Intelligent control method, device and system for ammonia concentration in flue gas

Abstract

The present application relates to the technical field of flue gas treatment, and particularly relates to a flue gas ammonia concentration intelligent control method, device and system, which is applied to a flue gas ammonia concentration intelligent control device, the device is respectively connected with a monitoring system and a denitration device; the monitoring system is used for collecting flue gas samples and detecting the ammonia concentration therein, and the denitration device is provided with an ammonia supply module to control the ammonia injection amount; the method comprises the following steps: obtaining sampling data collected by the monitoring system. The present application dynamically optimizes the monitoring parameters through a sampling control factor model, calibrates the ammonia concentration measurement value by using a measurement error correction model, and adjusts the ammonia injection amount in real time through an NH3-NOx linkage control model based on accurate ammonia escape concentration and NOx concentration data, so as to realize fine control of the denitration process, effectively reduce ammonia escape, improve denitration efficiency, reduce ammonia agent consumption, and help to simultaneously realize emission standard compliance and operation cost optimization.

Description

Technical Field

[0001] This invention relates to the field of flue gas treatment technology, and in particular to a method, device and system for intelligent control of ammonia concentration in flue gas. Background Technology

[0002] The ammonia slip concentration in flue gas is a key monitoring indicator for the operation of denitrification systems in industrial facilities such as coal-fired power plants. Accurate measurement of this concentration is crucial for controlling ammonia injection, ensuring denitrification efficiency, reducing operating costs, and preventing air preheater blockage. Currently, online monitoring technologies for ammonia concentration in flue gas are mainly divided into two categories: spectroscopic methods and chemical analysis methods. These include in-situ laser methods, direct extraction methods, and online systems based on chemical absorption and detection. While in-situ laser methods (such as tunable diode laser absorption spectroscopy) offer advantages such as fast response speed and no sampling process loss, their optical path is susceptible to misalignment due to flue gas vibration, deformation, and thermal expansion and contraction. Furthermore, high concentrations of dust, water vapor (whose absorption spectra are similar to ammonia), and other gaseous components in the flue gas can severely interfere with the measurement, resulting in a low signal-to-noise ratio and measurement accuracy, and making online automatic calibration difficult. While direct extraction can remove some particulate matter through filtration, if the heating temperature is below the flue gas acid dew point (which typically needs to be consistently above 300°C), ammonia in the flue gas will react with sulfur dioxide and sulfur trioxide to form ammonium bisulfate, causing ammonia loss and blockage of the measurement pipeline. Furthermore, ammonia has a strong adsorption capacity on the sampling tube wall, leading to sample distortion, delayed measurement results, and significant errors.

[0003] To overcome the shortcomings of the aforementioned physical measurement methods, online monitoring technologies based on chemical analysis have gradually been proposed. For example, related technology CN111982611A discloses an online ammonia detection device in flue gas, which employs continuous sample injection analysis combined with front-end atomization absorption and secondary absorption, aiming to achieve continuous and rapid detection with high absorption rate. However, this device still has shortcomings in the optimization of the structure and parameters of the gas sampling device, affecting the efficient and stable capture of ammonia in flue gas, and the system is complex with high maintenance requirements. Patent CN111982611A mainly solves the absorption rate problem, but it does not fully address the long-term stability and anti-interference ability in the face of complex flue gas conditions (such as high dust and moisture fluctuations). Another related technology CN111982610A discloses an online continuous detection device for ammonia in gas using chemical spectrophotometry, which achieves continuous monitoring through multi-stage absorption, gas-liquid separation, and rich liquid concentration. However, this method has a long process, limited detection cycle, and its real-time performance is still insufficient to meet the rapid control requirements of denitrification systems. Furthermore, the system involves multiple liquid path components, posing risks of residue and cross-contamination, and lacks an integrated, effective automatic cleaning and calibration mechanism. In addition, other related technologies such as CN115307990A and CN110763811A have also proposed ammonia concentration detection schemes from different perspectives, but they still generally suffer from some common problems: most systems use single-channel sampling and detection, failing to achieve continuous monitoring and resulting in poor representativeness; absorption devices are mostly made of glass and their inner walls are prone to adhesion, leading to ammonia loss; sensitive elements such as ion-selective electrodes are easily worn in dusty liquid flows, resulting in short lifespans and high maintenance costs; there is a lack of integrated online automatic calibration and cleaning functions, leading to insufficient long-term operational stability; and in particular, most technologies only remain at the "monitoring" level, failing to deeply integrate high-precision ammonia concentration measurement results with the ammonia injection control logic of the denitrification system to form a closed-loop intelligent control, thus failing to truly achieve the goal of optimizing ammonia injection based on real-time ammonia escape concentration, reducing material consumption and safety risks.

[0004] Therefore, developing a method and device for monitoring and controlling ammonia concentration that can achieve high precision, high stability, continuous online monitoring, and intelligent linkage with the denitrification system has become an urgent technical problem to be solved in this field. Summary of the Invention

[0005] In view of this, the purpose of the present invention is to provide a method, device and system for intelligent control of ammonia concentration in flue gas.

[0006] In a first aspect, embodiments of the present invention provide an intelligent control method for ammonia concentration in flue gas. This method is applied to an intelligent control device for ammonia concentration in flue gas, which is communicatively connected to a monitoring system and a denitrification device. The monitoring system is used to collect flue gas samples and detect the ammonia concentration therein, and the denitrification device is equipped with an ammonia supply module to control the ammonia injection rate. The method includes:

[0007] Acquire sampling data collected by the monitoring system;

[0008] The sampling parameters in the sampled data are input into a preset sampling control factor model, and the optimized sampling parameters are dynamically output and fed back to the monitoring system.

[0009] Acquire a new round of sampling data collected by the monitoring system based on the optimized sampling parameters;

[0010] Based on the new round of sampling data, the corrected flue gas ammonia escape concentration was calculated using a measurement error correction model.

[0011] The corrected flue gas ammonia escape concentration, the inlet NOx concentration and the outlet NOx concentration of the denitrification unit are input into the preset NH3-NOx linkage control model to generate ammonia supply control commands.

[0012] The ammonia supply control command is sent to the ammonia supply module of the denitrification unit to adjust the ammonia injection rate.

[0013] In conjunction with the first aspect, the monitoring system is connected to the pipelines of at least two ammonia absorption devices via multi-port valves;

[0014] Before the step of acquiring the sampling data collected by the monitoring system, the following steps are also included:

[0015] Control the multi-way valve to switch the sampling path and connect the target ammonia absorption device that has completed flue gas absorption to the post-monitoring system;

[0016] Start the transfer pump to deliver the ammonia-containing absorbent from the target ammonia absorption device to the detection pool;

[0017] The dosing device is used to add compound alkaline solution to the detection tank, and the pH of the absorption solution is adjusted to the specified pH range.

[0018] In conjunction with the first aspect, the steps of inputting the sampling parameters from the sampled data into a preset sampling control factor model and dynamically outputting the optimized sampling parameters include:

[0019] Based on orthogonal experimental design, the key factors affecting the accuracy of ammonia concentration measurement and their levels were determined. The key factors include at least the sampling flow rate, sampling time, NH3 concentration and pH value of the absorption solution.

[0020] For each key factor, the ammonia concentration at each level combination was measured using an orthogonal experimental design.

[0021] Perform range analysis on the measurement results, calculate the range analysis results of each key factor at each level, and the range analysis results include the average index value and the corresponding range;

[0022] Based on the range analysis results, the order of influence of each key factor on the ammonia concentration measurement results was determined.

[0023] Based on the range, the influence of each key factor on the measurement results is ranked, and the combination of key factor levels that yields the best measurement results is selected as the optimized sampling parameters.

[0024] In conjunction with the first aspect, the inlet end of the ammonia absorption device is connected to the outlet end of the sampling tube, and the inlet end of the sampling tube is connected to the flue gas source through a pre-filter; the measurement error correction model is used to compensate for the adsorption loss of ammonia in the pipeline during the sampling process.

[0025] The new round of sampling data includes the ammonia concentration in the detection pool, the volume of the solution in the detection pool, and the cumulative volume of sampled gas;

[0026] Based on the new round of sampling data, the steps for calculating the corrected flue gas ammonia slip concentration using a measurement error correction model include:

[0027] Obtain the ammonia adsorption capacity per unit length of the pre-calibrated sampling pipeline and the length of the sampling pipeline;

[0028] Based on the measured ammonia concentration in the detection pool, the volume of the solution in the detection pool, the cumulative volume of sampled gas, the ammonia adsorption per unit length, and the length of the sampling pipeline, the corrected ammonia escape concentration in the flue gas is calculated using a measurement error correction model.

[0029] In conjunction with the first aspect, the steps of inputting the corrected flue gas ammonia slip concentration, the inlet NOx concentration, and the outlet NOx concentration of the denitrification unit into a preset NH3-NOx linkage control model to generate ammonia supply control commands include:

[0030] Obtain the operating parameters of the denitrification system; the operating parameters include the corrected flue gas ammonia slip concentration, the NOx concentration at the inlet of the denitrification unit, the NOx concentration at the outlet, and the flue gas flow rate;

[0031] Based on the corrected flue gas ammonia slip concentration, NOx concentration at the inlet of the denitrification unit, NOx concentration at the outlet of the denitrification unit, and flue gas flow rate, the theoretical ammonia supply is calculated through a linkage control model.

[0032] Get the current running constraint parameters;

[0033] Based on the theoretical ammonia supply and system constraint parameters, the actual ammonia supply and corresponding control parameters are calculated through multi-parameter coupling relationships.

[0034] Ammonia supply control commands are generated based on control parameters. The commands include at least one of ammonia supply flow setpoint and valve opening adjustment commands.

[0035] The constraint parameters include at least one or more of the following: valve opening degree of the ammonia supply system, ammonia pressure, ammonia temperature, dilution air volume, flue gas flow field uniformity, and NOx concentration distribution uniformity.

[0036] In conjunction with the first aspect, the step of sending an ammonia supply control command to the ammonia supply module of the denitrification unit to adjust the ammonia injection rate includes:

[0037] The ammonia supply control command is sent to the ammonia supply module in real time via the communication interface;

[0038] The control valve openings on the ammonia supply main pipe and ammonia injection branch pipe in the ammonia supply module are adjusted based on the instructions, and / or the air volume output of the dilution fan is adjusted.

[0039] Secondly, embodiments of this application provide an intelligent control device for ammonia concentration in flue gas. This device is communicatively connected to a monitoring system and a denitrification device. The monitoring system collects flue gas samples and detects the ammonia concentration therein. The denitrification device is equipped with an ammonia supply module to control the ammonia injection rate. This device is used to execute the method described above. The device includes:

[0040] The initial acquisition module is used to acquire sampling data collected by the monitoring system;

[0041] The parameter optimization module is used to input the sampling parameters in the sampling data into a preset sampling control factor model, dynamically output the optimized sampling parameters, and feed them back to the monitoring system.

[0042] The optimized sampling module is used to acquire a new round of sampling data collected by the monitoring system based on the optimized sampling parameters;

[0043] The calculation module is used to calculate the corrected flue gas ammonia slip concentration based on the new round of sampling data and through the measurement error correction model.

[0044] The instruction generation module is used to input the corrected flue gas ammonia slip concentration and the NOx concentration at the inlet and outlet of the denitrification unit into the preset NH3-NOx linkage control model to generate ammonia supply control instructions.

[0045] The adjustment module is used to send ammonia supply control commands to the ammonia supply module of the denitrification unit to adjust the ammonia injection rate.

[0046] Thirdly, embodiments of this application also provide an intelligent control system for ammonia concentration in flue gas, including the intelligent control device for ammonia concentration in flue gas, a monitoring system, and a denitrification device as described above; the intelligent control device for ammonia concentration in flue gas is communicatively connected to the monitoring system and the denitrification device respectively; the monitoring system is used to collect flue gas samples and detect the ammonia concentration therein, and the denitrification device is equipped with an ammonia supply module to control the amount of ammonia injected.

[0047] In conjunction with the third aspect, the monitoring system includes:

[0048] The sampling unit has its inlet end connected to the flue via a pre-filtered nano-ceramic filter, and its outlet end connected to at least two ammonia absorption devices via a multi-way switching valve.

[0049] The heat tracing sampling tube is located between the pre-filter and the multi-way switching valve. It adopts a double-layer sleeve structure, with flue gas passing through the inner tube and molten salt heat storage material filling the interlayer. It is also equipped with an electric heating device.

[0050] Ammonia absorption device, comprising two or more traps connected in series, for capturing ammonia in flue gas with an absorbent liquid;

[0051] The detection unit includes a detection cell, a pH meter, an ammonia ion electrode, and a dosing device, and is used to adjust the volume, pH, and ammonia concentration of the ammonia-containing absorbent solution.

[0052] In conjunction with the third aspect, the ammonia ion electrode is an improved ammonium ion selective electrode, and its ion permeation membrane surface is provided with a diamond-like protective coating; the inner wall of the trap of the ammonia absorption device is provided with a superhydrophobic coating; the system also includes a waste liquid regeneration device for regenerating and recycling the absorption liquid after detection.

[0053] Fourthly, this application provides an electronic device, which includes a memory and a processor. The memory stores a computer program, and the processor runs the computer program to cause the electronic device to perform the above-described method.

[0054] Fifthly, this application provides a readable storage medium storing computer program instructions, which, when read and executed by a processor, perform the above-described method.

[0055] The embodiments of the present invention bring the following beneficial effects: This application provides a method, device, and system for intelligent control of ammonia concentration in flue gas. The method is applied to an intelligent control device for ammonia concentration in flue gas, which is communicatively connected to a monitoring system and a denitrification device. The monitoring system is used to collect flue gas samples and detect the ammonia concentration therein. The denitrification device is equipped with an ammonia supply module to control the ammonia injection rate. The method includes: acquiring sampling data collected by the monitoring system; inputting the sampling parameters in the sampling data into a preset sampling control factor model, dynamically outputting the optimized sampling parameters, and feeding them back to the monitoring system; acquiring a new round of sampling data collected by the monitoring system based on the optimized sampling parameters; calculating the corrected flue gas ammonia escape concentration based on the new round of sampling data through a measurement error correction model; inputting the corrected flue gas ammonia escape concentration, the inlet NOx concentration, and the outlet NOx concentration of the denitrification device into a preset NH3-NOx linkage control model to generate an ammonia supply control command; and sending the ammonia supply control command to the ammonia supply module of the denitrification device to adjust the ammonia injection rate. This invention dynamically optimizes monitoring parameters through a sampling control factor model, calibrates ammonia concentration measurements using a measurement error correction model, and, based on accurate ammonia escape and NOx concentration data, optimizes NH3-NO3 concentration. xThe linkage control model adjusts the ammonia injection rate in real time, enabling precise control of the denitrification process. This effectively reduces ammonia slip, improves denitrification efficiency, and reduces ammonia consumption, thus helping to achieve both emission compliance and operational cost optimization.

[0056] Other features and advantages of the invention will be set forth in the description which follows, and will be apparent in part from the description, or may be learned by practicing the invention. The objects and other advantages of the invention are realized and obtained in accordance with the structures particularly pointed out in the description, claims and drawings.

[0057] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, preferred embodiments are described below in detail with reference to the accompanying drawings. Attached Figure Description

[0058] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0059] Figure 1 A flowchart illustrating an intelligent control method for ammonia concentration in flue gas provided in this application;

[0060] Figure 2 A process flow diagram for the online monitoring and intelligent control system for ammonia concentration in flue gas provided in this application;

[0061] Figure 3 This is a schematic diagram illustrating the influence of various factors obtained from orthogonal experiments in the intelligent control method for ammonia concentration in flue gas provided in this application.

[0062] Figure 4 This is a schematic diagram comparing the measured value, the corrected measured value, and the NH3 standard gas concentration in an intelligent control method for ammonia concentration in flue gas, as provided in the application.

[0063] Figure 5 This is a schematic diagram of the electronic device structure provided in an embodiment of the present invention;

[0064] Figure 6 The schematic diagram of the control flow of the intelligent control system for ammonia concentration in flue gas provided in the embodiment of the present invention. Detailed Implementation

[0065] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions 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, 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.

[0066] To facilitate understanding of this embodiment, the application scenarios and design concepts of this application embodiment will be briefly introduced below.

[0067] Existing flue gas ammonia concentration monitoring technologies generally have shortcomings: in-situ laser methods are easily affected by moisture, dust, and vibration; direct extraction methods suffer from insufficient heating, leading to ammonia condensation loss or the formation of ammonium salts; chemical analysis methods have slow response and are difficult to perform continuous detection; and ion electrodes are prone to wear and require frequent maintenance. These problems result in inaccurate and untimely monitoring data, failing to provide real-time and reliable optimization basis for denitrification systems.

[0068] Based on this, this application provides a method, device, and flue gas treatment system for intelligent control of ammonia concentration in flue gas.

[0069] Example 1

[0070] This application provides an intelligent control method for ammonia concentration in flue gas. This method is applied to an intelligent ammonia concentration control device in flue gas, which is communicatively connected to a monitoring system and a denitrification device. The monitoring system collects flue gas samples and detects the ammonia concentration within them, while the denitrification device is equipped with an ammonia supply module to control the ammonia injection rate. Combined with... Figure 1 As shown, the method includes:

[0071] S110, acquire sampling data collected by the monitoring system.

[0072] S120 inputs the sampling parameters from the sampling data into a preset sampling control factor model, dynamically outputs the optimized sampling parameters, and feeds them back to the monitoring system.

[0073] S130: Acquire a new round of sampling data collected by the monitoring system based on the optimized sampling parameters.

[0074] S140, based on a new round of sampling data, calculates the corrected flue gas ammonia escape concentration using a measurement error correction model.

[0075] S150 inputs the corrected flue gas ammonia escape concentration, the inlet NOx concentration and the outlet NOx concentration of the denitrification unit into the preset NH3-NOx linkage control model to generate ammonia supply control commands.

[0076] S160 sends an ammonia supply control command to the ammonia supply module of the denitrification unit to adjust the ammonia injection rate.

[0077] This application uses a sampling control factor model to dynamically optimize monitoring parameters, improving the reliability of sampling data; it uses a measurement error correction model to calibrate ammonia concentration measurements, improving the accuracy of monitoring results; and based on accurate ammonia escape concentration and NOx concentration data, it uses NH3-NO... x The linkage control model adjusts the ammonia injection rate in real time, achieving precise control of the denitrification process. This method can effectively reduce ammonia slip, improve denitrification efficiency, reduce ammonia consumption, and help achieve both emission compliance and operating cost optimization.

[0078] Combination Figure 2 The process flow diagram shown systematically illustrates the overall process and material flow from flue gas sampling, ammonia capture, concentration detection, and intelligent feedback control. The system includes a pre-filter (nano-ceramic filter), a heated sampling tube and backflushing cleaning device, an ammonia absorption device, a dryer, a tail gas treatment device, an ammonia detection device, an automatic calibration device, an automatic cleaning device (i.e., a cleaning system), an intelligent ammonia concentration control device in the flue gas, a solution delivery device (i.e., a delivery pump), a dosing device, and a waste liquid regeneration device (i.e., a wastewater treatment system). Under the action of the suction pump, the flue gas passes through the pre-filter (nano-ceramic filter) and the heated sampling tube before entering the ammonia absorption device. Inside the ammonia absorption device, the flue gas sequentially enters the primary absorption bottle, the secondary absorption bottle, or the Nth stage absorption bottle, and then enters the dryer. The dried flue gas then enters the tail gas treatment device and is finally vented. After absorbing all the ammonia, the absorbent in the ammonia absorption unit is pumped to the ammonia detection device by a peristaltic pump. The dosing device first delivers fresh absorbent to a fixed volume, then adds a compound alkaline solution to adjust the pH of the absorbent to 12. At this point, the ammonia concentration in the solution is measured by the ammonia ion electrode, and the result is transmitted to the intelligent control device for ammonia concentration in the flue gas. One round of sampling and detection is completed.

[0079] This embodiment begins with raw flue gas extracted from the flue. The flue gas first flows through a pre-filter made of nano-ceramic material, whose built-in backflushing nano-ceramic filter core efficiently removes fine particulate matter with a diameter ≥0.5μm, providing a clean gas sample for subsequent systems. The flue gas then enters a molten salt thermal storage sampling tube. This tube employs a double-layered structure; the inner tube carries the flue gas, while the interlayer is filled with molten salt thermal storage material (such as nitrate, chloride, fluoride, and other molten salt thermal storage materials). Upon system startup, a resistance electric heating device heats the molten salt to above 220°C, liquefying it. The liquefied molten salt evenly coats the flue gas within the inner tube, effectively preventing water vapor condensation and ammonia loss. Subsequently, the high-temperature flue gas is used to heat and maintain the molten salt in its liquefied state. Electric heating is then stopped, fully utilizing the waste heat of the flue gas and conserving resources. If sampling is carried out at the chimney inlet, continuous electric heating is required to maintain the molten salt liquefaction state, so that the flue gas entering the sampling tube is continuously and evenly heated, and the heating temperature is 150°C higher than the conventional heating temperature. This effectively solves the problem of ammonia loss caused by flue gas condensation. Under high-temperature heating conditions, the airflow flows rapidly, which also avoids the accumulation of fine particulate matter that could cause pipe blockage.

[0080] Meanwhile, the heated sampling tube is equipped with a backflush port, which can be used to periodically purge the pipeline and pre-filter with 0.3~0.6MPa instrument compressed air to prevent blockage. This pretreatment unit fundamentally solves the problems of ammonia loss and measurement deviation caused by dust interference and condensation adsorption in traditional methods.

[0081] The pretreated flue gas is guided to one or more ammonia absorption units via a multi-port valve (such as a 6-port or 8-port valve). This unit typically includes multi-stage absorption bottles, connecting pipes, a peristaltic pump, a metering pump, and multi-port valves. Generally, two absorption bottles are used, each with the same specifications and a volume not exceeding 200 mL. The absorption bottles are designed to facilitate aeration, with the inner wall coated with a PTFE superhydrophobic nano-coating to significantly reduce liquid film residue. Each bottle contains a measured amount (volume not exceeding 150 mL), low-concentration (0.05 mol / L) dilute sulfuric acid absorbent. The flue gas is dispersed into small bubbles with a diameter ≤0.5 mm through a microporous aeration head, ensuring full contact with the absorbent in the absorption bottle, resulting in efficient ammonia capture. The sequential switching design of the multi-port valve allows one set of absorption bottles to perform sampling and absorption while another set is draining, detecting, or cleaning, achieving parallel and continuous operation of sampling, absorption, and detection, ensuring the timeliness and continuity of monitoring data. The inner wall of the pear-shaped absorption bottle is treated with nano-level hydrophobic coating to prevent the absorbent from sticking to the inner wall and causing ammonia loss. The absorption bottle contains absorbent, the main component of which is 0.05 mol / L H2SO4. The volume of the absorbent is controlled by a metering pump. Flue gas flows from the primary absorption bottle into the secondary absorption bottle. The ammonia in the flue gas is completely captured by the absorbent. The ammonia-containing absorbent is then transported to the ammonia detection device by a peristaltic pump.

[0082] After ammonia absorption, the flue gas passes sequentially through a dryer and a tail gas treatment device. The dryer is filled with a desiccant mixed with an acid-base indicator to remove moisture from the flue gas. When ammonia is carried in the moisture, the desiccant will show color, indicating changes in ammonia concentration in the flue gas, allowing managers to adjust the concentration or dosage of the absorbent liquid. The tail gas treatment device includes a gas flow meter, a vacuum pump, and a sampling control system. The sampling control system provides sampling parameter settings, the vacuum pump provides sampling power, and the gas flow meter records the sampling volume. Simultaneously, the ammonia-containing absorbent liquid, after ammonia capture, is quantitatively delivered to the detection pool of the ammonia detection device by a peristaltic pump.

[0083] The ammonia-containing absorbent solution delivered to the detection tank is first treated with a compound alkaline solution (such as a mixture of sodium hydroxide and buffer solution) by a dosing device. Under pH monitoring, the solution pH is rapidly and stably adjusted to 12. Under these conditions, ammonium ions in the absorbent solution are completely converted into free ammonia. Subsequently, an ammonia ion electrode (specifically, an improved ammonium ion selective electrode) measures the ammonia concentration in the solution. The ion-permeable membrane surface of this electrode is coated with a diamond-like carbon protective coating using plasma-enhanced chemical vapor deposition, greatly enhancing its wear resistance and extending the electrode replacement frequency from once a week to once every six months. The system also integrates an automatic calibration device and an automatic cleaning device. Regular online calibration is performed using a standard ammonia solution (deviation less than 0.1%), and the flow path is automatically cleaned with deionized water to ensure long-term system stability and measurement accuracy.

[0084] After testing, the waste liquid enters a waste liquid regeneration device (membrane separation system or EDI ion exchange system). During this process, cations such as ammonium ions in the solution are replaced by hydrogen ions, regenerating into fresh dilute sulfuric acid absorbent, which is then returned to the dosing system for recycling, achieving "zero reagent consumption" and "zero wastewater discharge." The central component of the entire system is an intelligent ammonia concentration control device in the flue gas, which receives concentration data from the ammonia detection device, volume data from the flow meter, and other operating parameters. The device's built-in data processing module uses deep learning algorithms to optimize monitoring accuracy not only through sampling control factor models and measurement error correction models, but more importantly, it runs an NH3-NOx linkage control model. Based on real-time and accurate ammonia escape concentration, NOx concentration at the inlet / outlet of the denitrification unit, flue gas flow rate, and other parameters, this model calculates the optimal ammonia injection rate and generates ammonia supply control commands, including ammonia supply flow rate setpoints and valve opening instructions.

[0085] Ultimately, the intelligent ammonia concentration control device in the flue gas sends ammonia supply control commands to the ammonia supply module of the denitrification unit in real time via a communication interface. Based on this, the ammonia supply module precisely adjusts the opening of control valves on the main and branch ammonia injection pipes, and coordinates with the adjustment of the dilution fan airflow, thereby achieving refined and adaptive control of the ammonia injection quantity. The control effect is then reflected in the NOx and ammonia escape concentrations at the flue gas outlet. This new data is then collected by the monitoring system and fed back to the intelligent ammonia concentration control device in the flue gas, forming a continuously optimizing "monitoring-analysis-control" closed loop.

[0086] This application embodiment is based on the intelligent control method for ammonia concentration in flue gas provided by the aforementioned system. First, in step S110, after the monitoring system completes a sampling and detection cycle, it uploads the generated comprehensive data packet to the intelligent control device for ammonia concentration in flue gas. This data packet not only includes operating parameters reflecting the sampling process itself (such as sampling flow rate, time, and cumulative volume), but also physicochemical parameters reflecting the state of the absorbent (such as pH value and temperature), and most importantly, the output—the preliminary ammonia concentration value in the solution measured by the ammonia ion electrode. Simultaneously, the data packet includes system operating condition markers for the sampling time (such as unit load and timestamp), providing complete contextual information for subsequent data analysis and parameter optimization.

[0087] Subsequently, in step S120, the intelligent control device for ammonia concentration in flue gas activates its optimization engine. It extracts key sampling parameters (such as flow rate and time) from the data packet received in S110 and inputs them into a built-in sampling control factor model. This model, based on a database established in advance through orthogonal experiments and range analysis, can dynamically assess the influence weight of each sampling parameter on the final measurement accuracy under current or expected operating conditions. Through calculation and comparison, the model quickly outputs a set of optimized sampling parameters for the next sampling cycle (e.g., optimizing the sampling flow rate from 5 L / min to 6 L / min and adjusting the sampling time from 25 min to 30 min). These optimized parameters are then fed back in real time and sent to the monitoring system, enabling it to operate under better settings for the next sampling detection cycle, thereby laying the foundation for obtaining more accurate and representative ammonia concentration data from the operational source.

[0088] Next, in step S130, the monitoring system receives and executes the optimized parameters from S120. The system automatically adjusts the operating settings of the sampling unit, controls the suction pump to extract flue gas at an optimized flow rate (e.g., 6 L / min), and simultaneously starts a new round of timing. During this process, the multi-channel switching valve switches the flue gas path to a ready-made ammonia absorption device (e.g., the second channel) containing fresh absorbent liquid according to a preset program, realizing parallel operation of sampling and detection. The molten salt heating system ensures that the flue gas temperature in the sampling tube remains stable at the set value (e.g., ≥180℃) to minimize the adsorption loss of ammonia due to condensation.

[0089] Subsequently, in step S140, based on the new round of sampling data obtained in S130, the intelligent control device for ammonia concentration in flue gas calls the measurement error correction model to calibrate the preliminary ammonia concentration measurement value. This model comprehensively considers systematic error sources such as adsorption in the sampling pipeline (calculated based on the standardized pipeline length and the pre-calibrated ammonia adsorption amount per unit length) and residues on the inner wall of the absorption bottle. It uses a preset correction algorithm to compensate for the original measurement value, and finally outputs a more accurate corrected flue gas ammonia escape concentration value that eliminates the main systematic biases, thereby significantly improving the authenticity and reliability of the monitoring results.

[0090] Subsequently, in step S150, the corrected flue gas ammonia escape concentration value, along with the real-time collected NO values ​​at the inlet and outlet of the denitrification device, are... X Concentration, was input together with NH3-NO X The linkage control model incorporates core functions based on material balance and reaction kinetics, and combines real-time flue gas flow rate, system pressure, valve status, and other constraint parameters for rapid calculation and optimization decisions. The model output is no longer a single theoretical value, but a set of ammonia supply control commands that can directly drive actuators, typically including the target ammonia supply flow rate and the recommended opening degree of each ammonia injection branch valve.

[0091] Finally, in step S160, the intelligent ammonia concentration control device in the flue gas sends the ammonia supply control command generated in S150 to the ammonia supply module of the denitrification unit in real time via the industrial communication network. After receiving the command, the control system (such as a PLC) in the ammonia supply module drives the regulating valve to change its opening, precisely controlling the ammonia flow rate injected into the flue gas duct, and can also adjust the dilution air volume to optimize the mixing effect. The system then enters the next monitoring and control cycle, and the newly generated outlet NO... X The ammonia slip data will be used as feedback input to evaluate the control effect and fine-tune the model parameters, thereby forming a continuous and adaptive "monitoring-optimization-control" intelligent closed loop, realizing high-precision and low-cost operation of the denitrification process.

[0092] In conjunction with the first aspect, the monitoring system is connected to the piping of at least two ammonia absorption units via multi-port valves. Prior to step S110, the following steps are also included:

[0093] S010, control the multi-way valve to switch the sampling path, connecting the target ammonia absorption device that has completed flue gas absorption to the post-monitoring system.

[0094] The intelligent ammonia concentration control device in the flue gas controls a multi-way valve (such as a six-way or eight-way valve) to switch pathways based on a preset time sequence or event trigger signal. Its core operation involves disconnecting a channel (denoted as the target ammonia absorption device, e.g., channel A) that has completed the current cycle of flue gas absorption and whose internal absorbent is saturated with ammonia from the flue gas sampling circuit, while simultaneously switching its outlet pipe to connect to the subsequent detection unit (i.e., the liquid processing and detection section of the "post-monitoring system"). At the same time, the multi-way valve connects another cleaned and freshly filled backup ammonia absorption device (e.g., channel B) to the flue gas sampling circuit, initiating a new round of flue gas sampling and absorption. This achieves complete overlap between the sampling and detection processes in time, avoiding detection waiting time and thus achieving true continuous monitoring.

[0095] S020, start the transfer pump to transfer the ammonia-containing absorbent from the target ammonia absorption device to the detection pool.

[0096] After the pathway switching is completed, the intelligent control device for ammonia concentration in the flue gas starts the delivery pump (usually a high-precision peristaltic pump). This pump quantitatively and steadily delivers the ammonia-containing absorbent liquid contained in the target ammonia absorption device (channel A) to the detection cell via connecting pipelines. This ensures that the captured ammonia is completely transferred to the analysis unit, and at the same time, the quantitative delivery provides an accurate liquid volume basis for subsequent concentration calculations.

[0097] S030, control the dosing device to add compound alkaline solution to the detection tank, and adjust the pH of the absorption solution to the specified pH range.

[0098] After all the ammonia-containing absorbent has been transferred to the detection tank, the intelligent control device for ammonia concentration in the flue gas controls the dosing device. The dosing device precisely injects a fixed amount of compound alkaline solution (usually a mixture of sodium hydroxide and buffer solution) into the detection tank. The core purpose of this operation is to rapidly and stably adjust the pH of the absorbent to a specified alkaline range (e.g., pH=12). Under this pH condition, ammonia present in the absorbent as ammonium ions will rapidly convert into free ammonia gas, which is the optimal chemical form for the ammonia ion electrode to detect with high sensitivity and high selectivity. This step not only optimizes the detection conditions but also avoids drastic pH fluctuations by using the compound alkaline solution, ensuring the stability and repeatability of the detection.

[0099] In conjunction with the first aspect, step S120, which involves inputting the sampling parameters from the sampled data into a preset sampling control factor model and dynamically outputting the optimized sampling parameters, includes:

[0100] S121. Based on orthogonal experimental design, determine the key factors and their levels that affect the accuracy of ammonia concentration measurement. The key factors include at least the sampling flow rate, sampling time, NH3 concentration, and pH value of the absorption liquid.

[0101] The model is based on the theoretical framework of orthogonal experimental design, and pre-determines several key factors affecting the accuracy of ammonia concentration measurement and their multiple selectable levels. These key factors include at least the sampling flow rate, sampling time, NH3 concentration in the flue gas, and pH value of the absorbent. Each factor is set with multiple levels (e.g., three flow rate levels: 3 L / min, 5 L / min, and 7 L / min) to cover the possible range of actual operating conditions.

[0102] S122, for each key factor, obtain the measurement results of ammonia concentration under each level combination according to orthogonal experimental design.

[0103] According to L9(3) 4 Nine sets of experiments with different parameter combinations were arranged using an orthogonal array. During the experimental platform or actual verification of the monitoring system, flue gas sampling and ammonia concentration measurement were strictly performed according to each parameter combination (e.g., A1B1C1D1, A1B2C2D2, …, A3B3C3D3). The final ammonia concentration value measured by the system under each set of experiments was recorded as the measurement result (or experimental index). These nine sets of results constitute the data source for subsequent analysis.

[0104] S123, Perform range analysis on the measurement results, calculate the range analysis results of each key factor at each level, and the range analysis results include the average index value and the corresponding range.

[0105] Range analysis was performed on the above 9 sets of experimental data. For each factor, the average value of all experimental results at the same level was calculated, i.e., the average index value (K value). For example, for factor A (sampling flow rate), the average value K{A1} of all experimental results containing A1 at level A1 was calculated, and similarly, K{A2} and K{A3} were obtained. Then, the range (R) of the factor was calculated, which is the difference between the maximum and minimum values ​​of the average index value at each level. The formula for the range of each factor is as follows:

[0106] (1) Rv=max(Yv1,Yv2… Yvn) min(Yv1,Yv2… Yvn);

[0107] (2) Rt=max(Yt1,Yt2… Ytn) min(Yt1,Yt2… Ytn);

[0108] (3) Ra = max(Ya1, Ya2, ... Yan) min(Ya1,Ya2… Yan);

[0109] (4) Rp=max(Yp1,Yp2… Ypn) min(Yp1,Yp2… Ypn);

[0110] Where Rv is the range of sampling flow rate, Rt is the range of sampling time, Ra is the range of NH3 concentration in flue gas, and Rp is the range of pH value of absorbent; max() is to take the maximum value, min() is to take the minimum value, Yvn is the sampling flow rate value at the Nth level; Ytn is the sampling time value at the Nth level; Yan is the NH3 concentration in flue gas at the Nth level; and Ypn is the pH value of absorbent at the Nth level.

[0111] S124. Based on the range analysis results, determine the order of influence of each key factor on the ammonia concentration measurement results.

[0112] Compare the four calculated range values ​​Rv, Rt, Ra, and Rp. The magnitude of the range R directly reflects the degree of influence of the factor's level variation on the measured index (accuracy of ammonia concentration). The larger the R value, the more significant the influence of the factor on the measurement result.

[0113] S125, based on the range, determine the order of the influence of each key factor on the measurement results, and select the combination of key factor levels that makes the measurement results optimal as the optimized sampling parameters.

[0114] Combination Figure 3 The influence trend diagram shown uses the horizontal axis to represent four key factors (sampling flow rate v, sampling time t, NH3 concentration a in flue gas, and pH value p in the absorbent) and their three levels (e.g., V: 4, 5, 6 L / min; t: 20, 25, 30 min; a: 1, 3, 5 ppm; p: 10, 11, 12). The vertical axis represents the measured index value, specifically the quantitative result obtained through orthogonal experiments reflecting the precision or accuracy of ammonia concentration measurement. The diagram illustrates how the measurement effect (index value) changes for each key factor (v, t, a, p) at different level settings. For example, for factor t (sampling time), the index value may continuously increase as time increases from 20 min to 30 min, indicating that extending the sampling time is beneficial to improving measurement accuracy within the experimental range. By comparing the fluctuation range (i.e., range R) of the index values ​​of each factor at different levels, the primary and secondary influences can be determined. Figure 3As shown, the factor with the largest variation in index value (difference between high and low points) is the one that has the most significant impact on the measurement results. The order of influence of each factor on NH3 concentration measurement is: sampling time > sampling flow rate > NH3 concentration > absorbent pH. Subsequently, for each factor, the highest level of index value is the optimal level for that factor. The optimal level points of each factor can be clearly read in the figure. Combining these optimal levels (e.g., v=6, t=30, a=5, p=12) constitutes the optimal combination of sampling parameters recommended by the sampling control factor model.

[0115] Steps S121-S125 are essentially the construction and training phase of the sampling control factor model. Once the model is established (i.e., the primary and secondary relationships of the factors and the optimal combination of levels are determined), it is pre-installed in the intelligent control device for ammonia concentration in flue gas. During real-time operation in step S120, the model does not repeat the experiment every time. Instead, based on this prior knowledge base, combined with the currently input sampling parameters (which may be non-optimal initial values ​​or parameters from the previous round) and operating conditions, it dynamically outputs a set of optimized sampling parameters that are suitable for the current context and approach the optimal combination (e.g., prioritizing sufficient sampling time and recommending higher sampling flow rates and pH values) through built-in logic (such as table lookup, interpolation, or rule-based reasoning). This achieves adaptive optimization of the monitoring system and improves data quality.

[0116] In conjunction with the first aspect, the inlet end of the ammonia absorption device is connected to the outlet end of the sampling tube, and the inlet end of the sampling tube is connected to the flue gas source through a pre-filter; the measurement error correction model is used to compensate for the adsorption loss of ammonia in the pipeline during the sampling process.

[0117] The new round of sampling data includes the ammonia concentration in the detection cell, the volume of the solution in the detection cell, and the cumulative volume of sampled gas. Step S140 includes:

[0118] S141, obtain the ammonia adsorption capacity per unit length of the pre-calibrated sampling pipeline and the length of the sampling pipeline.

[0119] S142, based on the measured ammonia concentration in the detection pool, the volume of the solution in the detection pool, the cumulative sampled gas volume, the ammonia adsorption amount per unit length, and the length of the sampling pipeline, the corrected flue gas ammonia escape concentration is calculated using the measurement error correction model.

[0120] In the monitoring system, the inlet of the ammonia absorption device is connected to the outlet of the sampling tube, and the inlet of the sampling tube is connected to the flue gas source (such as a flue) through a pre-filter made of nano-ceramic material. When the flue gas flows through this sampling tube, some of the ammonia (NH3) molecules are adsorbed onto the tube wall surface, resulting in the loss of the target substance. This adsorption loss is a systematic error; if not compensated for, the flue gas ammonia concentration calculated from the absorption liquid measurement results will consistently be lower than the true value, meaning the measurement results will be systematically undervalued.

[0121] In step S141, the sampling pipeline length (l) is an inherent structural parameter of the system. During the standardized design and manufacturing of the monitoring system, the sampling pipeline length from the filter outlet to the absorption device inlet is fixed, and its value (unit: mm) is stored as a known constant in the intelligent control device for ammonia concentration in flue gas.

[0122] Ammonia adsorption capacity per unit length of sampling pipeline (C) a The core calibration parameter is [parameter 1]. This parameter, obtained through prior experimental calibration, characterizes the adsorption capacity of a sampling tube of a specific material, inner diameter, and surface condition for ammonia gas per unit length under standard sampling conditions. The calibration method typically involves: introducing standard ammonia gas of a known concentration, collecting and measuring the total amount of ammonia that does not adsorb through the tube and enters the absorption device; the difference between this amount and the total amount of ammonia introduced is the total adsorption mass of the tube (m³). a (Unit: μg). The specific calculation is as follows: C a =m a ÷l.

[0123] The C value for this batch was determined by averaging multiple experiments. a The value is pre-stored in the system. This parameter is crucial for quantifying the correction model and compensating for adsorption losses.

[0124] Step S142 performs the core compensation calculation. The intelligent control device for ammonia concentration in the flue gas calls up the measured data obtained from the new round of sampling (specifically, the measured ammonia concentration C in the detection cell). L The volume of the solution in the detection cell, V L Cumulative sampled gas volume V Q ) and pre-calibration parameters (C a 、l). Among them, C L The unit is mg / L; V L The unit is mL; V Q The unit is L; C a The unit for is ug / mm; the unit for l is mm.

[0125] The revised calculation logic is as follows:

[0126] First, calculate the apparent total ammonia amount without considering pipeline losses: C L ×V L This corresponds to the actual amount of ammonia captured in the absorbent liquid.

[0127] Secondly, calculate the estimated total ammonia loss due to pipeline adsorption: C a ×l corresponds to the amount of ammonia that failed to enter the absorption liquid due to adsorption and retention in the pipeline.

[0128] Then, add the two together to obtain the estimated total amount of original ammonia in the flue gas.

[0129] Finally, divide this total amount by the cumulative sampled gas volume V. Q This yields the corrected ammonia slip concentration C, which is closer to the true gas phase concentration. A .

[0130] Based on the above correction logic, the basic calculation formula before correction is: C A =(C L ×V L )÷V Q .

[0131] Corrected ammonia slip concentration =[C L0 + (C a ×l)÷V0+ Ra÷2] ×V L ÷V Q ;

[0132] in, Corrected ammonia slip concentration (unit: mg / m³) 3 C, that is, the ammonia slip concentration measured at the outlet of the denitrification unit; L0 V0 represents the measured ammonia concentration in the detection cell (unit: mg / L); V0 represents the volume of the solution in the detection cell (unit: mL); Ra represents the range under the influence of ammonia concentration.

[0133] To verify the practical effectiveness of the NH3 concentration measurement correction formula, laboratory validation was conducted. The experimental parameters during the validation process were: sampling flow rate of 5 L / min, sampling time of 25 min, NH3 standard gas concentration of 3 ppm, sample solution volume adjusted to 200 mL, and pH of 12. The experimental results showed that the NH3 concentration measurement correction value matched the standard value, indicating high accuracy and good measurement performance of the NH3 concentration measurement correction formula. The experimental results are as follows: Figure 4As shown in the figure, the graph visually demonstrates the actual effect of the measurement error correction model of the present invention: In multiple repeated experiments, the concentration of the NH3 standard gas (the solid green line with triangular blocks) representing the true value remained constant, while the uncorrected system measurement value (the solid black line with square blocks) was consistently and stably lower than the true value, and the corrected measurement value obtained after model correction (represented by the solid red line with circular blocks in the figure). It can be seen from the figure that in five repeated experiments (combining the five samples on the horizontal axis), the true value curve remained horizontally stable, while the uncorrected system measurement value showed a consistently low trend; after processing by the correction model, the corrected measurement value highly overlapped with the true value curve, indicating that the model effectively compensated for the pipeline adsorption loss, significantly improved the accuracy of the monitoring results, and also exhibited less fluctuation in the corrected data, further proving its role in improving measurement precision and reliability. This is key experimental evidence verifying the effectiveness of the technical solution of the present invention.

[0134] Laboratory verification (using standard ammonia) showed that the measured corrected values ​​significantly improved in agreement with the standard values ​​after applying this correction model, proving the model's effectiveness. Therefore, the corrected flue gas ammonia slip concentration output in step S140 exhibits a substantial improvement in accuracy and reliability compared to the uncorrected original calculation, providing a reliable data foundation for subsequent intelligent control.

[0135] In conjunction with the first aspect, step S150 includes:

[0136] S151, obtain the operating parameters of the denitrification system; the operating parameters include the corrected flue gas ammonia slip concentration, the NOx concentration at the inlet of the denitrification unit, the NOx concentration at the outlet, and the flue gas flow rate.

[0137] The intelligent control device for ammonia concentration in flue gas collects and integrates key operational data from the monitoring system and the denitrification system in real time, forming the basic input for model calculations. These operational parameters include at least the corrected flue gas ammonia slip concentration, the NOx concentration at the inlet and outlet of the denitrification unit, and the flue gas flow rate.

[0138] The corrected flue gas ammonia slip concentration comes from the high-precision monitoring results of step S140, representing the current ammonia residue level at the denitrification outlet; the inlet NOx concentration and outlet NOx concentration of the denitrification unit reflect the treatment load and emission compliance status, respectively. The flue gas flow rate is a key parameter determining the total amount of reactants.

[0139] S152, based on the corrected flue gas ammonia slip concentration, inlet NOx concentration, outlet NOx concentration and flue gas flow rate, the theoretical ammonia supply is calculated through the linkage control model.

[0140] Input the operating parameters obtained from S151 into the core function of the linkage control model:

[0141]

[0142] in: Ammonia supply rate, kg / h; The ammonia slip concentration at the outlet of the denitrification unit, in mg / m³. 3 ; NO at the inlet of the denitrification reactor X Concentration, mg / m³ 3 ; NO at the outlet of the denitrification unit X Concentration, mg / m³ 3 ; The inlet flue gas flow rate of the denitrification unit is m. 3 / h.

[0143] This function is usually established based on the material balance and reaction kinetics of the reaction zone of the denitrification unit. Its physical meaning is: the theoretical ammonia consumption required at the current flue gas flow rate to achieve the conversion from the inlet NOx concentration to the target outlet NOx concentration, taking into account the currently measured ammonia slip level (reflecting the reaction utilization rate).

[0144] S153, retrieve the current running constraint parameters.

[0145] The model synchronously acquires current operating constraint parameters that reflect the actual physical state of the system and the capabilities of the equipment. These parameters ensure the executability and safety of control commands and include at least: the state of the ammonia supply system, mixing and flow field conditions, and measurement representativeness.

[0146] The ammonia supply system status includes the current valve opening degree of each ammonia injection branch pipe and the main pipe, as well as the ammonia gas pressure and temperature; the mixing and flow field conditions include the dilution air volume and the uniformity of the flue gas flow field; and the representative measurements include the uniformity of the NOx concentration distribution on the flue section.

[0147] S154 calculates the actual ammonia supply and corresponding control parameters based on the theoretical ammonia supply and system constraint parameters through multi-parameter coupling relationships.

[0148] The intelligent control device for ammonia concentration in flue gas is based on the theoretical ammonia supply obtained from S152, combined with the multi-dimensional constraint parameters obtained from S153, and performs comprehensive calculation through the multi-parameter coupling relationship built into the model.

[0149]

[0150] In the formula, The ammonia supply flow rate is expressed in kg / h. The opening degree of valves related to the ammonia supply system (ammonia supply pipe, main pipe, ammonia injection branch pipe, etc.) is expressed in % (%). This refers to the pressure of ammonia gas, expressed in MPa. The temperature of gaseous ammonia is expressed in °C. To dilute the air volume, m 3 / h; To improve the uniformity of the flue gas flow field in the denitrification system; NO at the inlet and outlet of the denitrification unit X Concentration uniformity.

[0151] The calculation assesses and avoids equipment limits (such as valves being nearly fully open), optimizes mixing effects (such as matching dilution air volume), compensates for measurement and flow field inhomogeneities, and finally outputs a set of actual ammonia supply and corresponding control parameters, such as: total ammonia supply flow rate setpoint, specific opening adjustment of ammonia injection valves in each zone, and recommended dilution fan frequency.

[0152] S155 generates ammonia supply control commands based on control parameters. The commands include at least one of ammonia supply flow rate setpoint and valve opening adjustment commands.

[0153] The constraint parameters include at least one or more of the following: valve opening degree of the ammonia supply system, ammonia pressure, ammonia temperature, dilution air volume, flue gas flow field uniformity, and NOx concentration distribution uniformity.

[0154] The control parameters calculated by S154 are encapsulated into specific ammonia supply control commands that can be directly recognized and executed by downstream actuators (such as PLCs and control valves). These commands are typically issued in the form of digital signals or standard communication protocols (such as 4-20mA or Modbus), and their content includes at least one or more of the following: ammonia supply flow setpoint and valve opening adjustment command.

[0155] In conjunction with the first aspect, step S160 includes:

[0156] S161 sends the ammonia supply control command to the ammonia supply module in real time via the communication interface.

[0157] After generating the S150 instruction, the intelligent ammonia concentration control device in the flue gas immediately transmits the encapsulated ammonia supply control instruction (including specific parameters such as target flow rate and valve opening) to the controller (such as a PLC or dedicated regulator) corresponding to the ammonia supply module of the denitrification unit in real time at millisecond speed via its integrated industrial communication interface (such as a communication module supporting protocols such as Modbus TCP, PROFINET, and OPC UA). This low-latency, high-reliability instruction transmission is a key link to ensure that the entire intelligent control system responds quickly and is synchronized with the actual operating conditions of the denitrification system, avoiding control inaccuracies or oscillations caused by instruction lag.

[0158] S162, based on instructions, adjusts the opening of the control valves on the ammonia supply main pipe and ammonia injection branch pipe in the ammonia supply module, and / or adjusts the air volume output of the dilution fan.

[0159] Upon receiving an instruction, the controller of the ammonia supply module drives its actuators to perform corresponding actions: precisely controlling the mass flow rate of ammonia injected into each area of ​​the SCR reactor flue by adjusting the opening of the main regulating valve on the ammonia supply header and the zone regulating valves on each ammonia injection branch pipe. This directly corresponds to the "valve opening adjustment instruction" in instruction S155 and is the core of achieving precise spatial distribution control of ammonia injection. Simultaneously, the speed of the dilution fan or the opening of the inlet damper can be adjusted synchronously according to the instruction to control the airflow output. The function of the dilution air is to carry and dilute the ammonia, ensuring it is fully and safely mixed with the flue gas. Coordinated adjustment of its airflow is an important means to optimize the uniformity of ammonia or flue gas mixing, prevent excessively high local ammonia concentrations, and improve reaction efficiency.

[0160] Secondly, embodiments of this application provide an intelligent control device for ammonia concentration in flue gas. The device is communicatively connected to a monitoring system and a denitrification device. The monitoring system is used to collect flue gas samples and detect the ammonia concentration therein. The denitrification device is equipped with an ammonia supply module to control the amount of ammonia injected. The device is used to execute the method described above. The device includes: an initial acquisition module, a parameter optimization module, an optimized sampling module, a calculation module, an instruction generation module, and an adjustment module.

[0161] The initial acquisition module is used to acquire the sampling data collected by the monitoring system.

[0162] The parameter optimization module is used to input the sampling parameters in the sampled data into a preset sampling control factor model, dynamically output the optimized sampling parameters, and feed them back to the monitoring system.

[0163] The optimized sampling module is used to acquire a new round of sampling data collected by the monitoring system based on the optimized sampling parameters.

[0164] The calculation module is used to calculate the corrected flue gas ammonia escape concentration based on the new round of sampling data and through the measurement error correction model.

[0165] The instruction generation module is used to input the corrected flue gas ammonia slip concentration and the NOx concentration at the inlet and outlet of the denitrification unit into the preset NH3-NOx linkage control model to generate ammonia supply control instructions.

[0166] The adjustment module is used to send ammonia supply control commands to the ammonia supply module of the denitrification unit to adjust the ammonia injection rate.

[0167] Thirdly, embodiments of the present invention also provide a flue gas treatment system, including an intelligent control device for ammonia concentration in flue gas as described above; the device is communicatively connected to a monitoring system and a denitrification device; the monitoring system is used to collect flue gas samples and detect the ammonia concentration therein, and the denitrification device is equipped with an ammonia supply module to control the amount of ammonia injected.

[0168] The flue gas treatment system provided in this application integrates high-precision online monitoring and real-time feedback control functions, forming a complete automated operation platform. The system comprises three core components connected via a communication network: a monitoring system, an intelligent ammonia concentration control device for flue gas, and a denitrification unit. The monitoring system is responsible for the collection, pretreatment, and accurate determination of ammonia concentration in flue gas samples. Its key components include a pre-filter for removing particulate matter, a molten salt thermal storage sampling tube to prevent condensation loss, a multi-port valve and multi-stage absorption bottle for continuous sampling, and an improved ammonium ion electrode and a matching automatic calibration and cleaning unit for detection. The intelligent ammonia concentration control device for flue gas, as the core processing unit of the system, incorporates a data model-based algorithm to receive monitoring data, perform error correction and optimization calculations, and generate control commands. The denitrification unit is equipped with a controlled ammonia supply module, capable of receiving commands and precisely adjusting the ammonia injection rate.

[0169] Combination Figure 6 As shown, the online ammonia concentration monitoring system in the flue gas (i.e., the monitoring system in this embodiment) provides real-time, accurate ammonia escape concentration data. Simultaneously, the denitrification unit and its DCS provide real-time operating parameters such as inlet / outlet NOx concentration, flue gas flow rate, and ammonia injection rate. This data is aggregated into the data aggregation and processing layer and combined with the stored historical database to form a dataset for in-depth analysis. Subsequently, it enters the intelligent analysis and decision-making layer. The control model, integrating NH3-NOx linkage control, error correction, and machine learning algorithms, uses this dataset for real-time calculation and self-learning. It iterates under the action of the iterative correction model and optimizes the denitrification system's operating parameters to find the optimal operating point while meeting emission constraints, thus forming optimal operating parameters. Finally, at the execution and feedback layer, the optimized parameters (such as the ammonia injection rate setpoint) are fed back to the denitrification control system in real time, automatically adjusting equipment operation. The denitrification unit operates under the optimal parameter command, achieving synchronous and precise control and efficiency improvement of NH3-NOx. The new data generated after optimization will then initiate the next optimization cycle, thereby achieving continuous self-optimization and intelligent operation of the system.

[0170] In this embodiment, the high precision and timeliness of the monitoring system provide reliable input for intelligent control, while the decision output of the intelligent control model directly optimizes the execution effect of the denitrification process. The system can automatically adjust the sampling strategy and control parameters according to changing operating conditions, thereby improving the representativeness and accuracy of ammonia concentration measurement as well as the precision and stability of denitrification control, realizing full-chain optimization from sample collection to process control.

[0171] In conjunction with the third aspect, the monitoring system includes: a sampling unit, a heated sampling tube, an ammonia absorption device, and a detection unit.

[0172] The sampling unit has its inlet end connected to the flue via a pre-filtered nano-ceramic filter, and its outlet end connected to at least two ammonia absorption devices via a multi-way switching valve.

[0173] The heat tracing sampling tube is located between the pre-filter and the multi-way switching valve. It adopts a double-layer sleeve structure, with flue gas passing through the inner tube and molten salt heat storage material filling the interlayer. It is also equipped with an electric heating device.

[0174] Ammonia absorption device, comprising two or more traps connected in series, for capturing ammonia in flue gas with an absorbent liquid.

[0175] The detection unit includes a detection cell, a pH meter, an ammonia ion electrode, and a dosing device, and is used to adjust the volume, pH, and ammonia concentration of the ammonia-containing absorbent solution.

[0176] In this embodiment, the monitoring system consists of a sampling unit, a heated sampling tube, an ammonia absorption device, and a detection unit connected in sequence. The inlet of the sampling unit is connected to the flue through a pre-filter (nano-ceramic filter) to remove particulate matter, and its outlet is connected in parallel with at least two ammonia absorption devices through a multi-way switching valve to achieve alternating sampling channels. The heated sampling tube is located between the filter and the multi-way switching valve. It adopts a double-layered tube structure with an inner tube for flue gas passage, a jacket filled with molten salt heat storage material, and equipped with an electric heating device. This structure is used to continuously and uniformly heat the flue gas to prevent condensation and ammonia loss. The ammonia absorption device includes two or more traps connected in series. The traps contain absorbent liquid and the inner walls are often treated with superhydrophobicity to efficiently capture ammonia in the flue gas. The detection unit includes a detection cell, a pH meter, a dosing device, and an ammonia ion electrode. This unit is used to adjust the volume of the ammonia-containing absorbent liquid after absorption, add alkali to adjust the pH to a set value, and finally measure the ammonia concentration in the solution.

[0177] In conjunction with the third aspect, the ammonia ion electrode is an improved ammonium ion selective electrode, and its ion-permeable membrane surface is provided with a diamond-like protective coating; the inner wall of the trap of the ammonia absorption device is provided with a superhydrophobic coating; the system also includes a waste liquid regeneration device for regenerating and recycling the absorption liquid after detection.

[0178] In this embodiment, the monitoring system has undergone targeted optimization of key components to improve overall performance and reliability. Specifically, the ammonia ion electrode used is an improved ammonium ion selective electrode. The ion-permeable membrane surface of this electrode is coated with a diamond-like carbon protective coating prepared by plasma-enhanced chemical vapor deposition, which significantly enhances the wear resistance of the membrane and thus extends the service life of the electrode under continuous analysis conditions. The inner wall of the trap of the ammonia absorption device is coated with a superhydrophobic coating, which can effectively reduce the adhesion and residue of the absorbent on the device wall, prevent ammonia loss caused by liquid film retention, and ensure the collection efficiency. In addition, the system also integrates a waste liquid regeneration device, which regenerates the absorbent after detection through membrane separation or ion exchange technology, removes ammonium ions and other components, restores its absorption capacity, and returns it to the system for recycling. This greatly reduces the consumption of fresh absorbent and the discharge of waste liquid.

[0179] Thirdly, embodiments of this application provide an electronic device, combined with Figure 5 As shown, the electronic device includes a memory 131 and a processor 130. The memory 131 stores a computer program, and the processor 130 runs the computer program to make the electronic device perform the above-described method.

[0180] Furthermore, combined Figure 5 The electronic device shown also includes a bus 132 and a communication interface 133, with the processor 130, the communication interface 133 and the memory 131 connected via the bus 132.

[0181] The memory 131 may include high-speed random access memory (RAM) and may also include non-volatile memory, such as at least one disk storage device. Communication between this system network element and at least one other network element is achieved through at least one communication interface 133 (which can be wired or wireless), such as the Internet, wide area network, local area network, metropolitan area network, etc. The bus 132 may be an ISA bus, PCI bus, or EISA bus, etc. The bus can be divided into address bus, data bus, control bus, etc. For ease of representation, Figure 5 The symbol is represented by a single double-headed arrow, but this does not mean that there is only one bus or one type of bus.

[0182] Processor 130 may be an integrated circuit chip with signal processing capabilities. In implementation, each step of the above method can be completed by the integrated logic circuitry in the hardware of processor 130 or by instructions in software form. Processor 130 may be a general-purpose processor, including a Central Processing Unit (CPU), a Network Processor (NP), etc.; it may also be a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field-Programmable Gate Array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. It can implement or execute the methods, steps, and logic block diagrams disclosed in the embodiments of this invention. The general-purpose processor may be a microprocessor or any conventional processor. The steps of the methods disclosed in the embodiments of this invention can be directly manifested as execution by a hardware decoding processor, or execution by a combination of hardware and software modules in the decoding processor. The software module can reside in a mature storage medium in the art, such as random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, or registers. This storage medium is located in memory 131, and processor 130 reads the information in memory 131 and, in conjunction with its hardware, completes the steps of the method described in the foregoing embodiments.

[0183] Fourthly, embodiments of this application provide a readable storage medium storing computer program instructions, which are read and executed by a processor to perform the above-described method.

[0184] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working process of the system and apparatus described above can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0185] Furthermore, in the description of the embodiments of the present invention, unless otherwise explicitly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art can understand the specific meaning of the above terms in the present invention based on the specific circumstances.

[0186] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, essentially, or the part that contributes to the prior art, or a portion 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 this 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.

[0187] In the description of this invention, it should be noted that the terms "center," "upper," "lower," "left," "right," "vertical," "horizontal," "inner," and "outer," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are used only for the convenience of describing the invention and for simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on the invention. Furthermore, the terms "first," "second," and "third" are used for descriptive purposes only and should not be construed as indicating or implying relative importance.

[0188] Finally, it should be noted that the above embodiments are merely specific implementations of the present invention, used to illustrate the technical solutions of the present invention, and not to limit it. The scope of protection of the present invention is not limited thereto. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that any person skilled in the art can still modify or easily conceive of changes to the technical solutions described in the foregoing embodiments within the technical scope disclosed in the present invention, or make equivalent substitutions for some of the technical features; and these modifications, changes, 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, and should all be covered within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A method for intelligent control of ammonia concentration in flue gas, characterized in that, The method is applied to an intelligent control device for ammonia concentration in flue gas, the device being communicatively connected to a monitoring system and a denitrification device; the monitoring system is used to collect flue gas samples and detect the ammonia concentration therein, and the denitrification device is equipped with an ammonia supply module to control the ammonia injection rate; the method includes: Acquire sampling data collected by the monitoring system; The sampling parameters in the sampled data are input into a preset sampling control factor model, the optimized sampling parameters are dynamically output, and the results are fed back to the monitoring system. The monitoring system acquires a new round of sampling data based on the optimized sampling parameters. Based on the new round of sampling data, the corrected flue gas ammonia escape concentration is calculated using a measurement error correction model; wherein, the measurement error correction model is used to compensate for the adsorption loss of ammonia in the pipeline during the sampling process; The corrected flue gas ammonia escape concentration, the inlet NOx concentration and the outlet NOx concentration of the denitrification device are input into a preset NH3-NOx linkage control model to generate an ammonia supply control command. The ammonia supply control command is sent to the ammonia supply module of the denitrification unit to adjust the ammonia injection rate; The step of inputting the corrected flue gas ammonia slip concentration, the inlet NOx concentration, and the outlet NOx concentration of the denitrification device into a preset NH3-NOx linkage control model to generate an ammonia supply control command includes: The system acquires the operating parameters of the denitrification system, including the corrected flue gas ammonia slip concentration, the inlet NOx concentration of the denitrification unit, the outlet NOx concentration, and the flue gas flow rate. Based on the corrected flue gas ammonia slip concentration, the inlet NOx concentration of the denitrification unit, the outlet NOx concentration, and the flue gas flow rate, the theoretical ammonia supply is calculated using the linkage control model. The system acquires the current operating constraint parameters. Based on the theoretical ammonia supply and the constraint parameters, the actual ammonia supply and corresponding control parameters are calculated using a multi-parameter coupling relationship. The system generates an ammonia supply control command based on the control parameters, which includes at least one of an ammonia supply flow rate setpoint and a valve opening adjustment command. The constraint parameters include at least one or more of the following: ammonia supply system valve opening, ammonia pressure, ammonia temperature, dilution air volume, flue gas flow field uniformity, and NOx concentration distribution uniformity. The steps of inputting the sampling parameters from the sampled data into a preset sampling control factor model and dynamically outputting the optimized sampling parameters include: Based on orthogonal experimental design, the key factors affecting the accuracy of ammonia concentration measurement and their levels were determined. The key factors include at least the sampling flow rate, sampling time, NH3 concentration and pH value of the absorption solution. For each key factor, the ammonia concentration of the key factor under each combination of levels was measured using an orthogonal experimental design. A range analysis is performed on the measurement results to calculate the range analysis results of each key factor at each level. The range analysis results include the average index value and the corresponding range. Based on the range analysis results, the degree of influence of each of the key factors on the ammonia concentration measurement results is ranked. Based on the range, the influence of each key factor on the measurement results is ranked, and the combination of key factor levels that makes the measurement results optimal is selected as the optimized sampling parameters.

2. The method according to claim 1, characterized in that, The monitoring system is connected to the pipelines of at least two ammonia absorption devices via a multi-port valve; Before the step of acquiring the sampling data collected by the monitoring system, the method further includes: Control the multi-way valve to switch the sampling path and connect the target ammonia absorption device that has completed flue gas absorption to the monitoring system; Start the transfer pump to transport the ammonia-containing absorbent from the target ammonia absorption device to the detection tank; The dosing device is used to add compound alkaline solution to the detection tank and adjust the pH of the absorption solution to the specified pH range.

3. The method according to claim 2, characterized in that, The inlet end of the ammonia absorption device is connected to the outlet end of the sampling tube, and the inlet end of the sampling tube is connected to the flue gas source through a pre-filter; The new round of sampling data includes the ammonia concentration in the detection pool, the volume of the solution in the detection pool, and the cumulative volume of sampled gas; Based on the new round of sampling data, the steps for calculating the corrected flue gas ammonia slip concentration using a measurement error correction model include: Obtain the ammonia adsorption capacity per unit length of the pre-calibrated sampling pipeline and the length of the sampling pipeline; Based on the ammonia concentration in the detection pool, the volume of the solution in the detection pool, the cumulative volume of the sampled gas, the ammonia adsorption per unit length, and the length of the sampling pipeline, the corrected ammonia escape concentration in the flue gas is calculated using the measurement error correction model.

4. The method according to claim 1, characterized in that, The step of sending the ammonia supply control command to the ammonia supply module of the denitrification unit to adjust the ammonia injection rate includes: The ammonia supply control command is sent to the ammonia supply module in real time via the communication interface; Based on the ammonia supply control command, adjust the opening of the control valves on the ammonia supply main pipe and ammonia injection branch pipe in the ammonia supply module, and / or adjust the air volume output of the dilution fan.

5. An intelligent control device for ammonia concentration in flue gas, characterized in that, The device is communicatively connected to a monitoring system and a denitrification device; the monitoring system is used to collect flue gas samples and detect the ammonia concentration therein; the denitrification device is equipped with an ammonia supply module to control the ammonia injection rate; the intelligent control device is used to execute the method as described in any one of claims 1-4. The intelligent control device includes: An initial acquisition module is used to acquire sampling data collected by the monitoring system; The parameter optimization module is used to input the sampling parameters in the sampling data into a preset sampling control factor model, dynamically output the optimized sampling parameters, and feed them back to the monitoring system. An optimized sampling module is used to acquire a new round of sampling data collected by the monitoring system based on the optimized sampling parameters; The calculation module is used to calculate the corrected flue gas ammonia escape concentration based on the new round of sampling data using a measurement error correction model. The instruction generation module is used to acquire the operating parameters of the denitrification system; input a preset NH3-NOx linkage control model to generate ammonia supply control instructions; the operating parameters include the corrected flue gas ammonia slip concentration, the NOx concentration at the inlet of the denitrification unit, the NOx concentration at the outlet, and the flue gas flow rate; based on the corrected flue gas ammonia slip concentration, the NOx concentration at the inlet of the denitrification unit, the NOx concentration at the outlet, and the flue gas flow rate, the theoretical ammonia supply is calculated through the linkage control model; the current operating constraint parameters are acquired; based on the theoretical ammonia supply and the constraint parameters, the actual ammonia supply and the corresponding control parameters are calculated through multi-parameter coupling relationships; the ammonia supply control instructions are generated according to the control parameters, and the ammonia supply control instructions include at least one of ammonia supply flow rate setpoint and valve opening adjustment instructions; wherein, the constraint parameters include at least one or more of the following: ammonia supply system valve opening, ammonia pressure, ammonia temperature, dilution air volume, flue gas flow field uniformity, and NOx concentration distribution uniformity; The adjustment module is used to send the ammonia supply control command to the ammonia supply module of the denitrification device to adjust the ammonia injection rate.

6. An intelligent control system for ammonia concentration in flue gas, characterized in that, The system includes an intelligent control device for ammonia concentration in flue gas, a monitoring system, and a denitrification device as described in claim 5; the intelligent control device is communicatively connected to the monitoring system and the denitrification device respectively; the monitoring system is used to collect flue gas samples and detect the ammonia concentration therein, and the denitrification device is equipped with an ammonia supply module to control the amount of ammonia injected.

7. The system according to claim 6, characterized in that, The monitoring system includes: The sampling unit has its inlet end connected to the flue via a pre-filtered nano-ceramic filter, and its outlet end connected to at least two ammonia absorption devices via a multi-way switching valve. The heat tracing sampling tube is located between the pre-filter and the multi-way switching valve. It adopts a double-layer sleeve structure, with flue gas passing through the inner tube and molten salt heat storage material filling the interlayer. It is also equipped with an electric heating device. The ammonia absorption device includes two or more traps connected in series for capturing ammonia in flue gas with an absorbent liquid. The detection unit includes a detection cell, a pH meter, an ammonia ion electrode, and a dosing device, and is used to adjust the volume, pH, and ammonia concentration of the ammonia-containing absorbent solution.

8. The system according to claim 7, characterized in that, The ammonia ion electrode is an improved ammonium ion selective electrode, and its ion permeation membrane surface is provided with a diamond-like protective coating. The inner wall of the collector of the ammonia absorption device is provided with a superhydrophobic coating. The system also includes a waste liquid regeneration device for regenerating and recycling the absorbent liquid after testing.

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