Method and apparatus for microbial replenishment and control of industrial wastewater with high concentrations of nitrate nitrogen

Abstract

This invention provides a method and apparatus for microbial supplementation control of industrial wastewater with high concentrations of nitrate nitrogen, relating to the field of environmental engineering technology. The method includes: determining the target denitrification volume rate of a wastewater treatment biochemical system and acquiring real-time water quality monitoring data of the system; calculating the real-time denitrification volume rate of the system based on a denitrification volume rate formula and the real-time water quality monitoring data, wherein the denitrification volume rate formula is constructed using the Monot equation for denitrification kinetics and the principle of material balance; and determining the corresponding microbial compensation amount for the wastewater treatment biochemical system based on the deviation between the target denitrification volume rate and the real-time denitrification volume rate. This invention improves the stability and treatment efficiency of wastewater treatment biochemical systems.

Description

Technical Field

[0001] This invention relates to the field of environmental engineering technology, and in particular to a method and apparatus for microbial replenishment and control of industrial wastewater with high concentrations of nitrate nitrogen. Background Technology

[0002] High-concentration total nitrogen industrial wastewater comes from a wide range of sources, such as the chemical, pharmaceutical, metallurgical, and coal chemical industries. This wastewater not only contains high concentrations of ammonia nitrogen, nitrate nitrogen, and nitrite nitrogen, but may also contain large amounts of recalcitrant organic pollutants, heavy metals, and toxic and harmful substances. These complex components interact and inhibit the growth and metabolic activities of microorganisms, leading to instability in the biochemical treatment process.

[0003] Traditional biological treatment relies on specific microbial communities to complete the nitrification and denitrification processes. However, the extreme water quality conditions of industrial wastewater with high concentrations of total nitrogen, such as high salinity, high pH, ​​and high toxicity, exceed the tolerance range of conventional microorganisms, making it difficult for them to adapt and maintain stable metabolic functions. This affects the effectiveness of biological treatment, resulting in unstable and inefficient operation of wastewater treatment biological systems for industrial wastewater with high concentrations of total nitrogen.

[0004] Therefore, there is an urgent need for a method and device for microbial replenishment and control of industrial wastewater with high concentrations of nitrate nitrogen to solve the above problems. Summary of the Invention

[0005] To address the problems existing in the prior art, the present invention provides a method and apparatus for microbial replenishment and control of industrial wastewater with high concentrations of nitrate nitrogen.

[0006] This invention provides a method for microbial replenishment and control of industrial wastewater with high concentrations of nitrate nitrogen, comprising:

[0007] Determine the target denitrification volume rate of the wastewater treatment biochemical system and acquire real-time water quality monitoring data of the wastewater treatment biochemical system;

[0008] Based on the denitrification volume rate formula and the real-time water quality monitoring data, the real-time denitrification volume rate of the wastewater treatment biochemical system is calculated. The denitrification volume rate formula is constructed using the Monot equation of denitrification kinetics and the principle of material balance.

[0009] The microbial compensation amount corresponding to the wastewater treatment biochemical system is determined based on the deviation between the target denitrification volume rate and the real-time denitrification volume rate.

[0010] According to the present invention, a method for microbial replenishment control of industrial wastewater with high concentrations of nitrate nitrogen is provided, wherein acquiring real-time water quality monitoring data of the wastewater treatment biochemical system includes:

[0011] Based on the influent tank, anoxic tank, aerobic tank, secondary sedimentation tank, and effluent tank of the wastewater treatment biochemical system, the maximum specific denitrification volumetric rate, preset denitrifying activated sludge concentration, nitrate concentration, biodegradable carbon source concentration, dissolved oxygen concentration, inhibitor concentration, temperature data, and pH value corresponding to the wastewater treatment biochemical system are obtained. The preset denitrifying activated sludge concentration is obtained based on the ratio of volatile suspended solids concentration in the mixed liquor to the preset denitrifying bacteria concentration, which is determined based on the denitrification process type of the wastewater treatment biochemical system.

[0012] The real-time water quality monitoring data of the wastewater treatment biochemical system is obtained based on the maximum specific denitrification volume rate, the preset denitrification activated sludge concentration, the nitrate concentration, the biodegradable carbon source concentration, the dissolved oxygen concentration, the inhibitor concentration, the temperature data, and the pH value.

[0013] According to the present invention, a method for microbial replenishment and control of industrial wastewater with high concentrations of nitrate nitrogen is provided, wherein the denitrification volume rate formula is specifically as follows:

[0014]

[0015] in, Indicates the concentration of denitrifying activated sludge. Indicates the denitrification volume rate; The temperature data is represented as The maximum specific denitrification volume rate at that time; Indicates nitrate concentration. This represents the half-saturation constant of nitrates; This represents the correction factor corresponding to different pH values; Indicates the concentration of biodegradable carbon sources. This represents the carbon source half-saturation constant. This represents the dissolved oxygen suppression constant. Indicates dissolved oxygen concentration. Represents the suppression constant. Indicates the concentration of the inhibitor.

[0016] According to the present invention, a method for microbial replenishment control of industrial wastewater with high concentrations of nitrate nitrogen is provided, wherein determining the microbial compensation amount corresponding to the wastewater treatment biochemical system based on the deviation between the target denitrification volume rate and the real-time denitrification volume rate includes:

[0017] Obtain a first deviation value and a second deviation value, wherein the first deviation value is the deviation between the target denitrification volume rate at the previous time and the real-time denitrification volume rate at the previous time; and the second deviation value is the deviation between the target denitrification volume rate at the current time and the real-time denitrification volume rate at the current time.

[0018] The deviation change rate is calculated based on the first deviation value, the second deviation value, and the time interval.

[0019] Based on the fuzzy control algorithm, the deviation change rate is matched with the preset fuzzy control threshold, and the microbial compensation amount and microbial replenishment method corresponding to the wastewater treatment biochemical system are determined according to the mapping relationship between the matching result and the preset microbial replenishment rules. The preset microbial replenishment rules include at least carbon source replenishment and bacterial agent replenishment.

[0020] According to the present invention, a method for microbial replenishment control of high-concentration nitrate nitrogen industrial wastewater, after determining the corresponding microbial compensation amount for the wastewater treatment biochemical system based on the deviation between the target denitrification volume rate and the real-time denitrification volume rate, the method further includes:

[0021] Based on the current amount of microbial compensation, the total nitrogen concentration of the wastewater treatment biochemical system is controlled to obtain water quality monitoring data after the total nitrogen concentration is controlled.

[0022] Based on the water quality monitoring data after the total nitrogen concentration is controlled, the preset microbial replenishment rules and parameters of the fuzzy control algorithm are adjusted to obtain the adjusted fuzzy control algorithm. Based on the adjusted fuzzy control algorithm, the microbial compensation amount of the sewage treatment biochemical system at the next moment is determined.

[0023] A method for microbial replenishment and control of high-concentration nitrate nitrogen industrial wastewater provided by the present invention further includes:

[0024] The real-time water quality monitoring data is preprocessed to obtain preprocessed real-time water quality monitoring data. The preprocessing includes protocol conversion, data parsing, data filtering, data confidence assessment, data verification, and data storage.

[0025] The present invention also provides a microbial replenishment and control device for industrial wastewater with high concentrations of nitrate nitrogen, comprising:

[0026] The data acquisition module is used to determine the target denitrification volume rate of the wastewater treatment biochemical system and to acquire real-time water quality monitoring data of the wastewater treatment biochemical system.

[0027] The denitrification volume rate dynamic prediction module is used to calculate the real-time denitrification volume rate of the wastewater treatment biochemical system based on the denitrification volume rate formula and the real-time water quality monitoring data. The denitrification volume rate formula is constructed by the Monot equation of denitrification kinetics and the principle of material balance.

[0028] The microbial dosing control module is used to determine the corresponding microbial compensation amount for the wastewater treatment biochemical system based on the deviation between the target denitrification volume rate and the real-time denitrification volume rate.

[0029] The present invention also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the microbial replenishment control method for high-concentration nitrate nitrogen industrial wastewater as described above.

[0030] The present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the microbial replenishment control method for high-concentration nitrate nitrogen industrial wastewater as described above.

[0031] The present invention also provides a computer program product, including a computer program that, when executed by a processor, implements the microbial replenishment control method for high-concentration nitrate nitrogen industrial wastewater as described above.

[0032] The present invention provides a method and apparatus for microbial supplementation control of industrial wastewater with high concentrations of nitrate nitrogen. By determining the target denitrification volume rate of the wastewater treatment biochemical system and acquiring real-time water quality monitoring data, the real-time denitrification volume rate is calculated using an algorithm based on the Monot equation of denitrification kinetics and the principle of material balance, combined with the real-time data. Finally, the amount of microbial compensation is determined based on the deviation between the target and the real-time rate, thereby improving the stability and treatment efficiency of the wastewater treatment biochemical system. Attached Figure Description

[0033] To more clearly illustrate the technical solutions in this invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0034] Figure 1 This is a schematic flowchart of the microbial replenishment and control method for high-concentration nitrate nitrogen industrial wastewater provided by the present invention.

[0035] Figure 2This is a schematic diagram of the process flow of the wastewater treatment biochemical system provided by the present invention;

[0036] Figure 3 A schematic diagram of the microbial replenishment and control device for high-concentration nitrate nitrogen industrial wastewater provided by the present invention;

[0037] Figure 4 This is a schematic diagram of the structure of the electronic device provided by the present invention. Detailed Implementation

[0038] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention.

[0039] In wastewater with high total nitrogen concentrations, it is extremely difficult to construct and maintain a stable microbial community with high nitrogen removal capacity using existing technologies. This is because different microorganisms have different environmental requirements, and under complex water conditions, it is difficult to find an equilibrium point that allows all types of microorganisms involved in nitrification and denitrification to grow and function well.

[0040] Furthermore, for key parameters in biological treatment processes, such as dissolved oxygen, temperature, pH, and hydraulic retention time, existing technologies require precise control when treating wastewater with high concentrations of total nitrogen. However, due to large fluctuations in water quality, these parameters are interconnected and mutually restrictive, making it difficult to achieve optimized control that simultaneously meets the needs of nitrification and denitrification.

[0041] When wastewater treatment systems are unstable, the total nitrogen removal rate becomes low, leading to the discharge of large amounts of nitrogenous pollutants into natural water bodies. This can cause eutrophication, resulting in excessive algae growth, oxygen depletion, and the death of aquatic organisms, disrupting the aquatic ecosystem. Poor treatment effectiveness also means the need for repeated treatment or additional steps, increasing energy and chemical consumption, extending equipment operating time, and raising maintenance costs. Furthermore, non-compliance with discharge standards may result in hefty fines, increasing the financial burden on businesses. For industrial enterprises, unstable wastewater treatment can disrupt normal production. If wastewater fails to meet discharge standards, companies may face penalties such as production restrictions or shutdowns, impacting their economic benefits and market reputation.

[0042] When a wastewater treatment biological system malfunctions, failure to address it promptly can lead not only to substandard effluent quality but also to the complete collapse of the system. Bypass systems, as an emergency protection measure, are currently mostly used to transfer a small amount of wastewater under normal water quality conditions. Activated sludge (5%-15% of the system volume) or microbial agents (0.2-1 kg / m³, 20 billion CFU / g) are added to the bypass system for cultivation. The bypass system's tank volume is 5%-15% of the biological system's volume. During cultivation, the bypass system is intermittently influent, and after the activated sludge or microbial agents have been acclimated, a small amount of wastewater is introduced to maintain normal operation.

[0043] When a wastewater treatment biological system encounters situations such as low temperatures (reduced activity of nitrifying and denitrifying bacteria), water quality deterioration (sharp increase in TN concentration, introduction of toxic substances, etc.), or water volume fluctuations (sudden increase in water volume), a bypass system will be activated to "support" the wastewater treatment biological system only after a series of human interventions and communication procedures. Operators need to handle these system changes based on the operation and maintenance manual and their experience. After handling the situation, the bypass biological system will be replenished and re-trained according to the actual conditions to prepare for the next system shock.

[0044] In current wastewater treatment biological systems, problems can only be discovered and reported by inspection personnel, requiring a series of procedures including reporting, communication, and handling. This leads to delays in resolving issues and can even worsen the situation. Furthermore, the timing and dosage of bacterial replenishment rely on experience-based judgment and lack quantitative control. The treatment process is based solely on the experience and operating habits of maintenance personnel, which can result in ineffective treatment, overdrawn bypass systems, and disrupted microbial communities within the biological treatment system. Furthermore, if the bypass system is supplied with water under abnormal conditions, it will also cause the bypass system to malfunction, at which point the bypass system will lose its protective function. At the same time, the bypass system also requires operators to perform sludge and microbial inoculation, cultivation, acclimatization, and daily operation. It is also important to pay attention to stopping the water intake of the bypass system in time when abnormal water quality occurs. Daily maintenance is very difficult. In addition, the setting of the bypass system increases the land area (its tank volume is about 5%-15% of the total tank volume of the biological system) and also increases the operation of the sewage treatment biological system. It requires the full support of operation and technical personnel. If unforeseen circumstances occur, the protective effect of the bypass system will be greatly reduced, which will increase the addition of carbon source, microbial agent and activated sludge, as well as the amount of oven-dried sludge produced.

[0045] Among existing technologies, a benign activated sludge backup tank technology can also be used. This involves transferring the mixed liquor from the main tank to the backup tank when the system is operating normally. Approximately 40% of the mixed liquor in the backup tank is replaced every three days. In case of abnormal situations, the mixed liquor in the backup tank is replenished to the wastewater treatment biological system. However, this method increases investment costs and places higher demands on the design and structure of the wastewater treatment biological system.

[0046] In addition to the above, existing technologies can also improve the system's resistance to water quality fluctuations and increase denitrification efficiency by periodically adding denitrifying bacteria or activated sludge to the anoxic tank of the wastewater treatment biological system. However, this method may lead to increased costs due to excessive addition of activated sludge / bacterial agents; furthermore, excessive activated sludge / bacterial agents consume large amounts of carbon sources, increasing operation and maintenance costs and significantly increasing sludge treatment and disposal costs. The addition of activated sludge / bacterial agents can disrupt the ecological balance of the microorganisms in the original biological system, resulting in poor treatment effects despite the addition of microorganisms. In addition, the addition of activated sludge / bacterial agents and carbon sources, as well as the treatment and disposal of tail-end sludge, all require a significant amount of manpower.

[0047] Based on the problems existing in the prior art, the present invention provides a method for microbial supplementation control of industrial wastewater with high concentration of nitrate nitrogen. The method involves real-time monitoring and calculation of the denitrification reaction rate in the anoxic tank, combined with the Monod model of denitrification kinetics and material balance, to calculate the amount of bacterial agent and carbon source required to meet the set reaction rate of nitrate nitrogen. This reflects the real demand of the denitrification process for bacterial agent and carbon source, avoiding waste of reagents and secondary pollution caused by excessive addition of bacterial agent and carbon source, or water quality exceeding the standard due to insufficient addition of bacterial agent and carbon source.

[0048] Figure 1 This is a schematic flowchart of the microbial replenishment and control method for high-concentration nitrate nitrogen industrial wastewater provided by the present invention, as shown below. Figure 1 As shown, this invention provides a method for microbial replenishment and control of industrial wastewater with high concentrations of nitrate nitrogen, comprising:

[0049] Step 101: Determine the target denitrification volume rate of the wastewater treatment biochemical system and obtain real-time water quality monitoring data of the wastewater treatment biochemical system.

[0050] In this invention, the target denitrification volumetric rate is set based on the effluent quality standards that the wastewater treatment biological system ultimately aims to achieve. For example, if the effluent requires a total nitrogen (TN) concentration to meet a specific discharge standard, the amount of denitrification reaction that the system needs to complete per unit time and per unit volume is determined by combining factors such as the influent TN concentration and the system's treatment scale, using relevant water quality models and empirical data. This is the target denitrification volumetric rate. This rate represents the denitrification treatment capacity that the system is expected to achieve under ideal conditions.

[0051] In this invention, real-time data is obtained by arranging monitoring devices at different locations in the wastewater treatment biochemical system. Figure 2 This is a schematic diagram of the process flow of the wastewater treatment biochemical system provided by the present invention, which can be referred to. Figure 2 As shown, this invention provides an overall process flow for a wastewater treatment biochemical system. Specifically, monitoring equipment is installed in the influent tank to measure the concentrations of chemical oxygen demand (COD), pH value, total nitrogen (TN), and ammonia nitrogen, as well as the influent flow rate in real time. These data reflect the quality and quantity of wastewater entering the system and serve as the basis for subsequent calculations and adjustments to the treatment process.

[0052] Temperature sensors, nitrate monitors, dissolved oxygen meters, and instruments for measuring mixed liquor volatile suspended solids (MLVSS) were installed in the anoxic tank, along with pH monitoring. The anoxic tank is the primary site for denitrification, and these parameters significantly influence the activity and reaction rate of denitrifying bacteria.

[0053] Flow meters were installed in the relevant areas of internal and external recirculation to monitor the flow rates of internal and external recirculation. The volume of water in internal and external recirculation affects the exchange of substances and the distribution of microorganisms between the anoxic and aerobic tanks, thereby affecting the denitrification effect.

[0054] Monitoring equipment is also installed in the effluent tank to measure the concentrations of COD, pH, TN, ammonia nitrogen, and effluent flow rate, in order to evaluate whether the system's treatment effect meets the target requirements.

[0055] Step 102: Based on the denitrification volume rate formula and the real-time water quality monitoring data, the real-time denitrification volume rate of the wastewater treatment biochemical system is calculated. The denitrification volume rate formula is constructed using the Monot equation of denitrification kinetics and the principle of material balance.

[0056] The Monot equation for denitrification kinetics describes the relationship between the growth rate of denitrifying bacteria and the concentration of substrates (such as nitrates). This invention, combining the principle of material balance (that the total amount of matter entering the system equals the total amount of matter leaving the system plus the total amount of matter accumulated within the system), considers the input, output, and transformation of various substances (such as nitrates, carbon sources, and microorganisms) during the denitrification reaction, and constructs a denitrification volumetric rate formula. This formula comprehensively considers multiple factors affecting the denitrification reaction, such as microbial concentration, substrate concentration, temperature, and pH.

[0057] Furthermore, this invention incorporates real-time water quality monitoring data, such as nitrate concentration, temperature, pH, MLVSS in the anoxic tank, and flow rates of internal and external recirculation, into the pre-constructed denitrification volumetric rate formula. The data is then processed and calculated by an AI control center (which integrates algorithms and logic control and possesses self-learning capabilities) to determine the real-time denitrification volumetric rate of the wastewater treatment biochemical system. This rate reflects the actual denitrification treatment capacity of the system during actual operation.

[0058] Step 103: Determine the microbial compensation amount corresponding to the wastewater treatment biochemical system based on the deviation between the target denitrification volume rate and the real-time denitrification volume rate.

[0059] In this invention, the target denitrification volumetric rate is compared with the calculated real-time denitrification volumetric rate to determine the deviation. The magnitude and direction of the deviation (positive deviation indicates the real-time rate is lower than the target rate, negative deviation indicates the real-time rate is higher than the target rate) reflect the gap between the system's current denitrification capacity and the ideal state. Furthermore, the causes of the deviation are analyzed by combining the denitrification rate model and the Monot equation for denitrification kinetics. For example, if the deviation shows that the real-time denitrification volumetric rate is lower than the target rate, it may be due to insufficient numbers or low activity of denitrifying bacteria in the anoxic tank.

[0060] In this invention, an automatic microbial agent replenishment controller (i.e., a microbial agent compensation controller, used to control the automatic microbial agent activator) is used, combined with a denitrification rate model and the Monot equation for denitrification kinetics. Based on the magnitude of the deviation and the current operating status of the system, the amount of microbial agent to be replenished into the system, i.e., the microbial compensation amount, is accurately calculated. By supplementing an appropriate amount of microbial agent, the number of denitrifying bacteria in the anoxic tank can be increased, improving the denitrification reaction rate and making the real-time denitrification volume rate of the system as close as possible to the target denitrification volume rate, thereby ensuring that the system's treatment effect is stable and meets the standards. In addition, a carbon source addition control module (i.e., a carbon source addition system controller, combined with an automatic carbon source dosing machine) is also installed in the wastewater treatment biochemical system. This module dynamically adds sodium acetate or methanol based on a preset carbon-to-nitrogen ratio (4:1 to 6:1).

[0061] The present invention provides a method for microbial supplementation control of industrial wastewater with high concentrations of nitrate nitrogen. This method determines the target denitrification volume rate of the wastewater treatment biochemical system and obtains real-time water quality monitoring data. Then, it uses an algorithm based on the Monot equation of denitrification kinetics and the principle of material balance to calculate the real-time denitrification volume rate in combination with the real-time data. Finally, based on the deviation between the target rate and the real-time rate, the amount of microbial compensation is determined, thereby improving the stability and treatment efficiency of the wastewater treatment biochemical system.

[0062] Based on the above embodiments, the step of obtaining real-time water quality monitoring data of the wastewater treatment biochemical system includes:

[0063] Based on the influent tank, anoxic tank, aerobic tank, secondary sedimentation tank, and effluent tank of the wastewater treatment biochemical system, the maximum specific denitrification volumetric rate, preset denitrifying activated sludge concentration, nitrate concentration, biodegradable carbon source concentration, dissolved oxygen concentration, inhibitor concentration, temperature data, and pH value corresponding to the wastewater treatment biochemical system are obtained. The preset denitrifying activated sludge concentration is obtained based on the ratio of volatile suspended solids concentration in the mixed liquor to the preset denitrifying bacteria concentration, which is determined based on the denitrification process type of the wastewater treatment biochemical system.

[0064] The real-time water quality monitoring data of the wastewater treatment biochemical system is obtained based on the maximum specific denitrification volume rate, the preset denitrification activated sludge concentration, the nitrate concentration, the biodegradable carbon source concentration, the dissolved oxygen concentration, the inhibitor concentration, the temperature data, and the pH value.

[0065] In this invention, relevant data are obtained based on several key treatment units in the wastewater treatment biochemical system, namely the influent tank, anoxic tank, aerobic tank, secondary sedimentation tank, and effluent tank. These treatment units perform different functions in the wastewater treatment process, and their water quality and operating parameters are interrelated and jointly affect the overall treatment effect of the system, thus comprehensively reflecting the system's operating status.

[0066] Specifically, the maximum specific denitrification volumetric rate (MDVCR) reflects the maximum amount of nitrate that a unit mass of denitrifying activated sludge can remove per unit time under specific conditions. It is an important indicator for measuring the denitrification capacity of denitrifying bacteria. Understanding the MSVCR helps assess the maximum treatment potential of denitrifying bacteria within the system, providing a reference for subsequent analysis of the system's actual denitrification efficiency and determining whether adjustments to operating parameters are necessary. For example, if the actual denitrification volumetric rate is significantly lower than the MSVCR, it may indicate that certain limiting factors in the system are affecting the activity of denitrifying bacteria.

[0067] The preset denitrifying activated sludge concentration is obtained based on the mixed liquor volatile suspended solids (MLVSS) concentration and the preset denitrifying bacteria concentration ratio. The MLVSS concentration represents the organic matter content in the activated sludge, while the preset denitrifying bacteria concentration ratio is determined based on the denitrification process type of the wastewater treatment biological system. Different denitrification processes (such as pre-denitrification, post-denitrification, etc.) have different concentration requirements for denitrifying bacteria. By determining a suitable ratio and combining it with MLVSS, the preset denitrifying activated sludge concentration can be calculated. In this invention, the preset denitrifying activated sludge concentration provides an ideal reference value for the number of denitrifying bacteria in the system. If the activated sludge concentration deviates from this preset value during actual operation, it may affect the denitrification effect, requiring adjustments to sludge return, sludge discharge, and other operations to maintain a suitable sludge concentration.

[0068] Nitrate concentration is obtained from monitoring equipment in the influent tank, anoxic tank, aerobic tank, and effluent tank. The nitrate concentration in the influent tank reflects the initial nitrate load entering the system; the anoxic tank is the main site of denitrification, and changes in its nitrate concentration directly reflect the progress of denitrification; the nitrate concentration in the aerobic tank is generally low, but incomplete nitrification or abnormal internal reflux can affect the nitrate concentration; the nitrate concentration in the effluent tank is a key indicator for evaluating the final treatment effect of the system and must meet discharge standards.

[0069] The concentration of biodegradable carbon sources directly affects the rate and efficiency of denitrification. This invention, by monitoring the concentration of biodegradable carbon sources in locations such as the influent tank and anoxic tank, can determine whether the carbon source in the system is sufficient. If the carbon source is insufficient, the denitrification reaction will be limited, leading to incomplete nitrate removal; while excessive carbon sources may result in waste, increase treatment costs, and potentially cause other problems such as sludge bulking.

[0070] In aerobic tanks, dissolved oxygen is essential for nitrifying bacteria to carry out nitrification. A suitable dissolved oxygen concentration ensures the smooth progress of nitrification, converting ammonia nitrogen into nitrate. In anoxic tanks, however, the dissolved oxygen concentration needs to be controlled at a low level (generally less than 0.5 mg / L) because denitrifying bacteria are facultative anaerobic bacteria; excessively high dissolved oxygen levels will inhibit their denitrification activity, affecting nitrate removal. This invention monitors the dissolved oxygen concentration in each tank, allowing for timely adjustments to aeration rates and other operations, creating a suitable living environment for nitrifying and denitrifying bacteria, and ensuring the efficient conduct of nitrification and denitrification reactions in the system.

[0071] Common inhibitors include heavy metals (such as mercury, cadmium, and lead), toxic organic compounds (such as phenol and cyanide), and high concentrations of ammonia nitrogen and sulfides. These substances can damage the cell structure and metabolic function of microorganisms, inhibiting their growth and activity, thereby affecting wastewater treatment efficiency. This invention, by detecting the concentration of inhibitors, can promptly identify the presence of harmful substances in the system and take corresponding measures for pretreatment or adjustment of operating parameters to mitigate the impact of inhibitors on microorganisms and ensure stable system operation.

[0072] Temperature is a crucial environmental factor affecting microbial growth and metabolism. Generally, the optimal growth temperature for denitrifying bacteria is around 20℃, within which the denitrification rate is relatively fast. When the temperature is below 15℃, the activity of denitrifying bacteria decreases significantly, and the denitrification rate slows down; while excessively high temperatures (above 40℃) may lead to microbial death. Monitoring temperature data allows for the implementation of appropriate insulation or cooling measures based on seasonal changes and actual operating conditions, creating a suitable temperature environment for microorganisms and improving the system's treatment efficiency.

[0073] The optimal pH range for denitrifying bacteria is generally between 6.5 and 8.0. Within this range, the enzyme activity of denitrifying bacteria is high, allowing the denitrification reaction to proceed smoothly. When the pH is too low (below 6.5) or too high (above 8.0), the activity of denitrifying bacteria is inhibited, affecting the denitrification effect. This invention monitors the pH value of each tank and can adjust the system's acidity or alkalinity in a timely manner, such as by adding acidic or alkaline agents, to maintain the pH value within the appropriate range and ensure the normal progress of the denitrification reaction.

[0074] Furthermore, the obtained data, including the maximum specific denitrification volumetric rate, preset denitrifying activated sludge concentration, nitrate concentration, biodegradable carbon source concentration, dissolved oxygen concentration, inhibitor concentration, temperature data, and pH value, are comprehensively compiled and analyzed. These data together constitute the real-time water quality monitoring data of the wastewater treatment biochemical system. This real-time data can comprehensively and accurately reflect the current operating status and treatment effect of the system, providing an important basis for subsequent system control and optimization. It should be noted that, in this invention, in order to improve the efficiency of collecting and processing the real-time water quality monitoring data of the wastewater treatment biochemical system, the above-mentioned real-time water quality monitoring data can all be obtained by monitoring the anoxic tank, that is, the real-time water quality monitoring data in the anoxic tank is mainly collected for the subsequent calculation of microbial compensation.

[0075] Based on the above embodiments, the denitrification volume rate formula is specifically as follows:

[0076]

[0077] in, Indicates the concentration of denitrifying activated sludge. Indicates the denitrification volume rate; The temperature data is represented as The maximum specific denitrification volume rate at that time; Indicates nitrate concentration. This represents the half-saturation constant of nitrates; This represents the correction factor corresponding to different pH values; Indicates the concentration of biodegradable carbon sources. This represents the carbon source half-saturation constant. This represents the dissolved oxygen suppression constant. Indicates dissolved oxygen concentration. Represents the suppression constant. Indicates the concentration of the inhibitor.

[0078] In this invention, based on the measurement of nitrate nitrogen concentration and timely replenishment of carbon source, it is applicable to wastewater treatment in municipal wastewater treatment and general service industries. However, when encountering highly polluting industries such as metallurgy, pharmaceuticals, and pesticides, the wastewater contains toxic and harmful substances. These toxic and harmful substances inhibit or kill denitrifying bacteria, causing the denitrification process to fail smoothly. Consequently, the nitrate nitrogen concentration in the anoxic tank gradually increases. After this data is fed back to the control center and calculated, it is found that simply gradually increasing the addition of carbon source will have a negligible effect.

[0079] Sudden changes in the quality and quantity of influent wastewater necessitate the addition of microbial agents, including situations such as a sudden increase in nitrate nitrogen concentration or the entry of harmful substances into the biological treatment system. Failure to add microbial agents can lead to reduced treatment efficiency (effluent exceeding standards) or even system collapse. However, routine addition of microbial agents and carbon sources results in waste of both, significantly increasing wastewater treatment plant operation and maintenance costs. For high-pollution industries, this invention utilizes real-time monitoring combined with a denitrification rate model and the Monot equation for denitrification kinetics. It employs a strategy of "real-time monitoring, model-based system prediction (MPC), system feedback (including internal feedback from the anoxic tank and post-feedback from the external discharge tank), intelligent dosing, and self-learning" to achieve real-time, intelligent adjustment and addition of microbial agents.

[0080] Specifically, denitrification volume rate The nitrate nitrogen removal rate is closely related to the activity and quantity of microorganisms. This invention relates to the nitrate nitrogen removal rate formula. Based on this, the effects of microbial growth and decay on the denitrification process are further considered.

[0081] Because net microbial growth alters microbial concentration (i.e., the concentration of activated sludge for denitrification), and the concentration of microorganisms directly affects the denitrification rate. Therefore, if the concentration of microorganisms increases and the substrate nitrate nitrogen is sufficient, the denitrification rate will increase; conversely, if the decline of microorganisms is dominant and the concentration of microorganisms decreases, the denitrification rate will decrease.

[0082] In this invention, It is the maximum specific growth rate of microorganisms (i.e., temperature data is) (maximum specific denitrification volume rate at time) It is a limiting substrate (in this invention, it is the concentration of nitrate nitrogen); This is the half-saturation constant, representing the substrate concentration at which the microbial growth rate reaches half of its maximum specific growth rate. At low nitrate nitrogen concentrations, the microbial growth rate increases significantly with increasing nitrate nitrogen concentration; however, at higher nitrate nitrogen concentrations, the microbial growth rate gradually approaches its maximum value. .

[0083] The decay rate b of microorganisms is generally assumed to be constant, but in reality, it is affected by environmental factors such as temperature and toxic substances. In this invention, the denitrification rate kinetic equation considers environmental factors (temperature, substrate concentration, pH, carbon source, dissolved oxygen, and toxic substances, etc.), so the decay rate b of microorganisms can be ignored. Therefore, based on the Monod equation (the denitrification kinetic model) and material balance, a denitrification volumetric rate formula (i.e., a denitrification drive control model) is constructed to calculate the theoretical denitrifying inoculant requirement in real time. The specific denitrification volumetric rate formula is as follows:

[0084]

[0085] in, This indicates the concentration of denitrifying activated sludge, expressed in mg MLVSS / L; This represents the denitrification volumetric rate, in units of... ; The temperature data is represented as The maximum specific denitrification volume rate at time, in units of ; This indicates nitrate concentration, in units of... ; This represents the nitrate half-saturation constant, in units of . The range is 0.1-5. ; This represents the correction factor corresponding to different pH values; This indicates the concentration of biodegradable carbon sources, expressed in mg COD / L. This represents the carbon source half-saturation constant, with units of mg COD / L and a range of 10-50 mg COD / L (depending on the type of carbon source). This represents the dissolved oxygen inhibition constant, expressed in mg O2 / L, with a range of 0.1-0.5 mg O2 / L. This indicates the dissolved oxygen concentration, expressed in mg / L, with a range of 0.1-0.3 mg / L. Represents the suppression constant, such as of ≈1-5mg / L; This indicates the concentration of the inhibitor, expressed in mg / L.

[0086] Preferably, considering that the denitrification volume rate is affected by temperature, this invention uses the Arrhenius equation to analyze the temperature data. The maximum specific denitrification volume rate at that time was corrected to achieve the corrected... Calculate the denitrification volumetric rate. The corrected formula is:

[0087] ;

[0088] Where θ represents the temperature correction factor, which is usually taken as 1.05-1.15, and is generally taken as 0.25 at 20℃; This indicates the current real-time temperature, in °C.

[0089] In this invention, the wastewater treatment biochemical system pre-sets a denitrifying activated sludge concentration (i.e., a preset denitrifying activated sludge concentration, which can be understood as the size of the denitrifying microbial community, denoted as ). By pre-setting the concentration of denitrifying activated sludge and using other acquired real-time water quality monitoring data, combined with the denitrification volume rate formula, the real-time denitrification volume rate is calculated. In this invention, the denitrifying microbial community... It is a component of MLVSS, and its concentration is related to MLVSS as follows:

[0090] ;

[0091] in, This indicates the proportion of denitrifying bacteria in MLVSS, and X represents the concentration of MLVSS. In this invention, different denitrification process types are considered. The values ​​also differ. Specifically, in the traditional activated sludge process: ≈10%; Pre-denitrification process (A / O, A 2 / O): ≈15%-25%; Post-denitrification (MBBP, biofilm): ≈20%-30% (due to the enrichment of obligate bacteria in biofilms).

[0092] In this invention, the denitrification rate is affected by the concentration of biodegradable carbon source. The influence of insufficient carbon source (C / N < 4) limits the denitrification rate; different carbon sources have different utilization rates (e.g., methanol > acetic acid > glucose), with a C / N ratio of 4-6 (methanol) or 6-8 (sodium acetate). In this invention, if the wastewater treatment biological system is a pre-denitrification system, then at 20°C... The threshold is 0.2-0.6d. -1 For post-denitrification systems without an external carbon source, The threshold is 0.1-0.3d -1 .

[0093] Furthermore, considering that the denitrification rate is affected by pH, with an optimal pH range of 6.5-8.0, and activity decreases when deviating from this range, this invention employs piecewise linear correction for different pH ranges:

[0094] ;

[0095] Furthermore, the denitrification rate is affected by the dissolved oxygen concentration. The optimal dissolved oxygen concentration is 0.1-0.3 mg / L. A concentration >0.5 mg / L will inhibit denitrifying enzyme activity, which is the dissolved oxygen inhibition constant in this invention. The range is 0.1-0.5 mg / L.

[0096] To address the issue that toxic substances (such as heavy metals and sulfides) can inhibit microbial activity and reduce denitrification rates, this invention proposes a correction factor:

[0097] ;

[0098] Under hypoxic conditions ( At levels ≤ 0.5 mg / L, Typically 5-15 (by (Calculation). For example, in a wastewater treatment reactor, when sodium acetate is used as the carbon source, the carbon content can be as low as 5%. When glucose is used as the carbon source, the concentration may rise to 10–15. .

[0099] Based on the above embodiments, determining the microbial compensation amount corresponding to the wastewater treatment biochemical system according to the deviation between the target denitrification volume rate and the real-time denitrification volume rate includes:

[0100] Obtain a first deviation value and a second deviation value, wherein the first deviation value is the deviation between the target denitrification volume rate at the previous time and the real-time denitrification volume rate at the previous time; and the second deviation value is the deviation between the target denitrification volume rate at the current time and the real-time denitrification volume rate at the current time.

[0101] The deviation change rate is calculated based on the first deviation value, the second deviation value, and the time interval.

[0102] Based on the fuzzy control algorithm, the deviation change rate is matched with the preset fuzzy control threshold, and the microbial compensation amount and microbial replenishment method corresponding to the wastewater treatment biochemical system are determined according to the mapping relationship between the matching result and the preset microbial replenishment rules. The preset microbial replenishment rules include at least carbon source replenishment and bacterial agent replenishment.

[0103] In this invention, the first deviation value refers to the deviation between the target denitrification volumetric rate at the previous moment and the real-time denitrification volumetric rate at the previous moment. The target denitrification volumetric rate is a pre-set denitrification volumetric rate that the wastewater treatment biological system is expected to achieve, reflecting the system's capacity to treat nitrate nitrogen under ideal conditions. The real-time denitrification volumetric rate is the denitrification volumetric rate that the system is currently performing, obtained through actual monitoring and calculation.

[0104] By calculating the first deviation value, we can understand the gap between the actual denitrification capacity and the expected capacity of the system at the previous moment. If the first deviation value is positive, it means that the real-time denitrification volume rate at the previous moment was lower than the target value, and the system's denitrification effect did not meet expectations; if it is negative, it means that the real-time denitrification volume rate was higher than the target value, and the system's denitrification capacity was strong.

[0105] The second deviation value is the difference between the target denitrification volumetric rate and the real-time denitrification volumetric rate at the current moment. Similar to the first deviation value, but with the time point being the current moment, the second deviation value reflects the difference between the actual and expected denitrification capacity of the system at the current moment. Combined with the first deviation value, the change of the deviation value over time can be observed, providing a basis for subsequent analysis of the changing trends of the system's operating status.

[0106] Furthermore, the deviation change rate is calculated based on the first deviation value, the second deviation value, and the time interval. The deviation change rate reflects how quickly the denitrification volumetric rate deviation changes over time. Specifically, assuming the first deviation value is... (Previous time deviation), the second deviation value is e t (Current time deviation), with a time interval of Δt, then the rate of change of the deviation. for:

[0107] ;

[0108] This formula quantifies the magnitude of change in the denitrification volumetric rate deviation over a given time interval. For example, if the deviation change rate is positive and large, it indicates that the denitrification volumetric rate deviation is increasing rapidly, and the gap between the system's denitrification capacity and the target capacity is widening quickly; if the deviation change rate is negative, it indicates that the deviation is decreasing, and the system's denitrification capacity is approaching the target value.

[0109] Furthermore, this invention matches the deviation change rate with a preset fuzzy control threshold. First, the deviation change rate needs to be fuzzified, dividing the input linguistic variable (deviation change rate) into fuzzy subsets such as negative large (NB), negative medium (NM), negative small (NS), positive small (PS), positive medium (PM), positive large (PB), and abnormal (AE). Each fuzzy subset corresponds to a fuzzy set, and the value of the deviation change rate can fall into different fuzzy subsets based on its magnitude, thus describing its state using fuzzy language. For example, if the deviation change rate is large and positive, it may be classified into the "positive large (PB)" fuzzy subset. The preset fuzzy control threshold is pre-set and used to divide the different fuzzy state ranges of the deviation change rate. It can be determined based on the actual operating experience of the wastewater treatment biochemical system, process requirements, and expert knowledge. By setting a reasonable threshold, the continuously changing deviation change rate can be discretized into a finite number of fuzzy states, facilitating subsequent fuzzy inference.

[0110] In this invention, the fuzzified deviation change rate is matched and inferred with preset rules according to fuzzy control rules. These fuzzy control rules are based on extensive practical experience and theoretical knowledge, describing the control strategies to be adopted under different deviation change rate states. For example, if the deviation change rate is "positive (PB)," the rules may infer that the system needs to significantly adjust the amount of microorganisms supplemented.

[0111] In this invention, the preset microbial replenishment rules include at least carbon source replenishment and microbial agent replenishment. These rules serve as the output basis for fuzzy inference, mapping the results of fuzzy inference to specific microbial replenishment operations. For example, when fuzzy inference determines that the system needs to increase microbial activity to accelerate the denitrification rate, according to the preset rules, it may be necessary to choose to increase the amount of carbon source replenishment (sufficient carbon source can promote denitrification) or add microbial agents (directly increasing the number of denitrifying bacteria). Furthermore, based on the matching results and the preset microbial replenishment rules, the specific amount of microbial compensation is determined. For example, if it is determined that microbial agents need to be replenished according to fuzzy inference and the rules, then the dosage of the microbial agents will be further determined; this dosage is the microbial compensation amount.

[0112] In this invention, in addition to determining the compensation amount, it is also necessary to determine the method of microbial replenishment, such as whether to use continuous or intermittent replenishment, or whether to use specific dosing equipment for local or comprehensive replenishment. Different replenishment methods are suitable for different operating conditions and needs. For example, for wastewater with large fluctuations in water quality and tight treatment time, a more flexible intermittent replenishment method may be necessary to adjust the replenishment amount in a timely manner according to real-time changes in water quality; while for large-scale, long-term stable wastewater treatment projects, a continuous replenishment method may be more suitable to ensure the stability of the system's microbial environment.

[0113] In this invention, the central control system of the wastewater treatment biochemical system employs a fuzzy control algorithm, using water quality monitoring data as input variables and microbial replenishment amount and replenishment time as output variables, and using the denitrification rate deviation e and deviation change rate as output variables. As an input linguistic variable, the amount of microbial replenishment *m* is used as an output linguistic variable.

[0114] The formula for calculating the denitrification rate deviation e (i.e., the deviation value) is:

[0115] ;

[0116] in, This is the set value for the denitrification rate (i.e., the target denitrification volume rate). To monitor the calculated denitrification rate in real time (i.e., the real-time denitrification volume rate).

[0117] Deviation change rate The calculation formula is:

[0118] ;

[0119] in, This represents the current denitrification rate deviation (i.e., the second deviation value). This represents the denitrification rate deviation at the previous moment (i.e., the first deviation value). For time intervals.

[0120] According to the fuzzy control rules, the rate of change of deviation Fuzzy processing is performed, dividing the data into fuzzy subsets such as Negative Large (NB), Negative Medium (NM), Negative Small (NS), Positive Small (PS), Positive Medium (PM), Positive Large (PB), and Abnormal (AE). The output variable is then derived through fuzzy inference. The fuzzy values ​​are then defuzzified (e.g., using the centroid method) to obtain the specific microbial supplementation control values. The specific fuzzy control rules are shown in Table 1.

[0121] Table 1

[0122]

[0123] In this invention, the selection of liquid or solid denitrifying bacteria in a highly efficient automatic microbial replenishment system for the biochemical treatment of industrial wastewater with high concentrations of nitrate nitrogen requires comprehensive consideration of factors such as the scale of wastewater treatment, water quality variations, treatment time requirements, and cost budget. For example, liquid bacteria may be more suitable for wastewater with large water quality fluctuations and tight treatment times; while for large-scale, long-term stable wastewater treatment projects, solid bacteria offer advantages in terms of cost and stability.

[0124] In one embodiment, two microbial supplementation control scenarios are described. One scenario is that the total nitrogen suddenly increases from 100 mg / L to 150 mg / L (predicted). The other scenario is that a toxic and harmful substance enters the anoxic tank, causing the total nitrogen in the effluent to exceed the standard (controlled by AI, combined with a denitrification-driven control model for microbial supplementation).

[0125] Specifically, a metallurgical wastewater treatment plant's normal influent total nitrogen (TN) is 100 mg / L, which suddenly increases to 150 mg / L (nitrate content 80%), requiring a rapid increase in denitrification capacity. Current conditions: daily influent flow rate Q = 900 m³ / d, mixed liquor volatile suspended solids concentration X = 3000 mg / L. =150mg COD / L, anoxic tank volume V=800m³, T=20℃, =0.2mg / L, pH=7.2, pre-denitrification process: ≈20%, This indicates the set concentration of nitrate nitrogen in the anoxic pool.

[0126] The process for directly calculating the total amount of denitrification is as follows:

[0127] 1. Under normal influent conditions: the original denitrification rate is: 900 × (100 × 0.8 - 8) = 64.8 kg / d;

[0128] Denitrification volume rate : .

[0129] 2. The amount of denitrification after the sudden increase: 900 × (150 × 0.8 - 8) = 100.8 kg / d;

[0130] The sudden increase in denitrification volume rate : .

[0131] For cases where no toxic or harmful substances enter the system, the calculation process using the denitrification volume rate formula provided by this invention is as follows:

[0132] 1. Denitrification volume rate (Normal water intake):

[0133] .

[0134] 2. The volumetric rate of denitrification after the sudden increase :

[0135] .

[0136] Denitrification volume rate increment ;

[0137] The current concentration of denitrification activated sludge that needs to be replenished is:

[0138] .

[0139] Total amount of inoculants needed: .

[0140] The verification process is as follows:

[0141] .

[0142] The supplementary bacterial dose calculated above can be used to achieve compliant emissions after adding the corresponding bacterial agent.

[0143] In the event of toxic or harmful substances entering the system, the calculation process using the denitrification volume rate formula provided by this invention is as follows:

[0144] 1. Denitrification volume rate The calculation process for (normal water intake) can refer to the calculation process described above when no toxic or harmful substances enter the system.

[0145] 2. The sudden increase in denitrification volume rate when toxic or harmful substances enter the system. :

[0146] .

[0147] Denitrification volume rate increment ;

[0148] The current concentration of denitrification activated sludge that needs to be replenished is:

[0149] .

[0150] Total amount of inoculants needed: .

[0151] The value ranges for the above parameters are shown in Table 2:

[0152] Table 2

[0153]

[0154] Based on the above embodiments, after determining the microbial compensation amount corresponding to the wastewater treatment biochemical system according to the deviation between the target denitrification volume rate and the real-time denitrification volume rate, the method further includes:

[0155] Based on the current amount of microbial compensation, the total nitrogen concentration of the wastewater treatment biochemical system is controlled to obtain water quality monitoring data after the total nitrogen concentration is controlled.

[0156] Based on the water quality monitoring data after the total nitrogen concentration is controlled, the preset microbial replenishment rules and parameters of the fuzzy control algorithm are adjusted to obtain the adjusted fuzzy control algorithm. Based on the adjusted fuzzy control algorithm, the microbial compensation amount of the sewage treatment biochemical system at the next moment is determined.

[0157] In this invention, the microbial compensation amount determined at the current moment is calculated by the fuzzy control algorithm based on previously acquired real-time data (such as nitrate nitrogen concentration, dissolved oxygen, pH value, etc.) and preset microbial replenishment rules and parameters. This compensation amount aims to adjust the quantity or activity of microorganisms in the wastewater treatment biological system, thereby affecting the total nitrogen removal effect. For example, if the currently monitored nitrate nitrogen concentration is high, the fuzzy control algorithm may increase the microbial compensation amount to promote the growth and metabolism of denitrifying bacteria, accelerate the conversion of nitrate nitrogen to nitrogen gas, and reduce the total nitrogen concentration.

[0158] Furthermore, based on the calculated current microbial compensation amount, appropriate amounts of microbial agents or carbon sources are added to the wastewater treatment biochemical system through corresponding control units (such as automatic microbial agent replenishers, carbon source dosing system controllers, etc.). The addition of these substances alters the living environment of the microorganisms within the system, affecting their growth and metabolic activities. For example, adding microbial agents can directly increase the number of denitrifying bacteria, while adding carbon sources can provide sufficient electron donors for denitrifying bacteria, promoting their denitrification reaction and thus controlling the total nitrogen concentration.

[0159] After the addition of the microbial compensation dose and a certain reaction time, various parameters of the wastewater are collected again using the water quality monitoring unit, including total nitrogen concentration, nitrate nitrogen concentration, dissolved oxygen, and pH value. These data reflect the changes in water quality of the wastewater treatment biological system under the influence of the current microbial compensation dose and are important indicators for evaluating the effectiveness of total nitrogen concentration control. For example, if the total nitrogen concentration decreases significantly, it indicates that the current microbial compensation dose has a positive effect on total nitrogen control; conversely, if the total nitrogen concentration does not change much or even increases, further analysis of the causes and adjustments to the control strategy are needed.

[0160] Furthermore, the water quality monitoring data after controlling the total nitrogen concentration were compared with the previously set target water quality parameters to analyze the differences between the actual and target water quality. Simultaneously, historical data were used to study the relationship between microbial compensation, environmental parameters (such as dissolved oxygen and pH), and total nitrogen removal efficiency over different time periods. For example, data analysis revealed that within a specific range of dissolved oxygen and pH, increasing the amount of microbial compensation significantly improved the total nitrogen removal rate; however, under other conditions, the same amount of microbial compensation might not be effective.

[0161] Based on the above analysis results, the preset microbial replenishment rules in the fuzzy control algorithm are optimized. For example, if it is found that under conditions of high nitrate nitrogen concentration and low dissolved oxygen, the original microbial replenishment rules cannot effectively reduce the total nitrogen concentration, then the rules can be modified to increase the amount of microbial compensation under this condition or adjust the replenishment method (such as changing from continuous replenishment to intermittent replenishment). Furthermore, when water quality monitoring data shows that carbon source replenishment contributes more to total nitrogen removal under certain water quality conditions, relevant content on carbon source replenishment can be added to the rules, specifying the amount and timing of carbon source replenishment under different deviation conditions.

[0162] In this invention, the parameters in the fuzzy control algorithm directly affect the accuracy of fuzzy inference and the control effect. These parameters are adjusted based on feedback from water quality monitoring data. For example, if the current fuzzy subset division is found to be too coarse, resulting in insufficient control precision, the fuzzy subset division range can be refined, enabling the algorithm to more accurately describe the state of input variables (such as deviation and rate of change of deviation).

[0163] After adjusting the preset microbial replenishment rules and parameters, a new fuzzy control algorithm is formed. This adjusted algorithm can better adapt to the actual operation of the wastewater treatment biochemical system, and more accurately calculate the microbial compensation amount based on real-time water quality monitoring data, thereby improving the accuracy and effectiveness of total nitrogen concentration control. At the next moment, various parameters of the wastewater, including nitrate nitrogen concentration, dissolved oxygen, and pH value, are collected in real time again using the water quality monitoring unit, and this data is input into the adjusted fuzzy control algorithm. Simultaneously, intermediate variables such as the denitrification rate deviation and the rate of change of deviation at the next moment are calculated, providing complete information for the algorithm's fuzzy inference.

[0164] The adjusted fuzzy control algorithm performs fuzzy inference based on the input data and according to new fuzzy rules and parameters. The input variables are matched with a preset fuzzy subset, and then inference is performed according to the fuzzy rules to obtain the fuzzy value of the output variable (i.e., the microbial compensation amount). In this invention, the output fuzzy value is defuzzified, commonly using methods such as the centroid method. Through defuzzification, the fuzzy output value is converted into a specific, operable microbial compensation amount. This value represents the amount of microbial compensation that the wastewater treatment biochemical system needs to add at the next moment, guiding actual microbial replenishment operations to achieve continuous and effective control of total nitrogen concentration.

[0165] The fuzzy control algorithm in this invention has online learning capabilities, enabling it to automatically adjust fuzzy rules and parameters based on long-term operational data and processing results. For example, by comparing the relationship between microbial replenishment, reaction environment parameters, and nitrate nitrogen removal efficiency over different time periods, the algorithm can identify patterns, optimize fuzzy rules, and ensure the system maintains good treatment performance under varying water quality and operating conditions.

[0166] Based on the above embodiments, the method further includes:

[0167] The real-time water quality monitoring data is preprocessed to obtain preprocessed real-time water quality monitoring data. The preprocessing includes protocol conversion, data parsing, data filtering, data confidence assessment, data verification, and data storage.

[0168] In this invention, water quality monitoring systems often connect to devices from different types of devices, which may employ different communication protocols. The protocol conversion module possesses strong compatibility, supporting device access via multiple protocols, such as the mainstream MQTT, S.212, and Modbus protocols, as well as proprietary custom protocols. This ensures that various devices can smoothly connect to the system, avoiding data collection failures due to protocol incompatibility. Furthermore, based on these mainstream protocols, the protocol conversion module can facilitate data interaction between hardware devices and the software system. It converts and encapsulates data sent by the device according to a specific protocol, enabling the software system to correctly recognize and process it. Simultaneously, it converts control commands issued by the software system according to the protocols supported by the device before sending them to the device, ensuring that the device can accurately execute the corresponding operations.

[0169] To ensure the security of real-time water quality monitoring data during transmission and prevent data theft or tampering, data is transmitted using encryption. Encryption methods can include common symmetric encryption algorithms (such as AES) or asymmetric encryption algorithms (such as RSA). Upon receiving the encrypted data packet, the parsing service uses the corresponding decryption algorithm and key to decrypt the packet. Only after successful decryption can the final raw water quality monitoring data be obtained, which contains key water quality parameters such as nitrate nitrogen concentration, dissolved oxygen, and pH value.

[0170] A water quality monitoring system may have numerous monitoring points, but not all data points have equal value for subsequent analysis and processing. Data screening evaluates the data from each point based on pre-defined rules and requirements, collecting only the valid data from those points that are meaningful for water quality monitoring and analysis. For example, in a large wastewater treatment plant, multiple monitoring points may be set up in different treatment stages and areas, but the data from some points may vary little or have little impact on the overall water quality assessment. Data screening will identify and exclude the collection of data from these useless points.

[0171] In this invention, by avoiding the collection of useless location data, the consumption of network bandwidth and storage resources can be effectively reduced. This is because the transmission and storage of useless location data not only increases the system burden but may also interfere with the analysis and processing of important data.

[0172] Furthermore, the raw water quality monitoring data collected by the instrument may be affected by various factors, such as the instrument's own accuracy, environmental interference, and equipment malfunction, leading to errors or anomalies in the data. It is necessary to perform confidence analysis on this raw data to assess its reliability and accuracy. For example, by analyzing the stability of the instrument's historical data and its correlation with other relevant parameters, the reliability of the currently collected data can be determined. If anomalies are found in the data, i.e., the confidence level is low, corresponding corrective measures will be taken. Corrective methods may include using the average or median of historical data as a substitute, or making reasonable adjustments based on the data's changing trends.

[0173] In this invention, the collected water quality monitoring data can also be verified and filtered according to pre-set data cleaning rules. These rules may include data range checks (e.g., nitrate nitrogen concentration should be between 0-50 mg / L), data integrity checks (ensuring the data contains all necessary fields), and data consistency checks (data from different monitoring points should conform to certain logical relationships). Through data verification, invalid data that does not conform to the rules can be promptly identified and removed, such as values ​​exceeding reasonable ranges, data missing key fields, and logically contradictory data. This ensures that the data ultimately used for analysis and processing has high quality, improving the accuracy and reliability of data analysis.

[0174] After screening and verification, the water quality monitoring data flows into the computing engine for further calculations. The engine processes the data according to preset algorithms and models, such as calculating total nitrogen concentration, average water quality indicators, and water quality trends. These calculation results provide valuable information for water quality assessment and decision support. The calculated data is then stored in real-time in a database or data forwarding middleware. Databases provide persistent data storage, facilitating subsequent querying, analysis, and data mining; data forwarding middleware enables rapid data forwarding and sharing, meeting the water quality monitoring data needs of different systems and applications.

[0175] This invention provides a microbial supplementation control method for industrial wastewater with high concentrations of nitrate nitrogen. It combines a denitrification rate model and the Monot equation for denitrification kinetics to dynamically calculate the dosage of microbial agents. Through dual closed-loop control (carbon source addition + microbial agent supplementation), it achieves dynamic C / N balance. Based on a model-driven and data-driven dual-drive control system, it reduces waste of microbial agents and carbon sources (microbial agent dosage reduced by 15%-25%, carbon source dosage reduced by 10%-20%). Furthermore, when toxic or harmful substances enter the system, the system can respond promptly after model comparison, enabling long-term stable operation. It accurately assesses the impact of high concentrations of toxic substances entering the system (based on the rate of change in denitrification rate), preventing system collapse and the need for re-cultivation and acclimatization of the biological system.

[0176] The microbial replenishment and control device for high-concentration nitrate nitrogen industrial wastewater provided by the present invention will be described below. The microbial replenishment and control device for high-concentration nitrate nitrogen industrial wastewater described below can be referred to in correspondence with the microbial replenishment and control method for high-concentration nitrate nitrogen industrial wastewater described above.

[0177] Figure 3 This is a schematic diagram of the microbial replenishment and control device for high-concentration nitrate nitrogen industrial wastewater provided by the present invention, as shown below. Figure 3 As shown, this invention provides a microbial replenishment control device for industrial wastewater with high concentrations of nitrate nitrogen, including a data acquisition module 301, a denitrification volume rate dynamic prediction module 302, and a microbial dosing control module 303. The data acquisition module 301 is used to determine the target denitrification volume rate of the wastewater treatment biochemical system and acquire real-time water quality monitoring data of the system. The denitrification volume rate dynamic prediction module 302 is used to calculate the real-time denitrification volume rate of the wastewater treatment biochemical system based on the denitrification volume rate formula and the real-time water quality monitoring data. The denitrification volume rate formula is constructed using the Monot equation of denitrification kinetics and the material balance principle. The microbial dosing control module 303 is used to determine the corresponding microbial compensation amount for the wastewater treatment biochemical system based on the deviation between the target denitrification volume rate and the real-time denitrification volume rate.

[0178] The microbial replenishment control device for high-concentration nitrate nitrogen industrial wastewater provided by this invention determines the target denitrification volume rate of the wastewater treatment biochemical system and acquires real-time water quality monitoring data. Then, it uses an algorithm formula based on the Monot equation of denitrification kinetics and the principle of material balance to calculate the real-time denitrification volume rate in combination with the real-time data. Finally, based on the deviation between the target and real-time rates, it determines the amount of microbial compensation, thereby improving the stability and treatment efficiency of the wastewater treatment biochemical system.

[0179] The system provided in this embodiment of the invention is used to execute the above-described method embodiments. For specific processes and details, please refer to the above embodiments, which will not be repeated here.

[0180] Figure 4 This is a schematic diagram of the structure of the electronic device provided by the present invention, such as... Figure 4As shown, the electronic device may include: a processor 401, a communication interface 402, a memory 403, and a communication bus 404, wherein the processor 401, the communication interface 402, and the memory 403 communicate with each other via the communication bus 404. The processor 401 can call logical instructions in the memory 403 to execute a microbial supplementation control method for industrial wastewater with high concentrations of nitrate nitrogen. This method includes: determining the target denitrification volume rate of the wastewater treatment biochemical system and acquiring real-time water quality monitoring data of the wastewater treatment biochemical system; calculating the real-time denitrification volume rate of the wastewater treatment biochemical system based on the denitrification volume rate formula and the real-time water quality monitoring data, wherein the denitrification volume rate formula is constructed through the Monot equation of denitrification kinetics and the principle of material balance; and determining the corresponding microbial compensation amount of the wastewater treatment biochemical system according to the deviation between the target denitrification volume rate and the real-time denitrification volume rate.

[0181] Furthermore, the logical instructions in the aforementioned memory 403 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, essentially, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0182] On the other hand, the present invention also provides a computer program product, the computer program product comprising a computer program stored on a non-transitory computer-readable storage medium, the computer program comprising program instructions, which, when executed by a computer, enable the computer to execute the microbial supplementation control method for high-concentration nitrate nitrogen industrial wastewater provided by the methods described above. This method comprises: determining a target denitrification volume rate for a wastewater treatment biochemical system and acquiring real-time water quality monitoring data of the wastewater treatment biochemical system; calculating a real-time denitrification volume rate for the wastewater treatment biochemical system based on a denitrification volume rate formula and the real-time water quality monitoring data, wherein the denitrification volume rate formula is constructed using the Monot equation for denitrification kinetics and the principle of material balance; and determining the corresponding microbial compensation amount for the wastewater treatment biochemical system based on the deviation between the target denitrification volume rate and the real-time denitrification volume rate.

[0183] In another aspect, the present invention also provides a non-transitory computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the microbial replenishment control method for high-concentration nitrate nitrogen industrial wastewater provided in the above embodiments. The method includes: determining a target denitrification volume rate for a wastewater treatment biochemical system and acquiring real-time water quality monitoring data of the wastewater treatment biochemical system; calculating a real-time denitrification volume rate for the wastewater treatment biochemical system based on a denitrification volume rate formula and the real-time water quality monitoring data, wherein the denitrification volume rate formula is constructed using the Monot equation for denitrification kinetics and the material balance principle; and determining the corresponding microbial compensation amount for the wastewater treatment biochemical system based on the deviation between the target denitrification volume rate and the real-time denitrification volume rate.

[0184] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0185] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0186] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for microbial replenishment and control of industrial wastewater with high concentrations of nitrate nitrogen, characterized in that, include: Determine the target denitrification volume rate of the wastewater treatment biochemical system and acquire real-time water quality monitoring data of the wastewater treatment biochemical system; Based on the denitrification volume rate formula and the real-time water quality monitoring data, the real-time denitrification volume rate of the wastewater treatment biochemical system is calculated. The denitrification volume rate formula is constructed using the Monot equation of denitrification kinetics and the principle of material balance. The amount of microbial compensation for the wastewater treatment biochemical system is determined based on the deviation between the target denitrification volume rate and the real-time denitrification volume rate. The acquisition of real-time water quality monitoring data from the wastewater treatment biochemical system includes: Based on the influent tank, anoxic tank, aerobic tank, secondary sedimentation tank, and effluent tank of the wastewater treatment biochemical system, the maximum specific denitrification volumetric rate, preset denitrifying activated sludge concentration, nitrate concentration, biodegradable carbon source concentration, dissolved oxygen concentration, inhibitor concentration, temperature data, and pH value corresponding to the wastewater treatment biochemical system are obtained. The preset denitrifying activated sludge concentration is obtained based on the ratio of volatile suspended solids concentration in the mixed liquor to the preset denitrifying bacteria concentration, which is determined based on the denitrification process type of the wastewater treatment biochemical system. The real-time water quality monitoring data of the wastewater treatment biochemical system is obtained based on the maximum specific denitrification volume rate, the preset denitrification activated sludge concentration, the nitrate concentration, the biodegradable carbon source concentration, the dissolved oxygen concentration, the inhibitor concentration, the temperature data, and the pH value. The specific formula for the denitrification volume rate is as follows: ； in, Indicates the concentration of denitrifying activated sludge. Indicates the denitrification volume rate; The temperature data is represented as The maximum specific denitrification volume rate at that time; Indicates nitrate concentration. This represents the half-saturation constant of nitrates; This represents the correction factor corresponding to different pH values; Indicates the concentration of biodegradable carbon sources. This represents the carbon source half-saturation constant. This represents the dissolved oxygen suppression constant. Indicates dissolved oxygen concentration. Represents the suppression constant. Indicates the concentration of the inhibitor.

2. The method for microbial replenishment and control of high-concentration nitrate nitrogen industrial wastewater according to claim 1, characterized in that, The step of determining the microbial compensation amount corresponding to the wastewater treatment biochemical system based on the deviation between the target denitrification volume rate and the real-time denitrification volume rate includes: Obtain a first deviation value and a second deviation value, wherein the first deviation value is the deviation between the target denitrification volume rate at the previous time and the real-time denitrification volume rate at the previous time; and the second deviation value is the deviation between the target denitrification volume rate at the current time and the real-time denitrification volume rate at the current time. The deviation change rate is calculated based on the first deviation value, the second deviation value, and the time interval. Based on the fuzzy control algorithm, the deviation change rate is matched with the preset fuzzy control threshold, and the microbial compensation amount and microbial replenishment method corresponding to the wastewater treatment biochemical system are determined according to the mapping relationship between the matching result and the preset microbial replenishment rules. The preset microbial replenishment rules include at least carbon source replenishment and bacterial agent replenishment.

3. The method for microbial replenishment and control of high-concentration nitrate nitrogen industrial wastewater according to claim 2, characterized in that, After determining the microbial compensation amount corresponding to the wastewater treatment biochemical system based on the deviation between the target denitrification volume rate and the real-time denitrification volume rate, the method further includes: Based on the current amount of microbial compensation, the total nitrogen concentration of the wastewater treatment biochemical system is controlled to obtain water quality monitoring data after the total nitrogen concentration is controlled. Based on the water quality monitoring data after the total nitrogen concentration is controlled, the preset microbial replenishment rules and parameters of the fuzzy control algorithm are adjusted to obtain the adjusted fuzzy control algorithm. Based on the adjusted fuzzy control algorithm, the microbial compensation amount of the sewage treatment biochemical system at the next moment is determined.

4. The method for microbial replenishment and control of industrial wastewater with high concentrations of nitrate nitrogen according to any one of claims 1 to 3, characterized in that, The method further includes: The real-time water quality monitoring data is preprocessed to obtain preprocessed real-time water quality monitoring data. The preprocessing includes protocol conversion, data parsing, data filtering, data confidence assessment, data verification, and data storage.

5. A microbial replenishment control device based on the microbial replenishment control method for high-concentration nitrate nitrogen industrial wastewater according to any one of claims 1 to 4, characterized in that, include: The data acquisition module is used to determine the target denitrification volume rate of the wastewater treatment biochemical system and to acquire real-time water quality monitoring data of the wastewater treatment biochemical system. The denitrification volume rate dynamic prediction module is used to calculate the real-time denitrification volume rate of the wastewater treatment biochemical system based on the denitrification volume rate formula and the real-time water quality monitoring data. The denitrification volume rate formula is constructed by the Monot equation of denitrification kinetics and the principle of material balance. The microbial dosing control module is used to determine the corresponding microbial compensation amount for the wastewater treatment biochemical system based on the deviation between the target denitrification volume rate and the real-time denitrification volume rate.

6. An electronic device comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that, When the processor executes the computer program, it implements the microbial supplementation control method for high-concentration nitrate nitrogen industrial wastewater as described in any one of claims 1 to 4.

7. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the microbial supplementation control method for industrial wastewater with high concentrations of nitrate nitrogen as described in any one of claims 1 to 4.

8. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by the processor, it implements the microbial supplementation control method for industrial wastewater with high concentrations of nitrate nitrogen as described in any one of claims 1 to 4.

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