Sewage treatment method and system based on internal circulation efficient denitrification nitrogen removal technology

Abstract

The invention relates to the technical field of sewage treatment, and discloses a sewage treatment method and system based on an internal circulation efficient denitrification technology, and the method comprises the following steps: obtaining a reflux ratio, water inlet flow and nitrogen concentration, capturing water quality fluctuation through the flow and the nitrogen concentration, and judging a load level; and analyzing the coupling relationship between the reflux ratio and the added carbon source amount by combining the load level to obtain a carbon source demand matching value. If the matching value exceeds the threshold value, predicting a lag risk, and generating a reflux ratio adjustment scheme; and simulating a denitrification reaction process of the scheme, determining a correction coefficient, and updating regulation and control parameters to obtain an addition control signal. Performing threshold comparison on the signal and the matching value, fusing business association of the load level and the correction coefficient, and calculating the matching coefficient; and based on the coefficient integration reflux ratio coupling relationship, judging a parameter updating amplitude, obtaining system operation state data after updating, and generating an instruction. And sending the instruction to a sewage treatment system, and carrying out efficient denitrification operation. The method can solve the problem of low denitrification efficiency.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of sewage treatment, and in particular to a sewage treatment method and system based on an internal circulation high-efficiency denitrification technology. BACKGROUND

[0002] At present, sewage treatment is an important field of environmental protection and resource recycling, and is directly related to the sustainable development of water resources and ecological balance. Especially in the process of urbanization and industrialization, sewage treatment technology needs to efficiently remove nitrogen pollutants to prevent water eutrophication and ecological system destruction. Denitrification as a core technology can convert nitrate into nitrogen gas, reducing water pollution.

[0003] In one prior art, the carbon source dosage of the denitrification tank is realized by a fixed flow pump, and the dosage is set according to the average influent nitrogen concentration in the design stage, and is not adjusted during operation; the internal circulation reflux ratio (the flow ratio of the mixed liquid of the denitrification tank to the aerobic tank) is fixedly adjusted to 1:3 (reflux flow: influent flow) by a manual valve, and is only adjusted by the operation and maintenance personnel according to historical data during quarterly maintenance.

[0004] However, in the face of influent water quality fluctuations, the fixed carbon source dosage cannot meet the denitrification demand, resulting in the accumulation of nitrate in the denitrification tank and a sharp decrease in denitrification efficiency; if excessive carbon source is manually added to avoid exceeding the standard, it will also cause the effluent COD to rise (causing secondary pollution) and increase the carbon source unit consumption; when the internal circulation reflux ratio is fixed at 1:3, it cannot match the change in carbon source demand, and therefore the prior art has the problem of low denitrification efficiency. SUMMARY

[0005] The present application provides a sewage treatment method and system based on an internal circulation high-efficiency denitrification technology to solve the problem of low denitrification efficiency in the prior art.

[0006] In a first aspect, to solve the above technical problems, the present application provides a sewage treatment method based on an internal circulation high-efficiency denitrification technology, comprising: obtaining internal circulation reflux ratio, influent flow and nitrogen concentration data, capturing water quality fluctuation characteristics according to the influent flow and the nitrogen concentration data, and determining the pollutant load level according to the water quality fluctuation characteristics; analyzing the dynamic coupling relationship between the internal circulation reflux ratio and the amount of carbon source to be added according to the pollutant load level, and obtaining a carbon source demand matching value; if the carbon source demand matching value exceeds a preset matching value threshold, predicting the regulation lag risk under the water quality fluctuation trend, and obtaining an internal circulation reflux ratio adjustment scheme; According to the internal circulation reflux ratio adjustment scheme, the denitrification reaction process is simulated, the coefficient of the carbon source dosage is judged, and a real-time correction coefficient is obtained. According to the real-time correction coefficient, the cooperative control parameter is updated, and a dosage control signal is obtained. According to the dosage control signal and the threshold comparison of the carbon source demand matching value, the business association of the pollutant load level and the real-time correction coefficient is fused, and an optimized matching coefficient is obtained. According to the optimized matching coefficient, the dynamic coupling relationship of the internal circulation reflux ratio is integrated, and the update amplitude of the cooperative control parameter is judged. According to the update amplitude, the cooperative control parameter is updated, the running state data of the system is obtained, and the instruction is generated, and the reflux optimization instruction is obtained. The reflux optimization instruction is sent to the sewage treatment system, the carbon source dosage and the internal circulation reflux ratio are cooperatively controlled, and the running state of high-efficiency denitrification is obtained.

[0007] In a second aspect, the present application provides a sewage treatment system based on internal circulation high-efficiency denitrification technology, comprising: A data acquisition module is used to acquire internal circulation reflux ratio, inflow rate and nitrogen concentration data, capture water quality fluctuation characteristics according to the inflow rate and the nitrogen concentration data, and judge the pollutant load level according to the water quality fluctuation characteristics. A 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 according to the pollutant load level, and obtain a carbon source demand matching value. A data prediction module is used to predict the regulation lag risk under water quality fluctuation trend if the carbon source demand matching value exceeds the preset matching value threshold, and obtain an internal circulation reflux ratio adjustment scheme. A data simulation module is used to simulate the denitrification reaction process according to the internal circulation reflux ratio adjustment scheme, judge the coefficient of the carbon source dosage, and obtain a real-time correction coefficient. A data update module is used to update the cooperative control parameter according to the real-time correction coefficient, and obtain a dosage control signal. A data comparison module is used to perform threshold comparison between the dosage control signal and the carbon source demand matching value, and fuse the business association of the pollutant load level and the real-time correction coefficient, and obtain an optimized matching coefficient. A data integration module is used to integrate the dynamic coupling relationship of the internal circulation reflux ratio according to the optimized matching coefficient, and judge the update amplitude of the cooperative control parameter. An instruction generation module is used to update the cooperative control parameter according to the update amplitude, obtain the running state data of the system, and generate the instruction, and obtain the reflux optimization instruction. An instruction regulation module is configured to send the backflow optimization instruction to the sewage treatment system, and to cooperatively regulate the carbon source dosage and the internal circulation backflow ratio to obtain a high-efficiency nitrogen removal operation state.

[0008] In a third aspect, the present application further provides an electronic device comprising a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, and the processor implements the sewage treatment method based on the internal circulation high-efficiency denitrification technology according to any one of the above aspects when executing the computer program.

[0009] In a fourth aspect, the present application further provides a computer readable storage medium comprising a stored computer program, wherein the computer readable storage medium controls the device where the computer readable storage medium is located to execute the sewage treatment method based on the internal circulation high-efficiency denitrification technology according to any one of the above aspects when the computer program is executed.

[0010] Compared with the prior art, the present application has the following beneficial effects: (1) The present application dynamically adjusts and cooperatively regulates the parameters by analyzing the dynamic coupling relationship between the backflow ratio and the carbon source dosage, combining the real-time correction coefficient and the optimization matching coefficient, and solves the problem that the internal circulation backflow ratio and the carbon source dosage are fixedly adjusted in the prior art, which cannot adapt to the dynamic change of the pollutant load, and either the carbon source dosage is excessive (increasing the cost and secondary pollution), or the dosage is insufficient, the denitrification is not complete, and the denitrification efficiency is low.

[0011] (2) The present application predicts the water quality fluctuation trend, quantifies the regulation lag risk, and generates an internal circulation backflow ratio adjustment scheme in advance; at the same time, the process stability data are combined for closed-loop optimization; the denitrification efficiency fluctuation amplitude is greatly reduced compared with the prior art, and the continuous stable operation time is prolonged.

[0012] (3) Compared with the prior art, the regulation of the carbon source dosage and the internal circulation backflow ratio is independent of each other, and no synergistic mechanism is formed, the present application realizes deep cooperation of the backflow ratio and the carbon source dosage through dynamic coupling analysis of the whole process, ensures that the denitrification reaction is always in the optimal condition, and improves the stability of the denitrification efficiency. BRIEF DESCRIPTION OF DRAWINGS

[0013] Figure 1 is a sewage treatment method flowchart based on the internal circulation high-efficiency denitrification technology provided by the first embodiment of the present application; Figure 2 is a sewage treatment system structure schematic diagram based on the internal circulation high-efficiency denitrification technology provided by the second embodiment of the present application. DETAILED DESCRIPTION

[0014] With reference to the accompanying drawings, the technical solutions in the embodiments of the present application will be clearly and completely described in order to make the technical solutions in the embodiments of the present application apparent to those skilled in the art. Obviously, the described embodiments are only a part rather than all of the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative efforts belong to the protection scope of the present application.

[0015] With reference to Figure 1 The first embodiment of the present application provides a sewage treatment method based on an internal circulation high-efficiency denitrification technology, comprising the following steps: S11, obtaining internal circulation reflux ratio, influent flow rate and nitrogen concentration data, capturing water quality fluctuation characteristics according to the influent flow rate and the nitrogen concentration data, and determining a pollutant load level according to the water quality fluctuation characteristics; S12, analyzing a dynamic coupling relationship between the internal circulation reflux ratio and a carbon source amount to be added according to the pollutant load level, and obtaining a carbon source demand matching value; S13, if the carbon source demand matching value exceeds a preset matching value threshold, predicting a regulation lag risk under a water quality fluctuation trend, and obtaining an internal circulation reflux ratio adjustment scheme; S14, simulating a denitrification reaction process according to the internal circulation reflux ratio adjustment scheme, determining a coefficient of the carbon source addition amount, and obtaining a real-time correction coefficient; S15, updating a cooperative regulation parameter according to the real-time correction coefficient, and obtaining an addition control signal; S16, performing threshold value comparison according to the addition control signal and the carbon source demand matching value, and fusing a business association of the pollutant load level and the real-time correction coefficient, and obtaining an optimized matching coefficient; S17, integrating a dynamic coupling relationship of the internal circulation reflux ratio according to the optimized matching coefficient, and determining an update amplitude of the cooperative regulation parameter; S18, updating the cooperative regulation parameter according to the update amplitude, obtaining running state data of the system, and generating an instruction, and obtaining a reflux optimization instruction; S19, sending the reflux optimization instruction to a sewage treatment system, cooperatively regulating the carbon source addition and the internal circulation reflux ratio, and obtaining a high-efficiency denitrification running state.

[0016] In step S11, the obtaining of the internal circulation reflux ratio, the influent flow rate and the nitrogen concentration data, the capturing of the water quality fluctuation characteristics according to the influent flow rate and the nitrogen concentration data, and the determination of the pollutant load level according to the water quality fluctuation characteristics, comprise: According to the influent flow rate and the nitrogen concentration data, analyzing the water quality fluctuation characteristics, and obtaining characteristic parameters of the 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 characteristic of the denitrification stage. The pollutant load is calculated according to the pollutant distribution characteristic to obtain the pollutant load level.

[0017] It should be noted that the influent flow is collected by an ultrasonic flow meter installed on the influent main pipeline of the sewage treatment system, the collection frequency is 1 time per minute, and the output data format is “cubic meters per hour (m³ / h)”; the nitrogen concentration data is collected by an online total nitrogen analyzer installed downstream of the influent pipeline, the collection frequency is synchronized with the flow, and the output data format is “milligrams per liter (mg / L)”; the internal circulation reflux ratio data is equal to the internal circulation reflux flow divided by the influent flow, wherein the internal circulation reflux flow is collected by an electromagnetic flow meter installed on the outlet pipeline of the internal circulation pump, the collection frequency is 1 time per minute, and the internal circulation reflux ratio is calculated by dividing the reflux flow by the influent flow at the same time. All collected data are transmitted to a time series database in real time and stored in a “time stamp-data type-value” structure.

[0018] According to the time sequence correlation of the obtained influent flow and nitrogen concentration data, three types of quantifiable water quality fluctuation characteristic parameters are extracted, including fluctuation amplitude (reflecting the degree of water quality mutation), fluctuation frequency (reflecting the frequency of water quality instability); the fluctuation amplitude can be taken as the nitrogen concentration in the continuous 10 minutes of influent flow, and the difference between the maximum value and the minimum value is calculated to obtain the fluctuation amplitude; the fluctuation frequency can be counted as the number of times that the nitrogen concentration fluctuation amplitude exceeds 5% of the average value within 1 hour; the parameters are integrated into a characteristic parameter set to obtain the characteristic parameter.

[0019] Collect normal operation data (at least 1000 groups) in the past 3 months, and after the data analysis shows that the 95% quantile value of the nitrogen concentration fluctuation amplitude is taken as the threshold, the system misjudgment rate and the missed judgment rate are greatly reduced to an acceptable range, that is, the 95% quantile value of the characteristic parameter when there is no water quality anomaly is taken as the threshold, wherein the nitrogen concentration fluctuation amplitude threshold = 10 mg / L (95% normal data fluctuation ≤ 10 mg / L, which can be calibrated based on actual historical data to adapt to specific water quality), and the fluctuation frequency threshold = 5 times / hour; compare the characteristic parameter set with the preset characteristic threshold, if all parameters do not exceed the threshold, directly calculate the pollutant load based on the average flow and the average nitrogen concentration; if any characteristic parameter exceeds the threshold, it is determined that the water quality fluctuation exceeds the normal range, and the pollutant distribution characteristic needs to be further analyzed, and the convolutional neural network (CNN) algorithm is used to analyze the space-time distribution of water quality fluctuation; the CNN input data is a time sequence matrix, which can be constructed into a two-dimensional feature map through a sliding window.

[0020] The convolutional neural network model structure adopts a lightweight architecture. The input layer receives a time series data matrix. Convolution layer 1 (Conv1) extracts the concentration peak area in the time dimension. Pooling layer 1 (MaxPool1) compresses the time dimension and retains the peak feature. Convolution layer 2 (Conv2) correlates the time peak and the spatial position. Pooling layer 2 (AvgPool2) outputs the spatial distribution feature. The fully connected layer (FC) quantifies the spatial distribution characteristics. The time granularity is 1 minute. The convolution kernel size is 3x1 (Conv1) and 5x1 (Conv2). The network has 2 layers of convolution and 2 layers of pooling. The activation function uses the ReLU function. The “influent flow-nitrogen concentration” time series data (time granularity 1 minute) of nearly 24 hours is extracted, and a two-dimensional data matrix is constructed according to the “time axis (x-axis)-value (y-axis)”. The structural parameters of the denitrification tank (such as tank length 10 m, divided into 5 compartments) are imported synchronously. The first layer of convolution extracts the concentration peak area in the time dimension (such as identifying that the nitrogen concentration is continuously higher than 40 mg / L from 8:00 to 8:30). The second layer of convolution combines the water residence time and maps to the spatial position of the denitrification tank (such as the high-concentration influent at 8:00 reaching the 3rd compartment of the tank). The output result obtains the pollutant distribution characteristics in the denitrification stage (for example, the pollutant concentration is highest in the front 1-2 compartments (0-4 m) of the denitrification tank, with an average of 42 mg / L; the concentration gradually decreases in the rear 3-5 compartments (4-10 m), with an average of 32 mg / L, showing a “high front, low rear” distribution characteristic).

[0021] Based on the pollutant distribution characteristics, the regional flow rate of each region is calculated. The flow rate of each compartment 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 coefficient (set as 0.001, 1 mg / L = 0.001 kg / m³). The total load is equal to the sum of the regional loads.

[0022] In step S12, the dynamic coupling relationship between the internal circulation reflux ratio and the amount of carbon source to be added is analyzed according to the pollutant load level, and a carbon source demand matching value is obtained, including: According to the pollutant load level, the dynamic coupling relationship between carbon source addition and internal circulation reflux ratio is analyzed to obtain the dynamic coupling relationship characteristics; According to the dynamic coupling relationship characteristics, the carbon source addition amount is calculated to obtain a preliminary carbon source addition amount adjustment value; If the preliminary carbon source addition amount adjustment value exceeds the preset adjustment value threshold, the influent flow rate and the nitrogen concentration data are updated, and the carbon source addition amount is recalculated to obtain a corrected carbon source addition amount adjustment value; According to the corrected carbon source addition amount adjustment value, the control parameter matched with the internal circulation reflux ratio is calculated to obtain the carbon source demand matching value.

[0023] It should be noted that the principle of denitrification reaction is to replace nitrogen with carbon source (electron donor) and nitrate (electron acceptor). The internal circulation reflux ratio determines the amount of nitrate supply. The higher the reflux ratio, the more nitrate produced in the aerobic tank will flow back to the denitrification tank (for example, when the reflux ratio is 200%, the amount of reflux nitrate is twice the amount of influent). The amount of carbon source determines the upper limit of reaction rate. Insufficient carbon source will limit the efficiency of denitrification (nitrate cannot be completely degraded), and excessive carbon source will result in residual COD (secondary pollution).

[0024] The dynamic coupling relationship between the two is that as the reflux ratio increases, the nitrate increases, and the carbon source required increases accordingly; as the reflux ratio decreases, the nitrate decreases, and the carbon source required decreases. Taking the pollutant load level as input, combining the real-time data of the internal circulation reflux ratio, and analyzing by the least squares linear regression algorithm, the input data is the internal circulation reflux ratio (such as 150%, 200%, 250%) and the corresponding carbon source dosage (such as 190 kg / h, 240 kg / h, 290 kg / h) in the past 1 hour, as well as the pollutant load (38 kg total nitrogen / h) in the same period; calculate the change amount of carbon source dosage (i.e. coupling coefficient) when the reflux ratio changes by 10%, for example, when the reflux ratio increases from 150% to 200% (+50%), the carbon source amount 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 obtains the dynamic coupling relationship characteristics, represented by "coupling coefficient and optimal C / N ratio" (for example, coupling coefficient 1 kg / (h·%), optimal C / N ratio 5:1, i.e. 5 kg carbon source is needed for every 1 kg nitrogen degradation).

[0025] The preliminary carbon source dosage adjustment value is equal to the pollutant load level multiplied by the optimal C / N ratio plus (current reflux ratio minus baseline reflux ratio) multiplied by the coupling coefficient; wherein the baseline reflux ratio is 200% by default (according to 1000 sets of historical data analysis, in conventional sewage, the influent total nitrogen concentration is about 20-40 mg / L, and after nitrification in the aerobic tank, the amount of nitrate generated is about 80%-90% of the influent total nitrogen. The data shows that when the reflux ratio is 200%, the total amount of nitrate refluxed to the denitrification tank (influent carried plus refluxed) can meet the denitrification demand of more than 90% (denitrification efficiency reaches 85%-90%); if the reflux ratio is less than 150%, the nitrate supply is insufficient, and the denitrification efficiency will decrease to below 70%). The preliminary carbon source dosage reflects the amount of carbon source required to degrade the pollutant load under the current reflux ratio, which includes both the basic demand (pollutant load multiplied by C / N) and the compensation amount due to the deviation of the reflux ratio from the baseline value (reflux ratio deviation multiplied by coupling coefficient).

[0026] The threshold setting is based on the upper limit of the carbon source of the denitrification tank (to avoid excessive COD, such as setting the threshold value to 280 kg / h), if the preliminary adjustment value does not exceed the threshold value, the value is directly used; if the preliminary adjustment value exceeds the threshold value (such as 320 kg / h>300 kg / h), the data is updated, the influent flow (such as from 1000 m³ / h to 950 m³ / h) and the nitrogen concentration (such as from 40 mg / L to 38 mg / L) in the last 10 minutes are collected again, and the pollutant load level (950×38÷1000=36.1 kg / h) is updated; 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 quantitative index of the adaptation of the carbon source demand and the current internal circulation reflux ratio, reflecting whether they are in an optimal cooperative state (the closer the value is to 1, the higher the matching degree). The carbon source demand matching value is equal to the corrected carbon source dosage divided by the total carbon source theoretical demand, wherein the total carbon source theoretical demand can be calculated by multiplying the sum of the influent nitrate amount and the internal circulation reflux nitrate amount by the optimal C / N ratio, the influent nitrate amount is equal to the pollutant load multiplied by the nitrification rate, the internal circulation reflux nitrate amount is equal to the reflux flow multiplied by the effluent nitrate concentration of the aerobic tank divided by 1000, the effluent nitrate concentration of the aerobic tank is equal to the influent nitrogen concentration multiplied by the nitrification rate, and the nitrification rate is the ratio of the amount of nitrate nitrogen generated in the aerobic tank to the total nitrogen in the influent, reflecting the ability of the aerobic tank to convert the nitifiable components in the influent total nitrogen into nitrate.

[0027] In step S13, if the carbon source demand matching value exceeds the preset matching value threshold, the control lag risk under the water quality fluctuation trend 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 according to the influent flow and the nitrogen concentration data, and a prediction value is obtained. If the prediction value exceeds the preset prediction value threshold, the control lag risk characteristics under the water quality fluctuation trend are predicted, and a quantitative value of the control lag risk is obtained. According to the quantitative value of the control lag risk, the internal circulation reflux ratio is adjusted to obtain an internal circulation reflux ratio adjustment scheme.

[0028] It should be noted that the matching value threshold is usually set to 1.5, which corresponds to 50% of the carbon source demand exceeding the baseline state. Experimental data shows that when the baseline state is exceeded by 50%, the cooperative relationship between carbon source and reflux ratio has been seriously unbalanced (such as excessive reflux ratio leading to rapid increase in carbon source demand, or insufficient carbon source dosage capacity); the "influent flow (m³ / h)" and "nitrogen concentration (mg / L)" data (time granularity 5 minutes) in the last 48 hours are extracted from the time series database, including historical fluctuation characteristics (such as sudden increase in peak flow, periodical impact of industrial wastewater).

[0029] The long short-term memory network (LSTM) is used, the standardized flow data (0-1 range) and the nitrogen concentration (0-1 range) are used to eliminate the dimensional effect; the LSTM is trained by using the historical data of the past 6 months (including normal and abnormal working conditions), the input is "the data of the past 24 hours", and the output is "the prediction value of every 10 minutes in the future 2 hours"; the final output is "the prediction value of the water quality fluctuation trend", which includes "the flow prediction curve" and "the nitrogen concentration prediction curve" in the future 2 hours (for example, the nitrogen concentration is increased from 40 mg / L to 55 mg / L and the flow is increased from 1000 m³ / h to 1200 m³ / h after 1 hour).

[0030] The input layer of the long short-term memory network (LSTM) receives the standardized "inlet flow-nitrogen concentration" time series data, the standardized layer performs 0-1 standardization on the flow and the nitrogen concentration, the LSTM layer (core layer) captures the long-term dependence relationship of the water quality fluctuation, the fully connected layer (FC) outputs the prediction value in the future 2 hours, the output layer is de-standardized, and the actual physical value is output; the time granularity is 5 minutes, the historical dependence length is 48 hours, the number of LSTM neurons is 64 per layer, the dropout is 0.2, and the prediction length is 2 hours; the historical data of the past 6 months is collected, which is divided according to the 5-minute granularity, and the flow and the nitrogen concentration in the past 48 hours are input; the measured values of the SCADA system are directly used as labels (actual values of the flow and the nitrogen concentration), the optimizer uses Adam (learning rate 0.001), the loss function is MSE (mean square error, suitable for regression tasks), and the iteration is 100 rounds (early stopping mechanism, the verification set error is not decreased for 3 rounds, and then the iteration is stopped), so that the flow prediction error is ≤8% and the nitrogen concentration prediction error is ≤10%.

[0031] It should be noted that the water quality fluctuation trend prediction can be realized by using the long short-term memory network (LSTM) model, or by using the sliding average method, the exponential smoothing method or the autoregressive integrated moving average model (ARIMA) known in the art.

[0032] The threshold value needs to be set as the maximum water quality fluctuation range that the denitrification tank can withstand. The threshold value of the nitrogen concentration prediction value is 50 mg / L (above this value, the denitrifying bacteria will be inhibited due to high substrate concentration). The threshold value of the flow prediction value is 1300 m³ / h (above this value, the hydraulic retention time of the tank will be less than 8 hours, affecting the reaction completeness). When the prediction value exceeds the threshold value (such as nitrogen concentration prediction 55 mg / L > 50 mg / L), the regulation lag risk needs to be analyzed. The regulation lag risk refers to the possibility and degree of water quality deterioration within the time difference from adjusting the internal circulation reflux ratio to the actual improvement of water quality. It includes three characteristics, including lag time, deterioration amplitude and fluctuation frequency. The lag time is the time required for water quality to meet the standard (such as nitrogen concentration ≤ 30 mg / L) after adjusting the reflux ratio. The deterioration amplitude is the maximum value of the possible increase in nitrogen concentration within the lag time. The fluctuation frequency is the number of times the water quality exceeds the standard during the lag period.

[0033] The above characteristics are converted into 0-1 quantification values (1 is the highest risk), and the characteristic weights are assigned as follows: lag time weight 0.4 (denitrifying bacteria have a time threshold for water quality deterioration. If the time exceeds the threshold, the microbial activity will irreversibly decrease. 1000 sets of historical data are extracted from the time series database for analysis. Experimental data shows that 45% of the effluent exceeding the standard is caused by "long lag time", so the second highest weight 0.4 is assigned. Deterioration amplitude weight 0.4 (the greater the deterioration amplitude, the greater the damage to microorganisms, and the higher the subsequent treatment cost. Experimental data shows that for every 5 mg / L increase in deterioration amplitude, the subsequent repair cost increases by 20%. Data analysis shows that 38% of historical failures are caused by excessive deterioration amplitude, so the weight is assigned as 0.4. 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 first two items, its instantaneous damage to the system is smaller. Data analysis shows that only 12% of historical failures are mainly caused by high frequency fluctuations, so a lower weight of 0.2 is assigned.

[0034] The risk coefficients of the three types of features are calculated, and the feature value interval is divided into a safe interval for a lag time less than 20 minutes, a warning interval for 21-30 minutes, and a dangerous interval for more than 30 minutes; a safe interval for a deterioration amplitude less than 5 mg / L, a warning interval for 6-8 mg / L, and a dangerous interval for more than 8 mg / L; a safe interval for a fluctuation frequency less than 1 time / hour, a warning interval for 2 times / hour, and a dangerous interval for more than 3 times / hour; the relationship between the feature value interval and the risk coefficient is analyzed using historical data of the past 6 months, when the lag time < 20 minutes, the deterioration amplitude < 5 mg / L, and the fluctuation frequency < 1 time / hour, the probability of out-of-specification effluent in the historical working condition is ≤8%, and the corresponding risk coefficient is 0.1 (low risk); when the feature value is in the warning interval, the historical out-of-specification probability rises to 30%-40%, and the corresponding risk coefficient is 0.5 (medium risk); when the feature value enters the dangerous interval, the historical out-of-specification probability exceeds 60%, and the corresponding risk coefficient is 0.9 (high risk); the quantified value is equal to the sum of the risk coefficients of the corresponding features multiplied by the weight.

[0035] According to the risk quantification value, a stepwise adjustment is used to determine the reflux ratio adjustment value, wherein the higher the risk, the larger the adjustment amplitude, but not more than the equipment limit; when the lag risk quantification value is 0.1-0.3 (low risk), the reflux ratio adjustment amplitude (relative to the current value) is +10%; when the lag risk quantification value is 0.4-0.6 (medium risk), the reflux ratio adjustment amplitude (relative to the current value) is +20%; when the lag risk quantification value is 0.7-1.0 (high risk), the reflux ratio adjustment amplitude (relative to the current value) is +30%. The final output is the internal circulation reflux ratio adjustment scheme.

[0036] In step S14, the denitrification reaction process is simulated according to the internal circulation reflux ratio adjustment scheme, the coefficient of carbon source dosage is determined, and a real-time correction coefficient is obtained, including: Obtaining environmental parameter data; Standardizing the environmental parameter data, the influent flow and the nitrogen concentration data to obtain a first data set; If the nitrogen concentration data in the first data set exceeds a preset concentration threshold, calculating the reaction rate according to the environmental parameter data in the first data set to obtain a real-time rate value of the denitrification reaction; Optimizing the internal circulation reflux ratio adjustment scheme according to the real-time rate value to obtain an optimized carbon source dosage parameter; Fine-tuning the dosage according to the optimized carbon source dosage parameter to obtain a real-time correction coefficient.

[0037] It should be noted that the denitrification reaction rate is significantly affected by environmental factors (such as temperature, pH value directly affecting microbial activity), and key environmental parameters need to be collected, including water temperature, mixed liquor pH value, and dissolved oxygen (DO) in the denitrification tank through a sensor matrix, with a collection frequency of 5 minutes / time. All parameters are transmitted to the central control system in real time, and the storage format is "time stamp-parameter name-value". The environmental parameter data, influent flow, and nitrogen concentration data are integrated into the first data set, and standardized processing is performed to unify the dimensions of different parameters. The minimum and maximum values of each parameter can be determined based on historical 3-month normal operation data, and 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. The first data set is obtained.

[0038] The preset concentration threshold is the safety control value of the denitrification tank outlet. The nitrogen concentration data of the denitrification tank outlet during normal operation in the past 6 months is counted, the stable operation interval of the denitrification tank is analyzed, and the 95% quantile value is taken as the threshold, which is set to 12 mg / L. If the standardized value of nitrogen concentration in the first data set 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 environmental parameters and nitrogen concentration. The real-time rate value (kg / (m³·h)) is equal to 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°C, pH 7.5, and DO=0 (0.005 kg / (m³·h)). The samples that meet the standard conditions (20±1°C, pH 7.5±0.2, DO≤0.2 mg / L) can be selected from historical operation data. The single group rate (kg / (m³·h)) of the sample is calculated as (influent nitrogen concentration minus outlet nitrogen concentration) multiplied by influent flow divided by denitrification tank effective volume divided by reaction time. The arithmetic mean value (excluding 10% highest value and 10% lowest value to avoid extreme value influence) of the selected sample rate is taken as the base rate. The real-time rate calculation model can use a more complex kinetic model (such as Monod equation) according to the specific characteristics of the wastewater. The embodiment provides a simplified version to ensure real-time performance.

[0039] The environmental parameter adaptation coefficient and the nitrogen concentration adaptation coefficient can be calculated in segments. When the temperature is 19-21℃, the pH is between 7.3-7.7, and DO≤0.2mg / L, the environmental parameter adaptation coefficient is 1.0 (this interval is the definition source of the standard working condition, and is also the working condition range with the highest denitrification efficiency (85%-90%) in historical data. The denitrifying bacteria are facultative anaerobes, and there is no oxygen competition when DO≤0.2mg / L, so the rate is the highest, which is the ideal interval for denitrification. The environmental parameter matching basic rate screening condition is that the rate has no attenuation, and the process stability is optimal). When the temperature is 15-19℃ or 21-25℃, the pH is 7.0-7.3 or 7.7-8.0, and DO is 0.2-0.5mg / L, the environmental parameter adaptation coefficient is 0.7 (according to the statistics of 1200 groups of collected operation data, 90% of the normal working conditions have a temperature of 15-25℃ and a pH of 7.0-8.0, and DO is 0.2-0.5mg / L. The denitrifying bacteria compete with aerobic bacteria for substrates. After excluding the ideal interval of 19-21℃, the remaining interval is a near-ideal interval. The environmental parameters deviate slightly, the rate is attenuated by 30% compared with the ideal interval, and the process stability is good). When the temperature is <15℃ or >25℃, the pH is <7.0 or >8.0, and DO is >0.5mg / L, the environmental parameter adaptation coefficient is 0.4 (according to the statistics of 1200 groups of operation data, the denitrification efficiency decreases sharply when DO is >0.5mg / L. The denitrification efficiency in this interval is <70%, the environmental parameters deviate seriously, the rate is attenuated by 60% compared with the ideal interval, and the process stability is poor). When the nitrogen concentration is in the safe interval, the nitrogen concentration adaptation coefficient is 0.5 (in this interval, the nitrogen concentration does not exceed the threshold value, the substrate is not limited, the rate increases linearly with the concentration, the contribution of the concentration to the rate is the highest, and the rate growth slope corresponds to the coefficient 0.5). When the nitrogen concentration is in the warning interval, the nitrogen concentration adaptation coefficient is 0.3 (the nitrogen concentration exceeds the threshold value, the substrate is close to saturation, the rate growth slows down, the contribution of the concentration to the rate decreases to 60% of that in the safe interval, the rate growth slope in this interval is 60% of that in the safe interval, so the coefficient is 0.5 multiplied by 60% equal to 0.3). When the nitrogen concentration is in the dangerous interval, the nitrogen concentration adaptation coefficient is 0.1 (the nitrogen concentration seriously exceeds the threshold value, the substrate is completely saturated, the rate tends to be stable, the contribution of the concentration to the rate decreases to 20% of that in the safe interval, and historical data shows that for every 1mg / L increase in concentration, the rate increases by only 0.00008kg / (m³·h), which is 20% of that in the safe interval. Take 20% of 0.5, so the coefficient is 0.1).

[0040] According to the deviation of the real-time rate value and the target rate value, the backflow ratio adjustment scheme output by the optimization step S13 is optimized, and the optimized carbon source dosage parameter is obtained synchronously. When the deviation of the real-time rate value and the target value is less than -20% (the rate is low), the deviation of the real-time rate value and the target value is reduced by 20% relative to -20% every time. The internal circulation backflow ratio adjustment is increased by 10% (the supply of nitrate is increased), and the carbon source dosage adjustment is increased by 15% (the carbon source is supplemented, and the reaction is accelerated). When the deviation of the real-time rate value and the target value is between -20% and +10% (basically up to standard), the internal circulation backflow ratio is unchanged, and the carbon source dosage is maintained unchanged. When the deviation of the real-time rate value and the target value is greater than +10% (the rate is high), the deviation of the real-time rate value and the target value is increased by 10% relative to +10% every time. The internal circulation backflow ratio is reduced by 5% (the energy consumption is reduced), and the carbon source dosage is reduced by 5% (the waste of carbon source is avoided), to obtain the optimized carbon source dosage parameter. The target rate value is preset to 0.01 kg / (m³·h), which is determined based on the actual metabolic capacity of denitrifying bacteria. A large amount of experimental data shows that the maximum daily metabolic rate of denitrifying bacteria in an ideal environment (20-30°C, pH 7.0-8.0, sufficient carbon source) is about 0.3 kg / (m³·d) (the hourly rate is 0.012-0.015 kg / (m³·h)). In actual operation, due to uneven distribution of nitrate, local carbon source shortage and other factors, 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 the interval, which does not exceed the actual metabolic capacity of microorganisms, and can fully exert the activity of microorganisms.

[0041] 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 is equal to the pollutant load multiplied by the best C / N ratio), which 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 demand. 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 correction coefficient) times. The step S14 process is repeated every 10 minutes (data is reacquired, and a new coefficient is calculated), to form a closed loop of "real-time monitoring → simulation → correction" (synchronous with the dynamic change of denitrification reaction).

[0042] In step S15, the real-time correction coefficient is used to update the cooperative control parameter, to obtain a dosing control signal.

[0043] It should be noted that the synergistic control parameter is a core parameter group reflecting the optimal matching relationship between the internal circulation reflux ratio and the carbon source dosage, containing 3 types of key parameters, including the optimized carbon source dosage, the real-time correction coefficient and the 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 group; the actual carbon source dosage is calculated as the baseline carbon source dosage multiplied by the real-time correction coefficient multiplied by the reflux ratio adaptation coefficient, wherein the reflux ratio adaptation coefficient can be calculated by multiplying the difference between 1 and the reflux ratio and 0.2, quantifying the degree of deviation of the current internal circulation reflux ratio from the baseline reflux ratio, and used as a coefficient for dynamically compensating the carbon source dosage. Based on the statistical data of 1000 groups of operation in the past 6 months, under the condition of fixing other conditions (such as temperature, pH, and carbon source type), the nitrate supply of the denitrification tank increases by 8%-10% when the internal circulation reflux ratio increases by 10%, and the carbon source demand needs to be increased by 2% to maintain the optimal C / N ratio. Therefore, the coefficient 0.2 is taken, and the addition control signal is converted into an executable instruction of the carbon source addition device. The updated parameter group is transmitted to the pump control system in the form of a Modbus protocol digital signal to obtain the addition control signal.

[0044] In step S16, threshold comparison is performed between the addition control signal and the carbon source demand matching value, and the service association of the pollutant load level and the real-time correction coefficient is fused to obtain an optimized matching coefficient.

[0045] It should be noted that threshold comparison is to identify whether the current system is in a controllable interval, and threshold values need to be set for the two types of parameters and comparison needs to be performed. The threshold value of the addition control signal is based on the safe operation range of the carbon source addition device, and is divided into a lower threshold value and an upper threshold value. The lower threshold value corresponds to the minimum effective dosage (such as 50 kg / h, below which the carbon source distribution will be uneven, affecting the uniformity of denitrification); the upper threshold value corresponds to the maximum capacity of the device (such as 300 kg / h, above which the device overload protection will be triggered). If the addition 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); the preset matching value threshold of step S13 is used, and 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 group [addition control signal state (1 / 0), carbon source demand matching value state (1 / 0)], such as [1, 1] (both normal).

[0046] The pollutant load level has a strong business correlation with the real-time correction coefficient. The higher the load, the more significant the impact of environmental factors on carbon source demand (e.g., when the load is high, a 1°C decrease in temperature may result in a 5% increase in carbon source demand, while when the load is low, it may only increase by 2%). The relationship needs to be quantified through the correlation degree calculation formula, which is equal to 0.6 times the load level divided by the reference load plus 0.4 times the real-time correction coefficient; the reference load is the historical average pollutant load, which is used to standardize the load level (to eliminate the dimension); the influence of the load level and the correction coefficient on the system's core indicator (denitrification efficiency) is quantified through a parameter influence degree experiment (based on 1000 sets of operation data in the past 6 months); the single variable influence test (controlled variable method) tests the influence of the load level and the correction coefficient respectively; the results show that when the correction coefficient is fixed at 1.0 and the load increases from 25 kg / h (low load) to 35 kg / h (high load), the denitrification efficiency decreases from 90% to 78% (a decrease of 12%), and for every 10% change in load, the efficiency changes by about 4.8%; when the load is fixed at 30 kg / h and the correction coefficient increases from 0.9 (low correction) to 1.1 (high correction), the denitrification efficiency increases from 82% to 88% (an increase of 6%), and for every 10% change in correction coefficient, the efficiency changes by about 3%; the ratio of the influence of load on efficiency (4.8% / 10%) to the correction coefficient (3% / 10%) is about 1.6:1, close to the ratio of 0.6:0.4 (1.5:1), proving that the weight can reflect the actual impact difference.

[0047] The optimization matching coefficient is the weighted fusion of the threshold comparison result (system status) and the business correlation degree (parameter coordination), which quantifies the coordination level of carbon source-reflux-load-environment of the system as a whole (value 0-1, closer to 1 is better). The optimization matching coefficient is equal to (state normal rate multiplied by 0.3) plus (correlation degree standardized value multiplied by 0.7); where the state normal rate is (the state of the dosing control signal plus the carbon source demand matching value) multiplied by 2; the correlation degree standardized value is the difference between the correlation degree and the minimum correlation degree divided by the difference between the maximum correlation degree and the minimum correlation degree; the role of the state normal rate is to exclude abnormal conditions. When the dosing control signal exceeds the equipment range (e.g., >300 kg / h) or the carbon source demand matching value is severely unbalanced (e.g., >1.5), the system is in a dangerous state and needs to trigger fault handling (e.g., shutdown inspection) first rather than optimization; but in the normal state (state normal rate = 1.0), its role in improving the accuracy of optimization is limited. Statistics of system failure cases in the past year (120 times) show that only 28% of the failures are directly caused by "state abnormality" (e.g., pump overload, matching value exceeding threshold); 72% of the failures are caused by normal state but imbalance of correlation degree (e.g., insufficient correction coefficient at high load, resulting in a sharp decrease in denitrification efficiency), so the weight of state normal rate is set to 0.3 and the weight of correlation degree standardized value is set to 0.7.

[0048] In step S17, the dynamic coupling relationship of the internal circulation reflux ratio is integrated according to the optimization matching coefficient to determine the update amplitude of the synergistic control parameter, including: obtaining process stability data; standardizing the internal circulation reflux ratio, the influent flow rate and the nitrogen concentration data to obtain a second data set; fusing the dynamic changes of the nitrogen concentration data and the internal circulation reflux ratio in the second data set to obtain a reflux ratio dynamic coupling coefficient; if the reflux ratio dynamic coupling coefficient is less than a preset coefficient threshold, comparing the optimization matching coefficient with the process stability data to determine the update amplitude of the synergistic control parameter.

[0049] It should be noted that the process stability data is a basis for judging whether the current running state of the denitrification system is stable, wherein the collection indexes include a denitrification efficiency fluctuation value (standard deviation of denitrification efficiency for three times in succession, reflecting the efficiency stability), a frequency of exceeding the effluent nitrogen concentration (counting the number of times that the effluent nitrogen concentration is greater than 12 mg / L in the past 1 hour), and an internal circulation reflux ratio execution deviation (difference percentage between the actual reflux ratio and the set value). The internal circulation reflux ratio, the influent flow rate and the nitrogen concentration data are standardized to eliminate the dimensional difference, and 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], to obtain a second data set.

[0050] The reflux ratio dynamic coupling coefficient is used to measure the dynamic response relationship between the internal circulation reflux ratio change and the nitrogen concentration change (such as whether the nitrogen concentration decreases as expected after the reflux ratio is adjusted), and to capture the hysteresis synergy of the two (because of the delay of the reaction, the change of 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 the hysteresis synergy, which refers to the time required for the outlet nitrogen concentration of the denitrification tank to decrease to a preset target concentration after the internal circulation reflux ratio is adjusted. The time point when the reflux ratio change rate is greater than 5% in the past 2 hours is taken, and the subsequent outlet nitrogen concentration is counted from the reflux ratio adjustment trigger point until the concentration is less than or equal to 12 mg / L, and the time required is the system response time. If the standard is not met within 2 hours, the system response time is taken as 2 hours (judging as serious synergy 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, there is no actual working condition, which is regarded as data anomaly, and the coupling coefficient=0.7 by default), the synergy is good, the coupling coefficient can be calculated by 0.6 plus 0.4 divided by the system response time, when 20

[0051] The system operation data (1200 groups of effective dynamic coupling coefficients) in the past 1 year are analyzed. According to the data analysis, when the coupling coefficient is greater than or equal to 0.6, 92% of the working conditions are in a stable operation state (denitrification efficiency is greater than or equal to 85%, and energy consumption is less than or equal to 0.3 kW·h / kg nitrogen); when the coupling coefficient is less than 0.6, 78% of the working conditions appear “cooperative imbalance” (such as an increase in reflux ratio but no decrease in nitrogen concentration, or a denitrification efficiency fluctuation of more than 10%). 0.6 is the demarcation point between the stable interval and the imbalance interval (the minimum value corresponding to a stable rate of 92%), which meets the characteristics of the “lower limit of 95% confidence interval” in statistics, so the coefficient threshold is set to 0.6.

[0052] If the coupling coefficient is greater than the threshold value, it indicates that the dynamic matching of the reflux ratio and the nitrogen concentration is good, and there is no need for significant adjustment; if the coupling coefficient is less than the coefficient threshold, it indicates that the correlation between the two is imbalanced (such as an increase in reflux ratio but no decrease in nitrogen concentration), and the update amplitude needs to be calculated. The indicators in the process stability data are scored for stability (0-1 points, 1 point for the most stable), the denitrification efficiency fluctuation value 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 exceeding frequency score is equal to 1 minus the difference between the actual number and 1 divided by 2 (if less than 0, take 0), and the internal circulation reflux ratio execution deviation is equal to 1 minus the difference between the actual value and the set value divided by the set value. The average of the above scores is taken to output the process stability comprehensive score. The optimized matching coefficient and the process stability comprehensive score are compared. When the optimized matching coefficient is less than 0.6 and the process stability score is less than 0.7, the update amplitude of the current cooperative control parameter is increased by 10%; when the optimized matching coefficient is between 0.6 and 0.8 and the process stability score is between 0.7 and 0.9, the update amplitude of the current cooperative control parameter is increased by 5%; and when the optimized matching coefficient is greater than 0.8 and the process stability score is greater than 0.9, the update amplitude of the current cooperative control parameter is increased by 10%.

[0053] In step S18, the cooperative control parameters are updated according to the update amplitude, the operation state data of the system is obtained, and instructions are generated to obtain reflux optimization instructions, including: The cooperative control parameters are updated according to the update amplitude, and the operation state data of the system is obtained; The operation state data and the influent flow are standardized to obtain a third data set; The dynamic changes of the operation state data and the influent flow in the third data set are fused to obtain an operation state dynamic coefficient; If the operation state dynamic coefficient exceeds a preset operation threshold, the preset demand matching logic and the process stability data are compared to determine the generation condition of the reflux optimization instructions; According to the generation condition, the matching relationship between the internal circulation reflux ratio and the nitrogen concentration data is adjusted, and instructions are generated to obtain the reflux optimization instructions.

[0054] It should be noted that based on the update amplitude output in step S17, the core coordination parameter is adjusted, the internal circulation reflux ratio is the current value multiplied by (1 plus the update amplitude); the carbon source dosage and the reflux ratio are adjusted in linkage (the C / N ratio is kept stable), and real-time running data within 10 minutes after adjustment (reflecting the actual effect after parameter update) is obtained synchronously, the collection indexes include the effluent nitrogen concentration, dissolved oxygen (DO) and carbon source residual amount (COD), the third data set contains running state data and influent flow, which needs to be converted into non-dimensional value in the interval of 0-1 through standardization processing, the standardized value of other indexes 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, and the format is standardized vector output third data set, such as [effluent nitrogen concentration 0.53, DO 0.5, COD residual 0.4, influent flow 0.5].

[0055] The running state dynamic coefficient is used to measure the coordinated adaptability of the system running state and the influent flow change after parameter update, capture the actual effect of state improvement after implementing the control measures, and the running state dynamic coefficient takes the average value of the state improvement degree and the flow adaptation degree, wherein the state improvement degree reflects the optimization degree of the running state after parameter update, and takes the average value of the standardized values of the effluent nitrogen concentration, DO and COD residual in the third data set; the flow adaptation degree reflects the matching degree of the current parameter and the influent flow fluctuation, and the deviation rate of the current reflux ratio standardized value and the influent flow standardized value can be calculated (the smaller the deviation, the higher the adaptation degree), and specifically, the flow adaptation degree is equal to 1 minus the absolute value of the difference between the current reflux ratio standardized value and the influent flow standardized value.

[0056] Through analyzing the system running data (1500 groups of effective dynamic coefficients) in the past year and through experimental simulation of the failure probability (denitrification efficiency <80%) of the system within 12 hours under different dynamic coefficients, it is obtained that when the dynamic coefficient is 0.7, the failure probability is 2.5% (acceptable risk); when the dynamic coefficient is equal to 0.65, the failure probability is 12% (risk significantly rises); when the dynamic coefficient is equal to 0.75, the failure probability is 0.8% (risk is too low but may lead to insufficient control), the threshold value needs to be greater than or equal to 0.7 to control the failure risk within 5%, so the preset running threshold value is 0.7 (based on historical data, when the coefficient is greater than or equal to 0.7, the system is in an “optimized response state”), if the dynamic coefficient is less than the running threshold value, the instruction generation condition is determined through comparison of the preset demand matching logic and the process stability data; the preset demand matching logic is that the internal circulation reflux ratio and the nitrogen concentration need to satisfy the reflux ratio standardized value equal to the nitrogen concentration standardized value multiplied by 1.2.

[0057] If the process stability score is less than 0.7 and does not meet the demand matching logic (deviation rate is greater than 10%), the reflux ratio is greatly increased by 15%, and the carbon source is simultaneously increased by 10%; if the process stability score is between 0.7 and 0.9 and partially meets the demand matching logic (deviation rate is between 5% and 10%), the reflux ratio is moderately increased by 8%, and the carbon source is simultaneously increased by 5%; if the process stability score is greater than 0.9 and basically meets the demand matching logic (deviation rate is less than 5%), the reflux ratio is finely adjusted by 3%, and the carbon source remains unchanged.

[0058] Based on the dynamic correction of the internal circulation reflux ratio and nitrogen concentration matching relationship under the generation condition, a correction coefficient is introduced according to the generation condition (greatly / moderately / finely), and the matching ratio is adjusted, that is, the reflux ratio is equal to the nitrogen concentration multiplied by 1.2 multiplied by the correction coefficient, wherein the correction coefficient is equal to 1.3 minus 0.3 times 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.

[0059] In step S19, the reflux optimization instructions are sent to the sewage treatment system to cooperatively control the carbon source addition and the internal circulation reflux ratio, and the high-efficiency denitrification operation state is obtained.

[0060] It should be noted that the Modbus RTU standard communication protocol is used to send the generated reflux optimization instructions to the sewage treatment system. After receiving the instructions, a successful reception confirmation frame (including the actual received parameter values, such as reflux pump frequency 46.64 Hz and carbon source addition amount 328.35 kg / h) needs to be returned within 10 seconds. If the confirmation frame is not received or the confirmation parameter deviates from the instruction by > ± 1%, the system automatically triggers a retry mechanism (up to 3 times, with an interval of 5 seconds each time). If the retry fails, an audible and light alarm is immediately triggered. After receiving the feedback confirmation information, the carbon source is added according to the reflux ratio, the control instruction is recalculated every 1 hour to adapt to the water quality changes, and the key data (effluent nitrogen concentration, DO, and carbon source residual COD) are collected every 2 minutes after the execution of the instruction for detection and feedback, so as to realize the high-efficiency denitrification operation state.

[0061] In summary, the present application solves the problems in the prior art that the fixed adjustment of the internal circulation reflux ratio and the carbon source dosage cannot adapt to the dynamic changes of the pollutant load, and that either the carbon source is excessively added (increasing the cost and secondary pollution) or the dosage is insufficient, resulting in incomplete denitrification and low denitrification efficiency. The present application predicts the water quality fluctuation trend, quantifies the regulation lag risk, and generates an internal circulation reflux ratio adjustment scheme in advance; at the same time, the process stability data are combined for closed-loop optimization; the denitrification efficiency fluctuation range is greatly reduced compared with the prior art, and the continuous stable operation time is prolonged. The present application, compared with the prior art in which the carbon source addition and the internal circulation reflux ratio are independently regulated and do not form a synergistic mechanism, realizes deep synergy of the reflux ratio and the carbon source dosage through dynamic coupling analysis of the whole process, ensures that the denitrification reaction is always in the optimal condition, and improves the stability of the denitrification efficiency.

[0062] With reference to Figure 2 The second embodiment of the present application provides a sewage treatment system based on an internal circulation high-efficiency denitrification technology, comprising: A data acquisition module is configured to acquire internal circulation reflux ratio, influent flow rate and nitrogen concentration data, capture water quality fluctuation characteristics according to the influent flow rate and the nitrogen concentration data, and determine a pollutant load level according to the water quality fluctuation characteristics. A data analysis module is configured to analyze a dynamic coupling relationship between the internal circulation reflux ratio and the amount of carbon source to be added according to the pollutant load level, and obtain a carbon source demand matching value. A data prediction module is configured to, if the carbon source demand matching value exceeds a preset matching value threshold, predict a regulation lag risk under a water quality fluctuation trend, and obtain an internal circulation reflux ratio adjustment scheme. A data simulation module is configured to simulate a denitrification reaction process according to the internal circulation reflux ratio adjustment scheme, determine a coefficient of the carbon source dosage, and obtain a real-time correction coefficient. A data updating module is configured to update a synergistic regulation parameter according to the real-time correction coefficient, and obtain an addition control signal. A data comparison module is configured to perform threshold comparison on the addition control signal and the carbon source demand matching value, and fuse the business association of the pollutant load level and the real-time correction coefficient, and obtain an optimized matching coefficient. A data integration module is configured to integrate the dynamic coupling relationship of the internal circulation reflux ratio according to the optimized matching coefficient, and determine an update range of the synergistic regulation parameter. An instruction generation module is configured to update the synergistic regulation parameter according to the update range, acquire system operation state data, generate an instruction, and obtain a reflux optimization instruction. The instruction regulation module is configured to send the backflow optimization instruction to the sewage treatment system, and cooperatively regulate the carbon source addition and the internal circulation backflow ratio, so as to obtain the high-efficiency nitrogen removal operation state.

[0063] It should be noted that the sewage treatment system based on the internal circulation high-efficiency denitrification technology provided by the embodiments of the present application is used to execute all process steps of the sewage treatment method based on the internal circulation high-efficiency denitrification technology provided by the above embodiments, and the working principles and beneficial effects of the two are one-to-one correspondence, thus not being described in detail.

[0064] The embodiments of the present application further provide an electronic device. The electronic device comprises a processor, a memory, and a computer program, such as an algorithm program, stored in the memory and executable on the processor. The processor implements the steps in the above various sewage treatment method embodiments based on the internal circulation high-efficiency denitrification technology when executing the computer program, such as Figure 1 The processor implements the functions of the modules / units in the above various system embodiments when executing the computer program, such as the instruction regulation module.

[0065] For example, the computer program can be divided into one or more modules / units, which are stored in the memory and executed by the processor to complete the present application. The one or more modules / units can be a series of computer program instruction segments capable of completing a specific function, which are used to describe the execution process of the computer program in the electronic device.

[0066] The electronic device can be a desktop computer, a notebook computer, a palm computer, a smart tablet and the like. The electronic device can include, but is not limited to, a processor, a memory. Those skilled in the art can understand that the above components are only examples of the electronic device, and do not constitute a limitation on the electronic device, and can include more or fewer components than the above, or combine certain components, or different components, for example, the electronic device can also include an input / output device, a network access device, a bus and the like.

[0067] The processor can be a central processing unit (CPU), and can also be other general-purpose processors, a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field-programmable gate array (FPGA) or other programmable logic device, discrete gate or transistor logic, discrete hardware components, etc. The general-purpose processor can be a microprocessor or the processor can also be any conventional processor. The processor is a control center of the electronic device, and connects various parts of the electronic device through various interfaces and lines.

[0068] The memory can be used to store the computer program and / or modules, and the processor realizes various functions of the electronic device by running or executing the computer program and / or modules stored in the memory, and calling data stored in the memory. The memory can mainly include a program storage area and a data storage area, wherein the program storage area can store an operating system, at least one application program required by a function (such as a sound playing function, an image playing function, etc.), etc.; and the data storage area can store data created according to the use of the mobile phone (such as audio data, a phone book, etc.), etc. In addition, the memory can include a high-speed random access memory, and can also include a nonvolatile memory, for example, a hard disk, a memory, a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, at least one disk storage device, a flash memory device, or other volatile solid-state memory device.

[0069] The modules / units integrated in the electronic device, if realized in the form of software function units and sold or used as independent products, can be stored in a computer readable storage medium. Based on such understanding, all or part of the processes in the above-mentioned embodiment methods can also be completed by a computer program instructing related hardware, and the computer program can be stored in a computer readable storage medium. The computer program can implement the steps of each method embodiment when executed by a processor. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or some intermediate forms, etc. The computer readable medium can include any entity or system, recording medium, U disk, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electric carrier signal, telecommunication signal, and software distribution medium, etc. that can carry the computer program code. It should be noted that the contents included in the computer readable medium can be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction, for example, in some jurisdictions, according to legislation and patent practice, the computer readable medium does not include electric carrier signals and telecommunication signals.

[0070] It should be noted that the system embodiments described above are only schematic, and the units described as separate components can or can not be physically separated, and the components shown as units can or can not be physical units, that is, they can be located in one place, or distributed on multiple network units. Part or all of the modules can be selected according to actual needs to achieve the purpose of the embodiment. In addition, the connection relationship between the modules in the system embodiment provided by the present application indicates that there is a communication connection between them, which can be realized as one or more communication buses or signal lines. Those skilled in the art can understand and implement it without creative labor.

[0071] The above specific embodiments further illustrate the purpose, technical solutions and beneficial effects of the present application. It should be understood that the above description is only for specific embodiments of the present application and is not intended to limit the protection scope of the present application. It is particularly pointed out that any modification, equivalent replacement, improvement, etc. made by those skilled in the art within the spirit and principles of the present application shall be included in the protection scope of the present application.

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 nitrogen removal 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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