Intelligent regulation and control flue gas denitration and desulfurization system

Abstract

The invention provides an intelligent regulation and control flue gas denitration and desulfurization system, and relates to the field of flue gas denitration and desulfurization. The intelligent regulation and control flue gas denitration and desulfurization system comprises a flue gas inlet, a pretreatment module is arranged at the output end of the flue gas inlet, and a denitration system C and a desulfurization system D are arranged at the two output ends of the pretreatment module. According to the system, flue gas is sequentially treated through the flue gas inlet, the pretreatment module, the denitration system C and the desulfurization system D, data intercommunication and cooperative regulation and control of all links are achieved through the intelligent management and control platform, the system is different from a traditional denitration-desulfurization independent operation mode, the removal efficiency is improved by 5%-10%, and the energy consumption is reduced. Meanwhile, a denitration waste catalyst is recycled through a resource recycling system, desulfurization waste water is subjected to zero-discharge treatment to achieve gypsum high-valued treatment and waste water recycling, the comprehensive utilization rate of solid waste is larger than or equal to 90%, the treatment cost is reduced by 30% compared with a traditional process, and a digital twin engine (the running state of a real-time mirroring physical system supports virtual debugging of process parameters) is adopted.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of flue gas denitration and desulfurization, in particular to an intelligent control flue gas denitration and desulfurization system. BACKGROUND

[0002] Flue gas desulfurization and denitration refers to the removal of sulfur dioxide (SO2) and nitrogen oxides (NOx) in flue gas through a series of processes to reduce environmental impact. Desulfurization and denitration processes can effectively reduce harmful gas emissions in the atmosphere, improve air quality, ensure production safety, and common desulfurization technologies include semi-dry desulfurization and ammonia desulfurization. The former uses Na2CO3 solution as a desulfurizer, and the latter uses ammonia as an absorbent to remove SO2 in flue gas. Denitration usually uses selective catalytic reduction (SCR) method, which reacts ammonia with NOx in flue gas to produce non-polluting nitrogen (N2) and water (H2O). The application of these technologies is crucial for reducing flue gas pollution, protecting the environment and human health. Flue gas denitration and desulfurization is a core technology for controlling atmospheric pollutants (nitrogen oxides NO x , sulfur dioxide SO2) in the industrial field, mainly used for waste gas treatment in power, steel, chemical, cement and other industries, and is a key means to achieve the "double carbon" target and improve air quality.

[0003] Although this patent technology uses a combination of traditional SCR denitration and wet desulfurization processes, it can achieve certain pollutant removal effects, but the existing system relies on manual setting of fixed parameters (such as ammonia injection amount, slurry pH value), and cannot respond in real time to fluctuations in flue gas composition (such as changes in fuel sulfur content, sudden load increase of the unit), resulting in unstable NO x / SO2 removal efficiency (fluctuation range up to 15%-20%), and even the risk of exceeding the standard. Therefore, the present application provides an intelligent control flue gas denitration and desulfurization system to solve the problems raised in the background art. SUMMARY

[0004] 1. Technical problems solved In view of the deficiencies of the prior art, the present application provides an intelligent control flue gas denitration and desulfurization system, which solves the problem of poor dynamic adaptability.

[0005] 2. Technical solutions To achieve the above purpose, the present application is implemented by the following technical solutions: The intelligent control flue gas denitration and desulfurization system comprises a flue gas inlet, the output end of the flue gas inlet is provided with a pretreatment module, and the two output ends of the pretreatment module are provided with a denitration system C and a desulfurization system D; The output end of the denitration system C is provided with a denitration byproduct treatment, the output end of the denitration byproduct treatment is provided with a resource recycling system, two output ends of the desulfurization system D are provided with a clean flue gas emission and desulfurization wastewater and gypsum treatment, and the output end of the desulfurization wastewater and gypsum treatment is provided with a wastewater zero emission treatment; The input end of the denitration system C and the input end of the desulfurization system D are provided with an intelligent management and control platform, the inside of the intelligent management and control platform is provided with a digital twin engine and an advanced control algorithm, and the inside of the advanced control algorithm is provided with a model predictive control and reinforcement learning.

[0006] Through the above technical solution, the flue gas is sequentially treated through a flue gas inlet, a pretreatment module, the denitration system C and the desulfurization system D, and each link realizes data intercommunication and collaborative regulation through the intelligent management and control platform. Different from the traditional independent operation mode of “denitration-desulfurization”, the removal efficiency is improved by 5%-10%. At the same time, the denitration waste catalyst is regenerated and utilized through the resource recycling system, the desulfurization wastewater is treated through the zero emission treatment to realize “gypsum high value and wastewater reuse”, the comprehensive utilization rate of solid waste is greater than or equal to 90%, the disposal cost is reduced by 30% compared with the traditional process, the digital twin engine (real-time mirror of the physical system running state, supporting virtual debugging of process parameters (such as simulation of the influence of ammonia injection amount change on denitration efficiency), and the debugging time is shortened by 50%) and the advanced control algorithm (model predictive control, prediction of future 30-minute change based on historical data of flue gas composition, advance adjustment of reagent addition amount, reduction of control hysteresis by 70%, reinforcement learning, self-iterative optimization of multiple objectives (removal efficiency, energy consumption, cost), global optimal control, and reduction of reagent consumption by 15%-20%) are introduced, so that the system has virtual simulation and autonomous optimization capabilities, and breaks through the hysteresis limitation of traditional PID control.

[0007] Further, the output end of the clean flue gas emission is provided with an online monitoring terminal, the input end of the online monitoring terminal is provided with a laser gas analyzer, an infrared thermal imager and a distributed optical fiber sensor, and the output end of the online monitoring terminal is arranged in the intelligent management and control platform. Through the above technical solution, the online monitoring terminal integrates a laser gas analyzer (NO x / SO2 monitoring accuracy ±1%), an infrared thermal imager (temperature field scanning) and a distributed optical fiber sensor (absorption tower slurry parameters), and the data acquisition frequency reaches 10Hz, which provides real-time support for intelligent control.

[0008] Further, the output end of the intelligent management and control platform is provided with a device state monitoring, the input end of the device state monitoring is provided with a vibration sensor and an oil monitoring instrument, and the output end of the device state monitoring is looped back to the intelligent management and control platform. Through the technical scheme, the device state monitoring captures device abnormalities (such as bearing wear and gear box failure) through a vibration sensor and an oil monitor, early warning is advanced by more than 30 minutes, and the number of unplanned shutdowns is reduced by 50%.

[0009] Further, the data transmitted between the intelligent management and control platform and the device state monitoring is vibration, temperature and oil data; Through the technical scheme, the vibration, temperature and oil data are transmitted to facilitate real-time adjustment of the system by personnel.

[0010] Further, the output end of the intelligent management and control platform is provided with a multi-source database, and the output end of the multi-source database is looped back to the intelligent management and control platform. Through the technical scheme, the multi-source database stores full life cycle operation data (historical working conditions, fault records and model parameters), supports algorithm iteration and fault tracing, and shortens the control strategy optimization period from traditional "manual quarterly adjustment" to "real-time self-optimization".

[0011] Further, the inside of the denitration system C is provided with ammonia injection grid partition control and acoustic cleaning intelligent triggering, the inside of the desulfurization system D is provided with slurry circulating pump variable frequency group control and gypsum dehydration prediction, and the intelligent management and control platform and the denitration system C and the desulfurization system D interact through control instructions. Through the technical scheme, the ammonia injection grid partition control can dynamically adjust the ammonia injection amount of each region according to the catalyst activity distribution, the ammonia escape rate is ≤3ppm (the traditional process is 8-10ppm), the secondary pollution and reagent waste are reduced, the acoustic cleaning intelligent triggering can automatically start cleaning combined with catalyst pressure drop data, the cleaning frequency is reduced by 40%, catalyst damage caused by manual misoperation is avoided, and the slurry circulating pump variable frequency group control can automatically adjust the pump set speed based on the pH value distribution in the absorption tower, the power consumption is reduced by 15%-20% compared with fixed speed operation, the "big horse pulling a small cart" problem is solved, the gypsum dehydration prediction adjusts the vacuum belt conveyor parameters in advance through the slurry composition model, the gypsum moisture content is stabilized at 8%-10% (the traditional process fluctuates by 15%-25%), and the high purity requirement of the building materials industry is met.

[0012] Further, the information looped back to the intelligent management and control platform in the multi-source database is historical data or model parameters. Through the technical scheme, the historical data and model parameters are stored to facilitate data loss and data tracing and recovery.

[0013] Further, the inner wall surface of the flue gas inlet is coated with a glass flake coating and acid-resistant mastic. Through the above technical scheme, through the inner wall coating glass scale coating and acid-resistant mastic composite layer, in the acidic flue gas with pH 1-4 and temperature ≤ 150 DEG C, the service life reaches 8 years or more (traditional carbon steel flue is only 1-2 years), and the maintenance cost is reduced by 60%.

[0014] 3. Beneficial effects The present application provides a smart control flue gas denitration and desulfurization system. It has the following beneficial effects: 1. The present application provides a smart control flue gas denitration and desulfurization system, which is different from the traditional "denitration-desulfurization" independent operation mode. The flue gas is sequentially treated by a flue gas inlet, a pretreatment module, a denitration system C, and a desulfurization system D. Each link realizes data intercommunication and collaborative control through an intelligent management and control platform, and the removal efficiency is improved by 5%-10%.

[0015] 2. The present application provides a smart control flue gas denitration and desulfurization system. The spent denitration catalyst is regenerated and utilized through a resource recovery system, and the desulfurization wastewater is treated by zero emission to realize "gypsum high value and wastewater reuse". The comprehensive utilization rate of solid waste is ≥ 90%, which reduces the disposal cost by 30% compared with the traditional process.

[0016] 3. The present application provides a smart control flue gas denitration and desulfurization system. Through the introduction of a digital twin engine (real-time mirroring of the physical system running state, supporting virtual debugging of process parameters (such as simulating the influence of ammonia injection amount change on denitration efficiency), and a advanced control algorithm (model predictive control, predicting the change in the next 30 minutes based on historical data of flue gas composition, adjusting the reagent dosage in advance, reducing the control hysteresis by 70%, and strengthening learning through self-iteration optimization of multiple objectives (removal efficiency, energy consumption, and cost) to achieve global optimal control, and reducing reagent consumption by 15%-20%), the system has virtual simulation and autonomous optimization capabilities, breaking through the hysteresis limitations of traditional PID control. BRIEF DESCRIPTION OF DRAWINGS

[0017] Figure 1 It is a main process structure schematic diagram of the flue gas treatment of the present application; Figure 2 It is a process structure schematic diagram of the denitration system C of the present application; Figure 3 It is a process structure schematic diagram of the desulfurization system D of the present application; Figure 4 It is a process structure schematic diagram of the monitoring and sensing layer of the present application; Figure 5 It is a process structure schematic diagram of the intelligent management and control platform of the present application; Figure 6 It is an internal program structure schematic diagram of the intelligent management and control platform of the present application; Figure 7It is an internal program structure schematic diagram of the denitration system C of the application. Figure 8 It is an internal program structure schematic diagram of the desulfurization system D of the application.

[0018] Among them, 1, flue gas inlet; 2, pretreatment module; 3, denitration system C; 301, ammonia injection grid partition control; 302, intelligent triggering of acoustic cleaning; 4, desulfurization system D; 401, frequency conversion group control of slurry circulating pump; 402, gypsum dehydration prediction; 5, denitration by-product treatment; 6, resource recovery system; 7, clean flue gas discharge; 8, desulfurization wastewater and gypsum treatment; 9, wastewater zero discharge treatment; 10, online monitoring terminal; 11, infrared thermal imaging instrument; 12, distributed optical fiber sensor; 13, laser gas analyzer; 14, intelligent management and control platform; 1401, digital twin engine; 1402, advanced control algorithm; 15, equipment state monitoring; 16, vibration sensor; 17, oil monitor; 18, multi-source database. DETAILED DESCRIPTION

[0019] The technical solutions in the embodiments of the application will be described clearly and completely below with reference to the drawings in the embodiments of the application. Obviously, the described embodiments are only some of the embodiments of the application, rather than all the embodiments of the application. Based on the embodiments in the application, all other embodiments obtained by a person of ordinary skill in the art without creative work fall within the protection scope of the application. Embodiment 1 As shown in Figure 1 , Figure 2 , Figure 3 , Figure 5 and Figure 6 indicate that the embodiments of the application provide an intelligent control flue gas denitration and desulfurization system, which comprises a flue gas inlet 1, the output end of the flue gas inlet 1 is provided with a pretreatment module 2, and the two output ends of the pretreatment module 2 are provided with a denitration system C 3 and a desulfurization system D 4; The output end of the denitration system C 3 is provided with a denitration by-product treatment 5, the output end of the denitration by-product treatment 5 is provided with a resource recovery system 6, the two output ends of the desulfurization system D 4 are provided with a clean flue gas discharge 7 and a desulfurization wastewater and gypsum treatment 8, and the output end of the desulfurization wastewater and gypsum treatment 8 is provided with a wastewater zero discharge treatment 9; The input end of the denitration system C3 and the input end of the desulfurization system D4 are provided with an intelligent management and control platform 14, the inside of the intelligent management and control platform 14 is provided with a digital twin engine 1401 and an advanced control algorithm 1402, the inside of the advanced control algorithm 1402 is provided with model predictive control and reinforcement learning, the flue gas is sequentially processed through a flue gas inlet 1, a pretreatment module 2, the denitration system C3 and the desulfurization system D4, and each link realizes data intercommunication and collaborative regulation through the intelligent management and control platform 14, which is different from the traditional independent operation mode of “denitration-desulfurization”, the removal efficiency is improved by 5%-10%, the waste catalyst of denitration is regenerated and utilized through the resource recycling system 6, the desulfurization wastewater is processed through zero emission to realize “gypsum high value and wastewater reuse”, the comprehensive utilization rate of solid waste is greater than or equal to 90%, the disposal cost is reduced by 30% compared with the traditional process, the digital twin engine 1401 (real-time mirror of the physical system operation state, supporting virtual debugging of process parameters (such as the influence of simulated ammonia injection amount change on denitration efficiency), the debugging time is shortened by 50%) and the advanced control algorithm 1402 (model predictive control, predicting the change in the next 30 minutes based on the historical data of flue gas composition, adjusting the reagent addition amount in advance, reducing the control hysteresis by 70%, reinforcement learning, optimizing multiple objectives (removal efficiency, energy consumption, cost) through self-iteration, realizing global optimal control, reducing the reagent consumption by 15%-20%) are introduced, so that the system has virtual simulation and autonomous optimization capabilities, and breaks through the hysteresis limitation of traditional PID control.

[0021] According to Figure 4 As shown in the figure, the output end of the clean flue gas discharge 7 is provided with an online monitoring terminal 10, the input end of the online monitoring terminal 10 is provided with a laser gas analyzer 13, an infrared thermal imager 11 and a distributed optical fiber sensor 12, and the output end of the online monitoring terminal 10 is provided in the intelligent management and control platform 14, the laser gas analyzer 13 (NO x / SO2 monitoring accuracy ±1%), the infrared thermal imager (temperature field scanning), the distributed optical fiber sensor 12 (absorption tower slurry parameters) are integrated through the online monitoring terminal 10, the data acquisition frequency reaches 10Hz, which provides real-time support for intelligent control, the output end of the intelligent management and control platform 14 is provided with an equipment state monitoring 15, the input end of the equipment state monitoring 15 is provided with a vibration sensor 16 and an oil monitoring instrument 17, and the output end of the equipment state monitoring 15 is looped to the intelligent management and control platform 14, the equipment state monitoring 15 captures equipment abnormalities (such as bearing wear and gear box failure) through the vibration sensor 16 and the oil monitoring instrument 17, the early warning lead is greater than or equal to 30 minutes, and the number of unplanned shutdowns is reduced by 50%.

[0022] According to Figure 4 and Figure 5As shown, the data transmitted between the intelligent management and control platform 14 and the equipment state monitoring 15 is vibration, temperature and oil data. Through the transmitted vibration, temperature and oil data, the purpose of facilitating personnel to make real-time adjustments to the system is achieved. The output end of the intelligent management and control platform 14 is provided with a multi-source database 18. The output end of the multi-source database 18 is looped to the intelligent management and control platform 14. The full life cycle operation data (historical working conditions, fault records, model parameters) are stored through the multi-source database 18, supporting algorithm iteration and fault tracing, and the control strategy optimization period is shortened from the traditional “manual quarterly adjustment” to “real-time self-optimization”.

[0023] According to Figure 5 , Figure 7 and Figure 8 , the inside of the denitration system C3 is provided with an ammonia injection grid partition control 301 and a sound wave ash removal intelligent trigger 302. The inside of the desulfurization system D4 is provided with a slurry circulating pump variable frequency group control 401 and a gypsum dehydration prediction 402. The intelligent management and control platform 14 interacts with the denitration system C3 and the desulfurization system D4 through control instructions. Through the ammonia injection grid partition control 301, the ammonia injection amount of each region can be dynamically adjusted according to the catalyst activity distribution. The ammonia escape rate is ≤3 ppm (the traditional process is 8-10 ppm), reducing secondary pollution and reagent waste. The sound wave ash removal intelligent trigger 302 can automatically start ash removal in combination with the catalyst pressure drop data, reducing the ash removal frequency by 40%, avoiding catalyst damage caused by manual misoperation. At the same time, the slurry circulating pump variable frequency group control 401 can automatically adjust the pump set speed based on the pH value distribution in the absorption tower, reducing power consumption by 15%-20% compared with constant speed operation, solving the “big horse pulling a small cart” problem. The gypsum dehydration prediction 402 adjusts the vacuum belt conveyor parameters in advance through the slurry composition model, and the gypsum moisture content is stably controlled at 8%-10% (the traditional process fluctuates by 15%-25%), meeting the high purity requirements of the building materials industry. The information in the multi-source database 18 looped to the intelligent management and control platform 14 is historical data or model parameters. Through the storage of historical data and model parameters, the effect of data loss and data tracing and recovery is facilitated. The inner wall surface of the flue gas inlet 1 is coated with glass flake coating and acid-resistant mortar. Through the coating of the glass flake coating and the acid-resistant mortar composite layer on the inner wall, the service life reaches more than 8 years (the traditional carbon steel flue gas only lasts for 1-2 years) in the acid flue gas with pH1-4 and temperature ≤150℃, reducing the maintenance cost by 60%.

[0024] Working principle: I. Full-process flue gas treatment and intelligent control logic 1. Flue gas treatment main process: Firstly, flue gas inlet 1 - pretreatment module 2: the flue gas first enters the pretreatment module 2 through the inlet flue, the temperature is adjusted to the best working range of the denitration system (such as 300-420℃ required by SCR) through the heat exchanger, and the large particle dust (particle size > 10um) is removed, which creates conditions for subsequent denitration and desulfurization; Then, denitration system C3: the pretreated flue gas enters the SCR / SNCR denitration device, the intelligent control platform 14 calculates the optimal ammonia injection amount in advance through model predictive control (MPC) according to the NO x Concentration data of the online monitoring terminal 10, and through the ammonia injection grid partition control 301, the ammonia water is accurately sprayed into the catalyst layer to react with NO x To generate N2 and H2O, the denitration efficiency is ≥92%; Desulfurization system D4: After denitration, the flue gas enters the wet / semi-dry desulfurization system, the intelligent control platform 14 dynamically adjusts the slurry circulating pump frequency (variable frequency group control) according to the SO2 concentration and pH value distribution in the absorption tower, so that the limestone slurry and SO2 fully react to generate gypsum, and the desulfurization efficiency is ≥97%; After that, clean flue gas discharge 7 and denitration byproduct treatment 5: standard flue gas is discharged through the chimney, denitration waste catalyst is sent to the resource recycling system 6 for regeneration and utilization, desulfurization wastewater is reused after zero emission treatment, and gypsum is dehydrated to a water content of ≤10% for building material production.

[0025] 2. Decision-making closed loop of intelligent control platform 14: Data acquisition: The online monitoring terminal 10 collects flue gas composition, temperature field, slurry parameters and other data at a frequency of 10Hz, and the equipment state monitoring 15 module transmits vibration, temperature, oil data to the platform in real time; Model prediction and optimization: The digital twin engine 1401 mirrors the physical system in real time, simulates the parameter response under different working conditions (such as the influence of ammonia injection amount change on denitration efficiency), and the MPC algorithm predicts the flue gas composition change in the next 30 minutes based on historical data, adjusts the reagent addition and reaction conditions in advance, and reduces the control lag by 70%; Instruction execution: The platform sends control instructions (such as ammonia injection grid opening, pump group frequency) to the denitration system C3 and the desulfurization system D4, and after the execution mechanism adjusts, the result is fed back through the monitoring layer, forming a "perception - decision - execution - feedback" closed loop.

[0026] II. Working principle of core technology module 1. Intelligent control of denitration system C3: Ammonia injection grid zoning control 301: Catalyst activity monitor detects catalyst activity in each zone in real time, and intelligent control platform 14 adjusts the ammonia injection amount of each zone according to the activity distribution (e.g. 20% attenuation of catalyst activity at the inlet section) to ensure uniform overall denitration efficiency, with ammonia escape rate ≤3 ppm (traditional process: 8-10 ppm); Acoustic wave dust cleaning intelligent triggering 302: Pressure sensors installed in the catalyst layer monitor pressure drop in real time. When the pressure drop exceeds the threshold (e.g. >1.5 kPa) or combined with historical dust accumulation trend model, the platform automatically triggers the acoustic wave dust cleaning device, reducing the cleaning frequency by 40% compared to manual setting, to avoid excessive cleaning causing mechanical damage to the catalyst.

[0027] 2. Dynamic optimization of desulfurization system D4: Variable frequency group control of slurry circulating pump 401: Distributed optical fiber sensor 12 monitors the pH value spatial distribution in the absorption tower (e.g. pH=5.8 at the top of the tower, pH=4.2 at the bottom of the tower), and intelligent control platform 14 calculates the optimal number of pump sets and frequency according to the pH gradient--reducing pump flow in high pH areas and increasing pump flow in low pH areas to stabilize the pH value in the tower at 5.0-5.5, reducing power consumption by 15%-20% compared to fixed speed operation; Gypsum dewatering prediction 402: Based on historical slurry density, running time and gypsum moisture content LSTM model, real-time prediction of dewatering effect, when the model predicts that the moisture content will exceed 10%, the platform automatically adjusts the speed of the vacuum belt conveyor (e.g. from 2m / min to 2.5m / min), to stabilize the moisture content at 8%-10%, meeting the building materials industry standards.

[0028] 3. Equipment condition monitoring 15 and predictive maintenance Vibration / temperature / oil data driven: Vibration sensor 16 collects vibration spectrum of fan impeller, when 1X rotational frequency amplitude exceeds threshold (e.g. >20 mm / s), combined with bearing temperature (>90℃) and oil iron element concentration (>80 ppm), intelligent control platform 14 locates bearing inner ring wear through fault tree analysis, 30 minutes in advance warning and generating replacement work order; Multi-source data fusion diagnosis: D-S evidence theory is used to fuse vibration, temperature and oil data--for example, under the joint evidence of "vibration kurtosis value >5 + bearing temperature >85℃ + oil abrasive particle size >10μm", the confidence of "bearing failure" is 0.92, triggering emergency shutdown protection, with false alarm rate ≤3%.

[0029] 4. Multi-source database 18 and algorithm iteration Historical data support real-time decision: When the SO2 concentration in flue gas rises from 300 mg / m³ to 500 mg / m³, the platform retrieves the historical data of 3 similar fluctuations in the past 6 months in the multi-source database 18, and calls the optimal parameter combination (slurry pH = 5.2, circulating pump frequency 45Hz). Complete parameter matching within 5 minutes, shorten 25 minutes compared with traditional manual debugging; Dynamic updating of model parameters: Based on the latest operation data (such as 15% activity attenuation of catalyst after 1 year of service), the SCR reaction kinetics model parameters (such as activity factor k from 0.023 min⁻¹ to 0.019 min⁻¹) are corrected by Bayesian optimization algorithm every week, so that NO x The prediction error of removal efficiency is reduced from ±8% to ±3%.

[0030] III. Material protection and system reliability principle Corrosion and wear-resistant design of flue gas inlet 1: The glass flake coating on the inner wall forms a labyrinth anti-permeation layer through the scale structure, preventing sulfuric acid droplets formed by SO2 / H2O from penetrating into the substrate. Acid-resistant putty fills the coating joints to enhance wear resistance. In flue gas with pH 1-4 and temperature ≤150℃, the composite layer can withstand dust scouring speed ≤30m / s. Subsequent protection can be performed on the flue gas inlet 1. System integration and fault tolerance: The intelligent control platform 14 and the denitration system C3 and the desulfurization system D4 use redundant communication links (such as OPC UA primary and backup channels). When the main link fails, the standby link automatically takes over, and the communication interruption time is ≤50ms. The multi-source database 18 is deployed in a remote disaster recovery site to ensure zero loss of historical data and model parameters, supporting fast recovery after failure.

[0031] Although specific embodiments of the present application have been shown and described, it will be understood by those of ordinary skill in the art that various changes, modifications, substitutions and alterations can be made thereto without departing from the principles and spirit of the present application, the scope of which is defined by the appended claims and their equivalents.

Claims

1. An intelligent control flue gas denitrification and desulfurization system, including a flue gas inlet (1), characterized in that: The output end of the flue gas inlet (1) is provided with a pretreatment module (2), and the two output ends of the pretreatment module (2) are provided with a denitrification system C (3) and a desulfurization system D (4). The output end of the denitrification system C (3) is equipped with a denitrification by-product treatment (5), the output end of the denitrification by-product treatment (5) is equipped with a resource recovery system (6), the two output ends of the desulfurization system D (4) are equipped with a clean flue gas emission (7) and a desulfurization wastewater and gypsum treatment (8), and the output end of the desulfurization wastewater and gypsum treatment (8) is equipped with a wastewater zero discharge treatment (9). The input end of the denitrification system C (3) and the input end of the desulfurization system D (4) are equipped with an intelligent control platform (14). The intelligent control platform (14) is equipped with a digital twin engine (1401) and an advanced control algorithm (1402). The advanced control algorithm (1402) is equipped with model predictive control and reinforcement learning.

2. The intelligent flue gas denitrification and desulfurization system according to claim 1, characterized in that: The output end of the clean flue gas emission (7) is equipped with an online monitoring terminal (10), the input end of the online monitoring terminal (10) is equipped with a laser gas analyzer (13), an infrared thermal imager (11) and a distributed fiber optic sensor (12), and the output end of the online monitoring terminal (10) is set on the intelligent control platform (14).

3. The intelligent flue gas denitrification and desulfurization system according to claim 1, characterized in that: The output end of the intelligent control platform (14) is equipped with equipment status monitoring (15), and the input end of the equipment status monitoring (15) is equipped with vibration sensor (16) and oil monitoring instrument (17). The output end of the equipment status monitoring (15) is looped back to the intelligent control platform (14).

4. The intelligent flue gas denitrification and desulfurization system according to claim 3, characterized in that: The data transmitted between the intelligent control platform (14) and the equipment status monitoring (15) are vibration, temperature and oil data.

5. The intelligent flue gas denitrification and desulfurization system according to claim 1, characterized in that: The output end of the intelligent management and control platform (14) is equipped with a multi-source database (18), and the output end of the multi-source database (18) is looped back to the intelligent management and control platform (14).

6. The intelligent flue gas denitrification and desulfurization system according to claim 1, characterized in that: The denitrification system C (3) is equipped with an ammonia injection grid partition control (301) and an acoustic cleaning intelligent trigger (302). The desulfurization system D (4) is equipped with a slurry circulation pump frequency conversion group control (401) and gypsum dewatering prediction (402). The intelligent management and control platform (14) interacts with the denitrification system C (3) and the desulfurization system D (4) through control commands.

7. The intelligent flue gas denitrification and desulfurization system according to claim 5, characterized in that: The information looped from the multi-source database (18) to the intelligent control platform (14) consists of historical data or model parameters.

8. The intelligent flue gas denitrification and desulfurization system according to claim 1, characterized in that: The inner wall surface of the flue gas inlet (1) is coated with a glass flake coating and acid-resistant putty.

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