Wastewater treatment method and system based on internal circulation high-efficiency denitrification technology

Abstract

The present application relates to sewage treatment technical field, disclose a kind of sewage treatment method and system based on internal circulation efficient denitrification technology, the method includes obtaining reflux ratio, influent flow and nitrogen concentration, by flow and nitrogen concentration capture water quality fluctuation, judge load level;Coupling relationship of reflux ratio and carbon source amount of dosing is analyzed in combination with load level, and carbon source demand matching value is obtained.If the matching value exceeds the threshold, predict the risk of lag, generate reflux ratio adjustment scheme;Simulate the denitrification reaction process of scheme, determine the correction coefficient, and update the control parameters to obtain the dosing control signal.Threshold value is compared with the signal and matching value, the business association of load level and correction coefficient is fused, and the matching coefficient is calculated;Based on the coefficient, the reflux ratio coupling relationship is integrated, the parameter update amplitude is judged, and the system operating state data is obtained after updating and the instruction is generated.The instruction is sent to the sewage treatment system, and efficient denitrification operation is carried out.The present application can solve the problem of low denitrification efficiency.

Description

Technical Field

[0001] This invention relates to the field of wastewater treatment technology, and in particular to a wastewater treatment method and system based on internal circulation high-efficiency denitrification technology. Background Technology

[0002] Currently, wastewater treatment is a crucial area for environmental protection and resource recycling, directly impacting sustainable water resource development and ecological balance. Especially during urbanization and industrialization, wastewater treatment technologies must efficiently remove nitrogenous pollutants to prevent eutrophication and ecosystem damage. Denitrification, as a core process, converts nitrates into nitrogen gas, reducing water pollution.

[0003] In one existing technology, carbon source addition to the denitrification tank is achieved by a fixed flow pump, relying on a preset fixed value. The addition amount is set according to the average influent nitrogen concentration during the design phase and is not adjusted during operation. The internal circulation return ratio (the flow ratio of the denitrification tank mixed liquor returning to the aerobic tank) is fixedly adjusted to 1:3 (return flow rate: influent flow rate) by a manual valve, and is only finely adjusted by the operation and maintenance personnel based on historical data during quarterly maintenance.

[0004] However, when faced with fluctuations in influent water quality, the fixed carbon source dosage cannot meet the denitrification requirements, leading to the accumulation of nitrates in the denitrification tank and a sharp drop in denitrification efficiency. If excessive carbon source is added manually to avoid exceeding the standard, it will lead to an increase in effluent COD (causing secondary pollution) and increase carbon source consumption. When the internal circulation reflux ratio is fixed at 1:3, it cannot match the changes in carbon source demand. In summary, the existing technology has the problem of low denitrification efficiency. Summary of the Invention

[0005] This invention provides a wastewater treatment method and system based on internal circulation high-efficiency denitrification technology to solve the problem of low denitrification efficiency in existing technologies.

[0006] Firstly, in order to solve the above-mentioned technical problems, the present invention provides a wastewater treatment method based on internal circulation high-efficiency denitrification technology, comprising:

[0007] The internal circulation reflux ratio, influent flow rate and nitrogen concentration data are obtained. Water quality fluctuation characteristics are captured based on the influent flow rate and nitrogen concentration data. The pollutant load level is determined based on the water quality fluctuation characteristics.

[0008] Based on the pollutant load level, the dynamic coupling relationship between the internal circulation reflux ratio and the amount of carbon source to be added is analyzed to obtain the carbon source demand matching value.

[0009] If the carbon source demand matching value exceeds the preset matching value threshold, the risk of regulation lag under the water quality fluctuation trend is predicted, and an internal circulation reflux ratio adjustment scheme is obtained.

[0010] Based on the internal circulation reflux ratio adjustment scheme, the denitrification reaction process is simulated, the coefficient of carbon source addition is determined, and the real-time correction coefficient is obtained.

[0011] The coordinated control parameters are updated based on the real-time correction coefficients to obtain the dosing control signal;

[0012] The optimal matching coefficient is obtained by comparing the dosing control signal with the carbon source demand matching value and integrating the business correlation between the pollutant load level and the real-time correction coefficient.

[0013] Based on the optimized matching coefficient, the dynamic coupling relationship of the internal circulation reflux ratio is integrated to determine the update magnitude of the coordinated control parameters;

[0014] The coordinated control parameters are updated according to the update magnitude, the system's operating status data is obtained, and instructions are generated to obtain the reflux optimization instructions.

[0015] The reflux optimization command is sent to the wastewater treatment system to coordinate the addition of carbon source and the internal circulation reflux ratio, thereby achieving a highly efficient denitrification operation.

[0016] Secondly, the present invention provides a wastewater treatment system based on internal circulation high-efficiency denitrification technology, comprising:

[0017] The data acquisition module is used to acquire data on internal circulation reflux ratio, influent flow rate and nitrogen concentration, capture water quality fluctuation characteristics based on the influent flow rate and nitrogen concentration data, and determine the pollutant load level based on the water quality fluctuation characteristics.

[0018] The data analysis module is used to analyze the dynamic coupling relationship between the internal circulation reflux ratio and the amount of carbon source to be added based on the pollutant load level, and to obtain the carbon source demand matching value.

[0019] The data prediction module is used to predict the risk of regulation lag under the water quality fluctuation trend if the carbon source demand matching value exceeds the preset matching value threshold, and to obtain the internal circulation reflux ratio adjustment scheme.

[0020] The data simulation module is used to simulate the denitrification reaction process according to the internal circulation reflux ratio adjustment scheme, determine the coefficient of carbon source addition, and obtain the real-time correction coefficient.

[0021] The data update module is used to update the coordinated control parameters according to the real-time correction coefficient to obtain the dosing control signal;

[0022] The data comparison module is used to compare the dosing control signal with the carbon source demand matching value based on a threshold, and to integrate the business correlation between the pollutant load level and the real-time correction coefficient to obtain an optimized matching coefficient.

[0023] The data integration module is used to integrate the dynamic coupling relationship of the internal circulation reflux ratio based on the optimized matching coefficient, and determine the update magnitude of the coordinated control parameters.

[0024] The instruction generation module is used to update the coordinated control parameters according to the update magnitude, obtain the system's operating status data, and generate instructions to obtain the reflux optimization instructions.

[0025] The command control module is used to send the reflux optimization command to the wastewater treatment system to coordinate the carbon source addition and the internal circulation reflux ratio to obtain an efficient denitrification operation.

[0026] Thirdly, the present invention also provides an electronic device, including a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein the processor executes the computer program to implement the wastewater treatment method based on the internal circulation high-efficiency denitrification denitrification technology described in any one of the above.

[0027] Fourthly, the present invention also provides a computer-readable storage medium comprising a stored computer program, wherein, when the computer program is executed, it controls the device containing the computer-readable storage medium to perform the wastewater treatment method based on the internal circulation high-efficiency denitrification nitrogen removal technology described above.

[0028] Compared with the prior art, the present invention has the following beneficial effects:

[0029] (1) This invention analyzes the dynamic coupling relationship between the reflux ratio and the carbon source dosage, and combines real-time correction coefficient and optimization matching coefficient to dynamically adjust the synergistic control parameters. This solves the problem in the prior art where the fixed adjustment of the internal circulation reflux ratio and carbon source dosage cannot adapt to the dynamic changes of pollutant load. Either the carbon source is added in excess (increasing costs and secondary pollution), or the addition is insufficient, resulting in incomplete denitrification and low denitrification efficiency.

[0030] (2) This invention predicts water quality fluctuation trends, quantifies the risk of control lag, and generates an internal circulation reflux ratio adjustment scheme in advance; at the same time, it combines process stability data to perform closed-loop optimization; thus, the fluctuation range of denitrification efficiency is greatly reduced compared with the existing technology, and the continuous stable operation time is extended.

[0031] (3) In contrast to the prior art, the carbon source addition and the regulation of the internal circulation reflux ratio are independent and do not form a synergistic mechanism. The present invention achieves deep synergy between the reflux ratio and the carbon source addition through dynamic coupling analysis of the whole process, ensuring that the denitrification reaction is always under optimal conditions and improving the stability of denitrification efficiency. Attached Figure Description

[0032] Figure 1 This is a schematic diagram of the wastewater treatment method based on internal circulation high-efficiency denitrification nitrogen removal technology provided in the first embodiment of the present invention;

[0033] Figure 2 This is a schematic diagram of a wastewater treatment system based on efficient internal circulation denitrification technology provided in the second embodiment of the present invention. Detailed Implementation

[0034] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. 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 are within the scope of protection of the present invention.

[0035] Reference Figure 1 The first embodiment of the present invention provides a wastewater treatment method based on internal circulation high-efficiency denitrification technology, including the following steps:

[0036] S11, acquire internal circulation reflux ratio, influent flow rate and nitrogen concentration data, capture water quality fluctuation characteristics based on the influent flow rate and nitrogen concentration data, and determine the pollutant load level based on the water quality fluctuation characteristics;

[0037] S12, Based on the pollutant load level, analyze the dynamic coupling relationship between the internal circulation reflux ratio and the amount of carbon source to be added, and obtain the carbon source demand matching value;

[0038] S13, If the carbon source demand matching value exceeds the preset matching value threshold, the risk of regulation lag under the water quality fluctuation trend is predicted, and the internal circulation reflux ratio adjustment scheme is obtained.

[0039] S14, simulate the denitrification reaction process according to the internal circulation reflux ratio adjustment scheme, determine the coefficient of carbon source addition, and obtain the real-time correction coefficient;

[0040] S15, update the coordinated control parameters according to the real-time correction coefficient to obtain the dosing control signal;

[0041] S16, compare the threshold value of the dosing control signal with the carbon source demand matching value, and integrate the business correlation between the pollutant load level and the real-time correction coefficient to obtain the optimized matching coefficient;

[0042] S17. Based on the optimized matching coefficient, integrate the dynamic coupling relationship of the internal circulation reflux ratio and determine the update amplitude of the coordinated control parameters.

[0043] S18, update the coordinated control parameters according to the update magnitude, obtain the system's operating status data, and generate instructions to obtain the backflow optimization instructions;

[0044] S19, the reflux optimization command is sent to the wastewater treatment system to coordinate the addition of carbon source and the internal circulation reflux ratio to obtain a highly efficient denitrification operation.

[0045] In step S11, acquiring the internal circulation reflux ratio, influent flow rate, and nitrogen concentration data, capturing water quality fluctuation characteristics based on the influent flow rate and nitrogen concentration data, and determining the pollutant load level based on the water quality fluctuation characteristics includes:

[0046] Based on the influent flow rate and nitrogen concentration data, the water quality fluctuation characteristics are analyzed to obtain the characteristic parameters of water quality fluctuation.

[0047] If the characteristic parameter exceeds the preset characteristic threshold, the water quality fluctuation characteristic distribution is analyzed to obtain the pollutant distribution characteristics of the denitrification stage;

[0048] The pollutant load is calculated based on the pollutant distribution characteristics to obtain the pollutant load level.

[0049] It should be noted that the influent flow rate is collected using an ultrasonic flow meter installed on the main influent pipeline of the wastewater treatment system, with a sampling frequency of once per minute, and the output data format is "cubic meters per hour (m³ / h)"; nitrogen concentration data is collected using an online total nitrogen analyzer installed downstream of the influent pipeline, with a sampling frequency synchronized with the flow rate, and the output data format is "milligrams per liter (mg / L)"; the internal circulation reflux ratio is equal to the internal circulation reflux flow rate divided by the influent flow rate. The internal circulation reflux flow rate is collected using an electromagnetic flow meter installed on the outlet pipeline of the internal circulation pump, with a sampling frequency of once per minute. Combined with the concurrent influent flow rate, the internal circulation reflux ratio is calculated by dividing the reflux flow rate by the influent flow rate. All collected data is transmitted to a time-series database in real time and stored in a structured format of "timestamp-data type-value".

[0050] Based on the obtained influent flow rate and nitrogen concentration data, the temporal correlation between the two was analyzed, and three types of quantifiable water quality fluctuation characteristic parameters were extracted, including fluctuation amplitude (reflecting the degree of water quality change) and fluctuation frequency (reflecting the frequency of water quality instability). The fluctuation amplitude can be obtained by taking the nitrogen concentration in the influent flow rate over a continuous 10-minute period and calculating the difference between the maximum and minimum values. The fluctuation frequency can be counted by counting the number of times the nitrogen concentration fluctuation amplitude exceeds 5% of the average value within 1 hour. The parameters are integrated into a set of characteristic parameters to obtain the characteristic parameters.

[0051] Data analysis of at least 1000 sets of normal operation data collected over the past three months showed that adopting the 95th percentile of nitrogen concentration fluctuation as the threshold significantly reduced the system's false positive and false negative rates to an acceptable range. Specifically, the threshold was set at the 95th percentile of characteristic parameters when there were no water quality anomalies. The nitrogen concentration fluctuation threshold was 10 mg / L (95% of normal data fluctuations are ≤10 mg / L, and can be calibrated based on actual historical data to adapt to specific water quality), and the fluctuation frequency threshold was 5 times / hour. The set of characteristic parameters was compared with the preset characteristic thresholds. If all parameters did not exceed the thresholds, the pollutant load was directly calculated based on the average flow rate plus the average nitrogen concentration. If any characteristic parameter exceeded the threshold, the water quality fluctuation was determined to be outside the normal range, requiring further analysis of the pollutant distribution characteristics. A convolutional neural network (CNN) algorithm was used to analyze the spatiotemporal distribution of water quality fluctuations. The CNN input data was a time-series matrix, which could be used to construct a two-dimensional feature map through a sliding window.

[0052] The convolutional neural network model adopts a lightweight architecture. The input layer receives a temporal data matrix. Convolutional layer 1 (Conv1) extracts the concentration peak region in the time dimension. Pooling layer 1 (MaxPool1) compresses the time dimension while retaining peak features. Convolutional layer 2 (Conv2) associates the temporal peak with spatial location. Pooling layer 2 (AvgPool2) outputs spatial distribution features. Fully connected layer (FC) quantifies spatial distribution characteristics. The time granularity is 1 minute. The convolutional kernel size is 3×1 (Conv1) and 5×1 (Conv2). The network has 2 convolutional layers and 2 pooling layers. The ReLU function is used for activation. The model extracts nearly 24 hours of "influent flow rate - nitrogen concentration" time-series data (time granularity 1 minute) and arranges it according to the "time axis (x-axis)". A two-dimensional data matrix is ​​constructed using the "numerical (y-axis)" method; the structural parameters of the denitrification tank (e.g., tank length 10m, divided into 5 compartments) are simultaneously imported; the first layer of convolution extracts the concentration peak region in the time dimension (e.g., identifying nitrogen concentration consistently above 40mg / L from 8:00 to 8:30); the second layer of convolution combines the water flow residence time and maps it to the spatial location of the denitrification tank (e.g., high concentration of influent at 8:00, reaching the 3rd compartment of the tank at 8:20); the output results show the pollutant distribution characteristics in the denitrification stage (e.g., the pollutant concentration is highest in the first 1-2 compartments (0-4m) of the denitrification tank, with an average of 42mg / L; the concentration gradually decreases in the last 3-5 compartments (4-10m), with an average of 32mg / L, showing a "high at the front and low at the back" distribution characteristic).

[0053] Based on the characteristics of pollutant distribution, the regional flow rate of each area is calculated. The flow rate of each cell is equal to the influent flow rate. The regional load is equal to the regional flow rate multiplied by the regional concentration multiplied by the unit conversion factor (set as 0.001, 1mg / L=0.001kg / m³). The total load is equal to the sum of the loads of each area.

[0054] In step S12, the step of analyzing the dynamic coupling relationship between the internal circulation reflux ratio and the amount of carbon source to be added based on the pollutant load level to obtain a carbon source demand matching value includes:

[0055] Based on the pollutant load level, the dynamic coupling relationship between carbon source addition and internal circulation reflux ratio is analyzed to obtain the characteristics of the dynamic coupling relationship.

[0056] The carbon source dosage is calculated based on the dynamic coupling relationship characteristics to obtain a preliminary carbon source dosage adjustment value;

[0057] If the initial carbon source dosage adjustment value exceeds the preset adjustment value threshold, the influent flow rate and nitrogen concentration data are updated, and the carbon source dosage is recalculated to obtain the corrected carbon source dosage adjustment value.

[0058] Based on the adjusted carbon source dosage, control parameters matching the internal circulation reflux ratio are calculated to obtain the carbon source demand matching value.

[0059] It should be noted that the principle of denitrification is to use carbon source (electron donor) and nitrate (electron acceptor) to replace nitrogen. The internal circulation reflux ratio determines the amount of nitrate supplied. The higher the reflux ratio, the more nitrate produced in the aerobic tank is returned to the denitrification tank (e.g., when the reflux ratio is 200%, the amount of nitrate returned is twice that of the influent). The amount of carbon source added determines the upper limit of the reaction rate. Insufficient carbon source will limit the denitrification efficiency (nitrate cannot be completely degraded), while excessive carbon source will lead to COD residue (secondary pollution).

[0060] The dynamic coupling relationship between the two is as follows: an increase in the reflux ratio leads to an increase in nitrates, which in turn increases the demand for carbon sources; a decrease in the reflux ratio leads to a decrease in nitrates, which in turn reduces the demand for carbon sources. Using the pollutant load level as input, combined with real-time data on the internal circulation reflux ratio, the analysis is performed using a least squares linear regression algorithm. The input data includes the internal circulation reflux ratio of the past hour (e.g., 150%, 200%, 250%) and the corresponding carbon source dosage (e.g., 190 kg / h, 240 kg / h, 290 kg / h), as well as the pollutant load during the same period (38 kg total nitrogen / h). ; Calculate the change in carbon source dosage (i.e., coupling coefficient) when the reflux ratio changes by 10%. For example, if the reflux ratio increases from 150% to 200% (+50%) and the carbon source dosage increases from 190 kg / h to 240 kg / h (+50 kg / h), then the coupling coefficient = 50 kg / h ÷ 50% = 1 kg / (h·%). The output shows the dynamic coupling relationship characteristics, represented by "coupling coefficient and optimal C / N ratio" (e.g., coupling coefficient 1 kg / (h·%), optimal C / N ratio 5:1, that is, 5 kg of carbon source is required to degrade 1 kg of nitrogen).

[0061] The initial carbon source dosage adjustment value equals the pollutant load level multiplied by the optimal C / N ratio plus (current recirculation ratio minus baseline recirculation ratio) multiplied by the coupling coefficient. The baseline recirculation ratio is defaulted to 200% (based on analysis of 1000 sets of historical data, in conventional wastewater, the total nitrogen concentration in the influent is approximately 20-40 mg / L. After nitrification in the aerobic tank, the nitrate production is approximately 80%-90% of the total nitrogen in the influent. Data shows that when the recirculation ratio is 200%, the total nitrate returned to the denitrification tank (including influent and recirculation supplementation) can meet more than 90% of the denitrification demand (denitrification efficiency reaches 85%-90%). If the recirculation ratio is below 150%, the nitrate supply is insufficient, and the denitrification efficiency will drop below 70%). The initial carbon source dosage reflects the amount of carbon source required to degrade the pollutant load at the current recirculation ratio, including both the basic requirement (pollutant load multiplied by C / N) and the compensation amount due to the recirculation ratio deviating from the baseline value (recirculation ratio deviation multiplied by the coupling coefficient).

[0062] The threshold setting is based on the upper limit of carbon source tolerance of the denitrification tank (to avoid excessive COD residue, such as a threshold of 280 kg / h). If the initial adjustment value does not exceed the threshold, the value is directly used. If the initial adjustment value exceeds the threshold (e.g., 320 kg / h > 300 kg / h), the data is updated by re-collecting the influent flow rate (e.g., decreasing from 1000 m³ / h to 950 m³ / h) and nitrogen concentration (e.g., decreasing from 40 mg / L to 38 mg / L) for the past 10 minutes, and updating the pollutant load level (950 × 38 ÷ 1000 = 36.1 kg / h). Based on the new load (36.1 kg / h) and the current reflux ratio (250%), the carbon source dosage is recalculated. The corrected carbon source dosage adjustment value (230.5 kg / h) is output. The carbon source demand matching value is a quantified indicator of the compatibility between the "corrected carbon source dosage" and the "current internal circulation reflux ratio," reflecting whether the two are in an optimal synergistic state (the closer the value is to 1, the higher the matching degree). The carbon source demand matching value equals the corrected carbon source dosage divided by the total theoretical carbon source demand. The total theoretical carbon source demand can be calculated by multiplying the sum of the nitrate amount brought in by the influent and the nitrate amount brought in by the internal circulation reflux by the optimal C / N ratio. The nitrate amount brought in by the influent equals the pollutant load multiplied by the nitrification rate. The nitrate amount brought in by the internal circulation reflux equals the reflux flow rate multiplied by the nitrate concentration in the aerobic tank effluent divided by 1000. The nitrate concentration in the aerobic tank effluent equals the influent nitrogen concentration multiplied by the nitrification rate. The nitrification rate is the ratio of the nitrate nitrogen generated in the aerobic tank to the total nitrogen in the influent, reflecting the aerobic tank's ability to convert nitrifiable components in the total nitrogen in the influent into nitrate.

[0063] In step S13, if the carbon source demand matching value exceeds a preset matching value threshold, the risk of control lag under water quality fluctuation trends is predicted, and an internal circulation reflux ratio adjustment scheme is obtained, including:

[0064] If the carbon source demand matching value exceeds the preset matching value threshold, the water quality fluctuation trend is predicted based on the influent flow rate and the nitrogen concentration data to obtain the predicted value;

[0065] If the predicted value exceeds the preset predicted value threshold, the control lag risk characteristics under the water quality fluctuation trend are predicted, and the quantitative value of the control lag risk is obtained.

[0066] The internal circulation reflux ratio is adjusted based on the quantified value of the aforementioned regulatory lag risk to obtain an internal circulation reflux ratio adjustment scheme.

[0067] It should be noted that the matching threshold is usually set to 1.5, which corresponds to the carbon source demand exceeding the baseline state by 50%. Experimental data shows that when it exceeds the baseline state by 50%, the synergistic relationship between the carbon source and the reflux ratio is seriously unbalanced (such as the carbon source demand surging due to an excessively high reflux ratio, or insufficient carbon source addition capacity). The data of "influent flow rate (m³ / h)" and "nitrogen concentration (mg / L)" for the past 48 hours (time granularity of 5 minutes) were extracted from the time series database, including historical fluctuation characteristics (such as sudden increases in flow rate during the morning peak and periodic impacts of industrial wastewater).

[0068] A Long Short-Term Memory (LSTM) network was used to standardize flow rate data (range 0-1) and nitrogen concentration (range 0-1) to eliminate the influence of dimensions. The LSTM was trained with historical data from the past 6 months (including normal and abnormal operating conditions). The input was "data from the previous 24 hours", and the output was "predicted values ​​every 10 minutes for the next 2 hours". The final output was "predicted water quality fluctuation trend", which included "flow rate prediction curve" and "nitrogen concentration prediction curve" for the next 2 hours (e.g., predicting that the nitrogen concentration will increase from 40 mg / L to 55 mg / L and the flow rate will increase from 1000 m³ / h to 1200 m³ / h after 1 hour).

[0069] The Long Short-Term Memory (LSTM) network receives standardized time-series data of "influent flow rate - nitrogen concentration" at its input layer. The standardization layer normalizes the flow rate and nitrogen concentration to 0-1. The LSTM layer (core layer) captures the long-term dependencies of water quality fluctuations. The fully connected layer (FC) outputs the predicted values ​​for the next 2 hours. The output layer denormalizes the data and outputs the actual physical values. The time granularity is 5 minutes, the historical dependency length is 48 hours, the number of LSTM neurons per layer is 64, the dropout is 0.2, and the prediction duration is 2 hours. Historical data from the past 6 months is collected, split into 5-minute granularities, and the flow rate and nitrogen concentration from the previous 48 hours are input. The measured values ​​from the SCADA system are directly used as labels (actual values ​​of flow rate and nitrogen concentration). The optimizer is Adam (learning rate 0.001). The loss function is MSE (mean squared error, adapted to regression tasks). The network iterates for 100 rounds (with an early stopping mechanism; if the validation set error does not decrease after 3 rounds), ensuring that the flow rate prediction error is ≤8% and the nitrogen concentration prediction error is ≤10%.

[0070] It should be noted that the prediction of water quality fluctuation trends can be achieved using a Long Short-Term Memory (LSTM) network model, or using the moving average method, exponential smoothing method, or autoregressive integral moving average (ARIMA) model known in the art.

[0071] The threshold values ​​should be set to the maximum water quality fluctuation range that the denitrification tank can withstand. Based on experimental data, the predicted nitrogen concentration threshold is determined to be 50 mg / L (exceeding this value will inhibit the activity of denitrifying bacteria due to excessively high substrate concentration); the predicted flow rate threshold is 1300 m³ / h (exceeding this value will result in a hydraulic retention time of less than 8 hours, affecting the sufficiency of the reaction). When the predicted value exceeds the threshold (e.g., predicted nitrogen concentration 55 mg / L > 50 mg / L), the risk of control lag needs to be analyzed. Control lag risk refers to the possibility and extent of continued water quality deterioration within the time difference between adjusting the internal circulation reflux ratio and the actual improvement in water quality. It includes three characteristics: lag time, deterioration magnitude, and fluctuation frequency. The lag time is the time required for water quality to reach the standard (e.g., nitrogen concentration ≤ 30 mg / L) after adjusting the reflux ratio; the deterioration magnitude is the maximum possible increase in nitrogen concentration within the lag time; and the fluctuation frequency is the number of times water quality exceeds the standard during the lag period.

[0072] The above features were converted into quantitative values ​​of 0-1 (1 being the highest risk). The feature weights were allocated as follows: lag time weight 0.4 (denitrifying bacteria have a time threshold for tolerance to water quality deterioration; after this time, microbial activity will irreversibly decline. Analysis of 1000 sets of historical data extracted from a time series database showed that 45% of effluent exceeding standards was caused by "excessive lag time," hence the second highest weight of 0.4); deterioration magnitude weight 0.4 (the greater the deterioration magnitude, the more severe the damage to microorganisms and the higher the subsequent treatment cost. Experiments showed that for every 5 mg / L increase in deterioration magnitude, the subsequent repair cost increased by 20%, and data analysis showed that 38% of historical failures were caused by exceeding the deterioration magnitude limit, hence the weight of 0.4); and fluctuation frequency weight 0.2 (the higher the frequency, the more unstable the water quality; high frequency will cause microorganisms to be repeatedly impacted, but compared to the previous two items, its instantaneous damage to the system is smaller. Data analysis showed that only 12% of historical failures were mainly caused by high-frequency fluctuations, hence the lower weight of 0.2).

[0073] Risk coefficients for three types of characteristics were calculated, and the characteristic value intervals were divided as follows: a lag time of less than 20 minutes was considered a safe interval, 21-30 minutes a warning interval, and greater than 30 minutes a dangerous interval; a deterioration range of less than 5 mg / L was considered a safe interval, 6-8 mg / L a warning interval, and greater than 8 mg / L a dangerous interval; and a fluctuation frequency of less than 1 time / hour was considered a safe interval, 2 times / hour a warning interval, and greater than 3 times / hour a dangerous interval. The relationship between characteristic value intervals and risk coefficients was analyzed using historical data from the past 6 months. When the lag time was <20 minutes, the deterioration range <5 mg / L, and the fluctuation frequency <1 time / hour, the probability of exceeding the standard in historical operating conditions was ≤8%, corresponding to a risk coefficient of 0.1 (low risk); when the characteristic value was in the warning interval, the historical probability of exceeding the standard rose to 30%-40%, corresponding to a risk coefficient of 0.5 (medium risk); and when the characteristic value entered the dangerous interval, the historical probability of exceeding the standard exceeded 60%, corresponding to a risk coefficient of 0.9 (high risk). The quantified value is equal to the sum of the risk coefficients of the corresponding characteristics multiplied by their weights.

[0074] Based on the risk quantification value, a tiered adjustment method is used to determine the reflux ratio adjustment value. The higher the risk, the larger the adjustment, but it cannot exceed the equipment limit. If the quantification value of the control lag risk is between 0.1 and 0.3 (low risk), the reflux ratio adjustment (relative to the current value) is +10%; if the quantification value of the control lag risk is between 0.4 and 0.6 (medium risk), the reflux ratio adjustment (relative to the current value) is +20%; and if the quantification value of the control lag risk is between 0.7 and 1.0 (high risk), the reflux ratio adjustment (relative to the current value) is +30%. The final output is the internal circulation reflux ratio adjustment scheme.

[0075] In step S14, the step of simulating the denitrification reaction process according to the internal circulation reflux ratio adjustment scheme, determining the coefficient of carbon source dosage, and obtaining the real-time correction coefficient includes:

[0076] Obtain environmental parameter data;

[0077] The environmental parameter data, influent flow rate, and nitrogen concentration data are standardized to obtain the first dataset;

[0078] If the nitrogen concentration data in the first dataset exceeds the preset concentration threshold, the reaction rate is calculated based on the environmental parameter data in the first dataset to obtain the real-time rate value of the denitrification reaction.

[0079] Based on the real-time rate value, the internal circulation reflux ratio adjustment scheme is optimized to obtain the optimized carbon source dosage parameters;

[0080] The dosage is fine-tuned based on the optimized carbon source dosage parameters to obtain a real-time correction coefficient.

[0081] It should be noted that the denitrification reaction rate is significantly affected by environmental factors (such as temperature and pH, which directly affect microbial activity). Key environmental parameters need to be collected, including the denitrification tank water temperature, mixed liquor pH, and dissolved oxygen (DO) collected via a sensor matrix at a frequency of 5 minutes per measurement. All parameters are transmitted to the central control system in real time, stored in the format of "timestamp-parameter name-value". The environmental parameter data, influent flow rate, and nitrogen concentration data are integrated into the first dataset and standardized to unify the dimensions of different parameters. The minimum and maximum values ​​of each parameter can be determined based on three months of historical normal operation data. The standardized value of each parameter is equal to the difference between the original value and the minimum value divided by the difference between the maximum value and the minimum value, thus obtaining the first dataset.

[0082] The preset concentration threshold is the safety control value at the denitrification tank outlet. Nitrogen concentration data at the denitrification tank outlet during normal operation over the past 6 months were statistically analyzed to determine the stable operating range of the denitrification tank. The 95th percentile value was taken as the threshold, set at 12 mg / L. If the standardized nitrogen concentration value in the first dataset corresponds to an actual concentration greater than the threshold, the real-time reaction rate needs to be calculated to analyze the reaction bottleneck. The denitrification reaction rate is affected by both environmental parameters and nitrogen concentration. The real-time rate value (kg / (m³·h)) equals the base rate multiplied by the environmental parameter adaptation coefficient plus the base rate multiplied by the nitrogen concentration adaptation coefficient. The base rate is the standard rate at 20℃, pH 7.5, and DO=0 (set to 0.00). The rate is 5 kg / (m³·h). Samples meeting the standard conditions (20±1℃, pH7.5±0.2, DO≤0.2mg / L) can be selected from historical operating data. The single-group rate (kg / (m³·h)) for the sample is calculated as (influent nitrogen concentration minus effluent nitrogen concentration) multiplied by the influent flow rate divided by the effective volume of the denitrification tank divided by the reaction time. The "arithmetic mean" of the selected sample rates (excluding the 10% highest and 10% lowest values ​​to avoid the influence of extreme values) is used to obtain the base rate. The real-time rate calculation model can adopt a more complex kinetic model (such as the Monod equation) according to the specific wastewater characteristics. This embodiment provides a simplified version to ensure real-time performance.

[0083] The environmental parameter fit coefficient and nitrogen concentration fit coefficient can be calculated in segments. When the temperature is 19-21℃, the pH is between 7.3-7.7, and DO ≤ 0.2 mg / L, the environmental parameter fit coefficient is set to 1.0 (this range is the definition source of the standard operating conditions and is also the operating range with the highest nitrogen removal efficiency (85%-90%) in historical data. Denitrifying bacteria are facultative anaerobic bacteria. When DO ≤ 0.2 mg / L, there is no oxygen competition, the rate is the highest, and it is the ideal range for nitrogen removal. The environmental parameters match the basic rate screening conditions, the rate has no decay, and the process stability is optimal). When the temperature is 15-19℃ or 21-25℃, and the pH is between 7.3-7.7, and the DO is ≤ 0.2 mg / L, the environmental parameter fit coefficient is set to 1.0 (this range is the ideal range for nitrogen removal, where environmental parameters match the basic rate screening conditions, the rate has no decay, and the process stability is optimal). With pH at 7.0-7.3 or 7.7-8.0 and DO at 0.2-0.5 mg / L, and an environmental parameter fit coefficient of 0.7 (statistical analysis of 1200 sets of operational data shows that under 90% of normal operating conditions, the temperature falls between 15-25℃ and the pH falls between 7.0-8.0. At DO of 0.2-0.5 mg / L, denitrifying bacteria compete with aerobic bacteria for substrate. After removing the ideal range of 19-21℃, the remaining range is close to the ideal range, with slight deviations in environmental parameters and a 30% decrease in the rate compared to the ideal range, indicating good process stability), the following conditions apply: temperature <15℃ or >25℃, pH <7.0 or >8.0. When DO > 0.5 mg / L, the environmental parameter fit coefficient is set to 0.4 (statistical data from 1200 operating groups show that denitrification efficiency drops sharply when DO > 0.5 mg / L, with nitrogen removal efficiency < 70% in this range, environmental parameters deviating significantly, rate decreasing by 60% compared to the ideal range, and poor process stability); when nitrogen concentration is within the safe range, the nitrogen concentration fit coefficient is set to 0.5 (in this range, nitrogen concentration does not exceed the threshold, there is no substrate limitation, rate increases linearly with concentration, concentration contributes the most to rate, and the rate growth slope corresponds to a coefficient of 0.5); when nitrogen concentration is within the warning range, the nitrogen concentration fit coefficient is set to 0.3 (when nitrogen concentration exceeds the threshold). When the substrate is close to saturation, the rate increase slows down, and the contribution of concentration to the rate drops to 60% of the safe range. The rate increase slope in this range is 60% of the safe range, so the coefficient is 0.5 multiplied by 60% equals 0.3. When the nitrogen concentration is in the danger range, the nitrogen concentration fit coefficient is 0.1 (when the nitrogen concentration is seriously over the threshold, the substrate is completely saturated, the rate tends to stabilize, and the contribution of concentration to the rate drops to 20% of the safe range. Historical data shows that for every 1 mg / L increase in concentration, the rate only increases by 0.00008 kg / (m³·h), which is 20% of the safe range. Therefore, 20% of 0.5 is taken, so the coefficient is 0.1).

[0084] Based on the deviation between the real-time rate value and the target rate value, the reflux ratio adjustment scheme output in step S13 is optimized, and the optimized carbon source dosage parameters are obtained simultaneously. If the deviation between the real-time rate value and the target value is less than -20% (rate is too low), then for every 20% decrease in the deviation between the real-time rate value and the target value relative to -20%, the internal circulation reflux ratio is increased by 10% (to increase nitrate supply), and the carbon source dosage is increased by 15% (to supplement carbon source and accelerate reaction). If the deviation between the real-time rate value and the target value is between -20% and +10% (basically meeting the target), then the internal circulation reflux ratio remains unchanged, and the carbon source dosage remains unchanged. If the deviation between the real-time rate value and the target value is greater than +10% (rate is too high), then for every 10% increase in the deviation between the real-time rate value and the target value relative to +10%, the internal circulation reflux ratio is decreased by 5% (to reduce energy consumption), and the carbon source dosage is decreased by 5% (to avoid carbon source waste), thus obtaining the optimized carbon source dosage parameters. The target rate is preset to 0.01 kg / (m³·h). This value is determined based on the actual metabolic capacity of denitrifying bacteria. A large number of experimental data show that under ideal conditions (20-30℃, pH 7.0-8.0, and sufficient carbon source), the maximum daily average metabolic rate of denitrifying bacteria is about 0.3 kg / (m³·d) (equivalent to an hourly rate of 0.012-0.015 kg / (m³·h)). In actual operation, due to factors such as uneven nitrate distribution and insufficient local carbon source, the actual achievable hourly rate is usually 70%-80% of the maximum theoretical value, i.e., 0.0084-0.012 kg / (m³·h). 0.01 kg / (m³·h) is in the middle of this range, which neither exceeds the actual metabolic capacity of the microorganisms nor fails to give full play to the activity of the microorganisms.

[0085] The real-time correction coefficient is the ratio of the optimized carbon source dosage to the theoretical carbon source dosage (the theoretical carbon source dosage equals the pollutant load multiplied by the optimal C / N ratio). It is used to adjust the output of the carbon source dosing system in real time to ensure that the actual dosage dynamically matches the reaction requirements. The correction coefficient is transmitted to the control system of the carbon source dosing pump, and the pump output is automatically adjusted to (theoretical value multiplied by the correction coefficient). Step S14 (re-collecting data → calculating new coefficient) is repeated every 10 minutes to form a closed loop of "real-time monitoring → simulation → correction" (synchronized with the dynamic changes of the denitrification reaction).

[0086] In step S15, the coordinated control parameters are updated according to the real-time correction coefficient to obtain the dosing control signal.

[0087] It should be noted that the coordinated control parameters are the core parameter set that reflects the optimal matching relationship between the internal circulation reflux ratio and the carbon source dosage. It includes three key parameters: optimized carbon source dosage, real-time correction coefficient, and current internal circulation reflux ratio. The real-time correction coefficient is integrated into the original parameter system to form a new linkage relationship and generate an updated parameter set. The actual carbon source dosage is calculated as the baseline carbon source dosage multiplied by the real-time correction coefficient and the reflux ratio adaptation coefficient. The reflux ratio adaptation coefficient can be calculated by multiplying the difference between the reflux ratio and the baseline value by 0.2. It quantifies the degree to which the current internal circulation reflux ratio deviates from the baseline reflux ratio and is used as a coefficient for dynamically compensating for the carbon source dosage. Based on statistics from 1,000 sets of operating data over the past 6 months, with other conditions fixed (such as temperature, pH, and carbon source type), for every 10% increase in the internal circulation reflux ratio, the nitrate supply in the denitrification tank increases by 8%-10%. To maintain the optimal C / N ratio, the carbon source demand needs to increase by 2% simultaneously, so a coefficient of 0.2 is taken. The dosing control signal is to convert the actual carbon source dosage into executable instructions for the carbon source dosing equipment. The updated parameter set is transmitted to the pump control system via Modbus protocol digital signals to obtain the dosing control signal.

[0088] In step S16, a threshold comparison is performed between the dosing control signal and the carbon source demand matching value, and the business correlation between the pollutant load level and the real-time correction coefficient is fused to obtain the optimized matching coefficient.

[0089] It should be noted that the threshold comparison is used to identify whether the current system is in a controllable range. Thresholds need to be set for the two types of parameters and the comparison needs to be performed. The threshold of the dosing control signal is based on the safe operating range of the carbon source dosing equipment and is divided into a lower limit threshold and an upper limit threshold. The lower limit threshold corresponds to the minimum effective dosing amount (e.g., 50 kg / h, below which the carbon source distribution will be uneven and affect the uniformity of denitrification); the upper limit threshold corresponds to the maximum capacity of the equipment (e.g., 300 kg / h, above which the equipment overload protection will be triggered). If the dosing control signal is within the range of [50, 300], it is determined that the signal is normal (marked as 1); if it is lower than 50 kg / h or higher than 300 kg / h, it is determined that the signal is abnormal (marked as 0); using the preset matching value threshold of step S13, if the carbon source demand matching value is less than 1.5, it is determined that the matching is normal (marked as 1); if it is greater than 1.5, it is determined that the matching is abnormal (marked as 0); the output comparison result is represented in the form of a binary tuple [dosing control signal status (1 / 0), carbon source demand matching value status (1 / 0)], such as [1, 1] (both are normal).

[0090] There is a strong operational correlation between pollutant load levels and real-time correction coefficients. Higher loads result in a more significant impact of environmental factors on carbon source demand (e.g., at high loads, a 1°C decrease in temperature may lead to a 5% increase in carbon source demand, while at low loads it may only increase it by 2%). This relationship needs to be quantified using a correlation coefficient calculation formula: correlation coefficient equals 0.6 times (load level divided by baseline load) plus 0.4 times the real-time correction coefficient. The baseline load is the historical average pollutant load, used to standardize the load level (eliminating dimensions). Through parameter impact experiments (based on 1000 sets of operational data from the past 6 months), the influence weights of load levels and correction coefficients on the system's core indicator (denitrification efficiency) are quantified. Single-variable impact tests (using the controlled variable method) are conducted to test the effects of load levels and correction coefficients respectively. The results show that with a fixed correction coefficient of 1.0, increasing the load from 25 kg / h (low load) to... At a load of 35 kg / h (high load), the denitrification efficiency decreased from 90% to 78% (a decrease of 12%), with an efficiency change of approximately 4.8% for every 10% change in load. At a fixed load of 30 kg / h, the denitrification efficiency increased from 82% to 88% (an increase of 6%) when the correction factor increased from 0.9 (low correction) to 1.1 (high correction), with an efficiency change of approximately 3% for every 10% change in the correction factor. The ratio of the impact of load on efficiency (4.8% / 10%) to the correction factor (3% / 10%) is approximately 1.6:1, close to the ratio of 0.6:0.4 (1.5:1), demonstrating that this weighting can reflect the actual difference in impact.

[0091] The optimized matching coefficient is a weighted fusion of the threshold comparison result (system status) and the business correlation (parameter synergy), which quantifies the overall carbon source-recirculation ratio-load-environment synergy level of the system (values ​​range from 0 to 1, with the closer to 1 being better). The optimization matching coefficient is equal to (normal state rate multiplied by 0.3) plus (standardized correlation value multiplied by 0.7); where normal state rate is (addition control signal status plus carbon source demand matching value status) multiplied by 2; the standardized correlation value is the difference between the correlation degree minus the minimum correlation degree divided by the difference between the maximum correlation degree minus the minimum correlation degree; the role of normal state rate is to eliminate abnormal operating conditions. When the addition control signal exceeds the equipment range (e.g., >300kg / h) or the carbon source demand matching value is severely unbalanced (e.g., >1.5), the system is in a dangerous state and should be prioritized for fault handling (e.g., shutdown inspection) rather than optimization; however, under normal conditions (normal state rate = 1.0), its effect on improving optimization accuracy is limited. Statistics from the past year's system failure cases (120 times) show that only 28% of the failures were directly caused by "abnormal state" (e.g., pump overload, matching value exceeding the threshold); 72% of the failures originated from normal state but unbalanced correlation (e.g., insufficient correction coefficient under high load, leading to a sharp drop in denitrification efficiency). Therefore, the weight of normal state rate is set to 0.3, and the weight of standardized correlation value is set to 0.7.

[0092] In step S17, the step of integrating the dynamic coupling relationship of the internal circulation reflux ratio based on the optimized matching coefficient and determining the update magnitude of the coordinated control parameters includes:

[0093] Obtain process stability data;

[0094] The internal circulation reflux ratio, influent flow rate, and nitrogen concentration data were standardized to obtain the second dataset;

[0095] By integrating the nitrogen concentration data in the second dataset with the dynamic changes in the internal circulation reflux ratio, a dynamic coupling coefficient for the reflux ratio is obtained.

[0096] If the dynamic coupling coefficient of the reflux ratio is less than the preset coefficient threshold, the optimized matching coefficient is compared with the process stability data to determine the update magnitude of the collaborative control parameters.

[0097] It should be noted that process stability data is the basis for judging whether the current operating status of the denitrification system is stable. The collected indicators include nitrogen removal efficiency fluctuation (the standard deviation of nitrogen removal efficiency over three consecutive tests, reflecting efficiency stability), frequency of effluent nitrogen concentration exceeding the standard (the number of times the effluent nitrogen concentration is >12 mg / L in the past hour), and internal circulation reflux ratio deviation (the percentage difference between the actual reflux ratio and the set value). The internal circulation reflux ratio, influent flow rate, and nitrogen concentration data are standardized to eliminate dimensional differences. The standardized value is equal to the difference between the original value and the historical minimum value divided by the difference between the historical maximum value and the historical minimum value, in the format of a standardized vector, such as [internal circulation reflux ratio 0.8, influent flow rate 0.5, nitrogen concentration 0.6], resulting in the second dataset.

[0098] The dynamic coupling coefficient of the reflux ratio is used to measure the dynamic response relationship between changes in the internal circulation reflux ratio and changes in nitrogen concentration (e.g., whether the nitrogen concentration decreases as expected after the reflux ratio is adjusted), and to capture the hysteretic synergy between the two (because of the reaction delay, changes in the reflux ratio will not be immediately reflected in the nitrogen concentration). The system response time can be used to measure the response relationship and hysteretic synergy. The system response time refers to the time required for the nitrogen concentration at the outlet of the denitrification tank to drop to the preset target concentration after the internal circulation reflux ratio is adjusted. The time point in the past 2 hours when the reflux ratio change rate is >5% is taken. Starting from the trigger point of the reflux ratio adjustment, the subsequent outlet nitrogen concentration is counted until the concentration is ≤12mg / L. The time required is the system response time. If the target is not met within 2 hours, the system response time is taken as 2 hours (judged as a serious synergistic imbalance). The coupling coefficient is calculated using the system response time. When the system response time is less than 20 and greater than 5 minutes (if T≤5 minutes, it does not exist in actual working conditions and is considered as data anomaly, the default coupling coefficient = 0.7), the coordination is good, and the coupling coefficient can be calculated by dividing 0.6 plus 0.4 by the system response time. When 20 < system response time ≤ 30, there is a slight coordination imbalance, and the coupling coefficient is calculated by dividing 0.4 plus 0.2 by the system response time. When T>30, there is a severe coordination imbalance, and the coupling coefficient can be calculated by dividing 0.4 minus 0.4 by the system response time.

[0099] Analysis of system operation data (1200 sets of effective dynamic coupling coefficients) over the past year revealed that when the coupling coefficient is ≥0.6, 92% of the operating conditions are in a stable state (denitrification efficiency ≥85%, energy consumption ≤0.3kW·h / kg nitrogen); when the coupling coefficient is <0.6, 78% of the operating conditions exhibit "cooperative imbalance" (e.g., increased reflux ratio but no decrease in nitrogen concentration, or denitrification efficiency fluctuation >10%). 0.6 is the boundary between the stable and imbalanced ranges (the lowest value corresponding to 92% stability), conforming to the statistical characteristic of the "lower limit of the 95% confidence interval," therefore, the coefficient threshold was set at 0.6.

[0100] If the coupling coefficient is greater than the threshold, it indicates that the dynamic matching between the reflux ratio and nitrogen concentration is good, and no significant adjustment is needed. If the coupling coefficient is less than the threshold, it indicates that the relationship between the two is unbalanced (e.g., the reflux ratio increases but the nitrogen concentration does not decrease), and the update range needs to be calculated. A stability score (0-1 point, 1 point being the most stable) should be assigned to the indicators in the process stability data. The denitrification efficiency fluctuation score is equal to 1 minus the difference between the actual value and the standard deviation, divided by the standard deviation. The effluent nitrogen concentration exceedance frequency score is equal to 1 minus the difference between the actual number of times and 1, divided by 2 (if less than 0, take 0). The internal circulation reflux ratio execution deviation is equal to 1 minus the actual value and the set value. The difference is divided by the set value, and the average of the above scores is taken to obtain the comprehensive score of process stability. The optimization matching coefficient is compared with the comprehensive score of process stability. When the optimization matching coefficient is less than 0.6 and the process stability score is less than 0.7, the update magnitude of the current collaborative control parameter increases by 10%. When the optimization matching coefficient is between 0.6 and 0.8 and the process stability score is between 0.7 and 0.9, the update magnitude of the current collaborative control parameter increases by 5%. When the optimization matching coefficient is greater than 0.8 and the process stability score is greater than 0.9, the update magnitude of the current collaborative control parameter increases by 10%.

[0101] In step S18, updating the coordinated control parameters according to the update magnitude, obtaining the system's operating status data, and generating instructions to obtain the reflux optimization instructions include:

[0102] The coordinated control parameters are updated according to the update magnitude to obtain the system's operating status data;

[0103] The operating status data and the influent flow rate are standardized to obtain a third dataset;

[0104] By integrating the operational status data and the dynamic changes in influent flow rate in the third dataset, the operational status dynamic coefficient is obtained;

[0105] If the dynamic coefficient of the operating state exceeds the preset operating threshold, the preset demand matching logic is compared with the process stability data to determine the generation conditions of the reflow optimization instruction.

[0106] Adjust the matching relationship between the internal circulation reflux ratio and the nitrogen concentration data according to the generation conditions, and generate instructions to obtain reflux optimization instructions.

[0107] It should be noted that, based on the update magnitude output in step S17, the core coordination parameters are adjusted, and the internal circulation reflux ratio is the current value multiplied by (1 plus the update magnitude); the carbon source dosage is adjusted in conjunction with the reflux ratio (to maintain a stable C / N ratio), and real-time operating data within 10 minutes after the adjustment is acquired simultaneously (reflecting the actual effect after the parameter update). The collected indicators include effluent nitrogen concentration, dissolved oxygen (DO), and residual carbon source (COD). The third dataset contains operating status data and influent flow rate, which need to be standardized and converted into dimensionless values ​​in the 0-1 range. The standardized values ​​of other indicators are equal to the difference between the original value and the historical minimum value divided by the difference between the historical maximum value and the historical minimum value. The format is a standardized vector output of the third dataset, such as [effluent nitrogen concentration 0.53, DO 0.5, COD residual 0.4, influent flow rate 0.5].

[0108] The dynamic coefficient of operating status is used to measure the synergistic adaptability between the system operating status and the changes in influent flow rate after parameter updates, and to capture the actual effect of status improvement after the implementation of control measures. The dynamic coefficient of operating status is the average of the degree of status improvement and the degree of flow adaptability. The degree of status improvement reflects the degree of optimization of the operating status after parameter updates, and is the average of the standardized values ​​of effluent nitrogen concentration, DO, and COD residue in the third dataset. The degree of flow adaptability reflects the degree of matching between the current parameters and the fluctuation of influent flow rate. It can be calculated as the deviation rate between the current standardized value of return ratio and the standardized value of influent flow rate (the smaller the deviation, the higher the adaptability). Specifically, the degree of flow adaptability is equal to 1 minus the absolute value of the difference between the current standardized value of return ratio and the standardized value of influent flow rate.

[0109] By analyzing system operation data from the past year (1500 sets of effective dynamic coefficients) and simulating the failure probability of the system within 12 hours under different dynamic coefficients (denitrification efficiency <80%), it was found that when the dynamic coefficient is 0.7, the failure probability is 2.5% (acceptable risk); when the dynamic coefficient is 0.65, the failure probability is 12% (significantly increased risk); and when the dynamic coefficient is 0.75, the failure probability is 0.8% (risk too low but may lead to insufficient control). The threshold needs to be ≥0.7 to control the failure risk within 5%, so the preset operating threshold is 0.7 (based on historical data, when the coefficient is ≥0.7, the system is in "optimized response state"). If the dynamic coefficient is less than the operating threshold, the instruction generation conditions need to be determined by comparing the preset demand matching logic with the process stability data. The preset demand matching logic is that the internal circulation reflux ratio and nitrogen concentration must satisfy the condition that the standardized value of the reflux ratio is equal to the standardized value of the nitrogen concentration multiplied by 1.2.

[0110] If the process stability score is less than 0.7 and does not meet the demand matching logic (deviation rate greater than 10%), significantly increase the reflux ratio (+15%) and simultaneously increase the carbon source by 10%; if the process stability score is between 0.7 and 0.9 and partially meets the demand matching logic (deviation rate between 5% and 10%), moderately increase the reflux ratio (+8%) and simultaneously increase the carbon source by 5%; if the process stability score is greater than 0.9 and basically meets the demand matching logic (deviation rate less than 5%), finely adjust the reflux ratio (+3%), and keep the carbon source unchanged.

[0111] The matching relationship between the internal circulation reflux ratio and nitrogen concentration is dynamically corrected based on the generation conditions. A correction coefficient is introduced according to the generation conditions (large / medium / fine adjustment) to adjust the matching ratio. That is, the reflux ratio is equal to the nitrogen concentration multiplied by 1.2 multiplied by the correction coefficient, where the correction coefficient is equal to 1.3 minus 0.3 multiplied by the process stability score. According to the Modbus device communication protocol, the verified parameters are converted into standardized instructions to obtain the reflux optimization instructions.

[0112] In step S19, the reflux optimization command is sent to the wastewater treatment system to coordinate the addition of carbon source and the internal circulation reflux ratio, thereby obtaining an efficient denitrification operation.

[0113] It should be noted that the generated reflux optimization command is sent to the wastewater treatment system using the Modbus RTU standard communication protocol. Upon receiving the command, a successful reception confirmation frame must be returned within 10 seconds (containing the actual received parameter values, such as the reflux pump frequency of 46.64Hz and the carbon source dosage of 328.35kg / h). If no confirmation frame is received or the confirmed parameters deviate from the command by more than ±1%, the system will automatically trigger a retry mechanism (up to 3 times, with an interval of 5 seconds each time). If the retry fails, an audible and visual alarm will be triggered immediately. After receiving the feedback confirmation information, the carbon source is added according to the reflux ratio, and the control command is recalculated every hour to adapt to changes in water quality. After the command is executed, key data (effluent nitrogen concentration, DO, and residual COD of carbon source) are collected every 2 minutes for detection and feedback to achieve a highly efficient denitrification operation.

[0114] In summary, this invention analyzes the dynamic coupling relationship between the reflux ratio and carbon source dosage, and combines real-time correction coefficients and optimized matching coefficients to dynamically adjust the synergistic control parameters. This solves the problem in existing technologies where fixed adjustments to the internal circulation reflux ratio and carbon source dosage fail to adapt to dynamic changes in pollutant load, resulting in either excessive carbon source dosage (increasing costs and secondary pollution) or insufficient dosage, leading to incomplete denitrification and low denitrification efficiency. This invention predicts water quality fluctuation trends, quantifies the risk of control lag, and generates internal circulation reflux ratio adjustment schemes in advance; simultaneously, it performs closed-loop optimization based on process stability data; significantly reducing the fluctuation range of denitrification efficiency compared to existing technologies and extending the continuous stable operation time. Unlike existing technologies where carbon source dosage and internal circulation reflux ratio control are independent and lack a synergistic mechanism, this invention achieves deep synergy between the reflux ratio and carbon source dosage through dynamic coupling analysis of the entire process, ensuring that the denitrification reaction is always under optimal conditions and improving the stability of denitrification efficiency.

[0115] Reference Figure 2 The second embodiment of the present invention provides a wastewater treatment system based on internal circulation high-efficiency denitrification technology, comprising:

[0116] The data acquisition module is used to acquire data on internal circulation reflux ratio, influent flow rate and nitrogen concentration, capture water quality fluctuation characteristics based on the influent flow rate and nitrogen concentration data, and determine the pollutant load level based on the water quality fluctuation characteristics.

[0117] The data analysis module is used to analyze the dynamic coupling relationship between the internal circulation reflux ratio and the amount of carbon source to be added based on the pollutant load level, and to obtain the carbon source demand matching value.

[0118] The data prediction module is used to predict the risk of regulation lag under the water quality fluctuation trend if the carbon source demand matching value exceeds the preset matching value threshold, and to obtain the internal circulation reflux ratio adjustment scheme.

[0119] The data simulation module is used to simulate the denitrification reaction process according to the internal circulation reflux ratio adjustment scheme, determine the coefficient of carbon source addition, and obtain the real-time correction coefficient.

[0120] The data update module is used to update the coordinated control parameters according to the real-time correction coefficient to obtain the dosing control signal;

[0121] The data comparison module is used to compare the dosing control signal with the carbon source demand matching value based on a threshold, and to integrate the business correlation between the pollutant load level and the real-time correction coefficient to obtain an optimized matching coefficient.

[0122] The data integration module is used to integrate the dynamic coupling relationship of the internal circulation reflux ratio based on the optimized matching coefficient, and determine the update magnitude of the coordinated control parameters.

[0123] The instruction generation module is used to update the coordinated control parameters according to the update magnitude, obtain the system's operating status data, and generate instructions to obtain the reflux optimization instructions.

[0124] The command control module is used to send the reflux optimization command to the wastewater treatment system to coordinate the carbon source addition and the internal circulation reflux ratio to obtain an efficient denitrification operation.

[0125] It should be noted that the wastewater treatment system based on internal circulation high-efficiency denitrification technology provided in this embodiment of the invention is used to execute all process steps of the wastewater treatment method based on internal circulation high-efficiency denitrification technology in the above embodiment. The working principles and beneficial effects of the two are one-to-one, so they will not be described again.

[0126] This invention also provides an electronic device. The electronic device includes a processor, a memory, and a computer program, such as an algorithm program, stored in the memory and executable on the processor. When the processor executes the computer program, it implements the steps in the various wastewater treatment method embodiments based on internal circulation high-efficiency denitrification nitrogen removal technology described above, for example... Figure 1 The step S11 shown. Alternatively, when the processor executes the computer program, it implements the functions of each module / unit in the above system embodiments, such as the instruction control module.

[0127] For example, the computer program may be divided into one or more modules / units, which are stored in the memory and executed by the processor to complete the present invention. The one or more modules / units may be a series of computer program instruction segments capable of performing a specific function, which describe the execution process of the computer program in the electronic device.

[0128] The electronic device may be a desktop computer, laptop, handheld computer, or smart tablet, etc. The electronic device may include, but is not limited to, a processor and memory. Those skilled in the art will understand that the above components are merely examples of electronic devices and do not constitute a limitation on the electronic device. It may include more or fewer components than described above, or combine certain components, or different components. For example, the electronic device may also include input / output devices, network access devices, buses, etc.

[0129] The processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor can be a microprocessor or any conventional processor. The processor is the control center of the electronic device, connecting all parts of the electronic device via various interfaces and lines.

[0130] The memory can be used to store the computer programs and / or modules. The processor implements various functions of the electronic device by running or executing the computer programs and / or modules stored in the memory and by calling data stored in the memory. The memory may mainly include a program storage area and a data storage area. The program storage area may store the operating system, at least one application program required for a function (such as sound playback function, image playback function, etc.), etc.; the data storage area may store data created according to the use of the mobile phone (such as audio data, phonebook, etc.). In addition, the memory may include high-speed random access memory, and may also include non-volatile memory, such as hard disk, memory, plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, at least one disk storage device, flash memory device, or other volatile solid-state storage device.

[0131] If the modules / units integrated into the electronic device are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the methods of the above embodiments of the present invention can also be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include: any entity or system capable of carrying the computer program code, recording media, USB flash drives, portable hard drives, magnetic disks, optical disks, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signals, telecommunication signals, and software distribution media, etc. It should be noted that the content included in the computer-readable medium can be appropriately added or removed according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, computer-readable media do not include electrical carrier signals and telecommunication signals.

[0132] It should be noted that the system embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Furthermore, in the accompanying drawings of the system embodiments provided by this invention, the connection relationships between modules indicate that they have communication connections, which can be specifically implemented as one or more communication buses or signal lines. Those skilled in the art can understand and implement this without any creative effort.

[0133] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above descriptions are merely specific embodiments of the present invention and are not intended to limit the scope of protection of the present invention. In particular, it should be noted that any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention for those skilled in the art.

Claims

1. A wastewater treatment method based on internal circulation high-efficiency denitrification nitrogen removal technology, characterized in that, include: The internal circulation reflux ratio, influent flow rate and nitrogen concentration data are obtained. Water quality fluctuation characteristics are captured based on the influent flow rate and nitrogen concentration data. The pollutant load level is determined based on the water quality fluctuation characteristics. Based on the pollutant load level, the dynamic coupling relationship between the internal circulation reflux ratio and the amount of carbon source to be added is analyzed to obtain the carbon source demand matching value. If the carbon source demand matching value exceeds the preset matching value threshold, the risk of regulation lag under the water quality fluctuation trend is predicted, and an internal circulation reflux ratio adjustment scheme is obtained. Based on the internal circulation reflux ratio adjustment scheme, the denitrification reaction process is simulated, the coefficient of carbon source addition is determined, and the real-time correction coefficient is obtained. The coordinated control parameters are updated based on the real-time correction coefficients to obtain the dosing control signal; The optimal matching coefficient is obtained by comparing the dosing control signal with the carbon source demand matching value and integrating the business correlation between the pollutant load level and the real-time correction coefficient. Based on the optimized matching coefficient, the dynamic coupling relationship of the internal circulation reflux ratio is integrated to determine the update magnitude of the coordinated control parameters; The coordinated control parameters are updated according to the update magnitude, the system's operating status data is obtained, and instructions are generated to obtain the reflux optimization instructions. The reflux optimization command is sent to the wastewater treatment system to coordinate the addition of carbon source and the internal circulation reflux ratio, thereby achieving a highly efficient denitrification operation.

2. The wastewater treatment method based on internal circulation high-efficiency denitrification nitrogen removal technology according to claim 1, characterized in that, The process of acquiring internal circulation reflux ratio, influent flow rate, and nitrogen concentration data, capturing water quality fluctuation characteristics based on the influent flow rate and nitrogen concentration data, and determining the pollutant load level based on the water quality fluctuation characteristics includes: Based on the influent flow rate and nitrogen concentration data, the water quality fluctuation characteristics are analyzed to obtain the characteristic parameters of water quality fluctuation. If the characteristic parameter exceeds the preset characteristic threshold, the water quality fluctuation characteristic distribution is analyzed to obtain the pollutant distribution characteristics of the denitrification stage; The pollutant load is calculated based on the pollutant distribution characteristics to obtain the pollutant load level.

3. The wastewater treatment method based on internal circulation high-efficiency denitrification nitrogen removal technology according to claim 1, characterized in that, The step of analyzing the dynamic coupling relationship between the internal circulation reflux ratio and the required amount of carbon source based on the pollutant load level to obtain a carbon source demand matching value includes: Based on the pollutant load level, the dynamic coupling relationship between carbon source addition and internal circulation reflux ratio is analyzed to obtain the characteristics of the dynamic coupling relationship. The carbon source dosage is calculated based on the dynamic coupling relationship characteristics to obtain a preliminary carbon source dosage adjustment value; If the initial carbon source dosage adjustment value exceeds the preset adjustment value threshold, the influent flow rate and nitrogen concentration data are updated, and the carbon source dosage is recalculated to obtain the corrected carbon source dosage adjustment value. Based on the adjusted carbon source dosage, control parameters matching the internal circulation reflux ratio are calculated to obtain the carbon source demand matching value.

4. The wastewater treatment method based on internal circulation high-efficiency denitrification nitrogen removal technology according to claim 1, characterized in that, The process of simulating the denitrification reaction according to the internal circulation reflux ratio adjustment scheme, determining the coefficient of carbon source addition, and obtaining the real-time correction coefficient includes: Obtain environmental parameter data; The environmental parameter data, influent flow rate, and nitrogen concentration data are standardized to obtain the first dataset; If the nitrogen concentration data in the first dataset exceeds the preset concentration threshold, the reaction rate is calculated based on the environmental parameter data in the first dataset to obtain the real-time rate value of the denitrification reaction. Based on the real-time rate value, the internal circulation reflux ratio adjustment scheme is optimized to obtain the optimized carbon source dosage parameters; The dosage is fine-tuned based on the optimized carbon source dosage parameters to obtain a real-time correction coefficient.

5. The wastewater treatment method based on internal circulation high-efficiency denitrification nitrogen removal technology according to claim 1, characterized in that, The step of integrating the dynamic coupling relationship of the internal circulation reflux ratio based on the optimized matching coefficient and determining the update magnitude of the coordinated control parameters includes: Obtain process stability data; The internal circulation reflux ratio, influent flow rate, and nitrogen concentration data were standardized to obtain the second dataset; By integrating the nitrogen concentration data in the second dataset with the dynamic changes in the internal circulation reflux ratio, a dynamic coupling coefficient for the reflux ratio is obtained. If the dynamic coupling coefficient of the reflux ratio is less than the preset coefficient threshold, the optimized matching coefficient is compared with the process stability data to determine the update magnitude of the collaborative control parameters.

6. The wastewater treatment method based on internal circulation high-efficiency denitrification technology according to claim 5, characterized in that, The step of updating the coordinated control parameters according to the update magnitude, obtaining the system's operating status data, and generating instructions to obtain the reflux optimization instructions includes: The coordinated control parameters are updated according to the update magnitude to obtain the system's operating status data; The operating status data and the influent flow rate are standardized to obtain a third dataset; By integrating the operational status data and the dynamic changes in influent flow rate in the third dataset, the operational status dynamic coefficient is obtained; If the dynamic coefficient of the operating state exceeds the preset operating threshold, the preset demand matching logic is compared with the process stability data to determine the generation conditions of the reflow optimization instruction. Adjust the matching relationship between the internal circulation reflux ratio and the nitrogen concentration data according to the generation conditions, and generate instructions to obtain reflux optimization instructions.

7. The wastewater treatment method based on internal circulation high-efficiency denitrification nitrogen removal technology according to claim 1, characterized in that, If the carbon source demand matching value exceeds a preset matching value threshold, the risk of control lag under water quality fluctuation trends is predicted, and an internal circulation reflux ratio adjustment scheme is obtained, including: If the carbon source demand matching value exceeds the preset matching value threshold, the water quality fluctuation trend is predicted based on the influent flow rate and the nitrogen concentration data to obtain the predicted value; If the predicted value exceeds the preset predicted value threshold, the control lag risk characteristics under the water quality fluctuation trend are predicted, and the quantitative value of the control lag risk is obtained. The internal circulation reflux ratio is adjusted based on the quantified value of the aforementioned regulatory lag risk to obtain an internal circulation reflux ratio adjustment scheme.

8. A wastewater treatment system based on internal circulation high-efficiency denitrification nitrogen removal technology, characterized in that, include: The data acquisition module is used to acquire data on internal circulation reflux ratio, influent flow rate and nitrogen concentration, capture water quality fluctuation characteristics based on the influent flow rate and nitrogen concentration data, and determine the pollutant load level based on the water quality fluctuation characteristics. The data analysis module is used to analyze the dynamic coupling relationship between the internal circulation reflux ratio and the amount of carbon source to be added based on the pollutant load level, and to obtain the carbon source demand matching value. The data prediction module is used to predict the risk of regulation lag under the water quality fluctuation trend if the carbon source demand matching value exceeds the preset matching value threshold, and to obtain the internal circulation reflux ratio adjustment scheme. The data simulation module is used to simulate the denitrification reaction process according to the internal circulation reflux ratio adjustment scheme, determine the coefficient of carbon source addition, and obtain the real-time correction coefficient. The data update module is used to update the coordinated control parameters according to the real-time correction coefficient to obtain the dosing control signal; The data comparison module is used to compare the dosing control signal with the carbon source demand matching value based on a threshold, and to integrate the business correlation between the pollutant load level and the real-time correction coefficient to obtain an optimized matching coefficient. The data integration module is used to integrate the dynamic coupling relationship of the internal circulation reflux ratio based on the optimized matching coefficient, and determine the update magnitude of the coordinated control parameters. The instruction generation module is used to update the coordinated control parameters according to the update magnitude, obtain the system's operating status data, and generate instructions to obtain the reflux optimization instructions. The command control module is used to send the reflux optimization command to the wastewater treatment system to coordinate the carbon source addition and the internal circulation reflux ratio to obtain an efficient denitrification operation.

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