Sewage treatment method and device

Abstract

The invention provides a sewage treatment method and device, and relates to the technical field of sewage treatment.The key points of the technical scheme are that the method comprises the steps that inflow water quality, temperature information and sludge state information are obtained; judging whether the wastewater is low-temperature high-concentration organic matter wastewater or not according to the inlet water quality and temperature information; when the wastewater is judged to be low-temperature high-concentration organic matter wastewater, adjusting operation parameters of each treatment area in the biological reaction tank, namely implementing partitioned dynamic aeration in the biological reaction tank, and adding a microbial activity enhancer according to the water temperature; acquiring a treatment effect monitored in real time, and adjusting the ratio of internal reflux to external reflux according to the treatment effect; and adding a flocculating agent into the biological reaction tank according to the sludge state information so as to improve the stability of sludge floc. The sewage treatment method and device provided by the invention have the advantage that high-concentration organic matter wastewater can be efficiently treated under a low-temperature condition.

Description

Technical Field

[0001] The present application relates to the field of sewage treatment, and more specifically, to a sewage treatment method and device. Background Art

[0002] Industrial park sewage treatment plants often need to treat a variety of mixed wastewaters from different factories. The water quality of these wastewaters fluctuates greatly, the pollutant composition is complex, and the treatment is difficult. Especially under low temperature conditions in winter, it is a challenge to treat high-concentration organic wastewater. Under low temperature conditions, the activity of microorganisms decreases, and the efficiency of traditional biological treatment methods decreases. In order to ensure the treatment effect, the usual practice is to increase the aeration volume, but this will lead to a significant increase in energy consumption. In addition, excessive aeration at low temperatures can easily cause sludge disintegration, increase the content of suspended solids in the effluent, and increase the burden on subsequent membrane treatment units, such as membrane bioreactors (MBRs), resulting in accelerated membrane fouling, shortening the service life of the membrane, and increasing the frequency of backwashing, which ultimately affects the overall treatment efficiency and operating costs. At the same time, the shock load of high-concentration organic wastewater may also exceed the capacity of conventional treatment systems, requiring additional emergency treatment measures. How to efficiently treat high-concentration organic wastewater under low temperature conditions while taking into account multiple factors such as energy consumption, membrane life, and effluent quality is a technical problem that needs to be solved urgently in the current sewage treatment field.

[0003] In view of the above problems, the existing technology needs to be improved urgently. Summary of the invention

[0004] The purpose of the present application is to provide a sewage treatment method and device, which has the advantage of being able to efficiently treat high-concentration organic wastewater under low temperature conditions.

[0005] This application provides a sewage treatment method, and the technical solution is as follows:

[0006] Used to treat high-concentration organic wastewater under low-temperature conditions, including: obtaining influent water quality, temperature information and sludge state information; judging whether it is low-temperature high-concentration organic wastewater according to the influent water quality and temperature information; when it is judged to be low-temperature high-concentration organic wastewater, adjusting the operating parameters of each treatment area in the biological reaction tank, including: implementing zoned dynamic aeration in the biological reaction tank, and adding a microbial activity enhancer according to the water temperature; obtaining real-time monitoring of the treatment effect, and adjusting the ratio of internal reflow and external reflow according to the treatment effect; adding a flocculant to the biological reaction tank according to the sludge state information to improve the stability of the sludge flocs.

[0007] Furthermore, the present application also proposes that the step of adding flocculants to the biological reaction tank to improve the stability of sludge flocs based on the sludge status information includes: obtaining the status information of the sludge monitored in real time; calculating the stability index of the sludge flocs based on the sludge status information; when the stability index is lower than a preset threshold, determining the type and dosage of flocculants to be added; controlling the flocculant dosing device to add the type and dosage of flocculants to the biological reaction tank; after adding the flocculants, obtaining the status information of the sludge monitored in real time again, and calculating the updated stability index; based on the updated stability index, evaluating the flocculant addition effect, and adjusting the subsequent flocculant addition strategy.

[0008] Furthermore, the present application also proposes that the step of obtaining the status information of the sludge monitored in real time includes: receiving data signals from multiple sludge sensors; preprocessing the data signals, including removing outliers and data smoothing; calculating key indicators including sludge concentration and sedimentation performance based on the preprocessed data signals; comparing the calculated key indicators with the preset normal range; when any key indicator exceeds the preset normal range, triggering an alarm signal; and outputting the key indicators and alarm signals as the status information of the sludge.

[0009] Furthermore, the present application also proposes that the step of calculating the stability index of sludge flocs based on the status information of the sludge includes: obtaining the status information of the sludge including sludge concentration and sedimentation performance; inputting the status information of the sludge into a preset stability index calculation model to obtain a preliminary sludge floc stability index; obtaining historical sludge floc stability index data; comparing and analyzing the preliminary sludge floc stability index with historical data; correcting the preliminary sludge floc stability index based on the comparison and analysis results; and outputting the corrected sludge floc stability index as the final calculation result.

[0010] Furthermore, the present application also proposes that the steps of implementing zoned dynamic aeration in the biological reaction tank and adding a microbial activity enhancer according to the water temperature include: obtaining dissolved oxygen concentration and water temperature data of each area of ​​the biological reaction tank; calculating the aeration demand of each area based on the dissolved oxygen concentration data; adjusting the aeration amount of the aerator in each area according to the aeration demand; determining the dosage of the microbial activity enhancer based on the water temperature data; controlling the metering pump to add the dosage of the microbial activity enhancer to the biological reaction tank; monitoring the treatment effect after adding the microbial activity enhancer, including the effluent water quality and sludge activity; and dynamically adjusting the aeration amount and the dosage of the microbial activity enhancer based on the treatment effect.

[0011] Furthermore, the present application also proposes that the step of determining the dosage of the microbial activity enhancer based on the water temperature data includes: obtaining real-time water temperature data of the biological reaction tank; querying a preset water temperature-activity relationship curve based on the real-time water temperature data to obtain the microbial activity level at the current water temperature; calculating the difference between the current microbial activity level and the target activity level; calculating the required dosage of the microbial activity enhancer based on the difference and the preset activity enhancer efficacy parameter; and also includes: comparing the dosage with a preset safety threshold; when the dosage does not exceed the safety threshold, outputting the dosage as the final dosage of the microbial activity enhancer; when the dosage exceeds the safety threshold, using the safety threshold as the final dosage of the microbial activity enhancer and triggering an alarm signal.

[0012] Furthermore, the present application also proposes that the method also includes: monitoring the concentration of organic matter in the inlet water; when it is detected that the concentration of organic matter in the inlet water exceeds a preset threshold, directing part of the high-concentration wastewater into a temporary storage tank; starting the bioreactor of the emergency treatment unit, the bioreactor using a combination of immobilized enzyme technology and membrane bioreactor; using the bioreactor to treat the high-concentration wastewater in the temporary storage tank; mixing the water treated by the bioreactor with the effluent of the main treatment system.

[0013] Furthermore, the present application also proposes that the step of starting the bioreactor of the emergency treatment unit includes: obtaining influent organic matter concentration and temperature data; selecting the most suitable immobilized enzyme formula from a plurality of preset immobilized enzyme formulas based on the influent organic matter concentration and temperature data; loading the selected immobilized enzyme formula into the bioreactor; adjusting the temperature and pH value of the bioreactor so that it is within the optimal activity range of the selected immobilized enzyme; starting the membrane bioreactor and adjusting the membrane flux according to the influent organic matter concentration; monitoring the immobilized enzyme activity and the degree of membrane contamination; and triggering the enzyme replacement or membrane cleaning procedure when it is detected that the immobilized enzyme activity is lower than a preset threshold or the membrane contamination degree exceeds a preset threshold.

[0014] Furthermore, the present application also proposes that a multi-stage immobilized enzyme system is composed of a plurality of the bioreactors, and the method further includes: obtaining operation data of the multi-stage immobilized enzyme system, including the influent organic matter concentration, temperature, enzyme activity, regeneration state of the bioreactors, and the overall treatment efficiency and energy consumption of the system; based on the obtained operation data, establishing a mathematical model of the multi-stage immobilized enzyme system, including: input variables: x(t) = [C(t), T(t), A(t), T_r(t), R(t)] wherein C(t) is the influent organic matter concentration vector, T(t) is the influent temperature, A(t) is the enzyme activity vector of each bioreactor, T_r(t) is the temperature vector of each bioreactor, and R(t) is the regeneration state vector of each bioreactor; output variables: y(t )=[α(t),T_set(t),η(t)]where α(t) is the water inlet ratio vector of each bioreactor, T_set(t) is the temperature set value vector of each bioreactor, and η(t) is the overall treatment efficiency of the system; state equation: dA_i(t) / dt=f(A_i(t),T_i(t),C(t))-k_i*A_i(t)+γ_i*R_i(t)*(A_max-A_i(t))where f() is the enzyme activity change function, k_i is the enzyme inactivation rate constant of the i-th bioreactor, and γ_i is the regeneration efficiency coefficient of the i-th bioreactor; output equation: y(t)=g(x(t),θ)where g() is the nonlinear mapping function and θ is the model parameter set; objective function: max J=w_1*η(t)+w_2*(1-σ(A(t)))-w_3*E(t)+w_4*η^(t+1)wherein, σ(A(t)) is the standard deviation of enzyme activity, E(t) is the energy consumption function, η^(t+1) is the predicted treatment efficiency at the next moment, and w_1, w_2, w_3, and w_4 are weight coefficients; constraint conditions: Σα_i(t)=1, T_min≤T_i_set(t)≤T_max, A_min≤A_i(t)≤A_max, ΣC_j(t)*(1-η(t))≤C_max_outwherein, T_min and T_max are temperature limits, A_min and A_max are enzyme activity limits, and C_max_out is the maximum organic concentration allowed in effluent; according to the mathematical model, the operating parameters of the multi-stage immobilized enzyme system are optimized in real time to improve the treatment effect of high-concentration organic wastewater under low temperature conditions.

[0015] Furthermore, the present application also proposes a sewage treatment device for treating high-concentration organic wastewater under low-temperature conditions, including: an acquisition module for acquiring influent water quality, temperature information and sludge status information; a judgment module for judging whether it is low-temperature and high-concentration organic wastewater based on the influent water quality and temperature information; an execution module for adjusting the operating parameters of each treatment area in the biological reaction tank according to the influent water quality, temperature information and sludge status information when it is judged to be low-temperature and high-concentration organic wastewater, including: implementing zoned dynamic aeration in the biological reaction tank, and adding microbial activity enhancer according to the water temperature; adjusting the ratio of internal reflux and external reflux according to the treatment effect monitored in real time; adding flocculants to the biological reaction tank to improve the stability of sludge flocs according to the sludge properties monitored in real time.

[0016] From the above, it can be seen that the sewage treatment method and device provided in the present application can dynamically adjust the treatment parameters according to the actual situation, improve the activity of microorganisms, stabilize the sludge flocs, and thus efficiently treat high-concentration organic wastewater under low temperature conditions, while taking into account multiple factors such as energy consumption and effluent water quality. It has the advantage of being able to efficiently treat high-concentration organic wastewater under low temperature conditions. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 A flow chart of a sewage treatment method provided for this application.

[0018] Figure 2 A schematic structural diagram of a sewage treatment device provided in this application.

[0019] In the figure: 210, acquisition module; 220, judgment module; 230, execution module. DETAILED DESCRIPTION

[0020] The technical solutions in the present application will be clearly and completely described below in conjunction with the drawings in the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. The components of the present application generally described and shown in the drawings here can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present application provided in the drawings is not intended to limit the scope of the present application for protection, but merely represents the selected embodiments of the present application. Based on the embodiments of the present application, all other embodiments obtained by those skilled in the art without making creative work belong to the scope of protection of the present application.

[0021] In the daily operation of the industrial park sewage treatment plant, the treatment of mixed wastewater from different factories faces severe challenges. The water quality of these wastewaters fluctuates greatly and the types of pollutants are complex, which brings significant difficulties to the treatment process. Especially when treating high-concentration organic wastewater under low temperature conditions in winter, the problem is more prominent. The low temperature environment leads to reduced microbial activity, which directly affects the efficiency of the biological treatment unit. In order to maintain the treatment effect, the conventional practice is to increase the aeration volume, but this method has multiple technical defects: first, the energy consumption increases significantly; second, excessive aeration under low temperature conditions can easily cause sludge disintegration, resulting in an increase in the content of suspended solids in the effluent; finally, the increase in suspended solids will increase the load on the subsequent MBR membrane, accelerate membrane pollution, and require more frequent backwashing, which not only affects the overall treatment efficiency, but also shortens the service life of the membrane. Therefore, how to efficiently treat high-concentration organic wastewater under low temperature conditions in winter, while balancing the treatment effect, energy consumption, membrane life and effluent water quality, has become a technical problem that needs to be solved urgently.

[0022] If this technical problem cannot be effectively solved, the decline in treatment efficiency may result in substandard effluent and violation of environmental regulations. Secondly, the substantial increase in energy consumption will significantly increase operating costs and affect the economic sustainability of the sewage treatment plant. Furthermore, the deterioration of sludge performance may cause secondary pollution, increasing the difficulty and cost of subsequent treatment. Finally, the accelerated pollution and shortened life of the MBR membrane will lead to more frequent membrane replacement, which not only increases maintenance costs, but may also cause temporary shutdown of the treatment system. The cumulative effect of these problems may cause the performance of the entire sewage treatment system to drop sharply and fail to meet increasingly stringent environmental protection requirements.

[0023] In this regard, refer to Figure 1 , the present application proposes a sewage treatment method for treating high-concentration organic wastewater under low temperature conditions, comprising:

[0024] S110, obtaining influent water quality, temperature information and sludge status information;

[0025] S120, judging whether the wastewater is low-temperature and high-concentration organic matter wastewater according to the influent water quality and temperature information;

[0026] S130, when it is determined to be low-temperature and high-concentration organic wastewater, the operating parameters of each treatment area in the biological reaction tank are adjusted, including:

[0027] Implement zoned dynamic aeration in the bioreactor and add microbial activity enhancers according to water temperature;

[0028] Obtain the treatment effect of real-time monitoring, and adjust the ratio of internal reflux and external reflux according to the treatment effect;

[0029] According to the sludge status information, flocculants are added to the biological reactor to improve the stability of the sludge flocs.

[0030] Among them, the influent water quality refers to the concentration and characteristics of various pollutants in the sewage, which can be obtained by online monitoring equipment or laboratory analysis.

[0031] The temperature information refers to the temperature of the sewage, which can be monitored in real time using a temperature sensor.

[0032] Among them, sludge status information refers to the various performance indicators of activated sludge, which can be obtained by using equipment such as sludge concentration meter and sedimentation specific volume meter.

[0033] Among them, zoned dynamic aeration refers to dynamically adjusting the aeration volume according to the actual oxygen demand of each treatment area, which can be achieved by using an online dissolved oxygen monitoring system and variable frequency aeration equipment.

[0034] Among them, microbial activity enhancers refer to additives that can improve the metabolic activity of microorganisms, which can be achieved by using formulas containing specific enzymes or nutritional elements.

[0035] Among them, internal reflux refers to the return of nitrification liquid to the anaerobic zone, and external reflux refers to the return of secondary sedimentation tank sludge to the biological reactor. The reflux ratio can be adjusted by using a reflux pump and a flow meter.

[0036] Among them, flocculants refer to chemical agents that can promote the aggregation of sludge particles, which can be achieved specifically by using inorganic salts or organic polymer flocculants.

[0037] The core innovation of this application is to propose a comprehensive low-temperature, high-concentration organic wastewater treatment method. This method dynamically adjusts the operating parameters of the biological reactor by obtaining influent and sludge information in real time, including implementing zoned dynamic aeration, adding microbial activity enhancers, adjusting the reflux ratio, and adding flocculants. This treatment strategy can effectively deal with problems such as reduced microbial activity and reduced sludge performance under low temperature conditions, while taking into account treatment efficiency and energy consumption control.

[0038] The working principle of this application can be explained in detail as follows:

[0039] First, the influent water quality information is obtained through online monitoring equipment or laboratory analysis, including pollutant indicators such as COD, ammonia nitrogen, and total nitrogen. At the same time, a temperature sensor is used to monitor the influent temperature in real time. For sludge status information, a sludge concentration meter is used to measure the MLSS concentration, and a sedimentation specific volume meter is used to measure the SVI value.

[0040] When the system determines that the influent is low-temperature, high-concentration organic wastewater, a special treatment mode is activated. In the biological reactor, a zoned dynamic aeration strategy is adopted. Specifically, multiple dissolved oxygen online monitoring probes are installed in the aerobic zone. According to the real-time dissolved oxygen data, the operating frequency of the variable frequency aeration equipment is adjusted through the PLC control system to achieve precise aeration.

[0041] At the same time, the dosage of microbial activity enhancer is automatically adjusted according to the inlet water temperature. The activity enhancer can be a composite formula containing specific enzyme preparations and trace elements, and is accurately added to the biological reaction tank through a quantitative pump.

[0042] The system also monitors the effluent quality in real time, including indicators such as COD, ammonia nitrogen, and total nitrogen. According to the treatment effect, the ratio of internal and external reflow is automatically adjusted. Internal reflow is achieved by pumping the nitrification liquid to the anaerobic zone, while external reflow is achieved by pumping the sludge at the bottom of the secondary sedimentation tank back to the biological reactor. The adjustment of the reflow ratio is precisely controlled by a variable frequency pump and an electromagnetic flowmeter.

[0043] In addition, the system will continuously monitor the sludge performance indicators. When the stability of the sludge flocs is found to decrease, the flocculant addition program will be automatically started. The flocculant can be a polyacrylamide polymer flocculant, which is accurately added to the biological reaction tank through a dedicated dosing device.

[0044] The synergistic effect of these measures can effectively improve the efficiency of sewage treatment under low temperature conditions, while optimizing energy consumption and sludge performance. Zoning dynamic aeration ensures the accuracy of oxygen supply and avoids energy waste caused by excessive aeration. The addition of microbial activity enhancers directly improves the metabolic capacity of microorganisms and compensates for the reduced activity caused by low temperature. The dynamic adjustment of the reflow ratio optimizes the hydraulic conditions and nutrient distribution in the biological reactor, and improves the efficiency of nitrogen removal and phosphorus removal. The addition of flocculants improves the sedimentation performance of sludge and reduces the impact of suspended matter on effluent quality and subsequent MBR membranes.

[0045] As a preferred embodiment, the present application can install 5 online dissolved oxygen monitoring probes in the aerobic pool, and divide the aerobic pool into 5 aeration zones. The aeration volume of each zone is independently controlled by a variable frequency fan. The system adjusts the aeration volume between 0.2-0.4m 3 / m 3 ·min to ensure that the dissolved oxygen concentration in each area is maintained within the optimal range of 2-3 mg / L.

[0046] At the same time, the system starts the dosing procedure of the microbial activity enhancer. A composite formula containing specific enzyme preparations and trace elements is selected, and the initial dosage is 5 mg / L. The system monitors the effluent COD every 2 hours and dynamically adjusts the dosage according to the removal efficiency, with the range controlled between 3-8 mg / L.

[0047] For internal and external reflow, the system initially sets the internal reflow ratio to 200% and the external reflow ratio to 100%. The total nitrogen concentration of the effluent is tested every 4 hours. If it exceeds 15 mg / L, the internal reflow ratio is increased by 20%, and the maximum is not more than 300%. The external reflow ratio is adjusted according to the MLSS concentration, and the goal is to maintain the MLSS concentration of the biological pool between 4500-5000 mg / L.

[0048] In terms of sludge performance, the system measures the SVI value once a day. When the SVI value exceeds 150mL / g, the flocculant addition program is started. Cationic polyacrylamide with a molecular weight of 12 million is selected, and the initial dosage is 0.5mg / L. The SVI value is measured every 6 hours. If it still exceeds 130mL / g, the dosage is increased by 0.1mg / L until the SVI value drops below 120mL / g.

[0049] Through this comprehensive treatment plan, the sewage treatment station has stabilized its COD removal rate at over 85% under low temperature and high concentration conditions, and the total nitrogen concentration in the effluent is controlled below 12 mg / L. At the same time, the increase in energy consumption is controlled within 20%, and the cleaning cycle of the MBR membrane is extended from once every 4 hours to once every 8 hours.

[0050] In some of the above embodiments, during the implementation of the present application, there is still the problem of how to improve the stability of sludge flocs to improve the sewage treatment effect.

[0051] In this regard, the present application further proposes obtaining the status information of the sludge monitored in real time; calculating the stability index of the sludge flocs based on the status information of the sludge; when the stability index is lower than a preset threshold, determining the type and dosage of flocculant to be added; controlling the flocculant dosing device to add the type and dosage of flocculant to the biological reaction tank; after adding the flocculant, obtaining the status information of the sludge monitored in real time again, and calculating the updated stability index; based on the updated stability index, evaluating the flocculant addition effect, and adjusting the subsequent flocculant addition strategy.

[0052] This application solves the problem of sludge floc stability by establishing a closed-loop feedback system. First, the sludge state information is obtained through real-time monitoring and converted into a quantifiable stability index. When the stability index is lower than the preset threshold, the system will automatically determine the type and dosage of flocculant to be added, and control the dosing device to add it accurately. After adding, the system will monitor the sludge state again and calculate the updated stability index to evaluate the effect of the addition. Finally, the subsequent flocculant addition strategy is adjusted according to the evaluation results. This method can not only respond to changes in the sludge state in a timely manner, but also optimize the use of flocculants through continuous feedback and adjustment, thereby effectively improving the stability of sludge flocs, thereby improving the overall sewage treatment effect.

[0053] The technical solution of this application involves multiple key features, each of which has its specific implementation method and function.

[0054] Obtaining real-time monitoring of sludge status information can be achieved through a variety of sensors, such as optical sensors, conductivity sensors or ultrasonic sensors. These sensors can be installed at different locations in the bioreactor to obtain comprehensive sludge status data. Specifically, optical sensors can be used to measure sludge concentration and color, conductivity sensors can detect the ion content in sludge, and ultrasonic sensors can be used to measure the sedimentation performance of sludge.

[0055] Calculating the sludge floc stability index is one of the core steps of this application. This can be achieved by building a mathematical model that takes various parameters of the sludge (such as concentration, settling velocity, floc size distribution, etc.) as input and outputs a comprehensive stability index. For example, the following formula can be used:

[0056] Stability index = w1*(sludge concentration / standard concentration)+w2*(sedimentation velocity / standard sedimentation velocity)+w3*(average floc size / standard floc size)

[0057] Among them, w1, w2, and w3 are weight coefficients, which can be adjusted according to actual conditions.

[0058] When the stability index is lower than the preset threshold, the system automatically determines the type and amount of flocculant to be added. This step can be achieved by querying a pre-established database. The database stores the most suitable flocculant type and dosage for different sludge states. The system can select the most suitable flocculant solution from the database based on the current stability index and other relevant parameters.

[0059] Controlling the flocculant dosing device is key to achieving accurate addition. This can be achieved by using a precision metering pump and flow controller. The metering pump can accurately control the rate of flocculant addition based on the dosage calculated by the system, while the flow controller ensures that the flocculant is evenly distributed in the bioreactor.

[0060] After adding the flocculant, the system will again obtain the real-time monitored sludge status information and calculate the updated stability index. This step is similar to the initial monitoring step, but the focus is on observing the changes in the sludge state after the flocculant is added. By comparing the stability index before and after the addition, the effect of the flocculant can be intuitively evaluated.

[0061] Finally, based on the updated stability index, the system evaluates the flocculant addition effect and adjusts the subsequent flocculant addition strategy. This can be achieved through a machine learning algorithm that can continuously optimize the selection and dosage of flocculants based on historical data and current results to achieve the best sludge floc stability.

[0062] There is a close correlation and interaction between these characteristics. For example, the real-time monitoring of sludge status information directly affects the calculation of the stability index, and the stability index determines whether flocculants need to be added and the type and amount of addition. The addition of flocculants will change the state of the sludge, and this change will be fed back to the system through monitoring again, forming a closed-loop control. This closed-loop control mechanism enables the system to dynamically respond to changes in sludge status and continuously optimize the treatment effect.

[0063] The technical solution of the present application has significant advantages in solving the problem of how to improve the stability of sludge flocs to improve the sewage treatment effect. First, through real-time monitoring and rapid response, the present solution can promptly discover and solve the problem of decreased stability of sludge flocs, avoiding the lag and fluctuation of treatment effects that may occur in traditional methods. Secondly, by establishing a correlation between the stability index and the flocculant addition strategy, the present solution achieves precise control of the use of flocculants, which not only ensures the treatment effect, but also avoids economic waste and secondary pollution caused by excessive use of flocculants. Thirdly, through continuous feedback and optimization, the present solution can adapt to different water quality conditions and environmental changes and maintain long-term stable treatment effects. Finally, this intelligent control method greatly reduces the need for manual operation and improves the automation level and operation efficiency of the treatment system.

[0064] As a preferred embodiment, multiple online monitoring sensors can be installed at different positions of the bioreactor, for example, 3 optical sensors are used to measure sludge concentration (measuring range 0-5000 mg / L, accuracy ±1%), 2 conductivity sensors are used to detect ion content (measuring range 0-200 mS / cm, accuracy ±0.5%), and 1 ultrasonic sensor is used to measure sedimentation performance (measuring range 0-10 m / h, accuracy ±2%). These sensors collect data every 5 minutes and transmit the data to the central control system.

[0065] The central control system uses a pre-trained neural network model to calculate the stability index. The model's inputs include sludge concentration, conductivity and settling velocity, and the output is a stability index value between 0 and 100. The preset stability index threshold is 60, and when the calculated index is lower than this value, the system triggers the flocculant addition procedure.

[0066] The flocculant addition system includes three different types of flocculants (cationic polyacrylamide, polyaluminium chloride and polyferric sulfate), each of which is equipped with an independent storage tank and metering pump (the pump has a flow range of 0-100L / h and an accuracy of ±0.1%). The system selects the most suitable flocculant type and dosage from a preset database based on the current stability index and historical data. For example, when the stability index is 55, the system may choose to add 20mg / L of cationic polyacrylamide.

[0067] After adding the flocculant, the system will wait for 30 minutes and then monitor the sludge status and calculate the stability index again. If the new stability index is increased to 65, the system will consider the addition effect to be good and record this data for future decision-making. If the index is still below 60, the system will try to increase the dosage or change the type of flocculant.

[0068] In this way, the present application can achieve precise control and continuous optimization of sludge floc stability, thereby significantly improving the sewage treatment effect. Compared with the traditional method of adding flocculants at a fixed period and fixed dosage, the method of the present application can improve treatment efficiency and economic benefits.

[0069] In some of the above-mentioned embodiments, during the implementation of the present application, there is still a problem of how to obtain sludge status information in real time for use in controlling and adjusting the sewage treatment process.

[0070] In this regard, the present application further proposes that the steps for obtaining real-time monitored sludge status information include: receiving data signals from multiple sludge sensors; preprocessing the data signals, including removing outliers and data smoothing; calculating key indicators including sludge concentration and sedimentation performance based on the preprocessed data signals; comparing the calculated key indicators with the preset normal range; when any key indicator exceeds the preset normal range, triggering an alarm signal; and outputting the key indicators and alarm signals as sludge status information.

[0071] The technical solution proposed in this application realizes the real-time acquisition and effective use of sludge status information through the steps of multi-sensor data collection, data preprocessing, key indicator calculation, indicator comparison and alarm, and status information output. This method can better control the sewage treatment process and improve treatment efficiency and stability.

[0072] Specifically, the technical solution of this application includes the following key features:

[0073] First, the multi-sensor data acquisition system can use multiple types of sensors, such as optical sensors, conductivity sensors, and pressure sensors. These sensors can be distributed in different locations of the biological reactor to comprehensively monitor the status of the sludge. The data collection frequency can be adjusted according to actual needs, and can usually be set to collect data every 5-10 minutes.

[0074] Secondly, in the data preprocessing step, outliers can be removed by using statistical methods, such as the 3σ rule or the quartile rule. Data smoothing can use moving average or exponential smoothing. The choice of these methods can be optimized according to the actual data characteristics.

[0075] Again, the calculation of key indicators involves multiple parameters. For example, sludge concentration can be expressed by suspended solids concentration (MLSS), which is usually in the range of 2000-5000mg / L. Settling performance can be measured by sludge volume index (SVI), and the normal range is usually between 80-120mL / g.

[0076] In addition, the indicator comparison and alarm triggering mechanism can set multiple thresholds. For example, two thresholds can be set: warning level and emergency level. When the indicator exceeds the warning level, the system will issue a reminder; when it exceeds the emergency level, the automatic adjustment mechanism will be triggered.

[0077] Finally, status information output can adopt standardized data formats such as JSON or XML to facilitate data exchange and integration with other systems.

[0078] Multi-sensor data acquisition provides comprehensive raw data for subsequent processing. Data preprocessing ensures data reliability and lays the foundation for accurate calculation of key indicators. Key indicator calculation and comparison directly reflect the real-time status of sludge and provide a basis for timely detection of abnormalities. Alarm triggering mechanism and status information output convert this information into actionable instructions to guide the adjustment of sewage treatment process.

[0079] The technical solution of this application can be implemented according to the following process in practical application:

[0080] First, multiple sludge sensors are installed at different locations in the bioreactor. These sensors may include optical sensors (for measuring sludge concentration), conductivity sensors (for measuring ion concentration) and pressure sensors (for measuring sedimentation performance).

[0081] Next, set up a data acquisition system to regularly receive data signals from these sensors. The data acquisition frequency can be set to once every 10 minutes. The collected raw data may contain some outliers or noise.

[0082] Then, the collected data was preprocessed. The 3σ rule was used to remove outliers, that is, data points that were beyond the range of ±3 times the standard deviation of the mean were considered outliers and removed. The 5-point moving average method was then used to smooth the data to reduce the impact of random fluctuations.

[0083] After pretreatment, calculate key indicators. For example, calculate the MLSS value based on the data of the optical sensor; calculate the SVI value based on the data of the pressure sensor. Assume that the calculated MLSS value is 3500mg / L and the SVI value is 100mL / g.

[0084] Compare the calculated index with the preset normal range. Assume that the normal range of MLSS is set to 2000-5000 mg / L and the normal range of SVI is set to 80-120 mL / g. In this example, both indexes are within the normal range.

[0085] If any indicator exceeds the normal range, the system will trigger an alarm signal. For example, if the MLSS value suddenly drops to 1800mg / L, the system will sound an alarm to inform the operator that the sludge concentration has dropped abnormally.

[0086] Finally, the system packages the calculated key indicators (MLSS = 3500 mg / L, SVI = 100 mL / g) and alarm status (normal) into JSON format data as sludge status information output. This information can be used by other control systems to adjust sewage treatment parameters, such as adjusting the reflow ratio or aeration volume.

[0087] In this way, the technical solution of the present application can obtain sludge status information in real time and accurately, providing reliable data support for the precise control of the sewage treatment process. Compared with traditional single parameter monitoring or regular manual sampling and analysis, the method of the present application has the advantages of strong real-time performance, comprehensive data, and high degree of automation. This not only improves the efficiency and stability of sewage treatment, but also reduces the need for manual operation and reduces operating costs.

[0088] In some of the above embodiments, during the implementation of the present application, there is still a problem of how to accurately calculate the stability index of sludge flocs.

[0089] In this regard, the present application further proposes to obtain sludge status information including sludge concentration and sedimentation performance; input the sludge status information into a preset stability index calculation model to obtain a preliminary sludge floc stability index; obtain historical sludge floc stability index data; compare and analyze the preliminary sludge floc stability index with the historical data; based on the comparison and analysis results, correct the preliminary sludge floc stability index; and output the corrected sludge floc stability index as the final calculation result.

[0090] The technical solution proposed in this application calculates the stability index of sludge flocs through multiple steps. First, the sludge state information is obtained, including sludge concentration and sedimentation performance, which are key parameters for evaluating the stability of sludge flocs. Then, this information is input into a preset calculation model to obtain a preliminary stability index.

[0091] In order to improve the accuracy of the calculation results, the scheme introduces historical data comparison and correction steps. By obtaining historical sludge floc stability index data and comparing the preliminary calculation results with them, potential anomalies or deviations can be found. Based on the comparison and analysis results, the preliminary calculated stability index is corrected to obtain a more accurate final result.

[0092] This method combines real-time data with historical data, taking into account not only the current sludge state but also historical trends and fluctuations, which helps to improve the accuracy and reliability of stability index calculation. By accurately calculating the stability index of sludge flocs, it can provide important basis for subsequent sewage treatment processes, such as determining whether flocculants need to be added and determining the amount of addition.

[0093] The innovation of this solution is the introduction of historical data comparison and correction mechanism, which can effectively reduce the error that may be caused by a single measurement or calculation, and improve the accuracy and reliability of the stability index. At the same time, this method also has a certain degree of adaptability, and can dynamically adjust the calculation results according to the changing trend of historical data, so as to better adapt to various changes in the sewage treatment process.

[0094] The technical solution proposed in this application includes multiple key steps, each of which has its specific implementation method and function.

[0095] Obtaining information on sludge status: This step can be achieved in a variety of ways. For example, online sensors can be used to monitor sludge concentration and settling performance in real time. Another way is to obtain this data through regular sampling and laboratory analysis. Sludge concentration can be expressed as suspended solids concentration (MLSS), while settling performance can be measured by the sludge volume index (SVI).

[0096] Input the sludge status information into the preset stability index calculation model: This model can be a simple model based on an empirical formula or a complex machine learning model. For example, a multivariate linear regression model can be used to output a preliminary stability index using sludge concentration and sedimentation performance as input variables. Another method is to use an artificial neural network to train the model with a large amount of historical data to obtain more accurate prediction results.

[0097] Obtain historical sludge floc stability index data: This can be achieved by establishing and maintaining a historical database. The database should contain stability index data under different operating conditions, as well as corresponding sludge status information. The time span of the database should be long enough to capture seasonal changes and long-term trends.

[0098] Comparison analysis and correction: This step can use a variety of statistical methods. For example, the deviation between the preliminary stability index and the average value of historical data in the recent period can be calculated. If the deviation exceeds the preset threshold, correction is made. Another method is to use time series analysis techniques, such as the ARIMA model, to predict the stability index at the current moment and compare it with the preliminary calculation results.

[0099] Corrected stability index output: The final stability index can be obtained by weighted average, where both the preliminary calculation results and the historical data prediction values ​​are given certain weights. The weights can be dynamically adjusted based on the current operating conditions and the reliability of historical data.

[0100] The accuracy of the sludge state information directly affects the calculation results of the preliminary stability index. At the same time, the quality and quantity of historical data determine the reliability of the comparative analysis. Through this multi-step, multi-data source approach, the present application can more comprehensively evaluate the stability of sludge flocs, thereby improving the accuracy and reliability of the calculation results.

[0101] In some of the above embodiments, during the implementation of the present application, there is still a problem of how to achieve efficient operation of the biological reaction tank under low temperature conditions to treat high-concentration organic wastewater.

[0102] In this regard, the present application further proposes obtaining dissolved oxygen concentration and water temperature data of each area of ​​the biological reaction tank; calculating the aeration demand of each area based on the dissolved oxygen concentration data; adjusting the aeration volume of the aerator in each area according to the aeration demand; determining the dosage of the microbial activity enhancer based on the water temperature data; controlling the metering pump to add the dosage of the microbial activity enhancer to the biological reaction tank; monitoring the treatment effect after adding the microbial activity enhancer, including the effluent water quality and sludge activity; and dynamically adjusting the aeration volume and the dosage of the microbial activity enhancer according to the treatment effect.

[0103] The technical solution of the present application maintains the efficient operation of the biological reactor under low temperature conditions through real-time monitoring, analysis and adjustment, and effectively treats high-concentration organic wastewater. The solution solves the problems of low microbial activity and poor organic degradation efficiency under low temperature conditions by using zoned dynamic aeration and microbial activity enhancers. The dynamic adjustment strategy ensures the stability of the treatment effect and the efficiency of energy utilization. Compared with the traditional method of simply increasing the aeration volume, this method not only guarantees the treatment effect, but also avoids the problems of increased energy consumption and sludge disintegration caused by excessive aeration.

[0104] The technical solution of this application involves several key features, each of which plays an important role in solving the problem of high-concentration organic wastewater treatment under low temperature conditions. First, obtaining dissolved oxygen concentration and water temperature data is the basis of the entire solution and provides necessary parameters for subsequent operations. This can be achieved by installing dissolved oxygen sensors and temperature sensors in various areas of the bioreactor, which can collect data in real time and transmit it to the central control system.

[0105] Secondly, the aeration demand is calculated based on the dissolved oxygen data and the aeration volume is adjusted. This step can be achieved through a preset algorithm. For example, when the dissolved oxygen concentration is lower than 2 mg / L, the aeration volume is increased; when the dissolved oxygen concentration is higher than 4 mg / L, the aeration volume is reduced. The aerator can use frequency conversion control to achieve precise aeration volume adjustment.

[0106] Thirdly, determine and add microbial activity enhancers based on water temperature data. A relationship model between water temperature and microbial activity can be established. When the water temperature is below 15°C, the activity enhancer is added. The types of enhancers can include enzyme preparations, nutrient salts or specific microbial strains. The dosage can vary according to the water temperature. For example, the dosage increases by 10% for every 1°C decrease in water temperature.

[0107] In addition, monitoring the treatment effect is achieved by detecting the effluent water quality and sludge activity. Online COD analyzers and sludge activity meters can be used to monitor these parameters in real time. The aeration volume and enhancer dosage are dynamically adjusted according to the treatment effect to form a closed-loop control system. For example, if the effluent COD exceeds the standard, the aeration volume and enhancer dosage can be increased; if the sludge activity decreases, the enhancer dosage can be increased.

[0108] Through real-time monitoring, analysis and adjustment, this solution can maintain the efficient operation of the biological reactor under low temperature conditions and effectively treat high-concentration organic wastewater. Compared with traditional methods, the solution of this application can not only ensure the treatment effect, but also optimize energy utilization and avoid the problems caused by excessive aeration.

[0109] Specifically, an embodiment of the present application is as follows:

[0110] In a sewage treatment plant in an industrial park, the biological reaction tank is divided into three areas: anaerobic zone, anoxic zone and aerobic zone. Dissolved oxygen sensors and temperature sensors are installed in each area, and data is collected every 5 minutes and transmitted to the central control system.

[0111] When the inlet water temperature is detected to be lower than 15°C and the COD concentration exceeds 500mg / L, the system automatically starts the low-temperature high-concentration wastewater treatment mode. First, the system calculates the aeration demand based on the dissolved oxygen data of each area. For example, in the aerobic zone, if the dissolved oxygen concentration is lower than 2mg / L, the system will increase the aeration volume; if it is higher than 4mg / L, the aeration volume will be reduced. The aerator adopts variable frequency control, which can accurately adjust the aeration volume, ranging from 10m 3 / h to 100m 3 / h.

[0112] At the same time, the system determines the dosage of microbial activity enhancer based on water temperature data. A compound enzyme preparation is used. When the water temperature is between 10-15℃, the dosage is 0.5g / m 3 When the water temperature is lower than 10℃, the dosage increases to 0.8g / m 3 The enhancer is accurately added to the biological reaction tank through a quantitative pump.

[0113] The system continuously monitors the treatment effect, including the use of an online COD analyzer to monitor the effluent quality and a respirometer to monitor the sludge activity. If the effluent COD exceeds 60 mg / L, the system will increase the aeration rate by 10% and the enhancer dosage by 20%. If the sludge activity index (SOUR) is lower than 10 mg / L, the system will increase the aeration rate by 10% and the enhancer dosage by 20%. 2 / gMLSS·h, the system will increase the dosage of enhancer by 30%.

[0114] Through this dynamic adjustment strategy, when the sewage treatment plant treats high-concentration organic wastewater (influent COD of about 800 mg / L) in winter (water temperature of about 8°C), the effluent COD is stabilized below 50 mg / L, saving about 20% of energy consumption compared with the traditional operation mode. At the same time, it avoids the problem of sludge disintegration and reduces the cleaning frequency of the MBR membrane by 30%.

[0115] When faced with low-temperature, high-concentration wastewater, traditional methods usually simply increase the amount of aeration, which not only leads to a significant increase in energy consumption, but may also cause sludge disintegration. The present application ensures the treatment effect and optimizes energy utilization by precisely controlling the aeration volume and combining the use of microbial activity enhancers. In addition, the dynamic adjustment strategy of the present application can be adjusted in a timely manner according to real-time monitoring data. Compared with the traditional method of fixed parameter operation, it can better adapt to fluctuations in water quality and temperature and ensure the stability of the treatment effect. This method not only solves the problem of treating high-concentration organic wastewater under low temperature conditions, but also improves the operating efficiency and stability of the entire system.

[0116] In some of the above embodiments, during the implementation of the present application, there is still the problem of how to determine the dosage of the microbial activity enhancer according to the water temperature data to improve the treatment effect of high-concentration organic wastewater under low temperature conditions.

[0117] In this regard, the present application further proposes obtaining real-time water temperature data of the biological reaction tank; based on the real-time water temperature data, querying the preset water temperature-activity relationship curve to obtain the microbial activity level at the current water temperature; calculating the difference between the current microbial activity level and the target activity level; based on the difference and the preset activity enhancer efficacy parameters, calculating the required microbial activity enhancer dosage; comparing the dosage with a preset safety threshold; when the dosage does not exceed the safety threshold, outputting the dosage as the final microbial activity enhancer dosage; when the dosage exceeds the safety threshold, using the safety threshold as the final microbial activity enhancer dosage, and triggering an alarm signal.

[0118] The technical solution of the present application uses a series of steps to accurately calculate and control the dosage of microbial activity enhancers to solve the problem of poor treatment effect of high-concentration organic wastewater under low temperature conditions. The core of the solution is to establish the relationship between water temperature and microbial activity, and dynamically adjust the dosage of enhancers through real-time monitoring and calculation. At the same time, by setting a safety threshold, it not only ensures the treatment effect, but also avoids the negative impact that may be caused by excessive addition. This method can optimize the use of agents and reduce operating costs while ensuring the treatment effect.

[0119] The technical solution of this application involves multiple key features, each of which has its specific implementation method and function. First, obtaining the real-time water temperature data of the biological reaction tank can be achieved by installing temperature sensors at different positions in the reaction tank. These sensors can be thermocouples, thermistors or optical fiber temperature sensors, etc. In order to ensure the accuracy and representativeness of the data, a method of multi-point temperature measurement and averaging can be adopted.

[0120] The water temperature-activity relationship curve is one of the cores of this solution and can be obtained through laboratory research or historical operation data analysis. This curve may be nonlinear because the relationship between microbial activity and temperature usually presents an inverted U-shaped curve. The storage and query of the curve can be achieved through a database or expressed by a mathematical function. For example, a polynomial fit or a piecewise function can be used to describe this relationship.

[0121] Calculating the difference between the current microbial activity level and the target activity level is a key step in determining how much activity needs to be increased. The target activity level can be set based on treatment requirements and historical experience, or it can be a dynamic value that is adjusted as the influent water quality and treatment requirements change. The difference can be calculated by simple subtraction, or a weighting factor can be considered to reflect the difficulty of increasing activity in different temperature ranges.

[0122] The core algorithm of this scheme is to calculate the dosage based on the difference and the preset activity enhancer efficacy parameters. The activity enhancer efficacy parameters can be determined by laboratory tests or field tests, which reflect how much microbial activity can be improved by a unit enhancer. The calculation formula may be nonlinear because the effect of the enhancer may be saturated. For example, the following formula can be used:

[0123] Dosage = k*(1-e^(-α*difference))

[0124] Where k and α are constants determined according to the properties of the enhancer.

[0125] The setting of the safety threshold is an important guarantee to ensure the safe operation of the system. This threshold can be determined based on the properties of the enhancer, the capacity of the reaction tank, the tolerance of the microorganisms and other factors. When the calculated dosage exceeds the safety threshold, the system will automatically limit the dosage to a safe range and trigger an alarm signal. The alarm signal can be an audible and visual alarm, or a text message or email notification to the operator.

[0126] The technical solution of the present application can be further optimized and expanded in practical applications. For example, a machine learning algorithm can be introduced to continuously optimize the water temperature-activity relationship curve and the activity enhancer performance parameters by analyzing historical operation data. It is also possible to consider integrating the system with other treatment units such as aeration systems, reflux systems, etc. to achieve overall optimization control.

[0127] As a preferred embodiment, the present application can be implemented in a sewage treatment plant in an industrial park. The treatment plant has a daily treatment capacity of 50,000 cubic meters and mainly treats mixed wastewater from various factories. In winter, when the inlet water temperature drops below 15°C, the system automatically starts the microbial activity enhancement control module.

[0128] Specifically, the water temperature is first monitored in real time by 10 temperature sensors distributed at various locations in the bioreactor, and the data is recorded every 5 minutes and the average value is taken. Then, the system calculates the current microbial activity level based on the pre-established water temperature-activity relationship curve. For example, when the water temperature is 12°C, the microbial activity level obtained by the query is 60% of the normal state.

[0129] Further, the system compares the current activity level with the preset target activity level (e.g., 80%) and calculates that the difference in activity that needs to be increased is 20%. Based on the predetermined activity enhancer efficacy parameters (e.g., each gram of enhancer can increase the activity by 1%), the system calculates that the amount of enhancer that needs to be added is 20 grams per cubic meter.

[0130] Therefore, the system compares the calculated dosage with the preset safety threshold (e.g. 30 g / m3). In this example, since the calculated dosage does not exceed the safety threshold, the system directly outputs 20 g / m3 as the final dosage. The control system then sends instructions to the metering pump to accurately control the dosage of the enhancer.

[0131] By implementing the technical solution of this application, the sewage treatment plant still maintains a high treatment efficiency during the low temperature period in winter. Compared with the traditional method, this application not only improves the treatment effect, but also avoids the increase in energy consumption and sludge disintegration caused by excessive aeration. At the same time, due to the precise control of the dosage of the enhancer, the cost of the agent is reduced and the potential impact on the environment is reduced.

[0132] The technical solution of the present application has significant advantages over the prior art. Traditional methods usually adopt a fixed dosage or manual adjustment based on experience, which is difficult to adapt to the dynamic changes of water temperature and water quality. The present application realizes the dynamic optimization of the dosage of the enhancer through real-time monitoring and precise calculation. In addition, the present application introduces the concept of safety threshold, which effectively prevents the negative impact that may be caused by excessive addition and improves the safety and stability of the system. This precise control not only improves the treatment effect, but also optimizes the use of reagents, reduces operating costs, and reflects high creativity and practical value.

[0133] In some of the above-mentioned embodiments, during the implementation of the present application, there is still the problem of sudden exceeding of the standard of high-concentration organic wastewater under low temperature conditions.

[0134] In this regard, the present application further proposes monitoring the concentration of organic matter in the inlet water; when it is detected that the concentration of organic matter in the inlet water exceeds a preset threshold, directing part of the high-concentration wastewater into a temporary storage tank; starting the bioreactor of the emergency treatment unit, the bioreactor adopts a combination of immobilized enzyme technology and membrane bioreactor; using the bioreactor to treat the high-concentration wastewater in the temporary storage tank; mixing the water treated by the bioreactor with the effluent of the main treatment system.

[0135] The technical solution of this application effectively solves the problem of sudden excessive concentration of high-concentration organic wastewater under low temperature conditions by introducing an emergency treatment unit. The core of this solution is the combination of immobilized enzyme technology and membrane bioreactor, which can maintain efficient treatment capacity under low temperature conditions and improve the stability and reliability of the system.

[0136] Specifically, the technical solution of this application includes the following key steps:

[0137] First, by real-time monitoring of the organic matter concentration in the influent, water quality abnormalities can be detected in a timely manner. When the influent organic matter concentration is detected to exceed the preset threshold, the system will automatically divert part of the high-concentration wastewater to a temporary storage tank. This step can prevent high-concentration wastewater from directly impacting the main treatment system, avoiding a sharp decline in treatment effect.

[0138] Secondly, the bioreactor of the emergency treatment unit is started. The bioreactor uses a combination of immobilized enzyme technology and membrane bioreactor. Immobilized enzyme technology can maintain high catalytic activity under low temperature conditions, while membrane bioreactor can effectively intercept biomass and improve treatment efficiency. This combination can not only cope with sudden high-concentration organic wastewater, but also maintain a stable treatment effect under low temperature conditions.

[0139] In practical applications, enzyme immobilization can be achieved in a variety of ways, such as by embedding, cross-linking or adsorption. The carrier can be made of porous materials, such as silica gel, activated carbon or polymer materials. Membrane bioreactors can use hollow fiber membranes or flat membranes, and the membrane pore size can be selected according to the treatment requirements, usually in the range of 0.01-0.1μm.

[0140] The operating parameters of the bioreactor need to be dynamically adjusted according to the influent water quality and temperature. For example, when the temperature is below 10°C, the dosage of the immobilized enzyme can be appropriately increased, while the membrane flux can be reduced to reduce membrane fouling. When the organic matter concentration exceeds 5000 mg / L, a multi-stage series connection can be used to improve the treatment efficiency.

[0141] When using bioreactors to treat high-concentration wastewater in temporary storage tanks, batch dosing can be adopted. The treatment time of each batch can be adjusted according to the wastewater concentration and temperature, usually within the range of 2-6 hours. During the treatment process, it is necessary to monitor the effluent quality in real time, including COD, ammonia nitrogen and other indicators, to ensure that the treatment effect reaches the expected goal.

[0142] Finally, the water treated by the bioreactor is mixed with the effluent from the main treatment system. This step can further stabilize the effluent quality and ensure that the final discharge meets the standards. The mixing ratio can be dynamically adjusted according to the water quality of the two streams, usually in the range of 1:5 to 1:10.

[0143] Through the above technical scheme, the present application can effectively deal with the problem of sudden excessive concentration of high-concentration organic wastewater under low temperature conditions. Compared with traditional biological treatment methods, the present application can respond to the wastewater exceeding the standard at the first time through real-time monitoring and automatic diversion mechanism, avoiding the impact on the main treatment system. Immobilized enzyme technology can maintain high activity under low temperature conditions, overcoming the defect of reduced efficiency of conventional biological treatment methods at low temperatures. The membrane bioreactor can effectively intercept biomass, improve the system's impact resistance and effluent stability. By adjusting the type and dosage of immobilized enzymes, as well as the operating parameters of the membrane bioreactor, it can adapt to organic wastewater of different types and concentrations. Compared with traditional emergency treatment methods (such as increasing the volume of the aeration tank), the emergency treatment unit of the present application has a small footprint and is more suitable for scenarios with limited space. Immobilized enzyme technology can still maintain high efficiency under low temperature conditions, reducing the need for additional heating and aeration, thereby reducing energy consumption.

[0144] In the specific implementation, the following embodiments may be considered:

[0145] In winter, a sewage treatment station in an industrial park received a batch of wastewater containing high concentrations of organic matter. The COD concentration of the inlet water suddenly increased to 8000mg / L, and the water temperature dropped to 8℃. After the system detected this abnormality, it immediately started the emergency treatment process. First, 50% of the high-concentration wastewater was introduced into a 500m 3 At the same time, the bioreactor of the emergency treatment unit was started, which was composed of immobilized lipase and hollow fiber membrane.

[0146] The immobilized lipase was prepared by sodium alginate embedding method, the enzyme activity was 500U / g, and the dosage was 50g / m 3 The membrane flux of the hollow fiber membrane was set to 15 L / (m 2 ·h). The effective volume of the bioreactor is 100m 3 The reactor was operated in an intermittent manner, with each batch processing time of 4 hours. During the processing, the pH value in the reactor was maintained at 7.0-7.5, and the dissolved oxygen concentration was maintained at 3-4 mg / L.

[0147] After 24 hours of continuous operation, the COD of the effluent from the emergency treatment unit dropped to 800 mg / L. This part of the treated water was mixed with the effluent from the main treatment system at a ratio of 1:8, and the final effluent COD was stabilized below 100 mg / L, meeting the discharge standard.

[0148] In this way, this application successfully dealt with the problem of sudden excessive low-temperature and high-concentration organic wastewater, ensuring the normal operation of the treatment station and the compliance of the effluent with the standard. Compared with traditional response methods, this application not only avoids the impact on the main system, but also greatly reduces energy consumption and the use of chemicals, reflecting good economic and environmental benefits.

[0149] In general, this application has effectively solved the technical problem of sudden excessive concentration of high-concentration organic wastewater under low temperature conditions by innovatively combining immobilized enzyme technology and membrane bioreactor. This solution not only improves the resilience and treatment efficiency of the sewage treatment system, but also has the advantages of energy saving and environmental protection. This technical solution provides new ideas and reliable technical support for industrial park sewage treatment stations to cope with complex water quality fluctuations.

[0150] In some of the above-mentioned embodiments, during the implementation of the present application, there is still a problem of how to start the bioreactor in the emergency treatment unit to treat high-concentration organic wastewater.

[0151] In this regard, the present application further proposes obtaining influent organic matter concentration and temperature data; selecting the most suitable immobilized enzyme formula from a plurality of preset immobilized enzyme formulas based on the influent organic matter concentration and temperature data; loading the selected immobilized enzyme formula into the bioreactor; adjusting the temperature and pH value of the bioreactor so that it is within the optimal activity range of the selected immobilized enzyme; starting the membrane bioreactor and adjusting the membrane flux based on the influent organic matter concentration; monitoring the immobilized enzyme activity and the degree of membrane fouling; and triggering the enzyme replacement or membrane cleaning procedure when it is detected that the immobilized enzyme activity is lower than a preset threshold or the membrane fouling degree exceeds a preset threshold.

[0152] The technical solution of this application provides an efficient and flexible solution for treating high-concentration organic wastewater by combining immobilized enzyme technology and membrane bioreactor. Immobilized enzyme technology can select the most suitable enzyme formula for different influent characteristics to improve treatment efficiency; membrane bioreactor can further improve effluent quality. Through real-time monitoring and timely maintenance, the system can operate stably for a long time, effectively solving the problem of high-concentration organic wastewater treatment. This method can not only cope with water quality fluctuations, but also reduce energy consumption and extend equipment life while ensuring treatment effects.

[0153] The technical solution of this application involves multiple key features, each of which has multiple possible implementation methods:

[0154] Obtaining influent organic matter concentration and temperature data: Data can be obtained in real time through online monitoring instruments or through regular sampling and analysis. Real-time monitoring can use organic matter concentration sensors and temperature sensors, and data can be collected and processed through the SCADA system. Regular sampling and analysis can be measured using a COD rapid tester and a thermometer.

[0155] Select the most suitable immobilized enzyme formula: A database can be established, containing the activity data of different immobilized enzyme formulas under various temperatures and organic matter concentration conditions. Based on the acquired influent data, the most suitable formula can be automatically selected through the algorithm. Another method is to use a machine learning model to train the model with historical data and predict the best formula.

[0156] Loading the immobilized enzyme formula: An automated loading system can be used to pump the selected immobilized enzyme formula into the bioreactor through a pipeline. Alternatively, a modular design can be used to pre-load immobilized enzymes of different formulas into replaceable modules, allowing modules to be quickly replaced as needed.

[0157] Adjusting reactor temperature and pH: Temperature regulation can be achieved through heating or cooling systems, such as electric heaters or heat exchangers. pH regulation can be achieved through automatic acid or alkali dosing systems. PID control algorithms can be used to automatically adjust temperature and pH based on real-time monitoring data to keep them within the optimal range.

[0158] Start the membrane bioreactor and adjust the membrane flux: A variable frequency pump control system can be used to automatically adjust the membrane flux according to the influent organic matter concentration. Another method is to use an intelligent control system to dynamically optimize the membrane flux by combining multiple parameters such as influent concentration and membrane pressure difference.

[0159] Monitoring enzyme activity and membrane fouling: Enzyme activity can be monitored indirectly by measuring the conversion rate of specific substrates. The degree of membrane fouling can be monitored by changes in membrane pressure difference or membrane flux. Optical sensors can be used to monitor the fouling of the membrane surface in real time.

[0160] Triggering enzyme replacement or membrane cleaning procedures: You can set up automated procedures to automatically start enzyme replacement or membrane cleaning procedures when monitoring parameters reach preset thresholds. You can also use predictive maintenance strategies to analyze historical data and current trends to predict in advance when replacement or cleaning is needed and optimize maintenance plans.

[0161] The influent organic matter concentration and temperature data directly affect the selection of immobilized enzyme formula, and the selected formula determines the optimal range of reactor temperature and pH value. The operating parameters of the membrane bioreactor need to be adjusted according to the water quality characteristics after the immobilized enzyme treatment. The monitoring results of enzyme activity and membrane fouling will be fed back to the operation control of the entire system, affecting the enzyme formula selection and membrane flux adjustment.

[0162] Through this close connection and interaction, the technical solution of the present application can achieve accurate treatment of high-concentration organic wastewater. The system can quickly adjust the treatment strategy according to the influent characteristics to ensure the treatment effect while optimizing energy consumption and equipment life. For example, when a sudden increase in the influent organic concentration is detected, the system will automatically select a more active immobilized enzyme formula while reducing the membrane flux to ensure the treatment effect. This dynamic adjustment capability enables the system to maintain a stable and efficient treatment effect when faced with complex and changeable wastewater characteristics.

[0163] In the specific implementation process, the technical solution of this application can be operated as follows:

[0164] First, the influent data is acquired in real time through the online organic matter concentration sensor and temperature sensor. Assume that the influent organic matter concentration is 5000 mg / L and the temperature is 15°C.

[0165] The system then selects the most suitable formulation from a database of preset immobilized enzyme formulations. In this case, the system may select a low-temperature resistant, highly active immobilized enzyme formulation, such as a composite immobilized enzyme formulation containing a cold-adapted enzyme.

[0166] After the formulation is selected, the automated loading system pumps the formulation into the bioreactor. At the same time, the reactor's temperature control system adjusts the temperature to 20°C (assuming this is the optimal activity temperature for the selected enzyme), and the pH adjustment system adjusts the pH to 7.5 (assuming this is the optimal pH for the selected enzyme).

[0167] Next, the membrane bioreactor was started. Considering the high concentration of influent water, the system was initially set to have a membrane flux of 15 L / (m 2 ·h), which is lower than the 20-30L / (m 2 h) to prevent membrane fouling.

[0168] The system continuously monitors the activity of the immobilized enzyme and the degree of membrane fouling. Assume that after 48 hours of detection, the activity of the immobilized enzyme drops to 80% of the initial value, but is still above the preset 70% replacement threshold, and the system continues to operate. At the same time, the membrane pressure difference rises to 30kPa, which is lower than the preset 50kPa cleaning threshold, so the cleaning procedure is not triggered for the time being.

[0169] The system fine-tunes operating parameters based on these monitoring data. For example, the reactor temperature is slightly increased to 21°C to compensate for the slight decrease in enzyme activity, while the membrane flux is adjusted to 18L / (m 2 h) to improve processing efficiency.

[0170] In this way, the technical solution of the present application can dynamically adjust the processing strategy according to the actual situation, while ensuring the processing effect, optimizing the system operation and extending the life of the equipment.

[0171] Compared with the prior art, the present application selects the most suitable immobilized enzyme formula, so that the system can better adapt to different influent characteristics, rather than relying on a single treatment method. Immobilized enzyme technology can maintain high activity at lower temperatures, solving the problem of reduced efficiency of traditional biological treatment under low temperature conditions. The use of membrane bioreactors improves the stability of effluent quality, while the strategy of dynamically adjusting membrane flux effectively extends the service life of the membrane. Through real-time monitoring and automatic adjustment, the system can maintain optimal operating conditions under different conditions, reducing the need for manual intervention.

[0172] In some of the above-mentioned embodiments, during the implementation of the present application, there is still a technical problem of how to solve the poor treatment effect of high-concentration organic wastewater under low temperature conditions.

[0173] In this regard, the present application further proposes a method for forming a multi-stage immobilized enzyme system with multiple bioreactors. The operation data of the multi-stage immobilized enzyme system is obtained, including the influent organic matter concentration, temperature, enzyme activity, regeneration state of the bioreactors, and the overall treatment efficiency and energy consumption of the system;

[0174] Based on the obtained operation data, a mathematical model of the multi-stage immobilized enzyme system was established, including:

[0175] Input variables: x(t) = [C(t), T(t), A(t), T_r(t), R(t)]

[0176] Among them, C(t) is the influent organic matter concentration vector, T(t) is the influent temperature, A(t) is the enzyme activity vector of each bioreactor, T_r(t) is the temperature vector of each bioreactor, and R(t) is the regeneration state vector of each bioreactor;

[0177] Output variables: y(t) = [α(t), T_set(t), η(t)]

[0178] Among them, α(t) is the water inlet ratio vector of each bioreactor, T_set(t) is the temperature set value vector of each bioreactor, and η(t) is the overall treatment efficiency of the system;

[0179] State equation: dA_i(t) / dt=f(A_i(t),T_i(t),C(t))-k_i*A_i(t)+γ_i*R_i(t)*(A_max-A_i(t))

[0180] Wherein, f() is the enzyme activity change function, k_i is the enzyme inactivation rate constant of the i-th bioreactor, and γ_i is the regeneration efficiency coefficient of the i-th bioreactor;

[0181] Output equation: y(t)=g(x(t),θ)

[0182] Among them, g() is a nonlinear mapping function, and θ is a model parameter set;

[0183] Objective function:

[0184] Among them, σ(A(t)) is the standard deviation of enzyme activity, E(t) is the energy consumption function, is the predicted processing efficiency at the next moment, w_1, w_2, w_3, w_4 are weight coefficients;

[0185] Constraints: Σα_i(t)=1, T_min≤T_i_set(t)≤T_max, A_min≤A_i(t)≤A_max, ΣC_j(t)*(1-η(t))≤C_max_out

[0186] Among them, T_min and T_max are temperature limits, A_min and A_max are enzyme activity limits, and C_max_out is the maximum organic matter concentration allowed in the effluent;

[0187] According to the mathematical model, the operating parameters of the multi-stage immobilized enzyme system are optimized in real time to improve the treatment effect of high-concentration organic wastewater under low temperature conditions.

[0188] This application uses a multi-stage immobilized enzyme system to treat high-concentration organic wastewater under low temperature conditions. The system consists of multiple bioreactors, each of which is loaded with immobilized enzymes. The core of this solution is to establish a complex mathematical model to describe and optimize the operation of the system.

[0189] The input variables of the model include these key factors, and the output variables are the water inlet ratio of each reactor, the temperature set point and the overall treatment efficiency of the system. The dynamic changes of enzyme activity are described by the state equation, taking into account the inactivation and regeneration process of the enzyme. The objective function comprehensively considers the treatment efficiency, the balance of enzyme activity, energy consumption and the prediction of future treatment efficiency. The constraints ensure that the system operates within a reasonable range.

[0190] Through this mathematical model, the system can optimize operating parameters in real time, such as adjusting the water inlet ratio and temperature setting value of each reactor to adapt to different water inlet conditions and ambient temperatures, thereby improving the treatment effect of high-concentration organic wastewater under low temperature conditions.

[0191] The advantage of this method is that it can dynamically adapt to environmental changes, balance treatment efficiency and energy consumption, and take into account the maintenance of enzyme activity, which is conducive to the long-term stable operation of the system. Compared with the traditional fixed parameter operation mode, this real-time optimization method based on mathematical models can better cope with the challenges of low-temperature and high-concentration wastewater treatment.

[0192] The innovation of this solution is to combine the multi-stage immobilized enzyme system with a complex mathematical model to achieve intelligent and refined control of the wastewater treatment process. Through real-time data collection and model calculation, the system can maintain efficient processing capacity under low temperature conditions, while optimizing energy use and extending the service life of the enzyme, thereby improving the economy and sustainability of the entire treatment system.

[0193] The multi-stage immobilized enzyme system of the present application is composed of multiple bioreactors. Each bioreactor can use different types of immobilized enzymes to adapt to different pollutants and environmental conditions. For example, the first-stage reactor can use immobilized lipase to treat high-concentration oil pollutants; the second-stage reactor can use immobilized protease to degrade protein pollutants; the third-stage reactor can use immobilized cellulase to treat difficult-to-degrade cellulose substances.

[0194] The core of the system is a mathematical model based on real-time data. The model includes input variables, output variables, state equations, output equations, objective functions and constraints. The input variable x(t) includes the influent organic matter concentration vector C(t), influent temperature T(t), enzyme activity vector A(t) of each bioreactor, temperature vector T_r(t) of each bioreactor and regeneration state vector R(t) of each bioreactor. These variables fully reflect the operating status and environmental conditions of the system.

[0195] The output variables y(t) include the water inlet ratio vector α(t) of each bioreactor, the temperature set value vector T_set(t) of each bioreactor, and the overall treatment efficiency η(t) of the system. These variables are the key parameters that need to be optimized in the system.

[0196] The state equation describes the dynamic change process of enzyme activity. In the equation, f() represents the enzyme activity change function, k_i represents the enzyme inactivation rate constant of the i-th bioreactor, and γ_i represents the regeneration efficiency coefficient of the i-th bioreactor. This equation takes into account the natural attenuation of enzyme activity over time, the influence of environmental factors, and the contribution of the regeneration process.

[0197] The output equation y(t) = g(x(t), θ) uses a nonlinear mapping function g() to map the input variables to the output variables, where θ is the model parameter set. This equation reflects the complex nonlinear characteristics of the system.

[0198] The objective function takes into account multiple aspects: w_1*η(t) represents the pursuit of overall processing efficiency; w_2*(1-σ(A(t))) represents the requirement for the balance of enzyme activity in each reactor; -w_3*E(t) represents the control of energy consumption; w_4*η^(t+1) represents the prediction and optimization of the processing efficiency at the next moment. By adjusting the weight coefficients w_1, w_2, w_3, and w_4, different objectives can be balanced according to actual needs.

[0199] The constraints ensure that the system operates within a reasonable range. For example, Σα_i(t)=1 ensures the rationality of the inlet water distribution; T_min≤T_i_set(t)≤T_max limits the range of the temperature setting value; A_min≤A_i(t)≤A_max ensures that the enzyme activity is within the effective range; ΣC_j(t)*(1-η(t))≤C_max_out limits the maximum concentration of organic matter in the effluent.

[0200] Based on this mathematical model, the system can optimize operating parameters in real time. For example, when a decrease in inlet water temperature is detected, the model may recommend increasing the temperature setpoints of certain reactors while adjusting the inlet water allocation ratio to introduce more wastewater to reactors that maintain higher activity. Or, when the enzyme activity of a certain reactor decreases, the model may recommend starting a regeneration procedure for that reactor and temporarily reducing its inlet water ratio.

[0201] This real-time optimization method based on mathematical models has significant advantages. First, it can quickly respond to environmental changes, such as temperature fluctuations or changes in influent concentration, thereby maintaining the stability and efficiency of the system. Second, by comprehensively considering treatment efficiency, energy consumption and enzyme activity, the system can find the best balance between multiple goals and improve overall economic efficiency. Furthermore, predictive optimization can respond to possible problems in advance, such as preventing a sharp drop in enzyme activity or a sudden drop in treatment efficiency.

[0202] As a specific example, consider a multi-stage immobilized enzyme system consisting of three bioreactors. The first reactor uses immobilized lipase, which is mainly used to treat oil pollutants; the second reactor uses immobilized protease, which is used to degrade protein pollutants; and the third reactor uses immobilized cellulase, which is used to treat difficult-to-degrade cellulose substances.

[0203] The system first obtains real-time operation data. Assume that the current influent organic matter concentration C(t) = [500, 300, 200] mg / L, representing the concentrations of oil, protein and cellulose respectively; influent temperature T(t) = 10°C; enzyme activity of the three reactors A(t) = [80%, 75%, 85%]; reactor temperature T_r(t) = [15°C, 18°C, 20°C]; regeneration state R(t) = [0, 0, 0], indicating that no reactor is currently being regenerated.

[0204] Based on these data, the mathematical model calculates the optimal operating parameters. For example, the model may recommend adjusting the influent ratio α(t) to [0.4, 0.3, 0.3], that is, 40% of the wastewater is introduced into the first reactor, 30% into the second reactor, and 30% into the third reactor. At the same time, the model may recommend adjusting the reactor temperature set value T_set(t) to [18°C, 20°C, 22°C] to improve enzyme activity.

[0205] The system adjusts its operating state according to these optimized parameters and continuously monitors the treatment effect. Assume that after a period of time, the overall treatment efficiency η(t) of the system reaches 85% and the energy consumption E(t) is 100kWh / d. The model will continue to optimize based on these new data. If it is found that the enzyme activity of the second reactor begins to decrease, it may recommend starting the regeneration program of the reactor and adjust the water distribution accordingly.

[0206] Through this continuous real-time optimization, the system is able to maintain efficient processing capabilities under low temperature conditions. For example, even at low temperatures of 10°C, the system can still maintain an overall processing efficiency of 85%, which is a significant improvement over the 60-70% efficiency that traditional systems can typically achieve under similar conditions. At the same time, due to optimized energy use, the system's energy consumption may be 20-30% lower than traditional systems.

[0207] In addition, this method can significantly extend the service life of the enzyme. In traditional systems, enzyme activity may drop below 50% within 7-10 days under low temperature conditions. In this system, by optimizing temperature control and timely regeneration, enzyme activity can be maintained above 70% within 30 days, greatly reducing the frequency and cost of enzyme replacement.

[0208] Compared with the prior art, the method of the present application has significant advantages. The traditional fixed parameter operation mode is difficult to cope with the treatment challenges of low-temperature and high-concentration wastewater, and often requires a significant increase in aeration or heating, resulting in a surge in energy consumption. However, the present application can minimize energy consumption while ensuring the treatment effect through real-time optimization. In addition, the traditional method is difficult to balance the load between multiple reactors, which can easily cause some reactors to be overloaded while other reactors are idle. The mathematical model of the present application can dynamically adjust the water inlet distribution to make full use of the processing capacity of each reactor. Finally, the traditional method usually adopts a fixed enzyme regeneration cycle, while the present application can dynamically determine the regeneration timing according to the actual enzyme activity, which not only avoids unnecessary regeneration, but also can restore enzyme activity in time, greatly improving the overall efficiency and economy of the system.

[0209] Second, refer to Figure 2 The present application further proposes a sewage treatment device for treating high-concentration organic wastewater under low temperature conditions, comprising:

[0210] An acquisition module 210 is used to acquire influent water quality, temperature information and sludge status information;

[0211] A judgment module 220 is used to judge whether the wastewater is low-temperature and high-concentration organic matter according to the influent water quality and temperature information;

[0212] The execution module 230 is used to adjust the operating parameters of each treatment area in the biological reaction tank according to the influent water quality, temperature information and sludge state information when determining that the wastewater is low-temperature and high-concentration organic matter wastewater, including:

[0213] Implement zoned dynamic aeration in the bioreactor and add microbial activity enhancers according to water temperature;

[0214] Adjust the ratio of internal reflux to external reflux according to the treatment effect monitored in real time;

[0215] According to the real-time monitored sludge properties, flocculants are added to the biological reactor to improve the stability of the sludge flocs.

[0216] Through this method, the treatment parameters can be dynamically adjusted according to actual conditions, the microbial activity can be improved, and the sludge flocs can be stabilized, so that high-concentration organic wastewater can be efficiently treated under low temperature conditions, while taking into account multiple factors such as energy consumption and effluent water quality. It has the advantage of being able to efficiently treat high-concentration organic wastewater under low temperature conditions.

[0217] In addition, in some preferred embodiments, a sewage treatment device proposed in the present application can perform any one of the steps in the above method.

[0218] The above description is only an embodiment of the present application and is not intended to limit the protection scope of the present application. For those skilled in the art, the present application may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. A sewage treatment method for treating high-concentration organic wastewater under low temperature conditions, characterized in that: include: Obtain influent water quality, temperature information and sludge status information; According to the influent water quality and temperature information, determining whether it is low-temperature and high-concentration organic wastewater; When it is judged to be low-temperature and high-concentration organic wastewater, the operating parameters of each treatment area in the biological reactor are adjusted, including: Implement zoned dynamic aeration in the bioreactor and add microbial activity enhancers according to water temperature; Obtain the treatment effect of real-time monitoring, and adjust the ratio of internal reflux and external reflux according to the treatment effect; According to the sludge status information, flocculants are added to the biological reactor to improve the stability of the sludge flocs.

2. A sewage treatment method according to claim 1, characterized in that: The step of adding flocculants to the biological reaction tank to improve the stability of sludge flocs according to the sludge state information comprises: Obtain real-time monitoring of sludge status information; Calculating the stability index of sludge flocs according to the state information of the sludge; When the stability index is lower than a preset threshold, determining the type and dosage of flocculant to be added; Controlling the flocculant dosing device to add the flocculant of the type and dosage to the biological reaction tank; After adding the flocculant, the real-time monitored sludge status information is obtained again, and the updated stability index is calculated; According to the updated stability index, the flocculant addition effect is evaluated and the subsequent flocculant addition strategy is adjusted.

3. A sewage treatment method according to claim 2, characterized in that: The step of obtaining the real-time monitored sludge status information comprises: receiving data signals from a plurality of sludge sensors; Preprocessing the data signal, including removing outliers and smoothing the data; Calculate key indicators including sludge concentration and sedimentation performance based on pre-treated data signals; Compare the calculated key indicators with the preset normal range; When any key indicator exceeds the preset normal range, an alarm signal is triggered; The key indicators and alarm signals are output as sludge status information.

4. A sewage treatment method according to claim 2, characterized in that: The step of calculating the stability index of sludge flocs according to the state information of the sludge comprises: Acquiring status information of the sludge including sludge concentration and settling performance; Inputting the state information of the sludge into a preset stability index calculation model to obtain a preliminary sludge floc stability index; Obtain historical sludge floc stability index data; Comparing and analyzing the preliminary sludge floc stability index with historical data; According to the comparative analysis results, the preliminary sludge floc stability index is revised; The corrected sludge floc stability index is output as the final calculation result.

5. A sewage treatment method according to claim 1, characterized in that: The steps of implementing zoned dynamic aeration in the biological reaction tank and adding a microbial activity enhancer according to the water temperature include: Obtain dissolved oxygen concentration and water temperature data for each area of ​​the biological reactor; Calculating the aeration requirements of each area based on the dissolved oxygen concentration data; According to the aeration demand, adjusting the aeration amount of the aerators in each area; Determining the dosage of the microbial activity enhancer according to the water temperature data; Controlling the quantitative pump to add the dosage of the microbial activity enhancer to the bioreactor; Monitor the treatment effect after adding microbial activity enhancer, including effluent quality and sludge activity; According to the treatment effect, the aeration volume and the dosage of the microbial activity enhancer are dynamically adjusted.

6. A sewage treatment method according to claim 5, characterized in that: The step of determining the dosage of the microbial activity enhancer according to the water temperature data comprises: Obtain real-time water temperature data of the biological reactor; According to the real-time water temperature data, a preset water temperature-activity relationship curve is queried to obtain the microbial activity level at the current water temperature; calculating the difference between the current microbial activity level and the target activity level; Calculating the required dosage of the microbial activity enhancer according to the difference and the preset activity enhancer efficacy parameter; Also includes: Comparing the dosage with a preset safety threshold; When the dosage does not exceed the safety threshold, outputting the dosage as the final dosage of the microbial activity enhancer; When the dosage exceeds the safety threshold, the safety threshold is used as the final dosage of the microbial activity enhancer and an alarm signal is triggered.

7. A sewage treatment method according to claim 1, characterized in that: The method further comprises: Monitor the concentration of organic matter in the influent; When it is detected that the concentration of organic matter in the influent exceeds the preset threshold, part of the high-concentration wastewater is directed into a temporary storage tank; Starting a bioreactor of an emergency treatment unit, wherein the bioreactor is a combination of immobilized enzyme technology and a membrane bioreactor; Using the bioreactor to treat the high-concentration wastewater in the temporary storage tank; The water treated by the bioreactor is mixed with the effluent of the main treatment system.

8. A sewage treatment method according to claim 7, characterized in that: The step of starting the bioreactor of the emergency treatment unit comprises: Obtain influent organic matter concentration and temperature data; According to the influent organic matter concentration and temperature data, selecting the most suitable immobilized enzyme formula from a plurality of preset immobilized enzyme formulas; loading the selected immobilized enzyme formulation into the bioreactor; Adjust the temperature and pH of the bioreactor to be within the optimal activity range of the selected immobilized enzyme; Start the membrane bioreactor and adjust the membrane flux according to the concentration of organic matter in the influent; Monitor immobilized enzyme activity and membrane fouling; When the activity of the immobilized enzyme is detected to be lower than a preset threshold or the membrane fouling degree exceeds a preset threshold, the enzyme replacement or membrane cleaning procedure is triggered.

9. A sewage treatment method according to claim 7, characterized in that: A multi-stage enzyme immobilization system is formed by a plurality of the bioreactors, and the method further comprises: Obtaining operation data of the multi-stage immobilized enzyme system, including influent organic matter concentration, temperature, enzyme activity, regeneration status of the bioreactor, and overall treatment efficiency and energy consumption of the system; Based on the obtained operation data, a mathematical model of the multi-stage immobilized enzyme system was established, including: Input variables: x(t) = [C(t), T(t), A(t), T_r(t), R(t)] Among them, C(t) is the influent organic matter concentration vector, T(t) is the influent temperature, A(t) is the enzyme activity vector of each bioreactor, T_r(t) is the temperature vector of each bioreactor, and R(t) is the regeneration state vector of each bioreactor; Output variables: y(t) = [α(t), T_set(t), η(t)] Among them, α(t) is the water inlet ratio vector of each bioreactor, T_set(t) is the temperature set value vector of each bioreactor, and η(t) is the overall treatment efficiency of the system; State equation: dA_i(t) / dt=f(A_i(t),T_i(t),C(t))-k_i*A_i(t)+γ_i*R_i(t)*(A_max-A_i(t)) Wherein, f() is the enzyme activity change function, k_i is the enzyme inactivation rate constant of the i-th bioreactor, and γ_i is the regeneration efficiency coefficient of the i-th bioreactor; Output equation: y(t)=g(x(t),θ) Among them, g() is a nonlinear mapping function, and θ is a model parameter set; Objective function: max J = w_1*η(t)+w_2*(1-σ(A(t)))-w_3*E(t)+w_4*η(t+1) Among them, σ(A(t)) is the standard deviation of enzyme activity, E(t) is the energy consumption function, η^(t+1) is the predicted processing efficiency at the next moment, and w_1, w_2, w_3, and w_4 are weight coefficients; Constraints: Σα_i(t)=1, T_min≤T_i_set(t)≤T_max, A_min≤A_i(t)≤A_max, ΣC_j(t)*(1-η(t))≤C_max_out Among them, T_min and T_max are temperature limits, A_min and A_max are enzyme activity limits, and C_max_out is the maximum organic matter concentration allowed in the effluent; According to the mathematical model, the operating parameters of the multi-stage immobilized enzyme system are optimized in real time to improve the treatment effect of high-concentration organic wastewater under low temperature conditions.

10. A sewage treatment device for treating high-concentration organic wastewater under low temperature conditions, characterized in that: include: An acquisition module is used to obtain influent water quality, temperature information and sludge status information; A judgment module, used to judge whether the wastewater is low-temperature and high-concentration organic matter according to the influent water quality and temperature information; The execution module is used to adjust the operating parameters of each treatment area in the biological reaction tank according to the influent water quality, temperature information and sludge state information when it is judged to be low-temperature and high-concentration organic wastewater, including: Implement zoned dynamic aeration in the bioreactor and add microbial activity enhancer according to water temperature; adjust the ratio of internal and external reflux according to the treatment effect monitored in real time; According to the real-time monitored sludge properties, flocculants are added to the biological reactor to improve the stability of the sludge flocs.

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