Sewage treatment control system and method based on mechanism model

Abstract

The invention relates to the technical field of sewage treatment, in particular to a sewage treatment control system and method based on a mechanism model. The server side comprises a real-time water inlet monitoring module, an abnormity judgment module, a comparison and selection circulation module, a control module, a water outlet monitoring module, a water outlet judgment module and a scheme updating module, and the water outlet judgment module is used for judging whether water outlet quality monitoring data meet a preset water quality value or not according to the water outlet quality monitoring data monitored in real time; and if yes, judging that the corresponding sewage treatment mechanism model is a feasible model, and if not, sequentially selecting a certain model parameter in the model parameter group in the sewage treatment mechanism model at the previous moment for correction and adjustment, and re-outputting corresponding effluent quality re-simulation data. And judging that the corresponding sewage treatment mechanism model is a feasible model until the effluent quality re-simulation data and the effluent quality monitoring data are within a preset simulation error.

Description

Technical Field

[0001] The present invention relates to the technical field of sewage treatment, and in particular to a sewage treatment control system and method based on a mechanism model. Background Art

[0002] With the acceleration of urbanization and the rapid development of industrial production, water shortage and water pollution are becoming increasingly serious. Wastewater treatment is an important part of ensuring water security and maintaining the ecological environment.

[0003] Traditional sewage treatment systems usually rely on fixed operating parameters and empirical rules, which can achieve good results under relatively stable treatment conditions. However, in actual operation, the influent water quality fluctuates greatly, and traditional methods are difficult to cope with such changes, resulting in unstable effluent water quality, which may even fail to meet the standards. In order to meet the standards, the aeration volume and dosage of the drug are increased, resulting in higher electricity and drug costs.

[0004] With the development of information technology, some sewage treatment facilities have begun to introduce automated control technology to improve treatment efficiency and stability. However, the existing automated control systems still have the following major problems:

[0005] When abnormal conditions occur in the inlet or outlet of a sewage treatment system, operators are often required to manually adjust process parameters based on experience. This is not only time-consuming and labor-intensive, but the consistency and accuracy of the adjustment results are difficult to guarantee.

[0006] Most existing control systems adopt fixed process solutions and lack the ability to continuously optimize process parameters. They are unable to find the optimal treatment solution for different influent conditions, resulting in poor reliability and adaptability of the corresponding control system when abnormal conditions occur in the influent or effluent of the sewage treatment system.

[0007] Based on this, there is an urgent need for a sewage treatment control system and method based on a mechanism model, which can automatically adjust the process parameters according to the changes in the water inlet conditions in the sewage treatment system and automatically take countermeasures when abnormalities occur in the effluent, so as to realize the automatic adjustment of the process parameters and response strategies in the sewage system, thereby improving the reliability and adaptability of the entire sewage treatment. Summary of the invention

[0008] One of the purposes of the present invention is to provide a sewage treatment control system and method based on a mechanism model, which can automatically adjust the process parameters according to the changes in the water inlet conditions in the sewage treatment system and automatically take countermeasures when abnormalities occur in the effluent, thereby realizing automatic adjustment of the process parameters and response strategies in the sewage system, thereby improving the reliability and adaptability of the entire sewage treatment.

[0009] In order to achieve the above-mentioned purpose, a sewage treatment control system based on a mechanism model is provided, including a service end;

[0010] The server includes:

[0011] Real-time water inflow monitoring module, used to monitor the water inflow data of the sewage treatment system in real time to form real-time water inflow data;

[0012] The abnormality judgment module is used to judge whether the real-time water inflow data corresponding to the current moment is abnormal based on the real-time water inflow data. If the judgment result is no, the real-time water inflow data at the current moment is judged to be accurate data, and the intermediate control parameters of the sewage treatment system at the previous moment are retrieved as the process control scheme corresponding to the sewage treatment system at the current moment;

[0013] The comparison cycle module is used to simulate the sewage treatment of the sewage treatment system based on the sewage treatment mechanism model at the previous moment according to the real-time water inflow data corresponding to the current moment and the process control scheme corresponding to the sewage treatment system at the current moment, and output the corresponding effluent water quality simulation data, and judge whether the corresponding effluent water quality meets the preset requirements according to the effluent water quality simulation data. If so, it is judged that the process control scheme corresponding to the sewage treatment system at the current moment is a feasible scheme; if not, the various intermediate control parameters in the process control scheme corresponding to the sewage treatment system at the current moment are adjusted and re-input into the sewage treatment mechanism model at the previous moment;

[0014] A control module, for calculating the control parameters of the control equipment corresponding to each intermediate control parameter in the process control scheme according to each intermediate control parameter in the process control scheme corresponding to the current moment when the result of the judgment is that the process control scheme corresponding to the sewage treatment system at the current moment is a feasible scheme, and controlling each control equipment in the sewage treatment system;

[0015] The effluent monitoring module is used to monitor the effluent water quality monitoring data of the sewage treatment system in real time when controlling various control devices in the sewage treatment system;

[0016] The effluent judgment module is used to judge whether the effluent water quality monitoring data meets the preset water quality value according to the effluent water quality monitoring data monitored in real time; if so, the corresponding sewage treatment mechanism model is judged to be a feasible model; if not, one of the model parameters in the model parameter group of the sewage treatment mechanism model at the previous moment is selected in turn for correction and adjustment, and the corresponding effluent water quality re-simulation data is re-output until the effluent water quality re-simulation data and the effluent water quality monitoring data are within the preset simulation error, at which time the corresponding sewage treatment mechanism model is judged to be a feasible model;

[0017] The model updating module is used to update the sewage treatment mechanism model at the previous moment according to the corrected and adjusted model parameters when the judgment result shows that the corresponding sewage treatment mechanism model is a feasible model.

[0018] Technical principle and effect of this scheme: In this scheme, first, the influent data of the sewage treatment system is monitored in real time, and the real-time influent data is used to judge whether there is any abnormality in the influent data at the current moment. When there is no abnormality, the intermediate control parameters corresponding to the sewage treatment system at the previous moment will be retrieved as the process control scheme of the corresponding sewage treatment system at the current moment. Then, the process control scheme at the current moment and the real-time influent data are used to simulate the sewage treatment corresponding to the sewage treatment system through the sewage treatment mechanism model at the previous moment to obtain the effluent water quality simulation data. Then, it is determined whether the effluent water quality simulation data meets the preset requirements to determine whether the effluent water quality simulation data meets the standards. If not, the corresponding intermediate control parameters of the process control scheme will be adjusted, and then re-input into the sewage treatment mechanism model at the previous moment for another simulation. Through repeated adjustments for multiple cycles, a process control scheme that meets the requirements is obtained.

[0019] Afterwards, the control parameters of the control equipment of the corresponding intermediate control parameters are calculated through the various intermediate control parameters in the process control scheme corresponding to the sewage treatment system at the current moment, so as to control the various control equipment in the sewage treatment system, thereby realizing the treatment of sewage in the sewage treatment system at the current moment.

[0020] In the process of sewage treatment, the effluent water quality monitoring data of the sewage treatment system is monitored in real time, and the effluent water quality of the sewage treatment system is monitored through the effluent water quality monitoring data. Once it is determined that the effluent water quality monitoring data does not meet the preset water quality value, one of the model parameters in the model parameter group in the sewage treatment mechanism model at the previous moment is selected in turn for correction and adjustment, and the corresponding effluent water quality re-simulation data is re-output until the effluent water quality re-simulation data and the effluent water quality monitoring data are within the preset simulation error. At this time, the corresponding sewage treatment mechanism model is judged to be a feasible model; thereby realizing the judgment of whether the sewage treatment mechanism model at the previous moment is suitable for the requirements of the current moment, and then realizing the update and correction of the sewage treatment mechanism model at the previous moment, so that the corresponding sewage treatment system can better treat the influent data at the current moment, so that the effluent water quality data of the sewage treatment system meets the preset water quality value.

[0021] In this solution, through the real-time water inlet monitoring module and the abnormal judgment module, the system can quickly identify the changes in the water inlet data and realize the accurate recognition of the water inlet data. After that, the process control scheme of the previous moment and the sewage treatment mechanism model of the previous moment are used to simulate the effluent water quality as soon as possible, so as to judge whether the corresponding process control scheme of the previous moment meets the sewage treatment requirements of the current moment, and if it does not meet the requirements, the various intermediate control parameters in the process control scheme corresponding to the sewage treatment system of the previous moment are adjusted. Through the preliminary adjustment of the intermediate control parameters, the various intermediate control parameters in the corresponding process control scheme are closer to the current effluent requirements, and the preliminary satisfaction of the process control scheme is achieved. Through this preliminary adjustment, the system reduces the unnecessary use of chemicals and reduces operating costs. Improve the treatment efficiency, reduce the residence time of sewage in the treatment unit, and speed up the overall treatment speed.

[0022] Afterwards, the process control scheme that preliminarily meets the requirements is adopted to control the various control devices of the corresponding sewage treatment system to achieve the corresponding preliminary sewage treatment, and the effluent water quality monitoring data is monitored in real time to further judge whether the process control scheme that preliminarily meets the requirements actually meets the requirements. Once the effluent water quality monitoring data does not meet the preset water quality value, one of the model parameters in the model parameter group in the sewage treatment mechanism model at the previous moment will be selected in turn for correction and adjustment, and the corresponding effluent water quality re-simulation data will be re-output until the effluent water quality re-simulation data and the effluent water quality monitoring data are within the preset simulation error. At this time, the corresponding sewage treatment mechanism model is judged to be a feasible model; then when the judgment result is that the corresponding sewage treatment mechanism model is a feasible model, the sewage treatment mechanism model at the previous moment is updated according to the corrected and adjusted model parameters.

[0023] On the basis of the first adjustment, the system again adjusted the model parameters of the sewage treatment mechanism model at the previous moment. Through this adjustment, the system finally made the effluent water quality fully meet the preset standards and ensured stable effluent quality. For example, the system may further optimize the dissolved oxygen concentration to minimize the pollutant content in the effluent. Through two consecutive parameter adjustments, the system not only achieved the expected effluent water quality standards, but also showed higher stability and reliability under different working conditions. The system can automatically adapt to changes in the influent water quality and continuously optimize through a closed-loop feedback mechanism to ensure long-term stable operation, that is, it can realize the rapid and accurate automatic adjustment of the corresponding process parameters when abnormal conditions occur in the influent or effluent of the sewage treatment system, thereby improving the reliability and adaptability of the entire sewage treatment. That is, according to the changes in the influent conditions in the sewage treatment system, the process parameters are automatically adjusted, and countermeasures are automatically taken when abnormalities occur in the effluent, and the process parameters and countermeasures in the sewage system are automatically adjusted, thereby improving the reliability and adaptability of the entire sewage treatment.

[0024] Furthermore, the abnormality judgment module is also used to correct the real-time water inflow data monitored at the current moment when the judgment result is yes, and judge that the corrected real-time water inflow data is accurate data, and retrieve the intermediate control parameters of the sewage treatment system at the previous moment as the process control scheme corresponding to the sewage treatment system at the current moment;

[0025] It also includes a data cleaning module, which is used to clean the monitored real-time water inflow data when it is determined that the real-time water inflow data monitored at the current moment is accurate data.

[0026] Beneficial effects: In this solution, when the monitored data is judged to be abnormal, the system will automatically correct it to ensure that subsequent processing is based on accurate data, avoiding decision-making errors caused by erroneous data. The corrected data will be re-evaluated for its accuracy. This step ensures that only verified data will be used in actual operations, improving the reliability of the overall system.

[0027] By cleaning the real-time water inflow data monitored in real time, it is ensured that the real-time water inflow data can meet the format required by the corresponding model, thereby improving the reliability of the data.

[0028] Furthermore, the server also includes:

[0029] The aerobic tank control module is used to monitor the DO value of the aerobic tank in the sewage treatment system when controlling various control devices in the sewage treatment system, and to determine whether the corresponding DO value meets the preset DO value. If not, based on the preset oxygen demand correction model, the oxygen demand parameters in the various intermediate control parameters in the process control scheme calculated in the control module are corrected.

[0030] Beneficial effects: By correcting the oxygen demand parameters based on the preset oxygen demand correction model, the system can more accurately control the working state of the aeration equipment. This not only avoids energy waste caused by excessive aeration, but also reduces the decline in treatment efficiency caused by insufficient aeration, and can ensure that the treatment process in the aerobic pool is always in the best state, thereby improving the stability of the effluent water quality.

[0031] Furthermore, the water outlet judgment module includes:

[0032] A first retrieval module is used to retrieve the historical effluent water quality monitoring data corresponding to the previous moment and the previous moment from the historical database after obtaining the effluent water quality monitoring data corresponding to the current moment, as well as the historical water inlet data corresponding to the effluent water quality monitoring data at the current moment and the historical effluent water quality monitoring data;

[0033] The error calculation module is used to calculate the prediction error value of the sewage treatment mechanism model corresponding to the current moment according to the effluent water quality monitoring data at the current moment, the historical effluent water quality monitoring data corresponding to the previous moment and the previous moment, and the effluent water quality simulation data corresponding to each moment, and judge whether the corresponding prediction error value is greater than the preset error threshold value. If so, it is judged that the sewage treatment mechanism model at the previous moment needs to be adjusted, otherwise it does not need to be adjusted;

[0034] A sorting module is used to identify the adjustment sensitivity of each model parameter in the model parameter group corresponding to the sewage treatment mechanism model at the previous moment when the judgment result is that the sewage treatment mechanism model at the previous moment needs to be adjusted, and sort them in order from large to small in adjustment sensitivity to form a sensitivity sorting table;

[0035] A selection module is used to select the model parameter with the highest adjustment sensitivity according to the sensitivity ranking table;

[0036] The correction and adjustment module is used to correct and adjust the model parameters based on the preset adjustment amount after selecting the corresponding intermediate control parameters. After the correction is completed, the sewage treatment mechanism model corresponding to the previous moment is updated, and the historical water inlet data corresponding to the effluent monitoring data corresponding to the current moment and the process control scheme corresponding to the sewage treatment system at the current moment are re-input as input data into the updated sewage treatment mechanism model corresponding to the previous moment, and the corresponding effluent water quality re-simulation data is output;

[0037] The iterative cycle module is used to determine whether the simulation error between the effluent water quality re-simulation data and the effluent water quality monitoring data is less than the preset simulation error. If so, the corresponding sewage treatment mechanism model is a feasible model;

[0038] If not, select the next model parameter with the highest adjustment sensitivity and repeat the correction and adjustment module until the effluent water quality re-simulation data and the effluent water quality monitoring data are within the preset simulation error. At this time, the corresponding sewage treatment mechanism model is judged to be a feasible model.

[0039] Beneficial effect: In this scheme, the effluent water quality monitoring data corresponding to the current moment, the previous moment and the previous moment are combined with the effluent water quality simulation data corresponding to each moment and the historical water inlet data to realize the calculation of the prediction error value of the corresponding sewage treatment mechanism model at the previous moment, thereby realizing a reliable and accurate evaluation of the feasibility of the corresponding sewage treatment mechanism model at the previous moment.

[0040] The adjustment sensitivity of the model parameters is identified and sorted in descending order of sensitivity. This method ensures that the model parameters that have the greatest impact on the effluent water quality are adjusted first, thereby optimizing the sewage treatment mechanism model more efficiently. The selection module and the correction adjustment module gradually correct and adjust the model parameters according to the sensitivity ranking table. This step-by-step optimization method can avoid system instability caused by adjusting too many parameters at one time, while ensuring that each adjustment can bring significant improvements. The iterative cycle module ensures that the system will stop adjusting only when the effluent water quality correction simulation data meets the preset water quality value. This closed-loop control mechanism ensures that the effluent water quality always meets the standard and reduces fluctuations.

[0041] Furthermore, the intermediate control parameters include gas volume parameters, DO values, oxygen demand parameters, internal reflow ratio parameters, external reflow ratio parameters, sludge discharge volume parameters and drug dosage parameters corresponding to the sewage treatment system.

[0042] The present invention also provides a sewage treatment control method based on a mechanism model, using the above-mentioned sewage treatment control system based on a mechanism model. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Figure 1 This is a logic block diagram of a sewage treatment control system based on a mechanism model in Embodiment 1 of the present invention. DETAILED DESCRIPTION

[0044] The following is further described in detail through specific implementation methods:

[0045] Embodiment 1

[0046] The sewage treatment control system based on the mechanism model is basically as follows Figure 1 As shown, including the server;

[0047] The server includes:

[0048] Real-time water inflow monitoring module, used to monitor the water inflow data of the sewage treatment system in real time to form real-time water inflow data;

[0049] The abnormality judgment module is used to judge whether the real-time water inflow data corresponding to the current moment is abnormal based on the real-time water inflow data. If the judgment result is no, the real-time water inflow data at the current moment is judged to be accurate data, and the intermediate control parameters of the sewage treatment system at the previous moment are retrieved as the process control scheme corresponding to the sewage treatment system at the current moment;

[0050] The abnormal judgment module is also used to correct the real-time water inflow data monitored at the current moment when the judgment result is yes, and judge that the corrected real-time water inflow data is accurate data, and retrieve the intermediate control parameters of the sewage treatment system at the previous moment as the process control scheme corresponding to the sewage treatment system at the current moment. In this embodiment, when correcting the intermediate control parameters corresponding to the sewage treatment system at the previous moment, combined with the real-time water inflow data at the current moment, the corresponding parameter correction is achieved through the operator's parameter adjustment experience. For example, if a certain content in one of the real-time water inflow data is relatively high, then the operator can know from experience that the corresponding adjustment of a certain intermediate control parameter can reduce the corresponding content. Of course, the system can also automatically adjust, for example, according to the change trend of the first two groups of data, 1 / 2 correction, such as the first two groups are 20, 24, then this group of abnormal data is corrected to 24+1 / 2*(24-20)=26, and the same applies to the trend of reduction. In this embodiment, the intermediate control parameters include gas volume parameters, DO value, oxygen demand parameters, internal reflow ratio parameters, external reflow ratio parameters, sludge discharge volume parameters, flow parameters and dosage parameters corresponding to the sewage treatment system.

[0051] It also includes a data cleaning module, which is used to clean the real-time inlet water data monitored at the current moment when it is determined that the real-time inlet water data monitored at the current moment is accurate data. Ensure that the inlet water monitoring data enters the model in the format required by the algorithm. This step includes the parameters of the inlet water component distribution ratio (the percentage of each component). The sewage treatment plant with relatively complete inlet water online monitoring mainly monitors: COD / TN / TP / SS / NH4. The model needs to clean these data before use, and the ratio needs to be dynamically calibrated.

[0052] The comparison cycle module is used to simulate the sewage treatment of the sewage treatment system based on the sewage treatment mechanism model of the previous moment according to the real-time water inlet data corresponding to the current moment and the process control scheme corresponding to the sewage treatment system at the current moment, and output the corresponding effluent water quality simulation data, and judge whether the corresponding effluent water quality meets the preset requirements according to the effluent water quality simulation data. If so, it is judged that the process control scheme corresponding to the sewage treatment system at the current moment is a feasible scheme; if not, the various intermediate control parameters in the process control scheme corresponding to the sewage treatment system at the current moment are adjusted and re-input into the sewage treatment mechanism model of the previous moment; in this embodiment, the corresponding adjustment of the various intermediate control parameters in the process control scheme corresponding to the sewage treatment system at the current moment is to adopt a preset comparison parameter adjustment model, and the comparison parameter adjustment model is constructed using the existing random forest algorithm.

[0053] A control module, for calculating the control parameters of the control equipment corresponding to each intermediate control parameter in the process control scheme according to each intermediate control parameter in the process control scheme corresponding to the current moment when the result of the judgment is that the process control scheme corresponding to the sewage treatment system at the current moment is a feasible scheme, and controlling each control equipment in the sewage treatment system;

[0054] The effluent monitoring module is used to monitor the effluent water quality monitoring data of the sewage treatment system in real time when controlling various control devices in the sewage treatment system;

[0055] The effluent judgment module is used to judge whether the effluent water quality monitoring data meets the preset water quality value according to the effluent water quality monitoring data monitored in real time; if so, the corresponding sewage treatment mechanism model is judged to be a feasible model; if not, one of the model parameters in the model parameter group of the sewage treatment mechanism model at the previous moment is selected in turn for correction and adjustment, and the corresponding effluent water quality re-simulation data is re-output until the effluent water quality re-simulation data and the effluent water quality monitoring data are within the preset simulation error, at which time the corresponding sewage treatment mechanism model is judged to be a feasible model;

[0056] The water outlet judgment module comprises:

[0057] A first retrieval module is used to retrieve the historical effluent water quality monitoring data corresponding to the previous moment and the previous moment from the historical database after obtaining the effluent water quality monitoring data corresponding to the current moment, as well as the historical water inlet data corresponding to the effluent water quality monitoring data at the current moment and the historical effluent water quality monitoring data;

[0058] The error calculation module is used to calculate the prediction error value of the sewage treatment mechanism model corresponding to the current moment according to the effluent water quality monitoring data at the current moment, the historical effluent water quality monitoring data corresponding to the previous moment and the previous moment, and the effluent water quality simulation data corresponding to each moment, and judge whether the corresponding prediction error value is greater than the preset error threshold value. If so, it is judged that the sewage treatment mechanism model at the previous moment needs to be adjusted, otherwise it does not need to be adjusted;

[0059] In this embodiment, the prediction error value calculation formula is:

[0060]

[0061] Where W is the prediction error value, y t is the effluent water quality monitoring data at the current time t, is the simulated data of the outlet water quality at the current moment t, w1, w2, w3 are the corresponding dynamically changing weight values. The greater the outlet water quality error corresponding to the current moment, the greater the corresponding weight value.

[0062] A sorting module is used to identify the adjustment sensitivity of each model parameter in the model parameter group corresponding to the sewage treatment mechanism model at the previous moment when the judgment result is that the sewage treatment mechanism model at the previous moment needs to be adjusted, and sort them in order from large to small in adjustment sensitivity to form a sensitivity sorting table;

[0063] The selection module is used to select the model parameters with the highest adjustment sensitivity according to the sensitivity ranking table; in this embodiment, the corresponding model parameters include the kinetic parameters and stoichiometric parameters of the mechanism model itself. These parameters change with the ambient temperature, season, and microbial growth conditions and need to be calibrated.

[0064] The correction and adjustment module is used to correct and adjust the model parameters based on the preset adjustment amount after selecting the corresponding intermediate control parameters. After the correction is completed, the sewage treatment mechanism model corresponding to the previous moment is updated, and the historical water inlet data corresponding to the effluent monitoring data corresponding to the current moment and the process control scheme corresponding to the sewage treatment system at the current moment are re-input as input data into the updated sewage treatment mechanism model corresponding to the previous moment, and the corresponding effluent water quality re-simulation data is output;

[0065] The iterative cycle module is used to determine whether the simulation error between the effluent water quality re-simulation data and the effluent water quality monitoring data is less than the preset simulation error. If so, the corresponding sewage treatment mechanism model is a feasible model;

[0066] If not, select the next model parameter with the highest adjustment sensitivity and repeat the correction and adjustment module until the effluent water quality re-simulation data and the effluent water quality monitoring data are within the preset simulation error. At this time, the corresponding sewage treatment mechanism model is judged to be a feasible model.

[0067] The model updating module is used to update the sewage treatment mechanism model at the previous moment according to the corrected and adjusted model parameters when the judgment result shows that the corresponding sewage treatment mechanism model is a feasible model.

[0068] The server also includes:

[0069] The aerobic tank control module is used to monitor the DO value of the aerobic tank in the sewage treatment system when controlling each control device in the sewage treatment system, and determine whether the corresponding DO value meets the preset DO value. If not, based on the preset oxygen demand correction model, the oxygen demand parameters in each intermediate control parameter in the process control scheme calculated in the control module are corrected. In this embodiment, the oxygen demand correction model is also constructed using the existing random forest algorithm. According to the corresponding DO value, the required air volume is calculated and converted into the final operating frequency of the fan equipment. After executing the control parameter, whether the executed control parameter needs to be further adjusted according to the data feedback of the aerobic tank DO electrode.

[0070] This embodiment also discloses a sewage treatment control method based on a mechanism model, using the above-mentioned sewage treatment control system based on a mechanism model.

[0071] The above is only an embodiment of the present invention. The common sense such as the known specific structure and characteristics in the scheme will not be described in detail here. The ordinary technicians in the relevant field know all the common technical knowledge in the technical field to which the invention belongs before the application date or the priority date, can obtain all the existing technologies in the field, and have the ability to apply the conventional experimental means before that date. The ordinary technicians in the relevant field can improve and implement this scheme in combination with their own abilities under the enlightenment given by this application. Some typical known structures or known methods should not become obstacles for the ordinary technicians in the relevant field to implement this application. It should be pointed out that for the technicians in this field, without departing from the structure of the present invention, several deformations and improvements can be made, which should also be regarded as the protection scope of the present invention, which will not affect the effect of the implementation of the present invention and the practicality of the patent. The protection scope required by this application shall be based on the content of its claims, and the specific implementation methods and other records in the specification can be used to explain the content of the claims.

Claims

1. The sewage treatment control system based on the mechanism model is characterized by: Including the server side; The server includes: Real-time water inflow monitoring module, used to monitor the water inflow data of the sewage treatment system in real time to form real-time water inflow data; The abnormality judgment module is used to judge whether the real-time water inflow data corresponding to the current moment is abnormal based on the real-time water inflow data. If the judgment result is no, the real-time water inflow data at the current moment is judged to be accurate data, and the intermediate control parameters of the sewage treatment system at the previous moment are retrieved as the process control scheme corresponding to the sewage treatment system at the current moment; The comparison cycle module is used to simulate the sewage treatment of the sewage treatment system based on the sewage treatment mechanism model at the previous moment according to the real-time water inflow data corresponding to the current moment and the process control scheme corresponding to the sewage treatment system at the current moment, and output the corresponding effluent water quality simulation data, and judge whether the corresponding effluent water quality meets the preset requirements according to the effluent water quality simulation data. If so, it is judged that the process control scheme corresponding to the sewage treatment system at the current moment is a feasible scheme; if not, the various intermediate control parameters in the process control scheme corresponding to the sewage treatment system at the current moment are adjusted and re-input into the sewage treatment mechanism model at the previous moment; A control module, for calculating the control parameters of the control equipment corresponding to each intermediate control parameter in the process control scheme according to each intermediate control parameter in the process control scheme corresponding to the current moment when the result of the judgment is that the process control scheme corresponding to the sewage treatment system at the current moment is a feasible scheme, and controlling each control equipment in the sewage treatment system; The effluent monitoring module is used to monitor the effluent water quality monitoring data of the sewage treatment system in real time when controlling various control devices in the sewage treatment system; The effluent judgment module is used to judge whether the effluent water quality monitoring data meets the preset water quality value according to the effluent water quality monitoring data monitored in real time; if so, the corresponding sewage treatment mechanism model is judged to be a feasible model; if not, one of the model parameters in the model parameter group of the sewage treatment mechanism model at the previous moment is selected in turn for correction and adjustment, and the corresponding effluent water quality re-simulation data is re-output until the effluent water quality re-simulation data and the effluent water quality monitoring data are within the preset simulation error, at which time the corresponding sewage treatment mechanism model is judged to be a feasible model; The model updating module is used to update the sewage treatment mechanism model at the previous moment according to the corrected and adjusted model parameters when the judgment result is that the corresponding sewage treatment mechanism model is a feasible model.

2. The sewage treatment control system based on the mechanism model according to claim 1 is characterized by: The abnormality judgment module is also used to correct the real-time water inflow data monitored at the current moment if the judgment result is yes, and judge that the corrected real-time water inflow data is accurate data, and retrieve the intermediate control parameters of the sewage treatment system at the previous moment as the process control scheme corresponding to the sewage treatment system at the current moment; It also includes a data cleaning module, which is used to clean the monitored real-time water inflow data when it is determined that the real-time water inflow data monitored at the current moment is accurate data.

3. The sewage treatment control system based on the mechanism model according to claim 2 is characterized in that: The server also includes: The aerobic tank control module is used to monitor the DO value of the aerobic tank in the sewage treatment system when controlling various control devices in the sewage treatment system, and to determine whether the corresponding DO value meets the preset DO value. If not, based on the preset oxygen demand correction model, the oxygen demand parameters in the various intermediate control parameters in the process control scheme calculated in the control module are corrected.

4. The sewage treatment control system based on the mechanism model according to claim 3 is characterized by: The water outlet judgment module comprises: A first retrieval module is used to retrieve the historical effluent water quality monitoring data corresponding to the previous moment and the previous moment from the historical database after obtaining the effluent water quality monitoring data corresponding to the current moment, as well as the historical water inlet data corresponding to the effluent water quality monitoring data at the current moment and the historical effluent water quality monitoring data; The error calculation module is used to calculate the prediction error value of the sewage treatment mechanism model corresponding to the current moment according to the effluent water quality monitoring data at the current moment, the historical effluent water quality monitoring data corresponding to the previous moment and the previous moment, and the effluent water quality simulation data corresponding to each moment, and judge whether the corresponding prediction error value is greater than the preset error threshold value. If so, it is judged that the sewage treatment mechanism model at the previous moment needs to be adjusted, otherwise it does not need to be adjusted; A sorting module is used to identify the adjustment sensitivity of each model parameter in the model parameter group corresponding to the sewage treatment mechanism model at the previous moment when the judgment result is that the sewage treatment mechanism model at the previous moment needs to be adjusted, and sort them in order from large to small in adjustment sensitivity to form a sensitivity sorting table; A selection module is used to select the model parameter with the highest adjustment sensitivity according to the sensitivity ranking table; The correction and adjustment module is used to correct and adjust the model parameters based on the preset adjustment amount after selecting the corresponding intermediate control parameters. After the correction is completed, the sewage treatment mechanism model corresponding to the previous moment is updated, and the historical water inlet data corresponding to the effluent monitoring data corresponding to the current moment and the process control scheme corresponding to the sewage treatment system at the current moment are re-input as input data into the updated sewage treatment mechanism model corresponding to the previous moment, and the corresponding effluent water quality re-simulation data is output; The iterative cycle module is used to determine whether the simulation error between the effluent water quality re-simulation data and the effluent water quality monitoring data is less than the preset simulation error. If so, the corresponding sewage treatment mechanism model is a feasible model; If not, select the next model parameter with the highest adjustment sensitivity and repeat the correction and adjustment module until the effluent water quality re-simulation data and the effluent water quality monitoring data are within the preset simulation error. At this time, the corresponding sewage treatment mechanism model is judged to be a feasible model.

5. The sewage treatment control system based on the mechanism model according to claim 4 is characterized in that: The intermediate control parameters include gas volume parameters, DO values, oxygen demand parameters, internal reflow ratio parameters, external reflow ratio parameters, sludge discharge volume parameters and drug dosage parameters corresponding to the sewage treatment system.

6. The sewage treatment control method based on the mechanism model is characterized by: A sewage treatment control system based on a mechanism model using any one of claims 1 to 5 above.

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