Aeration fan control method and device, electronic equipment and storage medium

Abstract

The embodiment of the invention discloses an aeration fan control method and device, electronic equipment and a storage medium. The method comprises the following steps: acquiring historical oxygen demand and historical ammonia nitrogen concentration of a contact oxidation pond in a sewage treatment system in a first time period; determining a target oxygen demand of the contact oxidation pond in a second time period based on the historical oxygen demand, the historical ammonia nitrogen concentration and an oxygen demand prediction model; based on the current ammonia nitrogen concentration, the current reaction temperature and the current oxygen mass transfer coefficient corresponding to the current collection moment in the second time period of the contact oxidation pond, determining the incidence relation between the fan frequency and the dissolved oxygen concentration corresponding to the current collection moment; and the current fan control strategy corresponding to the current acquisition moment is determined based on the association relationship between the fan frequency corresponding to the current acquisition moment and the dissolved oxygen concentration and the target oxygen demand, so that dynamic control of the aeration fan can be accurately and conveniently realized, the control accuracy of the dissolved oxygen concentration is improved, and the operation cost is saved.

Description

Technical Field

[0001] The present invention relates to the field of wastewater treatment technology, and in particular to an aeration blower control method, device, electronic equipment and storage medium. Background Technology

[0002] As a core power source in biological wastewater treatment processes, the operating efficiency of aeration blowers directly affects the treatment effect and energy economy of the wastewater treatment system. In aerobic biological treatment, the aeration system achieves its key functions through a dual-effect mechanism: firstly, by supplying dissolved oxygen (DO), it maintains the activity of aerobic microorganisms, promoting the efficient decomposition of organic matter; secondly, it uses pneumatic agitation to achieve homogeneous mixing of sludge and water, enhancing mass transfer efficiency. Statistics show that the energy consumption of the aeration system accounts for 30%-60% of the total energy consumption of a wastewater treatment plant, making it a key area for process optimization and energy conservation.

[0003] Currently, in cigarette factory wastewater treatment plants, aeration control often employs manual adjustment and timed start-stop modes. Operators manually adjust the blower operation based on dissolved oxygen concentration readings, or operate it according to a fixed cycle (e.g., starting for 20 minutes every 4 hours).

[0004] However, this type of control method has the following problems: First, the time-varying nature of water quality and quantity leads to a non-linear demand for dissolved oxygen concentration, making it difficult to achieve precise matching with a fixed control mode. Second, manual adjustment is subject to response lag and subjective error, easily resulting in insufficient or excessive aeration. More importantly, improper aeration control can trigger a series of chain reactions; excessive aeration not only increases energy consumption but also causes activated sludge flocs to break down, reducing settling performance. Furthermore, residual dissolved oxygen entering the anoxic / anaerobic zone will disrupt the biochemical environment for nitrogen and phosphorus removal. Therefore, an effective method for controlling aeration is urgently needed. Summary of the Invention

[0005] This invention provides an aeration blower control method, device, electronic equipment, and storage medium to accurately and conveniently achieve dynamic control of the aeration blower, improve the accuracy of dissolved oxygen concentration control, and save operating costs.

[0006] In a first aspect, embodiments of the present invention provide an aeration blower control method, comprising:

[0007] Obtain the historical oxygen demand and historical ammonia nitrogen concentration of the contact oxidation tank in the wastewater treatment system during the first time period;

[0008] Based on the historical oxygen demand, the historical ammonia nitrogen concentration, and the oxygen demand prediction model, the target oxygen demand of the contact oxidation tank in the second time period is determined.

[0009] Based on the current ammonia nitrogen concentration, current reaction temperature, and current oxygen mass transfer coefficient of the contact oxidation tank at the current sampling time in the second time period, the correlation between the fan frequency and dissolved oxygen concentration at the current sampling time is determined.

[0010] Based on the correlation between the fan frequency and dissolved oxygen concentration at the current data acquisition time and the target oxygen demand, the current fan control strategy at the current data acquisition time is determined.

[0011] Optionally, the method further includes: filtering and denoising the candidate ammonia nitrogen concentration and candidate reaction temperature collected at the current acquisition time based on a preset denoising method to determine the denoised current ammonia nitrogen concentration and current reaction temperature; and adjusting the candidate oxygen mass transfer coefficient corresponding to the current acquisition time based on a preset coefficient adjustment method to obtain the adjusted current oxygen mass transfer coefficient.

[0012] Optionally, the method further includes: filtering and denoising the candidate dissolved oxygen concentration collected at the current collection time based on a preset denoising method to determine the denoised current dissolved oxygen concentration; determining the current biofilm thickness corresponding to the current collection time based on the target biofilm thickness prediction model, the influent flow rate collected at the current collection time, the current dissolved oxygen concentration, the current ammonia nitrogen concentration, and the current reaction temperature; and adjusting the candidate oxygen mass transfer coefficient based on the current biofilm thickness and a preset thickness threshold to obtain the adjusted current oxygen mass transfer coefficient.

[0013] Optionally, the method further includes: if the current biofilm thickness is greater than a preset thickness threshold, adjusting the current oxygen mass transfer coefficient based on the current biofilm thickness, the preset thickness threshold, and the candidate oxygen mass transfer coefficient; if the current biofilm thickness is less than or equal to the preset thickness threshold, detecting the time relationship between the current acquisition time and the current adjustment period; if the current acquisition time is the end time of the current adjustment period, adjusting the current oxygen mass transfer coefficient based on a pre-constructed difference minimization function and the candidate oxygen mass transfer coefficient; if the current acquisition time is the beginning or middle time of the current adjustment period, adjusting the candidate oxygen mass transfer coefficient based on the current dissolved oxygen concentration and a preset dissolved oxygen concentration threshold to obtain the adjusted current oxygen mass transfer coefficient.

[0014] Optionally, the method further includes: determining a periodic adjustment method based on the degree of dissolved oxygen concentration fluctuation corresponding to the previous adjustment cycle and a preset fluctuation threshold; adjusting the previous adjustment cycle based on the periodic adjustment method to determine the current adjustment cycle; wherein, when the current oxygen mass transfer coefficient changes, the current control cycle ends.

[0015] Optionally, the method further includes: constructing a dynamic response model based on biofilm kinetics and oxygen mass transfer theory, with the fan operating frequency as input and dissolved oxygen concentration as output; and determining the correlation between the fan frequency and dissolved oxygen concentration at the current acquisition time based on the dynamic response model, the current ammonia nitrogen concentration, the current reaction temperature, and the current oxygen mass transfer coefficient.

[0016] Secondly, embodiments of the present invention also provide an aeration blower control device, the device comprising:

[0017] The historical data acquisition module is used to acquire the historical oxygen demand and historical ammonia nitrogen concentration of the contact oxidation tank in the wastewater treatment system during the first time period.

[0018] The target oxygen demand determination module is used to determine the target oxygen demand of the contact oxidation tank in the second time period based on the historical oxygen demand, the historical ammonia nitrogen concentration, and the oxygen demand prediction model.

[0019] The correlation determination module is used to determine the correlation between the fan frequency and dissolved oxygen concentration at the current sampling time based on the current ammonia nitrogen concentration, current reaction temperature and current oxygen mass transfer coefficient of the contact oxidation tank at the current sampling time in the second time period.

[0020] The current fan control strategy determination module is used to determine the current fan control strategy corresponding to the current acquisition time based on the correlation between the fan frequency and dissolved oxygen concentration at the current acquisition time and the target oxygen demand.

[0021] Thirdly, embodiments of the present invention also provide an electronic device, the electronic device comprising:

[0022] One or more processors;

[0023] Memory, used to store one or more programs;

[0024] When the one or more programs are executed by the one or more processors, the one or more processors implement the aeration blower control method as provided in any embodiment of the present invention.

[0025] Fourthly, embodiments of the present invention provide a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the aeration blower control method as provided in any embodiment of the present invention.

[0026] Fifthly, embodiments of the present invention provide a computer program product, including a computer program that, when executed by a processor, implements the aeration blower control method as provided in any embodiment of the present invention.

[0027] The technical solution of this invention involves acquiring the historical oxygen demand (OD) and historical ammonia nitrogen concentration of a contact oxidation tank in a wastewater treatment system during a first time period; determining the target O demand of the contact oxidation tank during a second time period based on the historical O demand, the historical ammonia nitrogen concentration, and an O demand prediction model; determining the correlation between the blower frequency and dissolved oxygen concentration at the current acquisition time within the second time period based on the current ammonia nitrogen concentration, current reaction temperature, and current oxygen mass transfer coefficient of the contact oxidation tank; and determining the current blower control strategy at the current acquisition time based on the correlation between the blower frequency and dissolved oxygen concentration and the target O demand. This allows for accurate and convenient dynamic control of the aeration blower using the current blower control strategy, improving the accuracy of dissolved oxygen concentration control and saving operating costs.

[0028] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of the present invention, nor is it intended to limit the scope of the invention. Other features of the invention will become readily apparent from the following description. Attached Figure Description

[0029] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0030] Figure 1 This is a flowchart of an aeration blower control method provided in Embodiment 1 of the present invention;

[0031] Figure 2 This is an example diagram of a wastewater treatment system according to Embodiment 1 of the present invention;

[0032] Figure 3 This is a flowchart of an aeration blower control method provided in Embodiment 2 of the present invention;

[0033] Figure 4 This is a schematic diagram of the structure of an aeration blower control device provided in Embodiment 3 of the present invention;

[0034] Figure 5 This is a schematic diagram of the structure of an electronic device that implements the aeration blower control method of the present invention. Detailed Implementation

[0035] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0036] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0037] Example 1

[0038] Figure 1 This is a flowchart illustrating an aeration blower control method provided in Embodiment 1 of the present invention. This embodiment is applicable to situations involving dynamic control of aeration blowers in wastewater treatment systems. The method can be executed by an aeration blower control device, which can be implemented in hardware and / or software and can be configured in an electronic device. For example... Figure 1 As shown, the method includes:

[0039] S110. Obtain the historical oxygen demand and historical ammonia nitrogen concentration of the contact oxidation tank in the wastewater treatment system during the first time period.

[0040] Here, "sewage treatment system" can refer to the sewage treatment system within a cigarette factory's wastewater treatment plant. "Contact oxidation tank" can refer to a biological treatment device that primarily uses biofilm technology, supplemented by activated sludge technology. The contact oxidation tank achieves the degradation and purification of organic matter through full contact between oxygenated wastewater and the biofilm on the packing material. "First time period" can refer to a pre-set historical time period. "Historical oxygen demand" can refer to the oxygen demand collected in the contact oxidation tank within the first time period. "Historical ammonia nitrogen concentration" can refer to the ammonia nitrogen concentration collected in the contact oxidation tank within the first time period. Both historical oxygen demand and historical ammonia nitrogen concentration correspond to various historical data collection moments within the first time period. Both historical oxygen demand and historical ammonia nitrogen concentration are discrete data corresponding to historical data collection moments within the first time period.

[0041] In this embodiment, Figure 2 An example diagram of a wastewater treatment system is provided. See also... Figure 2 The wastewater treatment system includes: equalization tank 1, equalization tank lift pump 2, COD sensor 3, ammonia nitrogen sensor 4, equalization tank outlet flow meter 5, influent dissolved oxygen sensor 6, influent flow meter 7, water tank temperature sensor 8, contact oxidation tank 9, effluent dissolved oxygen sensor 10, pressure transmitter 11, aeration blower 12, and motor temperature sensor 13. The COD sensor can refer to a Chemical Oxygen Demand (COD) sensor. The wastewater treatment process is as follows: Wastewater is treated in the equalization tank, then pumped to the coagulation reaction tank, followed by sedimentation and filtration in the sedimentation tank, and finally flows by gravity into the hydrolysis acidification tank for degradation. Afterward, it flows by gravity into the contact oxidation tank for further decomposition. The treated wastewater then undergoes subsequent flotation treatment, multi-media activated carbon filtration, and clean water reuse. The dissolved oxygen concentration (COD) is monitored in real time using the influent dissolved oxygen sensor (DO1) and effluent dissolved oxygen sensor (DO2) in the contact oxidation tank. in and C out (Unit: mg / L). DO1 (inlet) is used to monitor the oxygen replenishment efficiency of the aeration system in real time, while DO2 (outlet) reflects the actual oxygen consumption of microorganisms. The difference between the two can assess the dynamic balance of the system and avoid misjudgments caused by the hydraulic residence time lag of a single sensor.

[0042] Specifically, the historical oxygen demand and historical ammonia nitrogen concentration of the contact oxidation tank in the wastewater treatment system during the first time period are obtained from the data storage location of the wastewater treatment system.

[0043] S120. Based on historical oxygen demand, historical ammonia nitrogen concentration, and oxygen demand prediction model, determine the target oxygen demand of the contact oxidation tank in the second time period.

[0044] The oxygen demand (OD) prediction model can refer to a pre-trained time series model. This model can be used to predict the influent COD of a contact oxidation tank over a future period, such as 2 hours, based on historical data (i.e., historical OD and historical ammonia nitrogen concentration). The second time period can refer to the period immediately following the first. The target OD can refer to the OD corresponding to each data collection moment within the future period.

[0045] Specifically, historical oxygen demand (OD) and historical ammonia nitrogen concentration are input into the OD prediction model for prediction. Based on the output of the OD prediction model, the target OD for each data collection time in the contact oxidation tank during the second time period is determined. The target OD can be expressed as: O demand (t)=ARIMA(COD hist ,S hist ).

[0046] S130. Based on the current ammonia nitrogen concentration, current reaction temperature, and current oxygen mass transfer coefficient of the contact oxidation tank at the current sampling time in the second time period, determine the correlation between the fan frequency and dissolved oxygen concentration at the current sampling time.

[0047] The current acquisition time can refer to the moment when data is being collected within the second time period. As time progresses, the current acquisition time will be shifted, with the latest acquisition time being used as the current acquisition time. The current ammonia nitrogen concentration can refer to the ammonia nitrogen concentration in the contact oxidation tank at the current acquisition time. In this embodiment, an ammonia nitrogen sensor in the wastewater treatment system is used to collect the current ammonia nitrogen concentration (NH3-N), denoted as S. The current reaction temperature can refer to the water temperature in the contact oxidation tank at the current acquisition time. In this embodiment, a water temperature sensor in the wastewater treatment system is used to collect the current reaction temperature, denoted as T1. The oxygen mass transfer coefficient can refer to the volume of oxygen transferred per unit volume of wastewater per unit time through the gas-liquid interface. The physical meaning of the oxygen mass transfer coefficient can be the reciprocal of the time required for the dissolved oxygen concentration in the wastewater to rise from its initial value to its saturation value. The current oxygen mass transfer coefficient can refer to the oxygen mass transfer coefficient applicable to the current acquisition time. That is, the current oxygen mass transfer coefficient can refer to the one applicable to the current adjustment cycle. The current oxygen mass transfer coefficient will change according to environmental changes in the contact oxidation tank.

[0048] Specifically, the current ammonia nitrogen concentration, current reaction temperature, and current oxygen mass transfer coefficient of the contact oxidation tank at the current sampling time within the second time period are substituted into the preset closed-loop control model to determine the correlation between the fan frequency and dissolved oxygen concentration at the current sampling time. The preset closed-loop control model can be used to accurately reflect the current operating conditions.

[0049] Based on the above technical solution, "determining the correlation between the fan frequency and dissolved oxygen concentration at the current sampling time based on the current ammonia nitrogen concentration, current reaction temperature, and current oxygen mass transfer coefficient of the contact oxidation tank at the current sampling time in the second time period" can include: constructing a dynamic response model with the fan operating frequency as input and dissolved oxygen concentration as output based on biofilm kinetics and oxygen mass transfer theory; and determining the correlation between the fan frequency and dissolved oxygen concentration at the current sampling time based on the dynamic response model, the current ammonia nitrogen concentration, the current reaction temperature, and the current oxygen mass transfer coefficient.

[0050] The preset closed-loop control model may include, but is not limited to, a dynamic response model. The dynamic response model takes the fan operating frequency as input and dissolved oxygen concentration as output.

[0051] Specifically, based on biofilm kinetics and oxygen mass transfer theory, a dynamic response model is constructed with the fan operating frequency as input and dissolved oxygen concentration as output. The dynamic response model is as follows:

[0052]

[0053] Where, k La (f) is the oxygen mass transfer coefficient. C s It is the saturated dissolved oxygen concentration, calculated from the reaction temperature, using the formula: (Unit: mg / L). R NH (T1,S) is the ammonia nitrogen oxidation rate, calculated using the following formula: (Unit: mg / (L·h)), where the ammonia nitrogen oxidation rate coefficient and temperature index can be preset. For example, an ammonia nitrogen oxidation rate coefficient of 0.15 and a temperature index of 0.03 are derived from a multiple regression analysis of 3 years of historical data (R0). 2 =0.89). K s This is a half-saturation constant, which can also be preset, for example, set to 0.5 mg / L, determined by fitting 12 consecutive months of operating data from the wastewater treatment plant of the cigarette factory to which the wastewater treatment system belongs. The current ammonia nitrogen concentration, current reaction temperature, and current oxygen mass transfer coefficient are substituted into the dynamic response model to determine the correlation between the fan frequency and dissolved oxygen concentration at the current data collection moment.

[0054] In this embodiment, the oxygen mass transfer rate is the rate at which the aeration blower transfers oxygen to the water through the gas-liquid interface, and is related to the blower's operating frequency, characterizing the oxygen transfer efficiency. The saturated dissolved oxygen concentration is determined by the reaction temperature and gas pressure. The difference between the current dissolved oxygen concentration and the saturated dissolved oxygen concentration is positively correlated with the oxygen mass transfer rate. The microbial oxygen consumption rate is the rate at which microorganisms consume oxygen to degrade ammonia nitrogen. The ammonia nitrogen oxidation rate is affected by temperature and the influent ammonia nitrogen concentration, and dissolved oxygen has an inhibitory effect on the ammonia nitrogen oxidation reaction.

[0055] S140. Based on the correlation between the fan frequency and dissolved oxygen concentration and the target oxygen demand at the current data acquisition time, determine the current fan control strategy at the current data acquisition time.

[0056] The current wind turbine control strategy can refer to the control strategy for the wind turbine operating frequency. In this embodiment, the relationship between oxygen demand and dissolved oxygen concentration is preset. For example, taking the potassium dichromate method as an example, organic matter (in the form of C6H) 12 Taking O6 as an example, it is oxidized. The amount of oxygen consumed (COD) is directly proportional to the amount of potassium dichromate consumed. The amount of oxidant used can be deduced by titration. The expression is as follows:

[0057] COD=((C in -C out )·V·M o2 ·1000) / (M 氧化剂 ·θ);

[0058] Among them, C in C was collected by the influent dissolved oxygen sensor. out M was collected by the dissolved oxygen sensor in the effluent. o2 M is the molar mass of oxygen (32 g / mol). 氧化剂 θ is the molar mass of potassium dichromate (294.18 g / mol), θ is the molar ratio of the oxidant to the organic matter (e.g., θ = 1 / 6), and V is the liquid volume in the contact oxidation tank.

[0059] Specifically, based on the correlation between the fan frequency and dissolved oxygen concentration at the current data collection time, and the pre-set relationship between oxygen demand and dissolved oxygen concentration, the relationship between the fan frequency and oxygen demand at the current data collection time is determined. Based on the target oxygen demand at the current data collection time, and the relationship between the fan frequency and oxygen demand at the current data collection time, the total fan operating frequency at the current data collection time is determined, and the total fan operating frequency is evenly distributed to each aeration fan to obtain the current fan control strategy at the current data collection time.

[0060] The technical solution of this invention obtains the historical oxygen demand and historical ammonia nitrogen concentration of the contact oxidation tank in the sewage treatment system during a first time period; based on the historical oxygen demand, historical ammonia nitrogen concentration, and oxygen demand prediction model, determines the target oxygen demand of the contact oxidation tank during a second time period; based on the current ammonia nitrogen concentration, current reaction temperature, and current oxygen mass transfer coefficient of the contact oxidation tank at the current acquisition time in the second time period, determines the correlation between the blower frequency and dissolved oxygen concentration at the current acquisition time; based on the correlation between the blower frequency and dissolved oxygen concentration at the current acquisition time and the target oxygen demand, determines the current blower control strategy at the current acquisition time. Therefore, the current blower control strategy can accurately and conveniently achieve dynamic control of the aeration blower, improving the accuracy of dissolved oxygen concentration control and saving operating costs.

[0061] Example 2

[0062] Figure 3 This is a flowchart of an aeration blower control method provided in Embodiment 2 of the present invention. Based on the above embodiments, this embodiment describes in detail the process of determining the current ammonia nitrogen concentration, current reaction temperature, and current oxygen mass transfer coefficient. Explanations of terms that are the same as or corresponding to those in the above embodiments are not repeated here. Figure 3 As shown, the method includes:

[0063] S310. Obtain the historical oxygen demand and historical ammonia nitrogen concentration of the contact oxidation tank in the wastewater treatment system during the first time period.

[0064] S320. Based on historical oxygen demand, historical ammonia nitrogen concentration, and oxygen demand prediction model, determine the target oxygen demand of the contact oxidation tank in the second time period.

[0065] S330. Based on the preset denoising method, filter and denoise the candidate ammonia nitrogen concentration and candidate reaction temperature collected at the current acquisition time, and determine the current ammonia nitrogen concentration and current reaction temperature after denoising.

[0066] The preset denoising method can refer to the denoising method used during the data acquisition process in a wastewater treatment system. For example, the preset denoising method can be, but is not limited to, the Kalman filter algorithm. The candidate ammonia nitrogen concentration can refer to the undenoised ammonia nitrogen concentration. The candidate reaction temperature can refer to the undenoised reaction temperature.

[0067] Specifically, the Kalman filter algorithm is used to filter and denoise the candidate ammonia nitrogen concentration directly collected by the ammonia nitrogen sensor and the candidate reaction temperature directly collected by the water tank temperature sensor at the current acquisition time, and the denoised current ammonia nitrogen concentration and current reaction temperature are determined.

[0068] S340. Adjust the candidate oxygen mass transfer coefficient corresponding to the current acquisition time based on the preset coefficient adjustment method to obtain the adjusted current oxygen mass transfer coefficient.

[0069] The preset coefficient adjustment method refers to a pre-set adjustment method for the oxygen mass transfer coefficient under different conditions. The candidate oxygen mass transfer coefficient refers to the oxygen mass transfer coefficient applicable to the previous adjustment cycle. There is only one applicable oxygen mass transfer coefficient in each adjustment cycle, which can also be understood as the oxygen mass transfer coefficient that conforms to the operating conditions within the adjustment cycle.

[0070] Specifically, the operating conditions corresponding to the current data acquisition time are analyzed to determine whether the candidate oxygen mass transfer coefficient is applicable to these conditions. If applicable, the candidate oxygen mass transfer coefficient is used as the current oxygen mass transfer coefficient. If not applicable, a corresponding coefficient adjustment method is determined for the operating conditions corresponding to the current data acquisition time, and the candidate oxygen mass transfer coefficient is adjusted using this method to obtain the adjusted current oxygen mass transfer coefficient.

[0071] Based on the above technical solution, "adjusting the candidate oxygen mass transfer coefficient corresponding to the current acquisition time based on a preset coefficient adjustment method to obtain the adjusted current oxygen mass transfer coefficient" can include: filtering and denoising the candidate dissolved oxygen concentration acquired at the current acquisition time based on a preset denoising method to determine the denoised current dissolved oxygen concentration; determining the current biofilm thickness corresponding to the current acquisition time based on the target biofilm thickness prediction model, the influent flow rate acquired at the current acquisition time, the current dissolved oxygen concentration, the current ammonia nitrogen concentration, and the current reaction temperature; and adjusting the candidate oxygen mass transfer coefficient based on the current biofilm thickness and a preset thickness threshold to obtain the adjusted current oxygen mass transfer coefficient.

[0072] Here, candidate dissolved oxygen concentration can refer to the undenoised dissolved oxygen concentration. Candidate dissolved oxygen concentrations include: inlet dissolved oxygen concentration and outlet dissolved oxygen concentration. The target biofilm thickness prediction model can refer to a pre-trained biofilm thickness prediction model. The biofilm thickness is related to the difference between influent and effluent dissolved oxygen (C). out -C in The ammonia nitrogen degradation rate (ΔS / Δt) and influent flow rate Q showed a significant positive correlation. The target biofilm thickness prediction model can take the inlet dissolved oxygen concentration, outlet dissolved oxygen concentration, ammonia nitrogen concentration, influent flow rate, and reaction temperature as inputs, and the predicted biofilm thickness as the output. The biofilm thickness prediction model can be a prediction model built based on the random forest algorithm. The influent flow rate collected at the current sampling time can be collected using an influent flow meter. The current biofilm thickness can refer to the predicted biofilm thickness corresponding to the current sampling time. The preset thickness threshold can refer to the pre-set maximum biofilm thickness for which the oxygen mass transfer coefficient needs to be adjusted.

[0073] Specifically, the Kalman filter algorithm is used to filter and denoise the candidate dissolved oxygen concentrations collected at the current acquisition time to determine the denoised current dissolved oxygen concentration. In this embodiment, all collected candidate data can be filtered and denoised uniformly to obtain the corresponding current data. First, real-time data acquisition: the system collects influent dissolved oxygen DO1, effluent dissolved oxygen DO2, contact oxidation tank reaction temperature T1, and influent ammonia nitrogen NH3-N concentration S in real time. Second, Kalman filtering denoising: the collected data is denoised using the Kalman filter algorithm to improve data accuracy. Define state variable x. k :

[0074]

[0075] Where: C in,k Dissolved oxygen concentration at the inlet at time k (DO1, mg / L); C out,k Dissolved oxygen concentration at the outlet (DO2, mg / L) at time k; T 1,k: Temperature of the contact oxidation tank water at time k (°C); S k The influent ammonia nitrogen concentration (NH3-N, mg / L) at time k. Based on the dynamic balance of dissolved oxygen in the contact oxidation tank (inlet → outlet), the equation of state is established:

[0076] x k =Ax k-1 +Bu k-1 +w k-1

[0077] Wherein, the state transition matrix A:

[0078]

[0079] Where α is the natural decay coefficient of dissolved oxygen DO1 at the inlet (related to microbial oxygen consumption); β is the replenishment efficiency of dissolved oxygen DO1 at the inlet by the aeration system; γ is the diffusion rate of dissolved oxygen DO1 from the inlet to the outlet; and δ is the comprehensive decay coefficient of dissolved oxygen DO2 at the outlet (including microbial oxygen consumption and dissipation). Control input matrix B:

[0080]

[0081] Where, k La (f k C is the oxygen mass transfer coefficient at the current fan frequency. s The saturated dissolved oxygen concentration is determined by the water temperature T. 1,k Calculation. Control input u k =C s (T 1,k )-C in,k C s (T 1,k () represents the saturated dissolved oxygen concentration. In the equation of state, the process noise follows a Gaussian distribution with zero mean and covariance matrix Q, i.e.:

[0082]

[0083] The specific form of the covariance matrix Q is as follows:

[0084]

[0085] in, The noise variance of dissolved oxygen at the inlet is caused by the measurement error of the dissolved oxygen sensor DO1, aeration fluctuations, and changes in the oxygen consumption rate of microorganisms. The variance of dissolved oxygen noise at the outlet is affected by the noise of the dissolved oxygen sensor (DO2 sensor), uneven hydraulic mixing, and disturbances in the outlet environment. It is the noise variance of the water temperature sensor in the contact oxidation tank; This is the noise variance of ammonia nitrogen concentration, caused by fluctuations in influent load, sensor drift, and sampling delay.

[0086] Observation equation:

[0087] z k =Hx k +v k

[0088] Among them, z k H is the observation vector (DO1, DO2, water temperature, ammonia nitrogen concentration); H is the identity matrix (directly measured state variables); v k It is observation noise covariance matrix The observation noise covariance matrix R is a diagonal matrix. The covariance matrix R is the same as the covariance matrix Q. Its diagonal elements correspond to the measurement noise variances of the inlet dissolved oxygen sensor (DO1), the outlet dissolved oxygen sensor (DO2), the contact oxidation tank temperature sensor (T1), and the ammonia nitrogen sensor (NH3-N).

[0089] Specifically, the influent flow rate, dissolved oxygen concentration, ammonia nitrogen concentration, and reaction temperature collected at the current sampling time are input into the target biofilm thickness prediction model to determine the current biofilm thickness L corresponding to the current sampling time. bio L bio =RF model (C in C out (S,Q,T1); based on the current biofilm thickness and the preset thickness threshold L th Thickness comparison is performed, and the corresponding coefficient adjustment method is determined based on the thickness comparison results. The candidate oxygen mass transfer coefficient is then adjusted using the targeted coefficient adjustment method to obtain the current oxygen mass transfer coefficient after adjustment.

[0090] Based on the above technical solution, "adjusting the candidate oxygen mass transfer coefficient based on the current biofilm thickness and a preset thickness threshold to obtain the adjusted current oxygen mass transfer coefficient" can include: if the current biofilm thickness is greater than the preset thickness threshold, then adjusting based on the current biofilm thickness, the preset thickness threshold, and the candidate oxygen mass transfer coefficient to determine the adjusted current oxygen mass transfer coefficient; if the current biofilm thickness is less than or equal to the preset thickness threshold, then detecting the time relationship between the current acquisition time and the current adjustment period; if the current acquisition time is the end time of the current adjustment period, then adjusting based on a pre-constructed difference minimization function and the candidate oxygen mass transfer coefficient to determine the adjusted current oxygen mass transfer coefficient; if the current acquisition time is the beginning or middle time of the current adjustment period, then adjusting the candidate oxygen mass transfer coefficient based on the current dissolved oxygen concentration and a preset dissolved oxygen concentration threshold to obtain the adjusted current oxygen mass transfer coefficient.

[0091] The current adjustment period can refer to one of the adjustment periods included within the second time period. The length of the adjustment period is determined at the beginning of each current adjustment period or the end of the previous adjustment period. Under normal operating conditions, the oxygen mass transfer coefficient is adjusted at the end of each current adjustment period. Under abnormal operating conditions, the current acquisition time is forcibly taken as the end time of the current adjustment period, and the oxygen mass transfer coefficient is adjusted accordingly. The time relationship can refer to the relationship between the current acquisition time and the various acquisition times within the current adjustment period. For example, the current acquisition time may be the start, middle, or end time of the current adjustment period. The difference minimization function can refer to an objective function constructed by minimizing the difference between the measured value and the model prediction value within the current adjustment period using the least squares method. In this embodiment, the difference minimization function can be represented as J.

[0092]

[0093] Among them, C measured,i Let C be the dissolved oxygen concentration (i.e., the mean) measured at time i. model,i Let be the dissolved oxygen concentration (i.e., the mean) predicted at time i, and n be the total number of data collections within the current adjustment period. Parameters k and m are from the performance curves (Q) provided by the wind turbine manufacturer. air =0.8·f 1.2 That is, k is 0.8 and m is 1.2. La (f) is the oxygen mass transfer coefficient, calculated using the formula k. La (f)=a·(k·f m ) b a and b are the scaling factor and mass transfer efficiency index, respectively, which need to be dynamically calibrated, with initial values ​​of 1.0 and 0.5. Under normal operating conditions, they are adjusted once at the end of each current adjustment cycle, for example, every t minutes based on a data window of the past m hours. Here, t is the dynamically changing adjustment cycle length.

[0094] Specifically, if the current biofilm thickness is greater than a preset thickness threshold, the current oxygen mass transfer coefficient is adjusted based on the current biofilm thickness, the preset thickness threshold, and candidate oxygen mass transfer coefficients to determine the adjusted current oxygen mass transfer coefficient. The scaling factor 'a' is updated to:

[0095]

[0096] Where 0.1 represents the adjustment range coefficient; 0.5 represents the biofilm thickness adjustment step size (the scaling factor a increases by 10% for every 0.5 mm increase in biofilm thickness). new The adjusted scaling factor, i.e., the scaling factor in the current oxygen mass transfer coefficient, aold This is the scaling factor before adjustment, i.e., the scaling factor in the candidate oxygen mass transfer coefficient. The mass transfer efficiency index b is updated as follows:

[0097]

[0098] Among them, b new b is the adjusted mass transfer efficiency index, i.e., the mass transfer efficiency index in the current oxygen mass transfer coefficient. old The mass transfer efficiency index before adjustment is the mass transfer efficiency index among the candidate oxygen mass transfer coefficients. After correcting the scaling factor 'a' and the mass transfer efficiency index 'b', the oxygen mass transfer coefficient 'k' is recalculated. La (f) and update to the preset closed-loop control model.

[0099] Specifically, if the current biofilm thickness is less than or equal to a preset thickness threshold, the time relationship between the current acquisition time and the current adjustment cycle is detected. If the current acquisition time is the end time of the current adjustment cycle, adjustments are made based on a pre-constructed difference minimization function and candidate oxygen mass transfer coefficients to determine the adjusted current oxygen mass transfer coefficient. The scaling factor 'a' is updated as follows:

[0100]

[0101] Mass transfer efficiency index b is updated to:

[0102]

[0103] Where η = 0.01 is the learning rate, and the iteration termination condition is that the number of iterations is greater than 10. 5 After correcting the scaling factor 'a' and the mass transfer efficiency exponent 'b', the oxygen mass transfer coefficient 'k' is recalculated. La (f) and update to the preset closed-loop control model.

[0104] Specifically, if the current sampling time is the start or middle of the current adjustment cycle, the candidate oxygen mass transfer coefficient is adjusted based on the current dissolved oxygen concentration and a preset dissolved oxygen concentration threshold to obtain the adjusted current oxygen mass transfer coefficient. For example, if the current dissolved oxygen concentration (i.e., the mean (C)) at the current sampling time is detected... in -C out If the dissolved oxygen concentration at the current sampling time is greater than the preset dissolved oxygen threshold (e.g., 20 mg / L), then the current sampling time is forcibly taken as the end time of the current adjustment cycle, and the candidate oxygen mass transfer coefficient is adjusted according to the above adjustment method of taking the current sampling time as the end time of the current adjustment cycle, and the adjusted current oxygen mass transfer coefficient is determined. If the current dissolved oxygen concentration at the current sampling time is detected to be less than or equal to the preset dissolved oxygen threshold, then the candidate oxygen mass transfer coefficient is taken as the current oxygen mass transfer coefficient.

[0105] Based on the above technical solution, the process of determining the current adjustment cycle may include: determining the cycle adjustment method based on the degree of dissolved oxygen concentration fluctuation and the preset fluctuation threshold corresponding to the previous adjustment cycle; adjusting the previous adjustment cycle based on the cycle adjustment method to determine the current adjustment cycle; wherein, when the current oxygen mass transfer coefficient changes, the current control cycle ends.

[0106] The previous adjustment cycle can refer to the adjustment cycle preceding the current one. The degree of dissolved oxygen concentration fluctuation can be expressed using the dissolved oxygen concentration fluctuation rate or dissolved oxygen change rate. The preset fluctuation threshold can refer to the maximum dissolved oxygen concentration fluctuation corresponding to a pre-set stable operating condition. A change in the current oxygen mass transfer coefficient indicates the end of the current control cycle.

[0107] Specifically, the cycle time t can be adaptively adjusted based on the dissolved oxygen concentration fluctuation rate or dissolved oxygen change rate. For example, when the detected dissolved oxygen change rate is greater than a preset fluctuation threshold (e.g., 0.1 mg / L / min), the cycle time is shortened to 5-10 minutes to improve response speed. Under stable operating conditions (e.g., change rate ≤ ±0.1 mg / L / min), the cycle time is extended to 20-30 minutes to reduce computational load.

[0108] S350. Based on the current ammonia nitrogen concentration, current reaction temperature, and current oxygen mass transfer coefficient of the contact oxidation tank at the current sampling time in the second time period, determine the correlation between the fan frequency and dissolved oxygen concentration at the current sampling time.

[0109] S360. Based on the correlation between the fan frequency and dissolved oxygen concentration and the target oxygen demand at the current data acquisition time, determine the current fan control strategy at the current data acquisition time.

[0110] For example, the optimization objective is to minimize the total energy consumption of the multi-fan system while satisfying the constraints of dissolved oxygen concentration, frequency, and temperature. This ensures that at any time t, the dissolved oxygen concentration C(t) at each sampling moment in the contact oxidation tank reaches at least the target concentration C. target The operating frequency f of each wind turbine i It must be at the minimum frequency f min and maximum frequency f max Between, the motor temperature T of each fan 2,i The motor's safe operating temperature must be maintained. The temperature of each motor is monitored in real time using temperature sensors installed inside the motor itself, labeled T2. The temperature sensor for the first motor is labeled T. 2,1 The second one is labeled T. 2,2 The nth unit is labeled T. 2,n .

[0111] The objective function for minimizing total energy consumption is:

[0112]

[0113] The constraints are:

[0114]

[0115] Where N is the total number of fans in the system; C(t) is the average value of the readings from the two dissolved oxygen sensors (DO1 and DO2) at time t; C target The target dissolved oxygen concentration of 2 mg / L is dynamically set based on water quality requirements; i T is the motor frequency of the i-th fan; 2,i T represents the motor temperature of the i-th fan; safe =80℃ is the safe temperature threshold for the motor. Genetic algorithm parameters (e.g., population size 50, crossover rate 0.8, mutation rate 0.05) are used to adaptively adjust the system based on real-time operating conditions. The fan start / stop and frequency allocation are recalculated every adjustment cycle to adapt to water quality fluctuations. The length of the adjustment cycle is selected based on the system's response speed and optimization requirements to ensure timely adjustment of the fan operation strategy during water quality fluctuations.

[0116] It should be noted that, based on the power characteristics of the centrifugal fan, a cubic relationship model between power and frequency is constructed as follows:

[0117]

[0118] Where k is the proportionality coefficient, which is calculated by fitting the measured power, frequency and water temperature data of the blower; and T1 is the real-time water temperature in the contact oxidation tank. Temperature efficiency factor The attenuation coefficient of the temperature efficiency factor η(T1) is used, and its specific value is adjusted according to the real-time water temperature fluctuation characteristics through fuzzy rules; T 基准 This is the design reference temperature.

[0119] The technical solution of this invention improves the accuracy of the data used to judge the operating conditions and adjust the oxygen mass transfer coefficient by filtering and denoising the candidate ammonia nitrogen concentration and candidate reaction temperature collected at the current acquisition time based on a preset denoising method, thereby determining the denoised current ammonia nitrogen concentration and current reaction temperature. This improves the accuracy of the operating condition judgment and oxygen mass transfer coefficient adjustment. Furthermore, the candidate oxygen mass transfer coefficient corresponding to the current acquisition time is adjusted based on a preset coefficient adjustment method to obtain the adjusted current oxygen mass transfer coefficient, which further improves the accuracy of the current fan control strategy generation.

[0120] The following are embodiments of the aeration fan control device provided in this invention. This device and the aeration fan control methods in the above embodiments belong to the same inventive concept. For details not described in detail in the embodiments of the aeration fan control device, please refer to the embodiments of the above aeration fan control methods.

[0121] Example 3

[0122] Figure 4 This is a schematic diagram of an aeration blower control device provided in Embodiment 3 of the present invention. Figure 4 As shown, the device includes: a historical data acquisition module 410, a target oxygen demand determination module 420, a correlation determination module 430, and a current fan control strategy determination module 440.

[0123] The system includes the following modules: a historical data acquisition module 410, which acquires the historical oxygen demand (OD) and historical ammonia nitrogen concentration of the contact oxidation tank in the wastewater treatment system during the first time period; a target O demand determination module 420, which determines the target O demand of the contact oxidation tank during the second time period based on the historical O demand, historical ammonia nitrogen concentration, and an O demand prediction model; a correlation determination module 430, which determines the correlation between the fan frequency and dissolved oxygen concentration at the current acquisition time during the second time period based on the current ammonia nitrogen concentration, current reaction temperature, and current oxygen mass transfer coefficient of the contact oxidation tank; and a current fan control strategy determination module 440, which determines the current fan control strategy at the current acquisition time based on the correlation between the fan frequency and dissolved oxygen concentration and the target O demand.

[0124] The technical solution of this invention obtains the historical oxygen demand and historical ammonia nitrogen concentration of the contact oxidation tank in the sewage treatment system during a first time period; based on the historical oxygen demand, historical ammonia nitrogen concentration, and oxygen demand prediction model, determines the target oxygen demand of the contact oxidation tank during a second time period; based on the current ammonia nitrogen concentration, current reaction temperature, and current oxygen mass transfer coefficient of the contact oxidation tank at the current acquisition time in the second time period, determines the correlation between the blower frequency and dissolved oxygen concentration at the current acquisition time; based on the correlation between the blower frequency and dissolved oxygen concentration at the current acquisition time and the target oxygen demand, determines the current blower control strategy at the current acquisition time. Therefore, the current blower control strategy can accurately and conveniently achieve dynamic control of the aeration blower, improving the accuracy of dissolved oxygen concentration control and saving operating costs.

[0125] Based on the above technical solution, before determining the correlation, the device further includes:

[0126] The current data determination module is used to filter and denoise the candidate ammonia nitrogen concentration and candidate reaction temperature collected at the current acquisition time based on a preset denoising method, and determine the denoised current ammonia nitrogen concentration and current reaction temperature.

[0127] The current oxygen mass transfer coefficient determination module is used to adjust the candidate oxygen mass transfer coefficients corresponding to the current acquisition time based on a preset coefficient adjustment method, so as to obtain the adjusted current oxygen mass transfer coefficient.

[0128] Based on the above technical solution, the current oxygen mass transfer coefficient determination module may include:

[0129] The current dissolved oxygen concentration determination submodule is used to filter and denoise the candidate dissolved oxygen concentrations collected at the current acquisition time based on a preset denoising method, and determine the denoised current dissolved oxygen concentration.

[0130] The current biofilm thickness determination submodule is used to determine the current biofilm thickness at the current sampling time based on the target biofilm thickness prediction model, the influent flow rate, current dissolved oxygen concentration, current ammonia nitrogen concentration and current reaction temperature collected at the current sampling time.

[0131] The current oxygen mass transfer coefficient determination submodule is used to adjust the candidate oxygen mass transfer coefficients based on the current biofilm thickness and a preset thickness threshold to obtain the adjusted current oxygen mass transfer coefficient.

[0132] Based on the above technical solution, the current oxygen mass transfer coefficient determination submodule is specifically used for: if the current biofilm thickness is greater than a preset thickness threshold, then adjusting based on the current biofilm thickness, the preset thickness threshold, and candidate oxygen mass transfer coefficients to determine the adjusted current oxygen mass transfer coefficient; if the current biofilm thickness is less than or equal to the preset thickness threshold, then detecting the time relationship between the current acquisition time and the current adjustment cycle; if the current acquisition time is the end time of the current adjustment cycle, then adjusting based on a pre-constructed difference minimization function and candidate oxygen mass transfer coefficients to determine the adjusted current oxygen mass transfer coefficient; if the current acquisition time is the beginning or middle time of the current adjustment cycle, then adjusting the candidate oxygen mass transfer coefficients based on the current dissolved oxygen concentration and a preset dissolved oxygen concentration threshold to obtain the adjusted current oxygen mass transfer coefficient.

[0133] Based on the above technical solution, the device further includes: a current adjustment cycle determination submodule, used to determine the current adjustment cycle;

[0134] The current adjustment cycle determination submodule is specifically used to: determine the cycle adjustment method based on the degree of dissolved oxygen concentration fluctuation and the preset fluctuation threshold corresponding to the previous adjustment cycle; adjust the previous adjustment cycle based on the cycle adjustment method to determine the current adjustment cycle; wherein, when the current oxygen mass transfer coefficient changes, the current control cycle ends.

[0135] Based on the above technical solution, the correlation determination module 430 is specifically used to: construct a dynamic response model with the fan operating frequency as input and dissolved oxygen concentration as output based on biofilm dynamics and oxygen mass transfer theory; and determine the correlation between the fan frequency and dissolved oxygen concentration at the current acquisition time based on the dynamic response model, the current ammonia nitrogen concentration, the current reaction temperature and the current oxygen mass transfer coefficient.

[0136] The aeration fan control device provided in the embodiments of the present invention can execute the aeration fan control method provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects for executing the aeration fan control method.

[0137] It is worth noting that in the above embodiments of aeration blower control, the various units and modules included are only divided according to functional logic, but are not limited to the above division, as long as the corresponding functions can be achieved; in addition, the specific names of each functional unit are only for easy differentiation and are not used to limit the scope of protection of the present invention.

[0138] Example 4

[0139] Figure 5 A schematic diagram of an electronic device 10 that can be used to implement embodiments of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices (e.g., helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the invention described and / or claimed herein.

[0140] like Figure 5 As shown, the electronic device 10 includes at least one processor 11 and a memory, such as a read-only memory (ROM) 12 or a random access memory (RAM) 13, communicatively connected to the at least one processor 11. The memory stores computer programs executable by the at least one processor. The processor 11 can perform various appropriate actions and processes based on the computer program stored in the ROM 12 or loaded from storage unit 18 into the RAM 13. The RAM 13 may also store various programs and data required for the operation of the electronic device 10. The processor 11, ROM 12, and RAM 13 are interconnected via a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0141] Multiple components in electronic device 10 are connected to I / O interface 15, including: input unit 16, such as keyboard, mouse, etc.; output unit 17, such as various types of displays, speakers, etc.; storage unit 18, such as disk, optical disk, etc.; and communication unit 19, such as network card, modem, wireless transceiver, etc. Communication unit 19 allows electronic device 10 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0142] Processor 11 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. Processor 11 performs the various methods and processes described above, such as aeration blower control methods.

[0143] In some embodiments, the aeration blower control method may be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or mounted on electronic device 10 via ROM 12 and / or communication unit 19. When the computer program is loaded into RAM 13 and executed by processor 11, one or more steps of the aeration blower control method described above may be performed. Alternatively, in other embodiments, processor 11 may be configured to perform the aeration blower control method by any other suitable means (e.g., by means of firmware).

[0144] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), payload-programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0145] Computer programs used to implement the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when executed by the processor, the computer programs cause the functions / operations specified in the flowcharts and / or block diagrams to be performed. The computer programs may be executed entirely on a machine, partially on a machine, or as a standalone software package, partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0146] In the context of this invention, a computer-readable storage medium can be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination thereof. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0147] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device for displaying information to a user; and a keyboard and pointing device through which the user provides input to the electronic device. Other types of devices can also be used to provide interaction with a user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including voice input, speech input, or tactile input).

[0148] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or computing systems that include middleware components (e.g., application servers), or computing systems that include frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include local area networks (LANs), wide area networks (WANs), blockchain networks, and the Internet.

[0149] A computing system can include clients and servers. Clients and servers are generally located far apart and typically interact through a communication network. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a hosting product within the cloud computing service system to address the shortcomings of traditional physical hosts and VPS services, such as high management difficulty and weak business scalability.

[0150] This invention also provides a computer program product, including a computer program that, when executed by a processor, implements the aeration blower control method as provided in any embodiment of this application.

[0151] In implementing the computer program product, computer program code for performing the operations of this invention can be written in one or more programming languages ​​or a combination thereof. Programming languages ​​include object-oriented programming languages ​​such as Java, Smalltalk, and C++, as well as conventional procedural programming languages ​​such as C or similar languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider). This program product belongs to the same inventive concept as the aeration blower control method disclosed in the embodiments of this application, and therefore will not be described further here.

[0152] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this invention can be achieved, and this is not limited herein.

[0153] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. A method for controlling an aeration blower, characterized in that, include: Obtain the historical oxygen demand and historical ammonia nitrogen concentration of the contact oxidation tank in the wastewater treatment system during the first time period; Based on the historical oxygen demand, the historical ammonia nitrogen concentration, and the oxygen demand prediction model, the target oxygen demand of the contact oxidation tank in the second time period is determined. Based on the current ammonia nitrogen concentration, current reaction temperature, and current oxygen mass transfer coefficient of the contact oxidation tank at the current sampling time in the second time period, the correlation between the fan frequency and dissolved oxygen concentration at the current sampling time is determined. Based on the correlation between the fan frequency and dissolved oxygen concentration at the current data acquisition time and the target oxygen demand, the current fan control strategy at the current data acquisition time is determined.

2. The method according to claim 1, characterized in that, Before determining the association, the method further includes: Based on a preset denoising method, the candidate ammonia nitrogen concentration and candidate reaction temperature collected at the current acquisition time are filtered and denoised to determine the current ammonia nitrogen concentration and current reaction temperature after denoising. The candidate oxygen mass transfer coefficient corresponding to the current acquisition time is adjusted based on the preset coefficient adjustment method to obtain the adjusted current oxygen mass transfer coefficient.

3. The method according to claim 2, characterized in that, The process of adjusting the candidate oxygen mass transfer coefficient corresponding to the current acquisition time based on a preset coefficient adjustment method to obtain the adjusted current oxygen mass transfer coefficient includes: The candidate dissolved oxygen concentrations collected at the current acquisition time are filtered and denoised based on a preset denoising method to determine the current dissolved oxygen concentration after denoising. Based on the target biofilm thickness prediction model, the influent flow rate collected at the current sampling time, the current dissolved oxygen concentration, the current ammonia nitrogen concentration, and the current reaction temperature, the current biofilm thickness corresponding to the current sampling time is determined; Based on the current biofilm thickness and the preset thickness threshold, the candidate oxygen mass transfer coefficient is adjusted to obtain the adjusted current oxygen mass transfer coefficient.

4. The method according to claim 3, characterized in that, The step of adjusting the candidate oxygen mass transfer coefficient based on the current biofilm thickness and a preset thickness threshold to obtain the adjusted current oxygen mass transfer coefficient includes: If the current biofilm thickness is greater than a preset thickness threshold, then the current oxygen mass transfer coefficient is adjusted based on the current biofilm thickness, the preset thickness threshold, and the candidate oxygen mass transfer coefficient to determine the adjusted current oxygen mass transfer coefficient. If the current biofilm thickness is less than or equal to a preset thickness threshold, then the time relationship between the current acquisition time and the current adjustment cycle is detected. If the current acquisition time is the end time of the current adjustment cycle, then the current oxygen mass transfer coefficient is determined based on the pre-constructed difference minimization function and the candidate oxygen mass transfer coefficient. If the current acquisition time is the start or middle of the current adjustment cycle, the candidate oxygen mass transfer coefficient is adjusted based on the current dissolved oxygen concentration and the preset dissolved oxygen concentration threshold to obtain the adjusted current oxygen mass transfer coefficient.

5. The method according to claim 4, characterized in that, The process of determining the current adjustment cycle includes: Based on the degree of dissolved oxygen concentration fluctuation in the previous adjustment cycle and the preset fluctuation threshold, the cycle adjustment method is determined. The previous adjustment cycle is adjusted based on the aforementioned cycle adjustment method to determine the current adjustment cycle; The current control cycle ends when the current oxygen mass transfer coefficient changes.

6. The method according to claim 1, characterized in that, The determination of the correlation between the blower frequency and dissolved oxygen concentration at the current sampling time based on the current ammonia nitrogen concentration, current reaction temperature, and current oxygen mass transfer coefficient of the contact oxidation tank at the current sampling time in the second time period includes: Based on biofilm dynamics and oxygen mass transfer theory, a dynamic response model is constructed with the fan operating frequency as input and dissolved oxygen concentration as output. Based on the dynamic response model, the current ammonia nitrogen concentration, the current reaction temperature, and the current oxygen mass transfer coefficient, the correlation between the fan frequency and dissolved oxygen concentration at the current data collection time is determined.

7. An aeration blower control device, characterized in that, The device includes: The historical data acquisition module is used to acquire the historical oxygen demand and historical ammonia nitrogen concentration of the contact oxidation tank in the wastewater treatment system during the first time period. The target oxygen demand determination module is used to determine the target oxygen demand of the contact oxidation tank in the second time period based on the historical oxygen demand, the historical ammonia nitrogen concentration, and the oxygen demand prediction model. The correlation determination module is used to determine the correlation between the fan frequency and dissolved oxygen concentration at the current sampling time based on the current ammonia nitrogen concentration, current reaction temperature and current oxygen mass transfer coefficient of the contact oxidation tank at the current sampling time in the second time period. The current fan control strategy determination module is used to determine the current fan control strategy corresponding to the current acquisition time based on the correlation between the fan frequency and dissolved oxygen concentration at the current acquisition time and the target oxygen demand.

8. An electronic device, characterized in that, The electronic device includes: One or more processors; Memory, used to store one or more programs; When the one or more programs are executed by the one or more processors, the one or more processors implement the aeration blower control method as described in any one of claims 1-6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When executed by the processor, the program implements the aeration blower control method as described in any one of claims 1-6.

10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by the processor, it implements the aeration blower control method as described in any one of claims 1-6.

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