evaluation time period. acquire a starting time based on the historical evaluation time length and the ending time, and construct a historical evaluation time period.

[0009] In a preferred scheme, based on the pollutant concentration comprehensive information and the historical compensation, an ozone dosage control amount of the treated water body meeting the standard purification index requirement is acquired, and the steps executed include: acquire the corresponding pollutant concentration comprehensive value based on the pollutant concentration comprehensive information; acquire the pollutant compensation value based on the pollutant concentration comprehensive value and the historical compensation; acquire an ozone dosage table, wherein the ozone dosage table includes a plurality of pollutant compensation value intervals and an ozone dosage control amount corresponding to each pollutant compensation value interval; acquire the corresponding ozone dosage control amount from the ozone dosage table based on the pollutant compensation value interval corresponding to the pollutant compensation value, and execute the ozone dosage control amount.

[0010] In a preferred scheme, a feedback time period is constructed, the pollutant concentration comprehensive information after the ozone dosage control amount is executed is acquired based on the feedback time period, the pollutant concentration comprehensive deviation is acquired, and the steps of acquiring the ozone dosage optimization strategy based on the pollutant concentration comprehensive deviation include: acquire the feedback time period based on the ozone dosage control amount; acquire an ending node of the feedback time period based on the feedback time period, acquire the pollutant concentration comprehensive information of the ending node of the feedback time period, extract the corresponding pollutant concentration comprehensive value, and mark it as the post-control pollutant concentration comprehensive value; acquire the corresponding predicted pollutant concentration comprehensive value based on the ozone dosage control amount; acquire the pollutant concentration comprehensive deviation based on the post-control pollutant concentration comprehensive value and the predicted pollutant concentration comprehensive value; acquire a dosage optimization table, wherein the dosage optimization table includes a plurality of pollutant concentration comprehensive deviation intervals and an ozone dosage optimization strategy corresponding to each pollutant concentration comprehensive deviation interval; acquire the corresponding ozone dosage optimization strategy from the dosage optimization table based on the pollutant concentration comprehensive deviation interval corresponding to the pollutant concentration comprehensive deviation.

[0011] In a preferred scheme, the step of acquiring the feedback time period based on the ozone dosage control amount includes: acquire a time node of executing the ozone adding control quantity, and mark as a start time of the feedback period; acquire a plurality of ozone adding control quantities in the historical evaluation period, and mark as historical ozone adding control quantities respectively; acquire a reference feedback duration, acquire a feedback duration based on the ozone adding control quantity, the plurality of historical ozone adding control quantities and the reference feedback duration; acquire an end time based on the feedback duration and the start time of the feedback period, and construct the feedback period.

[0012] In a preferred scheme, the step of reconstructing the historical evaluation period based on the ozone adding optimization strategy and reacquiring the ozone adding control quantity until the requirement of the standard purification index is met comprises: acquire an iteration duration table, wherein the iteration duration table comprises a plurality of ozone adding optimization strategies and an iteration historical evaluation duration corresponding to each ozone adding optimization strategy; acquire the corresponding iteration historical evaluation duration from the iteration duration table based on the ozone adding optimization strategy; acquire an acquisition time of the ozone adding optimization strategy, and mark as an end time of the iteration historical evaluation period; acquire a start time based on the iteration historical evaluation duration and the end time of the iteration historical evaluation period, and construct the iteration historical evaluation period; take the iteration historical evaluation period as a new historical evaluation period, and acquire a new historical compensation according to the new historical evaluation period; return the comprehensive information of the pollutant concentration after executing the ozone adding control quantity to the step of acquiring the ozone adding control quantity of the treated water body based on the comprehensive information of the pollutant concentration and the historical compensation until the requirement of the standard purification index is met, reacquire the ozone adding control quantity until the requirement of the standard purification index is met.

[0013] The application also provides an ozone adding intelligent regulation and control system based on water purification, which is used for the ozone adding intelligent regulation and control method based on water purification, and comprises: a concentration comprehensive module, which is used for acquiring real-time water quality data of the treated water body, and acquiring comprehensive information of the pollutant concentration based on the water quality data; a historical compensation module, which is used for constructing a historical evaluation period based on the comprehensive information of the pollutant concentration, acquiring historical comprehensive information of the pollutant concentration in the historical evaluation period, and acquiring a historical compensation based on the historical comprehensive information of the pollutant concentration; an ozone adding module, which is used for acquiring an ozone adding control quantity of the treated water body based on the comprehensive information of the pollutant concentration and the historical compensation, and executing the ozone adding control quantity; The adding feedback module is configured to construct a feedback period, obtain comprehensive information of the pollutant concentration after executing the ozone adding control amount based on the feedback period, and obtain a comprehensive deviation of the pollutant concentration, and obtain an ozone adding optimization strategy based on the comprehensive deviation of the pollutant concentration. The adding iteration module is configured to reconstruct a historical evaluation period based on the ozone adding optimization strategy, and reobtain the ozone adding control amount until the requirement of the standard purification index is met.

[0014] In addition, the application provides an ozone adding intelligent regulation and control terminal based on water quality purification, which comprises: one or more processors; a storage device having one or more programs stored thereon; When the one or more programs are executed by the one or more processors, the one or more processors implement the ozone adding intelligent regulation and control method based on water quality purification.

[0015] The application has the following technical effects: The application can more accurately reflect the actual treatment load by weighting and synthesizing multiple water quality indexes into a comprehensive value, thereby obtaining a more suitable ozone adding amount, and can identify the recent pollution change trend and correct the adding amount, reduce the treatment failure or resource waste caused by sudden water quality fluctuation, continuously correct and approach the target index, improve the stability and response speed of meeting the standard, accurately add to reduce the excessive use of ozone, save chemical and energy consumption costs, reduce the risk of ozone residue and possible secondary pollution, improve environmental safety, and introduce expert experience by using table mapping for easy on-site parameter maintenance and gradual optimization. BRIEF DESCRIPTION OF DRAWINGS

[0016] Figure 1 is a method flowchart provided by the application; Figure 2 is a system module diagram provided by the application. DETAILED DESCRIPTION

[0017] In order to make the above-mentioned purposes, features and advantages of the application more obvious and easy to understand, the specific embodiments of the application will be described in detail below with reference to the accompanying drawings.

[0018] In the following description, many specific details are set forth in order to provide a thorough understanding of the application, but the application can also be implemented in other ways different from those described herein, and those skilled in the art can make similar generalizations without departing from the scope of the application, therefore the application is not limited to the specific embodiments disclosed below.

[0019] Second, the "one embodiment" or "an embodiment" referred to herein means a specific feature, structure, characteristic, or combination of features and / or characteristics described herein that can be included in at least one implementation of the present application. The various appearances of "in one preferred embodiment", "in another preferred embodiment", or "in at least one embodiment" in the specification do not necessarily all refer to the same embodiment, although they can.

[0020] Third, the present application is described in detail in conjunction with the schematic diagram. In the detailed description of the embodiments of the present application, the schematic diagram is only an example and should not limit the scope of protection of the present application.

[0021] Please refer to the accompanying Figure 1 As shown in the accompanying drawings, an intelligent control method for ozone addition based on water quality purification is provided, comprising: S1, obtaining real-time water quality data of the water body to be treated, and obtaining comprehensive information of pollutant concentration based on the water quality data; S2, constructing a historical evaluation period based on the comprehensive information of pollutant concentration, obtaining historical comprehensive information of pollutant concentration in the historical evaluation period, and obtaining historical compensation based on the historical comprehensive information of pollutant concentration; S3, obtaining an ozone addition control amount of the water body to be treated based on the comprehensive information of pollutant concentration and the historical compensation, and executing the ozone addition control amount; S4, constructing a feedback period, obtaining comprehensive information of pollutant concentration after executing the ozone addition control amount based on the feedback period, obtaining comprehensive deviation of pollutant concentration based on the comprehensive information of pollutant concentration, and obtaining an ozone addition optimization strategy based on the comprehensive deviation of pollutant concentration; S5, reconstructing the historical evaluation period based on the ozone addition optimization strategy, and re-obtaining the ozone addition control amount until the requirement of the standard purification index is met.

[0022] As in the above steps S1 to S5, a plurality of parameters (such as turbidity, organic matter concentration, algae content, odor substance concentration, temperature, etc.) of the water body to be treated are collected by the online water quality sensor, and each index is weighted and summed according to the preset weight to obtain a comprehensive information of pollutant concentration reflecting the pollution load, i.e. a comprehensive value of pollutant concentration, which can reflect the instantaneous water quality condition and unify various pollution factors to the same scale for comparison and mapping. According to the current comprehensive value of pollutant concentration, an appropriate historical evaluation time length is determined from the time length optimization table, and a historical evaluation period is constructed backwardly. The period is divided into a plurality of sampling points, the historical comprehensive values at these sampling points are calculated, and the historical pollutant change value is obtained. The historical compensation is obtained by looking up the pre-established compensation table, which is used to correct the calculation of the current dosage. The current comprehensive value is combined with the historical compensation to obtain a pollutant compensation value for meeting the standard purification index. The actual ozone dosage control amount is determined by looking up the ozone dosage table and executed. After the dosage, the feedback period is constructed according to the rules, and the post-control pollutant comprehensive value is collected at the end of the feedback period. At the same time, the pollutant concentration comprehensive deviation between the pre-predicted value and the post-control value is calculated, and the corresponding ozone dosage optimization strategy is obtained from the dosage optimization table according to the deviation value. According to the obtained optimization strategy, the iteration historical evaluation time length corresponding to the current strategy is obtained from the iteration time length table, the historical evaluation period is reconstructed, the historical compensation is recalculated, and a new dosage control amount is generated again. Return to execute and enter the next feedback and adjustment cycle. The weighted and combined comprehensive value of multiple water quality indexes avoids the misdirection of single index to the dosage decision, and more accurately reflects the actual treatment load, so as to obtain a more appropriate ozone dosage. The introduction of historical evaluation and compensation mechanism can identify the recent pollution change trend and correct it in the dosage, reduce the treatment failure or resource waste caused by sudden water quality fluctuation, continuously correct and approach the target index, improve the stability and response speed of reaching the standard, accurately dose to reduce the overuse of ozone, save chemical and energy consumption costs, and reduce the risk of ozone residue and possible secondary pollution, improve environmental safety, and use table mapping to facilitate on-site parameter maintenance, gradual optimization and introduction of expert experience.

[0023] In a preferred embodiment, real-time water quality data of the water body to be treated is obtained, and the step of obtaining comprehensive information of pollutant concentration based on the water quality data comprises: S101, obtaining real-time water quality data of the water body to be treated, wherein the water quality data includes turbidity, organic matter concentration, algae content, odor substance concentration and water temperature; S102, obtaining turbidity value, organic matter concentration value, algae content value, odor substance concentration value and water temperature value based on the water quality data; S103, obtaining water quality weight, wherein the water quality weight includes turbidity weight, organic matter weight, algae weight, odor weight and water temperature weight; S104, obtain a pollutant concentration comprehensive value based on the turbidity value, the organic matter concentration value, the algae content value, the odor substance concentration value, the water temperature value and the water quality weight, and mark it as pollutant concentration comprehensive information.

[0024] In the steps S101-S104, real-time water quality data (turbidity, organic matter concentration, algae content, odor substance concentration and water temperature) is obtained from online monitoring equipment or sensors, the values of each index are extracted to obtain the turbidity value, the organic matter concentration value, the algae content value, the odor substance concentration value and the water temperature value, and weights (such as turbidity weight, organic matter weight, algae weight, odor weight and water temperature weight) are assigned to each index. The weights can be derived from expert experience, historical regression analysis or feature importance based on data training. The pollutant concentration comprehensive value is calculated based on the turbidity value, the organic matter concentration value, the algae content value, the odor substance concentration value, the water temperature value and the water quality weight. The calculation formula of the pollutant concentration comprehensive value is , wherein W represents the pollutant concentration comprehensive value, D represents the turbidity value, J represents the organic matter concentration value, L represents the algae content value, N represents the odor substance concentration value, S represents the water temperature value, The multi-dimensional water quality information is compressed into a single continuous index, which is convenient for controllers, lookup tables or models to use directly, reduces complex multi-threshold judgment, avoids misjudgment caused by distortion of a single index, and ensures the integrity of water quality evaluation.

[0025] In a preferred embodiment, based on the pollutant concentration comprehensive information, a historical evaluation period is constructed, historical pollutant concentration comprehensive information in the historical evaluation period is obtained, and the step of obtaining historical compensation based on the historical pollutant concentration comprehensive information comprises: S201, constructing a historical evaluation period based on the pollutant concentration comprehensive information; S202, dividing the historical evaluation period into a plurality of historical evaluation data collection time points; S203, obtaining historical pollutant concentration comprehensive information in each historical evaluation data collection time point, and obtaining a historical pollutant concentration comprehensive value based on the historical pollutant concentration comprehensive information; S204, obtaining a corresponding historical evaluation duration based on the historical evaluation period; S205, obtaining a historical pollutant change value based on a plurality of historical pollutant concentration comprehensive values and the historical evaluation duration; S206, obtain a compensation table, wherein the compensation table comprises a plurality of historical pollutant change value intervals and a historical compensation corresponding to each historical pollutant change value interval; S207, obtain the corresponding historical compensation from the compensation table based on the historical pollutant change value interval corresponding to the historical pollutant change value.

[0026] In the steps S201 to S207, the end time and the approximate length of the evaluation window are determined according to the current pollutant concentration comprehensive information, a historical evaluation period is formed, the evaluation period is divided into a plurality of time points at a certain sampling frequency, the pollutant concentration comprehensive information at each collection time point is read to obtain the historical pollutant concentration comprehensive value of each collection point, the total length of the historical evaluation period (i.e. the time span from the beginning to the end) is calculated, the change value of the pollutant in the evaluation period is calculated based on the collected historical pollutant concentration comprehensive value and the length, so as to quantify the recent pollution dynamics. The calculation formula of the historical pollutant change value is , wherein, is the historical pollutant change value, is the historical evaluation length, i is the number of the plurality of historical pollutant concentration comprehensive values, i = 1, 2, 3…n, is the i-th historical pollutant concentration comprehensive value, and a compensation table is maintained in advance, which maps different historical pollutant change values to corresponding historical compensations. According to the calculated historical pollutant change value, the corresponding historical compensation is obtained, the recent change trend is considered in the dosing control, the overshoot or frequent oscillation caused by blind increase or decrease of dosing is reduced, and the control is more stable.

[0027] In a preferred embodiment, the step of constructing a historical evaluation period based on the pollutant concentration comprehensive information comprises: S2011, obtaining a pollutant concentration comprehensive value based on the pollutant concentration comprehensive information; S2012, obtaining a reference length and a reference pollutant concentration comprehensive value; S2013, obtaining a length optimization table, wherein the length optimization table comprises a plurality of pollutant concentration comprehensive value intervals and a length optimization value corresponding to each pollutant concentration comprehensive value interval; S2014, obtaining the corresponding length optimization value from the length optimization table based on the pollutant concentration comprehensive value interval corresponding to the pollutant concentration comprehensive value; S2015, obtaining a historical evaluation length based on the reference length, the reference pollutant concentration comprehensive value, the pollutant concentration comprehensive value and the length optimization value; S2016, obtaining a time node of obtaining the pollutant concentration comprehensive information, and marking it as the end time of the historical evaluation period; S2017, obtain the starting time based on the historical evaluation time length and the ending time, and construct the historical evaluation time period.

[0028] As in the above steps S2011 to S2017, the pollutant concentration comprehensive value is obtained according to the pollutant concentration comprehensive information, the reference pollutant concentration comprehensive value and the reference time length are set in advance as the reference points for comparison and calculation, and a time length optimization table is constructed, which contains different pollutant concentration comprehensive value intervals and corresponding time length optimization values. When the actual pollutant concentration comprehensive value falls into a certain interval, the time length optimization value corresponding to the interval is extracted from the table to realize dynamic adjustment of the evaluation time length. The reference time length, the reference pollutant concentration comprehensive value, the real-time pollutant concentration comprehensive value and the time length optimization value are jointly calculated to obtain the specific historical evaluation time length. The calculation formula of the historical evaluation time length is , wherein, W represents the pollutant concentration comprehensive value, represents the reference pollutant concentration comprehensive value, represents the reference time length, represents the time length optimization value. The time point at which the pollutant concentration comprehensive information is currently obtained is taken as the ending time of the historical evaluation time period, and the starting time of the historical evaluation time period is obtained by forward calculation based on the historical evaluation time length, so as to form a complete historical evaluation time period. By introducing the time length optimization table, the historical evaluation time period can be flexibly adjusted according to the change of the pollutant concentration, avoiding the irrationality caused by the fixed time length in the traditional method, improving the adaptability of the evaluation, and the dynamic evaluation time length adjustment mechanism can quickly respond when the pollutant level is low and can enhance the robustness when the pollutant level is high, so as to ensure that the ozone addition control is more scientific.

[0029] In a preferred embodiment, the ozone addition control amount of the standard purification index demand of the water body to be treated is obtained based on the pollutant concentration comprehensive information and the historical compensation, and the steps executed include: S301, obtain the corresponding pollutant concentration comprehensive value based on the pollutant concentration comprehensive information; S302, obtain the pollutant compensation value based on the pollutant concentration comprehensive value and the historical compensation; S303, obtain the ozone addition table, wherein the ozone addition table includes a plurality of pollutant compensation value intervals and the ozone addition control amount corresponding to each pollutant compensation value interval; S304, obtain the corresponding ozone addition control amount from the ozone addition table based on the pollutant compensation value corresponding to the pollutant compensation value interval, and execute the ozone addition control amount.

[0030] As in the above steps S301 to S304, based on the pollutant concentration comprehensive information acquisition corresponding pollutant concentration comprehensive value, the pollutant concentration comprehensive value and the historical compensation are combined to obtain the pollutant compensation value, and the calculation formula of the pollutant compensation value is , wherein C represents the pollutant compensation value, W represents the pollutant concentration comprehensive value, and B represents the historical compensation. The introduction of the historical compensation can reflect the pollutant change of the water body in the past period of time, correct the current concentration information, eliminate the influence of accidental fluctuation or extreme data, and preset an ozone addition table. The pollutant compensation value in different intervals is correspondingly related to the corresponding ozone addition control quantity. According to the interval where the pollutant compensation value is located, the corresponding ozone addition control quantity is obtained from the ozone addition table, and the addition is executed. Real-time pollutant concentration information combined with historical compensation data can more accurately reflect the real pollution level of the water body, avoid excessive or insufficient addition caused by short-time abnormality or data deviation, realize precise addition on demand through the zoning control mechanism of the addition table, effectively reduce ozone agent waste, reduce processing energy consumption and operation cost, and introduce historical compensation. The addition decision is not dependent on the monitoring data at a single moment, but is based on the comprehensive basis of historical trends and real-time data, ensuring the continuity and stability of the water quality purification process.

[0031] In a preferred embodiment, a feedback period is constructed, the pollutant concentration comprehensive information after executing the ozone addition control quantity is obtained based on the feedback period, and the pollutant concentration comprehensive deviation is obtained. Based on the pollutant concentration comprehensive deviation, the step of obtaining the ozone addition optimization strategy includes: S401, obtaining a feedback period based on the ozone addition control quantity; S402, obtaining the end node of the feedback period based on the feedback period, obtaining the pollutant concentration comprehensive information of the end node of the feedback period, and extracting the corresponding pollutant concentration comprehensive value, which is marked as the pollutant concentration comprehensive value after control; S403, obtaining the corresponding predicted pollutant concentration comprehensive value based on the ozone addition control quantity; S404, obtaining the pollutant concentration comprehensive deviation based on the pollutant concentration comprehensive value after control and the predicted pollutant concentration comprehensive value; S405, obtaining an addition optimization table, wherein the addition optimization table includes a plurality of pollutant concentration comprehensive deviation intervals and the corresponding ozone addition optimization strategy of each pollutant concentration comprehensive deviation interval; S406, obtaining the corresponding ozone addition optimization strategy from the addition optimization table based on the pollutant concentration comprehensive deviation interval corresponding to the pollutant concentration comprehensive deviation.

[0032] As in the above steps S401 to S406, according to the current execution of the ozone dosage control amount, the time range of the feedback period is determined as the time window for monitoring the dosage effect, at the end of the feedback period, the comprehensive information of the pollutant concentration of the water body is obtained, and the comprehensive value is extracted, marked as the post-control pollutant concentration comprehensive value, reflecting the actual purification effect of the water body after the dosage, according to the preset dosage and historical data, the corresponding predicted pollutant concentration comprehensive value is obtained through the comparison table, reflecting the purification effect that the dosage should achieve under ideal control conditions, the post-control pollutant concentration comprehensive value is compared with the predicted pollutant concentration comprehensive value, and the pollutant concentration comprehensive deviation is obtained, and the calculation formula of the pollutant concentration comprehensive deviation is , wherein is the pollutant concentration comprehensive deviation, is the post-control pollutant concentration comprehensive value, is the predicted pollutant concentration comprehensive value, and the deviation reflects the difference between the actual dosage effect and the expected target, the preset dosage optimization table associates different deviation intervals with corresponding optimization strategies, according to the calculated pollutant concentration comprehensive deviation, the corresponding interval in the optimization table is matched, and the corresponding ozone dosage optimization strategy is obtained, the dosage effect is monitored in real time through the feedback period, and the optimization strategy is automatically generated based on the deviation, realizing the closed-loop control of the ozone dosage, avoiding one-time dosage failure or excess, and the deviation analysis can accurately reflect the difference between the actual purification effect and the expected target, making the subsequent dosage adjustment more accurate, regardless of the change of the water pollution level, the mechanism can dynamically adjust the dosage strategy, and ensure the adaptability of the purification process to different working conditions.

[0033] In a preferred embodiment, the step of obtaining the feedback period based on the ozone dosage control amount comprises: S4011, obtaining the time node of executing the ozone dosage control amount, and marking it as the start time of the feedback period; S4012, obtaining a plurality of ozone dosage control amounts in a historical evaluation period, and marking them as historical ozone dosage control amounts respectively; S4013, obtaining a reference feedback duration, S4014, obtaining the feedback duration based on the ozone dosage control amount, the plurality of historical ozone dosage control amounts and the reference feedback duration; S4015, obtaining the end time based on the feedback duration and the start time of the feedback period, and constructing the feedback period.

[0034] As in the steps S4011 to S4015 described above, the time node of the currently executed ozone dosage control amount is taken as the start time of the feedback period, which ensures that the instantaneous response of water purification can be tracked from the start of the dosage, providing a basis for evaluating the effect, obtaining a plurality of ozone dosage control amounts in the historical evaluation period, and marking them as historical ozone dosage control amounts. The historical dosage amount is used to judge the trend of the current water response compared with the history, thereby providing a basis for the dynamic adjustment of the length of the feedback period. A reference feedback length is introduced as the default time reference to ensure that the feedback period has a minimum effective length and avoid unstable data caused by too short monitoring time. The actual feedback length is calculated by considering the current dosage amount, the historical dosage amount, and the reference feedback length. The calculation formula of the feedback length is , wherein represents the feedback length, represents the reference feedback length, represents the ozone dosage control amount, g represents the number of the plurality of historical ozone dosage control amounts, g = 1, 2, 3…m, represents the gth historical ozone dosage control amount, and the feedback period end time is determined based on the feedback period start time and the calculated feedback length, thereby completing the construction of the complete feedback period. The length of the feedback period is dynamically adjusted according to the current dosage amount and the historical dosage, which can adapt to different water quality conditions and dosage conditions. The precisely constructed feedback period ensures that the pollutant concentration data can truly reflect the water response after ozone dosage, thereby improving the accuracy of the deviation analysis.

[0035] In a preferred embodiment, the step of reconstructing the historical evaluation period based on the ozone dosage optimization strategy and reacquiring the ozone dosage control amount until the requirement of the standard purification index is met comprises: S501, obtaining an iteration length table, wherein the iteration length table comprises a plurality of ozone dosage optimization strategies and an iteration historical evaluation length corresponding to each ozone dosage optimization strategy; S502, obtaining the corresponding iteration historical evaluation length from the iteration length table based on the ozone dosage optimization strategy; S503, obtaining the acquisition time of the ozone dosage optimization strategy and marking it as the end time of the iteration historical evaluation period; S504, obtaining the start time based on the iteration historical evaluation length and the end time of the iteration historical evaluation period, and constructing the iteration historical evaluation period; S505, taking the iteration historical evaluation period as a new historical evaluation period, and obtaining a new historical compensation according to the new historical evaluation period; S506, return the pollutant concentration comprehensive information after executing the ozone dosage control amount to the step of obtaining the ozone dosage control amount based on the pollutant concentration comprehensive information and the history compensation to obtain the standard purification index requirement of the water body to be treated, re-obtain the ozone dosage control amount until the standard purification index requirement is met.

[0036] In the above steps S501 to S506, an iteration duration table is preset, different ozone dosage optimization strategies are associated with corresponding iteration history evaluation durations, the corresponding iteration history evaluation duration is obtained from the iteration duration table according to the currently adopted ozone dosage optimization strategy, the duration determines how long the data needs to be traced back for history compensation calculation in this iteration, the obtained time of the current ozone dosage optimization strategy is taken as the end time of the iteration history evaluation period, and the period is ensured to cover the effect of the optimization strategy, the start time of the iteration history evaluation period is calculated based on the end time of the iteration history evaluation period and the iteration history evaluation duration, the new period is constructed, the period contains the latest dosage effect and history trend information, the iteration history evaluation period is taken as a new history evaluation period, the history compensation is recalculated based on the new period, the pollutant concentration comprehensive information after executing the ozone dosage control amount is taken as a new input, and the dosage calculation step is re-entered to obtain a new ozone dosage control amount, the dosage is continuously corrected through multiple iterations until the water purification index meets the preset standard, a closed-loop intelligent control is realized, the iteration mechanism can continuously adjust the history evaluation period and the dosage according to the actual dosage effect, a real closed-loop control is realized, the purification effect meets the standard, the history evaluation period and the history compensation are dynamically updated, the dosage decision is based on the latest water quality change trend, the accuracy of ozone dosage is significantly improved, when the water pollution condition changes, the iteration mechanism can quickly re-evaluate and adjust the dosage strategy, the response capability of the system to water quality fluctuations is enhanced, the dosage amount is optimized on demand, and excessive or insufficient ozone dosage is avoided, thereby effectively saving the amount of reagent and energy consumption.

[0037] Please refer to the accompanying Figure 2 The application also provides an ozone dosage intelligent regulation and control system based on water quality purification, which is used for the ozone dosage intelligent regulation and control method based on water quality purification, and comprises: A concentration comprehensive module is configured to obtain real-time water quality data of the water body to be treated, and obtain pollutant concentration comprehensive information based on the water quality data. A history compensation module is configured to construct a history evaluation period based on the pollutant concentration comprehensive information, obtain historical pollutant concentration comprehensive information in the history evaluation period, and obtain history compensation based on the historical pollutant concentration comprehensive information. An ozone dosage module is configured to obtain an ozone dosage control amount based on the pollutant concentration comprehensive information and the history compensation to meet the standard purification index requirement of the water body to be treated, and execute the ozone dosage control amount. The adding feedback module is configured to construct a feedback period, obtain comprehensive information of the pollutant concentration after executing the ozone adding control amount based on the feedback period, and obtain a comprehensive deviation of the pollutant concentration based on the comprehensive deviation of the pollutant concentration, and obtain an ozone adding optimization strategy based on the comprehensive deviation of the pollutant concentration; The adding iteration module is configured to reconstruct a historical evaluation period based on the ozone adding optimization strategy, and reacquire the ozone adding control amount until the standard purification index requirement is met.

[0038] The concentration comprehensive module is configured to obtain real-time water quality data of the water body to be treated, including turbidity, organic matter concentration, algae content, odor substance concentration, water temperature and the like, and obtain comprehensive information of the pollutant concentration by weighted calculation based on the real-time water quality data, so as to quantify the overall pollution level of the water body. The historical compensation module is configured to construct a historical evaluation period, and obtain historical comprehensive information of the pollutant concentration in the period, and calculate a historical compensation value based on the historical data, so as to correct the current comprehensive information of the pollutant concentration, consider the time variation trend of the water pollution, and eliminate the influence of occasional fluctuations or data abnormalities. The historical compensation ensures that the ozone adding decision depends not only on real-time data, but also on the dynamic change characteristics of the water body. The ozone adding module is configured to calculate the ozone adding control amount required to reach the purification standard based on the comprehensive information of the pollutant concentration and the historical compensation, map the pollutant compensation value to the corresponding adding amount through a preset adding table, and execute the control, so as to ensure that the ozone adding is performed as needed, realize accurate purification, and the adding feedback module is configured to construct a feedback period, monitor the ozone adding effect after execution, obtain the comprehensive value of the pollutant concentration at the end node of the feedback period, compare it with the predicted value, calculate the comprehensive deviation of the pollutant concentration, match the adding optimization table according to the deviation, and generate the ozone adding optimization strategy, so as to provide a basis for the next adding amount adjustment. The adding iteration module is configured to reconstruct the historical evaluation period according to the ozone adding optimization strategy, update the historical compensation, and reacquire the ozone adding control amount. After multiple iterations, the system gradually corrects the adding amount until the water purification reaches the preset standard index, realizes closed-loop intelligent control, realizes dynamic adjustment of the ozone adding amount through the feedback and iteration mechanism, ensures that the purification effect is stable and meets the standard, realizes on-demand adding of the real-time pollutant concentration combined with the historical compensation, avoids over-addition or deficiency, improves the purification precision and reduces energy consumption and reagent waste, and the adding feedback and iteration module can quickly adjust the adding strategy according to the water quality change, so as to adapt to different pollution conditions and working condition changes.

[0039] In addition, an ozone adding intelligent control terminal based on water quality purification includes: One or more processors; A storage device having one or more programs stored thereon; When the one or more programs are executed by the one or more processors, the one or more processors implement the ozone adding intelligent control method based on water quality purification.

[0040] The above merely describes the preferred embodiments of the present application, and it should be pointed out that those skilled in the art can make several improvements and refinements without departing from the principles of the present application, and these improvements and refinements should also be considered as the protection scope of the present application. The structures, devices and operation methods not specifically described and explained in the present application are implemented according to the conventional means in the art, unless specifically described and limited.

Claims

1. An intelligent control method for ozone dosage based on water quality purification, characterized in that, The method comprises the following steps: obtaining real-time water quality data of the water body to be treated, and obtaining comprehensive information of pollutant concentration based on the water quality data; constructing a historical evaluation period based on the comprehensive information of pollutant concentration, obtaining historical comprehensive information of pollutant concentration in the historical evaluation period, and obtaining historical compensation based on the historical comprehensive information of pollutant concentration; obtaining an ozone dosage control amount of the water body to be treated based on the comprehensive information of pollutant concentration and the historical compensation, and executing the ozone dosage control amount; constructing a feedback period, obtaining the comprehensive information of pollutant concentration after executing the ozone dosage control amount based on the feedback period, obtaining a comprehensive deviation of pollutant concentration based on the comprehensive deviation of pollutant concentration, and obtaining an ozone dosage optimization strategy based on the comprehensive deviation of pollutant concentration; reconstructing the historical evaluation period based on the ozone dosage optimization strategy, and re-obtaining the ozone dosage control amount until the requirement of the standard purification index is met.

2. The method according to claim 1, wherein, The step of obtaining real-time water quality data of the water body to be treated and obtaining comprehensive information of pollutant concentration based on the water quality data comprises the following steps: obtaining real-time water quality data of the water body to be treated, wherein the water quality data comprises turbidity, organic matter concentration, algae content, odor substance concentration and water temperature; obtaining turbidity value, organic matter concentration value, algae content value, odor substance concentration value and water temperature value based on the water quality data; obtaining water quality weight, wherein the water quality weight comprises turbidity weight, organic matter weight, algae weight, odor weight and water temperature weight; obtaining comprehensive value of pollutant concentration based on the turbidity value, organic matter concentration value, algae content value, odor substance concentration value, water temperature value and water quality weight, and marking it as comprehensive information of pollutant concentration. 3.The method of claim 1, wherein, The step of constructing a historical evaluation period based on the comprehensive information of pollutant concentration, obtaining historical comprehensive information of pollutant concentration in the historical evaluation period, and obtaining historical compensation based on the historical comprehensive information of pollutant concentration comprises the following steps: constructing a historical evaluation period based on the comprehensive information of pollutant concentration; dividing the historical evaluation period into a plurality of historical evaluation data collection time points; obtaining historical comprehensive information of pollutant concentration in each historical evaluation data collection time point, and obtaining historical comprehensive value of pollutant concentration based on the historical comprehensive information of pollutant concentration; obtaining corresponding historical evaluation time length based on the historical evaluation period; obtaining historical pollutant change value based on a plurality of historical comprehensive values of pollutant concentration and the historical evaluation time length; obtaining a compensation table, wherein the compensation table comprises a plurality of historical pollutant change value intervals and historical compensation corresponding to each historical pollutant change value interval; obtaining corresponding historical compensation from the compensation table based on the historical pollutant change value corresponding to the historical pollutant change value interval.

4. The method according to claim 3, wherein, The step of constructing a historical evaluation period based on the comprehensive information of pollutant concentration comprises the following steps: obtaining comprehensive value of pollutant concentration based on the comprehensive information of pollutant concentration; obtaining a reference time length and a reference comprehensive value of pollutant concentration; obtaining a time length optimization table, wherein the time length optimization table comprises a plurality of pollutant concentration comprehensive value intervals and a time length optimization value corresponding to each pollutant concentration comprehensive value interval; obtaining corresponding time length optimization value from the time length optimization table based on the pollutant concentration comprehensive value corresponding to the pollutant concentration comprehensive value interval; obtaining historical evaluation time length based on the reference time length, the reference comprehensive value of pollutant concentration, the comprehensive value of pollutant concentration and the time length optimization value; An acquisition time node of the comprehensive information of the pollutant concentration is acquired, and is marked as an end time of the historical evaluation period; A start time is acquired based on the historical evaluation duration and the end time, and a historical evaluation period is constructed.

5. The method of claim 1, wherein the method is characterized by, An ozone dosage control amount required for the water body to be treated to meet the purification index requirement is acquired based on the comprehensive information of the pollutant concentration and the historical compensation, and the steps of execution include: A corresponding comprehensive value of the pollutant concentration is acquired based on the comprehensive information of the pollutant concentration; A pollutant compensation value is acquired based on the comprehensive value of the pollutant concentration and the historical compensation; An ozone dosage table is acquired, wherein the ozone dosage table includes a plurality of pollutant compensation value intervals and an ozone dosage control amount corresponding to each pollutant compensation value interval; The corresponding ozone dosage control amount is acquired from the ozone dosage table based on the pollutant compensation value interval corresponding to the pollutant compensation value, and the ozone dosage control amount is executed.

6. The method of claim 1, wherein the method is characterized by, A feedback period is constructed, the comprehensive information of the pollutant concentration after the ozone dosage control amount is executed is acquired based on the feedback period, and a comprehensive deviation of the pollutant concentration is acquired, and the steps of acquiring an ozone dosage optimization strategy based on the comprehensive deviation of the pollutant concentration include: The feedback period is acquired based on the ozone dosage control amount; An end node of the feedback period is acquired based on the feedback period, the comprehensive information of the pollutant concentration at the end node of the feedback period is acquired, and a corresponding comprehensive value of the pollutant concentration is extracted, which is marked as a post-control comprehensive value of the pollutant concentration; A predicted comprehensive value of the pollutant concentration is acquired based on the ozone dosage control amount; A comprehensive deviation of the pollutant concentration is acquired based on the post-control comprehensive value of the pollutant concentration and the predicted comprehensive value of the pollutant concentration; An optimization table of the dosage is acquired, wherein the optimization table of the dosage includes a plurality of pollutant concentration comprehensive deviation intervals and an ozone dosage optimization strategy corresponding to each pollutant concentration comprehensive deviation interval; The corresponding ozone dosage optimization strategy is acquired from the optimization table of the dosage based on the pollutant concentration comprehensive deviation interval corresponding to the pollutant concentration comprehensive deviation.

7. The method according to claim 6, wherein, The steps of acquiring the feedback period based on the ozone dosage control amount include: A time node of executing the ozone dosage control amount is acquired, and is marked as a start time of the feedback period; A plurality of ozone dosage control amounts in the historical evaluation period are acquired, and are respectively marked as historical ozone dosage control amounts; A reference feedback duration is acquired, A feedback duration is acquired based on the ozone dosage control amount, the plurality of historical ozone dosage control amounts and the reference feedback duration; An end time is acquired based on the feedback duration and the start time of the feedback period, and a feedback period is constructed. 8.The method of claim 1, wherein the method further comprises: determining a water quality index of the water quality based on the water quality data; and determining the ozone injection amount based on the water quality index. The steps of reconstructing the historical evaluation period based on the ozone dosage optimization strategy and re-acquiring the ozone dosage control amount until the purification index requirement is met include: An iteration duration table is acquired, wherein the iteration duration table includes a plurality of ozone dosage optimization strategies and an iteration historical evaluation duration corresponding to each ozone dosage optimization strategy; The corresponding iteration historical evaluation duration is acquired from the iteration duration table based on the ozone dosage optimization strategy; An acquisition time of the ozone dosage optimization strategy is acquired, and is marked as an end time of the iteration historical evaluation period; A start time is acquired based on the iteration historical evaluation duration and the end time of the iteration historical evaluation period, and an iteration historical evaluation period is constructed. The iteration history evaluation period is taken as a new history evaluation period, and a new history compensation is obtained according to the new history evaluation period; The pollutant concentration comprehensive information after executing the ozone adding control amount is returned to the step of obtaining the ozone adding control amount based on the pollutant concentration comprehensive information and the history compensation, and the ozone adding control amount is re-obtained until the standard purification index requirement is met.

9. An intelligent ozone dosing control system based on water purification, applied to the intelligent ozone dosing control method based on water purification in any one of claims 1 to 8, characterized in that, Comprise: A concentration comprehensive module is configured to obtain real-time water quality data of the water body to be treated, and obtain pollutant concentration comprehensive information based on the water quality data; A history compensation module is configured to construct a history evaluation period based on the pollutant concentration comprehensive information, obtain history pollutant concentration comprehensive information in the history evaluation period, and obtain a history compensation based on the history pollutant concentration comprehensive information; An ozone adding module is configured to obtain an ozone adding control amount based on the pollutant concentration comprehensive information and the history compensation, and execute the ozone adding control amount; A adding feedback module is configured to construct a feedback period, obtain pollutant concentration comprehensive information after executing the ozone adding control amount based on the feedback period, and obtain a pollutant concentration comprehensive deviation, and obtain an ozone adding optimization strategy based on the pollutant concentration comprehensive deviation; An adding iteration module is configured to re-construct a history evaluation period based on the ozone adding optimization strategy, and re-obtain an ozone adding control amount until the standard purification index requirement is met.

10. An ozone dosing intelligent regulation terminal based on water quality purification, characterized in that, Comprise: One or more processors; A storage device having one or more programs stored thereon; When the one or more programs are executed by the one or more processors, the one or more processors implement the ozone adding intelligent control method based on water quality purification according to any one of claims 1 to 8.

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