Intelligent equalization water distribution method for multi-series biological system of sewage plant sharing flow meter

Abstract

The present application relates to sewage treatment technical field, specifically to sewage plant multi-series biological system's intelligent equalization water distribution method of sharing flowmeter, the present application gathers total flow, branch pressure difference, water quality and biochemical operation parameter, constructs time-varying fouling resistance model with influent SS, running length, relies on total flow conservation to deduce each branch accurate flow;Combined with effluent COD, ammonia nitrogen, total nitrogen and MLSS, the load weight is calculated, and the target flow is dynamically distributed;Fuzzy PID regulating valve is used to suppress jitter;Through the hydraulic balance coefficient, the branch blockage and leakage are distinguished, the fault branch is isolated, and the water quantity is redistributed after reserving the bottom flow, forming the measurement-decision-regulation-fault correction closed loop.The present application does not need to install branch flowmeter, the transformation cost is low, the flow calculation error is ≤±2%, the water can be distributed according to demand, the automatic fault tolerance is realized, the biochemical operation is stable, and the risk of effluent exceeding standard is reduced.

Description

Technical Field

[0001] This invention relates to the field of wastewater treatment technology, specifically to an intelligent balanced water distribution method for multi-series biological systems in wastewater treatment plants that share a flow meter. Background Technology

[0002] Currently, the vast majority of wastewater treatment plants in China adopt a multi-series parallel operation mode for their biological treatment systems. In order to save on construction and renovation costs, many old and small-to-medium-sized wastewater treatment plants only install one total flow meter on the main influent pipe, and each biological branch pipeline has no independent flow meter or independent metering capability. The existing technology has the following core bottlenecks, and there is no mature solution in the industry: 1. No branch metering, water distribution is completely crude: Traditional water distribution must rely on branch flow meters to achieve precise allocation. In the case of no branch meter, it can only rely on fixed valve opening and manual experience to adjust. The water distribution of each series has a large deviation. There has been a long-term problem of some series being overloaded at high load and some series running at low load, resulting in large fluctuations in effluent water quality, high energy consumption and unstable biological community.

[0003] 2. Fixed water distribution logic, unable to adapt to fluctuations in water quality conditions: Existing intelligent water distribution technologies all adopt a fixed ratio distribution mode, which only allocates water based on the total flow rate. It does not take into account the real-time influent COD, ammonia nitrogen, total nitrogen pollution load and the operating status of each series of sludge, and cannot achieve "on-demand water distribution". It has poor anti-interference ability under water quality shock conditions and is very prone to treatment failure and effluent exceeding the standard.

[0004] 3. Complex wastewater conditions and unresolved latent hydraulic imbalances: Wastewater contains a large amount of suspended solids and impurities, which can easily lead to problems such as sludge accumulation, scaling, aging, local blockage, and leakage in pipelines over long-term operation. This causes time-varying drift in pipeline hydraulic resistance, resulting in latent water separation deviations. The existing system lacks quantitative fault identification and automatic correction and compensation capabilities, relying solely on manual inspection and troubleshooting. This leads to delayed maintenance, continuous accumulation of errors, and severely impacts the overall operational stability of the biochemical system.

[0005] In summary, existing technologies suffer from three major shortcomings: reliance on hardware metering, rigid allocation logic, and lack of operational condition tolerance and correction. There is a significant technological gap in low-cost retrofitting scenarios where multiple series share a single flow meter, and there is an urgent need for a new intelligent, instrument-free, adaptive, and self-correcting water separation technology solution. Summary of the Invention

[0006] The purpose of this invention is to provide an intelligent balanced water distribution method for multiple series of biological systems in wastewater treatment plants that share a flow meter. This method addresses the problems of existing parallel biological systems in wastewater treatment plants that are only equipped with a single total flow meter and lack independent metering instruments for each biological branch. These problems include the lack of a robust and fixed water distribution regulation, the inability to dynamically distribute water according to water quality and sludge load, the inability to automatically identify and compensate for hydraulic faults such as sludge accumulation and leakage in pipelines, and the lack of low-cost and accurate flow measurement methods.

[0007] To achieve the above objectives, the present invention adopts the following technical solution: an intelligent balanced water distribution method for multi-series biological systems in a wastewater treatment plant that shares a flow meter. The method is applied to parallel multi-series biological systems with only one main influent flow meter and no independent flow meters for each biological branch pipeline, and includes the following steps: S1. Basic Data Acquisition The total system inlet flow rate is obtained in real time by a total flow meter installed on the main inlet pipe. And obtain the pressure difference between the liquid level before and after each branch pipeline. Influent water quality parameters and operating parameters of each series of biological treatment tanks; S2, Branchless Instrument Traceability Measurement Based on the constraint of total flow conservation, a time-varying fouling resistance correction model for each branch is constructed, utilizing the total influent flow rate. Pressure difference between the liquid levels of each branch The real-time accurate flow rate of each branch pipeline under the condition of no independent flow meter can be calculated by inversion. Among them, the time-varying fouling resistance correction model dynamically corrects the pipeline friction coefficient based on the cumulative operating time and the concentration of suspended solids in the influent, so as to eliminate the interference of fouling deposition on flow estimation. S3, Adaptive Proportioning Decision of Water Quality and Sludge Load Based on the influent water quality parameters and the operating parameters of each series of biological treatment tanks, the real-time pollution load treatment weight of each biological treatment series is quantified. The optimal water allocation ratio for each series is dynamically calculated based on the weight normalization results of each series. With the target water diversion flow Pollution load treatment weight It should include at least the influencing factors of effluent COD, ammonia nitrogen, total nitrogen concentration and sludge concentration MLSS, so as to realize the on-demand water allocation decision of high load and low load. S4, Valve steady-state control execution Real-time accurate traffic With the target water diversion flow Compare and calculate the flow deviation The valve opening increment is adjusted by outputting a fuzzy PID controller. The valve opening of each branch pipeline is dynamically adjusted to make the actual flow rate of each branch pipeline approach the target water distribution flow rate, and to suppress flow fluctuations and valve vibrations during the adjustment process. S5. Hydraulic Fault Identification and Fault-Tolerant Correction Throughout the entire water distribution process from S2 to S4, the hydraulic balance coefficient of each branch is continuously calculated. and according to Compared with the average of all normal branches The comparison results determine whether there is a blockage or leakage fault; when determining a certain branch... In the event of a fault, the faulty branch is automatically isolated, and a preset safety margin flow rate is applied to it. The pollutant load treatment weight and target water distribution flow of the remaining normal branches are deducted from the total system flow and returned to S3 to recalculate. This achieves flow compensation allocation for the faulty branches and ensures that the system maintains balanced water distribution among the normal branches even under fault conditions. S6, Closed-loop iterative operation Repeatedly executing S2 to S5 forms a closed-loop intelligent water distribution control cycle of metering → decision-making → execution → fault identification → re-decision, enabling the system to achieve all-weather, unattended, adaptive, and balanced water distribution.

[0008] Furthermore, in S2, the real-time accurate flow rate of each branch pipeline is calculated through inversion. Specific methods include: S201, Calculate the... Basic theoretical instantaneous flow rate of branch pipeline

[0009]

[0010] in, For the first Flow coefficient of valves in branch pipelines; For the first Effective cross-sectional area of ​​branch pipes, in m² 2 g is the acceleration due to gravity, with a value of 9.8 m / s². 2 ; For the first Differential pressure / head difference before and after each branch pipeline, in meters; S202, Calculate the first Branch pipeline in Time-varying friction coefficient at time 1

[0011]

[0012] in, For the first The initial inherent friction coefficient of a branch pipeline in its brand-new state; This is a correction factor for fouling deposition conditions, calibrated based on on-site water quality conditions. The cumulative system running time, in hours (h). For integration time series variables; for Time of the first Instantaneous flow rate of each branch pipeline, in m³ 3 / h; for Concentration of suspended solids in influent at any given time, in mg / L; S203, Calculate the first Comprehensive resistance correction factor for branch pipelines With real-time accurate traffic

[0013]

[0014]

[0015] in, For the first The theoretical instantaneous flow rate of the branch pipeline, in m³ 3 / h; The total number of parallel branches in a biochemical system; The total influent flow rate of the system is collected in real time by the total flow meter, in cubic meters per second (m³). 3 / h.

[0016] Furthermore, in S3, the real-time pollution load treatment weight for each biochemical series is quantified. And calculate the optimal water distribution ratio. With the target water diversion flow Specific methods include: S301, Calculate the first Real-time pollution load treatment weight for each biochemical series

[0017]

[0018] in, , , , These are weighted correction factors for COD, ammonia nitrogen, total nitrogen, and sludge concentration, respectively, calibrated based on water toxicity and process priority; , , The first The concentrations of chemical oxygen demand, ammonia nitrogen, and total nitrogen in the effluent from each biochemical series are all in mg / L. For the first Real-time sludge concentration in each biochemical series of biochemical tanks, unit: mg / L; This is a negatively correlated term with sludge concentration, indicating that the higher the sludge concentration, the lower the remaining treatment capacity. S302, Calculate the first Real-time optimal water separation ratio for each biochemical series

[0019]

[0020] in, For the first The real-time optimal water separation ratio for each biochemical series, with a value ranging from 0 to 1; For the first Real-time pollution load treatment weights for each biochemical series; The total number of parallel branches in a biochemical system; S303, Calculate the first Real-time target water distribution flow rate for each biochemical series

[0021]

[0022] in, This represents the total real-time influent flow rate of the system, in cubic meters per second (m³). 3 / h.

[0023] Furthermore, in S4, the valve opening adjustment increment is output through a fuzzy PID controller. Specific methods include: S401, Calculate the first Flow deviation at sampling time

[0024]

[0025] in, For the first Sampling time number Real-time target flow rate of each branch pipeline, in m³ 3 / h; For the first Sampling time number Real-time accurate flow rate of each branch pipeline, in m³ 3 / h; S402: Calculate the... Valve opening adjustment increment at sampling time

[0026]

[0027] in, This is the proportional adjustment coefficient that has been corrected in real time using fuzzy rules; This is the integral adjustment coefficient that has been corrected in real time using fuzzy rules; The differential adjustment coefficient is corrected in real time by fuzzy rules; For the first Change in flow rate deviation at the sampling time; For the first The change in flow deviation at the previous sampling time.

[0028] Furthermore, in S5, the specific method for continuously calculating the hydraulic balance coefficient of each branch and determining the fault includes: S501, Calculate the first Real-time hydraulic balance coefficient of branch pipeline

[0029]

[0030] in, For the first Real-time accurate flow rate of each branch pipeline, in cubic meters. 3 / h; For the first Real-time head pressure difference before and after each branch pipeline, in meters; S502. Calculate the arithmetic mean of the hydraulic balance coefficients of all normally operating branches.

[0031]

[0032] in, The set of all normally functioning branches; This represents the number of normally functioning branch lines. S503. Judgment No. Is there a fault in the branch pipeline? when When, it is determined that there is a blockage fault in the branch; when Furthermore, if the valve opening of the branch is within the normal range, it is determined that there is a leakage fault in the branch; among them, 0.8 and 1.2 are the engineering steady-state adaptive calibration thresholds, which are adaptively fine-tuned according to the on-site working conditions.

[0033] Furthermore, in S5, when determining a certain branch... When a fault occurs, the specific methods for automatically isolating the faulty branch and performing flow compensation and distribution include: S504, Transfer the faulty branch Remove from the set of normally functioning branches, retaining only their preset safety margin flow. It is used to protect faulty branches from dry burning or overload damage; S505, Calculate the fault isolation after the first... Update target traffic of a normal branch

[0034]

[0035] in, For the first The pollution load treatment weight of the biochemical series where the normal branch is located; The sum of the pollution load treatment weights for all normally functioning branches in the biochemical series; Preset a safety margin flow rate for the faulty branch, in m³. 3 / h; The branch number is for the abnormal fault; S506, will update target traffic As the target input of the fuzzy PID controller in S4, it drives the normal branch valve to perform new opening regulation.

[0036] Furthermore, in S5, after performing fault isolation and flow compensation allocation, the system continuously monitors the hydraulic balance coefficient of the faulty branch. With respect to valve status, when Restored to [0.8] 1.2 When the faulty branch is within the specified range and the stable time reaches the preset threshold, it will be automatically reinstated into the normal working branch set and returned to S3 to recalculate the water distribution ratio and target flow of all branch pipelines.

[0037] The intelligent balanced water distribution system employing the above method is applied to parallel multi-series biochemical systems where only one total influent flow meter is installed and each biochemical branch pipeline does not have an independent flow meter, including: The data acquisition module is used to obtain the total inflow rate of the system in real time. Differential pressure between the liquid levels before and after each branch pipeline Influent water quality parameters and operating parameters of each series of biological treatment tanks; The flow rate projection module communicates with the data acquisition module and constructs a time-varying fouling resistance correction model for each branch based on the total flow rate conservation constraint, utilizing the total influent flow rate. Pressure difference between the liquid levels of each branch Inverse calculation of the real-time accurate flow rate of each branch pipeline under the condition of no independent flow meter ; The load allocation decision module communicates with the data acquisition module and the flow projection module, and quantifies the real-time pollution load treatment weight of each biological treatment series based on the influent water quality parameters and the operating parameters of each series of biological treatment tanks. The optimal water allocation ratio for each series is dynamically calculated based on the weight normalization results of each series. With the target water diversion flow ; The valve control module communicates with the flow projection module and the load allocation decision module to transmit real-time and accurate flow data. With the target water diversion flow The comparison is performed, and the valve opening adjustment increment is adjusted by outputting the fuzzy PID controller. Dynamically adjust the valve opening of each branch pipeline; The fault-tolerant module communicates with the flow projection module and the load allocation decision module to continuously calculate the hydraulic balance coefficient of each branch. ,according to The comparison result with the average of all normal branches determines whether there is a blockage or leakage fault. When a fault is determined to occur in a branch, the faulty branch is automatically isolated and the load allocation decision module is notified to recalculate the target water distribution flow of the remaining normal branches. The main control loop module is connected to the data acquisition module, flow projection module, load ratio decision module, valve control module, and fault tolerance module, respectively, and controls each module to run continuously in a closed-loop control cycle of acquisition → projection → decision → execution → fault identification → re-decision.

[0038] Furthermore, the system also includes a human-machine interface module, which communicates with the main control loop module to display in real time the estimated flow rate, target flow rate, valve opening, hydraulic balance coefficient, and fault status information of each branch. It also provides a parameter calibration interface for maintenance personnel to adjust the weighted correction coefficient. , , , Dirt deposit correction factor Fault detection threshold and safety margin flow rate Perform on-site adaptive calibration and online adjustment.

[0039] Furthermore, the influent water quality parameters shall include at least the influent COD concentration, influent ammonia nitrogen concentration, influent total nitrogen concentration, and influent suspended solids concentration; the operating parameters of each series of biological treatment tanks shall include at least the effluent COD concentration, effluent ammonia nitrogen concentration, effluent total nitrogen concentration, and real-time sludge concentration (MLSS) of each series of biological treatment tanks.

[0040] The beneficial effects of this invention are: 1. This invention breaks through the reliance on traditional hardware metering, eliminates the need to install branch flow meters, is suitable for all old sewage treatment plant renovation scenarios, has extremely low renovation costs, significantly reduces equipment, construction, and operation and maintenance costs, and has strong engineering feasibility.

[0041] 2. This invention controls the flow error within ±2% through a multi-dimensional correction model, abandons the crude fixed water distribution mode, realizes precise water distribution on demand in conjunction with water quality load, effectively balances biochemical load, stabilizes bacterial community, and improves the effluent compliance rate.

[0042] 3. This invention has the ability to quantitatively identify faults and actively correct deviations, solve the problem of hidden hydraulic imbalance under complex sewage conditions, is fault-tolerant and adaptive under all operating conditions, has strong anti-interference ability and high operational stability, and does not require frequent manual debugging. Detailed Implementation

[0043] The technical solution of the present invention will be clearly and completely described below with reference to the embodiments of the present invention.

[0044] The system flow of this invention is as follows: I. A traceability metering model for branchless flowmeters based on total flow conservation and time-varying resistance correction Breaking away from the industry's technical prejudice that "water distribution control must be equipped with branch flow meters," this approach completely abandons branch hardware metering equipment. Instead, it relies solely on the total flow data from the single on-site total flow meter, combined with hydraulic parameters and water quality time-series data for each branch, to construct a time-varying hydraulic resistance correction model, accurately predicting the real-time flow of each branch pipeline.

[0045] 1) Branch-based theoretical flow calculation formula:

[0046] In the formula: For the first Theoretical instantaneous flow rate of the biochemical branch pipeline, in m³ 3 / h; This is the valve flow coefficient, an inherent correction factor determined by the valve model and opening structure; For the first Effective cross-sectional area of ​​branch pipes, in m² 2 ; Let g be the acceleration due to gravity, a constant, with a value of 9.8 m / s². 2 ; For the first The pressure difference / head difference before and after each branch pipeline, in meters.

[0047] 2) Time-varying fouling resistance correction model:

[0048] In the formula: for Time of the first The real-time time-varying friction coefficient of the branch road; For the first The initial inherent friction coefficient of a branch pipeline in its brand-new state; This is a correction factor for fouling deposition conditions, which can be calibrated and adaptively fine-tuned according to on-site water quality conditions. The cumulative system running time, in hours (h). This is an integral time series variable, representing the running time at any given moment; for Time of the first Instantaneous flow rate of the branch, in m³ 3 / h; for The concentration of suspended solids in the influent at any given time, expressed in mg / L, is used to characterize the rate of fouling deposition.

[0049] 3) Total flow conservation calibration yields accurate branch flow:

[0050] Among them, the pipeline comprehensive correction factor is:

[0051] In the formula: For the first time after calibration The precise actual flow rate of each branch pipeline, in cubic meters. 3 / h; For the first The overall pipeline resistance correction factor for each branch road; For the first The theoretical instantaneous flow rate of the branch pipeline, in m³ 3 / h; The total number of parallel branches in a biochemical system; The total influent flow rate of the system is collected in real time by the total flow meter, in cubic meters per second (m³). 3 / h.

[0052] No branch metering equipment needs to be installed, and the flow calculation error is ≤±2%. It is perfectly adapted to old sewage treatment plants with no room for renovation and low-cost renovation scenarios, and completely solves the industry pain points of branchless instruments being unable to accurately measure flow and distribute water evenly.

[0053] II. Water Quality-Sludge Loading Dual-Dimensional Adaptive Dynamic Proportioning and Fuzzy PID Steady-State Control Algorithm Abandoning the traditional fixed-ratio equal distribution logic, the water volume is no longer allocated solely based on the total flow rate. Instead, it combines the pollutant load of the biological treatment tank (effluent ammonia nitrogen, COD, total nitrogen, etc.) with the treatment capacity of each series of biological sludge to quantify the real-time carrying capacity of each series and dynamically allocate the optimal water distribution ratio. At the same time, fuzzy PID incremental control is adopted to suppress valve vibration and water distribution instability caused by fluctuations in water quality and quantity.

[0054] 1) Formula for quantifying the weight of a single series of pollution loads:

[0055] In the formula: For the first Real-time pollution load treatment weights for each biochemical series; , , , These are weighted correction factors for COD, ammonia nitrogen, total nitrogen, and sludge concentration, respectively, calibrated based on water toxicity and process priority; For the first Series of effluent chemical oxygen demand concentrations, in mg / L; For the first Series of effluent ammonia nitrogen concentrations, unit: mg / L; For the first Total nitrogen concentration in effluent, unit: mg / L; For the first Real-time sludge concentration in a series of biological treatment tanks, in mg / L; It is negatively correlated with sludge concentration. The higher the sludge concentration, the lower the remaining treatment capacity and the smaller the water distribution weight, which is consistent with the process mechanism of activated sludge process.

[0056] 2) Normalized formula for dynamic water distribution ratio:

[0057] In the formula: For the first The real-time optimal water separation ratio for each biochemical series, with a value ranging from 0 to 1; For the first Real-time pollution load treatment weights for each biochemical series; This represents the total number of parallel biochemical series in the system.

[0058] 3) Formulas for target water distribution flow rates for each series:

[0059] In the formula: For the first Real-time target water distribution flow rate of the series, in m³ 3 / h; This represents the total real-time influent flow rate of the system, in cubic meters per second (m³). 3 / h.

[0060] 4) Incremental formula for steady-state control of fuzzy PID valve:

[0061] In the formula: For the first The valve opening adjustment increment at the sampling time; This is a proportional adjustment coefficient for real-time fuzzy correction. The integral adjustment coefficient is used for real-time fuzzy correction. The differential adjustment coefficient is used for real-time fuzzy correction. For the first Flow deviation at sampling time ; For the first Changes in flow rate deviation over time; This represents the change in flow rate deviation at the previous sampling time.

[0062] It achieves on-demand intelligent water distribution of "more water distribution under high load and less water distribution under low load", balances the load of various series of biochemical treatments, stabilizes the activity of bacterial communities, and avoids frequent valve vibration, thus greatly improving the system's regulation stability and resistance to water quality shocks.

[0063] III. Fault Identification and Dynamic Fault-Tolerant Correction Mechanism Based on Quantitative Analysis of Hydraulic Balance Coefficient To address the harsh operating conditions of sewage with high impurities, easy blockage, and easy leakage, a quantitative criterion for hydraulic balance coefficient is established to accurately identify hidden anomalies such as branch blockage, leakage, and valve jamming. When a single branch fails, the anomaly is automatically isolated and the flow is redistributed to achieve fault-tolerant correction without manual intervention, and the steady flow self-cleaning structure eliminates hydraulic turbulence errors.

[0064] 1) Formula for branch hydraulic balance coefficient:

[0065] In the formula: For the first The real-time hydraulic balance coefficient of a branch line characterizes the flow capacity of the pipeline; For the first Real-time accurate flow rate of each branch, unit m 3 / h; For the first Real-time head pressure difference before and after the branch road, in meters.

[0066] 2) Fault quantification judgment threshold formula: Branch road blockage determination:

[0067] Branch circuit leakage determination: (Valve opening is within the normal range) In the formula: This is the arithmetic mean of the hydraulic balance coefficients of all normally functioning branches;

[0068] In the formula: For the set of all normally functioning branches; This represents the number of normally functioning branches.

[0069] 0.8, 1.2: Engineering steady-state adaptive calibration thresholds, used to distinguish between normal operating conditions and fault conditions, and can be adaptively fine-tuned.

[0070] 3) Abnormal operating condition flow compensation and correction formula:

[0071] In the formula: For the first time after fault isolation Update target flow for a normal branch, in m 3 / h; The branch number identified as an abnormal fault; This is the sum of the load weights of all normally functioning branches; A safety margin flow is preset for abnormal branches to protect faulty branches and prevent them from being damaged by dry burning or overload.

[0072] Unlike traditional passive protection that only alarms without compensation, this system achieves automatic fault identification, automatic isolation, and automatic flow compensation, solving the problem of hidden hydraulic imbalance under complex working conditions. The system can operate stably 24 / 7 without human intervention, and its fault tolerance and reliability are greatly improved.

[0073] Example 1 A wastewater treatment plant has a daily treatment capacity of 200,000 tons. The water level in the plant's distribution well ranges from 0.8 to 1 meter. This distribution well is connected to biological treatment tanks No. 1, No. 2, and No. 3 via three branch pipes. The water level in all three biological treatment tanks is 0 meters. Each branch pipe connecting to a biological treatment tank is equipped with a butterfly valve of the same model. The pipe and valve diameter is DN700, meaning the effective cross-sectional area of ​​each branch is A = 0.3848 m². 2Among them, biological pond No. 2 is closest to the water distribution well and has the shortest branch pipe, while biological ponds No. 1 and No. 3 are at the same distance from the water distribution well and are relatively far away.

[0074] 1. Calculation of initial friction coefficient of branch pipe Table 1 shows the inflow rate of each biological tank and the opening degree of each branch valve after pipeline cleaning. Table 1. Instantaneous water inflow at the beginning of March 2023

[0075] Based on the data in Table 1, and combined with the branch flow calculation formula... The initial friction coefficient of each branch pipe in its brand-new state can be calculated. The valve flow coefficient can be found in Table 2. Finally, the initial friction coefficients of branch pipes 1, 2, and 3 are calculated. The values ​​are 0.79, 0.89, and 0.78, respectively.

[0076] Table 2. Correspondence between valve opening degree and valve flow coefficient

[0077] 2. Calculation of the correction factor for dirt deposition According to the reports, the total influent volume of the wastewater treatment plant in 2023 was 84.18 million tons, with an average influent suspended solids (SS) concentration of 201 mg / L. Table 3 shows the influent volume and valve opening of each biological treatment tank in March 2024. Table 3. Instantaneous water inflow at the beginning of March 2024

[0078] Based on the data in Table 3, the current friction coefficients of branch pipes 1, 2, and 3 can be calculated. The values ​​are 0.7, 0.75, and 0.69, respectively. Therefore, the fouling correction factors for branches 1, 2, and 3 can be calculated. It is 5.35×10 -6 8.31×10 -6 5.35×10 -6 .

[0079] 3. Example Verification Due to process control requirements, the influent flow rate to biological tank No. 3 needs to be reduced by approximately 600 m³. 3 / h, that is, increase the inflow of biological tanks No. 1 and No. 2 by 300m³ each. 3 / h, the instantaneous inflow rates of biological tanks 1, 2, and 3 are each 3500m³. 3 / h, 3500m 3 / h, 2600m 3 / h. Substituting the above flow rates into the formula, the valve openings for biological tanks 1, 2, and 3 are 69%, 65%, and 56%, respectively. After adjusting the valve openings, the measured flow rates are shown in Table 4. Table 4. Instantaneous water inflow after process control

[0080] The measured flow rate is close to the target flow rate.

[0081] This invention is not limited to the preferred embodiments described above. Anyone can derive other products in various forms under the guidance of this invention. However, regardless of any changes made in their shape or structure, any technical solution that is the same as or similar to this invention falls within the protection scope of this invention.

Claims

1. A smart balanced water distribution method for multi-series biological systems in a wastewater treatment plant using a shared flow meter, characterized in that: The method described above is applicable to parallel multi-series biochemical systems with only one total influent flow meter and no independent flow meters for each biochemical branch pipeline, and includes the following steps: S1. Basic Data Acquisition The total system inlet flow rate is obtained in real time by a total flow meter installed on the main inlet pipe. And obtain the pressure difference between the liquid level before and after each branch pipeline. Influent water quality parameters and operating parameters of each series of biological treatment tanks; S2, Branchless Instrument Traceability Measurement Based on the constraint of total flow conservation, a time-varying fouling resistance correction model for each branch is constructed, utilizing the total influent flow rate. Pressure difference between the liquid levels of each branch The real-time accurate flow rate of each branch pipeline under the condition of no independent flow meter can be calculated by inversion. Among them, the time-varying fouling resistance correction model dynamically corrects the pipeline friction coefficient based on the cumulative operating time and the concentration of suspended solids in the influent, so as to eliminate the interference of fouling deposition on flow estimation. S3, Adaptive Proportioning Decision of Water Quality and Sludge Load Based on the influent water quality parameters and the operating parameters of each series of biological treatment tanks, the real-time pollution load treatment weight of each biological treatment series is quantified. The optimal water allocation ratio for each series is dynamically calculated based on the weight normalization results of each series. With the target water diversion flow Pollution load treatment weight It should include at least the influencing factors of effluent COD, ammonia nitrogen, total nitrogen concentration and sludge concentration MLSS, so as to realize the on-demand water allocation decision of high load and low load. S4, Valve steady-state control execution Real-time accurate traffic With the target water diversion flow Compare and calculate the flow deviation The valve opening increment is adjusted by outputting a fuzzy PID controller. The valve opening of each branch pipeline is dynamically adjusted to make the actual flow rate of each branch pipeline approach the target water distribution flow rate, and to suppress flow fluctuations and valve vibrations during the adjustment process. S5. Hydraulic Fault Identification and Fault-Tolerant Correction Throughout the entire water distribution process from S2 to S4, the hydraulic balance coefficient of each branch is continuously calculated. and according to Compared with the average of all normal branches The comparison results determine whether there is a blockage or leakage fault; when determining a certain branch... In the event of a fault, the faulty branch is automatically isolated, and a preset safety margin flow rate is applied to it. The pollutant load treatment weight and target water distribution flow of the remaining normal branches are deducted from the total system flow and returned to S3 to recalculate. This achieves flow compensation allocation for the faulty branches and ensures that the system maintains balanced water distribution among the normal branches even under fault conditions. S6, Closed-loop iterative operation Repeatedly executing S2 to S5 forms a closed-loop intelligent water distribution control cycle of metering → decision-making → execution → fault identification → re-decision, enabling the system to achieve all-weather, unattended, adaptive, and balanced water distribution.

2. The method according to claim 1, characterized in that: In S2, the real-time accurate flow rate of each branch pipeline is calculated through inversion. Specific methods include: S201, Calculate the... Basic theoretical instantaneous flow rate of branch pipeline in, For the first Flow coefficient of valves in branch pipelines; For the first Effective cross-sectional area of ​​branch pipes, in m² 2 g is the acceleration due to gravity, with a value of 9.8 m / s². 2 ; For the first Differential pressure / head difference before and after each branch pipeline, in meters; S202, Calculate the first Branch pipeline in Time-varying friction coefficient at time 1 in, For the first The initial inherent friction coefficient of a branch pipeline in its brand-new state; This is a correction factor for fouling deposition conditions, calibrated based on on-site water quality conditions. The cumulative system running time, in hours (h). For integration time series variables; for Time of the first Instantaneous flow rate of each branch pipeline, in m³ 3 / h; for Concentration of suspended solids in influent at any given time, in mg / L; S203, Calculate the first Comprehensive resistance correction factor for branch pipelines With real-time accurate traffic in, For the first The theoretical instantaneous flow rate of the branch pipeline, in m³ 3 / h; The total number of parallel branches in a biochemical system; The total influent flow rate of the system is collected in real time by the total flow meter, in cubic meters per second (m³). 3 / h.

3. The method according to claim 1, characterized in that: In S3, the real-time pollution load treatment weight for each biochemical series is quantified. And calculate the optimal water distribution ratio. With the target water diversion flow Specific methods include: S301, Calculate the first Real-time pollution load treatment weight for each biochemical series in, , , , These are weighted correction factors for COD, ammonia nitrogen, total nitrogen, and sludge concentration, respectively, calibrated based on water toxicity and process priority; , , The first The concentrations of chemical oxygen demand, ammonia nitrogen, and total nitrogen in the effluent from each biochemical series are all in mg / L. For the first Real-time sludge concentration in each biochemical series of biochemical tanks, unit: mg / L; This is a negatively correlated term with sludge concentration, indicating that the higher the sludge concentration, the lower the remaining treatment capacity. S302, Calculate the first Real-time optimal water separation ratio for each biochemical series in, For the first The real-time optimal water separation ratio for each biochemical series, with a value ranging from 0 to 1; For the first Real-time pollution load treatment weights for each biochemical series; The total number of parallel branches in a biochemical system; S303, Calculate the first Real-time target water distribution flow rate of each biochemical series in, This represents the total real-time influent flow rate of the system, in cubic meters per second (m³). 3 / h.

4. The method according to claim 3, characterized in that: In step S4, the valve opening adjustment increment is output through a fuzzy PID controller. Specific methods include: S401, Calculate the first Flow deviation at sampling time in, For the first Sampling time number Real-time target flow rate of each branch pipeline, in m³ 3 / h; For the first Sampling time number Real-time accurate flow rate of each branch pipeline, in m³ 3 / h; S402: Calculate the... Valve opening adjustment increment at sampling time in, This is the proportional adjustment coefficient that has been corrected in real time using fuzzy rules; This is the integral adjustment coefficient that has been corrected in real time using fuzzy rules; The differential adjustment coefficient is corrected in real time by fuzzy rules; For the first Change in flow rate deviation at the sampling time; For the first The change in flow deviation at the previous sampling time.

5. The method according to claim 4, characterized in that: In S5, the specific method for continuously calculating the hydraulic balance coefficient of each branch and determining the fault includes: S501, Calculate the first Real-time hydraulic balance coefficient of branch pipeline in, For the first Real-time accurate flow rate of each branch pipeline, in cubic meters. 3 / h; For the first Real-time head pressure difference before and after each branch pipeline, in meters; S502. Calculate the arithmetic mean of the hydraulic balance coefficients of all normally operating branches. in, For the set of all normally functioning branches; This represents the number of normally functioning branch lines. S503. Judgment No. Is there a fault in the branch pipeline? when When, it is determined that there is a blockage fault in the branch; when Furthermore, if the valve opening of the branch is within the normal range, it is determined that there is a leakage fault in the branch; among them, 0.8 and 1.2 are the engineering steady-state adaptive calibration thresholds, which are adaptively fine-tuned according to the on-site working conditions.

6. The method according to claim 5, characterized in that: In S5, when determining a certain branch... When a fault occurs, the specific methods for automatically isolating the faulty branch and performing flow compensation and distribution include: S504, Transfer the faulty branch Remove from the set of normally functioning branches, retaining only their preset safety margin flow. It is used to protect faulty branches from dry burning or overload damage; S505, Calculate the fault isolation after the first... Update target traffic of a normal branch in, For the first The pollution load treatment weight of the biochemical series where the normal branch is located; The sum of the pollution load treatment weights for all normally functioning branches in the biochemical series; Preset a safety margin flow rate for the faulty branch, in m³. 3 / h; The branch number is for the abnormal fault; S506, will update target traffic As the target input of the fuzzy PID controller in S4, it drives the normal branch valve to perform new opening regulation.

7. The method according to claim 6, characterized in that: In S5, after performing fault isolation and flow compensation allocation, the system continuously monitors the hydraulic balance coefficient of the faulty branch. With respect to valve status, when Restored to [0.8] 1.2 When the faulty branch is within the specified range and the stable time reaches the preset threshold, it will be automatically reinstated into the normal working branch set and returned to S3 to recalculate the water distribution ratio and target flow of all branch pipelines.

8. An intelligent balanced water distribution system for multi-series biological systems in a wastewater treatment plant that uses a shared flow meter, characterized in that: The intelligent balanced water distribution system is applied to parallel multi-series biochemical systems with only one main influent flow meter and no independent flow meters for each biochemical branch pipeline, including: The data acquisition module is used to obtain the total inflow rate of the system in real time. Differential pressure between the liquid levels before and after each branch pipeline Influent water quality parameters and operating parameters of each series of biological treatment tanks; The flow rate projection module communicates with the data acquisition module and constructs a time-varying fouling resistance correction model for each branch based on the total flow rate conservation constraint, utilizing the total influent flow rate. Pressure difference between the liquid levels of each branch Inverse calculation of the real-time accurate flow rate of each branch pipeline under the condition of no independent flow meter ; The load allocation decision module communicates with the data acquisition module and the flow projection module, and quantifies the real-time pollution load treatment weight of each biological treatment series based on the influent water quality parameters and the operating parameters of each series of biological treatment tanks. The optimal water allocation ratio for each series is dynamically calculated based on the weight normalization results of each series. With the target water diversion flow ; The valve control module communicates with the flow projection module and the load allocation decision module to transmit real-time and accurate flow data. With the target water diversion flow The comparison is performed, and the valve opening adjustment increment is adjusted by outputting the fuzzy PID controller. Dynamically adjust the valve opening of each branch pipeline; The fault-tolerant module communicates with the flow projection module and the load allocation decision module to continuously calculate the hydraulic balance coefficient of each branch. ,according to The comparison result with the average of all normal branches determines whether there is a blockage or leakage fault. When a fault is determined to occur in a branch, the faulty branch is automatically isolated and the load allocation decision module is notified to recalculate the target water distribution flow of the remaining normal branches. The main control loop module is connected to the data acquisition module, flow projection module, load ratio decision module, valve control module, and fault tolerance module, respectively, and controls each module to run continuously in a closed-loop control cycle of acquisition → projection → decision → execution → fault identification → re-decision.

9. The system according to claim 8, characterized in that: The system also includes a human-machine interface module that communicates with the main control loop module. This module displays the calculated flow rate, target flow rate, valve opening, hydraulic balance coefficient, and fault status information for each branch in real time. It also provides a parameter calibration interface for maintenance personnel to adjust the weighted correction coefficient. , , , Dirt deposit correction factor Fault determination threshold and safety margin flow rate Perform on-site adaptive calibration and online adjustment.

10. The system according to claim 8, characterized in that: The influent water quality parameters should include at least the influent COD concentration, influent ammonia nitrogen concentration, influent total nitrogen concentration, and influent suspended solids concentration; the operating parameters of each series of biological treatment tanks should include at least the effluent COD concentration, effluent ammonia nitrogen concentration, effluent total nitrogen concentration, and real-time sludge concentration (MLSS) of each series of biological treatment tanks.

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