Industrial wastewater treatment control method and system based on digital twin

Abstract

The present invention relates to the technical field of wastewater treatment control, and provides an industrial wastewater treatment control method and system based on digital twins. The method comprises: constructing a digital twin of a wastewater treatment pool structure, establishing a flow model of the digital twin as a whole with wastewater flow data monitored by various water flow sensors in the treatment pool, and being able to map in real time the time required for wastewater to flow between any two points in the treatment pool; then establishing a relationship between wastewater component changes and flow conditions in the digital twin based on the flow model with wastewater component detection probe positions and component detection data; substituting real-time data acquired by sensors at a water inlet or a middle section of a wastewater treatment pool into a trained digital twin, and being able to predict the wastewater component at a water outlet, and judging whether the discharge standard is met, and regulating the treatment system with empirical values ​​according to component differences, and being able to perform immediate regulation based on the industrial wastewater component input into the treatment pool, thereby improving treatment efficiency and reducing waste of treatment resources.

Description

Technical Field

[0001] The present invention relates to the technical field of wastewater treatment control, and in particular to an industrial wastewater treatment control method and system based on digital twins. Background Art

[0002] Industrial wastewater may contain heavy metals, compounds or organic matter, which require chemical or biological treatment. Industrial wastewater can only be discharged after being fully treated with chemicals or microorganisms. The process of industrial wastewater entering the outflow treatment pool is wastewater treatment, and the treatment process of industrial wastewater requires experienced wastewater engineers to operate, control the treatment time of industrial wastewater and the dosage of chemical agents or microbial concentrations used to treat the wastewater, ensure that the content of industrial wastewater components meets the standards, and that too many agents, too concentrated microorganisms or too long treatment will lead to over-treatment, increase treatment costs and cause waste of resources. In addition, the treatment is mostly based on the component data at the outlet, and the treatment has a lag, which affects the efficiency of industrial wastewater treatment. Summary of the invention

[0003] The present invention provides an industrial wastewater treatment control method based on digital twin, which is used to solve the problem of low efficiency of industrial wastewater treatment in the prior art.

[0004] The first aspect of the present invention provides an industrial wastewater treatment control method based on digital twin, comprising:

[0005] Obtain the structural model of the industrial wastewater treatment pool and establish the corresponding digital twin based on the structural model; obtain the setting position of each monitoring sensor and the corresponding wastewater flow historical data, and build an overall flow model in the digital twin based on the positional relationship between the monitoring sensors and the wastewater flow historical data.

[0006] Obtain the setting position of the wastewater component detection probe and the historical data of wastewater component detection, and identify the wastewater flow situation corresponding to the probe setting position at the time of the wastewater component detection historical data; based on the positional relationship between the component detection probes, establish the wastewater treatment association relationship between the component detection probes in the digital twin according to the component detection historical data and the wastewater flow situation; then establish the overall wastewater treatment relationship model based on the overall flow model and the wastewater treatment association relationship between points;

[0007] Real-time data on wastewater composition and wastewater flow are obtained and substituted into the digital twin to obtain the predicted value of wastewater composition at the outlet of the treatment pool. The wastewater treatment equipment is controlled based on the difference between the standard value of wastewater composition and the predicted value of wastewater composition.

[0008] Optionally, after obtaining the setting position of the wastewater component detection probe and the wastewater component detection historical data, the method further includes:

[0009] Obtain the historical data of the control parameters of the wastewater treatment system, and supplement the wastewater treatment association relationship with the historical data of the control parameters based on time association.

[0010] Optionally, after controlling the wastewater treatment equipment according to the difference between the standard value of the wastewater component and the predicted value of the wastewater component, the method further includes:

[0011] Obtain real-time data on wastewater composition at the outlet of the treatment pool, compare the predicted value with the real-time data, and modify the wastewater treatment relationship model in the digital twin based on the difference.

[0012] The second aspect of the present application provides an industrial wastewater treatment control system based on digital twins, including:

[0013] The digital twin construction module is used to obtain the structural model of the industrial wastewater treatment pool and establish the corresponding digital twin based on the structural model; obtain the setting position of each monitoring sensor and the corresponding wastewater flow historical data, and build an overall flow model in the digital twin based on the positional relationship between the monitoring sensors and the wastewater flow historical data.

[0014] The processing relationship training module is used to obtain the setting position of the wastewater component detection probe and the historical data of wastewater component detection, and identify the wastewater flow situation corresponding to the probe setting position at the time of the wastewater component detection historical data; based on the positional relationship between the component detection probes, the wastewater treatment association relationship between the component detection probes is established in the digital twin according to the component detection historical data and the wastewater flow situation; and then the overall wastewater treatment relationship model is established based on the overall flow model and the wastewater treatment association relationship between the points;

[0015] The wastewater treatment control module is used to obtain real-time data on wastewater composition and wastewater flow, and substitute them into the digital twin to obtain the predicted value of wastewater composition at the outlet of the treatment pool, and control the wastewater treatment equipment according to the difference between the standard value of wastewater composition and the predicted value of wastewater composition.

[0016] Optionally, in the processing relationship training module, after obtaining the setting position of the wastewater component detection probe and the wastewater component detection historical data, it also includes:

[0017] Obtain the historical data of the control parameters of the wastewater treatment system, and supplement the wastewater treatment association relationship with the historical data of the control parameters based on time association.

[0018] Optionally, in the wastewater treatment control module, after controlling the wastewater treatment equipment according to the difference between the standard value of the wastewater component and the predicted value of the wastewater component, the module further includes:

[0019] Obtain real-time data on wastewater composition at the outlet of the treatment pool, compare the predicted value with the real-time data, and modify the wastewater treatment relationship model in the digital twin based on the difference.

[0020] The third aspect of the present application provides an industrial wastewater treatment control method device based on digital twins, the device comprising a processor and a memory:

[0021] The memory is used to store program codes and transmit the program codes to the processor;

[0022] The processor is used to execute an industrial wastewater treatment control method based on digital twins as described in any one of the first aspects of the present invention according to the instructions in the program code.

[0023] The fourth aspect of the present application provides a computer-readable storage medium, which is used to store program code, and the program code is used to execute an industrial wastewater treatment control method based on digital twins as described in any one of the first aspects of the present invention.

[0024] It can be seen from the above technical scheme that the present invention has the following advantages: a digital twin is constructed through the structure of a wastewater treatment pool, and the wastewater flow data monitored by each water flow sensor in the treatment pool is used to establish the overall flow model of the digital twin, which can map the time required for the wastewater to flow through any two points in the treatment pool in real time; then based on the flow model, the position of the wastewater component detection probe and the component detection data are used to establish the relationship between the change in wastewater composition and the flow conditions in the digital twin; the real-time data obtained by the sensor at the water inlet or the middle section of the wastewater treatment pool is substituted into the trained digital twin, which can predict the wastewater composition at the outlet, determine whether it meets the discharge standard, and regulate the treatment system according to the empirical value based on the component difference, which can be based on the input treatment pool. The industrial wastewater composition can be immediately regulated to improve the treatment efficiency and reduce the waste of treatment resources. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0026] Figure 1 It is a flow chart of an industrial wastewater treatment control method based on digital twin;

[0027] Figure 2 This is a structural diagram of an industrial wastewater treatment control system based on digital twins. DETAILED DESCRIPTION

[0028] In order to make the purpose, features and advantages of the present invention more obvious and easy to understand, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the embodiments described below are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0029] The present invention provides an industrial wastewater treatment control method based on digital twin, which is used to solve the problem of low efficiency of industrial wastewater treatment in the prior art.

[0030] See also Figure 1 , Figure 1 The first flow chart of an industrial wastewater treatment control method based on digital twin is provided in an embodiment of the present invention.

[0031] S100, obtain the structural model of the industrial wastewater treatment pool, and establish a corresponding digital twin based on the structural model; obtain the setting position of each monitoring sensor and the corresponding wastewater flow historical data, and build an overall flow model in the digital twin based on the positional relationship between the monitoring sensors and the wastewater flow historical data.

[0032] It should be noted that there are multiple treatment pools in the wastewater treatment system, and the treatment pools correspond to different wastewater treatment stages. Different types of treatment pools have different structures. The corresponding digital twin can be constructed based on the data and three-dimensional model of the wastewater treatment pool when it is designed and constructed, and the actual positions of various sensors are set accordingly in the digital twin. The established digital twin of the wastewater treatment system can reflect the structural properties of the system and present the wastewater treatment data at the sensor in real time.

[0033] In the wastewater treatment system, an online wastewater monitoring system will be set up. Various sensors will be used to monitor the flow at the water inlet and outlet to determine the load conditions in the treatment pool for adjustment. During the wastewater treatment process, the wastewater flows in the treatment pool. In the process of chemical treatment and biological treatment, the wastewater needs to be mixed with chemicals and microorganisms. The wastewater treatment effect from the water inlet to the water outlet will vary with the mixing conditions. The flow sensor set in the treatment pool can be equipped with direction detection elements such as a compass to integrate the function of measuring the direction and speed of the water flow. The flow model in the digital twin is constructed based on the wastewater flow conditions at multiple points in a limited and known space in the treatment pool. In a container with a certain shape and liquid inlet and outlet, The approximate flow path of the liquid in the container is constructed. Although the flow path will change with the flow rate, the change in the flow rate of the wastewater in the wastewater pool in this embodiment will not significantly change the flow path. The flow rate only affects the flow time of the wastewater between two points in the wastewater pool. After the wastewater flow model is established, the overall flow conditions in the treatment pool can be predicted based on the flow conditions of multiple point sensors, and the flow conditions at the sensorless points in the treatment pool can be analyzed to determine the flow relationship between any two points in the treatment pool, such as the path of the water flow from one point to another in the treatment pool based on the structure and flow conditions of the treatment pool under the overall flow model, which can reflect the flow time between any two points corresponding to the flow rate.

[0034] S200, obtaining the setting position of the wastewater component detection probe and the wastewater component detection historical data, and identifying the wastewater flow situation corresponding to the probe setting position at the time of the wastewater component detection historical data; based on the positional relationship between the component detection probes, establishing the wastewater treatment association relationship between the component detection probes in the digital twin according to the component detection historical data and the wastewater flow situation; and then establishing the overall wastewater treatment relationship model based on the overall flow model and the wastewater treatment association relationship between the points;

[0035] It should be noted that a component detection probe will also be set in the wastewater treatment system to monitor and record the wastewater treatment situation, and historical data of wastewater component detection can be obtained. The historical data can be constructed in the form of a curve graph to reflect the changes in components such as organic matter, heavy metals and compounds in the wastewater over time; while monitoring the wastewater composition, the setting position of the component detection probe can also be obtained, and the overall flow model constructed in the digital twin in the aforementioned step S100 can determine the wastewater flow conditions at various locations in the wastewater treatment system, that is, the wastewater flow conditions corresponding to the time of the wastewater component detection historical data can be obtained according to the setting position of the component detection probe, that is, the changes in the component composition of the wastewater in a certain time period can be obtained, and how the wastewater of this component flows in the wastewater treatment tank;

[0036] Based on the flow relationship between the locations of the component detection probes, the processing time can be obtained, and the component data detected by the two component detection probes at that time can be used to obtain the treatment effect of the wastewater. For example, the flow relationship between detection probe A and detection probe B in the digital twin, the wastewater flows from detection probe A to detection probe B. Under the flow rate and flow rate within a certain period of time, the pollutant component value x of the wastewater at detection probe A at time a, the wastewater flows to detection probe B at time b after ba time, and the pollutant component value of the wastewater is processed to y. These data can be directly mapped in the digital twin; the time length ba is the time when the wastewater flows from detection probe A to detection probe B. The time during which the probe flows to the B detection probe and is treated by chemical agents or microorganisms, the wastewater treatment association relationship can be regarded as the relationship between the wastewater composition and the treatment time. When the treatment parameters of the treatment pool, such as the concentration of the reagent, the density of the microorganism, the pH value and the oxygen content, are not adjusted, the wastewater treatment association relationship is consistent in the treatment pool. Therefore, after obtaining the wastewater treatment association relationship between any two points of the component detection probe, the overall wastewater treatment association relationship can be constructed based on the overall flow model, so that after obtaining the component data at any component detection probe, the digital twin can predict the change of the wastewater composition at any point in the treatment pool based on the flow model;

[0037] Furthermore, there will be chemical treatment agent input ports or areas with dense activated sludge sedimentation in the wastewater treatment pool. Therefore, when considering the treatment correlation between two points in the treatment pool, the component prediction value at the target point can also be corrected according to the specific flow area of ​​the flow model. For example, after obtaining the wastewater component data at a certain point, the water flow path between the target point to be predicted will pass through the chemical agent input port. The chemical agent density here will be higher than the overall density of the treatment pool, so the treatment effect will be higher, and the component prediction value of the target point can be corrected accordingly.

[0038] S300, obtain real-time data on wastewater composition and wastewater flow, and substitute them into the digital twin to obtain the predicted value of wastewater composition at the outlet of the treatment pool, and control the wastewater treatment equipment according to the difference between the standard value of wastewater composition and the predicted value of wastewater composition.

[0039] It should be noted that after the digital twin of the wastewater treatment system is established in the aforementioned steps and trained and corrected with the flow model and component association relationship, the multi-point data monitored by the sensors in the wastewater treatment system can be used to predict the wastewater composition at the outlet of the treatment pool. That is, in the actual wastewater treatment process, the wastewater component content data at the water inlet of the treatment pool or the wastewater component content data at any point in the middle of the treatment pool can be obtained in real time according to the sensor, and the wastewater component content at the outlet of the treatment pool can be predicted to determine whether the wastewater treatment effect meets the requirements, that is, the standard value of the wastewater component is compared with the predicted value of the wastewater component; the treatment pool must achieve the standard content of the wastewater discharge component. When the wastewater composition at the outlet is predicted to be substandard, In this case, the inlet flow rate can be adjusted according to the difference between the predicted value of the wastewater composition and the standard value of the wastewater composition, the treatment time of the wastewater in the treatment tank can be changed, or the treatment load in the treatment tank can be changed, or the dosage of chemical agents mixed into the treatment tank and the density of microorganisms can be changed to change the wastewater treatment efficiency, so that the wastewater composition near the outlet meets the standard. Adjusting the inlet flow rate can change the total amount of wastewater that needs to be treated and the residence time in the treatment tank. For example, when the heavy metal content of the wastewater component compounds exceeds the standard, the current treatment tank load is large, and the wastewater inlet flow rate can be reduced or the chemical agent dosage and microbial density can be increased. The specific wastewater treatment system adjustment control parameters can be set according to empirical values.

[0040] In this embodiment, a digital twin is constructed through the structure of a wastewater treatment pool, and the wastewater flow data monitored by each water flow sensor in the treatment pool is used to establish an overall flow model of the digital twin, which can map in real time the time required for the wastewater to flow between any two points in the treatment pool; then, based on the flow model, the position of the wastewater component detection probe and the component detection data are used to establish the relationship between the change in wastewater composition and the flow conditions in the digital twin; the real-time data obtained by the sensor at the water inlet or the middle section of the wastewater treatment pool is substituted into the trained digital twin, which can predict the composition of the wastewater at the outlet, determine whether it meets the emission standards, and regulate the treatment system with empirical values ​​based on the composition differences, which can perform real-time regulation based on the industrial wastewater composition input into the treatment pool, thereby improving treatment efficiency and reducing waste of treatment resources.

[0041] The above is a detailed description of the first embodiment of an industrial wastewater treatment control method based on digital twin provided by the present application. The following is a detailed description of the second embodiment of an industrial wastewater treatment control method based on digital twin provided by the present application.

[0042] In this embodiment, an industrial wastewater treatment control method based on digital twin is further provided. In the aforementioned step S200, after obtaining the setting position of the wastewater component detection probe and the wastewater component detection historical data, it also includes: obtaining the wastewater treatment system control parameter historical data, and supplementing the wastewater treatment association relationship with the control parameter historical data according to time association.

[0043] It should be noted that the wastewater treatment system can control parameters such as the pH, water temperature, concentration of chemical treatment agents, dissolved oxygen content, sludge age, etc. in the treatment pool to regulate the effect of chemical or biological treatment of wastewater in the treatment pool. The wastewater treatment association in the aforementioned steps only reflects the relationship between the wastewater treatment effect and the treatment time, and the treatment effect is also related to the control parameters of the treatment system. In the prior art, the control parameters are generally adjusted according to the component parameters detected in the treatment pool or the outlet detection parameters with a predetermined control ratio control relationship, but the treatment effect is more complicated to adjust under multiple control parameters to be adjusted, while the digital twin can be adjusted with a more fuzzy control logic to improve control efficiency.

[0044] Furthermore, in the aforementioned step S300, after controlling the wastewater treatment equipment according to the difference between the standard value of the wastewater component and the predicted value of the wastewater component, it also includes: obtaining real-time data of the wastewater component at the outlet of the treatment pool, comparing the predicted value with the real-time data, and correcting the wastewater treatment relationship model in the digital twin based on the difference. After the digital twin predicts with the first component probe detection data of the earlier treatment stage in the treatment pool, the predicted wastewater composition at the outlet position is the wastewater composition when the wastewater currently in the area where the first component probe is detected flows to the outlet after being treated in the treatment pool. Therefore, the corresponding one should be the first processing time from the first component probe detection position to the outlet position under the flow model, that is, the real-time component data detected at the outlet position after the first processing time corresponds to the predicted data. Since the final actual composition may be different from the predicted value due to various other factors such as chemical agent consumption, microbial reproduction or death after the first processing time, the predicted value and the corresponding real-time data can be compared, and the wastewater treatment relationship model in the digital twin can be corrected by the difference. The specific correction relationship can be empirical value or substituted into the digital twin for learning and training.

[0045] The above is a detailed description of an industrial wastewater treatment control method based on digital twins provided in the first aspect of the present application. The following is a detailed description of an embodiment of an industrial wastewater treatment control system based on digital twins provided in the second aspect of the present application.

[0046] See also Figure 2 , Figure 2This is a structural diagram of an industrial wastewater treatment control system based on digital twins. This embodiment provides an industrial wastewater treatment control system based on digital twins, including:

[0047] The digital twin construction module 10 is used to obtain the structural model of the industrial wastewater treatment pool and establish the corresponding digital twin based on the structural model; obtain the setting position of each monitoring sensor and the corresponding wastewater flow historical data, and construct an overall flow model in the digital twin based on the positional relationship between the monitoring sensors and the wastewater flow historical data.

[0048] The processing relationship training module 20 is used to obtain the setting position of the wastewater component detection probe and the wastewater component detection historical data, and identify the wastewater flow situation corresponding to the probe setting position at the time of the wastewater component detection historical data; based on the positional relationship between the component detection probes, the wastewater treatment association relationship between the component detection probes is established in the digital twin according to the component detection historical data and the wastewater flow situation; and then based on the overall flow model, the overall wastewater treatment relationship model is established with the wastewater treatment association relationship between the points;

[0049] The wastewater treatment control module 30 is used to obtain real-time data on wastewater composition and wastewater flow, and substitute them into the digital twin to obtain the predicted value of wastewater composition at the outlet of the treatment pool, and control the wastewater treatment equipment according to the difference between the standard value of the wastewater composition and the predicted value of the wastewater composition.

[0050] Furthermore, in the processing relationship training module 20, after obtaining the setting position of the wastewater component detection probe and the wastewater component detection historical data, it also includes:

[0051] Obtain the historical data of the control parameters of the wastewater treatment system, and supplement the wastewater treatment association relationship with the historical data of the control parameters based on time association.

[0052] Furthermore, in the wastewater treatment control module 30, after controlling the wastewater treatment equipment according to the difference between the standard value of the wastewater component and the predicted value of the wastewater component, it also includes:

[0053] Obtain real-time data on wastewater composition at the outlet of the treatment pool, compare the predicted value with the real-time data, and modify the wastewater treatment relationship model in the digital twin based on the difference.

[0054] The third aspect of the present application also provides an industrial wastewater treatment control method device based on digital twins, including a processor and a memory: wherein the memory is used to store program code and transfer the program code to the processor; the processor is used to execute the above-mentioned industrial wastewater treatment control method based on digital twins according to the instructions in the program code.

[0055] The fourth aspect of the present application provides a computer-readable storage medium, characterized in that the computer-readable storage medium is used to store program code, and the program code is used to execute the above-mentioned industrial wastewater treatment control method based on digital twins.

[0056] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the above-described devices and equipment can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0057] In the several embodiments provided in the present application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interfaces, devices or units, which can be electrical, mechanical or other forms.

[0058] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0059] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0060] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc. Various media that can store program codes.

[0061] As described above, the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features thereof may be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A digital twin-based industrial wastewater treatment control method, characterized in that include: Obtain the structural model of the industrial wastewater treatment pool, and establish a corresponding digital twin based on the structural model; obtain the setting position of each monitoring sensor and the corresponding wastewater flow historical data, obtain the wastewater flow direction and speed at multiple positions in the industrial wastewater treatment pool, and construct an overall flow model in the digital twin based on the positional relationship between the monitoring sensors and the wastewater flow historical data, wherein the overall flow model reflects the flow path of the wastewater in the industrial wastewater treatment pool; Obtain the setting position of the wastewater component detection probe and the historical data of wastewater component detection, and use the overall flow model to identify the wastewater flow situation corresponding to the probe setting position at the time of the wastewater component detection historical data, wherein the wastewater flow situation includes the flow direction and speed of the wastewater; obtain the component value change and processing time of the wastewater between any two component detection probes based on the component detection historical data and wastewater flow situation of the setting position of each component detection probe, and establish the wastewater treatment association relationship between each component detection probe in the digital twin based on the component value change and processing time of the wastewater between the component detection probes; then establish the overall wastewater treatment relationship model based on the wastewater treatment association relationship between the location points of any two component detection probes based on the overall flow model; Real-time data on wastewater composition and wastewater flow are obtained and substituted into the digital twin to obtain the predicted value of wastewater composition at the outlet of the treatment pool. The wastewater treatment equipment is controlled based on the difference between the standard value of wastewater composition and the predicted value of wastewater composition.

2. According to claim 1, a method for controlling industrial wastewater treatment based on digital twins is characterized in that: After obtaining the setting position of the wastewater component detection probe and the wastewater component detection historical data, the method further includes: Obtain the historical data of the control parameters of the wastewater treatment system, and supplement the wastewater treatment association relationship with the historical data of the control parameters based on time association.

3. The industrial wastewater treatment control method based on digital twin according to claim 1 is characterized in that: After the wastewater treatment equipment is controlled according to the difference between the standard value of the wastewater component and the predicted value of the wastewater component, the method further includes: Obtain real-time data on wastewater composition at the outlet of the treatment pool, compare the predicted value with the real-time data, and modify the wastewater treatment relationship model in the digital twin based on the difference.

4. An industrial wastewater treatment control system based on digital twin, characterized in that: include: A digital twin construction module is used to obtain the structural model of the industrial wastewater treatment pool and establish a corresponding digital twin based on the structural model; obtain the setting position of each monitoring sensor and the corresponding wastewater flow history data, obtain the wastewater flow direction and speed at multiple positions in the industrial wastewater treatment pool, and construct an overall flow model in the digital twin based on the positional relationship between the monitoring sensors and the wastewater flow history data. The overall flow model reflects the flow path of the wastewater in the industrial wastewater treatment pool; A processing relationship training module is used to obtain the setting position of the wastewater component detection probe and the historical data of wastewater component detection, and use the overall flow model to identify the wastewater flow situation corresponding to the probe setting position at the time of the wastewater component detection historical data, wherein the wastewater flow situation includes the flow direction and speed of the wastewater; based on the component detection historical data and wastewater flow situation of the setting position of each component detection probe, the component value change and processing time of the wastewater between any two component detection probes are obtained, and the wastewater treatment association relationship between each component detection probe is established in the digital twin based on the component value change and processing time of the wastewater between the component detection probes; and then based on the overall flow model, the overall wastewater treatment relationship model is established based on the wastewater treatment association relationship between the location points of any two component detection probes; The wastewater treatment control module is used to obtain real-time data on wastewater composition and wastewater flow, and substitute them into the digital twin to obtain the predicted value of wastewater composition at the outlet of the treatment pool, and control the wastewater treatment equipment according to the difference between the standard value of wastewater composition and the predicted value of wastewater composition.

5. The industrial wastewater treatment control system based on digital twin according to claim 4 is characterized in that: In the processing relationship training module, after obtaining the setting position of the wastewater component detection probe and the wastewater component detection historical data, it also includes: Obtain the historical data of the control parameters of the wastewater treatment system, and supplement the wastewater treatment association relationship with the historical data of the control parameters based on time association.

6. The industrial wastewater treatment control system based on digital twin according to claim 4 is characterized in that: In the wastewater treatment control module, after controlling the wastewater treatment equipment according to the difference between the standard value of the wastewater component and the predicted value of the wastewater component, it also includes: Obtain real-time data on wastewater composition at the outlet of the treatment pool, compare the predicted value with the real-time data, and modify the wastewater treatment relationship model in the digital twin based on the difference.

7. An industrial wastewater treatment control device based on digital twin, characterized in that: The device comprises a processor and a memory: The memory is used to store program code and transmit the program code to the processor; The processor is used to execute an industrial wastewater treatment control method based on digital twins as described in any one of claims 1 to 3 according to the instructions in the program code.

8. A computer-readable storage medium, characterized in that: The computer-readable storage medium is used to store program code, and the program code is used to execute an industrial wastewater treatment control method based on digital twins as described in any one of claims 1 to 3.

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