2311 results about "Combustion process" patented technology

The invention provides a multi-target combustion optimization method based on economic predictive control, and aims to solve the problems that the power generation load and the in-furnace coal quality are frequently changed, conventional DCS control has defects in the aspects of air quantity and oxygen quantity optimization, boiler efficiency balancing, NOx emission, steam temperature control and the like, part of boiler parameters are difficult to accurately measure, and the existing combustion optimization technology is limited in applicability. The method comprises the following steps: collecting and preprocessing historical operation data, classifying and screening according to steady-state working conditions, and constructing a correlation model to perform preliminary combustion optimization; a load and coal quality change prediction model and a combustion process dynamic relation model are established according to unit characteristics and historical data; then, in the online secondary optimization stage, an initial parameter combination is selected according to the current state and the prediction state, and the combustion parameter adjustment amount meeting the multiple constraints is calculated through an economic prediction control algorithm and applied and corrected. Experiments show that the method can improve the boiler efficiency, reduce NOx emission, optimize steam temperature control, relieve the labor intensity of personnel and effectively improve the combustion performance.

The invention discloses a rotational flow micro-mixing nozzle with built-in plasma combustion supporting and a micro-mixing combustor. The rotational flow micro-mixing nozzle comprises a tangential rotational flow part, a fuel pipe and a mixing pipe which are coaxially arranged, and plasma combustion supporting exciters arranged on the fuel pipe and the mixing pipe. The plasma combustion-supporting exciter is integrated in the nozzle, the structural design of the micro-mixing combustor can be simplified, and the size and complexity of the micro-mixing combustor are reduced; the plasma combustion-supporting exciter is installed at the top of the mixed gas channel of the rotational flow micro-mixing nozzle, stable adjustment of the combustion process under the variable working conditions can be achieved by controlling opening and closing and the discharge intensity of the plasma combustion-supporting exciter when the load changes, and meanwhile the response speed under the different working conditions is increased; air or an oxidizing agent can be fully mixed with fuel at a specific rotational flow degree through rotational flow air flow generated by the tangential rotational flow component, the combustion range can be widened, and the stable combustion effect under the extreme working condition is enhanced.

A data-driven multi-objective optimization control method for a municipal solid waste incineration (MSWI) process. The method comprises: first, establishing an MSWI process whole-process model for pollutant emission, wherein the model includes controlled object models, i.e. a furnace hearth temperature model, a boiler steam flow model and a flue gas oxygen-content model, and CO, CO2 and NOx pollutant emission index models; then, using single-neuron adaptive PID to establish a multi-input multi-output loop controller for key controlled variables, so as to realize stable control over a combustion process; and finally, in view of expert knowledge in the field, realizing adaptive solving of a key controlled variable optimization set value based on a multi-objective particle swarm optimization algorithm. Multi-objective optimization control over an MSWI process can be realized, existing running factories are guided, the pollutant emission concentration can be reduced, and the efficiency of combustion is improved.

The invention discloses a boiler combustion optimization method and device based on CFD numerical simulation and a medium, and belongs to the technical field of boiler combustion simulation. The method comprises the steps of obtaining operation parameters and historical operation data of a boiler combustion system; processing the data based on a three-dimensional modeling algorithm to generate a three-dimensional combustion model of the combustion area of the boiler; the three-dimensional combustion model is processed based on a CFD numerical simulation algorithm, and multi-physical field coupling data of the combustion process is generated; processing the multi-physical field coupling data and the historical operation data based on a multi-objective optimization algorithm to establish a combustion parameter optimization model; adjusting the ratio of the air speed at the inlet of the combustor to the fuel flow to update the model and optimize combustion parameters; verifying whether the optimized combustion parameters meet constraint conditions or not; and when the constraint conditions are met, finally optimized combustion parameters are output. By means of the method, multi-physical-field dynamic coupling optimization in the boiler combustion process is achieved, and the purposes of synchronously improving the combustion efficiency and the pollutant control effect are achieved.

The invention provides a method for constructing a differential diffusion small flame model for buoyancy-driven plume, and the method is applied and expanded to a pool fire combustion process in the field of fire safety. According to the method, the buoyancy driven plume is solved by using the small flame model, the solving number of component equations of the buoyancy plume is greatly reduced through coordinate conversion dimensionality reduction processing, and the main characteristics of the buoyancy plume can be reproduced with relatively high precision and a faster calculation rate. According to the method, high-precision numerical solution of buoyancy plume is realized, and pool fire combustion of gas fuel and liquid fuel and numerical solution of all plume driven by buoyancy can be processed.

The invention discloses a gas mixing control device for an LPG (Liquefied Petroleum Gas) generator set, which relates to the technical field of generator set operation control, and comprises a gas engine for realizing accurate mixing proportion control under the matching of a proportion dynamic response component, predicting the optimal gas mixing proportion and flow demand under the current working condition, and controlling the gas engine to operate according to the optimal gas mixing proportion and flow demand. When the propane content in the LPG is increased, the model prediction controller properly reduces the gas inflow and increases the air amount, sufficient combustion is ensured, the mixing proportion and flow can be rapidly corrected, the combustion process is rapidly recovered to be stable, it is ensured that the gas engine stably operates under different loads, the whole device forms flow balance and stable operation, and the service life of the gas engine is prolonged. Under different gas sources and LPG component differences, effective components actually participating in combustion are accurately judged, so that the needed gas and air amount is accurately calculated, accurate mixing proportion control is achieved, and meanwhile accurate control over the mixed gas mixing process is achieved under the cooperation of an adjusting control assembly.

The invention discloses a numerical calculation method for simulating combustion of iron powder group particles, belongs to the field of numerical simulation calculation of iron powder combustion, can perform numerical simulation on single-particle and iron powder group combustion under a microgravity condition, quantitatively analyzes the influence of differential diffusion on single-particle iron powder and iron powder group combustion flame temperature, and improves the calculation accuracy of the single-particle and iron powder group combustion flame temperature. And meanwhile, the influence of iron powder combustion characteristics and flame propagation speeds under different iron powder and oxygen concentration conditions is considered. The method has a certain guiding significance in research on low-propagation-speed lean-burn iron powder flames and subsequent application of iron powder fuel. The microgravity environment can eliminate the influence of convection and buoyancy, so that the combustion process is more stable and predictable, and the basic mechanisms of iron powder combustion, including combustion rate, oxidation process, phase change and the like, can be deeply researched.

The invention provides a method for constructing a thickened flame surface model of hydrogen turbulent combustion, which belongs to the technical field of hydrogen fuel engines, and specifically comprises the following steps: modeling a diffusion enhancement effect and a flame surface wrinkle effect caused by multi-scale turbulent flow by constructing a hydrogen fuel turbulent flame speed scale rate under a wide working condition; and the combustion process of the hydrogen fuel can be described more accurately. In addition, on the basis of a thin reaction zone combustion mode, key physical quantities are extracted, a combustion efficiency function is optimized, multi-scale turbulence and a difference diffusion effect are considered, and the thickened flame surface model is further perfected. The development of the method provides powerful technical support for the forward design of the hydrogen fuel engine based on numerical simulation, promotes the engineering application of the hydrogen fuel engine, and assists the hydrogen fuel engine to play a greater role in efficient, clean and safe energy transformation.

The invention relates to the technical field of boiler combustion control, and discloses a boiler closed-loop combustion dynamic optimization control system based on big data, and the system comprises an intelligent sensing module which is used for obtaining and outputting time-synchronized monitoring data in real time; the edge calculation module is used for processing multi-source sensor data in real time, realizing data credible processing and combustion state feature coding, and executing local caching of working condition perception; the digital twin modeling module is used for constructing a combustion process dynamic model and realizing real-time prediction of a combustion state; the optimization control module is used for dynamically adjusting combustion parameters and achieving collaborative optimization of the air-coal ratio, the opening degree of a secondary air door and the over-fire air ratio; and the closed-loop execution module is used for executing and feeding back the control instruction and realizing transmission and closed-loop verification of the control instruction. The combustion efficiency can be improved, pollutant emission can be reduced, and the stability and safety of boiler operation can be enhanced.

The invention discloses a natural gas hydrogen-doped combustion optimization method and system for a gas turbine, and the method comprises the steps: obtaining combustion state parameters of a mixed fuel under different mixing proportions under an experimental condition, the combustion state parameters comprising combustion characteristic data and emission characteristic data; establishing a numerical calculation model for describing the combustion process and emission characteristics of the mixed fuel on the basis of combustion science and fluid mechanics, and performing numerical simulation on the mixed fuel in different mixing proportions by adopting the numerical calculation model to obtain combustion state parameters of the mixed fuel; comparing and analyzing the combustion state parameters obtained by the experiment and the combustion state parameters obtained by the numerical simulation, and optimizing the numerical calculation model according to the analysis result; expanding the mixing proportion of the mixed fuel, and performing numerical simulation on the expanded mixed fuel by adopting the optimized numerical calculation model to obtain combustion state parameters of the mixed fuel and construct a training data set; and adopting the training data set to train the machine learning model, and adopting the trained machine learning model to predict the mixing proportion of the mixed fuel. According to the method, by updating a numerical calculation model and a machine learning model, optimal prediction under different fuel and combustion conditions can be realized.

The invention belongs to the technical field of equipment intelligent control, and discloses a multi-objective optimization intelligent control method for a combustion carbon dioxide production system. The method comprises the following steps: constructing a combustion mechanism model; training a combustion data model; fusing the combustion mechanism model and the combustion data model to obtain a dual-drive model, and determining an optimization target; a dual-drive model is adopted to simulate the garbage combustion process, the control strategy is optimized according to the optimization target, and combustion equipment is adjusted; the advantages of the two models are effectively fused, advantage complementation between the models is achieved, and therefore the physical interpretability and adaptability of the models are improved; in the control strategy optimization process, not only is the combustion efficiency considered, but also carbon emission and pollutant emission are considered, the combustion efficiency is improved, and the carbon emission and the pollutant emission are reduced, so that multi-target optimization of the combustion carbon dioxide production system is achieved, and the control strategy optimization efficiency is improved. And the environment-friendly performance and the economic performance of the garbage combustion carbon dioxide production system are improved.

The invention relates to the technical field of boiler combustion optimization, and discloses an Agent-driven pulverized coal boiler combustion optimization closed-loop control method and system, and the method comprises the steps: obtaining combustion data in the combustion process of a pulverized coal boiler; according to the combustion data and a preset combustion task, generating an initial combustion control strategy through a multi-agent layered cooperation mode of the power system; according to the combustion data and an initial combustion control strategy, optimizing the initial combustion control strategy by predicting the combustion state of the boiler in a preset future time period to obtain an optimized combustion strategy, and guiding the boiler to carry out combustion adjustment so as to carry out closed-loop control on the combustion optimization process of the gas turbine; through closed-loop control over the combustion optimization process of the pulverized coal boiler, different combustion tasks can be responded in time, the control strategy is automatically adjusted according to the combustion tasks and the combustion state of the boiler, the control performance is continuously improved, the combustion state meets the task requirement all the time, and stable operation of the gas turbine is guaranteed.

The invention discloses a porcelainized expansion type fireproof heat-insulating coating and a preparation method thereof, and relates to the technical field of fire prevention, and the fireproof heat-insulating coating comprises an inner coating and an outer coating; the preparation method comprises the following steps: S1, weighing the raw materials of the component A and the component B; s2, preparing the component A; s3, preparing a component B; s4, the surface of the steel structure is coated with the component A, and an inner coating of the fireproof heat-insulating coating is obtained after normal-temperature drying; and continuously coating the surface of the dried inner coating with the component B through a spraying or brushing method, and drying at normal temperature to obtain the ceramifiable expansive fireproof heat-insulating coating. A porcelainized reaction and an intumescent flame-retardant system are combined to protect the steel structure material from two aspects of efficient flame retardance and high-temperature heat insulation, and the effect is excellent; a nitrogen-phosphorus synergistic flame retardant is used for actively inhibiting the flame combustion process, a high-temperature expansion layer formed by expansible graphite and a vitrifiable heat insulation layer formed by ceramic forming filler are used for greatly improving the high-temperature stability and heat insulation efficiency of a carbon layer, and the fire endurance of a steel structure is prolonged.

The invention discloses a combustion chemical reaction kinetic data processing method and system for an ADN-based liquid propellant, and belongs to the technical field of data processing. According to the method, firstly, key information in the combustion process can be comprehensively captured by obtaining a combustion chemical reaction kinetic vector and an element state linkage vector; structured semantic mapping is carried out on the primitive state linkage vector to obtain a reaction state structured vector and a strategy association demand vector, which is helpful for accurate classification and positioning of combustion reaction related information. And the integration confidence weights of the first data and the second data are determined, so that the association degree of the element reaction data and the visual association labels under different integration strategies can be quantified, and the analysis of the combustion process is more scientific and meticulous. The finally determined visual monitoring result can visually present the characteristics of the element reaction data under different strategies, and clear and accurate data support is provided for deeply understanding the combustion mechanism of the ADN-based liquid propellant, optimizing the performance of the propellant and ensuring safe use.

The invention discloses a machine learning multi-objective optimization control method based on coal quality characteristics and combustion state feedback, and belongs to the technical field of industrial process automatic control. According to the method, collaborative optimization control over the combustion efficiency, NOx emission and combustion stability is achieved under the multi-working-condition operation condition of the combustor. According to the method, coal quality characteristic parameters and combustion state data are collected, working condition clustering is carried out after data fusion, and a historical combustion operation data set coupling coal quality characteristics and combustion states is constructed; a combustion state evaluation model and a combustion control model are established by adopting machine learning, on the basis of identifying working conditions in real time and evaluating combustion performance, a control parameter adjustment amount is generated in combination with trend extrapolation and a multi-objective cost function, and a combustion state feedback rolling correction model and a control strategy are utilized to realize combustion control. The self-adaptive closed-loop collaborative optimization control of the combustion process under multiple coal types and multiple working conditions is realized, the boiler efficiency is improved, the NOx emission is reduced, and the operation robustness is enhanced.

The invention discloses a gasification slag mixed biomass fuel blending combustion control method and system, and relates to the field of energy and environmental engineering. The method comprises the steps of collecting sensor data for data fusion, and preprocessing original data; according to the preprocessed data, an environment combustion synergy index is constructed, and the raw materials are classified; screening an optimal mixing ratio by utilizing dynamic game scores; temperature and flame stability parameters are collected in real time to construct a closed-loop feedback system, and intelligent adjustment of the combustion process is achieved; and a dynamic emission risk index is constructed, and closed-loop optimization control of pollutant emission is realized in combination with variable regression and a dynamic adjustment algorithm. Advanced technologies such as sensor data fusion, environment combustion synergy index, dynamic game scoring and feedback control are combined, on the premise that the combustion efficiency and stability are ensured, the blending combustion strategy of the gasified slag mixed biomass fuel can be optimized, and pollutant emission is effectively reduced.

The invention relates to a preparation method of a three-dimensional ferrocobalt metal oxide oxygen evolution catalyst. According to the method, foamed nickel is selected as a carrier, the foamed nickel is pretreated, a metal ion and ethanol mixed solution is evenly adsorbed to the surface of the foamed nickel, then open fire ignition is carried out, and a second-level self-limiting combustion process is carried out, so that metal ions form a ferrocobalt metal oxide material with a three-dimensional network structure in situ on the surface of the foamed nickel. The method is simple and easy to implement, a target product can be generated within second-level time, and the area of a foamed nickel matrix is adjusted according to needs, so that the three-dimensional ferrocobalt metal oxide catalyst is prepared on a large scale. The material obtained by the invention is used as an oxygen evolution anode catalyst, and the three-dimensional network-shaped ferrocobalt metal oxide oxygen evolution catalyst shows excellent electrochemical performance.

The invention provides a DOPO-HQ-based flame retardant, a preparation method and application thereof, a flame-retardant anti-dripping PET composite material and preparation thereof, and belongs to the technical field of flame retardants. The DOPO-HQ-based flame retardant provided by the invention contains an efficient phosphorus-based flame retardant DOPO structure, so that the composite material can be endowed with efficient flame-retardant self-extinguishing performance; besides, the DOPO-HQ-based flame retardant contains a triazine structure, is high in thermal stability and has excellent high-temperature carbonization capacity, so that a large number of carbon layers are generated in the combustion process of the composite material and cover the surface of a base material, and the effects of molten drop resistance and smoke suppression are achieved. The thermal performance of the flame-retardant PET composite material prepared from the DOPO-HQ-based flame retardant is similar to that of pure PET, and the flame-retardant PET composite material has the characteristics of high flame-retardant efficiency, no halogen, no molten drop, low smoke release amount and the like under the condition of a small addition amount (2-8wt%) (the current commercially available flame-retardant anti-molten drop addition amount is greater than or equal to 15wt%).

The invention relates to the technical field of environmental protection, in particular to a garbage incinerator combustion management system which comprises a data acquisition module, a data preprocessing module, a data analysis module, a decision control module and a combustion adjustment module. Wherein the data acquisition module is used for acquiring combustion data in the combustion process of the garbage incinerator; the data preprocessing module is used for preprocessing the collected combustion data; the data analysis module is used for analyzing the preprocessed combustion data in real time and judging the efficiency and the pollutant emission level of the current combustion process; the decision control module is used for generating a combustion adjustment instruction; and the combustion adjusting module is used for adjusting the air flow, the temperature and the fuel input amount in the combustion process. Through real-time data analysis and automatic adjustment and optimization of combustion parameters, efficient control over the combustion process of the garbage incinerator is achieved, the combustion efficiency is remarkably improved, pollutant emission is reduced, and the environmental protection property and economical efficiency are improved.

The invention discloses a fluoride-free environment-friendly flame-retardant PC (polycarbonate) material and a preparation method thereof. The fluoride-free environment-friendly flame-retardant PC material is prepared from the following raw materials in parts by weight: 68-99.98% of polycarbonate resin; 0.01 to 25% of a flame retardant; 0.01 to 5% of a synergistic flame retardant; and 0-2% of a processing aid. The flame retardant does not contain any flame retardant, does not generate toxic gas or smoke in the combustion process and is harmless to the environment and human bodies, the components of the flame-retardant PC material meet the PFAS environment-friendly requirement, the flame-retardant PC material belongs to an environment-friendly material, and the prepared fluoride-free environment-friendly flame-retardant PC material is applied to the fields of the automobile industry, the electric appliance and instrument industry, the mechanical industry and the like.

The invention discloses a chemical spontaneous ignition-based underground in-situ combustion method for low-permeability oil reservoirs, oil shale and shale oil reservoirs, and relates to the technical field of oil and gas exploitation. The chemical spontaneous ignition composition comprises the following components in percentage by mass: 20%-45% of an ignition agent, 10%-20% of a fuel additive, 8%-12% of a combustion improver, 3%-5% of a catalyst, 2%-3% of an emulsifier and the balance of water. According to the chemical spontaneous ignition-based underground in-situ combustion method for the low-permeability oil reservoir, the oil shale and the shale oil reservoir, through optimal combination of the ignition agent, the combustion improver, the catalyst, the emulsifier and the fuel additive, a spontaneous combustion reaction can be rapidly initiated in the oil reservoir, and a stable high-temperature combustion process is maintained; the method is suitable for exploiting low-permeability oil reservoirs, oil shale, shale oil reservoirs and sandstone reservoirs, the recovery efficiency can be remarkably improved, and the method is particularly suitable for complex oil reservoir conditions where a conventional oil displacement technology is difficult to effectively apply.

The invention discloses a gas-solid two-phase flow numerical simulation method for bidirectional coupling of non-spherical particles and a flow field, and belongs to the technical field of biomass fuel utilization, and the method comprises the following steps: constructing a flow field model in Fluent, and correspondingly setting an initial boundary condition of the flow field; setting initialization conditions of non-spherical particles in the UDF; establishing an inertial coordinate system and a particle coordinate system, and coupling the two coordinate systems; and obtaining a translational motion table / rotational motion characterization equation, determining the position and direction of the particles by solving the two equations, correcting flow field parameters by using the positions and direction of the particles, and iteratively calculating particle motion parameters to realize bidirectional coupling of the non-spherical particles and the flow field. According to the numerical simulation method, through Fluent-UDF numerical simulation, the interaction between the non-spherical particles and the flow field can be accurately simulated, the accuracy of gas-solid two-phase flow numerical simulation is guaranteed, understanding of the complex process of direct combustion coupling of biomass particles of a coal-fired boiler is deepened, and theoretical support is provided for optimization of combustor design and the combustion process.

The invention relates to the field of blast furnace pulverized coal preheating. A blast furnace pulverized coal preheating system comprises a coal injection workshop, a nitrogen heater, a common pulverized coal heater, a compressed nitrogen tank, a blast furnace, an oil storage tank, an expansion tank, a waste heat exchanger, a heat conduction oil pump, a PLC control system and a sound-light alarm device. Pulverized coal discharged from a coal injection workshop is heated in a common pulverized coal heater through waste heat of a blast furnace, and the heated pulverized coal enters the blast furnace to be combusted. The combustion characteristic of the preheated pulverized coal is remarkably improved, and the pulverized coal can be quickly combusted after entering a main combustion chamber of the blast furnace, so that the conventional three-section combustion process of heating, ignition and combustion is broken through.

The pulverized coal rotational flow stable combustion burner comprises a shell, a primary air pipe, a first swirler, a backflow cap and a laser generator assembly, a secondary air duct is defined between the primary air pipe and an air guide section, the first swirler is arranged in the secondary air duct, the backflow cap is arranged in the secondary air duct, and the laser generator assembly is arranged in the secondary air duct. The backflow cap is arranged in the combustion chamber and located at the outlet end of the primary air pipe. The laser generator assembly is used for emitting sheet-shaped laser beams into the combustion chamber so as to ignite pulverized coal in the combustion chamber. According to the invention, the size and the shape of the laser beam spot are adjusted, and the ignition efficiency and the stability in the pulverized coal combustion process are obviously improved by the aid of a cooling and combustion control strategy in which tertiary air and secondary air are matched; meanwhile, the laser power and mode can be flexibly switched, different coal quality and load working conditions can be adapted, the adaptability and combustion efficiency of the combustor are greatly improved, the service life of a hearth and related parts is prolonged, and the operation cost is reduced.

The invention discloses gel foam for preventing spontaneous combustion of coal, and belongs to the technical field of gel foam fire extinguishing. The gel foam comprises the following components: 0.1-0.5% of a composite foaming agent, 5-15% of a gelling agent, 0.1-0.5% of a cross-linking agent and the balance of water, the composite foaming agent is sodium lignin sulfonate and sodium fatty alcohol polyoxyethylene ether carboxylate; the gels are silica sol and sodium alginate. The gel foam has excellent water-retaining property, and can relieve water loss and weight loss of coal; the flame retardant can effectively hinder the contact between coal and oxygen, interrupt the free radical chain reaction of coal and avoid the oxidation weight gain of coal, and has an excellent flame retardant effect; in the combustion process, less heat is generated, and the smoke suppression effect is excellent. The gel foam does not contain antioxidants and flame retardants, can avoid environmental pollution, is an environment-friendly anti-oxidation gel foam, and can be used as an efficient fire preventing and extinguishing material in the field of preventing spontaneous combustion of coal.

The invention discloses a thermal power plant boiler combustion optimization method and system, and the method comprises the steps: obtaining historical combustion data and historical control data of a thermal power plant boiler, and carrying out the analysis to determine control parameters affecting the combustion; extracting features of the control parameters, and constructing a combustion data prediction model based on the features and a preset neural network model for prediction to obtain combustion prediction data; analyzing the combustion prediction data, determining combustion data characteristics, and determining a combustion state coefficient of the thermal power plant boiler based on the combustion data characteristics; an expected combustion state coefficient preset in advance by the thermal power plant boiler is obtained, and the difference value between the combustion state coefficient and the expected combustion state coefficient is determined; and determining a parameter control optimization coefficient according to the difference value to optimize the current control parameter. According to the invention, refined and intelligent monitoring and optimal control of the combustion process can be realized, so that the combustion efficiency of the thermal power plant boiler is improved, the cost is reduced, the emission is reduced, and the stability and the safety of boiler operation are improved.

The invention belongs to the field of pollutant control, and particularly discloses a method and system for reducing generation of nitric oxide in the ammonia coal combustion process. The method specifically comprises the steps that liquid ammonia is gasified and then subjected to a thermocatalytic reaction to generate hydrogen and nitrogen, and ammonia-doped mixed gas is obtained; and judging whether the ratio of the concentration of hydrogen to the concentration of ammonia in the ammonia-doped mixed gas is greater than or equal to a threshold value or not, if so, discharging the ammonia-doped mixed gas for blending combustion, and if not, carrying out thermal catalytic reaction on the ammonia-doped mixed gas again. According to the method, the ratio of the concentration of hydrogen to the concentration of ammonia in the ammonia-doped mixed gas serves as the judgment standard for whether blending combustion can be conducted or not, the calculation formula of the threshold value is provided by balancing the influence of H2 and NH3 on NOx generation in the combustion process, then flexible regulation and control can be conducted on the raw material side according to the actual blending combustion condition, and the blending combustion efficiency is improved. The method effectively reduces the generation of nitrogen oxides in the ammonia coal combustion process, does not need to regulate and control the combustion side, does not affect the combustion stability and the boiler thermal efficiency, and has the advantages of simple operation and low cost.

The invention relates to the technical field of boiler combustion control, in particular to a boiler combustion automatic detection control system based on a big data model. The system comprises a data acquisition module used for acquiring various parameter data in a boiler combustion process; the data processing module is used for preprocessing and fusing the collected data; the big data model module constructs a model based on the processed data, learns a combustion process rule and predicts the combustion process rule; the intelligent control module is used for generating a control instruction according to a model prediction result and performing optimization control on boiler combustion equipment; and the monitoring and alarming module is used for monitoring the combustion state and the equipment operation condition in real time, and giving an alarm and taking emergency measures when abnormity occurs. The system overcomes the limitation of traditional boiler combustion control means, realizes comprehensive and accurate monitoring, intelligent and efficient control and advanced fault prediction and treatment of the combustion process, effectively improves the combustion efficiency, reduces the energy consumption and pollutant emission, enhances the operation safety and reliability of the boiler, and is suitable for various industrial boiler application scenes.

The invention discloses a turbulent combustion characteristic prediction method, device, equipment and medium, and aims to rapidly and accurately predict hydrocarbon fuel turbulent combustion characteristics, the turbulent combustion characteristic prediction method comprises the following steps: constructing a three-step reaction mechanism, the three-step reaction mechanism comprises a first reaction mechanism using hydrocarbon fuel and oxygen as reaction fuels; a second reaction mechanism using carbon monoxide and oxygen as reaction fuels; a third reaction mechanism in which hydrogen and oxygen are used as reaction fuels; a three-step reaction mechanism is carried out by taking hydrocarbon fuel as fuel through a zero-dimensional isobaric flame model, the highest temperature during complete combustion of the hydrocarbon fuel is determined as adiabatic equilibrium temperature, and the maximum value point of the temperature change rate in the combustion process of the hydrocarbon fuel is determined as ignition delay; the laminar flame velocity is determined according to the index relationship between the reaction pressure and the laminar flame velocity through a three-step reaction mechanism by taking hydrocarbon fuel as fuel through a one-dimensional isobaric flame model.

The invention relates to an engine tail flame anomaly detection method and system based on spectrum contrast, and the method comprises the steps: simulating an ideal combustion process of an engine based on a radiation model, generating an ideal tail flame spectrum for reference, and extracting the reference spectrum intensity of a target substance; the actual tail flame spectrum of the tail flame of the engine to be detected is collected, and the actual spectrum intensity of the target substance is obtained; based on the reference spectral intensity and the actual spectral intensity, obtaining dynamic characteristics used for judging whether the to-be-detected engine fails or not; constructing a dynamic threshold range for judging whether the dynamic characteristics are abnormal or not; whether the dynamic features are abnormal or not is judged based on the dynamic threshold value range, if the dynamic features exceed the dynamic threshold value range, the dynamic features are abnormal, and if the dynamic features are within the dynamic threshold value range, the dynamic features are not abnormal. According to the invention, organic combination between simulation and actual monitoring is realized, and high-precision and real-time fault diagnosis can be flexibly realized.