Sewage treatment method and device, electronic equipment and storage medium

Abstract

The embodiment of the invention provides a sewage treatment method and device, electronic equipment and a storage medium, and is applied to a server. The method comprises the following steps: acquiring attribute information of a previous batch of sewage in a container, first processing information of the previous batch of sewage and resource configuration information; according to the attribute information, the first processing information and the resource configuration information, determining the water inflow of the current batch of the container and second processing information of the sewage of the current batch; based on the water inflow of the current batch, water inflow of the container is controlled; and based on the second treatment information, controlling at least one treatment device to treat the current batch of sewage. The method improves the flexibility of sewage treatment.

Description

Technical Field

[0001] The present application relates to the technical field of sewage treatment, and in particular to a sewage treatment method, device, electronic equipment and storage medium. Background Art

[0002] The Sequencing Batch Reactor (SBR) process is a batch-by-batch method for treating wastewater within a reaction tank. In related technologies, SBR can be implemented using a Programmable Logic Controller (PLC). Specifically, the SBR treats wastewater based on at least one treatment device, where the operating parameters of the at least one treatment device and the dosage of chemicals used for treatment are pre-set. For each treatment device, the PLC controls the treatment of the wastewater based on the device's operating parameters and administers chemicals based on the dosage of chemicals used for treatment.

[0003] However, for different batches of sewage, the operating parameters of each treatment equipment and the dosage of the required chemicals may vary due to factors such as sewage quality, water volume, and environmental factors. Therefore, the flexibility of sewage treatment using the above method is limited. Summary of the Invention

[0004] Embodiments of the present application provide a sewage treatment method, device, electronic device, and storage medium to improve the flexibility of sewage treatment.

[0005] In a first aspect, an embodiment of the present application provides a sewage treatment method, the method comprising:

[0006] Obtaining attribute information of a previous batch of sewage in the container, first treatment information of the previous batch of sewage, and resource allocation information;

[0007] Determining the water intake of the current batch of the container and the second processing information of the current batch of sewage according to the attribute information, the first processing information, and the resource allocation information;

[0008] Control the water inflow to the container based on the water inflow of the current batch;

[0009] Based on the second processing information, at least one processing device is controlled to process the current batch of sewage.

[0010] In one possible implementation, determining the amount of water inflow of a current batch in the container and second processing information of the current batch of sewage based on the attribute information, the first processing information, and the resource allocation information includes:

[0011] Based on the attribute information, the water quality parameters of the previous batch of effluent, the water volume of the current batch, and the treatment time of the current batch of sewage are determined; the effluent is obtained after the sewage of the previous batch is treated;

[0012] Determining a first dosage of a chemical for a current batch of sewage and first operating parameters of at least one treatment device based on effluent water quality parameters, influent volume, treatment time, attribute information, first treatment information, and resource allocation information;

[0013] The second processing information includes the first dosage and the first operating parameter.

[0014] In one possible implementation, determining the water quality parameters of the previous batch of effluent, the water volume of the current batch, and the treatment time of the current batch of sewage based on the attribute information includes:

[0015] Inputting the attribute information into a first prediction model to obtain water quality parameters of a current batch of sewage and sludge mass of the current batch of sewage; wherein the first prediction model is trained based on the first sample data and the first label; the first sample data includes sample attribute information of the first batch of sewage; the first label includes water quality parameters of a second batch of sewage and sludge mass of the second batch of sewage; and the second batch is the next batch after the first batch;

[0016] According to the attribute information, the water quality parameters of the current batch of sewage and the sludge quality of the current batch of sewage, the water quality parameters of the previous batch of effluent, the water intake of the current batch and the treatment time of the current batch of sewage are obtained.

[0017] In one possible implementation, the water quality parameters of the effluent of the previous batch, the water intake of the current batch, and the treatment time of the current batch of sewage are obtained based on the attribute information, the water quality parameters of the current batch of sewage, and the sludge mass of the current batch of sewage, including:

[0018] Inputting the attribute information, the water quality parameters of the current batch of sewage, and the sludge mass of the current batch of sewage into the second prediction model to obtain the water quality parameters of the effluent of the previous batch, the water intake of the current batch, and the treatment time of the current batch of sewage;

[0019] The second prediction model is trained based on the second sample data and the second label; the second sample data includes sample attribute information of the third batch of sewage, sample water quality parameters of the fourth batch of sewage, and sample sludge mass of the fourth batch of sewage;

[0020] The second label includes the water quality parameters of the effluent of the third batch, the water intake of the fourth batch, and the treatment time of the sewage of the fourth batch; the fourth batch is the next batch after the third batch.

[0021] In one possible implementation, determining a first dosage of a drug for a current batch of sewage and a first operating parameter of at least one treatment device based on effluent water quality parameters, influent volume, treatment time, attribute information, first treatment information, and resource allocation information includes:

[0022] Inputting the effluent water quality parameters, influent volume, treatment time, attribute information, first treatment information, and resource allocation information into a third prediction model to obtain a first dosage of a drug for a current batch of sewage and a first operating parameter of at least one treatment device;

[0023] The third prediction model is trained based on the third sample data and the third label; the third sample data includes sample water quality parameters of the fifth batch of effluent, the sample water volume of the sixth batch, the sample processing time of the sixth batch of sewage, sample attribute information of the fifth batch of sewage, first processing information of the fifth batch of sewage, and sample resource configuration information of the sixth batch;

[0024] The third label includes the first dosage of the sixth batch of sewage and the first operating parameters of at least one device; the sixth batch is the next batch of the fifth batch.

[0025] In one possible implementation, the at least one treatment device includes a first device and a second device; and based on the second treatment information, controlling the at least one treatment device to treat the current batch of sewage includes:

[0026] Controlling the first device to inject the agent into the current batch of sewage according to the first injection amount;

[0027] According to the first operating parameter, the second device is controlled to process the current batch of sewage.

[0028] In one possible implementation, the method further includes:

[0029] determining whether the sludge mass of the current batch of sewage is greater than or equal to a preset threshold;

[0030] When the sludge mass of the current batch of sewage is greater than or equal to a preset threshold, a prompt message is sent to the client; the prompt message is used to prompt that the sludge mass of the current batch of sewage is greater than or equal to the preset threshold.

[0031] In a second aspect, an embodiment of the present application provides a sewage treatment device, the device comprising:

[0032] an acquisition module, configured to acquire attribute information of a previous batch of sewage in the container, first treatment information of the previous batch of sewage, and resource allocation information;

[0033] a determination module, configured to determine the water inflow of a current batch of the container and second treatment information of the current batch of sewage based on the attribute information, the first treatment information, and the resource allocation information;

[0034] A control module controls water inflow into the container based on the water inflow volume of the current batch;

[0035] The processing module controls at least one processing device to process the current batch of sewage based on the second processing information.

[0036] In a possible implementation, the determination module is specifically configured to:

[0037] Based on the attribute information, the water quality parameters of the previous batch of effluent, the water volume of the current batch, and the treatment time of the current batch of sewage are determined; the effluent is obtained after the sewage of the previous batch is treated;

[0038] Determining a first dosage of a chemical for a current batch of sewage and first operating parameters of at least one treatment device based on effluent water quality parameters, influent volume, treatment time, attribute information, first treatment information, and resource allocation information;

[0039] The second processing information includes the first dosage and the first operating parameter.

[0040] In a possible implementation, the determination module is specifically configured to:

[0041] Inputting the attribute information into a first prediction model to obtain water quality parameters of a current batch of sewage and sludge mass of the current batch of sewage; wherein the first prediction model is trained based on the first sample data and the first label; the first sample data includes sample attribute information of the first batch of sewage; the first label includes water quality parameters of a second batch of sewage and sludge mass of the second batch of sewage; and the second batch is the next batch after the first batch;

[0042] According to the attribute information, the water quality parameters of the current batch of sewage and the sludge quality of the current batch of sewage, the water quality parameters of the previous batch of effluent, the water intake of the current batch and the treatment time of the current batch of sewage are obtained.

[0043] In a possible implementation, the determination module is specifically configured to:

[0044] Inputting the attribute information, the water quality parameters of the current batch of sewage, and the sludge mass of the current batch of sewage into the second prediction model to obtain the water quality parameters of the effluent of the previous batch, the water intake of the current batch, and the treatment time of the current batch of sewage;

[0045] The second prediction model is trained based on the second sample data and the second label; the second sample data includes sample attribute information of the third batch of sewage, sample water quality parameters of the fourth batch of sewage, and sample sludge mass of the fourth batch of sewage;

[0046] The second label includes the water quality parameters of the effluent of the third batch, the water intake of the fourth batch, and the treatment time of the sewage of the fourth batch; the fourth batch is the next batch after the third batch.

[0047] In a possible implementation, the determination module is specifically configured to:

[0048] Inputting the effluent water quality parameters, influent volume, treatment time, attribute information, first treatment information, and resource allocation information into a third prediction model to obtain a first dosage of a drug for a current batch of sewage and a first operating parameter of at least one treatment device;

[0049] The third prediction model is trained based on the third sample data and the third label; the third sample data includes sample water quality parameters of the fifth batch of effluent, the sample water volume of the sixth batch, the sample processing time of the sixth batch of sewage, sample attribute information of the fifth batch of sewage, first processing information of the fifth batch of sewage, and sample resource configuration information of the sixth batch;

[0050] The third label includes the first dosage of the sixth batch of sewage and the first operating parameters of at least one device; the sixth batch is the next batch of the fifth batch.

[0051] In a possible implementation, the at least one processing device includes a first device and a second device; the processing module is specifically configured to:

[0052] Controlling the first device to inject the agent into the current batch of sewage according to the first injection amount;

[0053] According to the first operating parameter, the second device is controlled to process the current batch of sewage.

[0054] In a possible implementation, the device further includes a prompt module, which is specifically configured to:

[0055] determining whether the sludge mass of the current batch of sewage is greater than or equal to a preset threshold;

[0056] When the sludge mass of the current batch of sewage is greater than or equal to a preset threshold, a prompt message is sent to the client; the prompt message is used to prompt that the sludge mass of the current batch of sewage is greater than or equal to the preset threshold.

[0057] In a third aspect, an embodiment of the present application provides an electronic device, comprising: a memory, a processor;

[0058] Memory stores computer-executable instructions;

[0059] The processor executes the computer-executable instructions stored in the memory, so that the processor executes the above first aspect and / or various possible implementations of the first aspect.

[0060] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, in which computer-executable instructions are stored. When the computer-executable instructions are executed by a processor, they are used to implement the first aspect above and / or various possible implementation methods of the first aspect.

[0061] The sewage treatment method, device, electronic device and storage medium provided in the embodiment of the present application determine the water intake of the current batch and the second treatment information of the current batch of sewage based on the attribute information of the previous batch of sewage, the treatment information of the previous batch of sewage and the resource allocation information, and then treat the current batch of sewage according to the second treatment information. In this way, the amount of the drug added when treating different sewage and the operating parameters of at least one treatment device can be adaptively adjusted according to the conditions of different batches of sewage, thereby improving the flexibility of sewage treatment. The sewage treatment method provided in the embodiment of the present application can also determine the water intake of the current batch, accurately control the water intake of the container in the current batch, and avoid excessive sewage pollution in the container due to a large water intake. In addition, the second treatment information is determined in combination with the resource allocation information of the current batch of sewage. In this way, the relevant parameters for treating the current batch of sewage can be determined under the set resource limit, saving sewage treatment costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0062] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0063] Figure 1 A schematic diagram of an application scenario provided in an embodiment of the present application;

[0064] Figure 2 A schematic flow chart of a sewage treatment method provided in this application;

[0065] Figure 3 A schematic diagram of a process for determining the water intake volume of a current batch and second processing information provided in an embodiment of the present application;

[0066] Figure 4 A schematic diagram of a process for controlling at least one treatment device to treat a current batch of sewage provided in an embodiment of the present application;

[0067] Figure 5An architectural diagram of a sewage treatment system provided in an embodiment of the present application;

[0068] Figure 6 A schematic structural diagram of a sewage treatment device provided in an embodiment of the present application;

[0069] Figure 7 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application.

[0070] The above drawings illustrate specific embodiments of the present application, which will be described in more detail below. These drawings and the textual description are not intended to limit the scope of the present application in any way, but rather to illustrate the concepts of the present application to those skilled in the art by reference to specific embodiments. DETAILED DESCRIPTION

[0071] Exemplary embodiments will be described in detail herein, with examples illustrated in the accompanying drawings. In the following description, when referring to the drawings, identical numerals in different figures represent identical or similar elements, unless otherwise indicated. The embodiments described in the following exemplary embodiments are not intended to represent all embodiments consistent with the present application. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the present application, as detailed in the appended claims.

[0072] For ease of understanding, the following Figure 1 , briefly describe the application scenarios used in the embodiments of this application.

[0073] Figure 1 A schematic diagram of an application scenario provided in an embodiment of the present application is shown in FIG. Figure 1 As shown, the system includes a container 11, a treatment device 12, a treatment device 13, a treatment device 14, and a server 15. The container 11 includes a sewage pool, the treatment device 12 is used to inject chemicals into the sewage in the container 11, the treatment devices 13 and 14 are used to treat the sewage in the container 11, and the server 15 is the background server of the sewage treatment system.

[0074] In actual application, the sewage treatment system includes the amount of medicine added by the treatment equipment 12 to the sewage in the container 11, the equipment operating parameters when the treatment equipment 13 treats the sewage, and the equipment operating parameters when the treatment equipment 14 treats the sewage. The equipment operating parameters include at least one item such as the start-up time, operating time, and operating speed of the equipment.

[0075] The server 15 can control the treatment equipment 12 to add the agent to the sewage in the container 11 according to the amount of medicine added to the sewage in the container 11 by the treatment equipment 12 in the sewage treatment system; the server 15 can control the treatment equipment 13 to treat the sewage in the container 11 according to the equipment operating parameters of the treatment equipment 13 in the sewage treatment system; the server 15 can control the treatment equipment 14 to treat the sewage in the container 11 according to the equipment operating parameters of the treatment equipment 14 in the sewage treatment system.

[0076] It should be noted that Figure 1 This is merely an example of an application scenario and is not intended to limit the application scenario used in this application.

[0077] SBR can treat sewage in multiple stages, including water inlet, chemical addition, anoxic conditions, aeration, sedimentation, and effluent, and each stage requires corresponding treatment equipment to complete the treatment of the sewage at that stage.

[0078] In related technologies, SBR can be implemented based on a PLC. Specifically, for each treatment device, the operating parameters of the treatment device and the amount of chemicals to be added during sewage treatment are set in advance. The PLC controls the treatment device to treat the sewage in the container based on the operating parameters of the treatment device. Based on the amount of chemicals added during sewage treatment, the PLC controls the device responsible for chemical addition to release chemicals into the sewage.

[0079] However, different batches of sewage may vary in terms of water quality, volume, and treatment environment. This can lead to different operating parameters and dosages of chemicals required by each treatment equipment when treating different batches of sewage. Therefore, the flexibility of using the above-mentioned sewage treatment method is limited.

[0080] The present application provides a sewage treatment method that can determine the water intake of the current batch and the relevant parameters for treating the current batch of sewage based on the attribute information of the previous batch of sewage, the dosage of at least one agent added to the previous batch of sewage, the equipment operating parameters of at least one treatment equipment for treating the previous batch of sewage, and the target power and / or target dosage when treating the current batch of sewage. Then, based on the water intake of the current batch, the water intake of the container is controlled to obtain the current batch of sewage in the container, and based on the relevant parameters for treating the current batch of sewage, at least one treatment equipment is controlled to treat the current batch of sewage. In this way, the dosage of the agent added when treating different sewage and the respective operating parameters of at least one treatment equipment can be adaptively adjusted according to the conditions of different batches of sewage, thereby improving the flexibility of sewage treatment.

[0081] The following specific embodiments describe in detail the technical solution of the present application and how the technical solution of the present application solves the above-mentioned technical problems. The following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be repeated in some embodiments. The embodiments of the present application will be described below in conjunction with the accompanying drawings.

[0082] Figure 2 A schematic diagram of a sewage treatment method provided for this application is available at Figure 2 , the method comprising:

[0083] S21. Obtaining attribute information of a previous batch of sewage in the container, first treatment information of the previous batch of sewage, and resource allocation information.

[0084] The executor of this application may be a background server of the sewage treatment system, or a sewage treatment device installed in the server. The sewage treatment device may be implemented through software, or through a combination of software and hardware.

[0085] The container is a reaction pool for sewage treatment. It includes a water inlet and a water outlet. The water inlet is used to allow sewage to flow into the container. After sewage treatment, the sewage in the container is treated to obtain clean water with water quality that meets the water quality standards. The water outlet is used to discharge the clean water that meets the water quality standards out of the container.

[0086] In some embodiments, the process of treating sewage includes multiple stages, which may include, for example, water intake, chemical addition, anoxic, aeration, sedimentation, and water discharge. Among them, the water intake stage refers to using treatment equipment to allow sewage to flow into the container through the water inlet of the container; the chemical addition stage refers to the addition of at least one chemical to the sewage in the container; the anoxic stage refers to the stage in the sewage treatment process where no air is introduced into the sewage to cause denitrification reaction; the aeration stage refers to the stage where air is introduced into the sewage to allow the sewage to fully contact with the air, increase the dissolved oxygen (DO), and cause nitrification reaction; the sedimentation stage refers to the stage where the sludge after sewage treatment is separated into layers by sedimentation and clean water; the water discharge stage refers to the stage where the clean water after sewage treatment is discharged from the container through the outlet.

[0087] Sewage treatment in the container is carried out in batches. Each batch of sewage flows into the container through the water inlet, undergoes treatment with chemicals, anoxic conditions, aeration, and sedimentation, and finally produces treated clean water. This clean water is then discharged from the container through the outlet. The previous batch of sewage refers to the previous batch of sewage.

[0088] In some embodiments, the attribute information of the previous batch of sewage includes water quality parameters of the previous batch of sewage, water volume parameters of the previous batch of sewage, and the ambient temperature of the previous batch of sewage. The water quality parameters of the previous batch of sewage are used to indicate the quality of the previous batch of sewage. For example, the water quality parameters may include chemical oxygen demand (COD), ammonia nitrogen (NH3-N), total phosphorus (TP), hydrogen ion concentration index (pH), water temperature, and other parameters of the sewage.

[0089] The water volume parameters of the previous batch of sewage may include, for example, the inlet volume, outlet volume, and sludge discharge volume of the previous batch of sewage. The ambient temperature of the previous batch of sewage may be, for example, the temperature of the air during the treatment of the previous batch of sewage.

[0090] During sewage treatment, each stage has corresponding treatment equipment for the chemical administration, anoxic phase, and aeration phase. The chemical administration equipment is used to administer chemicals to the sewage. The anoxic phase equipment, for example, creates an environment with low DO content and uniform sludge distribution during the sewage treatment process. The anoxic phase equipment, for example, can be a blender. The aeration phase equipment, for example, creates an environment with high DO content during the sewage treatment process. Therefore, the sewage treatment process involves at least one treatment equipment.

[0091] The first treatment information for the previous batch of sewage includes: the dosage of chemicals administered to the previous batch of sewage, and the equipment operating parameters of at least one treatment device for treating the previous batch of sewage. The dosage of chemicals administered to the previous batch of sewage refers to the dosage of at least one chemical administered to the previous batch of sewage; the equipment operating parameters may include, for example, at least one parameter such as the equipment's startup time, operating frequency, and operating duration.

[0092] For example, assuming that during the reagent injection stage, at least one reagent injected into the previous batch of sewage includes phosphate, caustic soda, and glucose, and at least one treatment device includes a mixer and a blower, the first treatment information of the previous batch of sewage is shown in Table 1:

[0093] Table 1:

[0094]

[0095] The first processing information indicates that the amount of phosphate added to the previous batch of sewage is 25 kg, and the amount of liquid alkali added to the previous batch of sewage is 100 kg; the amount of glucose added to the previous batch of sewage is 200 kg; the operating time of the mixer when treating the previous batch of sewage is 120 minutes, and the operating frequency is 20 Hz; the operating time of the fan when treating the previous batch of sewage is 180 minutes, and the operating frequency is 35 Hz.

[0096] In some embodiments, the attribute information and first treatment information of the previous batch of sewage in the container can be obtained through sensors and / or manual collection. In some embodiments, multiple pieces of attribute information and first treatment information of the previous batch of sewage can be periodically obtained, and then data cleaning can be performed on each of the multiple pieces of attribute information and first treatment information to obtain the final attribute information and first treatment information of the previous batch of sewage. This can improve the accuracy of the acquired attribute information and first treatment information of the previous batch of sewage.

[0097] In some embodiments, a data analysis algorithm can be used to analyze the attribute information of a previous batch of sewage and the first treatment information of the previous batch of sewage to determine the inherent correlation and regularity between the attribute information and the first treatment information, and to analyze the water quality change trends of the previous batch of sewage at various stages under different attribute information and different first treatment information. The data analysis algorithm may include, for example, time series analysis and correlation analysis.

[0098] Resource allocation information indicates the maximum amount of resources that can be consumed when treating the current batch of sewage. Resources used to treat the current batch of sewage may include, for example, electricity and medication dosage. Therefore, resource allocation information may include, for example, the maximum amount of electricity and / or the maximum amount of medication.

[0099] For example, assuming that the resource configuration information includes a maximum power consumption, and the maximum power consumption is 300 kWh, it means that when treating the current batch of sewage, the total power consumed by at least one treatment device must be less than or equal to 300 kWh.

[0100] S22. Determine the water intake of the current batch of the container and the second processing information of the current batch of sewage according to the attribute information, the first processing information, and the resource allocation information.

[0101] The container's current batch of water inflow refers to the volume of sewage flowing into the container through the water inlet during the current batch. The second processing information indicates the relevant parameters for treating the current batch of sewage. This second processing information may include, for example, the operating parameters of each treatment device during the treatment of the current batch of sewage, as well as the dosage of the chemical administered to the current batch of sewage.

[0102] Because the volume of each incoming and outgoing water batch is approximately 1 / 10 of the total container volume, the incoming water of the current batch will be fully mixed with the remaining 9 / 10 of the outgoing water from the previous batch in the container. Therefore, the second treatment information for the current batch of sewage can be determined based on the property information of the previous batch of sewage, the first treatment information of the previous batch of sewage, and the resource allocation information.

[0103] S23. Based on the water intake of the current batch, control the water intake of the container.

[0104] In some embodiments, the server controls the water inlet of the container by controlling the opening and closing of the water inlet. Based on the water inlet of the current batch, the method of controlling the water inlet of the container can be as follows: the closing time of the water outlet of the container in the previous batch is determined as the opening time of the water inlet of the container in the current batch. At the opening time of the water inlet, the server turns on the processing equipment, such as a pump, to flow the sewage into the container through the water inlet. The server monitors the liquid level of the container and determines the closing time of the pump based on the opening time of the water inlet, the liquid level of the container, and the water inlet of the current batch. Finally, the pump is turned off at the closing time of the pump.

[0105] It should be noted that when the pump is turned off, the volume of sewage in the container is basically the same as the amount of sewage entering the current batch.

[0106] S24. Based on the second processing information, control at least one processing device to process the current batch of sewage.

[0107] Because the second processing information indicates relevant parameters for processing the current batch of sewage, the server can determine the relevant parameters for processing the current batch of sewage based on the second processing information, and then control at least one processing device to process the current batch of sewage based on the relevant parameters for processing the current batch of sewage.

[0108] The sewage treatment method provided in an embodiment of the present application determines the water intake of a current batch and second treatment information for the current batch of sewage based on the sewage property information of a previous batch, the dosage of at least one agent added to the previous batch of sewage, the equipment operating parameters of at least one treatment device used to treat the previous batch of sewage, and resource allocation information. Based on the water intake of the current batch, the water intake of a container is controlled to obtain the current batch of sewage in the container. The at least one treatment device is then controlled to treat the current batch of sewage based on the relevant parameters for treating the current batch of sewage indicated by the second treatment information. This allows the dosage of the agent added and the operating parameters of the at least one treatment device to be adaptively adjusted for different sewage batches, thereby improving the flexibility of sewage treatment. The sewage treatment method provided in an embodiment of the present application also determines the water intake of the current batch and accurately controls the current batch of water intake to avoid excessive sewage contamination in the container due to a large current batch of water intake. Furthermore, by combining the second treatment information with the resource allocation information for the current batch of sewage, the relevant parameters for treating the current batch of sewage can be determined within a set resource limit, saving sewage treatment costs.

[0109] Based on the above embodiments, Figure 3 A method for determining the amount of water inflow of a current batch in a container and second processing information of the current batch of sewage according to the attribute information, the first processing information and the resource allocation information in the sewage treatment method is further described.

[0110] Figure 3 A flow chart of determining the water intake of the current batch and the second processing information provided in the embodiment of the present application. Figure 3 As shown, the process may include the following steps:

[0111] S31. Determine the water quality parameters of the effluent of the previous batch, the water intake of the current batch, and the treatment time of the current batch of sewage based on the attribute information; the effluent is obtained after the sewage of the previous batch is treated.

[0112] The water quality parameters of the effluent of the previous batch may include, for example, pH value, conductivity, COD, ammonia nitrogen content, total phosphorus, total alkalinity, nitrate content, nitrite content, sludge concentration, and total cyanide.

[0113] When the effluent quality meets the standards, the effluent is discharged from the container through the water outlet of the container. In some embodiments, the effluent quality meets the standards means that the effluent water quality parameters meet the following standards: pH value of the effluent is between 6.8-7.5, conductivity of the effluent is between 0-12500, thiocyanate content of the effluent is between 0-8 mg / L, COD of the effluent is between 0-250 mg / L, ammonia nitrogen content of the effluent is between 0-8 mg / L, total phosphorus content of the effluent is between 0.3-0.5 mg / L, total alkalinity of the effluent is between 200-350 mg / L, nitrite content of the effluent is between 0-1 mg / L, nitrate content of the effluent is between 0-5 mg / L, sludge concentration of the container is between 2-3 g / L, and total cyanide content of the effluent is between 0-5 mg / L.

[0114] The treatment duration of the current batch of sewage includes the duration of each stage of the treatment of the current batch of sewage. For example, assuming that the stages of the treatment of the current batch of sewage include the addition of chemicals, anoxic phase, aeration phase, and sedimentation phase, the treatment duration of the current batch of sewage includes the duration of the anoxic phase, the duration of the aeration phase, and the duration of the sedimentation phase.

[0115] In some embodiments, based on the attribute information, the water quality parameters of the effluent of the previous batch, the water intake of the current batch, and the treatment time of the current batch of sewage can be determined as follows: the attribute information is input into the first prediction model to obtain the water quality parameters of the current batch of sewage and the sludge quality of the current batch of sewage.

[0116] According to the attribute information, the water quality parameters of the current batch of sewage and the sludge quality of the current batch of sewage, the water quality parameters of the previous batch of effluent, the water intake of the current batch and the treatment time of the current batch of sewage are obtained.

[0117] The method for obtaining the water quality parameters of the effluent of the previous batch, the water intake of the current batch, and the treatment time of the current batch of sewage can be as follows: input the attribute information, the water quality parameters of the current batch of sewage, and the sludge mass of the current batch of sewage into the second prediction model to obtain the water quality parameters of the effluent of the previous batch, the water intake of the current batch, and the treatment time of the current batch of sewage.

[0118] The water quality parameters of the current batch of sewage are used to indicate the quality of the current batch of sewage. The sludge quality of the current batch of sewage is used to indicate the quality of the sludge in the sewage before sewage treatment. Sewage sludge quality can include, for example, COD sludge load parameters, ammonia nitrogen sludge load parameters, and total nitrogen sludge load parameters.

[0119] The first prediction model may include, for example, a Random Forest (RF) algorithm, a Long Short-Term Memory (LSTM) algorithm, or the like.

[0120] In some embodiments, the first prediction model is trained based on the first sample data and the first label; the first sample data includes the sample attribute information of the first batch of sewage; the first label includes the water quality parameters of the second batch of sewage and the sludge quality of the second batch of sewage; the second batch is the next batch of the first batch.

[0121] The sample attribute information may include sample water quality parameters, sample water volume parameters, and sample ambient temperature.

[0122] It should be noted that the first batch may include one or more batches. If the first batch includes one batch, the second batch also includes one batch, and the second batch is the batch following the first batch. If the first batch includes multiple batches, the second batch also includes multiple batches, and the number of batches included in the second batch is the same as the number of batches included in the first batch. For any batch in the first batch, the second batch contains the batch following it.

[0123] For example, the first batch includes batch 1, batch 2, batch 3 and batch 4, and the second batch includes batch 5, batch 6, batch 7 and batch 8. Batch 5 is the next batch after batch 1, batch 6 is the next batch after batch 2, batch 7 is the next batch after batch 3, and batch 8 is the next batch after batch 4.

[0124] The first sample data includes the sample water quality parameters of the sewage of batch 1, the sample water quantity parameters of the sewage of batch 1, and the sample ambient temperature of the sewage of batch 1; the sample water quality parameters of the sewage of batch 2, the sample water quantity parameters of the sewage of batch 2, and the sample ambient temperature of the sewage of batch 2; the sample water quality parameters of the sewage of batch 3, the sample water quantity parameters of the sewage of batch 3, and the sample ambient temperature of the sewage of batch 3; the sample water quality parameters of the sewage of batch 4, the sample water quantity parameters of the sewage of batch 4, and the sample ambient temperature of the sewage of batch 4.

[0125] The first label includes the water quality parameters of the sewage of batch 5 and the sludge quality of the sewage of batch 5; the water quality parameters of the sewage of batch 6 and the sludge quality of the sewage of batch 6; the water quality parameters of the sewage of batch 7 and the sludge quality of the sewage of batch 7; the water quality parameters of the sewage of batch 8 and the sludge quality of the sewage of batch 8.

[0126] During a training cycle of the first prediction model, the server may input the first sample data into the first prediction model, process the first sample data using the first prediction model, and obtain outputs from the first prediction model of the water quality parameter predicted values ​​for the second batch of sewage and the sludge mass predicted values ​​for the second batch of sewage. Then, based on the predicted water quality parameter predicted values ​​for the second batch of sewage, the predicted sludge mass predicted values ​​for the second batch of sewage, and the first label, a loss value is calculated, and the model parameters of the first prediction model are adjusted based on the calculated loss value, thereby completing one round of training.

[0127] The server can perform one or more rounds of training on the first prediction model until a training termination condition for the first prediction model is met. The training process is then terminated to obtain a trained first prediction model. The training termination condition can be set based on actual needs. For example, the training termination condition can be set to a loss value less than or equal to a preset loss value, or to a training cycle reaching a preset number of times. The trained first prediction model is capable of determining the water quality parameters and sludge quality of the current batch of sewage based on the attribute information of the previous batch of sewage.

[0128] In some embodiments, it can be determined whether the sludge mass of the current batch of sewage is greater than or equal to a preset threshold; if the sludge mass of the current batch of sewage is greater than or equal to the preset threshold, a prompt message is sent to the client, and the prompt message is used to prompt that the sludge mass of the current batch of sewage is greater than or equal to the preset threshold.

[0129] If the sludge mass of the current batch of sewage is greater than or equal to a preset threshold, it indicates that the current batch of sewage has exceeded the pollution standard. In this case, to avoid accidents during the sewage treatment process of the current batch of sewage, the sludge of the current batch of sewage in the container needs to be treated. Therefore, if the sludge mass of the current batch of sewage is greater than or equal to the preset threshold, the server sends a prompt message to the client, indicating that the current batch of sewage has exceeded the pollution standard. The client can be, for example, a client of a sewage treatment system.

[0130] In some embodiments, since the sludge quality of the current batch of sewage includes at least one parameter, a treatment method for the sludge of the current batch of sewage can be determined based on the parameter of the at least one parameter that is greater than or equal to a preset threshold. The server then sends the treatment method and prompt information to the client.

[0131] In some embodiments, the client may include a first client and a second client, and the level of the first client is higher than that of the second client; the preset threshold may include a first preset threshold and a second preset threshold, and the first preset threshold is greater than the second preset threshold.

[0132] When the sludge mass of the current batch of sewage is greater than or equal to the second preset threshold, and the sludge mass of the current batch of sewage is less than the first preset threshold, it means that the pollution of the current batch of sewage does not exceed the standard seriously. At this time, the server will send a prompt message to the second client; when the sludge mass of the current batch of sewage is greater than or equal to the first preset threshold, it means that the pollution of the current batch of sewage exceeds the standard seriously. At this time, the server will send a prompt message to the first client.

[0133] In some embodiments, the second prediction model is trained based on the second sample data and the second label; wherein the second sample data includes the sample attribute information of the third batch of sewage, the sample water quality parameters of the fourth batch of sewage, and the sample sludge quality of the fourth batch of sewage; the second label includes the water quality parameters of the effluent of the third batch, the water intake of the fourth batch, and the processing time of the fourth batch of sewage; the fourth batch is the next batch of the third batch.

[0134] It should be noted that the third batch may include one or more batches. If the third batch includes one batch, the fourth batch also includes one batch, and the fourth batch is the batch following the third batch. If the third batch includes multiple batches, the fourth batch also includes multiple batches, and the number of batches included in the fourth batch is the same as the number of batches included in the third batch. For any batch in the third batch, the fourth batch contains the batch following it.

[0135] The second prediction model, for example, can be a nitrification and denitrification kinetic model. This model calculates and monitors the conversion of ammonia nitrogen in the wastewater to nitrates through anoxic reactions and the conversion of nitrates to nitrogen gas through aerobic reactions during the aeration phase. This model determines the water quality parameters of the previous batch of effluent, the current batch of influent volume, and the treatment time for the current batch of wastewater.

[0136] During a training cycle of the second prediction model, the server may input the second sample data into the second prediction model, process the second sample data using the second prediction model, and obtain outputs from the second prediction model of the water quality parameter predictions for the third batch of effluent, the water inflow predictions for the fourth batch, and the treatment time predictions for the fourth batch of sewage. The server then calculates a loss value based on the water quality parameter predictions for the third batch of effluent, the water inflow predictions for the fourth batch, the treatment time predictions for the fourth batch of sewage, and the second label, and adjusts the model parameters of the second prediction model based on the calculated loss value, thereby completing one round of training.

[0137] The server can perform one or more rounds of training on the second prediction model until the training termination condition of the second prediction model is reached, and then stop the training process to obtain a trained second prediction model. The training termination condition can be set according to actual needs. For example, the training termination condition can be set to a loss value less than or equal to a preset loss value, or the training termination condition can be set to a preset number of training times, etc. The trained second prediction model has the ability to obtain the water quality parameters of the previous batch of effluent, the water inflow of the current batch, and the treatment time of the current batch of sewage based on the attribute information of the previous batch of sewage, the water quality parameters of the current batch of sewage, and the sludge quality of the current batch of sewage.

[0138] S32. Determine a first dosage of the sewage for the current batch and first operating parameters of at least one treatment device based on the effluent water quality parameters, the influent volume, the treatment time, the attribute information, the first treatment information, and the resource allocation information.

[0139] The second treatment information includes a first dosage amount and a first operating parameter. The first dosage amount includes the dosage of at least one agent administered to the current batch of sewage, and the first operating parameter includes the operating parameter of at least one device when treating the current batch of sewage.

[0140] For example, assume that at least one reagent administered to the current batch of sewage includes liquid caustic soda, phosphate salt, and glucose, and that the at least one treatment equipment used to treat the current batch of sewage includes a mixer and a fan. The amount of phosphate salt administered to the current batch of sewage is 30 kg; the amount of liquid caustic soda administered to the current batch of sewage is 200 kg; and the amount of glucose administered to the current batch of sewage is 200 kg. The operating parameters for the mixer include: a running time of 150 minutes and a running speed of 20 Hz; and the operating parameters for the fan include: a running time of 180 minutes and a running speed of 38 Hz. The second processing information can then be shown in Table 2:

[0141] Table 2

[0142]

[0143] The first dosage of chemicals for the current batch of sewage and the first operating parameters of at least one treatment equipment can be determined based on the effluent water quality parameters, water inlet volume, treatment time, attribute information, first treatment information and resource allocation information in the following manner: the effluent water quality parameters, water inlet volume, treatment time, attribute information, first treatment information and resource allocation information are input into the third prediction model to obtain the first dosage of chemicals for the current batch of sewage and the first operating parameters of at least one treatment equipment.

[0144] The third prediction model may include, for example, a genetic algorithm (GA) or the least squares method. In some embodiments, the third prediction model is trained based on third sample data and third labels. The third sample data includes water quality parameters of the fifth batch of effluent, the sixth batch of sample inflow, the sixth batch of wastewater sample processing time, sample attribute information of the fifth batch of wastewater, first treatment information of the fifth batch of wastewater samples, and resource allocation information of the sixth batch of samples. The third label includes the first dosage of the drug for the sixth batch of wastewater and the first operating parameters of at least one device. The sixth batch is the next batch after the fifth batch.

[0145] It should be noted that the fifth batch may include one or more batches. If the fifth batch includes one batch, the sixth batch also includes one batch, and the sixth batch is the batch following the fifth batch. If the fifth batch includes multiple batches, the sixth batch also includes multiple batches, and the number of batches included in the sixth batch is the same as the number of batches included in the fifth batch. For any batch in the fifth batch, the sixth batch contains the batch following it.

[0146] During a single training cycle of the third prediction model, the server may input the third sample data into the third prediction model, process the third sample data using the third prediction model, and obtain outputs from the third prediction model, including a first dose prediction value for the sixth batch of sewage and a first operating parameter prediction value for at least one device. The server then calculates a loss value based on the first dose prediction value for the sixth batch of sewage, the first operating parameter prediction value for at least one device, and the third label, and adjusts the model parameters of the third prediction model based on the calculated loss value, thereby completing one round of training.

[0147] The server can perform one or more rounds of training on the third prediction model until the training termination condition of the third prediction model is reached, and then stop the training process to obtain a trained third prediction model. The training termination condition can be set according to actual needs. For example, the training termination condition can be set to a loss value less than or equal to a preset loss value, or the training termination condition can be set to a preset number of training times, etc. The trained third prediction model has the ability to determine the first dosage of the drug for the current batch of sewage and the first operating parameters of at least one treatment equipment based on the water quality parameters of the effluent, the water intake, the treatment time, the attribute information, the first treatment information, and the resource allocation information.

[0148] exist Figure 3In the embodiment shown, the water quality parameters of the previous batch of sewage, the water volume parameters of the previous batch of sewage, and the ambient temperature of the previous batch of sewage are first input into the first prediction model to obtain the water quality parameters of the current batch of sewage and the sludge mass of the current batch of sewage; then the water quality parameters of the previous batch of sewage, the water volume parameters of the previous batch of sewage, the ambient temperature of the previous batch of sewage, the water quality parameters of the current batch of sewage, and the sludge mass of the current batch of sewage are input into the second prediction model to obtain the water quality parameters of the effluent of the previous batch, the water inflow of the current batch, and the treatment time of the current batch of sewage; finally, the water quality parameters of the effluent, the water inflow, the treatment time, attribute information, the first treatment information, and the resource allocation information are input into the third prediction model to obtain the first dosage of the current batch of sewage and the first operating parameters of at least one treatment equipment, thereby improving the accuracy of determining the first dosage of the current batch of sewage and the first operating parameters of at least one treatment equipment.

[0149] Based on the above embodiments, Figure 4 The method of controlling at least one treatment device to treat the current batch of sewage based on the second treatment information in the embodiment of the present application is further explained.

[0150] Figure 4 A schematic diagram of a process for controlling at least one treatment device to treat the current batch of sewage provided in an embodiment of the present application is provided. Figure 4 , the process may include the following steps:

[0151] S41. Control the first device to add a chemical to the current batch of sewage according to the first dosage.

[0152] The at least one device for treating the current batch of sewage includes: a first device and a second device. The first device is used to administer a chemical to the current batch of sewage, and may be, for example, a chemical administration device; the second device is used to treat the current batch of sewage, and may include, for example, a mixer, a fan, or the like.

[0153] In some embodiments, the first device adds at least one agent to the current batch of sewage. For each agent, the server can control the first device to add the agent to the current batch of sewage according to the amount of the agent in the first added amount.

[0154] For example, assume that the first device is a chemical dosing device, and the chemical dosing device delivers phosphate salt, liquid caustic soda, and glucose to the current batch of sewage. The first dosage includes: 30 kg of phosphate salt, 200 kg of liquid caustic soda, and 200 kg of glucose. Then, the server controls the chemical dosing device to deliver 30 kg of phosphate salt to the current batch of sewage; the server controls the chemical dosing device to deliver 200 kg of liquid caustic soda to the current batch of sewage; and the server controls the chemical dosing device to deliver 200 kg of glucose to the current batch of sewage.

[0155] S42. Control the second device to process the current batch of sewage according to the first operating parameter.

[0156] The first operating parameters include equipment operating parameters when the second equipment processes the current batch of sewage.

[0157] For example, assuming that the second device includes a mixer and a fan, the first operating parameters may be as shown in Table 3:

[0158] Table 3

[0159]

[0160] The server controls the mixer to process the current batch of sewage at a running rate of 20 Hz and a running time of 150 minutes; the server controls the fan to process the current batch of sewage at a running rate of 38 Hz and a running time of 180 minutes.

[0161] exist Figure 4 In the illustrated embodiment, the server controls the first device to administer a reagent to the current batch of sewage based on the dosage administered to the current batch of sewage, and the server controls the second device to treat the sewage based on the operating parameters of at least one treatment device used to treat the current batch of sewage. The dosage of the administered reagent and the operating parameters of the at least one device used to treat the current batch of sewage are determined based on parameters such as the water quality of the current batch of sewage, thereby increasing the flexibility of sewage treatment. Furthermore, the dosage of the administered reagent is less than or equal to the specified maximum dosage, and the amount of electricity consumed by the at least one treatment device during treatment of the current batch of sewage is less than or equal to the specified maximum electricity, thereby saving sewage treatment costs.

[0162] Based on the above embodiments, a sewage treatment system provided in an embodiment of the present application is introduced below.

[0163] Figure 5 For a diagram of the sewage treatment system provided in this application embodiment, please see Figure 5The sewage treatment system includes platform support layer, data layer, production management layer and intelligent decision-making layer.

[0164] Among them, the platform support layer is used to provide communication infrastructure, data processing resources, data intelligent analysis, device interconnection and other functions; the platform support layer may include at least one of the following: fifth-generation mobile communication technology (5th Generation, 5G), industrial big data, industrial Internet of Things, cloud platform, artificial intelligence, etc.

[0165] The data layer is used to implement functions such as data collection and preprocessing, data storage and management, data analysis and mining, and data visualization. The data layer can include data sources and data functions. Data sources are mainly used to implement data acquisition methods, which can include manual input, distributed control systems (DCS), file import, mobile devices, PLCs, and other application systems. Data functions are mainly used to implement data acquisition, data storage, data query, data processing, data change trends, historical data, data security, and data usage.

[0166] The production management layer is used to realize the planning and scheduling, equipment management, process management, personnel management, and safety management functions of sewage treatment; the production management layer can include process monitoring, energy consumption management, drug consumption management, alarm management, batch analysis, report generation, configuration analysis and other functional components.

[0167] The intelligent decision-making layer is used to realize functions such as decision support, decision customization, risk warning and response, performance evaluation and continuous improvement; the intelligent decision-making layer can include functional components such as automated control, intelligent optimization, production guidance, alarm post-processing, and intelligent evaluation.

[0168] In some embodiments, the intelligent decision-making layer can control the first device to add a drug to the current batch of sewage according to the first dosage; and control the second device to process the current batch of sewage according to the first operating parameters.

[0169] In some embodiments, the sewage treatment system includes a visual interface so that operators can monitor the status of the sewage during the sewage treatment process and the operating status of at least one treatment equipment in real time.

[0170] exist Figure 5 In the illustrated embodiment, the sewage treatment system provided by the present application is primarily composed of a platform support layer, a data layer, a production management layer, and an intelligent decision-making layer. This system enables intelligent management, precise control, and flexible treatment of sewage treatment, improving its flexibility and reducing its costs.

[0171] Figure 6For a schematic diagram of the structure of a sewage treatment device provided in an embodiment of the present application, see Figure 6 The sewage treatment device 60 provided in the embodiment of the present application includes:

[0172] an acquisition module 61 for acquiring attribute information of a previous batch of sewage in the container, first treatment information of the previous batch of sewage, and resource allocation information;

[0173] a determination module 62 for determining the amount of water inflow of a current batch of the container and second treatment information of the current batch of sewage based on the attribute information, the first treatment information, and the resource allocation information;

[0174] A control module 63 controls water inflow into the container based on the water inflow of the current batch;

[0175] The processing module 64 controls at least one processing device to process the current batch of sewage based on the second processing information.

[0176] In a possible implementation, the determination module 62 is specifically configured to:

[0177] Based on the attribute information, the water quality parameters of the previous batch of effluent, the water volume of the current batch, and the treatment time of the current batch of sewage are determined; the effluent is obtained after the sewage of the previous batch is treated;

[0178] Determining a first dosage of a chemical for a current batch of sewage and first operating parameters of at least one treatment device based on effluent water quality parameters, influent volume, treatment time, attribute information, first treatment information, and resource allocation information;

[0179] The second processing information includes the first dosage and the first operating parameter.

[0180] In a possible implementation, the determination module 62 is specifically configured to:

[0181] Inputting the attribute information into a first prediction model to obtain water quality parameters of a current batch of sewage and sludge mass of the current batch of sewage; wherein the first prediction model is trained based on the first sample data and the first label; the first sample data includes sample attribute information of the first batch of sewage; the first label includes water quality parameters of a second batch of sewage and sludge mass of the second batch of sewage; and the second batch is the next batch after the first batch;

[0182] According to the attribute information, the water quality parameters of the current batch of sewage and the sludge quality of the current batch of sewage, the water quality parameters of the previous batch of effluent, the water intake of the current batch and the treatment time of the current batch of sewage are obtained.

[0183] In a possible implementation, the determination module 62 is specifically configured to:

[0184] Inputting the attribute information, water quality parameters of the current batch of sewage, and sludge mass of the current batch of sewage into the second prediction model to obtain the water quality parameters of the effluent of the previous batch, the water intake of the current batch, and the treatment time of the current batch of sewage; wherein the second prediction model is trained based on the second sample data and the second label; the second sample data includes sample attribute information of the third batch of sewage, sample water quality parameters of the fourth batch of sewage, and sample sludge mass of the fourth batch of sewage;

[0185] The second label includes the water quality parameters of the effluent of the third batch, the water intake of the fourth batch, and the treatment time of the sewage of the fourth batch; the fourth batch is the next batch after the third batch.

[0186] In a possible implementation, the determination module 62 is specifically configured to:

[0187] Inputting the effluent water quality parameters, influent volume, treatment time, attribute information, first treatment information, and resource allocation information into a third prediction model to obtain a first dosage of a drug for a current batch of sewage and a first operating parameter of at least one treatment device;

[0188] The third prediction model is trained based on the third sample data and the third label; the third sample data includes sample water quality parameters of the fifth batch of effluent, the sample water volume of the sixth batch, the sample processing time of the sixth batch of sewage, sample attribute information of the fifth batch of sewage, first processing information of the fifth batch of sewage, and sample resource configuration information of the sixth batch;

[0189] The third label includes the first dosage of the sixth batch of sewage and the first operating parameters of at least one device; the sixth batch is the next batch of the fifth batch.

[0190] In a possible implementation, the at least one processing device includes a first device and a second device; the processing module 64 is specifically configured to:

[0191] Controlling the first device to inject the agent into the current batch of sewage according to the first injection amount;

[0192] According to the first operating parameter, the second device is controlled to process the current batch of sewage.

[0193] In a possible implementation, the device further includes a prompt module, which is specifically configured to:

[0194] determining whether the sludge mass of the current batch of sewage is greater than or equal to a preset threshold;

[0195] When the sludge mass of the current batch of sewage is greater than or equal to a preset threshold, a prompt message is sent to the client; the prompt message is used to prompt that the sludge mass of the current batch of sewage is greater than or equal to the preset threshold.

[0196] The sewage treatment device 60 provided in this embodiment can execute the sewage treatment method provided in the above method embodiment. Its implementation principle and technical effects are similar, and will not be described in detail in this embodiment.

[0197] Figure 7 For a schematic diagram of the structure of an electronic device provided in an embodiment of the present application, see Figure 7 The electronic device 70 provided in this embodiment includes: at least one processor 701 and a memory 702. The processor 701 and the memory 702 are connected via a bus 703.

[0198] During the specific implementation process, at least one processor 701 executes the computer-executable instructions stored in the memory 702, so that the at least one processor 701 performs the above method.

[0199] The specific implementation process of the processor 701 can be found in the above method embodiment. Its implementation principle and technical effects are similar and will not be repeated here in this embodiment.

[0200] In the above embodiments, it should be understood that the processor may be a central processing unit (CPU), other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASICs), etc. A general-purpose processor may be a microprocessor or any conventional processor. The steps of the method disclosed in the present invention may be directly executed by a hardware processor or by a combination of hardware and software modules within the processor.

[0201] The memory may include random access memory (RAM) and may also include non-volatile memory (NVM), such as at least one disk storage.

[0202] A bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus. Buses can be categorized as address buses, data buses, and control buses. For ease of illustration, the buses in the drawings of this application are not limited to just one bus or just one type of bus.

[0203] The present application also provides a computer program product, including a computer program, which implements the above-mentioned sewage treatment method when executed by a processor.

[0204] The present application also provides a computer-readable storage medium, in which computer-executable instructions are stored. When a processor executes the computer-executable instructions, the above-mentioned sewage treatment method is implemented.

[0205] The readable storage medium may be implemented by any type of volatile or non-volatile memory device, or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk. The readable storage medium may be any available medium that can be accessed by a general-purpose or special-purpose computer.

[0206] An exemplary readable storage medium is coupled to a processor so that the processor can read information from the readable storage medium and write information to the readable storage medium. Of course, the readable storage medium can also be an integral part of the processor. The processor and the readable storage medium can be located in an application specific integrated circuit (ASIC). Of course, the processor and the readable storage medium can also exist in the device as discrete components.

[0207] The division of units is merely a logical functional division; actual implementations may employ alternative divisions, such as combining or integrating multiple units or components into another system, or omitting or disabling certain features. Furthermore, any direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection between devices or units, either through an interface, electrical, mechanical, or other means.

[0208] Units described as separate components may or may not be physically separate, and components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0209] 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.

[0210] If a function is implemented as 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, or the portion that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the various embodiments of the method of the present invention. The aforementioned storage medium includes various media that can store program code, such as USB flash drives, mobile hard drives, read-only memories (ROMs), random access memories (RAMs), magnetic disks, or optical disks.

[0211] Those skilled in the art will appreciate that all or part of the steps in the above-described method embodiments can be implemented using hardware associated with program instructions. The aforementioned program can be stored in a computer-readable storage medium. When executed, the program performs the steps of the above-described method embodiments. The aforementioned storage medium includes various media capable of storing program code, such as ROM, RAM, magnetic disks, or optical disks.

[0212] Finally, it should be noted that those skilled in the art will readily identify other embodiments of the present invention after considering the specification and practicing the invention disclosed herein. The present invention is intended to cover any variations, uses, or adaptations of the present invention that follow the general principles of the present invention and include common knowledge or customary techniques in the art not disclosed herein. The present invention is not limited to the precise structure described above and illustrated in the accompanying drawings, and various modifications and variations may be made without departing from the scope thereof. The scope of the present invention is limited solely by the appended claims.

Claims

1. A sewage treatment method, characterized in that: Applied to a server, the method includes: Acquiring attribute information of a previous batch of sewage in the container, first treatment information of the previous batch of sewage, and resource allocation information; Determining a current batch of water inflow into the container and second processing information of the current batch of sewage based on the attribute information, the first processing information, and the resource allocation information; controlling water inflow into the container based on the water inflow of the current batch; Based on the second processing information, at least one processing device is controlled to process the current batch of sewage.

2. The method according to claim 1, characterized in that Determining the amount of water in the current batch in the container and second processing information of the current batch of sewage according to the attribute information, the first processing information, and the resource allocation information, including: Determining, based on the attribute information, water quality parameters of the effluent of the previous batch, the water intake of the current batch, and the treatment time of the current batch of sewage; the effluent is obtained after sewage treatment of the previous batch of sewage; Determining a first dosage of a drug for the current batch of sewage and a first operating parameter of the at least one treatment device based on the effluent water quality parameter, the influent volume, the treatment time, the attribute information, the first treatment information, and the resource allocation information; The second processing information includes the first dosage and the first operating parameter.

3. The method according to claim 2, characterized in that Determining, based on the attribute information, the water quality parameters of the previous batch of effluent, the water intake of the current batch, and the treatment time of the current batch of sewage, including: Inputting the attribute information into a first prediction model to obtain water quality parameters of the current batch of sewage and sludge mass of the current batch of sewage; wherein the first prediction model is trained based on first sample data and a first label; the first sample data includes sample attribute information of the first batch of sewage; the first label includes water quality parameters of the second batch of sewage and sludge mass of the second batch of sewage; the second batch is the next batch after the first batch; According to the attribute information, the water quality parameters of the current batch of sewage and the sludge quality of the current batch of sewage, the water quality parameters of the effluent of the previous batch, the water intake of the current batch and the treatment time of the current batch of sewage are obtained.

4. The method according to claim 3, characterized in that The step of obtaining the water quality parameters of the effluent of the previous batch, the water intake of the current batch, and the treatment time of the current batch of sewage based on the attribute information, the water quality parameters of the current batch of sewage, and the sludge mass of the current batch of sewage includes: Inputting the attribute information, the water quality parameters of the current batch of sewage, and the sludge mass of the current batch of sewage into a second prediction model to obtain the water quality parameters of the effluent of the previous batch, the water intake of the current batch, and the treatment time of the current batch of sewage; The second prediction model is trained based on the second sample data and the second label; the second sample data includes sample attribute information of the third batch of sewage, sample water quality parameters of the fourth batch of sewage, and sample sludge mass of the fourth batch of sewage; The second label includes water quality parameters of the effluent of the third batch, the water intake of the fourth batch, and the treatment time of the sewage of the fourth batch; the fourth batch is the next batch after the third batch.

5. The method according to any one of claims 2 to 4, characterized in that: The determining, based on the effluent water quality parameter, the influent volume, the treatment time, the attribute information, the first treatment information, and the resource allocation information, of a first dosage of the sewage for the current batch and a first operating parameter of the at least one treatment device includes: Inputting the effluent water quality parameter, the influent volume, the treatment time, the attribute information, the first treatment information, and the resource allocation information into a third prediction model to obtain a first dosage of the drug for the current batch of sewage and a first operating parameter of the at least one treatment device; The third prediction model is trained based on the third sample data and the third label; the third sample data includes sample water quality parameters of the fifth batch of effluent, the sample water volume of the sixth batch, the sample processing time of the sixth batch of sewage, sample attribute information of the fifth batch of sewage, first processing information of the fifth batch of sewage, and sample resource configuration information of the sixth batch; The third label includes the first dosage of the sixth batch of sewage and the first operating parameter of the at least one device; the sixth batch is the next batch of the fifth batch.

6. The method according to any one of claims 2 to 4, characterized in that: The at least one treatment device includes a first device and a second device; and controlling the at least one treatment device to treat the current batch of sewage based on the second treatment information includes: controlling the first device to inject the agent into the current batch of sewage according to the first injection amount; According to the first operating parameter, the second device is controlled to process the current batch of sewage.

7. The method according to claim 3 or 4, characterized in that The method further comprises: Determining whether the sludge mass of the current batch of sewage is greater than or equal to a preset threshold; When the sludge mass of the current batch of sewage is greater than or equal to the preset threshold, a prompt message is sent to the client; the prompt message is used to prompt that the sludge mass of the current batch of sewage is greater than or equal to the preset threshold.

8. A sewage treatment device, characterized in that: Applied to a server, the device includes: an acquisition module, configured to acquire attribute information of a previous batch of sewage in the container, first treatment information of the previous batch of sewage, and resource allocation information; a determination module, configured to determine the water intake of a current batch of the container and second treatment information of the current batch of sewage based on the attribute information, the first treatment information, and the resource allocation information; a control module, configured to control water inflow into the container based on the water inflow of the current batch; The processing module controls at least one processing device to process the current batch of sewage based on the second processing information.

9. An electronic device, characterized in that: include: Memory, processor; The memory stores computer-executable instructions; The processor executes the computer-executable instructions stored in the memory, so that the processor performs the method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium stores computer-executable instructions, which are used to implement the method according to any one of claims 1 to 7 when executed by a processor.

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