22545 results about "Flue gas" patented technology

The invention discloses a distributed real-time monitoring and early warning system for a temperature field of a smelting furnace, and relates to the technical field of industrial process intelligent monitoring. The problems of accumulated measurement errors and non-stationary hotspot escape reconstruction hysteresis caused by static emissivity setting in an existing system are solved. Collecting multiband radiation intensity and voltage signals through time domain alignment of the multispectral sensor array and the thermocouple array; iterating emissivity parameters in real time by adopting a dynamic ash body spectrum ratio algorithm in combination with flue gas absorption characteristics; fusing non-contact and contact temperature measurement data based on weighted Kalman filtering and complementary filtering; constructing a space-time variable covariance function to carry out non-stationary Kriging interpolation; dynamically optimizing the local grid resolution by combining an adaptive grid module; the processing flow is accelerated through the parallel computing module; early warning is triggered based on abnormal probability judgment and is fed back to emissivity correction and grid optimization; according to the invention, the monitoring precision and real-time performance of the temperature field are obviously improved, and the risks of false alarm, missing alarm and equipment melting loss are effectively inhibited.

The invention relates to the technical field of thermal power plant flue gas denitration, in particular to a thermal power plant APC advanced process control system and a denitration optimization method.The system comprises a data acquisition module for acquiring boiler combustion parameters, flue gas emission data and the operation state of a denitration system in real time; the multivariable predictive control module is used for optimizing the combustion efficiency and the NOx generation amount based on a dynamic matrix control algorithm; the denitration optimization decision module is used for dynamically adjusting the ammonia spraying amount through an ammonia escape feedback model; the intelligent coordination module integrates a unit load instruction and an environmental protection constraint condition and is used for cooperative control of combustion-denitration; according to the system, boiler combustion parameters, flue gas emission data and the operation state of the denitration system are obtained in real time through the data acquisition module, a dynamic matrix control algorithm of the multivariable prediction control module is combined, the NOx generation trend can be predicted in advance, the combustion efficiency can be optimized, and therefore the problem that adjustment is lagged when loads fluctuate in traditional PID control is effectively solved.

The invention discloses a tunnel segmented exhaust method and system based on train working conditions, a medium and a product, and relates to the technical field of ventilation. The method comprises the steps that a target tunnel is divided into a plurality of control sections according to fan installation configuration of the target tunnel; acquiring train passing data and train configuration information of the control section, and calculating a flue gas growth value of the control section in a preset time period; collecting flue gas concentration data of the control section, and calculating a ventilation demand index of the control section in combination with the flue gas growth value; collecting wind direction parameters of the control sections, determining a ventilation control relationship between the adjacent control sections based on the ventilation demand indexes and the wind direction parameters, and generating a ventilation cooperation scheme; according to the ventilation cooperation scheme, operation parameters of the tunnel fans in all the control sections are calculated, and control instructions corresponding to the operation parameters are sent to the tunnel fans. By implementing the application, the fan operation can be adjusted according to the actual train operation condition, and the ventilation effect is optimized.

A process system and process method for treating hydrogen sulfide-containing acid gas. The process system comprises a sulfur recovery unit, a tail gas treatment unit having an acid gas concentration function, and a flue gas alkaline scrubbing unit. The method comprises: subjecting sulfur-containing tail gas to concentration treatment by means of an absorption column (1) of the tail gas treatment unit, and then introducing same into the sulfur recovery unit to undergo a Claus reaction for separation, so as to obtain sulfur and sulfur recovery tail gas; introducing the sulfur recovery tail gas into the tail gas treatment unit, successively carrying out combustion and hydrotreating, and introducing the obtained gas into the absorption column (1) of the tail gas treatment unit; and in the tail gas treatment unit, introducing gas absorbed by the absorption column (1) into the flue gas alkaline scrubbing unit, and successively carrying out incineration and alkaline scrubbing, so as to discharge desulfurized gas. The content of SO2 in the tail gas treated by the process system is ≤50 mg / Nm3, and the requirements for full-period standard reaching of sulfur dioxide emission of tail gas during startup, shutdown and normal operations can be satisfied.

The invention relates to the technical field of anode carbon block roasting, and discloses an energy-saving control system of an anode carbon block roasting furnace, which comprises a data acquisition module, an energy-saving analysis module, a digital twin modeling module, a control execution module and a feedback optimization module, when the combustion state of the roasting furnace is monitored in real time, a multi-layer monitoring framework is constructed to dynamically track the change trend of temperature, flue gas oxygen content and pressure parameters, continuous comparison is performed based on a preset energy-saving reference interval, and when the parameters deviate from an optimization interval, a digital twinborn model is immediately triggered to intervene in analysis, so that the real-time monitoring of the combustion state of the roasting furnace is realized. Prejudgment identification of potential risks of combustion efficiency reduction and abnormal heat loss is achieved, hidden energy loss caused by imbalance of the air-fuel ratio is avoided, the non-planned shutdown frequency of equipment is reduced, and the continuous energy efficiency management and control stability of the production process is guaranteed.

An SCR flue gas denitration intelligent control method based on multivariable collaborative optimization specifically comprises the following steps: S1, collecting multi-key variable data of SCR flue gas denitration, processing the multi-key variable data, and storing the processed multi-key variable data into a historical database; s2, on the basis of the processed data, constructing a multivariable correlation model, and predicting operation states of the denitration system under different working conditions; s3, according to the actual operation condition of the system and the equipment performance, determining constraint conditions and optimization targets of SCR flue gas denitration; s4, performing multivariable collaborative optimization calculation in combination with the multivariable correlation model, the optimization target and the constraint condition, and searching an optimal control variable combination; and S5, intelligent control is implemented according to the optimal variable combination, and re-optimization is performed by monitoring feedback deviation in real time. The system can keep stable control precision in different operation scenes, and denitration efficiency fluctuation or parameter adjustment lag caused by sudden change of working conditions is avoided.

A system for capturing carbon dioxide from flue gas produced by a coke oven includes a coke oven system and a capture system. The coke oven is configured to process coal to produce coke and a flue gas comprising carbon dioxide. The coke oven includes an induced draft fan positioned downstream of the coke oven. The induced draft fan is configured to provide a vacuum to the coke oven and move the flue gas away from the coke oven. The coke oven system also includes a stack open to atmosphere and downstream of the induced draft fan. The capture system is fluidically coupled to the coke oven system at a point between the coke oven and the stack. The capture system is configured to remove carbon dioxide from the flue gas.

The present invention relates to the technical field of waste heat recovery equipment, and specifically discloses a waste heat recovery device for flue gas in a thermal power plant. It includes a box body with an upper smoke chamber, a heat exchange chamber and a lower smoke chamber inside. A number of smoke pipes connecting the upper smoke chamber and the lower smoke chamber are fixed in the heat exchange chamber; above the smoke pipes, there is a piston cylinder fixed by the box body; the upper end of the piston cylinder is connected to a high-pressure gas supply pipe, and a piston is arranged inside. The piston is connected with a scraping head through a push rod; side holes are provided on the push rod; when the high-pressure gas drives the piston to move downward, the scraping head moves along the inner wall of the smoke pipe to scrape off the ash slag. The waste heat recovery device for flue gas in this thermal power plant has a cleaning function and a better cleaning effect, high heat exchange efficiency and good waste heat recovery effect. The waste heat recovery device for flue gas in this thermal power plant can be automatically cleaned without disassembling components, is fast and efficient, and can be operated online. The ash slag scraped off during the cleaning process can be centrally recovered, avoiding re-mixing into the flue gas again, reducing the workload in the flue gas dust treatment link, and saving the subsequent environmental protection treatment cost.

The invention belongs to the technical field of industrial waste heat recovery, and discloses a flue gas waste heat recovery system optimization design method considering external parameter changes. The method comprises the steps of system monitoring data acquisition and feature extraction, thermodynamic modeling and parameter sensitivity analysis, external environment parameter and system performance coupling mechanism modeling, equipment failure prediction and reliability constraint determination, multi-objective optimization and self-adaptive control strategy generation and the like. Optimized operation of the flue gas waste heat recovery system under the condition of dynamic change of external environment parameters is achieved. According to the method, a dynamic influence matrix of external environment parameters and system performance is initiatively established, the reliability of the system is evaluated in combination with a stress-life analysis technology, efficiency and cost targets are balanced through a multi-target optimization algorithm, and a self-adaptive control strategy library for different working conditions is generated. The adaptability and stability of the system under complex working conditions are improved, the service life of equipment is prolonged, and the operation cost is reduced.

The invention relates to the technical field of industrial flue gas purification, and discloses a flue gas denitration pollution reduction and carbon reduction method and system based on model prediction control. The method comprises the following steps: collecting flue gas data through a sensor to obtain a flue gas distribution state; the state is processed through a preset model, and a nitrogen oxide concentration predicted value is determined; judging a regulation and control demand based on the predicted value and generating an adjustment coefficient sequence; calculating an opening value of an ammonia spraying distributor by adopting a particle swarm optimization algorithm, and determining ammonia spraying amount distribution; a control instruction is sent according to ammonia spraying amount distribution, and a temperature uniformity index is evaluated based on temperature feedback data; adjusting optimization algorithm parameters according to the indexes, and generating an optimized ammonia spraying strategy; updating the predicted value and determining the stable range of the denitration efficiency; verifying the ammonia escape concentration in the stable range to obtain a system performance index; and forming a continuous regulation and control sequence according to cyclic feedback of the indexes. According to the invention, accurate dynamic regulation and control of ammonia spraying amount are realized, denitration efficiency and system stability are effectively improved, and the risk of ammonia escape is significantly reduced.

The invention discloses a big data prediction model intelligent ammonia spraying control method and system suitable for kiln flue gas denitration. According to the ammonia spraying control method, historical and real-time data of multiple parameters such as the fuel gas flow of the glass kiln are collected firstly, the NOx amount is predicted through modeling of the LSTM-GRU hybrid neural network, the ammonia spraying amount is calculated through self-adaptive control, and the accuracy is ensured through two-stage correction. And the calculated ammonia spraying amount is transmitted to a production master control system to adjust an ammonia supply valve, and automatic alarm and manual control are switched in case of failure. The system comprises a data acquisition module, an intelligent prediction module, a self-adaptive control module and the like, and further comprises a dynamic catalytic reaction simulation test platform for optimization. According to the invention, intelligent automatic control of the big data model is realized, the ammonia spraying amount is accurately adjusted, the denitration efficiency and the ammonia utilization rate are improved, the operation cost is reduced, and the system reliability and stability are enhanced.

The invention discloses an operation balance optimization method for a waste incineration thermal power plant. Efficient and environment-friendly waste treatment and green energy recovery are achieved through regulation and control of core parameters. Comprising an intelligent control system, a carbon cyclic utilization technology and a flue gas purification technology, an optimization model taking comprehensive net income maximization and carbon emission intensity minimization as targets is constructed, a garbage heat value, incinerator temperature, steam parameters, power generation efficiency, station service power consumption rate and the like are selected as core parameters, an operation balance optimization target function is constructed, and the comprehensive net income maximization and the carbon emission intensity minimization are realized. And through an intelligent control system, key parameters such as the incinerator temperature, the excess air coefficient and the flue gas treatment temperature are monitored and adjusted in real time, it is ensured that garbage is fully combusted in the incinerator, harmful gas emission is reduced, and the power generation efficiency is improved. Compared with the prior art, efficient operation of the waste incineration thermal power plant and maximum utilization of green energy are achieved, and remarkable economic and environmental benefits are achieved.

The invention relates to the technical field of flue gas treatment, in particular to a sintering flue gas denitration and dust removal integrated post-CO removal method which is specifically completed through cooperation of a sintering flue gas treatment system, and the sintering flue gas treatment system comprises a GGH heat exchanger, a desulfurization reactor, a denitration dust remover and a CO reactor which are sequentially communicated through pipelines. The CO catalyst module is a transition metal oxide CO catalyst; the cleaning device is used for cleaning ash of the CO catalyst module; the ammonia gas is sprayed into the outlet of the desulfurization reactor, so that ammonia escape is reduced, poisoning of the CO catalyst module is reduced, the catalytic efficiency of the CO catalyst module is improved, and the service life of the CO catalyst module is prolonged; the CO catalyst module is regularly subjected to air blowing and back blowing in a closed area, so that impurities such as carbon deposition on the CO catalyst module are cleaned, more active sites are exposed, the service life of the CO catalyst module is prolonged, and the investment and operation cost is reduced by adopting a transition metal oxide CO catalyst.

The invention discloses a low-carbon flexible coal-fired unit power control system and method, and relates to the technical field of power systems, and the system comprises a cascade waste heat recovery module, a boiler deep regulation and control module, a thermal coordination module, an environmental protection and emission reduction module, an intelligent operation scheduling module and an energy efficiency monitoring module. The gradient waste heat recovery module carries out gradient recovery on flue gas heat energy according to temperature zone grades; the boiler depth regulation and control module is used for regulating combustion air supply and heat absorption paths to realize low-load stable combustion; the thermal coordination module dynamically distributes thermal loads between the multiple heat sources and the thermal units; the environmental protection and emission reduction module jointly controls desulfurization, denitration and wastewater resourceful treatment; the intelligent operation scheduling module generates a load regulation and control instruction and coordinates multi-module response; the energy efficiency monitoring module collects and analyzes energy consumption and emission indexes and assists strategy optimization. The energy efficiency utilization and emission control capability of the unit under the deep peak regulation condition is improved, and flexible, efficient and low-carbon operation is achieved.

The present application provides a molten salt heat storage and release unit and a deep peak regulation system for a boiler unit, the molten salt heat storage and release unit comprising a molten salt storage assembly, a heat exchange energy storage assembly, and a heat exchange energy release assembly, wherein the molten salt storage assembly comprises a high-temperature molten salt storage tank and a low-temperature molten salt storage tank; the heat exchange energy storage assembly is connected to the high-temperature molten salt storage tank and the low-temperature molten salt storage tank, and comprises a flue gas heat exchange device and a steam heat exchange device, and molten salt in the low-temperature molten salt storage tank sequentially passes through the flue gas heat exchange device and the steam heat exchange device and then flows into the high-temperature molten salt storage tank; and the heat exchange energy release assembly is connected to the high-temperature molten salt storage tank and the low-temperature molten salt storage tank, and comprises a pulverized coal heating device and a feedwater heating device, and molten salt in the high-temperature molten salt storage tank releases energy through the pulverized coal heating device and / or the feedwater heating device and then flows into the low-temperature molten salt storage tank. The present application provides a molten salt heat storage and release unit and a deep peak regulation system for a boiler unit with flexible peak regulation and high energy efficiency.

The invention provides low-carbon fuel blending coupling combustion test equipment and method, and the equipment comprises a blending fuel feeding system which is used for blending solid-phase, liquid-phase and gas-phase low-carbon fuels with fossil solid fuels or other solid fuels in proportion; the one-dimensional combustion furnace is used for coupling combustion of the blended fuel; the flue gas treatment system is used for carrying out cooling, dust removal, desulfurization, denitration and carbon dioxide adsorption and trapping treatment on flue gas generated by coupling combustion; the control cabinet is used for controlling the stable and safe operation of the whole experiment platform; the low-carbon coupling combustion test system and method and the coupling combustion low-carbon technology have the beneficial effects that the coupling combustion condition that the actual boiler is internally mixed with low-carbon fuel is simulated by adopting a feeding and conveying mode of accurately controlling the blending combustion proportion, and the low-carbon coupling combustion test system and method and the coupling combustion low-carbon technology are formed; the device has multiple innovative functions of controlling the blending combustion ratio, efficiently coupling combustion, comprehensively purifying flue gas, adsorbing and trapping carbon dioxide, saving energy, reducing carbon and the like.

The invention discloses a coal-fired unit SCR denitration system ammonia injection prediction control method based on data driving, which is used for realizing better SCR denitration system ammonia injection control based on a data driving model in combination with an implicit generalized prediction control algorithm. The SCR inlet NOx concentration and the flue gas temperature serve as feedforward of an ammonia spraying amount instruction, the initial control instruction increment of the ammonia spraying amount is calculated through the SCR outlet NOx concentration, the SCR outlet NOx concentration set value and the ammonia spraying amount instruction at the previous moment through an implicit generalized predictive control algorithm, and the final ammonia spraying amount instruction is obtained through summation and amplitude limiting of the last three instructions. Wherein the feedforward instruction of the NOx concentration of the SCR inlet is obtained by a BP neural network prediction model, and the feedforward instruction of the SCR inlet is obtained by a long-short term memory network prediction model fused with an attention mechanism. According to the method, the problem that the concentration of NOx at an SCR outlet fluctuates severely in the frequent load changing process can be effectively solved, meanwhile, transient overshoot of NOx in tail flue gas of a coal-fired unit is restrained, and the SCR denitration control effect is improved.

The invention relates to a flue gas desulfurization device, and relates to the technical field of flue gas treatment.The flue gas desulfurization device comprises a barrel, the outer side of the barrel communicates with a flue gas inlet pipe, the top of the barrel communicates with a flue gas outlet pipe, and a filtering mechanism and a spraying mechanism are arranged in the barrel; the filtering mechanism comprises a mounting circular frame and a plurality of filtering units, the mounting circular frame is coaxially arranged in the cylinder body, a plurality of mounting sockets are formed in the outer side of the mounting circular frame, the filtering units correspond to the mounting sockets one to one, and the filtering units are matched with the corresponding mounting sockets in an inserted mode; a plurality of filter hole groups are formed in the upper side of the mounting circular frame in a penetrating manner, are in one-to-one correspondence with the mounting sockets and are communicated with the corresponding mounting sockets; a plurality of replacement ports are formed in the outer side of the barrel, correspond to the mounting insertion ports one to one and are communicated with the corresponding mounting insertion ports in an opposite manner, and the filter units are matched with the corresponding replacement ports in an insertion manner. The shutdown time of the flue gas desulfurization device can be shortened, and the flue gas desulfurization efficiency is guaranteed.

The invention discloses a rotary kiln flue gas waste heat recovery device capable of preventing smoke particle blockage, and relates to the technical field of flue gas waste heat recovery, the rotary kiln flue gas waste heat recovery device comprises a flue gas treatment mechanism and a fan mounted on one side of the interior of the flue gas treatment mechanism, and a waste heat recovery mechanism is arranged on one side of the flue gas treatment mechanism; a cleaning motor is arranged at the top of the waste heat recovery mechanism, the flue gas treatment mechanism comprises a flue gas filtering pipe, a plurality of rotating discs are arranged in the flue gas filtering pipe, a plurality of mounting sliding grooves are formed in the rotating discs, and the rotating discs are symmetrically arranged on the two sides of the interior of the flue gas filtering pipe; the two rotating discs are arranged up and down in a step shape, fixing holes are symmetrically formed in the ends, close to the mounting sliding grooves, of the rotating discs, and by arranging the flue gas treatment mechanism, flue gas in a flue gas filtering pipe can be pretreated through a filtering net plate, meanwhile, rotation of the whole rotating discs can be achieved, impurities on the filtering net plate are thrown onto a cleaning plate, and therefore the flue gas treatment efficiency is improved. And the filter screen plate is preliminarily cleaned.

The embodiment of the invention discloses a waste incineration SNCR precise control method based on a mechanism model and dynamic prediction, and relates to the technical field of waste incineration power plant flue gas denitration. The method comprises the steps that operation parameters of the garbage incinerator are obtained; constructing a mechanism model, namely a thermodynamic-combustion coupling model, and realizing three-dimensional flow field reconstruction and axial temperature field estimation by utilizing a virtual sensing technology and based on an energy conservation equation, a radiation transfer equation and CFD reverse solution and inversion of a flue gas temperature and a flow field velocity vector; combining the mechanism model and actually measured data, optimizing spray gun parameters by using a particle swarm optimization algorithm, and realizing multi-target balance of denitration efficiency and ammonia escape; and the flow, angle and layout of the spray gun are dynamically adjusted according to the optimized parameters. The method is high in denitration efficiency and low in reducing agent consumption.

The invention relates to the technical field of furnace tube intelligent diagnosis, in particular to a big data AI-based furnace tube leakage intelligent diagnosis method, which comprises the following steps: collecting boiler operation data in real time through a multi-source sensor, including temperature, pressure, vibration, sound wave and flue gas component data; performing time sequence alignment, abnormal value elimination and standardized preprocessing on the collected original data; inputting the preprocessed data into a pre-trained deep neural network model, wherein the deep neural network model is obtained through comparison training of historical normal data and leakage accident data; generating a real-time diagnosis result and an early warning level based on the leakage probability value and the feature contribution degree analysis output by the model; through multi-source sensing, AI deep analysis, dynamic early warning and predictive maintenance closed loop, early, accurate and automatic diagnosis of boiler tube leakage is realized, and the safety and operation and maintenance efficiency of industrial equipment are remarkably improved.

A system and method for quantifying CO2 capture by photobioreactors using microalgal biomass are disclosed. The method involves accurately quantifying carbon dioxide capture by photobioreactors using microalgal biomasses involves determining a unique ratio relating carbon consumed to biomass produced for each microalgae strain. This ratio is then used to predict CO2 removal from flue gases or industrial processes based on the dry mass of the corresponding biomass produced. Machine learning models are also trained on data obtained from the photobioreactors to predict CO2 consumption rates under varying conditions, thereby enhancing the accuracy and efficiency of carbon capture technologies.

This disclosure includes systems and methods of operating a convection section of an furnace in a chemical production process with simulated combustion gas (SCG) that is heated by an electric or thermal energy source instead of by combustion. Some such systems and methods utilize a thermal mass that is configured to store thermal energy such that the thermal mass can be used to heat a working fluid. The thermal mass can be coupled to a heater that receives electrical energy from a renewable source, and converts the electrical energy into thermal energy to heat the thermal mass and thereby store the thermal energy. In some aspects, a furnace is in fluid communication with the thermal mass such that the furnace receives the working fluid from the thermal mass to provide thermal energy to process for chemical production that would otherwise typically be provided by flue gas from a hydrocarbon-fired radiant section in conventional systems. In some configurations, the working fluid is or comprises one or more radiatively participating gases heated to exceed a threshold above which the working fluid transfers heat through radiation.

The invention discloses a portable flue gas analysis device and method, and relates to the technical field of flue gas analys.The portable flue gas analysis device comprises a sampling pipe analysis module, a basic sampling analysis module and a resampling analysis module.The portable flue gas analysis device is characterized in that firstly, a sampling pipe use scheme is set through the sampling pipe analysis module; secondly, a basic sampling analysis module collects basic environment information according to a sampling pipe use scheme, sets a flue gas collector use scheme, carries out basic sampling, sets a resampling scheme according to a basic sampling data analysis result, and finally, a resampling analysis module sets each effective wind speed according to the resampling scheme for resampling. According to the invention, the arrangement of the collector is flexibly adjusted, so that the collection process is more suitable for the actual environment, and the adaptability of the device to the complex environment is enhanced.

The invention discloses an optimal control method for a straw pyrolysis carbonization process. The method comprises: performing multipoint temperature real-time acquisition and data processing on a carbonization zone of a carbonization furnace, obtaining temperature information and calculating a deviation from a preset ideal temperature curve (S01); dynamically adjusting an operating parameter of the combustion zone using a control algorithm based on the temperature deviation (S02); performing on-line monitoring on the flue gas components (S03); and regulating and controlling the return air flow and the secondary air supply amount of the combustion area in a linkage manner according to the flue gas monitoring result so as to optimize combustion and energy recovery (S04). Through accurate and intelligent process control, efficient, environment-friendly and high-valued utilization of the straw carbonization process is realized.

The present invention proposes a system and method for automatic adjustment of secondary and tertiary dust removal of a converter, the system comprising: a dust collector, an angle sensor and a control module, the control module is respectively connected to the fan motor of the dust collector and the angle sensor signal; the angle sensor is arranged on the converter, and is used to monitor the tilting angle of the converter in real time and send it to the control module; the control module is used to identify the production stage of the converter in the current smelting cycle according to the tilting angle of the converter, determine the speed of the fan motor of the dust collector according to the production stage, generate a speed control signal and send it to the dust collector; the dust collector is used to adjust the speed of the fan motor according to the speed control signal. The present invention can control the speed of the fan through the tilting angle signal of the converter according to the different amounts of flue gas generated at different stages in the converter smelting cycle, adjust the air volume of the dust collector, and achieve power saving and energy saving.

The invention relates to a mining damage control method for multi-medium carbon pollution cooperative reduction and control and resource application, and belongs to the technical field of full-waste resource treatment and utilization of a short-distance coal seam mining goaf. The mining damage control method comprises the following steps that filling liquid and filling materials are stirred and mixed while carbon dioxide gas is introduced to form filling slurry; then all-directional shower type spraying is conducted from the filling pipeline to the goaf; performing full grouting on the goaf in a sealed form until the goaf is full, introducing carbon dioxide into the goaf while performing full grouting, monitoring and analyzing underground behaviors, rock reaction and rock stratum stability of carbon dioxide in a backfilling area, and when underground water exists in a sealing and storing area, establishing an underground water monitoring system to monitor the water quality of the underground water; the power plant flue gas is treated and then injected into the goaf to be mixed with the filling material, so that the oxygen concentration of the goaf is effectively reduced, goaf fire disasters are prevented and treated, mining disasters in the goaf are effectively controlled, and the stability of rock strata is improved.

The invention relates to the technical field of data processing, and discloses a flue gas treatment intelligent regulation and control method and system based on artificial intelligence and a medium. The method comprises the following steps: collecting parameter data of a flue gas system through a sensor network and processing to obtain preprocessed data; using unsupervised clustering to identify working condition features and categories; constructing an emission concentration error active switching control model according to the working condition information; different working condition control parameters are optimized by adopting a differential evolution algorithm; optimized parameters are input into a controller, and modes are dynamically switched according to pollutant errors. The control strategy can be automatically switched according to the working condition characteristics of the flue gas treatment system, the complex and changeable industrial production environment can be effectively dealt with, and the system operation cost is optimized while stable and up-to-standard emission of pollutants is guaranteed.

The invention discloses a water heater and a control method thereof, and relates to the technical field of water heaters. The condensing heat exchanger has a water collecting cavity; the atomization module is arranged in the water collecting cavity; the water path switching assembly is arranged among the water inlet main pipe, the main heat exchanger and the condensing heat exchanger, has a first working mode and a second working mode, and is used for sequentially communicating the water inlet main pipe, the condensing heat exchanger and the main heat exchanger to form a first flow path in the first working mode; in the second working mode, the water inlet header pipe communicates with the main heat exchanger to form a second flow path, and the water inlet end and / or the water outlet end of the condensation heat exchanger are / is disconnected from the second flow path; according to the condensation gas water heater, condensed water is discharged along with flue gas after being atomized, meanwhile, the water inlet path is switched through the water path switching assembly, and the problems that in the efficient flue gas waste heat recovery process of an existing condensation gas water heater, the condensed water generated is inconvenient to discharge, a pipeline is prone to being corroded, or frequent manual intervention is needed can be solved.

The invention relates to the technical field of dynamic regulation, in particular to a CFD (computational fluid dynamics) simulation-based flue gas flow field dynamic regulation system, which comprises a multi-dimensional data collaborative acquisition module, an anti-ash deposition sensor array is deployed at a key position of a flue, and a time-space fusion input data set is generated; the dual-mechanism CFD dynamic coupling module operates the main CFD prediction model and the simplified fluid network model in parallel, compares output differences through an evidence theory fusion algorithm, corrects boundary conditions and reconstructs network parameter characteristics when the confidence coefficient is lower than a threshold value, and updates a dynamic parameter knowledge base; the multi-target self-adaptive regulation and control module is used for solving a Pareto optimal strategy meeting the safety constraint by taking the baffle opening degree and the pump frequency as variables based on the updating model, driving an actuator and feeding back flow field response data; and the system forms a closed-loop adaptive mechanism, so that the CFD model continuously tracks the degradation state of the equipment, and the effectiveness of the regulation and control strategy is maintained.