A sewage treatment method, system, intelligent terminal and storage medium

Abstract

The application relates to a sewage treatment method and system, an intelligent terminal and a storage medium, and relates to the field of sewage treatment technology.The application comprises the following steps: obtaining an inflow trigger signal of a preset reaction tank; obtaining inflow detection parameters of the reaction tank based on the inflow trigger signal; determining a set dissolved oxygen concentration of the reaction tank based on similar historical data of a time difference time sequence model according to the inflow detection parameters and ideal outflow detection parameters; controlling a preset aeration device to aerate the reaction tank according to the set dissolved oxygen concentration; obtaining outflow detection parameters of the reaction tank; judging whether the outflow detection parameters meet the requirements of preset treatment detection parameters, and judging whether the set dissolved oxygen concentration is regenerated accordingly; and continuing to control the aeration device to aerate the reaction tank according to the regenerated set dissolved oxygen concentration.The application has the effects of improving sewage treatment efficiency and outflow water quality, and reducing sewage treatment cost.

Description

Technical Field

[0001] This application relates to the field of wastewater treatment technology, and in particular to a wastewater treatment method, system, smart terminal and storage medium. Background Technology

[0002] Wastewater treatment aims to purify polluted water through chemical or physical treatment before releasing it back into the natural environment, thereby reducing pollution.

[0003] Among related technologies, the activated sludge process is a commonly used technology in the field of wastewater treatment. Aeration is the key to ensuring the normal operation of the activated sludge wastewater treatment process. Aeration in the activated sludge process provides suitable dissolved oxygen for processes such as organic carbon removal, nitrification, and phosphorus uptake, so as to ensure the normal progress of the three biochemical reactions. At present, the dissolved oxygen concentration in the aerobic zone is usually determined by the operators based on their operating experience, and then a rough over-aeration control is carried out to ensure that the dissolved oxygen value in the aerobic zone is not lower than the set dissolved oxygen concentration, thereby ensuring the oxygen supply in the wastewater treatment process.

[0004] Regarding the aforementioned technologies, operators set the dissolved oxygen concentration to a relatively high value. However, when the influent load is low, excessive oxygen supply can cause severe over-aeration, wasting a large amount of electrical energy and resulting in high wastewater treatment costs. There is still room for improvement. Summary of the Invention

[0005] In order to reduce the cost of wastewater treatment, this application provides a wastewater treatment method, system, smart terminal and storage medium.

[0006] In a first aspect, this application provides a wastewater treatment method, which adopts the following technical solution:

[0007] A wastewater treatment method, comprising:

[0008] Obtain the water inlet trigger signal of the preset reaction tank;

[0009] The influent detection parameters of the reaction tank are obtained based on the influent trigger signal;

[0010] Based on the influent detection parameters and ideal effluent detection parameters, the set dissolved oxygen concentration of the reaction tank is determined using similar historical data from a dissolved oxygen concentration estimation model.

[0011] The preset aeration device is controlled to aerate the reaction tank according to the set dissolved oxygen concentration.

[0012] Obtain the effluent detection parameters of the reaction tank;

[0013] Determine whether the effluent detection parameters meet the preset treatment detection parameter requirements;

[0014] If the conditions are met, the aeration device will continue to aerate the reaction tank according to the set dissolved oxygen concentration, and the effluent detection parameters will continue to be acquired for cyclical judgment.

[0015] If it does not meet the requirements, the set dissolved oxygen concentration will be updated and regenerated based on the effluent detection parameters.

[0016] The aeration device continues to aerate the reaction tank based on the newly generated dissolved oxygen concentration.

[0017] By adopting the above technical solution, the influent trigger signal refers to the signal that sewage enters the reaction tank. This signal can be automatically collected by setting gate valve opening, flow rate, or pressure sensors. Based on the influent detection parameters, the set dissolved oxygen concentration for sewage treatment is quickly and accurately determined. Then, the aeration device is controlled to aerate the reaction tank according to the set dissolved oxygen concentration, ensuring that the dissolved oxygen in the sewage is suitable for treatment, improving sewage treatment efficiency, and preventing excessive aeration that would waste electricity, thereby reducing sewage treatment costs. After aeration, the set dissolved oxygen concentration is updated based on the effluent detection parameters, thus reducing sewage treatment costs while ensuring that the treated water quality meets the requirements of discharge standards and other regulations.

[0018] Optionally, the steps for determining the set dissolved oxygen concentration in the reaction tank include:

[0019] A time-series model correlation analysis was performed on historical dissolved oxygen concentrations, influent detection parameters, effluent detection parameters, and other process parameters to obtain a dissolved oxygen concentration estimation model.

[0020] Based on the correlation analysis results of the dissolved oxygen concentration estimation model, and based on the collected influent detection parameters and ideal effluent detection parameters, the set dissolved oxygen concentration of the reaction tank is adjusted and determined.

[0021] If the influent detection parameters do not conform to the dissolved oxygen concentration estimation model, the set dissolved oxygen concentration of the reaction tank shall be determined according to the preset model estimation method.

[0022] The influent detection parameters are defined as historical detection parameters, and the influent detection parameters and the set dissolved oxygen concentration are stored in the preset influent dissolved oxygen concentration relationship.

[0023] By adopting the above technical solution, when the influent detection parameters exist in the historical detection parameters, the set dissolved oxygen concentration corresponding to the influent detection parameters is directly retrieved from the influent dissolved oxygen concentration relationship to determine the efficiency of the set dissolved oxygen concentration. When the parameters do not exist in the historical detection parameters, the set dissolved oxygen concentration is determined according to the model estimation method, and the influent detection parameters and the set dissolved oxygen concentration are stored in the influent dissolved oxygen concentration relationship to facilitate the next determination of the influent dissolved oxygen concentration, thereby improving the convenience of determining the influent dissolved oxygen concentration.

[0024] Optionally, the step of determining the set dissolved oxygen concentration of the reaction tank according to a preset model estimation method includes:

[0025] Obtain the historical update time of the preset dissolved oxygen concentration estimation model;

[0026] Determine whether the historical update time meets the preset baseline update time requirement;

[0027] If not, the dissolved oxygen concentration estimation model is used to calculate based on the influent detection parameters to determine the set dissolved oxygen concentration for the reaction tank.

[0028] If the conditions are met, the operating experience parameters of the reaction tank are obtained;

[0029] Analyze operational experience parameters to update the dissolved oxygen concentration estimation model;

[0030] The dissolved oxygen concentration estimation model is calculated based on the influent detection parameters to determine the set dissolved oxygen concentration in the reaction tank.

[0031] By adopting the above technical solution, the dissolved oxygen concentration estimation model is updated when the historical update time is not lower than the baseline update time. The updated dissolved oxygen concentration estimation model is then used to calculate the set dissolved oxygen concentration based on the influent detection parameters, thereby improving the accuracy of determining the set dissolved oxygen concentration.

[0032] Optionally, the steps of analyzing operational experience parameters to update the dissolved oxygen concentration estimation model include:

[0033] Data preprocessing is performed on operational experience parameters to generate usable experience parameters;

[0034] The historical dissolved oxygen concentration matrix and historical influent parameter vector of the reactor were analyzed using empirical parameters.

[0035] The historical dissolved oxygen concentration matrix and historical influent parameter vector were analyzed to determine the regression coefficient vector;

[0036] The dissolved oxygen concentration estimation model is updated based on the regression coefficient vector.

[0037] By adopting the above technical solution, empirical parameters are selected from the operational experience parameters of the reaction tank, thereby ensuring the accuracy of the linear relationship between influent parameters and dissolved oxygen concentration. Then, regression coefficient vectors are calculated based on the historical dissolved oxygen concentration matrix and the historical influent parameter vector, and the dissolved oxygen concentration estimation model is updated using the regression coefficient vectors, thereby ensuring the accuracy of the dissolved oxygen concentration estimation model.

[0038] Optionally, the step of controlling the preset aeration device to aerate the reaction tank according to the set dissolved oxygen concentration includes:

[0039] Analyze the influent detection parameters to determine the influent flow rate and the dissolved oxygen concentration.

[0040] Obtain the gas-to-water ratio in the reaction tank;

[0041] The influent flow rate and gas-water ratio were analyzed to determine the baseline gas volume.

[0042] The measured dissolved oxygen concentration and the set dissolved oxygen concentration were analyzed to determine the gas volume influence coefficient.

[0043] The gas volume influence coefficient and the baseline gas volume are analyzed to determine the total gas volume;

[0044] The aeration device is controlled to aerate the reaction tank according to the total gas volume.

[0045] By adopting the above technical solution, the basic air volume is calculated based on the influent volume and air-to-water ratio. Then, the total air volume is calculated based on the air volume influence coefficient of dissolved oxygen and the basic air volume. The aeration device is then controlled to aerate the reaction tank according to the total air volume, so that the dissolved oxygen in the reaction tank tends to the set dissolved oxygen concentration, thereby improving the accuracy of aeration to the reaction tank.

[0046] Optionally, the step of controlling the aeration device to aerate the reaction tank according to the total gas volume includes:

[0047] The aeration device is controlled to aerate at the total air volume, and the dissolved oxygen concentration of the preset zone is obtained.

[0048] Determine whether the dissolved oxygen concentration in the zone meets the set dissolved oxygen concentration requirements;

[0049] If the condition is met, continue to obtain the dissolved oxygen concentration of the partition and perform a cyclical judgment.

[0050] If it does not meet the requirements, then obtain the partition size.

[0051] The volume of each zone, the dissolved oxygen concentration in each zone, the set dissolved oxygen concentration, and the preset efficiency factor are analyzed to determine the change in dissolved oxygen demand.

[0052] The relationship between the change in dissolved oxygen demand and the preset change in dissolved oxygen opening is analyzed to determine the preset valve opening.

[0053] The valve is adjusted according to the change in opening degree.

[0054] By adopting the above technical solution, the dissolved oxygen concentration of the zone is compared with the set dissolved oxygen concentration. The change in dissolved oxygen demand is calculated based on the zone volume, the zone dissolved oxygen concentration, the set dissolved oxygen concentration, and the efficiency factor. The valve opening is determined according to the change in dissolved oxygen demand, so that the dissolved oxygen concentration of the zone is maintained at the set dissolved oxygen concentration, thereby improving the accuracy and precision of aeration in the reaction tank.

[0055] Optionally, the steps of controlling the aeration device to aerate at the total air volume include:

[0056] The parameters for starting the device are determined based on the relationship between the total gas volume and the preset gas volume device parameters.

[0057] Obtain the adjustment parameters of the aeration device; the adjustment parameters are characterized by the single adjustment time and single adjustment step of the aeration device;

[0058] The aeration device is started according to the parameters of the starting device, and the started aeration device is controlled to adjust the parameters for aeration.

[0059] Obtain the real-time air volume detected by the aeration device;

[0060] Determine whether the real-time gas volume meets the total gas volume requirement;

[0061] If it does not meet the requirements, continue to control the aeration device to adjust the parameters for aeration, and continue to obtain the real-time air volume detected by the aeration device for cyclical judgment.

[0062] If the conditions are met, the aeration device will be controlled to maintain stable aeration.

[0063] By adopting the above technical solution, the starting device parameters are determined based on the relationship between the total air volume and the air volume device parameters. This allows the corresponding aeration device to be activated according to these parameters, preventing situations where reducing the air volume of the aeration device results in insufficient air volume, or increasing it excessively. After activation, the aeration device is controlled to adjust parameters, resulting in a step-like increase in air volume. This contrasts with PID control, where improper PID parameter settings cause frequent adjustments to the aeration device when the air volume approaches the total air volume, or where adjusting the air volume downwards from its maximum causes a sudden pressure increase. This improves the rationality and safety of the aeration process.

[0064] Secondly, this application provides a wastewater treatment system, which adopts the following technical solution:

[0065] A wastewater treatment system, comprising:

[0066] The acquisition module is used to acquire the inlet trigger signal, inlet detection parameters, and outlet detection parameters;

[0067] A memory for storing a program of a wastewater treatment method as described in any of the preceding claims;

[0068] The processor and the program in the memory can be loaded and executed by the processor to implement a wastewater treatment method as described in any of the above.

[0069] By adopting the above technical solution, the controller loads and executes a wastewater treatment program stored in the memory. The control acquisition module acquires a series of data related to wastewater treatment, thereby determining the set dissolved oxygen concentration for wastewater treatment based on the influent detection parameters. Then, based on the set dissolved oxygen concentration, the aeration device is controlled to aerate the reaction tank, thereby ensuring that the dissolved oxygen in the wastewater is suitable for wastewater treatment and preventing excessive aeration that would lead to power waste, thus reducing the cost of wastewater treatment.

[0070] Thirdly, this application provides a smart terminal, which adopts the following technical solution:

[0071] A smart terminal includes a memory and a processor, wherein the memory stores a computer program that can be loaded by the processor and executed as described in any of the preceding claims for wastewater treatment.

[0072] By adopting the above technical solution, the processor loads and executes a computer program for a wastewater treatment method stored in the memory through the operation of the smart terminal. The program determines the set dissolved oxygen concentration for wastewater treatment based on the influent detection parameters, and then controls the aeration device to aerate the reaction tank according to the set dissolved oxygen concentration. This ensures that the dissolved oxygen in the wastewater is suitable for wastewater treatment, avoids excessive aeration which would lead to power waste, and thus reduces the cost of wastewater treatment.

[0073] Fourthly, this application provides a computer storage medium capable of storing corresponding programs, which facilitates cost reduction in wastewater treatment, and adopts the following technical solution:

[0074] A computer-readable storage medium storing a computer program that can be loaded by a processor and executed by any of the above-described wastewater treatment methods.

[0075] By adopting the above technical solution, a computer program for a wastewater treatment method is stored in a computer-readable storage medium. The processor loads and executes the computer program in the storage medium, thereby determining the set dissolved oxygen concentration for wastewater treatment based on the influent detection parameters. Then, the aeration device is controlled to aerate the reaction tank according to the set dissolved oxygen concentration, thereby ensuring that the dissolved oxygen in the wastewater is suitable for wastewater treatment and preventing excessive aeration that would lead to power waste, thus reducing the cost of wastewater treatment.

[0076] In summary, this application includes at least one of the following beneficial technical effects:

[0077] 1. By quickly and accurately determining the set dissolved oxygen concentration for wastewater treatment based on influent detection parameters, the aeration device is then controlled to aerate the reaction tank according to the set dissolved oxygen concentration, thereby ensuring that the dissolved oxygen in the wastewater is suitable for wastewater treatment, improving wastewater treatment efficiency, and avoiding excessive aeration that would lead to power waste, thus reducing wastewater treatment costs.

[0078] 2. By comparing the dissolved oxygen concentration of the zone with the set dissolved oxygen concentration, the change in dissolved oxygen demand is calculated based on the zone volume, the zone dissolved oxygen concentration, the set dissolved oxygen concentration, and the efficiency factor. The valve opening is then determined based on the change in dissolved oxygen demand, and the valve is adjusted accordingly to maintain the dissolved oxygen concentration of the zone at the set dissolved oxygen concentration. This improves the accuracy and precision of aeration in the reaction tank, ensuring that the treated water quality meets the requirements of discharge standards and other regulations.

[0079] 3. By determining the starting device parameters based on the relationship between the total air volume and the air volume device parameters, the corresponding aeration device is activated accordingly. This prevents situations where reducing the air volume of the aeration device results in insufficient air volume, while increasing the air volume of the aeration device results in excessive air volume. After the aeration device is activated, it is controlled to adjust the parameters to aerate the air volume in a step-like manner, rather than as with PID control. In this case, when the air volume approaches the total air volume, unreasonable PID parameter settings can cause frequent adjustments to the aeration device, or the air volume of the aeration device can be adjusted downwards from its maximum, resulting in a sudden increase in pressure. This improves the rationality and safety of the aeration device's aeration. Attached Figure Description

[0080] Figure 1 This is a flowchart of a wastewater treatment method according to an embodiment of this application.

[0081] Figure 2 This is a flowchart of the steps in this application embodiment to analyze the influent detection parameters to determine the set dissolved oxygen concentration of the reaction tank.

[0082] Figure 3 This is a flowchart of the steps for determining the set dissolved oxygen concentration of the reaction tank according to a preset model estimation method in the embodiments of this application.

[0083] Figure 4 This is a flowchart of the steps in this application embodiment to analyze operational experience parameters in order to update the dissolved oxygen concentration estimation model.

[0084] Figure 5 This is a flowchart of the steps in this application embodiment to control a preset aeration device to aerate the reaction tank according to a set dissolved oxygen concentration.

[0085] Figure 6This is a flowchart of the steps in this application embodiment to control the aeration device to aerate the reaction tank according to the total gas volume.

[0086] Figure 7 This is a flowchart of the steps for controlling the aeration device to aerate with the total air volume in the embodiments of this application. Detailed Implementation

[0087] To make the purpose, technical solution, and advantages of this application clearer, the following description is provided in conjunction with the appendix. Figures 1-7 The present application will be further described in detail below with reference to embodiments. It should be understood that the specific embodiments described herein are for illustrative purposes only and are not intended to limit the scope of the application.

[0088] This application discloses a wastewater treatment method, specifically a controller and an aeration device. The controller is connected to the aeration device via an industrial ring network to achieve data interaction and control. After receiving the influent trigger signal from the reaction tank, the controller issues instructions to control relevant sensors to detect and provide feedback on the influent detection parameters of the reaction tank. After analyzing the influent detection parameters, the controller determines the set dissolved oxygen concentration and controls the aeration device to aerate the reaction tank according to the set dissolved oxygen concentration. This ensures that the dissolved oxygen in the wastewater is suitable for wastewater treatment and avoids excessive aeration that would waste electricity. The controller also controls relevant sensors to detect the effluent detection parameters of the reaction tank. If the effluent detection parameters do not meet the requirements of the treatment detection parameters, the set dissolved oxygen concentration is updated according to the effluent detection parameters, thereby making the set dissolved oxygen concentration more suitable for improving the water quality of the wastewater treatment.

[0089] Reference Figure 1 This application discloses a wastewater treatment method, including the following steps:

[0090] Step S100: Obtain the water inlet trigger signal of the preset reaction tank.

[0091] The reaction tank refers to the biological tank for wastewater treatment. The reaction tank carries out processes such as organic carbon removal, nitrification and phosphorus uptake. Providing suitable dissolved oxygen can form a stable dissolved oxygen environment in the reaction tank, establishing a dynamic balance and reliable living environment for microbial growth and pollutant degradation. In the embodiments of this application, the reaction tank is divided into several identical partitions, and each branch pipe of the aeration device is responsible for the dissolved oxygen of one partition.

[0092] The influent trigger signal is the signal that wastewater enters the reaction tank. It can be obtained by the operator by inputting it into the controller, or it can be automatically collected by a pressure sensor.

[0093] Step S101: Obtain the influent detection parameters of the reaction tank based on the influent trigger signal.

[0094] When the controller receives the inlet trigger signal, it responds to the inlet trigger signal by detecting the inlet parameters of the reaction tank, providing data support for subsequent determination of dissolved oxygen.

[0095] Influent detection parameters refer to relevant parameters when wastewater enters the system, including data such as chemical oxygen demand (COD), ammonia nitrogen concentration, influent flow rate, influent dissolved oxygen concentration, and influent temperature. Some of these parameters are input into the controller by the operator, such as COD, while ammonia nitrogen concentration, influent flow rate, and influent dissolved oxygen concentration can be detected by online ammonia nitrogen detectors, flow meters, and dissolved oxygen meters.

[0096] Step S102: Analyze the influent detection parameters to determine the set dissolved oxygen concentration of the reaction tank.

[0097] The set dissolved oxygen concentration refers to the concentration of dissolved oxygen in the wastewater. Setting this concentration ensures that the total oxygen transfer rate in the reaction tank is approximately equal to the total oxygen consumption rate, thus preventing excessive aeration and wasted electricity while still meeting the oxygen requirements for wastewater treatment. The concentration is determined by the controller based on analysis of influent detection parameters; specific analysis methods are described in [reference needed]. Figure 2 The steps.

[0098] Preferably, the set dissolved oxygen concentration of the reaction tank is determined based on similar historical data from a time-difference time-series model, according to the influent detection parameters and ideal effluent detection parameters. Specifically, this includes:

[0099] A correlation analysis of historical dissolved oxygen concentration, influent detection parameters, effluent detection parameters and other process parameters was conducted to obtain a dissolved oxygen concentration estimation model.

[0100] Based on the correlation analysis results of the dissolved oxygen concentration estimation model, and based on the collected influent detection parameters and ideal effluent detection parameters, the set dissolved oxygen concentration of the reaction tank is adjusted and determined.

[0101] If the influent detection parameters do not conform to the dissolved oxygen concentration estimation model, the set dissolved oxygen concentration of the reaction tank shall be determined according to the preset model estimation method.

[0102] The influent detection parameters are defined as historical detection parameters, and the influent detection parameters and the set dissolved oxygen concentration are stored in the preset influent dissolved oxygen concentration relationship.

[0103] Step S103: Control the preset aeration device to aerate the reaction tank according to the set dissolved oxygen concentration.

[0104] After the controller determines the set dissolved oxygen concentration, it controls the aeration device to aerate the reaction tank according to the set dissolved oxygen concentration. The specific method is described in [reference needed]. Figure 5This process creates a dynamic balance between oxygen in the reaction tank and the growth of microorganisms and degradation of pollutants in the wastewater.

[0105] An aeration device is a device used to supply oxygen to a reaction tank. It includes blowers of different air volumes, pipes, valves, and flow meters. The blowers use a combination of large and small air volumes and are connected to the pipes, which are installed in each zone. Aeration discs are installed on the pipes to deliver the air supplied by the blowers to the reaction tank. The valves are the main control equipment of the entire aeration device. By adjusting the opening of the valves, the flow rate in the pipes is adjusted, thereby regulating the dissolved oxygen concentration. The flow meter is used to measure the flow rate in the pipes and can be a mass flow meter.

[0106] Step S104: Obtain the effluent detection parameters of the reaction tank.

[0107] In this process, after the aeration device aerates the reaction tank, the effluent parameters of the reaction tank are measured to provide data support for subsequent updates to the dissolved oxygen concentration settings.

[0108] The effluent detection parameters refer to the parameters of the effluent water quality, which are obtained by the controller controlling the online monitoring system to monitor parameters such as dissolved oxygen concentration, temperature, pH, organic matter load, and ammonia nitrogen concentration in real time.

[0109] Step S105: Determine whether the effluent detection parameters meet the preset requirements of the treatment detection parameters.

[0110] Among them, the treatment and testing parameters refer to the effluent water quality parameters that meet the requirements. The specific values ​​are determined by the operators based on the actual situation. The requirements for the treatment and testing parameters refer to the parameters being within the corresponding range.

[0111] The controller determines whether the effluent detection parameters are within the range corresponding to the treatment detection parameters, thereby determining whether the current set dissolved oxygen concentration can support the wastewater treatment in the reaction tank.

[0112] Step S1051: If the conditions are met, continue to control the aeration device to aerate the reaction tank according to the set dissolved oxygen concentration, and continue to acquire effluent detection parameters for cyclic judgment.

[0113] If the controller determines that the effluent detection parameters are within the range corresponding to the treatment detection parameters, it indicates that the aeration device can support the wastewater treatment in the reaction tank with the current set dissolved oxygen concentration. Therefore, the controller continues to control the aeration device to aerate the reaction tank according to the set dissolved oxygen concentration, and continues to detect the effluent detection parameters, thereby continuously monitoring the wastewater treatment status in the reaction tank.

[0114] Step S1052: If it does not meet the requirements, update the set dissolved oxygen concentration according to the effluent detection parameters and regenerate the set dissolved oxygen concentration.

[0115] If the controller determines that the effluent detection parameters exceed the range of the corresponding treatment detection parameters, it indicates that the aeration device cannot support the wastewater treatment in the reaction tank with the current set dissolved oxygen concentration. Therefore, the set dissolved oxygen concentration is updated according to the effluent detection parameters to regenerate the set dissolved oxygen concentration, making the wastewater treatment more in line with the requirements. The specific update method is as follows: First, determine the parameters in the effluent water quality parameters that exceed the treatment detection parameters. For example, if the temperature exceeds the reference temperature, calculate the temperature difference. Then, calculate the dissolved oxygen concentration that needs to be increased according to the correlation coefficient between temperature and dissolved oxygen concentration. Add the dissolved oxygen concentration that needs to be increased to the original set dissolved oxygen concentration to obtain the updated set dissolved oxygen concentration.

[0116] Step S106: Continue to control the aeration device to aerate the reaction tank according to the newly generated set dissolved oxygen concentration.

[0117] After obtaining the newly generated set dissolved oxygen concentration, the aeration device is controlled to continue aeration to the reaction tank with the new set dissolved oxygen concentration. The specific method logic is the same as that in step S103, and will not be repeated here.

[0118] Reference Figure 2 The steps for analyzing influent detection parameters to determine the set dissolved oxygen concentration for the reaction tank include:

[0119] Step S200: Determine whether the influent detection parameters meet the requirements of the preset historical detection parameters.

[0120] Among them, historical detection parameters refer to the detection parameters of the previous influent to the reaction tank, which are obtained by the controller backup. The requirement for historical detection parameters is that they exist in the historical detection parameters.

[0121] The controller determines whether the inlet water detection parameters exist in the historical detection parameters, thereby determining whether the current inlet water parameters are the same as those of the previous inlet water.

[0122] Step S201: If it does not meet the requirements, the set dissolved oxygen concentration of the reaction tank shall be determined according to the preset model estimation method.

[0123] If the controller determines that the influent detection parameters are not present in the historical detection parameters, it indicates that the previously set dissolved oxygen concentration cannot be used. Therefore, the set dissolved oxygen concentration for the reaction tank is determined according to the model estimation method. The specific method is described in [reference needed]. Figure 3 The steps.

[0124] The model estimation method refers to the method of using a machine learning model to calculate the set dissolved oxygen concentration based on the influent detection parameters, which is then stored in the controller by the operator.

[0125] Step S2011: Define the influent detection parameters as historical detection parameters, and store the influent detection parameters and the set dissolved oxygen concentration in the preset influent dissolved oxygen concentration relationship.

[0126] In this process, after determining the set dissolved oxygen concentration corresponding to the influent detection parameters, the influent detection parameters are defined as historical detection parameters. The influent detection parameters and the set dissolved oxygen concentration are then stored in the influent dissolved oxygen concentration relationship, which facilitates the subsequent determination of the set dissolved oxygen concentration based on the influent detection parameters.

[0127] The relationship between influent dissolved oxygen concentration refers to the correspondence between influent detection parameters and set dissolved oxygen concentration. The controller maps the influent detection parameters to the set dissolved oxygen concentration calculated by the model to form a mapping table.

[0128] Step S202: If the conditions are met, the set dissolved oxygen concentration of the reaction tank is determined based on the relationship between the influent detection parameters and the preset dissolved oxygen concentration of the influent.

[0129] If the controller determines that the influent detection parameters exist in the historical detection parameters, it means that the previously set dissolved oxygen concentration can be used. Therefore, the set dissolved oxygen concentration can be found in the mapping table corresponding to the influent dissolved oxygen concentration relationship based on the influent detection parameters, without having to make the model calculate the set dissolved oxygen concentration again, thereby improving the efficiency of determining the set dissolved oxygen concentration.

[0130] Reference Figure 3 The steps for determining the set dissolved oxygen concentration in the reaction tank based on a preset model estimation method include:

[0131] Step S300: Obtain the historical update time of the preset dissolved oxygen concentration estimation model.

[0132] The dissolved oxygen concentration estimation model refers to the model that calculates the set dissolved oxygen concentration based on the influent detection parameters. In this embodiment, a multivariate linear model is used. Each parameter in the influent detection parameters has a linear relationship with the set dissolved oxygen concentration and has a corresponding regression coefficient. After calculating the product of the regression coefficient and the parameter, all products are added together to obtain the set dissolved oxygen concentration.

[0133] The historical update time refers to the time since the last update of the dissolved oxygen concentration estimation model, which is obtained by timing the timer.

[0134] Step S301: Determine whether the historical update time meets the preset baseline update time requirement.

[0135] The baseline update time refers to the shortest interval between updates to the dissolved oxygen concentration estimation model. The specific value is determined by the operator based on the actual situation. The requirement for the baseline update time is that it should not be less than the baseline update time.

[0136] The controller determines whether the dissolved oxygen concentration estimation model needs to be updated by checking whether the historical update time is not less than the baseline update time.

[0137] Step S3011: If it does not meet the requirements, the dissolved oxygen concentration estimation model is used to calculate based on the influent detection parameters to determine the set dissolved oxygen concentration of the reaction tank.

[0138] If the controller determines that the historical update time is less than the baseline update time, it means that there is no need to update the dissolved oxygen concentration estimation model. Instead, the parameters corresponding to the influent detection parameters are directly input into the dissolved oxygen concentration estimation model to calculate the product of the parameters and the corresponding regression coefficients. Finally, the set dissolved oxygen concentration is obtained by summing all the products and adding the constant regression coefficient.

[0139] Step S3012: If the conditions are met, obtain the operating experience parameters of the reaction tank.

[0140] If the controller determines that the historical update time is not less than the baseline update time, it indicates that the dissolved oxygen concentration estimation model needs to be updated. Therefore, the operating experience parameters of the reaction tank are called to provide data support for subsequent updates to the dissolved oxygen concentration estimation model.

[0141] Operating experience parameters refer to the influent detection parameters and corresponding set dissolved oxygen concentrations in the previous reaction tank, which are backed up and recalled by the controller.

[0142] Step S302: Analyze the operational experience parameters to update the dissolved oxygen concentration estimation model.

[0143] Specifically, after the controller invokes the operational experience parameters, it updates the dissolved oxygen concentration estimation model based on these parameters. The specific method is described in [reference needed]. Figure 4 This process improves the accuracy of dissolved oxygen concentration estimation models.

[0144] Step S303: The dissolved oxygen concentration estimation model is used to calculate based on the influent detection parameters to determine the set dissolved oxygen concentration of the reaction tank.

[0145] In this process, after updating the dissolved oxygen concentration estimation model, the set dissolved oxygen concentration is obtained by controlling the dissolved oxygen concentration estimation model to calculate based on the influent detection parameters. The specific method is the same as that in step S3011, and will not be described in detail here.

[0146] Reference Figure 4The steps for analyzing operational experience parameters to update the dissolved oxygen concentration estimation model include:

[0147] Step S400: Perform data preprocessing on the operating experience parameters to generate usable experience parameters.

[0148] Among them, the empirical parameters refer to the influent parameters that can be used to calculate the regression coefficients. These parameters are obtained by removing outliers and missing values ​​from the operational empirical parameters, thereby ensuring the integrity and consistency of the data.

[0149] Step S401: Analyze the empirical parameters to determine the historical dissolved oxygen concentration matrix and historical influent parameter vector of the reactor.

[0150] The historical dissolved oxygen concentration matrix is ​​formed by taking each set of influent parameters from the empirical parameters as an element of each row of the matrix, and using the constant 1 as the first element of each row of the matrix to calculate the constant regression coefficient.

[0151] The historical influent parameter vector refers to the vector formed by using the dissolved oxygen concentration corresponding to the influent parameters from the empirical parameters as the elements of the column vector.

[0152] Step S402: Analyze the historical dissolved oxygen concentration matrix and historical influent parameter vector to determine the regression coefficient vector.

[0153] The regression coefficient vector is a vector composed of regression coefficients from the dissolved oxygen concentration estimation model. It is calculated by the controller from the historical dissolved oxygen concentration matrix and the historical influent parameter vector. The calculation process is as follows: first, calculate the transpose of the historical dissolved oxygen concentration matrix; then, calculate the dot product of the transpose matrix and the historical dissolved oxygen concentration matrix, and calculate the inverse matrix of the dot product; then, calculate the dot product of the inverse matrix, the transpose matrix, and the historical influent parameter vector in sequence to obtain the regression coefficient vector.

[0154] Step S403: Update the dissolved oxygen concentration estimation model based on the regression coefficient vector.

[0155] Specifically, after determining the regression coefficient vector, each element of the regression coefficient vector is called, and the regression coefficients of the dissolved oxygen concentration estimation model are replaced accordingly, thereby updating the dissolved oxygen concentration trajectory model and making the dissolved oxygen concentration estimation model more accurate.

[0156] Reference Figure 5 The steps for controlling the pre-set aeration device to aerate the reaction tank according to the set dissolved oxygen concentration include:

[0157] Step S500: Analyze the influent detection parameters to determine the influent flow rate and the dissolved oxygen concentration.

[0158] Among them, the influent volume refers to the amount of water entering the reaction tank per unit time, and the detected dissolved oxygen concentration refers to the dissolved oxygen concentration of the influent, which is obtained by the controller by identifying and calling the influent detection parameters.

[0159] Step S501: Obtain the gas-water ratio of the reaction tank.

[0160] The air-to-water ratio refers to the volume of air required to supply each cubic meter of incoming water, which is obtained by the operator inputting it into the controller.

[0161] Step S502: Analyze the influent flow rate and gas-water ratio to determine the baseline gas volume.

[0162] The basic gas volume refers to the gas volume calculated based on the complete dissolution of oxygen, which is obtained by the controller by multiplying the water intake volume and the gas-water ratio.

[0163] Step S503: Analyze the detected dissolved oxygen concentration and the set dissolved oxygen concentration to determine the gas volume influence coefficient.

[0164] Among them, the gas volume influence coefficient refers to the influence coefficient of dissolved oxygen concentration on gas volume demand. It is determined by the controller after analyzing the detected dissolved oxygen concentration and the set dissolved oxygen concentration. The analysis method is as follows: calculate the difference between the set dissolved oxygen concentration and the detected dissolved oxygen concentration, multiply it by the set proportional coefficient, and add 1 to obtain the gas volume influence coefficient. The proportional coefficient is used to adjust the degree of influence of dissolved oxygen concentration deviation on gas volume demand. The proportional coefficient is derived from the respiration rate of microorganisms, oxygen transfer efficiency, and design parameters of the reaction tank.

[0165] Step S504: Analyze the gas volume influence coefficient and the basic gas volume to determine the total gas volume.

[0166] The total gas volume refers to the amount of gas required to meet the dissolved oxygen concentration, which is obtained by the controller multiplying the gas volume influence coefficient with the base gas volume.

[0167] Step S505: Control the aeration device to aerate the reaction tank according to the total gas volume.

[0168] After the controller receives the total air volume, it controls the aeration device to aerate the reaction tank based on the total air volume. The specific method is described in [reference needed]. Figure 6 This process ensures that the dissolved oxygen concentration in the reaction tank approaches the set dissolved oxygen concentration.

[0169] Reference Figure 6 The steps for controlling the aeration device to aerate the reaction tank according to the total gas volume include:

[0170] Step S600: Control the aeration device to aerate with the total air volume and obtain the dissolved oxygen concentration of the preset zone.

[0171] The controller issues a command to the aeration device to aerate using the total air volume; the specific method is described in [reference needed]. Figure 7 The steps involve detecting the dissolved oxygen concentration in each zone to precisely control the dissolved oxygen concentration within the reaction tank.

[0172] A zone refers to a partition within the reaction tank defined by the operator, as explained in step S100. The dissolved oxygen concentration within a zone refers to the dissolved oxygen concentration within that zone, which is detected by a dissolved oxygen meter installed in that zone and transmitted to the controller.

[0173] Step S601: Determine whether the dissolved oxygen concentration of the zone meets the requirements of the set dissolved oxygen concentration.

[0174] The requirement for setting the dissolved oxygen concentration refers to being within a set range. The controller determines whether the dissolved oxygen concentration of a zone is within the set range, thereby determining whether the dissolved oxygen concentration of that zone supports wastewater treatment.

[0175] Step S6011: If the condition is met, continue to obtain the dissolved oxygen concentration of the partition and perform cyclic judgment.

[0176] If the controller determines that the dissolved oxygen concentration of a zone is within the set dissolved oxygen concentration range, it indicates that the dissolved oxygen concentration of the zone supports wastewater treatment. Therefore, the dissolved oxygen concentration of the zone is continuously monitored to keep track of changes in the dissolved oxygen concentration of the zone.

[0177] Step S6012: If it does not meet the requirements, then obtain the partition volume of the partition.

[0178] If the controller determines that the dissolved oxygen concentration of a zone is not within the set dissolved oxygen concentration range, it indicates that the dissolved oxygen concentration of the zone cannot efficiently support wastewater treatment. Therefore, the zone volume is detected to provide data support for subsequent control of zone aeration changes.

[0179] The zone volume refers to the effective volume of water within the zone, which is obtained by the operator inputting it into the controller.

[0180] Step S602: Analyze the partition volume, partition dissolved oxygen concentration, set dissolved oxygen concentration and preset efficiency factor to determine the change in dissolved oxygen demand.

[0181] The efficiency factor is a coefficient that reflects the aeration efficiency and oxygen transfer rate in the reaction tank. It is obtained by the operator after determining the relationship between dissolved oxygen concentration and aeration volume, calling the regression coefficient, and calculating the quotient between the regression coefficient and the effective volume.

[0182] The change in dissolved oxygen demand refers to the change in gas volume that brings the dissolved oxygen concentration closer to the set value. The controller calculates the difference between the set dissolved oxygen concentration and the dissolved oxygen concentration of the zone, and the product of the efficiency factor, the zone volume, and the difference is obtained.

[0183] Step S603: Analyze the relationship between the change in dissolved oxygen demand and the preset change in dissolved oxygen opening to determine the preset valve opening.

[0184] The dissolved oxygen opening change relationship refers to the relationship between gas volume and opening degree, which is obtained by the operator inputting the opening degree that needs to be adjusted to change the unit gas volume into the controller.

[0185] A valve is a device used to control the flow rate in a pipeline. Refer to the explanation in step S103; further details will not be provided here. The variable opening degree refers to the required change in valve opening, calculated by the controller as the product of the change in dissolved oxygen demand and the constant corresponding to the change in dissolved oxygen opening degree.

[0186] Step S604: Adjust the control valve according to the change in opening degree.

[0187] In this process, after obtaining the change in opening degree, the corresponding valve is controlled to adjust the opening degree, thereby changing the aeration rate of the zone and making the dissolved oxygen concentration in the zone tend to the set dissolved oxygen concentration, thus supporting the efficient treatment of wastewater in the zone.

[0188] Reference Figure 7 The steps for controlling the aeration device to aerate at the total air volume include:

[0189] Step S700: Determine the start-up device parameters based on the relationship between the total gas volume and the preset gas volume device parameters.

[0190] Among them, the air volume device parameter relationship refers to the correspondence between the total air volume and the starting device parameters. The operator ensures that the starting aeration device can fully meet the total air volume requirement according to the principle of matching large and small, and that even when the aeration device is running at the minimum air volume, there will be no excessive air volume. The operator forms a mapping table by matching the total air volume with the starting device parameters one by one.

[0191] The start-up device parameters refer to the aeration devices that can be started, which are obtained by the controller by looking up the corresponding mapping table of air volume device parameters based on the total air volume.

[0192] Step S701: Obtain the adjustment parameters of the aeration device; the adjustment parameters are characterized by the single adjustment time and single adjustment step of the aeration device.

[0193] Among them, the adjustment parameters refer to the amount of air adjusted by the aeration device each time and the interval between adjustments, which are set by the operator on the aeration device.

[0194] Step S702: Control the aeration device to start according to the starting device parameters, and control the started aeration device to adjust the parameters for aeration.

[0195] After obtaining the parameters of the starting device, the controller sends a command to the corresponding aeration device to start the aeration device according to the parameters, and controls the started aeration device to perform aeration according to the set adjustment parameters, so as to ensure that the aeration volume increases step by step from small to large, unlike PID control which causes an instantaneous increase in pipeline pressure.

[0196] Step S703: Obtain the real-time air volume detected by the aeration device.

[0197] Among them, the real-time air volume detection refers to the output air volume of the aeration device, which is detected by the flow meter and sent to the controller.

[0198] Step S704: Determine whether the real-time gas volume meets the total gas volume requirement.

[0199] The requirement for total air volume means that it equals the total air volume. The controller determines whether the real-time detected air volume equals the total air volume, thereby determining whether the air output of the aeration device can support wastewater treatment.

[0200] Step S7041: If it does not meet the requirements, continue to control the aeration device to adjust the parameters for aeration, and continue to acquire the real-time air volume detected by the aeration device for cyclic judgment.

[0201] If the controller determines that the real-time detected air volume is not equal to the total air volume, it indicates that the air volume output by the aeration device cannot support wastewater treatment. Therefore, the controller continues to control the aeration device to adjust the parameters for aeration and continues to monitor the real-time detected air volume of the aeration device to continuously monitor the changes in the output air volume of the aeration device.

[0202] Step S7042: If the condition is met, control the aeration device to maintain stable aeration.

[0203] If the controller determines that the real-time detected air volume is equal to the total air volume, it indicates that the current output air volume of the aeration device can support the wastewater treatment in the reaction tank. Therefore, the controller controls the aeration device to maintain stable aeration, thereby providing a stable and continuous oxygen environment.

[0204] A time-series model correlation analysis was performed on historical dissolved oxygen concentrations, influent detection parameters, effluent detection parameters, and other process parameters to obtain a dissolved oxygen concentration estimation model. Based on similar historical data from the dissolved oxygen concentration estimation model, and using influent and ideal effluent detection parameters, the set dissolved oxygen concentration for the reactor was determined. Specifically, this includes the following:

[0205] 1. Data Collection and Preprocessing

[0206] Collect historical data on influent water quality parameters (such as COD, BOD, ammonia nitrogen, etc.), effluent water quality parameters (such as COD, BOD, ammonia nitrogen, etc.), and dissolved oxygen concentration (DO) during the aeration process.

[0207] Data is cleaned, denoised, and normalized to ensure data quality.

[0208] 2. Time difference analysis

[0209] Time difference determination: The time difference τ_in and the time difference τ_out of the influence of influent water quality parameters on DO demand are determined by correlation analysis or mutual information methods.

[0210] Time difference application: Based on the determined time difference, adjust the time series of influent and effluent water quality parameters to correspond to the current DO demand.

[0211] 3. Feature Engineering

[0212] Feature selection: Select influent and effluent water quality parameters that are highly correlated with DO requirements as features.

[0213] Feature construction: Construct a feature matrix based on the time series adjusted for time difference.

[0214] 4. Model Selection and Training

[0215] Model selection: Select a model suitable for time series analysis, such as LSTM, GRU, ARIMA, etc.

[0216] Model training: Train the model using historical data and adjust the model parameters to optimize prediction performance.

[0217] 5. Model Evaluation and Optimization

[0218] Model evaluation: The model performance is evaluated using metrics such as cross-validation, mean squared error (MSE), and mean absolute error (MAE).

[0219] Model optimization: Based on the evaluation results, adjust the model structure, parameters, or feature engineering methods to further optimize the model.

[0220] 6. Model Application

[0221] Real-time prediction: The trained model is applied to real-time data to predict the DO requirement of the current aeration stage.

[0222] Feedback and Adjustment: Continuously adjust model parameters based on actual operation to improve prediction accuracy.

[0223] Multivariate time series prediction for water quality regulation parameters:

[0224] 1. Based on historical data of influent water quality parameters (such as COD, BOD, ammonia nitrogen, etc.) and effluent water quality parameters, predict the dissolved oxygen (DO) requirement for the current aeration stage.

[0225] Key points:

[0226] The impact of influent water quality parameters on DO demand has a time delay τ_in.

[0227] The effluent water quality parameters are the results of past aeration processes, reflecting the impact of historical DO demand τ_out.

[0228] 2. Mathematical Model Framework

[0229] The problem is modeled as a multivariate time series forecasting problem, combining delay effects and time series correlations.

[0230] 2.1 Variable Definition

[0231] DO_t: Dissolved oxygen demand at the current time t.

[0232] X_in(t): Influent water quality parameters (such as COD, BOD, ammonia nitrogen, etc.) at the current time t.

[0233] X_out(t): The effluent water quality parameters at the current time t.

[0234] τ_in: The time delay of the impact of influent water quality parameters on DO demand.

[0235] τ_out: The time delay of the impact of effluent water quality parameters on DO demand.

[0236] 2.2 Model Formula

[0237] Assume that the DO requirement DO_t is affected by the following factors:

[0238] Historical data of influent water quality parameters X_in(t-τ_in).

[0239] Historical data of effluent water quality parameters X_out(t-τ_out).

[0240] Other possible system conditions or environmental factors (such as temperature, pH, etc.).

[0241] The model can be represented as:

[0242] DO_t = f(X_in(t-τ_in), X_in(t-τ_in-1), ..., X_in(t-τ_in-k),

[0243] X_out(t-τ_out), X_out(t-τ_out-1), ..., X_out(t-τ_out-m),

[0244] θ) + ϵ_t

[0245] in:

[0246] - f(.) is the function to be fitted, which can be a linear model, a nonlinear model (such as a neural network), or a time series model (such as ARIMA, LSTM).

[0247] - θ are model parameters.

[0248] - ϵ_t is the random error term.

[0249] -k and m are the historical window sizes for the influent and effluent parameters, respectively.

[0250] 3. Detailed Model Design

[0251] Here are some specific mathematical model design methods:

[0252] 3.1 Linear Regression Model

[0253] Assume a linear relationship exists between DO demand and influent and effluent parameters:

[0254] DO_t = β_0 + sum_{i=0 to k}β_{in,i} X_in(t-τ_in-i) + sum_{j=0 to m}β_{out,j}X_out(t-τ_out-j) + ϵ_t

[0255] in:

[0256] β_0 is the intercept term.

[0257] β_{in,i} and β_{out,j} are regression coefficients.

[0258] k and m are the sizes of the history window.

[0259] 3.2 Time Series Model (ARIMA)

[0260] Modeling DO demand as a time series, considering its autocorrelation and the external influences of influent and effluent parameters:

[0261] DO_t = c + sum_{i=1 to p} Φ_i DO_{ti} + sum_{i=0}^{k} γ_{in,i} X_in(t-τ_in-i) + sum_{j=0}^{m} γ_{out,j} X_out(t-τ_out-j) + ϵ_t

[0262] in:

[0263] Φ_i is the autoregressive coefficient.

[0264] γ_{in,i} and γ_{out,j} are the coefficients of the external variables.

[0265] p is the autoregressive order.

[0266] 3.3 Nonlinear Model (LSTM)

[0267] Using a Long Short-Term Memory (LSTM) network to capture the nonlinear relationship between DO demand and historical influent and effluent parameters:

[0268] DO_t = LSTM(X_in(t-τ_in), X_in(t-τ_in-1), ..., X_in(t-τ_in-k)

[0269] X_out(t-τ_out), X_out(t-τ_out-1), ..., X_out(t-τ_out-m); θ)

[0270] in:

[0271] LSTM is a recurrent neural network that can capture long-term dependencies in time series.

[0272] θ is the parameter of LSTM.

[0273] 4. Model Solving and Optimization

[0274] Linear regression model: The regression coefficients are solved using the least squares method.

[0275] ARIMA model: Solve for model parameters using maximum likelihood estimation or least squares method.

[0276] LSTM model: A neural network trained using gradient descent (such as the Adam optimizer).

[0277] 5. Model Evaluation

[0278] Evaluation metrics: Mean squared error (MSE), mean absolute error (MAE), and coefficient of determination (R^2).

[0279] Cross-validation: Use time series cross-validation (TimeSeriesSplit) to evaluate model performance.

[0280] A time-series model correlation analysis algorithm based on the time difference between influent and effluent water quality is constructed to predict the dissolved oxygen (DO) requirement in the aeration stage of wastewater treatment. This model effectively utilizes historical data, considering the time difference between influent and effluent water quality parameters to improve prediction accuracy. Simultaneously, the latest influent water quality parameters, the set DO concentration, and the effluent water quality parameters are continuously incorporated as historical data into the constantly updated DO estimation model, with higher weights assigned to new data to optimize the accuracy of the set DO concentration.

[0281] Simultaneously, water quality conditioning processes beyond the set dissolved oxygen concentration are incorporated into the expert database for regulating influent and effluent water quality. When updating historical data and weights, the water quality conditioning processes in the expert database are applied to the process of setting dissolved oxygen concentration. The water quality conditioning processes in the expert database are simultaneously screened, updated, and their weights adjusted. Ultimately, this achieves time-series model optimization that considers the time difference between influent and effluent water quality from multiple dimensions, enabling precise regulation of the set dissolved oxygen concentration for ideal effluent parameters.

[0282] Based on the same inventive concept, embodiments of this application provide a wastewater treatment system, including:

[0283] The acquisition module is used to acquire inlet trigger signal, inlet detection parameters, outlet detection parameters, historical update time, operating experience parameters, air-water ratio, zone dissolved oxygen concentration, zone volume, adjustment parameters, and real-time detected air volume.

[0284] A memory used to store a program for a wastewater treatment method;

[0285] A processor is a device that can load and execute programs in memory to implement a wastewater treatment method.

[0286] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional modules is used as an example. In practical applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. The specific working process of the system, device, and unit described above can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0287] This application provides a computer-readable storage medium storing a computer program that can be loaded by a processor and executed as a wastewater treatment method.

[0288] Computer storage media include, for example, USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, optical disks, and other media that can store program code.

[0289] Based on the same inventive concept, embodiments of this application provide a smart terminal, including a memory and a processor, wherein the memory stores a computer program that can be loaded by the processor and executed as a wastewater treatment method.

[0290] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional modules is used as an example. In practical applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. The specific working process of the system, device, and unit described above can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0291] The above are all preferred embodiments of this application and are not intended to limit the scope of protection of this application. Any feature disclosed in this specification (including the abstract and drawings) may be replaced by other equivalent or similar features unless specifically stated otherwise. That is, unless specifically stated otherwise, each feature is only one example of a series of equivalent or similar features.

Claims

1. A wastewater treatment method, characterized in that, include: Obtain the water inlet trigger signal of the preset reaction tank; The influent detection parameters of the reaction tank are obtained based on the influent trigger signal; Based on the influent detection parameters and ideal effluent detection parameters, the set dissolved oxygen concentration of the reaction tank is determined using similar historical data from a dissolved oxygen concentration estimation model. The preset aeration device is controlled to aerate the reaction tank according to the set dissolved oxygen concentration. Obtain the effluent detection parameters of the reaction tank; Determine whether the effluent detection parameters meet the preset treatment detection parameter requirements; If the conditions are met, the aeration device will continue to aerate the reaction tank according to the set dissolved oxygen concentration, and the effluent detection parameters will continue to be acquired for cyclical judgment. If it does not meet the requirements, the set dissolved oxygen concentration will be updated and regenerated based on the effluent detection parameters. The aeration device will continue to aerate the reaction tank according to the newly generated dissolved oxygen concentration. The steps for determining the set dissolved oxygen concentration in the reaction tank include: A time-series model correlation analysis was performed on historical dissolved oxygen concentrations, influent detection parameters, effluent detection parameters, and other process parameters to obtain a dissolved oxygen concentration estimation model. Based on the correlation analysis results of the dissolved oxygen concentration estimation model, and based on the collected influent detection parameters and ideal effluent detection parameters, the set dissolved oxygen concentration of the reaction tank is adjusted and determined. If the influent detection parameters do not conform to the dissolved oxygen concentration estimation model, the set dissolved oxygen concentration of the reaction tank shall be determined according to the preset model estimation method. The influent detection parameters are defined as historical detection parameters, and the influent detection parameters and the set dissolved oxygen concentration are stored in the preset influent dissolved oxygen concentration relationship. A time-series model correlation analysis was performed on historical dissolved oxygen concentrations, influent detection parameters, effluent detection parameters, and other process parameters to obtain a dissolved oxygen concentration estimation model. Based on similar historical data from the dissolved oxygen concentration estimation model, the set dissolved oxygen concentration for the reactor was determined using influent and ideal effluent detection parameters. Specifically, this included the following: (1) Data collection and preprocessing: Historical data on influent water quality parameters, effluent water quality parameters, and dissolved oxygen concentration in the aeration stage were collected. The data were cleaned, denoised, and normalized to ensure data quality. Influent water quality parameters included COD, BOD, and ammonia nitrogen; effluent water quality parameters included COD, BOD, and ammonia nitrogen; and dissolved oxygen concentration in the aeration stage included DO. (2) Time difference analysis: The time difference is determined by using correlation analysis or mutual information methods to ascertain the time difference τ_in of the impact of influent water quality parameters on DO demand. The time difference τ_out between the impact of effluent water quality parameters on DO demand; Time difference application: Based on the determined time difference, adjust the time series of influent and effluent water quality parameters to correspond to the current DO demand; (3) Feature engineering: Feature selection: Select influent and effluent water quality parameters that are highly correlated with DO requirements as features; Feature construction: Construct a feature matrix based on the time series adjusted for time difference. Model selection and training: Model selection: Choose a model suitable for time series analysis. Suitable models for time series analysis include LSTM, GRU, and ARIMA. Model training involves using historical data to train the model and adjusting model parameters to optimize prediction performance. (4) Model evaluation and optimization: Model evaluation uses cross-validation, mean squared error (MSE), and mean absolute error (MAE) to assess model performance. Model optimization involves adjusting the model structure, parameters, or feature engineering methods based on the evaluation results to further optimize the model. (5) Model application: Real-time prediction involves applying the trained model to real-time data to predict the DO demand in the current aeration stage. Feedback and adjustments are made to continuously adjust model parameters based on actual operating conditions to improve prediction accuracy.

2. The wastewater treatment method according to claim 1, characterized in that, The steps for determining the set dissolved oxygen concentration in the reaction tank based on the preset model estimation method include: Obtain the historical update time of the preset dissolved oxygen concentration estimation model; Determine whether the historical update time meets the preset baseline update time requirement; If not, the dissolved oxygen concentration estimation model is used to calculate based on the influent detection parameters to determine the set dissolved oxygen concentration for the reaction tank. If the conditions are met, the operating experience parameters of the reaction tank are obtained; Analyze operational experience parameters to update the dissolved oxygen concentration estimation model; The dissolved oxygen concentration estimation model is calculated based on the influent detection parameters to determine the set dissolved oxygen concentration in the reaction tank.

3. The wastewater treatment method according to claim 2, characterized in that, The steps for analyzing operational experience parameters to update the dissolved oxygen concentration estimation model include: Data preprocessing is performed on operational experience parameters to generate usable experience parameters; The historical dissolved oxygen concentration matrix and historical influent parameter vector of the reactor were analyzed using empirical parameters. The historical dissolved oxygen concentration matrix and historical influent parameter vector were analyzed to determine the regression coefficient vector; The dissolved oxygen concentration estimation model is updated based on the regression coefficient vector.

4. The wastewater treatment method according to claim 1, characterized in that, The steps for controlling the pre-set aeration device to aerate the reaction tank according to the set dissolved oxygen concentration include: Analyze the influent detection parameters to determine the influent flow rate and the dissolved oxygen concentration. Obtain the gas-to-water ratio in the reaction tank; The influent flow rate and gas-water ratio were analyzed to determine the baseline gas volume. The measured dissolved oxygen concentration and the set dissolved oxygen concentration were analyzed to determine the gas volume influence coefficient. The gas volume influence coefficient and the baseline gas volume are analyzed to determine the total gas volume; The aeration device is controlled to aerate the reaction tank according to the total gas volume.

5. A wastewater treatment method according to claim 4, characterized in that, The steps for controlling the aeration device to aerate the reaction tank according to the total air volume include: The aeration device is controlled to aerate at the total air volume, and the dissolved oxygen concentration of the preset zone is obtained. Determine whether the dissolved oxygen concentration in the zone meets the set dissolved oxygen concentration requirements; If the condition is met, continue to obtain the dissolved oxygen concentration of the partition and perform a cyclical judgment. If it does not meet the requirements, then obtain the partition size. The volume of each zone, the dissolved oxygen concentration in each zone, the set dissolved oxygen concentration, and the preset efficiency factor are analyzed to determine the change in dissolved oxygen demand. The relationship between the change in dissolved oxygen demand and the preset change in dissolved oxygen opening is analyzed to determine the preset valve opening; the valve is then adjusted according to the change in opening.

6. A wastewater treatment method according to claim 5, characterized in that, The steps for controlling the aeration device to aerate at the total air volume include: The parameters for starting the device are determined based on the relationship between the total gas volume and the preset gas volume device parameters. Obtain the adjustment parameters of the aeration device; the adjustment parameters are characterized by the single adjustment time and single adjustment step of the aeration device; control the aeration device to start according to the starting device parameters, and control the started aeration device to perform aeration with the adjustment parameters; Obtain the real-time air volume detected by the aeration device; Determine whether the real-time gas volume meets the total gas volume requirement; If it does not meet the requirements, continue to control the aeration device to adjust the parameters for aeration, and continue to obtain the real-time air volume detected by the aeration device for cyclical judgment. If the conditions are met, the aeration device will be controlled to maintain stable aeration.

7. A wastewater treatment system, characterized in that, include: The acquisition module is used to acquire the inlet trigger signal, inlet detection parameters, and outlet detection parameters; A memory for storing a program of a wastewater treatment method as described in any one of claims 1 to 6; The processor and the program in the memory can be loaded and executed by the processor to implement the wastewater treatment method as described in any one of claims 1 to 6.

8. A smart terminal, characterized in that, It includes a memory and a processor, wherein the memory stores a computer program that can be loaded by the processor and executed as described in any one of claims 1 to 6 for wastewater treatment.

9. A computer-readable storage medium, characterized in that, The computer program is stored and can be loaded by a processor and executed as described in any one of claims 1 to 6.

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