Intelligent control method, system, storage medium and equipment for sewage plant aeration tank fan

Abstract

This invention relates to the field of wastewater treatment technology, and discloses an intelligent control method, system, storage medium, and equipment for blowers in aeration tanks of wastewater treatment plants. It aims to solve the problems of slow response and high energy consumption in traditional manual control, and the poor adaptability, excessive complexity, or insufficient accuracy of existing automatic control systems. This method is based on the flow characteristics and biochemical reaction requirements of a closed-loop circulating corridor aeration tank. It achieves precise automatic regulation of blower airflow through a dual-mechanism coupling of "dynamic DO grading feedback + theoretical airflow quantitative prediction," combined with a seasonally adapted DO control benchmark. The system, through a full-process design of data acquisition, grading calculation, airflow optimization, automatic execution, and closed-loop verification, ensures that dissolved oxygen remains stable within the set range while reducing energy consumption and operation and maintenance costs. This invention is compatible with various processes such as AAO, SBR, oxidation ditch, multi-stage AO, and MBR. It has strong resistance to shock loads, is easy to operate, and has low implementation costs, making it suitable for wastewater treatment plants of all sizes and possessing high promotional value.

Description

Technical Field

[0001] This invention belongs to the field of wastewater treatment technology, specifically relating to an intelligent control method, system, storage medium and equipment for blowers in aeration tanks of wastewater treatment plants. It is applicable to aeration tanks using conventional processes such as AAO, multi-stage AO and MBR, and is especially suitable for precise control of the aeration process in scenarios with two or more parallel operations. Background Technology

[0002] As the core unit of the biochemical reaction in wastewater treatment, the dissolved oxygen (DO) concentration in the aeration tank directly affects microbial activity, pollutant degradation efficiency, and effluent quality. Currently, there are two main problems in the control of blowers in wastewater treatment plant aeration tanks:

[0003] One type is the inherent defects of traditional manual control methods. Maintenance personnel adjust the fan airflow based on experience and reference to data from a single DO instrument, requiring constant monitoring. When they leave the central control room, they cannot respond promptly to fluctuations in water quality and quantity. Moreover, the adjustment range varies from person to person, which is highly subjective. Under the impact load of influent water, frequent adjustments are required, which not only increases the workload of maintenance, but also easily leads to frequent start-stop of the fan, energy waste, and even disruption of the biochemical reaction balance.

[0004] Another issue is the insufficient adaptability of existing automatic control systems. Some systems use single DO feedback regulation without considering the prediction of oxygen demand in biochemical reactions, resulting in significant control lag. Others rely on complex water quality analysis models or fuzzy neural networks, which require high hardware computing power and have high investment costs, making them only suitable for large-scale wastewater treatment plants. Still other systems have simple control logic that is not optimized for the flow characteristics of aeration tanks, resulting in insufficient regulation accuracy and difficulty in adapting to seasonal changes and fluctuations in influent load.

[0005] Therefore, there is an urgent need to develop an intelligent control technology that combines precision, energy efficiency, and practicality to address the pain points of existing technologies and adapt to the actual operational needs of wastewater treatment plants of various sizes. Summary of the Invention

[0006] In view of the problems mentioned above in the background art, the purpose of this invention is to provide an intelligent control method, system, storage medium and equipment for blowers in aeration tanks of wastewater treatment plants.

[0007] In a first aspect, the present invention provides an intelligent control method for blowers in aeration tanks of wastewater treatment plants, comprising the following steps: S1 Benchmark Setting and Data Acquisition: Under the premise that the effluent ammonia nitrogen meets the standard, set the minimum target value of dissolved oxygen, select representative DO monitoring points in the aeration tank, and set a seasonally appropriate DO control range; collect influent data in real time: flow rate Q, CODin, TNin, and process data: DO value, ammonia nitrogen value, reaction temperature T, blower opening degree, actual air volume Gs0; and effluent data TNo; S2 DO variation calculation: Using a time window of 0.5h, calculate the average DO value (aveDO) from the 30th to the 40th minute. 30-40 min and mean DO from 0 to 10 minutes aveDO 0-10 min, and obtain the change magnitude ΔDO. 0-40 min=|aveDO 30-40 min-aveDO 0-10 min|; S3 DO range matching with basic adjustment range: based on ΔDO 0-40min The basic adjustment range is set in three levels: Part 1: ΔDO 0-40 If min < 0.2 mg / L, the basic adjustment range of the fan air volume is 3% Qg; Section 2: 0.2≤ΔDO 0-40 min≤0.5mg / L, fan air volume basic adjustment range 5%Qg; Gear 3: ΔDO 0-40 If the concentration of min is greater than 0.5 mg / L, the basic adjustment range of the fan air volume is 7% Qg; Where Qg is the maximum air volume of a single fan; S4 Theoretical Airflow Prediction and Adjustment Range Optimization: Based on the inlet water and reaction parameters, the required airflow GsL is calculated using a theoretical formula: GsL = (((Q)) COD in Bc-4) 1.47 / 1000+Q (TN in -2) 4.57 / 1000-(Q (TNin-TNo) / 1000-0.12(Q (CODin Bc-4) Y / 1000)) 3-(Q COD in Bc-4) Y / 1000)1.42))Cs / (α (β Csb-DO)1.024^(T-20))) / (0.28 E A ); Where Q represents the influent flow rate and COD. in For influent COD concentration, TN inTNo represents the total nitrogen concentration in the influent, TNo represents the total nitrogen concentration in the effluent, correction factor Bc = 0.3~0.6, sludge yield coefficient Y = 0.5~0.8, mixed liquor temperature T = 15~30℃, standard saturated dissolved oxygen concentration Cs = 9~10 mg / L, wastewater oxygen transfer correction factor α = 0.8~0.9, mixed liquor saturated oxygen concentration Csb = 10~11 mg / L, and oxygen transfer efficiency E0 A =20~30%, DO is the residual dissolved oxygen value of the mixture; calculate the air volume difference ΔG=GsL-Gs0, and optimize it in combination with the basic adjustment range: Gear 1: Fan airflow adjustment 3% Qg; Gear 2: Fan air volume adjustment max{ΔG / a,5%Qg}, not exceeding 10%Qg; Gear 3: Fan air volume adjustment max{ΔG / 0.5a,7%Qg}, not exceeding 12%Qg; Where 'a' is the time (h) from the influent to the aeration tank.

[0008] Further specifying, in S1, the DO control range is set as follows: when the water temperature is ≥20℃, the DO target control is 0.8~1.6mg / L, and when the water temperature is <20℃, the DO target control is 1.2~1.7mg / L.

[0009] Further restrictions include S5: constraint execution and closed-loop verification. Based on the characteristics of the fan, the air volume control range of a single fan is set; after adjustment, the DO value is continuously monitored. If it still deviates from the set range, steps S2 to S4 are repeated until the DO stabilizes in the target range.

[0010] To further define the criteria, in step S1, the representative DO monitoring point is selected at the middle and end of the aeration tank, avoiding the influent impact zone and the effluent transition zone.

[0011] Further specifying, for scenarios where two processes operate in parallel, the optimization and adjustment logic in step S4 is as follows: prioritize the aeration tank with lower dissolved oxygen as the benchmark to calculate the adjustment range, and distribute the air volume through valve opening to ensure that the DO of both tanks remains stable within the set range.

[0012] A second aspect of the present invention provides a system for implementing the intelligent control method for blowers in aeration tanks of wastewater treatment plants as described in any of the preceding claims, comprising: Data acquisition module: Composed of DO sensor, ammonia nitrogen sensor, flow sensor, influent online monitor (monitoring COD and TN), temperature sensor and air volume sensor, used to collect various operating data in real time; Data processing module: used to calculate the change in DO, ΔDO 0-40 min, theoretical air volume GsL and air volume difference ΔG, to complete the classification judgment and adjustment range optimization; Control decision module: Used to generate fan opening adjustment commands that meet the constraints based on the classification results and the optimized adjustment range; Execution module: includes fan frequency converter and electric valve, used to receive commands to adjust the opening degree and control the air volume output; Closed-loop monitoring module: Used to display DO concentration, fan operating status, and air volume data in real time. It supports historical curve query, abnormal alarm and parameter fine-tuning. When DO deviates from the set range, it triggers readjustment.

[0013] Furthermore, the data acquisition module supports Modbus and Profinet communication protocols, and can interface with the existing SCADA system of the wastewater treatment plant to achieve data exchange and centralized management.

[0014] Further defining the abnormal alarm functions of the closed-loop monitoring module, it includes alarms for excessive DO, excessive ammonia nitrogen, abnormal fan operation, and sensor failure. The alarm methods are audible and visual alarms and platform push notifications, and the alarm thresholds can be customized.

[0015] The present invention also provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the intelligent control method for blowers in aeration tanks of wastewater treatment plants as described in any of the preceding claims.

[0016] The present invention also provides a computer device, the computer device including a processor and a memory, the memory being used to store a computer program, and the processor being configured to invoke the computer program to execute the steps of the intelligent control method for the blower of the aeration tank in the wastewater treatment plant as described above.

[0017] Compared with the prior art, the beneficial effects of the present invention are as follows: This invention employs a dual-mechanism coupling design: DO (dissolved oxygen) fluctuations are captured in real-time through tiered adjustments, while theoretical airflow is used to predict oxygen demand. Optimized adjustment range balances response speed and stability, ensuring DO concentration remains stable within the set range, maximizing nitrogen and phosphorus removal efficiency, and significantly improving effluent quality compliance. Compared to manual control, it avoids over-aeration and ineffective adjustments, reducing energy consumption through "on-demand oxygen supply." Compared to complex model control systems, it requires no additional hardware computing power; existing facilities can be adapted, resulting in low implementation costs and energy savings of 10%–30%. Differentiated adjustment cycles are designed to address various disturbances such as water quality, quantity, and temperature, enabling adaptive adjustments within as little as 5 minutes. This adapts to the shock load resistance characteristics of closed-loop circulating corridor aeration tanks, demonstrating outstanding ability to handle complex operating conditions.

[0018] This invention features standardized control logic, eliminating the need for maintenance personnel to possess specialized programming knowledge. They can simply monitor and fine-tune parameters through a visual interface, lowering the operational threshold and making it suitable for application in wastewater treatment plants of all sizes. By constraining the opening range and adjustment intervals, it avoids overloading the blower and frequent, large-scale adjustments, extending equipment lifespan and reducing maintenance costs. Attached Figure Description

[0019] The present invention can be further illustrated by the non-limiting embodiments given in the accompanying drawings.

[0020] Figure 1 This is a flowchart of the intelligent control method of the present invention; Figure 2 This is a schematic diagram of the modular structure of the intelligent control system of the present invention; Figure 3 This is a schematic diagram of the air volume adjustment logic of the present invention. Detailed Implementation

[0021] To enable those skilled in the art to better understand the present invention, the technical solution of the present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0022] The SCADA (Supervisory Control and Data Acquisition) system of a wastewater treatment plant is currently the core automation and monitoring hub of the plant. It is responsible for real-time perception, centralized monitoring, remote control, data management and alarms throughout the entire process. It is the basic platform for achieving automated and energy-saving operation of processes such as aeration, chemical dosing and sludge treatment.

[0023] See appendix Figures 1-3 The present invention provides an intelligent control method for blowers in aeration tanks of wastewater treatment plants, comprising the following steps: S1 Benchmark Setting and Data Acquisition: Under the premise that the effluent ammonia nitrogen meets the standard, set the minimum target value of dissolved oxygen, select representative DO monitoring points in the aeration tank, and set a seasonally appropriate DO control range; collect influent data in real time: flow rate Q, CODin, TNin, and process data: DO value, ammonia nitrogen value, reaction temperature T, blower opening degree, actual air volume Gs0; and effluent data TNo; S2 DO variation calculation: Using a time window of 0.5h, calculate the average DO value (aveDO) from the 30th to the 40th minute. 30-40 min and mean DO from 0 to 10 minutes aveDO 0-10 min, and obtain the change magnitude ΔDO. 0-40 min=|aveDO 30-40 min-aveDO 0-10 min|; S3 DO range matching with basic adjustment range: based on ΔDO 0-40min The basic adjustment range is set in three levels: Part 1: ΔDO 0-40 If min < 0.2 mg / L, the basic adjustment range of the fan air volume is 3% Qg; Section 2: 0.2≤ΔDO 0-40 min≤0.5mg / L, fan air volume basic adjustment range 5%Qg; Gear 3: ΔDO 0-40 If the concentration of min is greater than 0.5 mg / L, the basic adjustment range of the fan air volume is 7% Qg; Where Qg is the maximum air volume of a single fan; S4 Theoretical Airflow Prediction and Adjustment Range Optimization: Based on the inlet water and reaction parameters, the required airflow GsL is calculated using a theoretical formula: GsL = (((Q)) COD in Bc-4) 1.47 / 1000+Q (TN in -2) 4.57 / 1000-(Q (TNin-TNo) / 1000-0.12(Q (CODin Bc-4) Y / 1000)) 3-(Q COD in Bc-4) Y / 1000)1.42))Cs / (α (β Csb-DO)1.024^(T-20))) / (0.28 E A ); Where Q represents the influent flow rate and COD. in For influent COD concentration, TN in TNo represents the total nitrogen concentration in the influent, TNo represents the total nitrogen concentration in the effluent, correction factor Bc = 0.3~0.6, sludge yield coefficient Y = 0.5~0.8, mixed liquor temperature T = 15~30℃, standard saturated dissolved oxygen concentration Cs = 9~10 mg / L, wastewater oxygen transfer correction factor α = 0.8~0.9, mixed liquor saturated oxygen concentration Csb = 10~11 mg / L, and oxygen transfer efficiency E0 A =20~30%, DO is the residual dissolved oxygen value of the mixture; calculate the air volume difference ΔG=GsL-Gs0, and optimize it in combination with the basic adjustment range: Gear 1: Fan airflow adjustment 3% Qg; Gear 2: Fan air volume adjustment max{ΔG / a,5%Qg}, not exceeding 10%Qg; Gear 3: Fan air volume adjustment max{ΔG / 0.5a,7%Qg}, not exceeding 12%Qg; Where 'a' is the time (h) from the influent to the aeration tank.

[0024] In a preferred embodiment, in step S1, the DO control range is set as follows: when the water temperature is ≥20℃, the target DO control is 0.8~1.6mg / L; when the water temperature is <20℃, the target DO control is 1.2~1.7mg / L.

[0025] In a preferred embodiment, S5 is also included: constraint execution and closed-loop verification. Based on the characteristics of the fan, the air volume control range of a single fan is set; after adjustment, the DO value is continuously monitored. If it still deviates from the set range, steps S2 to S4 are repeated until the DO stabilizes in the target range.

[0026] In a preferred embodiment, the representative DO monitoring point in step S1 is selected at the middle and end of the aeration tank, avoiding the influent impact zone and the effluent transition zone.

[0027] In a preferred embodiment, for a scenario where two processes operate in parallel, the optimization and adjustment logic in step S4 is as follows: the adjustment range is calculated based on the aeration tank with lower dissolved oxygen, and the air volume is distributed by the valve opening to ensure that the dissolved oxygen (DO) of both tanks is stable within the set range.

[0028] like Figure 2 As shown, this embodiment provides a system for implementing the intelligent control method for blowers in aeration tanks of wastewater treatment plants as described in any of the above claims, comprising: Data acquisition module: Composed of DO sensor, ammonia nitrogen sensor, flow sensor, influent online monitor (monitoring COD and TN), temperature sensor and air volume sensor, used to collect various operating data in real time; Data processing module: used to calculate the change in DO, ΔDO 0-40 min, theoretical air volume GsL and air volume difference ΔG, to complete the classification judgment and adjustment range optimization; Control decision module: Used to generate fan opening adjustment commands that meet the constraints based on the classification results and the optimized adjustment range; Execution module: includes fan frequency converter and electric valve, used to receive commands to adjust the opening degree and control the air volume output; Closed-loop monitoring module: Used to display DO concentration, fan operating status, and air volume data in real time. It supports historical curve query, abnormal alarm and parameter fine-tuning. When DO deviates from the set range, it triggers readjustment.

[0029] The system of this invention has a data acquisition module that supports Modbus and Profinet communication protocols, and can interface with the existing SCADA system of a wastewater treatment plant to achieve data exchange and centralized management.

[0030] In a preferred embodiment, the abnormal alarm function of the closed-loop monitoring module includes DO exceeding standard alarm, ammonia nitrogen exceeding standard alarm, fan opening abnormality alarm, and sensor fault alarm. The alarm methods are audible and visual alarms and platform push notifications, and the alarm threshold can be customized.

[0031] This embodiment provides a computer-readable storage medium storing a computer program. When the computer program is executed by a processor, it implements the intelligent control method for blowers in aeration tanks of wastewater treatment plants as described in any of the above embodiments.

[0032] This embodiment provides a computer device, which includes a processor and a memory. The memory is used to store computer programs, and the processor is configured to call the computer programs to execute the steps of the intelligent control method for blowers in aeration tanks of wastewater treatment plants as described above.

[0033] The intelligent control method for blowers in aeration tanks of wastewater treatment plants according to the present invention will be described below with reference to specific embodiments.

[0034] Example 1 This embodiment selects a municipal wastewater treatment plant that uses the AAO process, with a designed treatment capacity of 40,000 m³ / d. It is equipped with three centrifugal aeration blowers (two in operation and one on standby), each with a maximum airflow of Qg = 8000 m³ / h and a rated power of 160 kW. The influent time to the aeration tank is a = 6 hours. The aeration tanks are divided into two parallel groups, each equipped with one DO sensor installed at the middle and end positions along the tank length (avoiding the influent impact zone and effluent transition zone). Additionally, ammonia nitrogen sensors, flow sensors, COD / TN online monitoring instruments, temperature sensors, and airflow sensors are also provided. All sensors support the Modbus communication protocol and can seamlessly integrate with the wastewater treatment plant's existing SCADA system.

[0035] The influent water quality of the plant fluctuates within the following ranges: CODin = 180~350 mg / L, TNin = 25~40 mg / L. The effluent complies with the Class A standard of the "Discharge Standard of Pollutants for Municipal Wastewater Treatment Plants" (GB18918-2002), requiring TNo ≤ 15 mg / L and ammonia nitrogen ≤ 5 mg / L. In summer (water temperature T > 20℃), the DO control range is set at 0.8~1.6 mg / L, and in winter (water temperature T ≤ 20℃), the DO control range is set at 1.2~1.7 mg / L.

[0036] Benchmark settings: Confirm that the effluent ammonia nitrogen consistently meets the standard (measured average value of 0.5 mg / L), set the minimum target value of DO in summer to 0.8 mg / L, and control the range to 0.8~1.6 mg / L; select the DO sensors at the end of two sets of aeration tanks as representative monitoring points, and take the average value of the two sets of sensors.

[0037] Data Acquisition: Data is collected in real time through various sensors. The core data collected at a certain moment are as follows: influent flow rate Q = 1667 m³ / h (corresponding to a treatment scale of 40,000 m³ / d), CODin = 280 mg / L, TNin = 32 mg / L, reaction temperature T = 26℃, current actual air volume of the blower Gs0 = 10500 m³ / h (total of two operating blowers), effluent TNo = 12 mg / L, ammonia nitrogen value = 0.4 mg / L.

[0038] Calculate aveDO using a time window of 0.5h. 30-40 min = 1.0 mg / L; calculate aveDO 0-10 min = 1.1 mg / L; then ΔDO 0-40 min = |1.0 - 1.1| = 0.1 mg / L.

[0039] Based on the calculated ΔDO 0-40 The value min = 0.1 mg / L < 0.2 mg / L, which falls under level 1. The corresponding basic adjustment range for the fan airflow is 3% Qg. The maximum airflow of a single fan is Qg = 8000 m³ / h, and the total basic adjustment range for both operating fans is 3% × 8000 = 240 m³ / h.

[0040] Constraint execution: Set the air volume control range of a single fan to 30%~95%Qg (to avoid low-load surge or overload operation of the fan). The adjustment range in this case is 3%Qg, which does not exceed 5%Qg. Therefore, there is no need to set an adjustment interval. The adjustment command will be executed directly to increase the fan air volume by 240m³ / h.

[0041] Closed-loop validation: After adjustment, the DO value was continuously monitored. The average DO value collected after 5 minutes was 1.13 mg / L, which is within the summer DO control range (0.8~1.6 mg / L), and ΔDO 0-40 The concentration of DO remained below 0.2 mg / L, indicating that the concentration was stable within the target range and the adjustment was effective.

[0042] When there is a difference in DO concentration between the two aeration tanks in the plant, for example, the average DO concentration in one tank is 0.9 mg / L and that in the other tank is 1.3 mg / L, the following adjustment logic will be followed: Based on the pool with a low DO (0.9 mg / L), the theoretical air volume GsL = 12500 m³ / h (total of two fans) was calculated. The actual current total air volume Gs0 = 11500 m³ / h, ΔG = 1000 m³ / h. ΔDO 0-40 The minimum calculated value is 0.3 mg / L (at level 2). The basic adjustment range is 5%Qg = 400 m³ / h. The optimized adjustment range is max{ΔG / a, 5%Qg} = max{1000 / 6, 400} = max{166, 400} = 400 m³ / h, which does not exceed 10%Qg (800 m³ / h). Therefore, the total adjustment range is determined to be 400 m³ / h. The control decision module generates the following instructions: Increase the total air volume of the two fans to 11500 + 400 = 11900 m³ / h, and at the same time adjust the opening of the electric valves of the two sets of tanks. Increase the valve opening of the tank with low DO by 5%, and keep the valve opening of the tank with high DO unchanged, so as to ensure that the DO concentration of the two sets of tanks gradually stabilizes within the range of 0.8~1.6 mg / L.

[0043] Operation monitoring: The closed-loop monitoring module displays real-time data on DO concentration in the two aeration tanks, blower operating status (opening degree, air volume, power), and influent water quality, generating daily / weekly / monthly operation reports. The DO concentration fluctuation curve shows that the fluctuation range after adjustment is controlled within 0.3 mg / L, and the energy consumption per unit volume of water treated is reduced from 0.42 kWh / m³ to 0.25 kWh / m³, demonstrating significant energy-saving effects.

[0044] Anomaly Handling: When a DO sensor fails, the system triggers a sensor failure alarm (audible and visual alarm + SCADA platform push), and automatically switches to backup sensor data; when the DO concentration remains below 0.8 mg / L or above 1.6 mg / L for 30 minutes, a DO over-limit alarm is triggered, and steps S2 to S4 are repeated to increase the adjustment range (maximum adjustment of 12% Qg in level 3) until the DO returns to stability.

[0045] The above embodiments are merely illustrative of the principles and effects of the present invention and are not intended to limit the invention. Any person skilled in the art can modify or alter the above embodiments without departing from the spirit and scope of the present invention. Therefore, all equivalent modifications or alterations made by those skilled in the art without departing from the spirit and technical concept disclosed in the present invention should still be covered by the claims of the present invention.

Claims

1. A method for intelligent control of blowers in aeration tanks of wastewater treatment plants, characterized in that, Includes the following steps: S1 Benchmark Setting and Data Acquisition: Under the premise that the effluent ammonia nitrogen meets the standard, set the minimum target value of dissolved oxygen, select representative DO monitoring points in the aeration tank, and set a seasonally appropriate DO control range; collect influent data in real time: flow rate Q, CODin, TNin, and process data: DO value, ammonia nitrogen value, reaction temperature T, blower opening degree, actual air volume Gs0; and effluent data TNo; S2 DO variation calculation: Using a time window of 0.5h, calculate the average DO value (aveDO) from the 30th to the 40th minute. 30-40 min and mean DO from 0 to 10 minutes aveDO 0-10 min, and obtain the change magnitude ΔDO. 0-40 min=|aveDO 30-40 min-aveDO 0-10 min|; S3 DO range matching with basic adjustment range: based on ΔDO 0-40min The basic adjustment range is set in three levels: Part 1: ΔDO 0-40 If min < 0.2 mg / L, the basic adjustment range of the fan air volume is 3% Qg; Section 2: 0.2≤ΔDO 0-40 min≤0.5mg / L, fan air volume basic adjustment range 5%Qg; Gear 3: ΔDO 0-40 If the concentration of min is greater than 0.5 mg / L, the basic adjustment range of the fan air volume is 7% Qg; Where Qg is the maximum air volume of a single fan; S4 Theoretical Airflow Prediction and Adjustment Range Optimization: Based on the inlet water and reaction parameters, the required airflow GsL is calculated using a theoretical formula: GsL = (((Q)) COD in Bc-4) 1.47 / 1000+Q (TN in -2) 4.57 / 1000-(Q (TNin-TNo) / 1000-0.12(Q (CODin Bc-4) Y / 1000)) 3-(Q COD in Bc-4) Y / 1000)1.42))Cs / (α (β Csb-DO)1.024^(T-20))) / (0.28 E A ); Where Q represents the influent flow rate and COD. in For influent COD concentration, TN in TNo represents the total nitrogen concentration in the influent, TNo represents the total nitrogen concentration in the effluent, correction factor Bc = 0.3~0.6, sludge yield coefficient Y = 0.5~0.8, mixed liquor temperature T = 15~30℃, standard saturated dissolved oxygen concentration Cs = 9~10 mg / L, wastewater oxygen transfer correction factor α = 0.8~0.9, mixed liquor saturated oxygen concentration Csb = 10~11 mg / L, and oxygen transfer efficiency E0 A =20~30%, DO is the residual dissolved oxygen value of the mixture; calculate the air volume difference ΔG=GsL-Gs0, and optimize it in combination with the basic adjustment range: Gear 1: Fan airflow adjustment 3% Qg; Gear 2: Fan air volume adjustment max{ΔG / a,5%Qg}, not exceeding 10%Qg; Gear 3: Fan air volume adjustment max{ΔG / 0.5a,7%Qg}, not exceeding 12%Qg; Where 'a' is the time (h) from the influent to the aeration tank.

2. The intelligent control method for blowers in aeration tanks of wastewater treatment plants according to claim 1, characterized in that: In S1, the DO control range is set as follows: when the water temperature is ≥20℃, the DO target control is 0.8~1.6mg / L, and when the water temperature is <20℃, the DO target control is 1.2~1.7mg / L.

3. The intelligent control method for blowers in aeration tanks of wastewater treatment plants according to claim 2, characterized in that: It also includes S5: constraint execution and closed-loop verification. Based on the characteristics of the fan, the air volume control range of a single fan is set; after adjustment, the DO value is continuously monitored. If it still deviates from the set range, steps S2 to S4 are repeated until the DO stabilizes in the target range.

4. The intelligent control method for blowers in aeration tanks of wastewater treatment plants according to claim 3, characterized in that: In step S1, representative DO monitoring points are selected at the middle and end of the aeration tank, avoiding the influent impact zone and the effluent transition zone.

5. The intelligent control method for the blower of the aeration tank in a wastewater treatment plant according to claim 4, characterized in that: For scenarios where two processes operate in parallel, the optimization and adjustment logic in step S4 is as follows: the adjustment range is calculated based on the aeration tank with lower dissolved oxygen, and the air volume is distributed by the valve opening to ensure that the DO of both tanks is stable within the set range.

6. A system for implementing the intelligent control method for blowers in aeration tanks of wastewater treatment plants according to any one of claims 1-5, characterized in that, include: Data acquisition module: Composed of DO sensor, ammonia nitrogen sensor, flow sensor, influent online monitor (monitoring COD and TN), temperature sensor and air volume sensor, used to collect various operating data in real time; Data processing module: used to calculate the change in DO, ΔDO 0-40 min, theoretical air volume GsL and air volume difference ΔG, to complete the classification judgment and adjustment range optimization; Control decision module: Used to generate fan opening adjustment commands that meet the constraints based on the classification results and the optimized adjustment range; Execution module: includes fan frequency converter and electric valve, used to receive commands to adjust the opening degree and control the air volume output; Closed-loop monitoring module: Used to display DO concentration, fan operating status, and air volume data in real time. It supports historical curve query, abnormal alarm and parameter fine-tuning. When DO deviates from the set range, it triggers readjustment.

7. The system according to claim 6, characterized in that, The data acquisition module supports Modbus and Profinet communication protocols and can interface with the existing SCADA system of the wastewater treatment plant to achieve data exchange and centralized management.

8. The system according to claim 6, characterized in that, The closed-loop monitoring module's abnormal alarm functions include DO exceeding standard alarm, ammonia nitrogen exceeding standard alarm, fan opening abnormality alarm, and sensor fault alarm. The alarm methods are audible and visual alarms and platform push notifications, and the alarm thresholds can be customized.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program, which, when executed by a processor, implements the intelligent control method for the blower of the aeration tank in a wastewater treatment plant as described in any one of claims 1-5.

10. A computer device, characterized in that: The computer device includes a processor and a memory, the memory being used to store computer programs, and the processor being configured to invoke the computer programs to execute the steps of the intelligent control method for the blower of the aeration tank in a wastewater treatment plant according to any one of claims 1-5.

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