A wastewater treatment carbon source control system and method

Abstract

The present invention relates to the technical field of automated sewage treatment, and in particular to a sewage treatment carbon source control system and method, comprising an online analysis module, a carbon source budget module, and a delivery control module. The system extracts historical data of discharge information in a sewage discharge area, selects an influent flow rate in the discharge information as a first parameter, processes the influent flow rate in the historical data, determines a flow interval, extracts a target data group in the flow interval, performs simulation training on the target data group, determines a correlation model of the flow interval, obtains the influent flow rate and nitrogen load of the sewage discharge area, determines a corresponding flow interval and its correlation model according to the influent flow rate, then inputs the nitrogen load into the corresponding correlation model, determines a carbon source delivery optimal value, and a carbon source delivery device automatically controls the carbon source delivery amount according to the carbon source delivery optimal value, thereby improving the accuracy of carbon source delivery control and reducing sewage treatment costs.

Description

Technical Field

[0001] The present invention relates to the technical field of automated sewage treatment, and in particular to a sewage treatment carbon source control system and method. Background Art

[0002] The pace of urbanization is gradually accelerating, the living standards of residents are gradually improving, and the amount of urban domestic sewage is increasing. Carbon sources play a vital role in the sewage treatment process. They not only provide the energy required for microbial growth, but also optimize the effluent quality, meet the needs of nitrogen and phosphorus removal, and ensure the stability of the system.

[0003] Prior art CN113674809A discloses a method for adding carbon source to sewage treatment based on predictive control, which includes: establishing an energy consumption and water quality model, optimizing the energy consumption and water quality model using the NSGA2 algorithm, and obtaining a solution set with the lowest energy consumption or the highest water quality as Concentration and The set value of concentration; input the solution set with the lowest energy consumption or the highest water quality into the total nitrogen prediction model of sewage treatment effluent to obtain the total nitrogen prediction value corresponding to the current input; determine whether the total nitrogen prediction value exceeds the standard and adopt different carbon source fuzzy control rules to add carbon source.

[0004] However, in sewage treatment, the amount of added carbon source will be affected by many factors in actual operation, which makes the theoretical value calculated by the traditional carbon source addition calculation formula very limited in guiding the actual process operation. In addition, if the carbon source is added based on artificial experience, it is easy to cause insufficient or excessive carbon source addition, which reduces the sewage treatment effect and increases the cost of sewage treatment. Summary of the invention

[0005] The purpose of the present invention is to solve the problems in the background technology and to propose a carbon source control system and method for sewage treatment.

[0006] In order to achieve the above object, the present invention adopts the following technical solutions:

[0007] A sewage treatment carbon source control system, comprising a data monitoring module, an online analysis module, a carbon source budget module, and a delivery control module;

[0008] The data monitoring module is used to conduct online monitoring of regional sewage discharge information, where the discharge information includes water inflow and nitrogen load. The water inflow refers to the transportation flow of sewage in the sewage pipe.

[0009] The online analysis module, based on the historical data of the discharge information in the sewage discharge area, selects the water inflow in the discharge information as the first parameter, processes the water inflow in the historical data, determines the flow interval, then matches the water inflow collected online with the flow interval, and marks the flow interval corresponding to the matching result as the belonging interval;

[0010] The carbon source budget module is used to process and simulate the target data group in each flow interval, and determine the association model between the nitrogen load and the carbon source input in each flow interval, wherein the target data group refers to the information combination of the discharge information and the treatment information of each influent flow in the flow interval, and the treatment information includes the carbon source input, reaction temperature and effluent water quality. Then, according to the real-time attribution interval of the sewage discharge area, the corresponding attribution interval and its association model are determined, and then the nitrogen load of the online collected discharge information is detected, and then the nitrogen load is input into the corresponding association model to determine the carbon source input merit;

[0011] The delivery control module is used to generate a carbon source delivery instruction to the carbon source delivery device according to the carbon source delivery merit, and the carbon source delivery device automatically controls the carbon source delivery amount according to the delivery instruction.

[0012] As a further solution of the present invention, a method for determining a flow interval includes:

[0013] S101: Acquire historical data of a sewage discharge area in an information storage terminal of a cloud platform, where the sewage discharge area refers to an area managed by a sewage treatment plant, and the historical data is data corresponding to the discharge information stored in the cloud platform;

[0014] S102: selecting the inflow flow rate as the first parameter, identifying the maximum value of the inflow flow rate of the sewage discharge area based on the historical data of the sewage discharge area, and taking the maximum values ​​as the endpoints of the interval, to obtain the flow discharge interval of the sewage discharge area, wherein the maximum value includes the maximum value and the minimum value;

[0015] Arrange the inlet flow in order from small to large, taking the first data as the starting point, taking m data as a group, identifying the mth data, and taking the first data and the mth data as the left and right endpoints of the flow interval respectively, to obtain the first flow interval, then taking the m+1th data as the starting point, identifying the 2mth data, and then taking the m+1th data and the 2mth data as the left and right endpoints of the flow interval respectively, to obtain the second flow interval, and so on, until the maximum value of the inlet flow is identified. At this time, the flow interval setting of the sewage discharge area is completed, where m is the threshold.

[0016] As a further solution of the present invention, when setting the flow interval according to the historical data of the sewage discharge area, it is necessary to detect the weather factors of the sewage discharge area, and divide the water inflow flow into mixed flow and regional flow, wherein the mixed flow refers to the water that is mixed with rainwater and domestic sewage and transported to the sewage treatment area through the sewage pipe, and the regional flow refers to the water containing only domestic sewage;

[0017] Afterwards, the water inlet flow is classified into regional flow and mixed flow, and the flow interval is set for each type of water inlet flow according to the above method, so as to obtain the flow interval of the regional flow and the flow interval of the mixed flow.

[0018] As a further solution of the present invention, a method for determining a correlation model between nitrogen load and carbon source input amount in a flow interval includes:

[0019] Randomly select a flow interval as the target analysis interval, compare the influent flow collected in the historical data with the target analysis interval, and if the influent flow belongs to the target analysis interval, obtain the emission information and treatment information of the influent flow, and bind the emission information of the influent flow with the treatment information to generate a target data group. The emission information includes nitrogen load, and the treatment information includes carbon source input, reaction temperature and effluent water quality.

[0020] Take the flow characteristic value TL of the water inlet flow in the target data group, where the flow characteristic value TL is the mean value of the water inlet flow in the target data group;

[0021] Based on the nitrogen load FNj and carbon source input TCj in the target data group, j represents different target data groups, j∈[1,J], indicating that there are J target data groups in the target analysis interval;

[0022] The nitrogen load FNj and carbon source input TCj in the target data group are simulated and trained to obtain the correlation model M: ; Wherein, Csi represents the effluent water quality coefficient of the target analysis interval i, FN is the nitrogen load in the target analysis interval, TC is the carbon source input in the target analysis interval, a1 represents the carbon-nitrogen ratio required for the reaction, Xi represents the environmental impact factor of the target analysis interval i, and are the first correction factor and the second correction factor respectively, and a2 and a3 are adjustment parameters;

[0023] The remaining flow intervals are taken as target analysis intervals in turn and processed according to the above method to obtain the association model Mi of each flow interval.

[0024] As a further solution of the present invention, the smaller the effluent water quality coefficient is, the more accurate the carbon source input is, and the closer the water quality parameters at the outlet are to the effluent standard parameters. Conversely, the larger the effluent water quality coefficient is, the less or more carbon source input is.

[0025] As a further solution of the present invention, a method for determining the carbon source placement merit includes:

[0026] The association model of the belonging interval is obtained, and the nitrogen load in the emission information collected online is extracted. The nitrogen load is input into the association model of the belonging interval for calculation, and the corresponding carbon source input amount when the water quality coefficient is the smallest is obtained, and the carbon source input amount obtained at this time is marked as the carbon source input merit.

[0027] As a further solution of the present invention, when the carbon source delivery device automatically controls the carbon source delivery amount according to the carbon source delivery merit, sewage with high COD concentration is used as the carbon source for sewage treatment.

[0028] As a further solution of the present invention, the online analysis module includes a cloud data analysis unit and a real-time data analysis unit;

[0029] The cloud data analysis unit determines the flow range of regional sewage based on the emission information stored in the cloud platform. The real-time data analysis unit matches the interval information of the emission information collected online based on the flow range, and there is a one-way communication connection between the cloud data analysis module and the real-time data analysis unit.

[0030] A method for controlling carbon sources in sewage treatment comprises the following steps:

[0031] Step 1: extract historical data of discharge information in the sewage discharge area, select the inflow flow in the discharge information as the first parameter, process the inflow flow in the historical data, and determine the flow range;

[0032] Step 2: Extract the target data group in the flow interval. The target data group refers to the data information combination of the discharge information and the treatment information of the inlet flow. Process the data of all target data groups in the flow interval, perform simulation training, and determine the association model of the flow interval.

[0033] Step 3: Collect the discharge information of the sewage discharge area in real time, and obtain the influent flow and nitrogen load of the sewage discharge area. First, determine the corresponding flow range and its correlation model according to the influent flow, and then input the nitrogen load into the corresponding correlation model to determine the optimal value of carbon source placement;

[0034] Step 4: According to the carbon source delivery merit, a carbon source delivery instruction is generated for the carbon source delivery device, and the carbon source delivery device automatically controls the carbon source delivery amount according to the delivery instruction.

[0035] Compared with the prior art, the advantages of the present invention are:

[0036] The present invention constructs a correlation model for carbon source placement based on historical discharge information and treatment information of the sewage discharge area, and inputs the nitrogen load in the discharge information into the correlation model based on the discharge information collected online, thereby obtaining the optimal value of the actual carbon source placement, thereby improving the accuracy of carbon source placement control and reducing sewage treatment costs;

[0037] The present invention sets flow intervals according to the water inflow in the historical emission information, and performs fitting calculations on the emission information and the treatment information in each flow interval separately, thereby obtaining correlation models of different flow intervals. On the one hand, the local characteristics can be better captured and the data fitting accuracy can be improved. On the other hand, the fitting error can be controlled separately, which is convenient for the optimization and adjustment of the carbon source control.

[0038] The present invention uses sewage with high COD concentration as the carbon source for sewage treatment. The organic matter in the high COD sewage can promote the growth and metabolism of microorganisms, accelerate the degradation rate of organic matter in the sewage treatment process, improve the treatment efficiency, and reduce the sewage treatment cost. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Figure 1 It is a schematic diagram of the system structure of the present invention;

[0040] Figure 2 It is a schematic diagram of the method flow structure of the present invention. DETAILED DESCRIPTION

[0041] The technical solutions in the embodiments of the present invention will be described clearly and completely below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments.

[0042] Reference Figure 1 and Figure 2 , a sewage treatment carbon source control system, including a data monitoring module, an online analysis module, a carbon source budget module, and a delivery control module;

[0043] The data monitoring module is used to monitor the emission information online during the sewage treatment process, where the emission information includes water inflow, ammonia nitrogen and total nitrogen. The water inflow refers to the transportation flow of sewage in the sewage pipe. The data monitoring module then transmits the emission information collected online to the online analysis module in real time.

[0044] The online analysis module is used to perform behavioral analysis on the discharge information and determine the inertial discharge action of regional sewage. Furthermore, the online analysis module includes a cloud data analysis unit and a real-time data analysis unit. The cloud data analysis unit determines the flow interval of regional sewage based on the discharge information stored in the cloud platform. The real-time data analysis unit matches the interval information of the discharge information collected online based on the flow interval, and the cloud data analysis module and the real-time data analysis unit are connected in a one-way communication manner.

[0045] The specific analysis methods include:

[0046] S101: Acquire historical data of a sewage discharge area in an information storage terminal of a cloud platform, wherein the sewage discharge area refers to an area managed by a sewage treatment plant, and the historical data is data corresponding to the discharge information stored in the cloud platform;

[0047] It should be further explained that when the data monitoring module performs online monitoring of the emission information, it also transmits the monitoring data to the cloud platform, and the cloud platform is used to store the emission information. Furthermore, the cloud platform is used to store the analysis data in the control system;

[0048] S102: Selecting the inflow flow rate as the first parameter, and setting a flow interval Li for the inflow flow rate of the sewage discharge area based on the historical data of the sewage discharge area, where i represents different flow intervals, i∈[1,I], indicating that there are I flow intervals in the sewage discharge area;

[0049] The flow interval setting methods include:

[0050] Identify the maximum value of the water inflow flow rate in the sewage discharge area, and use the maximum value as the endpoint of the interval to obtain the flow discharge interval of the sewage discharge area, where the maximum value includes the maximum value and the minimum value;

[0051] Then, the inflow flow is arranged in order from small to large, with the first data as the starting point, m data are taken as a group, the mth data is identified, and the first data and the mth data are used as the left endpoint and the right endpoint of the flow interval respectively to obtain the first flow interval, and then the m+1th data is used as the starting point to identify the 2mth data, and then the m+1th data and the 2mth data are used as the left endpoint and the right endpoint of the flow interval respectively to obtain the second flow interval, and so on, until the maximum value of the inflow flow is identified. At this time, the flow interval setting of the sewage discharge area is completed, wherein m is a threshold value, and the specific value of m in this embodiment is obtained by those skilled in the art after big data calculation;

[0052] In another embodiment of the present invention, when setting the flow interval according to the historical data of the sewage discharge area, it is necessary to detect the weather factors of the sewage discharge area, and divide the water inflow flow into a mixed flow and a regional flow, wherein the mixed flow refers to the water that is mixed with rainwater and domestic sewage and transported to the sewage treatment area through the sewage pipe, and the regional flow refers to the water containing only domestic sewage. Furthermore, when it is raining in the sewage treatment area, the monitoring data at this time is marked as a mixed flow, and when it is not raining in the sewage treatment area, the monitoring data at this time is marked as a regional flow;

[0053] Then, the water inflow is classified into regional flow and mixed flow, and the flow interval is set for each type of water inflow according to the above method, so as to obtain the flow interval of the regional flow and the flow interval of the mixed flow;

[0054] When the real-time data analysis unit identifies the inflow flow, it is necessary to match the inflow flow of the discharge information with the flow interval according to the real-time weather in the sewage discharge area and the discharge information collected online, and mark the flow interval corresponding to the matching result as the belonging interval;

[0055] There is a one-way communication connection between the online analysis module and the carbon source budget module;

[0056] The carbon source budget module is used to determine the amount of carbon source input according to the flow interval and the attribution interval. The specific determination methods include:

[0057] S201: arbitrarily selecting a flow interval as a target analysis interval, and extracting a target data group from historical data;

[0058] Among them, the influent flow collected in the historical data is compared with the target analysis interval. If the influent flow belongs to the target analysis interval, the discharge information and treatment information of the influent flow are obtained, and the discharge information of the influent flow is bound with the treatment information to generate a target data group. Furthermore, the treatment information includes data information such as carbon source input, reaction time, reaction temperature, terminal water quality and microbial activity, among which the terminal water quality refers to the water quality after sewage treatment;

[0059] S202: obtaining a flow characteristic value TL of the water inlet flow in the target data group, wherein the flow characteristic value TL is the average value of the water inlet flow in the target data group;

[0060] At the same time, based on the nitrogen load FNj and carbon source input amount TCj in the target data group, j represents different target data groups, j∈[1,J], indicating that there are J target data groups in the target analysis interval;

[0061] The nitrogen load FNj and carbon source input TCj in the target data group are simulated and trained to obtain the correlation model M: ; Wherein, Csi represents the effluent water quality coefficient of the target analysis interval i. Furthermore, the smaller the effluent water quality coefficient, the more accurate the carbon source input amount is, and the closer the water quality parameters at the outlet are to the effluent standard parameters. Conversely, the larger the effluent water quality coefficient, the less or more carbon source input amount is.

[0062] FN is the nitrogen load in the target analysis interval, TC is the amount of carbon source input in the target analysis interval, a1 represents the carbon-nitrogen ratio required for the reaction, Xi represents the environmental impact factor of the target analysis interval i, and are the first correction factor and the second correction factor respectively, a2 and a3 are adjustment parameters, and the specific Xi, , The values ​​of a2 and a3 are obtained by technicians in this field after big data simulation calculation;

[0063] After that, the remaining flow intervals are taken as target analysis intervals in turn and processed according to the above method to obtain the association model Mi of each flow interval;

[0064] It should be further explained that the advantages of dividing the inlet flow into flow intervals based on historical data and performing fitting calculations on each flow interval separately include: being able to better capture local characteristics and improve data fitting accuracy; at the same time, performing data fitting on each flow interval can control fitting errors separately, which is convenient for optimizing and adjusting carbon source control;

[0065] S203: then, the association model of the belonging interval is obtained, and the nitrogen load in the emission information collected online is extracted, and the nitrogen load is input into the association model of the belonging interval for calculation, and the corresponding carbon source input amount when the water quality coefficient is the smallest is obtained, and the carbon source input amount obtained at this time is marked as the carbon source input merit;

[0066] There is a one-way communication connection between the carbon source budget module and the delivery control module;

[0067] The delivery control module generates a carbon source delivery instruction to the carbon source delivery device based on the carbon source delivery merit, and then the carbon source delivery device automatically controls the carbon source delivery amount according to the carbon source delivery merit;

[0068] It should be further explained that in this embodiment, sewage with high COD concentration is used as a carbon source for sewage treatment. Furthermore, the advantages of using sewage with high COD concentration as a carbon source include that the organic matter in the high COD sewage can promote the growth and metabolism of microorganisms, accelerate the degradation rate of organic matter in the sewage treatment process, improve the treatment efficiency, and reduce the cost of sewage treatment.

[0069] A method for controlling carbon sources in sewage treatment, the method specifically comprising the following steps:

[0070] Step 1: extract historical data of discharge information in the sewage discharge area, select the inflow flow in the discharge information as the first parameter, process the inflow flow in the historical data, and determine the flow range;

[0071] Step 2: Extract the target data group in the flow interval. The target data group refers to the data information combination of the discharge information and the treatment information of the influent flow. The data in the specific target data group includes nitrogen load, carbon source input and environmental parameters. The data of all target data groups in the flow interval are processed and simulated and trained to determine the association model of the flow interval.

[0072] Step 3: Collect the discharge information of the sewage discharge area in real time, and obtain the influent flow and nitrogen load of the sewage discharge area. First, determine the corresponding flow range and its correlation model according to the influent flow, and then input the nitrogen load into the corresponding correlation model to determine the optimal value of carbon source placement;

[0073] Step 4: According to the carbon source delivery merit, a carbon source delivery instruction is generated for the carbon source delivery device, and the carbon source delivery device automatically controls the carbon source delivery amount according to the delivery instruction.

[0074] The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can make equivalent replacements or changes according to the technical scheme and inventive concept of the present invention within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. A wastewater treatment carbon source control system, characterized in that: Including data monitoring module, online analysis module, carbon source budget module, and delivery control module; The data monitoring module is used to conduct online monitoring of regional sewage discharge information, where the discharge information includes water inflow and nitrogen load. The water inflow refers to the transportation flow of sewage in the sewage pipe. The online analysis module, based on the historical data of the discharge information in the sewage discharge area, selects the water inflow in the discharge information as the first parameter, processes the water inflow in the historical data, determines the flow interval, then matches the water inflow collected online with the flow interval, and marks the flow interval corresponding to the matching result as the belonging interval; The carbon source budget module is used to process and simulate the target data group in each flow interval, and determine the association model between the nitrogen load and the carbon source input in each flow interval, wherein the target data group refers to the information combination of the discharge information and the treatment information of each influent flow in the flow interval, and the treatment information includes the carbon source input, reaction temperature and terminal water quality. Then, according to the real-time attribution interval of the sewage discharge area, the corresponding attribution interval and its association model are determined, and then the nitrogen load of the online collected discharge information is detected, and then the nitrogen load is input into the corresponding association model to determine the carbon source input merit. The specific processing method includes: Randomly select a flow interval as the target analysis interval, compare the inflow flow collected in the historical data with the target analysis interval, and if the inflow flow belongs to the target analysis interval, obtain the emission information and treatment information of the inflow flow, and bind the emission information of the inflow flow with the treatment information to generate a target data group. The emission information includes nitrogen load, and the treatment information includes carbon source input, reaction temperature and terminal water quality. Take the flow characteristic value TL of the water inlet flow in the target data group, where the flow characteristic value TL is the mean value of the water inlet flow in the target data group; Based on the nitrogen load FNj and carbon source input TCj in the target data group, j represents different target data groups, j∈[1,J], indicating that there are J target data groups in the target analysis interval; The nitrogen load FNj and carbon source input TCj in the target data group are simulated and trained to obtain the correlation model M: ; Among them, Csi represents the effluent water quality coefficient of the target analysis interval i, FN is the nitrogen load in the target analysis interval, TC is the amount of carbon source input in the target analysis interval, a1 represents the carbon-nitrogen ratio required for the reaction, Xi represents the environmental impact factor of the target analysis interval i, and are the first correction factor and the second correction factor respectively, and a2 and a3 are adjustment parameters; The remaining flow intervals are taken as target analysis intervals in turn, and processed according to the above method to obtain the association model Mi of each flow interval; Obtain the association model of the belonging interval, extract the nitrogen load from the emission information collected online, input the nitrogen load into the association model of the belonging interval for calculation, take out the carbon source input amount corresponding to the minimum water quality coefficient, and mark the carbon source input amount obtained at this time as the carbon source input merit; The delivery control module is used to generate a carbon source delivery instruction to the carbon source delivery device according to the carbon source delivery merit, and the carbon source delivery device automatically controls the carbon source delivery amount according to the delivery instruction.

2. A wastewater treatment carbon source control system according to claim 1, characterized in that: Methods for determining flow intervals include: S101: Acquire historical data of a sewage discharge area in an information storage terminal of a cloud platform, where the sewage discharge area refers to an area managed by a sewage treatment plant, and the historical data is data corresponding to the discharge information stored in the cloud platform; S102: selecting the inflow flow rate as the first parameter, identifying the maximum value of the inflow flow rate of the sewage discharge area based on the historical data of the sewage discharge area, and taking the maximum values ​​as the endpoints of the interval, to obtain the flow discharge interval of the sewage discharge area, wherein the maximum value includes the maximum value and the minimum value; Arrange the inlet flow in order from small to large, taking the first data as the starting point, taking m data as a group, identifying the mth data, and taking the first data and the mth data as the left and right endpoints of the flow interval respectively, to obtain the first flow interval, then taking the m+1th data as the starting point, identifying the 2mth data, and then taking the m+1th data and the 2mth data as the left and right endpoints of the flow interval respectively, to obtain the second flow interval, and so on, until the maximum value of the inlet flow is identified. At this time, the flow interval setting of the sewage discharge area is completed, where m is the threshold.

3. A sewage treatment carbon source control system according to claim 2, characterized in that: When setting the flow interval based on the historical data of the sewage discharge area, it is necessary to detect the weather factors in the sewage discharge area and divide the inflow flow into mixed flow and regional flow. The mixed flow refers to the water that is mixed with rainwater and domestic sewage and transported to the sewage treatment area through the sewage pipe, and the regional flow refers to the water that contains only domestic sewage. Afterwards, the water inlet flow is classified into regional flow and mixed flow, and the flow interval is set for each type of water inlet flow according to the above method, so as to obtain the flow interval of the regional flow and the flow interval of the mixed flow.

4. A wastewater treatment carbon source control system according to claim 1, characterized in that: The smaller the effluent water quality coefficient is, the more accurate the carbon source input is, and the closer the water quality parameters at the outlet are to the effluent standard parameters. Conversely, the larger the effluent water quality coefficient is, the more insufficient or excessive the carbon source input is.

5. A wastewater treatment carbon source control system according to claim 1, characterized in that: When the carbon source delivery device automatically controls the carbon source delivery amount according to the carbon source delivery merit, the sewage with high COD concentration is used as the carbon source for sewage treatment.

6. A wastewater treatment carbon source control system according to claim 1, characterized in that: The online analysis module includes a cloud data analysis unit and a real-time data analysis unit; The cloud data analysis unit determines the flow range of regional sewage based on the emission information stored in the cloud platform. The real-time data analysis unit matches the interval information of the emission information collected online based on the flow range, and there is a one-way communication connection between the cloud data analysis module and the real-time data analysis unit.

7. A method for controlling a carbon source in sewage treatment, the method for controlling a carbon source being applied to a control system as claimed in any one of claims 1 to 6, characterized in that: The following steps are involved: Step 1: extract historical data of discharge information in the sewage discharge area, select the inflow flow in the discharge information as the first parameter, process the inflow flow in the historical data, and determine the flow range; Step 2: Extract the target data group in the flow interval. The target data group refers to the data information combination of the discharge information and the treatment information of the inlet flow. Process the data of all target data groups in the flow interval, perform simulation training, and determine the association model of the flow interval. Step 3: Collect the discharge information of the sewage discharge area in real time, and obtain the influent flow and nitrogen load of the sewage discharge area. First, determine the corresponding flow range and its correlation model according to the influent flow, and then input the nitrogen load into the corresponding correlation model to determine the optimal value of carbon source placement; Step 4: According to the carbon source delivery merit, a carbon source delivery instruction is generated for the carbon source delivery device, and the carbon source delivery device automatically controls the carbon source delivery amount according to the delivery instruction.

Images