Method, device, equipment and medium for establishing and applying dissolved oxygen concentration change model

Abstract

The application discloses a method and device for establishing and applying a dissolved oxygen concentration change model, equipment and a medium, and relates to the technical field of sewage treatment. In the application, a description model of turbulence-induced dissolved oxygen increase and a description model of microbial dissolved oxygen consumption are constructed, and the following dissolved oxygen balance is considered: when the reactor reaches a steady state, the dissolved oxygen consumption rate of microorganisms at each height of the target area from the aerator to the bottom of the reactor is equal to the turbulence-induced dissolved oxygen increase rate. Therefore, based on the description model of turbulence-induced dissolved oxygen increase, the description model of microbial dissolved oxygen consumption and the dissolved oxygen balance of the target area, a dissolved oxygen concentration change model of the target area is constructed. The technical problem of high cost and inaccuracy of field monitoring of the dissolved oxygen concentration of the target area below the aerator is solved, and the technical problem that the existing classical diffusion theory is difficult to quantitatively describe the nonlinear transmission process of the dissolved oxygen in the space below the aerator and cannot realize accurate prediction is solved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of sewage treatment, and in particular to a method for establishing a dissolved oxygen concentration variation model, a method for applying the dissolved oxygen concentration variation model, a device for establishing the dissolved oxygen concentration variation model, a device for applying the dissolved oxygen concentration variation model, a sewage treatment device, and a storage medium. BACKGROUND

[0002] In the field of sewage treatment, the aeration process is the core technology for maintaining the activity of microorganisms in the activated sludge method. The core goal is to meet the oxygen demand of microorganisms for degrading pollutants (such as organic matter, nitrogen and phosphorus) by delivering oxygen to the water body. The dissolved oxygen (DO) concentration, as a key control parameter of the aeration process, directly affects the growth and metabolism efficiency of microorganisms, the pollutant removal effect, and the system energy consumption.

[0003] Currently, the evaluation and optimization of aeration effect in the industry mainly focus on the dissolved oxygen distribution in the space above the aerator (such as the area from the water surface to the height of the aerator). The aeration efficiency can be intuitively reflected by online monitoring of the DO concentration, but the dissolved oxygen variation mechanism in the space below the aerator (i.e. the area between the aerator and the bottom of the tank) has been ignored for a long time. In this case, the industry's research on the dissolved oxygen below the aerator relies on field monitoring, but the monitoring cost is high, the data is highly discrete, and there is a lack of effective theoretical formula for process description, making it difficult to achieve accurate prediction.

[0004] The fundamental reason for this phenomenon is that the water flow and mass transfer process below the aerator is more complex than above the aerator, and the application of classical dissolved oxygen diffusion theory such as Fick's law has significant limitations. The classical theory usually assumes that the fluid is static or laminar, and only considers the direct mass transfer diffusion of oxygen from the gas phase to the liquid phase, but the area below the aerator is actually in a strong turbulent mixing environment (dominated by water disturbance caused by rising aeration bubbles), and is simultaneously affected by the coupling of multiple processes such as microbial metabolism (such as oxygen consumption by aerobic bacteria), pollutant migration and transformation (such as the decomposition of organic matter to consume DO, and the release of nitrogen gas by denitrification to affect gas-liquid interface mass transfer). These complex factors cause the dissolved oxygen concentration to present a nonlinear, non-steady state variation law in the vertical direction (along the water depth) and the horizontal direction, which cannot be quantitatively described by a simple diffusion model.

[0005] The above content is only used to assist in understanding the technical solutions of the present application, and does not represent the acknowledgement of the above content as prior art. SUMMARY

[0006] The main purpose of the present application is to provide a dissolved oxygen concentration change model establishment method, a dissolved oxygen concentration change model application method, a dissolved oxygen concentration change model establishment device, a dissolved oxygen concentration change model application device, a sewage treatment equipment and a storage medium, aiming to solve the technical problems that the existing classical diffusion theory is difficult to quantitatively describe the nonlinear transmission process of dissolved oxygen under the aerator, cannot realize accurate prediction, and the on-site monitoring cost of the dissolved oxygen concentration of the target area under the aerator is high and inaccurate.

[0007] To achieve the above-mentioned purpose, the present application provides a dissolved oxygen concentration change model establishment method, which comprises:

[0008] A description model of the increase of dissolved oxygen caused by turbulence is constructed.

[0009] A description model of the consumption of dissolved oxygen by microorganisms is constructed.

[0010] According to the description model of the increase of dissolved oxygen caused by turbulence, the description model of the consumption of dissolved oxygen by microorganisms, and the dissolved oxygen balance of the target area, a dissolved oxygen concentration change model of the target area is constructed, wherein the target area is the area from the aerator to the bottom of the reactor, and the dissolved oxygen balance is that the dissolved oxygen consumption rate of microorganisms at each height in the target area is equal to the dissolved oxygen increase rate caused by turbulence when the reactor reaches a stable state.

[0011] In an embodiment, the step of constructing the description model of the increase of dissolved oxygen caused by turbulence comprises:

[0012] According to the installation height of the aerator, the target height, and the aeration intensity, the fitting parameters of the influence of the aeration intensity on the turbulence oxygenation, the fitting parameters of the decay relationship of the turbulence oxygenation with the height, and the fitting parameters of the decay relationship of the turbulence oxygenation with the installation height of the aerator, a description model of the increase of dissolved oxygen caused by turbulence is constructed.

[0013] In an embodiment, the step of constructing the description model of the consumption of dissolved oxygen by microorganisms comprises:

[0014] According to the specific oxygen consumption rate of sludge, the sludge concentration and the dissolved oxygen concentration at each height in the target area, and the half-saturation constant, a description model of the consumption of dissolved oxygen by microorganisms is constructed.

[0015] In an embodiment, the step of constructing the description model of the consumption of dissolved oxygen by microorganisms according to the specific oxygen consumption rate of sludge, the sludge concentration and the dissolved oxygen concentration at each height in the target area, and the half-saturation constant, comprises:

[0016] According to the average sludge concentration of the target area, the sludge settling rate constant, the installation height of the aerator, the target height, and the sludge concentration at different target heights in the target area, a sludge concentration longitudinal distribution model of the target area is constructed.

[0017] According to the sludge concentration longitudinal distribution model of the target region, the sludge concentration at each height of the target region is determined.

[0018] In an embodiment, the method for establishing the dissolved oxygen concentration variation model further comprises:

[0019] The coefficients in the description model of the dissolved oxygen increase caused by turbulence or the sludge concentration longitudinal distribution model of the target region are fitted by a nonlinear least square method, the coefficients in the description model of the dissolved oxygen increase caused by turbulence are fitting parameters of the influence of the aeration intensity on the turbulence oxygenation, fitting parameters of the decay relationship of the turbulence oxygenation with the height, fitting parameters of the decay relationship of the turbulence oxygenation with the installation height of the aerator, and the coefficient in the sludge concentration longitudinal distribution model of the target region is the sludge settling rate constant.

[0020] To achieve the above object, the application further provides a method for applying a dissolved oxygen concentration variation model, which comprises:

[0021] According to the installation height of the aerator, the target height, and the dissolved oxygen concentration variation model of the target region established by the method for establishing the dissolved oxygen concentration variation model as described above, the dissolved oxygen concentration at the target height is determined.

[0022] According to the installation height of the aerator, the dissolved oxygen concentration, and the dissolved oxygen concentration variation model, the target height corresponding to the dissolved oxygen concentration is determined.

[0023] According to the dissolved oxygen concentration of the target region, the target height, and the dissolved oxygen concentration variation model, the installation height of the aerator is determined.

[0024] In addition, to achieve the above object, the application further provides an establishment device of a dissolved oxygen concentration variation model, which comprises:

[0025] A first construction module is configured to construct a description model of the dissolved oxygen increase caused by turbulence.

[0026] A second construction module is configured to construct a description model of the dissolved oxygen consumption by microorganisms.

[0027] A third construction module is configured to construct a dissolved oxygen concentration variation model of a target region according to the description model of the dissolved oxygen increase caused by turbulence, the description model of the dissolved oxygen consumption by microorganisms, and a dissolved oxygen balance of the target region, wherein the target region is a region from the aerator to the bottom of the reactor, and the dissolved oxygen balance is that the dissolved oxygen consumption rate of microorganisms at each height of the target region is equal to the dissolved oxygen increase rate caused by turbulence when the reactor reaches a steady state.

[0028] In addition, to achieve the above object, the application further provides an application device of the dissolved oxygen concentration change model.

[0029] The first application module is configured to determine the dissolved oxygen concentration at the target height according to the installation height of the aerator, the target height, and the dissolved oxygen concentration change model of the target region established by the establishing device of the dissolved oxygen concentration change model.

[0030] The second application module is configured to determine the target height corresponding to the dissolved oxygen concentration according to the installation height of the aerator, the dissolved oxygen concentration, and the dissolved oxygen concentration change model.

[0031] The third application module is configured to determine the installation height of the aerator according to the dissolved oxygen concentration of the target region, the target height, and the dissolved oxygen concentration change model.

[0032] In addition, to achieve the above object, the application further provides a sewage treatment device, which comprises a memory, a processor, and a computer program stored in the memory and executable on the processor, and the computer program is configured to implement the establishing method of the dissolved oxygen concentration change model and / or the steps of the application method of the dissolved oxygen concentration change model.

[0033] In addition, to achieve the above object, the application further provides a storage medium, which is a computer readable storage medium, and the storage medium stores a computer program, and the computer program is executed by a processor to implement the establishing method of the dissolved oxygen concentration change model and / or the steps of the application method of the dissolved oxygen concentration change model.

[0034] In addition, to achieve the above object, the application further provides a computer program product, which comprises a computer program, and the computer program is executed by a processor to implement the establishing method of the dissolved oxygen concentration change model and / or the steps of the application method of the dissolved oxygen concentration change model.

[0035] The one or more technical solutions provided by the application have at least the following technical effects:

[0036] In the present application, a description model of turbulence-induced increase of dissolved oxygen and a description model of microbial consumption of dissolved oxygen are constructed, and the following dissolved oxygen balance is considered: when the reactor reaches a steady state, the rate of microbial consumption of dissolved oxygen at each height of the target region below the aerator to the bottom of the reactor is equal to the rate of turbulence-induced increase of dissolved oxygen, so that the dissolved oxygen concentration change model of the target region is constructed based on the description model of turbulence-induced increase of dissolved oxygen, the description model of microbial consumption of dissolved oxygen, and the dissolved oxygen balance of the target region, so that the dissolved oxygen concentration at any target height of the target region can be determined based on the installation height of the aerator and the dissolved oxygen concentration change model of the target region. Compared with the existing classical diffusion theory which is difficult to quantitatively describe the nonlinear transmission process of dissolved oxygen in the space below the aerator, the present application quantitatively analyzes the dissolved oxygen concentration at different target heights of the target region by fully considering the microbial consumption of dissolved oxygen and the turbulence-induced increase of dissolved oxygen, and the entire confirmation process has low cost and high accuracy. BRIEF DESCRIPTION OF DRAWINGS

[0037] The accompanying drawings, which are incorporated into and form a part of the specification, illustrate an embodiment consistent with the present application and, together with the description, serve to explain the principles of the application.

[0038] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the accompanying drawings needed to be used in the embodiments or prior art description will be briefly introduced as follows. Obviously, for those skilled in the art, other drawings can also be obtained based on these drawings without any creative effort.

[0039] Figure 1 A flowchart is provided for the first embodiment of the method for establishing the dissolved oxygen concentration change model of the present application;

[0040] Figure 2 A flowchart is provided for the first embodiment of the application method of the dissolved oxygen concentration change model of the present application;

[0041] Figure 3 A DO longitudinal distribution diagram under the aerobic aerator is provided for different aeration intensities and installation heights of the aerobic aerator of the present application;

[0042] Figure 4 A sludge concentration distribution diagram is provided for different aeration intensities and installation heights of the aerobic aerator of the present application;

[0043] Figure 5 A module structure diagram of the establishment device of the dissolved oxygen concentration change model of the embodiment of the present application is provided;

[0044] Figure 6 A module structure diagram of the application device of the dissolved oxygen concentration change model of the embodiment of the present application is provided;

[0045] Figure 7 Figure 1 is a schematic diagram of a device structure of a hardware operating environment of a sewage treatment device according to an embodiment of the present application.

[0046] The object, features and advantages of the present application will be further illustrated in conjunction with the embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0047] It should be understood that the specific embodiments described herein are merely intended to explain the technical solutions of the present application, and are not intended to limit the present application.

[0048] In order to better understand the technical solutions of the present application, the following will be described in detail in conjunction with the accompanying drawings and specific embodiments.

[0049] It should be noted that the execution subject of the present embodiment can be a computing service device with data processing, network communication and program running functions, such as a tablet computer, a personal computer, a mobile phone, etc., or an electronic device, a sewage treatment device, etc. capable of realizing the above functions. The present embodiment and the following embodiments will be described below taking the sewage treatment device as an example.

[0050] Based on this, the present embodiment provides a method for establishing a dissolved oxygen concentration change model, which will be described in detail with reference to Figure 1 , Figure 1 Figure 2 is a flowchart of a method for establishing a dissolved oxygen concentration change model according to a first embodiment of the present application.

[0051] In the present embodiment, the method for establishing a dissolved oxygen concentration change model comprises steps S10-S30:

[0052] Step S10, constructing a description model of dissolved oxygen increase caused by turbulent flow;

[0053] Step S20, constructing a description model of dissolved oxygen consumption by microorganisms;

[0054] Step S30, constructing a dissolved oxygen concentration change model of the target area according to the description model of dissolved oxygen increase caused by turbulent flow, the description model of dissolved oxygen consumption by microorganisms and the dissolved oxygen balance of the target area; wherein the target area is the area from the aerator to the bottom of the reactor, and the dissolved oxygen balance is that the dissolved oxygen consumption rate of microorganisms at each height in the target area is equal to the dissolved oxygen increase rate caused by turbulent flow when the reactor reaches a stable state.

[0055] Currently, the evaluation and optimization of aeration effect in the industry mainly focus on the dissolved oxygen distribution in the space above the aerator (such as the area from the water surface to the height of the aerator), and the aeration efficiency can be intuitively reflected by online monitoring of the DO concentration, but the dissolved oxygen variation mechanism in the space below the aerator (i.e. the area between the aerator and the bottom of the tank) has been ignored for a long time. The fundamental reason for this phenomenon is that the water flow and mass transfer process below the aerator is more complex than that above the aerator, and the application of classical dissolved oxygen diffusion theory such as Fick's law has significant limitations. The classical theory usually assumes that the fluid is static or laminar, only considers the direct mass transfer diffusion of oxygen from the gas phase to the liquid phase, but the area below the aerator is actually in a strong turbulent mixing environment (dominated by water disturbance caused by rising aeration bubbles), and is simultaneously affected by the coupling of multiple processes such as microbial metabolism (such as aerobic bacteria consuming oxygen, anaerobic / aerobic bacteria producing oxygen), pollutant migration and transformation (such as organic matter decomposition consuming DO, denitrification reaction releasing nitrogen affecting gas-liquid interface mass transfer). These complex factors cause the dissolved oxygen concentration to present a nonlinear, non-steady state variation law in the vertical direction (along the water depth) and the horizontal direction, which cannot be quantitatively described by a simple diffusion model.

[0056] To this end, in the present application, a theoretical model is established that can comprehensively reflect the influence of turbulent mixing, biological metabolism and pollutant migration on dissolved oxygen, and a theoretical derivation formula for the spatial distribution of dissolved oxygen concentration below the aerator is provided, to solve the key problem that the classical diffusion theory in the prior art cannot quantitatively describe the nonlinear transfer process of dissolved oxygen in the space below the aerator. It provides clear theoretical guidance for clarifying the dissolved oxygen concentration variation process below the aerator which is comprehensively affected by turbulent flow, microbial activity, pollutant migration and transformation, etc., and greatly helps the design optimization and system operation energy consumption reduction of the aeration system.

[0057] In an embodiment, the area below the aerobic aerator to the bottom of the reactor is selected as the research area, i.e. the target area, to establish a dissolved oxygen concentration variation model. It is assumed that the dissolved oxygen concentration in the target area is affected by two aspects, the decrease of dissolved oxygen concentration caused by microbial consumption and the increase of dissolved oxygen caused by turbulent flow , without considering the influence of other processes on the dissolved oxygen concentration, such as the influence of other substances in the influent on the dissolved oxygen concentration. It is assumed that when the reactor reaches a steady state, the DO concentration at any height in the target area no longer changes, i.e. at each height, the dissolved oxygen consumption rate is equal to the increase rate.

[0058]

[0059] In a feasible implementation, step S10 comprises:

[0060] Based on the installation height of the aerator, the target height, the aeration intensity, the fitting parameters of the influence of aeration intensity on turbulent oxygenation, the fitting parameters of the attenuation relationship of turbulent oxygenation with height, and the fitting parameters of the attenuation relationship of turbulent oxygenation with the installation height of the aerator, a descriptive model for the increase of dissolved oxygen caused by turbulence is constructed.

[0061] In models describing fluid mixing and diffusion, attenuation processes are often presented in an exponential form. For example, the exponential form fits experimental data well when describing eddy diffusion or turbulent diffusion. In this embodiment, dissolved oxygen mass transfer caused by turbulence can be considered a diffusion-like process; therefore, the exponential form is chosen to describe the effect of the turbulent component on dissolved oxygen concentration, thus illustrating the gradual decrease in turbulence intensity with increasing distance from the aerator. Aeration intensity Target height and the installation height of the aerator All of these affect the turbulent oxygenation effect; specifically, The larger the value, the more significant the increase in oxygenation in the turbulent part; The larger the volume, the slightly reduced oxygenation in the turbulent portion; From 0 to As the turbulent oxygenation gradually increases from 0 to its maximum / maximum value, the following functional form is considered to satisfy the above requirements:

[0062]

[0063] in, These are fitting parameters for the effect of aeration intensity on turbulent oxygenation. These are fitting parameters for the attenuation relationship of turbulent oxygenation with altitude. These are fitting parameters for the attenuation relationship of turbulent oxygenation with the installation height of the aerator.

[0064] In another feasible implementation, step S20 includes:

[0065] Based on the sludge specific oxygen consumption rate, the sludge concentration and dissolved oxygen concentration at each height in the target area, and the half-saturation constant, a descriptive model for microbial dissolved oxygen consumption is constructed.

[0066] The rate of dissolved oxygen consumption by microorganisms can be described by the classic monood equation:

[0067]

[0068] in, It is the specific oxygen consumption rate of sludge: the amount of oxygen consumed per unit volume of sludge mixture per unit time, which can be taken as 10 gO2 / gSS-h. MLVSS is the sludge concentration at each height of the target region, i.e. the mass concentration of volatile suspended solids in the mixed liquor, which represents the approximate amount of active microorganisms in the biological reactor (such as an aeration tank) and is related to the degree of sludge settling, and further, OUR is the oxygen utilization rate, i.e. the amount of oxygen consumed per unit time. DO is the dissolved oxygen concentration at each height of the target region, K is the half-saturation constant, which is 1.0 mg / L. It should be noted that, S corresponds to the single limiting substrate concentration in the classical Monod equation. In this embodiment, since the oxygen consumption rate is significantly affected by the dissolved oxygen concentration when the dissolved oxygen concentration approaches the half-saturation constant of the microorganisms, the substrate concentration S in the classical Monod equation can be replaced by the dissolved oxygen concentration and the parameters adjusted, thereby describing the oxygen transfer kinetics of the target region.

[0069] In a feasible implementation, the step of constructing a description model of the consumption of dissolved oxygen by microorganisms according to the specific oxygen consumption rate of the sludge, the sludge concentration at each height of the target region, the dissolved oxygen concentration, and the half-saturation constant can include steps A11-A12 before the step:

[0070] Step A11, constructing a sludge concentration longitudinal distribution model of the target region according to the average sludge concentration of the target region, the sludge settling rate constant, the installation height of the aerator, the target height, and the sludge concentration at different target heights of the target region;

[0071] Step A12, determining the sludge concentration at each height of the target region according to the sludge concentration longitudinal distribution model of the target region.

[0072] The function of the sludge concentration longitudinal distribution, i.e. the sludge concentration at each target height of the target region is related to the degree of sludge settling, and assuming that the sludge settling in this embodiment follows the model of sludge settling in an ideal state, its concentration at different heights can be described as follows:

[0073]

[0074] wherein, ML is the average sludge concentration of the target region, K is the sludge settling rate constant.

[0075] It should be noted that the above formula (4) refers to the ideal settling tank model in the classical sedimentation theory, which assumes that the sludge concentration is exponentially distributed in the vertical direction.

[0076] In summary, the change in the dissolved oxygen concentration at the final steady state can be represented as:

[0077]

[0078] In an embodiment, the method for establishing the dissolved oxygen concentration variation model further comprises:

[0079] coefficients in the model describing the increase of dissolved oxygen caused by turbulence or the model of longitudinal distribution of sludge concentration in the target region, the coefficients in the model describing the increase of dissolved oxygen caused by turbulence being the fitting parameters of the influence of aeration intensity on turbulence oxygenation, the fitting parameters of the decay relationship of turbulence oxygenation with height, and the fitting parameters of the decay relationship of turbulence oxygenation with the installation height of aerators, and the coefficients in the model of longitudinal distribution of sludge concentration in the target region being the sludge settling rate constant.

[0080] It is worth noting that the equation (dissolved oxygen concentration variation model of the target region) derived in the present application is a complex multiple exponential function with many unknown quantities, and the variables cannot be isolated by simple algebraic operations, which makes it impossible to express the solution of the equation by algebra or closed form, i.e., the equation has no analytical solution. Numerical solution is an important method for solving equations without analytical solution. For the dissolved oxygen concentration variation model of the target region in the present application, numerical solution is used to obtain the best estimated value of the parameters. The basic principle of numerical solution is to convert the solving process into a discrete calculation that can be executed by a computer. By defining an approximation function or an iterative method, the numerical solution can approximate the actual solution of the equation within a limited number of calculation steps. Common numerical solution methods include bisection method, Newton method, gradient descent method, and quasi-Newton method, etc. The appropriate solving algorithm can be selected according to the nonlinearity, dimension, and number of parameters, boundary and constraint conditions, convergence speed and efficiency, etc.

[0081] In an embodiment, the sludge settling rate constant can be fitted by experimental data using nonlinear least squares method. As can be seen from equation (4), the nonlinearity of the sludge concentration model is low, and the curve_fit function in Python is a numerical optimization algorithm that combines gradient descent method and Newton method, which can automatically handle the optimization of residual squares with simple initial value setting, and can obtain a local optimal solution in a short time. Therefore, in this embodiment, the curve_fit function is used to adjust the sludge settling rate constant to make the model prediction value consistent with the experimental measurement value as much as possible, and the fitting process is optimized by minimizing the sum of squares of residuals RSS. The model determination coefficient is used to quantify the explanatory power of the model, which is defined as follows:

[0082]

[0083] wherein, RSS is the sum of squares of residuals, i.e., the sum of squares of differences between the model prediction value and the experimental measurement value, The total variation of the measured values from their mean value is given by the following formula:

[0084]

[0085] wherein is the mean value of the measurements.

[0086] For each data set, the value of the set is first calculated, which is used to assess the fit of the model to the set. Then the overall is calculated by the ratio between the sum of the values of all sets and the sum of the values of all sets:

[0087]

[0088] In another embodiment, the parameters in the dissolved oxygen concentration variation model are also fitted using the nonlinear least squares method to optimize the model parameters. The optimal set of turbulence parameters is found by minimizing the sum of the squared residuals between the model output and the experimental data, so that the predicted dissolved oxygen concentration by the model matches the experimental measurement data as much as possible. The parameter set includes the turbulence oxygenation impact parameter of aeration intensity , the turbulence oxygenation decay parameter with height , and the turbulence oxygenation decay parameter with aerator installation height . Since the parameters are complexly related to each other and involve multiple dimensions such as aeration intensity , aerobic aerator installation height , and target height , the above curve_fit function is no longer suitable for solving this parameter set.

[0089] The L-BFGS-B algorithm in Python is used in this embodiment for turbulence partial parameter fitting, and the main reasons include: (1) the L-BFGS-B algorithm is a global optimization method based on the quasi-Newton method, which is suitable for nonlinear least squares models with boundary constraints; (2) the invention needs to globally fit the turbulence parameter set , not just a local optimal solution, and the L-BFGS-B algorithm can effectively find the parameter set that minimizes the sum of squared residuals in a multi-dimensional parameter space; (3) in the process of nonlinear least squares fitting, the L-BFGS-B algorithm shows good robustness and can effectively converge to the global optimal solution.

[0090] The fitting steps are briefly described as follows: (1) set the initial value of the turbulence partial parameter set; (2) define the objective function as the sum of squared residuals , i.e., the sum of squared errors between the model predicted value and the experimental measured value. The smaller, the better the model fits the data; (3) using the minimize function in the scipy library, using the L-BFGS-B algorithm to minimize , get the optimal turbulent parameter value; (4) generate model prediction value through optimal parameter, and compare with experimental data, through calculating model to quantify model explanation ability. Similarly, the model explanation ability is quantified by using the coefficient of determination, which is defined as follows:

[0091]

[0092] is the sum of squared residuals, that is, the sum of squared differences between the model prediction value and the experimental measurement value, is the total variation of the measurement value and its mean, and the specific formula is as follows:

[0093]

[0094] is the measurement mean.

[0095] For each group of data, first calculate the value of the group, which is used to evaluate the fitting effect of the model on the group. Then the overall is calculated by the ratio between the sum of of all groups and the sum of of all groups:

[0096]

[0097] Through the above fitting process, the complex relationship between turbulent effect, sludge concentration and dissolved oxygen change can be quantitatively described, which provides model support for subsequent accurate determination of the position of the anoxic zone below the aerator, such as the area where DO<0.5 mg / L. At the same time, this fitting process also reveals the dynamic change characteristics of the influence of turbulence and microorganisms on dissolved oxygen concentration under different heights and aeration intensities, which provides a theoretical basis for further clarifying the pollutant removal mechanism in this area.

[0098] The application embodiment further provides an application method of the dissolved oxygen concentration change model. Referring to Figure 2 , Figure 2 is a flowchart of the first embodiment of the application method of the dissolved oxygen concentration change model.

[0099] In this embodiment, the application method of the dissolved oxygen concentration change model comprises steps T10-T30:

[0100] ​​Step T10, determining the dissolved oxygen concentration at the target height according to the installation height of the aerator, the target height, and the dissolved oxygen concentration variation model of the target region established by the method for establishing a dissolved oxygen concentration variation model;

[0101] Step T20, determining the target height corresponding to the dissolved oxygen concentration according to the installation height of the aerator, the dissolved oxygen concentration, and the dissolved oxygen concentration variation model;

[0102] Step T30, determining the installation height of the aerator according to the dissolved oxygen concentration of the target region, the target height, and the dissolved oxygen concentration variation model.

[0103] It should be noted that the dissolved oxygen concentration variation model involved in the present embodiment is established according to the method for establishing a dissolved oxygen concentration variation model in the first embodiment of the method for establishing a dissolved oxygen concentration variation model.

[0104] That is, in the case where any two parameter values of the installation height of the aerator, the target height, and the dissolved oxygen concentration of the target region are known, the specific value of the third parameter other than the two known parameter values is determined according to the dissolved oxygen concentration variation model of the target region.

[0105] By substituting the reactor aeration intensity , the average sludge concentration of the target region , the sludge specific oxygen consumption rate , the half-saturation constant , and the sludge settling rate constant k, the aeration intensity effect on turbulent oxygenation parameter , the turbulent oxygenation decay parameter with height , and the turbulent oxygenation decay parameter with the installation height of the aerator fitted by the nonlinear least squares method into the dissolved oxygen concentration variation model of the target region, the dissolved oxygen concentration corresponding to different target heights can be solved under the condition that the installation height of the aerobic aerator is known , the dissolved oxygen concentration corresponding to a certain target height can be solved under the condition that the installation height of the aerobic aerator is known , and the corresponding target height can be solved under the condition that the installation height of the aerobic aerator and the dissolved oxygen concentration .

[0106] In another embodiment, in the design of a vertical A / O reactor, the aeration intensity and the height of the anoxic zone, i.e., the target height (corresponding height at DO=0.5 mg / L ​​​), the installation height of the aerator can be solved using the brentq function in Python The reason for choosing the brentq function is that the brentq method is a numerical root-finding algorithm suitable for monotonic increasing or decreasing continuous functions. The advantages of this method include: (1) the brentq method can stably find the root if there is a root in the domain. (2) The algorithm will reduce the interval according to the positive and negative changes of the function value, and quickly converge to the root. (3) The algorithm is suitable for complex equations that cannot directly calculate the derivative. The specific steps are as follows: First, define the difference function DO_difference (C), which represents the difference between the turbulent oxygenation rate and the microbial oxygen consumption rate at each target height h. This difference function should be close to zero in ideal conditions, i.e., the balance between the oxygen supplied by turbulence and the oxygen consumed by microorganisms. Then provide a reasonable initial interval for the installation height of the aerator Then call the brentq function to solve it by continuously narrowing the interval to find the root until a H value is found that makes the difference function close to zero, and output the optimal H value.

[0107] In one application scenario of the present application, the reactor handles a water volume of 120 m 3 / d, with an effective volume of 53 m 3 , a cross-sectional area of 9.2 m 2 , an aeration intensity of 9 m 3 / m 3 -ww, an oxygen concentration in the aerobic zone of 1.0 mg / L, and a theoretical anoxic zone effective volume of 12 m 3 , which corresponds to an anoxic zone height (target height) of 1.3 m, i.e., the DO concentration at a water depth of 1.3 m is 0.5 mg / L. The DO concentration in the region below the target height is stably below 0.5 m. The target height at which the DO concentration is 0.5 mg / L is 1.3 m, and the monitoring data of the dissolved oxygen concentration and sludge concentration distribution below the aerator are shown in Figure 3 and Figure 4 .

[0108] According to the monitoring results of the sludge concentration at different heights below the aerator, the sludge concentration distribution is fitted using formula (4), and the fitting results of the sludge settling parameters are as follows:

[0109]

[0110]

[0111] The model determination coefficient is used to quantify the model explanation ability, and the overall The value of 0.6 indicates that the model can explain 60% of the data variation. Considering that the reactor size is large, sludge settling may cause uneven distribution of sludge concentration on the same plane, and the acceptable range of sludge concentration is usually large, with an up-and-down fluctuation of 1-2 g / L being a common phenomenon, the fitting effect of the model should be given a large tolerance. Although the fitting effect is not high, it is also acceptable.

[0112] The calculated optimal parameter set has the following values:

[0113]

[0114]

[0115]

[0116] The overall value is 0.82, indicating that the model can explain 82% of the data variation, and has a good fitting effect. Therefore, the function relationship of dissolved oxygen at different heights under the aerobic aerator is:

[0117]

[0118] By substituting the actual aeration intensity of the reactor during operation , the sludge concentration at the corresponding height, the sludge specific oxygen consumption rate , and the half-saturation constant , through the above equation, both the dissolved oxygen concentration C corresponding to different target heights h can be obtained under the condition of known aerobic aerator installation height H, and the aerobic aerator installation height H can be obtained under the condition of known dissolved oxygen concentration C corresponding to a certain target height h.

[0119] Figure 3 In this embodiment, the sludge concentration under the condition of an aeration intensity of 9 m 3 / m 3 -ww can be obtained, in addition, the sludge specific oxygen consumption rate is 10 mg-O2 / (g-MLVSS·h), and the half-saturation constant is 0.2 mg / L. The DO concentration corresponding to a height of 1.3 m is 0.5 mg / L. By substituting these parameters into equation (6), the installation height of the aerobic aerator can be obtained as 2.4 m.

[0120] Currently, 1. The classical diffusion theory cannot accurately describe the nonlinear transfer process of dissolved oxygen in the strong turbulent environment under the aerator; 2. The existing model does not systematically integrate the coupling effect of turbulent mixing, microbial metabolism, and pollutant degradation on dissolved oxygen; 3. There is a lack of theoretical tools that can quantitatively predict the dissolved oxygen concentration corresponding to different water depths under the aerator. In view of this, for the first time in this application, the three key processes of turbulent transport, biological metabolism, and pollutant migration are integrated into a single theoretical model, breaking through the limitations of the classical diffusion theory which only considers gas-liquid mass transfer. Through theoretical derivation, the vertical space and time distribution of dissolved oxygen concentration under the aerator is accurately predicted, providing a mathematical basis for the dynamic regulation of the aeration system. The parameters used in the model can be calibrated through actual working condition experiments and are suitable for different scales and different aeration modes.

[0121] By predicting the DO distribution under the aerator, the application can guide the installation height of the aerator and the distribution of the aeration amount, avoiding local DO being too high or too low. Secondly, based on the prediction results of the model, the aeration strategy is dynamically adjusted, the fan frequency is timely adjusted, the oxygen utilization rate is improved, and the energy consumption is reduced. In addition, the application can provide theoretical support for the process upgrade of the sewage treatment plant, such as converting from a single aerobic unit to an anoxic-aerobic simultaneous denitrification unit, to help improve the pollutant removal efficiency.

[0122] In summary, by constructing a theoretical model of dissolved oxygen concentration coupled with multiple processes, the application fills the gap in the research on the distribution of dissolved oxygen under the aerator, and provides a key technical tool for the fine design and operation of the aeration system of the sewage treatment plant, which has significant engineering application value and environmental benefits.

[0123] It should be noted that the above examples are only for understanding the application and do not constitute a limitation on the establishment method of the dissolved oxygen concentration variation model and the application method of the dissolved oxygen concentration variation model. Based on this technical concept, more forms of simple transformation are within the protection scope of the application.

[0124] The application also provides an establishment device of a dissolved oxygen concentration variation model, please refer to Figure 5 , the establishment device of the dissolved oxygen concentration variation model comprises:

[0125] The first construction module 10 is used for constructing a description model of the increase of dissolved oxygen caused by turbulent flow;

[0126] The second construction module 20 is used for constructing a description model of the consumption of dissolved oxygen by microorganisms;

[0127] The third construction module 30 is configured to construct a dissolved oxygen concentration variation model of the target region according to a description model of the increase of the dissolved oxygen caused by the turbulence, a description model of the consumption of the dissolved oxygen by the microorganisms, and a dissolved oxygen balance of the target region, wherein the target region is a region from the aerator to the bottom of the reactor, and the dissolved oxygen balance is that the consumption rate of the dissolved oxygen by the microorganisms at each height of the target region is equal to the increase rate of the dissolved oxygen caused by the turbulence when the reactor reaches a steady state.

[0128] In an embodiment, the first construction module 10 is further configured to:

[0129] The description model of the increase of the dissolved oxygen caused by the turbulence is constructed according to the installation height of the aerator, the target height, the aeration intensity, the fitting parameters of the influence of the aeration intensity on the turbulence oxygenation, the fitting parameters of the attenuation relationship of the turbulence oxygenation with the height, and the fitting parameters of the attenuation relationship of the turbulence oxygenation with the installation height of the aerator.

[0130] In an embodiment, the second construction module 20 is further configured to:

[0131] The description model of the consumption of the dissolved oxygen by the microorganisms is constructed according to the specific oxygen consumption rate of the sludge, the sludge concentration and the dissolved oxygen concentration at each height of the target region, and the half-saturation constant.

[0132] In an embodiment, the second construction module 20 is further configured to:

[0133] The step of constructing the description model of the consumption of the dissolved oxygen by the microorganisms according to the specific oxygen consumption rate of the sludge, the sludge concentration and the dissolved oxygen concentration at each height of the target region, and the half-saturation constant comprises:

[0134] The longitudinal distribution model of the sludge concentration of the target region is constructed according to the average sludge concentration of the target region, the sludge settling rate constant, the installation height of the aerator, the target height, and the sludge concentration at different target heights of the target region.

[0135] In an embodiment, the establishment device of the dissolved oxygen concentration variation model further comprises a fitting module configured to:

[0136] The coefficients in the description model of the increase of the dissolved oxygen caused by the turbulence or the longitudinal distribution model of the sludge concentration of the target region are fitted by a nonlinear least square method, wherein the coefficients in the description model of the increase of the dissolved oxygen caused by the turbulence are the fitting parameters of the influence of the aeration intensity on the turbulence oxygenation, the fitting parameters of the attenuation relationship of the turbulence oxygenation with the height, and the fitting parameters of the attenuation relationship of the turbulence oxygenation with the installation height of the aerator, and the coefficient in the longitudinal distribution model of the sludge concentration of the target region is the sludge settling rate constant.

[0137] The application further provides an application device of the dissolved oxygen concentration variation model, which is described in detail in the following. Figure 6 The application device of the dissolved oxygen concentration variation model comprises:

[0138] The first application module A is configured to determine the dissolved oxygen concentration at the target height according to the installation height of the aerator, the target height, and the dissolved oxygen concentration variation model.

[0139] The second application module B is configured to determine the target height corresponding to the dissolved oxygen concentration according to the installation height of the aerator, the dissolved oxygen concentration, and the dissolved oxygen concentration variation model.

[0140] The third application module C is configured to determine the installation height of the aerator according to the dissolved oxygen concentration of the target region, the target height, and the dissolved oxygen concentration variation model.

[0141] The establishment device of the dissolved oxygen concentration variation model provided in the present application adopts the establishment method of the dissolved oxygen concentration variation model in the above embodiments, and the application device of the dissolved oxygen concentration variation model provided in the present application adopts the application method of the dissolved oxygen concentration variation model in the above embodiments, which can solve the technical problems that the existing classical diffusion theory is difficult to quantitatively describe the nonlinear transmission process of the dissolved oxygen in the space below the aerator, cannot realize accurate prediction, and the cost of on-site monitoring of the dissolved oxygen concentration in the target region below the aerator is high and inaccurate. Compared with the prior art, the establishment device of the dissolved oxygen concentration variation model provided in the present application has the same beneficial effects as the establishment method of the dissolved oxygen concentration variation model provided in the above embodiments, and other technical features in the establishment device of the dissolved oxygen concentration variation model are the same as the features disclosed in the above embodiments, which will not be repeated here. Compared with the prior art, the application device of the dissolved oxygen concentration variation model provided in the present application has the same beneficial effects as the application method of the dissolved oxygen concentration variation model provided in the above embodiments, and other technical features in the application device of the dissolved oxygen concentration variation model are the same as the features disclosed in the above embodiments, which will not be repeated here.

[0142] The present application provides a sewage treatment equipment, which comprises at least one processor and a memory in communication connection with the at least one processor, wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to execute the establishment method of the dissolved oxygen concentration variation model in the above embodiments and / or the application method of the dissolved oxygen concentration variation model in the above embodiments.

[0143] Reference will be made to the following Figure 7The diagram illustrates a structural schematic of a wastewater treatment device suitable for implementing embodiments of this application. The wastewater treatment device in these embodiments may include, but is not limited to, mobile terminals such as mobile phones, laptops, digital radio receivers, PDAs (Personal Digital Assistants), PADs (Portable Application Description), PMPs (Portable Media Players), and in-vehicle terminals (e.g., in-vehicle navigation terminals), as well as fixed terminals such as digital TVs and desktop computers. Figure 7 The wastewater treatment equipment shown is merely an example and should not impose any limitations on the functionality and scope of use of the embodiments of this application.

[0144] like Figure 7 As shown, the wastewater treatment equipment may include a processing device 1001 (e.g., a central processing unit, a graphics processing unit, etc.), which can perform various appropriate actions and processes according to a program stored in a read-only memory 1002 or a program loaded from a storage device 1003 into a random access memory 1004. The random access memory 1004 also stores various programs and data required for the operation of the wastewater treatment equipment. The processing device 1001, the read-only memory 1002, and the random access memory 1004 are interconnected via a bus 1005. An input / output interface 1006 is also connected to the bus. Typically, the following systems can be connected to the input / output interface 1006: input devices 1007 including, for example, a touch screen, touchpad, keyboard, mouse, image sensor, microphone, accelerometer, gyroscope, etc.; output devices 1008 including, for example, a liquid crystal display (LCD), speaker, vibrator, etc.; storage devices 1003 including, for example, magnetic tape, hard disk, etc.; and communication devices 1009. Communication device 1009 allows the wastewater treatment equipment to communicate wirelessly or wiredly with other equipment to exchange data. Although the figure shows wastewater treatment equipment with various systems, it should be understood that it is not required to implement or have all the systems shown. More or fewer systems may be implemented alternatively.

[0145] In particular, the processes described above with reference to the flowcharts can be implemented as computer software programs in accordance with embodiments of the present application. For example, embodiments of the present application include a computer program product comprising a computer program carried on a computer readable medium, the computer program comprising program code for performing the methods illustrated by the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via a communication device, or installed from a storage device 1003, or installed from a read-only memory 1002. When the computer program is executed by the processing device 1001, the above-mentioned functions defined in the methods of the embodiments of the present application are performed.

[0146] The sewage treatment equipment provided by the present application adopts the method for establishing the dissolved oxygen concentration change model in the above embodiment and / or the method for applying the dissolved oxygen concentration change model in the above embodiment, which can solve the technical problems that the existing classical diffusion theory cannot quantitatively describe the nonlinear transmission process of dissolved oxygen in the space below the aerator, cannot realize accurate prediction, and the cost of on-site monitoring of the dissolved oxygen concentration in the target area below the aerator is high and inaccurate. Compared with the prior art, the sewage treatment equipment provided by the present application has the same beneficial effects as the method for establishing the dissolved oxygen concentration change model in the above embodiment and / or the method for applying the dissolved oxygen concentration change model in the above embodiment, and other technical features in the sewage treatment equipment are the same as the features disclosed in the above embodiment, which will not be repeated here.

[0147] It should be understood that various parts of the present application can be realized by hardware, software, firmware or a combination thereof. In the description of the above embodiments, specific features, structures, materials or characteristics can be combined in any one or more embodiments or examples in a suitable manner.

[0148] The above describes only the specific implementation of the present application, but the protection scope of the present application is not limited thereto, and any person skilled in the art can easily think of changes or replacements within the technical scope disclosed by the present application, which should be covered within the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

[0149] The present application provides a computer readable storage medium having stored thereon computer readable program instructions (i.e. computer programs) for performing the method for establishing the dissolved oxygen concentration change model in the above embodiment and / or the method for applying the dissolved oxygen concentration change model in the above embodiment.

[0150] The computer readable storage medium provided in the application may, for example, be a U disk, but is not limited to an electric, magnetic, optical, electromagnetic, infrared, or semiconductor system or device, or any combination of the above. More specific examples of the computer readable storage medium may include, but are not limited to, an electric connection with one or more conductive wires, a portable computer disk, a hard disk, a random access memory (RAM), a read only memory (ROM), an erasable programmable read only memory (EPROM or flash memory), an optical fiber, a portable compact disk read only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the embodiment, the computer readable storage medium may be any tangible medium containing or storing a program that can be used by or in combination with an instruction execution system or device. The program code contained on the computer readable storage medium can be transmitted by any suitable medium, including but not limited to an electric wire, an optical cable, an RF (Radio Frequency), and the like, or any suitable combination of the above.

[0151] The computer readable storage medium described above may be contained in the sewage treatment equipment, or may exist separately without being assembled into the sewage treatment equipment.

[0152] The computer readable storage medium described above carries one or more programs, which, when executed by the sewage treatment equipment, cause the sewage treatment equipment to: construct a description model of turbulence-induced dissolved oxygen increase; construct a description model of microbial consumption of dissolved oxygen; construct a dissolved oxygen concentration change model of a target region according to the description model of turbulence-induced dissolved oxygen increase, the description model of microbial consumption of dissolved oxygen, and a dissolved oxygen balance of the target region; wherein the target region is a region from the aerator to the bottom of the reactor, and the dissolved oxygen balance is that the microbial dissolved oxygen consumption rate at each height in the target region is equal to the turbulence-induced dissolved oxygen increase rate when the reactor reaches a steady state. And / or, according to the installation height of the aerator, the target height, and the dissolved oxygen concentration change model established by the establishment method, determine the dissolved oxygen concentration at the target height; according to the installation height of the aerator, the dissolved oxygen concentration, and the dissolved oxygen concentration change model, determine the target height corresponding to the dissolved oxygen concentration; according to the dissolved oxygen concentration of the target region, the target height, and the dissolved oxygen concentration change model, determine the installation height of the aerator.

[0153] Computer program code for carrying out operations of the present application can be written in any combination of one or more programming languages, including an object oriented programming language such as Java, Smalltalk, C++ or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code can execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the latter scenario, the remote computer can be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or the connection can be made to an external computer (for example, through the Internet using an Internet Service Provider).

[0154] The computer program instructions can also be loaded onto a computer, other programmable data processing apparatus, or other devices to cause a series of operational steps to be performed on the computer, other programmable apparatus or other devices to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide processes for implementing the functions / acts specified in the flowchart and / or block diagram block or blocks.

[0155] The modules involved in the embodiments of the present application can be implemented in software or hardware. In some cases, the names of the modules do not constitute a limitation on the modules themselves.

[0156] The readable storage medium provided by the application is a computer readable storage medium, which stores computer readable program instructions (i.e., computer programs) for executing the above-mentioned establishment method of the dissolved oxygen concentration change model and / or the application method of the dissolved oxygen concentration change model, and can solve the technical problems that the existing classical diffusion theory is difficult to quantitatively describe the nonlinear transmission process of dissolved oxygen in the space below the aerator, cannot realize accurate prediction, and the cost of on-site monitoring of the dissolved oxygen concentration in the target area below the aerator is high and inaccurate. Compared with the prior art, the computer readable storage medium provided by the application has the same beneficial effects as the establishment method of the dissolved oxygen concentration change model and / or the application method of the dissolved oxygen concentration change model provided by the above-mentioned embodiments, and details are not repeated here.

[0157] The application further provides a computer program product comprising a computer program, which, when executed by a processor, implements the steps of the above-mentioned establishment method of the dissolved oxygen concentration change model and / or the application method of the dissolved oxygen concentration change model.

[0158] The computer program product provided by the application can solve the technical problems that the existing classical diffusion theory is difficult to quantitatively describe the nonlinear transmission process of dissolved oxygen in the space below the aerator, cannot realize accurate prediction, and the cost of on-site monitoring of the dissolved oxygen concentration in the target area below the aerator is high and inaccurate. Compared with the prior art, the computer program product provided by the application has the same beneficial effects as the establishment method of the dissolved oxygen concentration change model and / or the application method of the dissolved oxygen concentration change model provided by the above-mentioned embodiments, and details are not repeated here.

[0159] The above-mentioned is only part of the embodiments of the application, and does not limit the patent scope of the application, and any equivalent structural transformation made by using the content of the application specification and drawings, or direct / indirect application in other related technical fields is included in the patent protection scope of the application.

Claims

1. A method for establishing a dissolved oxygen concentration variation model, characterized in that, The method for establishing the dissolved oxygen concentration variation model comprises the following steps: According to the installation height of the aerator, the target height, the aeration intensity, the fitting parameters of the influence of the aeration intensity on the turbulent oxygenation, the fitting parameters of the attenuation relationship of the turbulent oxygenation with the height, and the fitting parameters of the attenuation relationship of the turbulent oxygenation with the installation height of the aerator, a description model of the increase of the dissolved oxygen caused by the turbulent flow is constructed: ； wherein, is the aeration intensity, is the target height, is the installation height of the aerator, is a fitting parameter of the effect of aeration intensity on turbulent oxygenation, is a fitting parameter of the decay relationship of turbulent oxygenation with height, is a fitting parameter of the decay relationship of turbulent oxygenation with the installation height of the aerator; According to the specific oxygen consumption rate of the sludge, the sludge concentration and the dissolved oxygen concentration at each height in the target area, and the half-saturation constant, a description model of the consumption of the dissolved oxygen by the microorganisms is constructed: ； The longitudinal distribution model of the sludge concentration in the target area is: ； wherein, is the specific oxygen uptake rate of the sludge, is the sludge concentration at each height of the target zone, is the average sludge concentration of the target zone, is the settling rate constant of the sludge, is the dissolved oxygen concentration at each height of the target zone, is the half-saturation constant; According to the description model of the increase of the dissolved oxygen caused by the turbulent flow, the description model of the consumption of the dissolved oxygen by the microorganisms, and the dissolved oxygen balance of the target area, a dissolved oxygen concentration variation model of the target area is constructed: ； The target area is the area from the aerator to the bottom of the reactor, and the dissolved oxygen balance is that the consumption rate of the dissolved oxygen by the microorganisms is equal to the increase rate of the dissolved oxygen caused by the turbulent flow at each height in the target area when the reactor reaches a stable state.

2. The method for establishing the dissolved oxygen concentration change model as described in claim 1, characterized in that, The method for establishing the dissolved oxygen concentration variation model further comprises the following steps: By using a nonlinear least square method, the coefficients in the description model of the increase of the dissolved oxygen caused by the turbulent flow or the longitudinal distribution model of the sludge concentration in the target area are fitted, the coefficients in the description model of the increase of the dissolved oxygen caused by the turbulent flow are the fitting parameters of the influence of the aeration intensity on the turbulent oxygenation, the fitting parameters of the attenuation relationship of the turbulent oxygenation with the height, and the fitting parameters of the attenuation relationship of the turbulent oxygenation with the installation height of the aerator, and the coefficients in the longitudinal distribution model of the sludge concentration in the target area are the sludge settling rate constant.

3. A method for applying a dissolved oxygen concentration change model, characterized in that, The application method of the dissolved oxygen concentration variation model comprises the following steps: According to the installation height of the aerator, the target height, and the dissolved oxygen concentration variation model of the target area established by the method for establishing the dissolved oxygen concentration variation model according to any one of claims 1 to 2, the dissolved oxygen concentration at the target height is determined; or, According to the installation height of the aerator, the dissolved oxygen concentration, and the dissolved oxygen concentration variation model, the target height corresponding to the dissolved oxygen concentration is determined; or, According to the dissolved oxygen concentration of the target area, the target height, and the dissolved oxygen concentration variation model, the installation height of the aerator is determined.

4. An apparatus for establishing a dissolved oxygen concentration variation model, comprising: The device for establishing the dissolved oxygen concentration variation model comprises: A first construction module is configured to construct a description model of the increase of the dissolved oxygen caused by the turbulent flow according to the installation height of the aerator, the target height, the aeration intensity, the fitting parameters of the influence of the aeration intensity on the turbulent oxygenation, the fitting parameters of the attenuation relationship of the turbulent oxygenation with the height, and the fitting parameters of the attenuation relationship of the turbulent oxygenation with the installation height of the aerator: ； wherein, is the aeration intensity, is the target height, is the installation height of the aerator, is a fitting parameter of the effect of aeration intensity on turbulent oxygenation, is a fitting parameter of the decay relationship of turbulent oxygenation with height, is a fitting parameter of the decay relationship of turbulent oxygenation with the installation height of the aerator; A second construction module is configured to construct a description model of the consumption of the dissolved oxygen by the microorganisms according to the specific oxygen consumption rate of the sludge, the sludge concentration and the dissolved oxygen concentration at each height in the target area, and the half-saturation constant: ； The longitudinal distribution model of the sludge concentration in the target area is: ； wherein, is the specific oxygen uptake rate of the sludge, is the sludge concentration at each height of the target zone, is the average sludge concentration of the target zone, is the settling rate constant of the sludge, is the dissolved oxygen concentration at each height of the target zone, is the half-saturation constant; A third construction module is configured to construct a dissolved oxygen concentration variation model of the target area according to the description model of the increase of the dissolved oxygen caused by the turbulent flow, the description model of the consumption of the dissolved oxygen by the microorganisms, and the dissolved oxygen balance of the target area: ； The target region is a region from the aerator to the bottom of the reactor, and the dissolved oxygen balance is that the dissolved oxygen consumption rate of microorganisms is equal to the dissolved oxygen increase rate caused by turbulence at each height of the target region when the reactor reaches a steady state.

5. An apparatus for applying a dissolved oxygen concentration variation model, characterized by The application device of the dissolved oxygen concentration change model comprises: a first application module configured to determine the dissolved oxygen concentration at the target height according to the installation height of the aerator, the target height, and the dissolved oxygen concentration change model of the target region established by the establishment device of the dissolved oxygen concentration change model according to claim 4; or a second application module configured to determine the target height corresponding to the dissolved oxygen concentration according to the installation height of the aerator, the dissolved oxygen concentration, and the dissolved oxygen concentration change model; or a third application module configured to determine the installation height of the aerator according to the dissolved oxygen concentration of the target region, the target height, and the dissolved oxygen concentration change model.

6. A sewage treatment apparatus characterised in that, The device comprises a memory, a processor, and a computer program stored on the memory and executable on the processor, and the computer program is configured to implement the establishment method of the dissolved oxygen concentration change model according to any one of claims 1 to 2, and / or the steps of the application method of the dissolved oxygen concentration change model according to claim 3.

7. A storage medium, characterized by The storage medium is a computer readable storage medium, and the storage medium stores a computer program, and the computer program is executed by the processor to implement the establishment method of the dissolved oxygen concentration change model according to any one of claims 1 to 2, and / or the steps of the application method of the dissolved oxygen concentration change model according to claim 3.

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