A system for on-line monitoring and regulation of nitrification inhibition by thiourea for sewage treatment

Abstract

The application discloses a kind of thiocarbamide inhibits nitrification online monitoring and regulation system for sewage treatment, and relates to the technical field of sewage treatment.The application discloses a kind of thiocarbamide inhibits nitrification online monitoring and regulation system for sewage treatment, and relates to the technical field of sewage treatment.The application discloses a kind of thiocarbamide inhibits nitrification online monitoring and regulation system for sewage treatment, and relates to the technical field of sewage treatment.The application discloses a kind of thiocarbamide inhibits nitrification online monitoring and regulation system for sewage treatment, and relates to the technical field of sewage treatment.The application discloses a kind of thiocarbamide inhibits nitrification online monitoring and regulation system for sewage treatment, and relates to the technical field of sewage treatment.The application discloses a kind of thiocarbamide inhibits nitrification online monitoring and regulation system for sewage treatment, and relates to the technical field of sewage treatment.The application discloses a kind of thiocarbamide inhibits nitrification online monitoring and regulation system for sewage treatment, and relates to the technical field of sewage treatment.The application discloses a kind of thiocarbamide inhibits nitrification online monitoring and regulation system for sewage treatment, and relates to the technical field of sewage treatment.The application discloses a kind of thiocarbamide inhibits nitrification online monitoring and regulation system for sewage treatment, and relates to the technical field of sewage treatment.The application discloses a kind of thiocarbamide inhibits nitrification online monitoring and regulation system for sewage treatment, and relates to the technical field of sewage treatment.The application discloses a kind of thiocarbamide inhibits nitrification online monitoring and regulation system for sewage treatment, and relates to the technical field of sewage treatment.The application discloses a kind of thiocarbamide inhibits nitrification online monitoring and regulation system for sewage treatment, and relates to the technical field of sewage treatment.The application discloses a kind of thiocarbamide inhibits nitrification online monitoring and regulation system for sewage treatment, and relates to the technical field of sewage treatment.The application discloses a kind of thiocarbamide inhibits nitrification online monitoring and regulation system for

Description

Technical Field

[0001] This invention relates to the field of wastewater treatment technology, specifically to an online monitoring and control system for inhibiting nitrification reactions using thiourea in wastewater treatment. Background Technology

[0002] With the acceleration of urbanization and industrial development, wastewater discharge continues to increase, posing a severe challenge to water environmental quality. Biological denitrification is a key step in wastewater treatment, mainly achieved through two stages: nitrification and denitrification. The nitrification reaction is synergistically completed by ammonia-oxidizing bacteria (AOB) and nitrite-oxidizing bacteria (NOB), gradually oxidizing ammonia nitrogen into nitrite nitrogen and nitrate nitrogen. Under anoxic conditions, denitrifying bacteria utilize organic matter as electron donors to reduce nitrate nitrogen back to nitrogen gas, thus achieving effective removal of total nitrogen.

[0003] In recent years, novel nitrogen removal processes such as partial nitrification-denitrification (PND) and anammox have attracted widespread attention due to their advantages such as energy saving, reduced sludge production, and lower energy consumption. The core of these processes lies in achieving and maintaining stable partial nitrification, that is, oxidizing ammonia nitrogen only to the nitrite nitrogen stage, while inhibiting the further oxidation of nitrite nitrogen to nitrate nitrogen. Therefore, selectively inhibiting NOB activity has become a key technology for achieving efficient partial nitrification.

[0004] Currently, commonly used methods for NOB suppression mainly include controlling operating parameters such as dissolved oxygen (DO), pH, and temperature, as well as adding specific inhibitors. Among these, chemical inhibitors have the advantages of rapid action and significant effects. Thiourea, as a nitrogen-containing organic compound, has been shown to have a strong specific inhibitory effect on NOB, while having a smaller impact on AOB, and is therefore considered a potentially effective inhibitor for achieving short-cut nitrification.

[0005] Chinese invention patent CN113860495A discloses a short-cut nitrification feedback control system and its control method for wastewater treatment, comprising: a short-cut nitrification agent dosing device, an online data acquisition module, and a agent dosing control module; the short-cut nitrification agent dosing device is used for preparing short-cut agents and adding the prepared short-cut agents to the wastewater treatment biological treatment tank; the online data acquisition module detects the required component data in the wastewater treatment biological treatment tank; the agent dosing control module is electrically connected to the short-cut nitrification agent dosing device and the online data acquisition module, and controls the short-cut nitrification agent dosing device to prepare and add short-cut agents according to the acquired component data. This achieves automated dosing of short-cut nitrification agents and enables precise monitoring of the entire process of agent dosing in wastewater treatment plants and key short-cut nitrification data.

[0006] While the above-mentioned technical solutions have achieved automated dosing of short-range nitrifying agents, when the wastewater treatment plant process system is put into operation for the first time or restarted after a major overhaul, the newly inoculated or cultured nitrifying bacteria in the biological tank will be in an "infancy" stage, meaning that their biomass is low, their activity is weak, and their ecosystem is unstable. Therefore, when using a control model directly established from historical data, it is not only impossible to quickly and safely guide the system to a stable state, but it may even completely inhibit and kill the nitrifying bacteria, leading to the failure of the cultivation process. This will not only prolong the system start-up time, but also cause serious economic losses. Summary of the Invention

[0007] The purpose of this invention is to provide an online monitoring and control system for inhibiting nitrification reaction with thiourea in wastewater treatment, so as to solve the problems mentioned in the background art.

[0008] To achieve the above objectives, the present invention provides the following technical solution: an online monitoring and control system for inhibiting nitrification reaction with thiourea in wastewater treatment, comprising:

[0009] Online monitoring module: Through online analyzers and sensor networks, it monitors and acquires nitration parameters and environmental parameters during the nitration process, and adjusts the parameter monitoring frequency according to the nitration parameters;

[0010] Intelligent control module: Based on the nitration parameters and environmental parameters, it determines the optimal parameters of the PID controller through a virtual reference model, and determines the amount of thiourea solution to be added based on the optimal parameters, including:

[0011] SB1: Initial Dosing: Based on the current influent flow rate and influent ammonia nitrogen concentration, determine the current instantaneous influent ammonia nitrogen load, and combine the current instantaneous influent ammonia nitrogen load with disturbance parameters to determine the disturbance amplitude. At the same time, based on the disturbance amplitude and the current instantaneous influent ammonia nitrogen load, determine the initial dosage of thiourea solution.

[0012] SB2: Determine the adjustment parameters: Based on the initial nitration activity, the set inhibition time, and the target nitration activity, a nitration activity trajectory curve is constructed. At the same time, through the virtual reference feedback tuning algorithm, the initial dosage of thiourea solution is compared with the initial dosage corresponding to the nitration activity trajectory curve to obtain the optimal parameters of the PID controller.

[0013] SB3: Switching control: The optimal parameters of the PID controller are loaded into the PID controller in the thiourea dosing unit to determine the corresponding thiourea solution dosage;

[0014] Thiourea dosing unit: Based on the amount of thiourea solution to be added, thiourea solution is added at the dosing point using a dosing device.

[0015] Furthermore, the online analyzer is installed at the end of the aerobic zone of the biological treatment tank to monitor and acquire the concentrations of ammonia nitrogen, nitrate nitrogen, and nitrite nitrogen. The sensor network is installed in the inlet pipe of the biological treatment tank to monitor and acquire the inlet flow rate and the inlet ammonia nitrogen concentration.

[0016] Furthermore, based on the nitration parameters, the parameter monitoring frequency is adjusted, including:

[0017] SA1: Determine the design load: Based on the design average daily flow rate and the design maximum ammonia nitrogen concentration in the influent, determine the maximum design load, and set 70% of the maximum design load as the safe design load;

[0018] SA2: Determine the load threshold: Combine the maximum design load and the safety factor to determine the upper limit of the corresponding preset load threshold range. At the same time, take the maximum average influent ammonia nitrogen load in the static load level as the basic estimated load, and combine the basic estimated load with the buffer coefficient to obtain the buffer load. At the same time, combine the buffer load and the basic estimated load to determine the lower limit of the corresponding preset load threshold range, and the lower limit of the preset load threshold range is less than the safe design load.

[0019] SA3: Determine the load level: Based on the influent flow rate and ammonia nitrogen concentration in the biochemical tank inlet pipe, determine the influent ammonia nitrogen load of the biochemical tank inlet pipe. Simultaneously, compare the influent ammonia nitrogen load with a preset load threshold range, and determine the corresponding monitoring frequency based on the comparison results. Specifically:

[0020] When the influent ammonia nitrogen load exceeds the upper limit of the preset load threshold range, data monitoring is performed at a high frequency of 1 minute / time; when the influent ammonia nitrogen load is within the preset load threshold range, data monitoring is performed at a medium frequency of 3 minutes / time; when the influent ammonia nitrogen load is less than the lower limit of the preset load threshold range, data monitoring is performed at a low frequency of 5 minutes / time.

[0021] Furthermore, the standard deviation of the rate of change corresponding to the average influent ammonia nitrogen load within a preset time range is compared with a preset standard deviation threshold range. Based on the comparison results, the corresponding load change level is determined, specifically:

[0022] When the standard deviation of the rate of change is greater than the upper limit of the preset standard deviation threshold range, the corresponding load change level is fluctuating load; when the standard deviation of the rate of change is within the preset standard deviation threshold range, the corresponding load change level is leveling load; when the standard deviation of the rate of change is less than the lower limit of the preset standard deviation threshold range, the corresponding load change level is stationary load.

[0023] Furthermore, based on the amount of thiourea solution added, the mode of the PID controller in the thiourea dosing unit is switched from the initialization disturbance mode to the PID feedback control mode, and the PID feedback control mode is set according to the optimal parameters of the PID controller.

[0024] Furthermore, the dosage of the thiourea solution is detected using a safety constraint reinforcement learning model to determine the final dosage of thiourea, including:

[0025] SC1: Model Construction: Based on the nitration parameters and environmental parameters, the state space, action space, and reward function are set to construct a safety-constrained reinforcement learning model;

[0026] SC2: Safety Constraints: The thiourea solution dosage corresponding to the optimal parameters of the PID controller is used as the suggested dosage, and the suggested dosage is used as the input to the safety constraint reinforcement learning model. The output obtains the corresponding safe dosage fluctuation range and safe dosage. At the same time, the suggested dosage is compared with the safe dosage fluctuation range, and the final thiourea dosage is determined based on the comparison result. Specifically:

[0027] When the recommended dosage is within the safe fluctuation range of the dosage, the final thiourea dosage is the recommended dosage; otherwise, the final thiourea dosage is the safe dosage.

[0028] Furthermore, the nitrification activity, influent ammonia nitrogen load, water temperature, pH value, operating time, and cumulative thiourea dosage are combined to construct and obtain the corresponding state vector;

[0029] Based on the adjustment amount of thiourea solution, the corresponding action range is determined by setting the dosage reduction, maintaining the dosage, and increasing the dosage.

[0030] Based on the main reward item, security penalty item, and economic penalty item, construct the corresponding reward function, as follows:

[0031] ;

[0032] in: Let be the reward function corresponding to time step t. For the target nitration activity, The weighting coefficients for the target tracking item. The current nitration activity corresponds to time step t. The weighting coefficient for the rate of activity decline term. The rate of decrease in nitration activity. The weighting coefficient for the cumulative dosage item. This represents the cumulative dosage of thiourea solution at time step t. For indicating parameters.

[0033] Furthermore, based on the difference between the current nitration activity and the target nitration activity, the main reward item is determined; based on the rate of decrease in nitration activity, the safety penalty item is determined; based on the cumulative dosage of thiourea solution, the economic penalty item is determined; and simultaneously, based on the comparison between the cumulative dosage of thiourea solution and the preset dosage threshold, the magnitude of the indicator parameter is set, specifically as follows:

[0034] When the cumulative dosage of the thiourea solution exceeds the preset dosage threshold, the indicator parameter is set to 1; otherwise, the indicator parameter is set to 0.

[0035] Furthermore, the dosing equipment includes a thiourea solution storage tank and a metering pump, which are connected by a pipeline valve. The thiourea solution storage tank is equipped with a level gauge and an internal stirrer, and the metering pump is a mechanical diaphragm metering pump.

[0036] Furthermore, the thiourea dosing pipe in the thiourea dosing unit is connected to the main sewage pipeline, and a static mixer is installed between the thiourea dosing pipe and the main sewage pipeline.

[0037] Compared with the prior art, the beneficial effects of the present invention are:

[0038] Firstly, this invention determines the final dosage from the suggested dosage and the safe dosage by coordinating the initial perturbation addition and the safety constraint reinforcement learning model. This avoids the over-suppression that may be caused by traditional control models based on historical data, effectively prevents the risk of completely killing the fragile nitrifying bacteria, ensures the success of the cultivation process, and shortens the system startup time.

[0039] Secondly, this invention can automatically tune the optimal parameters of the PID controller through a virtual reference feedback tuning algorithm and nitrification activity trajectory, thereby enabling the control system to adapt to the current wastewater quality and bacterial community status, achieving precise dynamic control of the dosage of thiourea solution, and enabling it to stably and accurately maintain the nitrification activity at the target level.

[0040] Thirdly, this invention dynamically adjusts the monitoring frequency in real time according to the influent load, strengthens monitoring to respond to changes during high load, and reduces monitoring during low load to save equipment wear and energy consumption, thereby achieving optimal resource allocation;

[0041] Fourthly, this invention introduces an economic penalty term into the reward function of the safety constraint reinforcement learning model to penalize excessively high cumulative dosage, thereby reducing reagent consumption while the model achieves the process target, and thus reducing long-term operating costs.

[0042] Fifthly, this invention performs secondary verification of the output suggestions of the PID controller through a safety constraint reinforcement learning model, thereby ensuring that the dosage is always within a safe fluctuation range. This enhances the system's anti-interference ability and robustness in the face of uncertainties such as drastic fluctuations in water quality and equipment malfunctions, and ensures the reliability of operation.

[0043] Sixth: This invention uses a static mixer to ensure that the thiourea solution is uniformly mixed with the wastewater at the molecular level before entering the biological treatment tank, thereby avoiding the problem of excessively high or low local concentrations and ensuring the stability and reliability of the inhibition effect. Attached Figure Description

[0044] Figure 1 This is a system block diagram of the online monitoring and control system in this invention;

[0045] Figure 2 This is a schematic diagram illustrating the process of determining the preset load threshold range in this invention;

[0046] Figure 3 This is a schematic diagram illustrating the process of determining the optimal parameters of the PID controller in this invention;

[0047] Figure 4 This is a schematic diagram illustrating the process for determining the final thiourea dosage in this invention. Detailed Implementation

[0048] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0049] When a wastewater treatment plant's process system is first put into operation or restarted after a major overhaul, the newly inoculated or cultured nitrifying bacteria in the biological treatment tank are in their "infancy," meaning their biomass is low, their activity is weak, and their ecosystem is unstable. Therefore, using a control model directly built from historical data not only fails to quickly and safely guide the system to a stable state but may even completely inhibit and kill the nitrifying bacteria, leading to cultivation failure. This not only prolongs system startup time but also causes significant economic losses. The technical solution in this application dynamically adjusts the monitoring frequency based on real-time acquired nitrification and environmental parameters. Based on these parameters, a virtual reference model and virtual reference feedback tuning algorithm determine the optimal parameters for the corresponding PID controller, thereby obtaining the recommended dosage of thiourea solution. Simultaneously, a safety-constrained reinforcement learning model determines the final dosage from the recommended and safe dosage. The thiourea solution is then uniformly added to the wastewater pipeline using a dosing device and a static mixer, achieving safe and efficient inhibition of the nitrification reaction. This solution is suitable for the unstable conditions of a fragile nitrifying bacteria community during the initial startup phase of the system. Example 1

[0050] refer to Figures 1-3 This embodiment provides an online monitoring and control system for thiourea-induced nitrification inhibition in wastewater treatment. The system includes an online monitoring module, an intelligent control module, and a thiourea dosing unit. The online monitoring module monitors and acquires key parameters of nitrification activity and system operating status. The intelligent control module determines the thiourea dosage for each stage based on the key parameters acquired by the online monitoring module, ensuring safe microbial cultivation while inhibiting nitrification activity. The thiourea dosing unit executes the thiourea dosing action according to the dosage determined by the intelligent control module.

[0051] In this embodiment, the online monitoring module uses an online analyzer to monitor and acquire key parameters during the nitrification process, facilitating a direct and rapid assessment of the strength of nitrification activity. Simultaneously, a sensor network monitors environmental parameters to determine the magnitude of parameters affecting nitrifying bacteria activity and thiourea inhibition. Notably, the online monitoring module in this embodiment can adjust the monitoring frequency of corresponding parameters in real time according to changes in the system's state.

[0052] Furthermore, the online analyzer in this embodiment includes an online ammonia nitrogen analyzer, an online nitrate nitrogen analyzer, and an online nitrite nitrogen analyzer. All three analyzers are installed at the end of the aerobic zone of the biological treatment tank to monitor and obtain the ammonia nitrogen concentration, nitrate nitrogen concentration, and nitrite nitrogen concentration in the corresponding aerobic zone of the biological treatment tank.

[0053] Furthermore, the sensor network in this embodiment includes an electromagnetic flow meter, a DO meter, and an MLSS concentration meter. The electromagnetic flow meter is installed on the inlet pipe of the biological treatment tank, and an online ammonia nitrogen analyzer is also installed on the inlet pipe to monitor and acquire the inlet flow rate and ammonia nitrogen concentration. Based on the inlet flow rate and ammonia nitrogen concentration, the corresponding inlet ammonia nitrogen load of the biological treatment tank's inlet pipe is determined, allowing for real-time adjustment of the corresponding parameter monitoring frequency. Specifically:

[0054] Step SA1: Determine the design load. This involves obtaining the corresponding average daily design flow rate and the maximum design influent ammonia nitrogen concentration from the wastewater treatment plant's design documents to determine the maximum influent ammonia nitrogen load, i.e., the maximum design load. Specifically:

[0055] ;

[0056] in: For the maximum influent ammonia nitrogen load, To design the average daily flow, To design the maximum ammonia nitrogen concentration in the influent.

[0057] In the specific implementation process, the designed average daily flow rate is 10,000 m³ / h. 3 If the maximum ammonia nitrogen concentration in the influent is designed to be 60 mg / L, then the corresponding maximum influent ammonia nitrogen load is 25 kg / h.

[0058] Furthermore, based on the obtained maximum influent ammonia nitrogen load, i.e., the maximum design load, the corresponding safe design load is determined. That is, the safe design load is 70% of the maximum influent ammonia nitrogen load. Therefore, when the maximum influent ammonia nitrogen load is 25 kg / h, the corresponding safe design load is 17.5 kg / h.

[0059] Step SA2: Determine the load threshold. Based on the maximum influent ammonia nitrogen load (maximum design load) and safe design load obtained in Step SA1, determine the corresponding preset load threshold range. Specifically, based on the magnitude of the maximum design load, combine the maximum design load with a set safety factor (i.e., 115% to 120% of the maximum treatment capacity) to determine the upper limit of the corresponding preset load threshold range.

[0060] In the specific implementation process, the maximum influent ammonia nitrogen load is 25 kg / h, and the safety factor is set to 120%, so the upper limit of the corresponding preset load threshold range is 30 kg / h.

[0061] Furthermore, based on the magnitude of the safe design load, the lower limit of the preset load threshold range is set to be less than the safe design load. Simultaneously, in the initial stage of data acquisition, the ammonia nitrogen concentration in the biological treatment tank is monitored at a high frequency (1 minute / time) to obtain the average influent ammonia nitrogen load within a preset time range. Based on the obtained average influent ammonia nitrogen load, the corresponding standard deviation of the rate of change is determined. This standard deviation is then compared with the preset standard deviation threshold range (set according to actual data, therefore not specifically described in this embodiment) to determine the corresponding load change level, specifically:

[0062] When the standard deviation of the rate of change is greater than the upper limit of the preset standard deviation threshold range, the corresponding load change level is fluctuating load. When the standard deviation of the rate of change is within the preset standard deviation threshold range, the corresponding load change level is leveling load. When the standard deviation of the rate of change is less than the lower limit of the preset standard deviation threshold range, the corresponding load change level is stationary load.

[0063] Furthermore, based on the obtained static load, the corresponding maximum average influent ammonia nitrogen load is determined, and this maximum average influent ammonia nitrogen load is used as the basic estimated load. Simultaneously, the basic estimated load is combined with the set buffer coefficient (i.e., 20% to 50%) to determine the corresponding buffer load. The buffer load and the basic estimated load are then combined to obtain the lower limit of the corresponding preset load threshold range. It is worth noting that both the maximum average influent ammonia nitrogen load (i.e., the basic estimated load) and the lower limit of the preset load threshold range are less than the safe design load.

[0064] In the specific implementation process, the basic estimated load is 10 kg / h, the buffer coefficient is 50%, the corresponding buffer load is 5 kg / h, and the lower limit of the preset load threshold range is: 10 kg / h + 5 kg / h = 15 kg / h.

[0065] Step SA3: Determine the load level. This involves determining the influent ammonia nitrogen load corresponding to the influent pipe of the biological treatment tank based on the influent flow rate and ammonia nitrogen concentration. Specifically:

[0066] ;

[0067] in: For influent ammonia nitrogen load, This refers to the inlet water flow rate. This refers to the ammonia nitrogen concentration in the influent.

[0068] Furthermore, the obtained influent ammonia nitrogen load is compared with the preset load threshold range (i.e., 15 kg / h - 30 kg / h) set in step SA2. Based on the comparison results, the corresponding monitoring frequency is determined, specifically as follows:

[0069] When the influent ammonia nitrogen load exceeds the upper limit of the preset load threshold range (30 kg / h), the corresponding load level is high, and data monitoring is performed at a high frequency (1 minute / time). When the influent ammonia nitrogen load is within the preset load threshold range (15 kg / h-30 kg / h), the corresponding load level is medium, and data monitoring is performed at a medium frequency (3 minutes / time). When the influent ammonia nitrogen load is less than the lower limit of the preset load threshold range (15 kg / h), the corresponding load level is low, and data monitoring is performed at a low frequency (5 minutes / time).

[0070] During the implementation process, the following monitoring table was set up:

[0071] Table 1: Monitoring Table

[0072]

[0073] In this embodiment, the thiourea dosing unit adds thiourea solution to the biological treatment tank at a designated dosing point using a dosing device, ensuring thorough mixing of the thiourea solution with the mixed liquid within the tank. Specifically, the thiourea dosing point is located at the inlet of the biological treatment tank (e.g., the aerobic zone). This means the thiourea dosing pipe is connected to the main wastewater pipeline, installed in the inlet channel or post-pump pipeline, and connected via a static mixer. In other words, during the transport of the thiourea solution before it reaches the biological treatment tank, the vigorous agitation of the static mixer ensures thorough mixing between the thiourea solution and the wastewater. This allows for a uniform molecular-level distribution of the thiourea solution before it enters the biological treatment tank and comes into contact with the nitrifying bacteria, thus avoiding the risk of excessively high or low concentrations in localized areas within the biological treatment tank.

[0074] Furthermore, the dosing equipment in this embodiment includes a thiourea solution storage tank and a metering pump. The thiourea solution storage tank is equipped with an internal stirrer to prevent thiourea crystallization and precipitation. The tank is also equipped with a level gauge to display the amount of thiourea solution stored within. The metering pump and the thiourea solution storage tank are connected via a matching pipeline valve. The metering pump is a mechanical diaphragm metering pump, which controls the flow rate of the thiourea solution based on the analog signal output from the intelligent control module.

[0075] In this embodiment, the intelligent control module determines the optimal parameters for the PID controller based on the key parameters obtained by the online monitoring module and the set virtual reference model. By adjusting the PID controller using these optimal parameters, the thiourea dosing unit can be controlled. Specifically:

[0076] Step SB1: Perform initial dosing. This involves determining the corresponding initial dosing amount based on the set base dosing amount and disturbance dosing amount, and then adding the thiourea solution through the thiourea dosing unit according to the determined initial dosing amount.

[0077] Specifically, based on the current influent flow rate and ammonia nitrogen concentration in the influent pipeline of the biological treatment tank, the corresponding instantaneous influent ammonia nitrogen load is determined. Simultaneously, based on the current instantaneous influent ammonia nitrogen load and the set disturbance parameters (which can be specifically set according to actual needs, and therefore not specifically described in this embodiment), the corresponding disturbance amplitude is determined. In other words, the current instantaneous influent ammonia nitrogen load and the disturbance parameters are combined to determine the corresponding disturbance amplitude. At the same time, based on the obtained disturbance amplitude and the set pseudo-random binary sequence generator, the corresponding disturbance sequence data is obtained. This disturbance sequence data is then combined with the initial dosage to obtain the corresponding amount of thiourea solution to be added within the preset time period.

[0078] In the specific implementation process, the current instantaneous influent ammonia nitrogen load is 20 kg / h, and the disturbance parameter is 5%, which corresponds to a disturbance amplitude of 1 kg / h, or 2 mg / L. That is, by using a pseudo-random binary sequence generator and the disturbance amplitude, the disturbance sequence data for this half-hour period can be obtained, with each disturbance sequence data point spaced 5 minutes apart, specifically (+2,+2,-2,-2,+2,-2). The corresponding initial dosage is shown in the initial time-dosing table below (it is worth noting that during the dosage process, the minimum dosage is set to 0, i.e., the dosage is not negative).

[0079] Table 2: Initial Time - Dosing Table

[0080]

[0081] Step SB2: Determine the adjustment parameters. Based on the initial nitrification activity and the set inhibition time and target nitrification activity, a corresponding nitrification activity trajectory curve is constructed, which is the corresponding virtual reference model. This model guides the initial nitrification activity to smoothly and slowly decrease to the target nitrification activity. Simultaneously, based on the actual thiourea solution dosage obtained in Step SB1, the optimal parameters for the corresponding PID controller are obtained through a virtual reference feedback tuning algorithm.

[0082] Furthermore, based on the actual thiourea solution dosage obtained in step SB1, it is combined with the set nitration activity trajectory curve to obtain nitration activity response data corresponding to each actual thiourea solution dosage. Simultaneously, the obtained nitration activity response data and the nitration activity response data in the nitration activity trajectory curve are compared using a virtual reference feedback tuning algorithm to determine the optimal parameters for the corresponding PID controller.

[0083] Step SB3: Switching Control. This involves loading the optimal parameters of the PID controller obtained in Step SB2 into the online control loop. Specifically, it loads these parameters into the PID controller of the thiourea dosing unit to switch the thiourea dosing unit from the initialization disturbance mode in Step SB1 to the PID feedback control mode. In this mode, the corresponding thiourea solution dosage is determined based on the loaded optimal PID controller parameters. Example 2

[0084] This embodiment provides an online monitoring and control system for inhibiting nitrification reaction with thiourea in wastewater treatment. The specific implementation method is the same as in Embodiment 1, except that the intelligent control module in this embodiment acquires monitoring data from the online monitoring module, constructs a safety constraint reinforcement learning model, and uses this model to verify the optimal parameters of the PID controller determined in step SB3. The invention will be illustrated below with specific examples of this embodiment.

[0085] refer to Figure 4 In this embodiment, the determined optimal parameters of the PID controller are verified using a safety constraint reinforcement learning model, as follows:

[0086] Step SC1: Model Construction. This involves constructing a corresponding state vector based on monitoring data obtained from the online monitoring module, including but not limited to nitrification activity, influent ammonia nitrogen load, water temperature, pH value, operating time, and cumulative thiourea dosage. In other words, the obtained nitrification activity, influent ammonia nitrogen load, water temperature, pH value, operating time, and cumulative thiourea dosage are combined to form the corresponding state vector.

[0087] In the specific implementation process, the nitrification activity is 92%, the influent ammonia nitrogen load is 18 kg / h, the water temperature is 25℃, the pH value is 7.4, the running time is 10 hours, and the cumulative dosage of thiourea is 25 kg. The corresponding state vector is [92,18,25,7.4,10,25].

[0088] Furthermore, based on the adjustment amount of the thiourea solution, the corresponding reduction, maintenance, and increase dosage are determined, and the corresponding action range is set according to the reduction, maintenance, and increase dosage.

[0089] In the specific implementation process, the dosage reduction is set to -0.5 mg / L, the dosage maintenance is set to 0 mg / L, and the dosage increase is set to 5 mg / L. The corresponding action range is {-0.5 mg / L, 0 mg / L, 5 mg / L}.

[0090] Furthermore, based on the difference between the current nitration activity and the target nitration activity, a corresponding primary reward term is determined; based on the rate of decrease in nitration activity, a corresponding safety penalty term is determined; and based on the cumulative dosage of thiourea solution, a corresponding economic penalty term is determined. In other words, based on the determined primary reward term, safety penalty term, and economic penalty term, a corresponding reward function is constructed, specifically:

[0091] ;

[0092] in: Let be the reward function corresponding to time step t. For the target nitration activity, The weighting coefficients for the target tracking item. The current nitration activity corresponds to time step t. The weighting coefficient for the rate of activity decline term. The rate of decrease in nitration activity. The weighting coefficient for the cumulative dosage item. This represents the cumulative dosage of thiourea solution at time step t. For indicating parameters.

[0093] It is worth noting that the indicator parameter in this embodiment is determined based on the cumulative dosage of the thiourea solution. Specifically, the cumulative dosage of the thiourea solution is compared with a preset dosage threshold (which is set based on actual data and is not specifically described in this embodiment), and the corresponding indicator parameter is determined based on the comparison result. That is, when the cumulative dosage of the thiourea solution is greater than the preset dosage threshold, the corresponding indicator parameter is set to 1. Conversely, when the cumulative dosage of the thiourea solution is not greater than the preset dosage threshold, the corresponding indicator parameter is set to 0.

[0094] In other words, based on the set state space, action space, and reward function, a corresponding safety constraint reinforcement learning model is constructed.

[0095] Step SC2: Safety Constraints. Based on the optimal parameters of the PID controller determined in Step SB3, the corresponding recommended dosage is determined. Simultaneously, the determined recommended dosage is used as input to the safety constraint reinforcement learning model constructed in Step SC1, and the output obtains the corresponding safe dosage fluctuation range and safe dosage.

[0096] Furthermore, the recommended dosage is compared with the safe fluctuation range of the dosage, and based on the comparison results, the final thiourea dosage is determined, specifically as follows:

[0097] If the recommended dosage falls within the safe fluctuation range of the dosage, then the final thiourea dosage is the recommended dosage. Conversely, if the recommended dosage does not fall within the safe fluctuation range of the dosage, then the final thiourea dosage is the safe dosage.

[0098] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended embodiments and their equivalents.

Claims

1. An online monitoring and control system for inhibiting nitrification reaction with thiourea in wastewater treatment, characterized in that, Including: Online monitoring module: Through online analyzers and sensor networks, it monitors and acquires nitration parameters and environmental parameters during the nitration process, and adjusts the parameter monitoring frequency according to the nitration parameters; Intelligent control module: Based on the nitration parameters and environmental parameters, it determines the optimal parameters of the PID controller through a virtual reference model, and determines the amount of thiourea solution to be added based on the optimal parameters, including: SB1: Initial Dosing: Based on the current influent flow rate and influent ammonia nitrogen concentration, determine the current instantaneous influent ammonia nitrogen load, and combine the current instantaneous influent ammonia nitrogen load with disturbance parameters to determine the disturbance amplitude. At the same time, based on the disturbance amplitude and the current instantaneous influent ammonia nitrogen load, determine the initial dosage of thiourea solution. SB2: Determine the adjustment parameters: Based on the initial nitration activity, the set inhibition time, and the target nitration activity, a nitration activity trajectory curve is constructed. At the same time, through the virtual reference feedback tuning algorithm, the initial dosage of thiourea solution is compared with the initial dosage corresponding to the nitration activity trajectory curve to obtain the optimal parameters of the PID controller. SB3: Switching control: The optimal parameters of the PID controller are loaded into the PID controller in the thiourea dosing unit to determine the corresponding thiourea solution dosage; Thiourea dosing unit: Based on the stated amount of thiourea solution to be added, thiourea solution is added at the dosing point using a dosing device. The amount of thiourea solution added is detected using a safety constraint reinforcement learning model to determine the final amount of thiourea solution added. This includes: SC1: Model Construction: Based on the nitration parameters and environmental parameters, the state space, action space, and reward function are set to construct a safety-constrained reinforcement learning model; The nitrification activity, influent ammonia nitrogen load, water temperature, pH value, operating time, and cumulative thiourea dosage are combined to construct the corresponding state vector. Based on the adjustment amount of thiourea solution, the corresponding action range is determined by setting the dosage reduction, maintaining the dosage, and increasing the dosage. Based on the main reward item, security penalty item, and economic penalty item, construct the corresponding reward function, as follows: ； in: Let be the reward function corresponding to time step t. For the target nitration activity, The weighting coefficients for the target tracking item. The current nitration activity corresponds to time step t. The weighting coefficient for the rate of activity decline term. The rate of decrease in nitration activity. The weighting coefficient for the cumulative dosage item. This represents the cumulative dosage of thiourea solution at time step t. For indicating parameters; The main reward item is determined based on the difference between the current nitration activity and the target nitration activity; the safety penalty item is determined based on the rate of decrease in nitration activity; the economic penalty item is determined based on the cumulative dosage of thiourea solution; and the magnitude of the indicator parameter is set based on the comparison between the cumulative dosage of thiourea solution and the preset dosage threshold. Specifically: When the cumulative dosage of the thiourea solution exceeds the preset dosage threshold, the indicator parameter is set to 1; otherwise, the indicator parameter is set to 0. SC2: Safety Constraints: The thiourea solution dosage corresponding to the optimal parameters of the PID controller is used as the suggested dosage, and the suggested dosage is used as the input to the safety constraint reinforcement learning model. The output obtains the corresponding safe dosage fluctuation range and safe dosage. At the same time, the suggested dosage is compared with the safe dosage fluctuation range, and the final thiourea dosage is determined based on the comparison result. Specifically: When the recommended dosage is within the safe fluctuation range of the dosage, the final thiourea dosage is the recommended dosage; otherwise, the final thiourea dosage is the safe dosage.

2. The online monitoring and control system for inhibiting nitrification reaction with thiourea in wastewater treatment according to claim 1, characterized in that, The online analyzer is installed at the end of the aerobic zone of the biological treatment tank to monitor and acquire the concentrations of ammonia nitrogen, nitrate nitrogen, and nitrite nitrogen. The sensor network is installed in the inlet pipe of the biological treatment tank to monitor and acquire the inlet flow rate and the inlet ammonia nitrogen concentration.

3. The online monitoring and control system for inhibiting nitrification reaction with thiourea in wastewater treatment according to claim 1, characterized in that, Based on the nitration parameters, the parameter monitoring frequency is adjusted, including: SA1: Determine the design load: Based on the design average daily flow rate and the design maximum ammonia nitrogen concentration in the influent, determine the maximum design load, and set 70% of the maximum design load as the safe design load; SA2: Determine the load threshold: Combine the maximum design load and the safety factor to determine the upper limit of the corresponding preset load threshold range. At the same time, take the maximum average influent ammonia nitrogen load in the static load level as the basic estimated load, and combine the basic estimated load with the buffer coefficient to obtain the buffer load. At the same time, combine the buffer load and the basic estimated load to determine the lower limit of the corresponding preset load threshold range, and the lower limit of the preset load threshold range is less than the safe design load. SA3: Determine the load level: Based on the influent flow rate and ammonia nitrogen concentration in the biochemical tank inlet pipe, determine the influent ammonia nitrogen load of the biochemical tank inlet pipe. Simultaneously, compare the influent ammonia nitrogen load with a preset load threshold range, and determine the corresponding monitoring frequency based on the comparison results. Specifically: When the influent ammonia nitrogen load exceeds the upper limit of the preset load threshold range, data monitoring is performed at a high frequency of 1 minute / time; when the influent ammonia nitrogen load is within the preset load threshold range, data monitoring is performed at a medium frequency of 3 minutes / time; when the influent ammonia nitrogen load is less than the lower limit of the preset load threshold range, data monitoring is performed at a low frequency of 5 minutes / time.

4. The online monitoring and control system for inhibiting nitrification reaction with thiourea in wastewater treatment according to claim 3, characterized in that, The standard deviation of the rate of change of the average influent ammonia nitrogen load within a preset time range is compared with a preset standard deviation threshold range. Based on the comparison results, the corresponding load change level is determined, specifically as follows: When the standard deviation of the rate of change is greater than the upper limit of the preset standard deviation threshold range, the corresponding load change level is fluctuating load; when the standard deviation of the rate of change is within the preset standard deviation threshold range, the corresponding load change level is leveling load; when the standard deviation of the rate of change is less than the lower limit of the preset standard deviation threshold range, the corresponding load change level is stationary load.

5. The online monitoring and control system for inhibiting nitrification reaction with thiourea in wastewater treatment according to claim 1, characterized in that, Based on the dosage of the thiourea solution, the mode of the PID controller in the thiourea dosing unit is switched from the initialization disturbance mode to the PID feedback control mode, and the PID feedback control mode is set according to the optimal parameters of the PID controller.

6. The online monitoring and control system for inhibiting nitrification reaction with thiourea in wastewater treatment according to claim 1, characterized in that, The dosing equipment includes a thiourea solution storage tank and a metering pump. The thiourea solution storage tank and the metering pump are connected by a pipeline valve. The thiourea solution storage tank is equipped with a level gauge and an internal stirrer. The metering pump is a mechanical diaphragm metering pump.

7. A thiourea-based online monitoring and control system for inhibiting nitrification in wastewater treatment according to claim 1 or 6, characterized in that, The thiourea dosing pipe in the thiourea dosing unit is connected to the main sewage pipeline, and a static mixer is installed between the thiourea dosing pipe and the main sewage pipeline.

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