1285 results about "Combustion process" patented technology

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 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 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 relates to the technical field of intelligent monitoring of the waste incineration process, in particular to an intelligent monitoring method and system for the waste incineration process and electronic equipment. The method comprises the following steps: (1) collecting multi-dimensional historical data, and cleaning and normalizing the multi-dimensional historical data; (2) constructing a combustion process model by using a convolutional neural network (CNN) and a recurrent neural network (RNN), and weighting time sequence features through an attention mechanism; (3) introducing a transfer learning technology, and reducing cross-scene distribution difference based on a domain adaptive algorithm; and (4) fusing reinforcement learning to dynamically adjust equipment parameters, and giving consideration to thermal efficiency and pollution suppression targets by a reward function. According to the system, an edge-cloud collaborative architecture is adopted, the edge nodes complete real-time calculation, and the cloud executes model iteration. The incineration stability is remarkably improved, pollutant emission is reduced, and the method is suitable for complex working conditions.

The invention discloses a self-adaptive optimization control system and method for the combustion process of a biomass generator set. The self-adaptive optimization control system comprises a multi-dimensional sensing array module, an edge calculation module, a self-adaptive decision server, an execution mechanism cluster and a closed-loop verification terminal. The multi-dimensional sensing array module comprises a temperature field monitoring unit, a flue gas component analysis unit and a fuel characteristic detection unit; a data fusion processor is arranged in the edge calculation module; the self-adaptive decision-making server carries a dual-module decision-making engine; the executing mechanism cluster comprises a frequency conversion fan, a precise feeding machine and an adjustable fire grate. Through multi-source sensing data fusion and a self-adaptive decision-making mechanism, real-time response to biomass component fluctuation and load change is achieved, and the combustion efficiency is improved; a deep learning prediction model is combined, the air-coal ratio and the hearth temperature set value are adjusted in advance, and CO emission is reduced; the manual intervention frequency is reduced through an optimization mechanism, and the equipment maintenance period is prolonged.

The invention discloses a boiler combustion energy efficiency improving method and system based on digital twinning and a medium, and relates to the technical field of boilers, and the method comprises the steps that design information and historical data of a target boiler combustion system are obtained, digital twinning modeling is carried out, and a digital twinning model is built; key parts are identified based on design information, sensors are deployed, a combustion system sensing assembly is constructed, and real-time combustion state data are collected; constructing a boiler combustion energy efficiency evaluation system, performing multi-dimensional evaluation on real-time data, and determining a current energy efficiency coefficient; and performing energy efficiency improvement control on the target boiler combustion system based on the energy efficiency coefficient through a digital twin model. The technical problems of low combustion efficiency and high energy consumption caused by difficulty in real-time monitoring and optimization of energy efficiency in the boiler combustion process are solved, and accurate evaluation and intelligent optimization control of the boiler combustion state are realized through digital twin modeling and real-time sensing. The combustion energy efficiency of the boiler is improved, the energy consumption is reduced, and the operation stability is ensured.

The invention belongs to the field of combustion process monitoring, and particularly discloses a hearth flue gas CO and O2 measuring method which comprises the following steps: S1, acquiring original signals of CO concentration data and O2 concentration data; s2, performing data preprocessing on the obtained original signals of the CO concentration data and the O2 concentration data to generate a standardized electric signal sequence; s3, calculating the concentration of CO and the concentration of O2 through the standardized electric signal sequence; s4, acquiring environment temperature, humidity and concentration data of interference gas in flue gas to obtain a correction data set, and dynamically correcting the calculation results of the CO concentration and the O2 concentration according to the correction data set; according to the method, advanced data preprocessing and an accurate concentration calculation model are combined, the accuracy of CO and O2 concentration measurement is effectively improved, and the stability of a measurement system is enhanced by combining temperature drift compensation of the sensor and dynamic correction of the pre-trained neural network model on the detection concentration.

The invention relates to the technical field of garbage feeding control, in particular to a garbage feeding device for incineration power generation and an adjusting method. Garbage water content characteristics are analyzed through leachate flow time sequence data, density characteristics are quantified in combination with load coefficients, combustion characteristics are represented through carbon monoxide concentration changes, and a leachate characteristic coefficient, density characteristic coefficient and combustion characteristic coefficient three-dimensional index system is constructed. A clustering algorithm is adopted to carry out mode recognition on garbage grabbing operation, and clustering clusters with similar combustion characteristics are formed. In a cluster to which current garbage grabbing operation belongs, parameters of a feeding speed and a shake-off speed are dynamically optimized based on carbon monoxide concentration distribution characteristics, and a traditional fixed control mode is replaced. According to the method, intelligent matching of garbage component changes and process parameters is achieved, the combustion process is optimized through leachate management, pile compaction degree and the like, and garbage combustion sufficiency is remarkably improved.

The invention belongs to the technical field of hazardous waste treatment, and particularly relates to a treatment method of organic hazardous waste. An inner core is prepared from the organic hazardous waste and an additive, outer shell powder is obtained from an oxidizing agent and a reducing agent, then the core-shell structure energetic material is prepared in a coating mode, and finally the prepared core-shell structure energetic material is ignited for organic hazardous waste treatment. Compared with an existing incineration treatment technology, organic hazardous waste treatment can be conducted without traditional incineration equipment; as the oxidizing agent is in uniform and tight contact with the organic matter, large heat is released in the combustion process, the local temperature is high, oxygenolysis is rapid and thorough, and a good treatment effect is achieved; the method is short in technological process, low in energy consumption and cost and remarkable in economic and environmental benefits. According to the treatment method provided by the invention, inorganic gas and inorganic compounds are presented after combustion, so that group components forming the dioxin are fully dispersed, and generation of the dioxin is favorably inhibited.

Disclosed in the present invention are a 90°C thermoplastic halogen-free low-smoke flame-retardant polyolefin sheath material and a preparation method therefor. The sheath material is prepared from raw materials comprising the following components in parts by mass: 20-40 parts of an ethylene-vinyl acetate copolymer, 20-40 parts of a linear low-density polyethylene, 2-10 parts of a high-density polyethylene, 20-40 parts of a metallocene ethylene-octylene copolymer, 10-15 parts of a maleic-anhydride-grafted metallocene linear low-density polyethylene copolymer, 58-73 parts of aluminum hydroxide, 20-25 parts of modified magnesium hydroxide, 64-84 parts of a synergistic flame retardant, 2-3 parts of a coupling agent, 1-4 parts of a lubricant, 1-3 parts of an antioxidant, and 2-7 parts of a coloring agent, wherein the synergistic flame retardant comprises lithium oxide. A matrix resin has low-temperature performance, mechanical properties and cracking resistance. With regard to flame retardance, a large amount of the synergistic flame retardant, i.e., lithium oxide, is added to a traditional magnesium-aluminum compound flame-retardant system, and therefore an off-white hard shell can be formed during a combustion process while low heat release is ensured, thereby ensuring no dripping during the combustion process.

The invention discloses a dual-fuel engine combustion control method based on hydrogen-ammonia energy ratio and gas distribution overlap angle regulation and control, which comprises the following steps: 1) fuel ratio control: acquiring current operation state parameters of an engine, determining a target AER according to preset mapping, regulating ammonia gas supply quantity and hydrogen supply quantity to enable the actual AER to reach the target AER, and controlling the fuel ratio; the AER is adaptively set according to engine load and combustion stability conditions; 2) valve timing control: adjusting the opening time of an intake valve or the closing time of an exhaust valve through a variable valve timing mechanism so as to change a valve timing overlap angle VOA, wherein the VOA is set to be a negative value, a small overlap angle or a positive overlap angle according to the working condition of an engine; (3) injection time sequence optimization is conducted, specifically, the injection time of ammonia gas and the in-cylinder direct injection time of hydrogen are controlled respectively, and coordinated optimization of a fuel injection strategy and valve timing is achieved; and 4) closed-loop steady-state control: monitoring a combustion state and an emission index in real time, comparing the combustion state and the emission index with a threshold value to serve as a feedback signal, and correcting the target AER and VOA settings in time. According to the dual-fuel engine combustion control method based on regulation and control of the hydrogen-ammonia energy ratio and the gas distribution overlapping angle, the energy ratio of hydrogen fuel and ammonia fuel and the overlapping opening angle of an intake valve and an exhaust valve are dynamically adjusted under different working conditions, so that the combustion reaction rate and temperature are coordinated, and the stable and efficient combustion process is achieved; and harmful emissions of NOx, unburned ammonia and the like are obviously reduced.

The invention provides an intelligent control method for natural gas continuous heat treatment equipment based on digital twinning, and relates to the technical field of heat treatment equipment control. The method comprises the steps that a digital twinning model of the natural gas continuous heat treatment equipment is established, and production monitoring data collected on line are utilized; the method comprises the following steps: predicting combustion process characteristics and unmeasurable states through a digital twin model, performing multi-layer strategy search by adopting a hierarchical control strategy according to a state prediction result, performing safety constraint simulation verification on the multi-layer strategy in the digital twin model, and predicting unmeasurable state parameters through a soft sensor. And introducing the quality index as a soft constraint condition into optimization control, and generating a control execution parameter meeting the constraint condition. The technical problems that in the prior art, natural gas continuous thermal treatment equipment is poor in control effect and unstable in workpiece quality are solved. The technical effects that the natural gas continuous heat treatment equipment is intelligently, accurately and reliably controlled, and the product quality is improved are achieved.

The invention discloses an incineration condition multi-scale identification method based on a capsule network. The method comprises the following steps: S1, collecting multi-modal image sequence data of a waste incineration hearth; s2, obtaining a weighted multi-scale SE attention feature map; s3, outputting a time sequence stable waste incineration hearth working condition judgment vector; s4, a garbage incineration hearth working condition classification result is obtained; s5, updating the combustion condition identification model; and S6, the garbage incineration hearth working condition classification result is input into an edge control interface, and a control signal for the combustion process of the incinerator is generated. According to the method, the characteristic weight of each scale channel can be adaptively adjusted according to the actual working condition of severe change of the temperature field of the incineration site and smoke disturbance, so that the high robustness and fine granularity discrimination capability of the working condition identification characteristics are still kept under the complex conditions of high smoke shielding, high moisture garbage and large piece feeding; actual measurement working condition identification accuracy can be kept above 95% for a long time.

The invention discloses a phosphorus-tin-based flame retardant synergistic flame-retardant epoxy resin composition and a preparation method thereof, and belongs to the technical field of high polymer material modification and flame retardance. The preparation process of the flame-retardant epoxy resin composition comprises the following steps: respectively adding the phosphorus-based flame retardant, the tin-based flame retardant and the curing agent into the epoxy resin, uniformly mixing, pouring into a mold, and curing to obtain the flame-retardant epoxy resin composition. The phosphorus-based flame retardant and tin-based flame retardant synergistic flame-retardant epoxy resin composition has the advantages of good flame retardance, smoke suppression and thermal stability, low carbon, environmental protection and the like. The flame-retardant system overcomes the defect that toxic smoke and corrosive gas can be generated in the combustion process of traditional halogen-series flame retardants, antimony trioxide flame retardants and the like, and becomes one of environment-friendly flame retardants which reduce halogen and replace antimony trioxide.

The invention discloses a storage and supply system for enhancing flexible operation of a coal power unit by a pulverized coal bunker, particularly relates to the field of thermal power generation, and is used for solving the problem that fuel conveying and combustion are asynchronous during rapid load adjustment of the coal power unit. Coordination control is carried out with the unified fuel demand as the center, the lag effect of pulverized coal storage and release is accurately predicted and counteracted before pulverized coal enters a boiler, and the pulverized coal conveying rhythm is closely aligned with the actual coal use demand. In this way, the oxygen amount and temperature fluctuation in the boiler combustion process are greatly reduced, and the problems that due to the fact that fuel supply is fast and slow, combustion in the boiler is not stable, and pollutant emission is increased are solved; meanwhile, the whole control method can automatically learn and adjust, frequent human intervention is not needed, operation is simpler, more convenient and safer, the capacity of a power plant for rapidly adapting to power grid load changes is remarkably improved, and the flexible advantage of pulverized coal storage and supply is fully played.

The invention discloses a gas turbine multi-fuel reference real-time voting scheduling method, and relates to the technical field of gas turbine combustion control, and the method comprises the steps: constructing a plurality of fuel control references, carrying out the collection, integration and comparison of the output of each fuel control reference through a real-time voting control loop, and generating a final fuel control reference; according to the real-time monitoring result, intervention and quit of each fuel control reference are dynamically judged; the proportion of diffusion fuel and premixed fuel and the flow of each branch are controlled through a fuel distribution system, and gas turbine multi-fuel reference real-time voting scheduling is achieved. The fuel distribution proportion can be flexibly adjusted under different working conditions, the combustion process is optimized, fine combustion control of the gas turbine under different working conditions is achieved, the comprehensive performance and economical efficiency of the gas turbine are remarkably improved while the combustion efficiency is improved, pollutant emission is reduced, and the equipment safety is enhanced, and the method is suitable for popularization and application. The method has important application value and wide market prospect.

Embodiments of the present application relate to the technical field of nuclear reactors, and disclose a method and system for predicting the state of a reactor core, a device, and a medium. The method comprises: acquiring first reactor core state measurement parameters of a target reactor core in a first time step, the first time step being a time step obtained by dividing a combustion process of the target reactor core, and the first reactor core state measurement parameters comprising state measurement parameters of the target reactor core in a plurality of physical fields; when the first reactor core state measurement parameters are inputted into a data fusion model, by means of the data fusion model, performing fusion processing on the state measurement parameters of the plurality of physical fields, and obtaining a target data matrix; and when the target data matrix is inputted into a state prediction model, by means of the state prediction model, performing prediction to obtain first reactor core state information, the first reactor core state information being used for representing a reactor core state of the target reactor core in a second time step, and the second time step being later than the first time step.

The invention belongs to the field of coupling blending combustion of a thermal power plant, and discloses a system and a method for blending combustion by utilizing biomass furfural residues, through the synergistic effect of a blending combustion pretreatment system and an intelligent control system, accurate and efficient control of the whole furfural residue blending combustion process is realized, and acidity is monitored in real time by utilizing an acidity sensor in a stirrer; the adding amount of a neutralizer is intelligently adjusted, full neutralization reaction is ensured, excessive use is avoided, the screw extruder detects initial moisture through a moisture sensor and automatically adjusts current to optimize extrusion strength and speed, the dryer is monitored in real time through a temperature sensor, stable temperature control is achieved, and the production efficiency is improved. Meanwhile, the waste gas recovery device preheats materials to be dried through heat exchange, efficient recovery of waste heat is achieved, the filtrate treatment device recovers valuable components such as furfural through distillation, extraction and filtration processes, and resource waste is reduced. Material loss and energy loss are reduced through a closed pipeline and automatic conveying, and finally it is ensured that the moisture and acidity of the dried furfural residues reach the standard, and the quality is uniform and stable.

The invention provides a polyolefin base material standard sample for measuring the flame retardant property of a cable material and a preparation method of the polyolefin base material standard sample, and belongs to the field of standard preparation. The sample adopts polyolefin resin as a matrix, and an inorganic flame retardant subjected to silane surface treatment, an anti-dripping agent and the like are added to adjust the combustion rate, so that the product can meet the combustion range corresponding to an actual test. The inorganic flame retardant modified by the silane coupling agent can promote the dispersion of the inorganic flame retardant in the resin and the affinity of the inorganic flame retardant and the resin, improves the uniformity of the material, and also can ensure the structural stability of the material in the combustion process; meanwhile, the lubricant is added, so that the material uniformity and dispersity are improved, and the uniformity and stability of combustion data are ensured; the anti-dripping agent is added, so that unstable data between parallel tests due to the dripping phenomenon of the material during combustion is avoided. The polyolefin-based combustion test standard sample can be applied to calibration of combustion tests of a cone calorimeter, a smoke density experimental box and the like and comparison of experimental data in the same row.

The invention relates to a blast furnace multi-parameter coupling optimization energy-saving control system, and belongs to the technical field of blast furnace control systems. The system comprises a raw material and material distribution determining module used for determining an initial proportioning scheme and an initial material distribution matrix; the parameter acquisition module is used for distributing the crude fuel into the blast furnace according to the initial distribution matrix and acquiring a plurality of real-time combustion parameters of combustion of the crude fuel; the parameter screening module is used for screening key real-time combustion parameters of a plurality of key combustion parameter types; the combustion control module is used for adjusting equipment parameters of the blast furnace according to the multi-parameter coupling combustion field model framework and the blast furnace combustion energy consumption at the current moment; the raw material distribution adjusting module is used for adjusting an initial raw material proportioning scheme and an initial distribution matrix by adopting a double-layer optimization framework; and the closed-loop control module is used for performing closed-loop control on the blast furnace combustion process. Intelligent control over energy consumption optimization of multiple parameters in the blast furnace combustion process is achieved, the cost can be reduced, and the combustion efficiency of the blast furnace can be improved.

The invention discloses a pulverized coal combustion wind speed prediction method and system based on a neural network, and the method comprises the steps: S1, obtaining and preprocessing historical combustion data, and obtaining a standardized time series data set; s2, constructing a time sequence training set based on the standardized time sequence data set, extracting dynamic change characteristics of the combustion process, and performing abnormal value correction on the time sequence training set based on the dynamic change characteristics; s3, based on the corrected time sequence training set, key features are extracted, an optimization framework is selected, an initial wind speed prediction model is constructed and trained, and a final wind speed prediction model is obtained; and S4, embedding the final wind speed prediction model into a combustion control system, obtaining combustion state data in real time, calculating a predicted wind speed value through forward propagation, dynamically updating model parameters according to the deviation between the predicted value and an actual value, and updating control parameters of the combustion control system according to the predicted wind speed value to realize real-time optimization of the combustion process. According to the invention, the accuracy and real-time performance of wind speed prediction can be improved.

The invention belongs to the technical field of industrial combustion safety control, and provides a double-channel industrial furnace gas combustion safety interlocking control system which comprises a gas / air flow ratio dynamic monitoring module, a flue CO concentration online detection module, a double-channel data conflict arbitration processor and a visual human-computer interface. Aiming at the prominent problems of incomplete combustion of coal gas, carbon deposition, detonation risk and the like which are easy to occur under the working condition of accelerated temperature rise, the system integrates visual double-insurance safety control of dynamic calculation of a flow ratio and real-time analysis of tail gas components, and all-directional safety protection in the combustion process is realized through a multi-parameter cooperative monitoring and intelligent interlocking mechanism; the detonation risk is obviously reduced; meanwhile, the air-fuel ratio fluctuation is accurately controlled within the range of + / -5%, and the carbon deposition phenomenon is effectively reduced; and remarkable economic benefits are created while reliable operation of equipment is guaranteed.

The invention discloses a visual measurement device and method for the combustion process of an electronic control solid propellant. The measurement device comprises a grain sample, a power source, a control system, a high-speed camera, a constant-volume combustion bomb, a temperature controller and a gas supply system. The constant-volume combustion bomb comprises a heating element, a combustion chamber and an integrated seat, and the high-speed camera directly faces the visual window; the integrated seat comprises an adapter and an electrode assembly, the electrode assembly comprises an electrode column, an electrode clamping plate and an electrode slice, the electrode slice is attached to the side face of a grain sample, the grain sample is located in an electrode slice excitation area and comprises a medicine core and an insulating layer, and the lower end of the medicine core is an initial combustion section; according to the measuring device, the image technology and the controllable environment cavity are fused, the burning rate of the solid propellant under various working conditions is collected, the burning rate and related burning parameters can be accurately measured without interference under various set working conditions through a grain sample special for non-contact measurement and an exciting electrode assembly, and the measuring method can achieve synchronous triggering collection of multiple physical quantities, so that the measuring efficiency is improved. And the multi-physical coupling combustion characteristics of the propellant can be conveniently analyzed.

The invention provides a device for monitoring a combustion process in real time, and belongs to the technical field of combustion process monitoring and control. The device comprises a multispectral light source module, an optical detection module, a data processing module and a control module. The multispectral light source module can emit multispectral signals covering ultraviolet, visible and infrared bands, and multiple paths of light beams are generated through light beam shaping, frequency doubling, optical parametric oscillation and the like and are incident to a combustion area. The data processing module performs feature extraction, mode recognition and trend prediction on the signals, and recognizes parameters such as flame state, temperature, gas concentration, combustion efficiency and pollutant emission. The control module dynamically adjusts operation parameters of the combustor according to the analysis result, and closed-loop control is achieved. Through multi-band spectrum joint detection and intelligent algorithm analysis, the defect that single-band detection is prone to interference is overcome, and high-sensitivity, multi-dimensional and real-time monitoring and intelligent control over the combustion process are achieved.

The invention relates to waste heat recovery equipment and a natural gas hydrogen-doped combustion system. The waste heat recovery equipment comprises a first heat exchanger, a second heat exchanger and a spray tower, the first heat exchanger is provided with a first heat absorption side and a first heat release side, an outlet of the first heat absorption side is communicated with a combustion-supporting gas inlet of the combustor, the second heat exchanger is provided with a second heat absorption side and a second heat release side, and an inlet of the second heat release side is connected with a high-temperature flue gas outlet of the combustor. The spray tower is provided with a cooling water inlet, a smoke inlet, a smoke outlet and a spray water outlet, the smoke inlet is communicated with the outlet of the second heat release side, the spray water outlet is communicated with the inlet of the second heat absorption side, and the outlet of the second heat absorption side is communicated with the inlet of the first heat release side. According to the waste heat recovery equipment, two-stage waste heat recovery of high-temperature flue gas is achieved, the waste heat recovery efficiency is remarkably improved, combustion-supporting gas can be heated, accordingly, other combustion efficiency is improved, natural gas consumption and carbon emission are reduced, and the requirements for energy conservation and carbon reduction in the industrial high-temperature combustion process are met.

The invention discloses an in-cylinder combustion process and chemical reaction mechanism-based hydrogen ammonia emission generation prediction system and method, and relates to the technical field of hydrogen internal combustion engine tail gas emission control, and the system comprises an input variable acquisition module, a combustion simulation module, a chemical reaction simulation module, an emission generation prediction module and an output interface module; according to the method, a mechanism-driven multi-physics field coupling prediction system is constructed, the simplified assumption limitation of a traditional empirical model is broken through, high-precision dynamic analysis of the emission characteristics of the hydrogen-ammonia engine is achieved, in combustion process simulation, in-cylinder turbulence mixing and flame propagation details are accurately described by using a CFD model, and in-cylinder combustion simulation is achieved. The chemical reaction module can significantly improve the prediction credibility of unburned fuel residues and pollutant generation through sensitivity analysis and mechanism optimization, in addition, through real-time coupling sensor data and simulation calculation, the abnormal emission trend can be pre-judged in advance, and a feedforward control basis is provided for the ammonia injection amount, the EGR rate and the ignition angle.

The invention discloses an in-cylinder flame multi-characteristic parameter extraction and instantaneous evaluation method based on machine learning, and belongs to the technical field of power energy. Aiming at the problem that a traditional method is difficult to accurately extract flame transient characteristic parameters in a dynamic combustion environment, the method comprises the following steps: acquiring an in-cylinder flame image sequence through an endoscopic high-speed camera, and extracting an event driving key frame and a uniform time key frame by adopting optical flow analysis and fixed interval sampling; utilizing a double-flow feature extraction network to respectively obtain flame spatial form features and radiation features; capturing a flame parameter time evolution law through a time sequence convolutional network, and dynamically fusing key frame features in combination with a self-attention mechanism; and finally outputting flame temperature field and soot distribution prediction results. According to the method, instantaneous evaluation of the combustion process is realized, and a basis is provided for engine performance optimization and combustion fault diagnosis.

The invention provides a vehicle control method and system, a vehicle and a storage medium, and the method comprises the steps that when the temperature of a downstream switch oxygen sensor is smaller than the dew point temperature, an engine control unit determines the target maximum allowable rotating speed and the target maximum allowable torque of an engine according to the water temperature of the engine, a working condition coordination request is sent to the hybrid power control unit; and the hybrid power control unit controls the engine and the motor to enter a series connection mode according to the working condition coordination request, and controls the maximum allowable rotating speed of the engine to be smaller than or equal to the target maximum allowable rotating speed and the maximum allowable torque of the engine to be smaller than or equal to the target maximum allowable torque. Therefore, the actual rotating speed of the engine does not exceed the target maximum allowable rotating speed, and the actual torque of the engine does not exceed the target maximum allowable torque. The temperature of the engine in the combustion process can be reduced, generation of harmful substances in originally discharged waste gas is reduced, and therefore the emission performance of the vehicle is improved to a certain degree.

The invention provides a ternary synergistic flame retardant suitable for a polylactic acid composite material and a preparation method thereof. The ternary synergistic flame retardant comprises ternary components of magnesium hydroxide, zinc oxide and titanium dioxide, the ternary component is subjected to surface modification through a silane coupling agent solution containing an epoxy group, the mass ratio of magnesium hydroxide to zinc oxide to titanium dioxide is 4: 1.5: 1-5: 2: 1, and the ternary component is used for maintaining the mechanical property of polylactic acid and achieving the synergistic effect of flame retardance and smoke suppression at the same time. According to the polylactic acid composite material prepared by the invention, the limit oxygen index is increased to 28.85% from 19.91%, the increase amplitude is about 45%, and the UL-94 V-0 grade is reached; the maximum smoke density is reduced from 287 to 198, the reduction amplitude is about 31%, and the flame retardant efficiency of the material and the visibility in the combustion process are remarkably improved. The addition amount of the ternary synergistic flame retardant is controlled in a range of 15-25%, an excellent flame retardant effect can be obtained, the addition amount is greatly reduced compared with that of a single magnesium hydroxide system (generally, the addition amount needs to be larger than or equal to 40%), and the mechanical property loss caused by high filling is effectively avoided.