14123 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 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.

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 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 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.

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.

The invention discloses a pyrolysis recovery system for cooperative treatment of waste wind power blades by a power station boiler, and belongs to the technical field of solid waste recovery. The system comprises a power station boiler, a pyrolyzing furnace, a mixed flue, a nitrogen air flue and a controller. Oxygen is accurately controlled by mixing flue gas at different temperature levels and mixing nitrogen, and a safe and stable heat source is provided for the pyrolyzing furnace; pyrolysis gas returns to a boiler hearth through an outlet flue to be burnt out, and recyclable fibers and residues are conveyed out through a chain grate stoker; and the controller is linked with each sensor to execute oxygen control, temperature regulation, fiber quality protection and safety interlocking operation. The problems that in pyrolysis of the waste wind power blade, heat source adaptability is poor, oxygen concentration is out of control, fiber quality is poor, the risk is high, and pyrolysis gas is difficult to dispose are solved, and gradient utilization of energy, intrinsically safe operation, high-quality and high-purity recovery of fibers and collaborative treatment of pollutants are achieved.

The invention relates to the technical field of environmental monitoring, and discloses an uncertainty evaluation method based on establishment of a carbon emission monitoring method and an accounting method, and the method comprises the following steps: establishing an uncertainty evaluation model of a coal-fired unit carbon emission monitoring method to quantify the uncertainty of the carbon dioxide emission of the monitoring method; establishing a coal-fired unit carbon emission accounting method uncertainty evaluation model to quantify the uncertainty of the carbon dioxide emission of the accounting method; based on results obtained by the monitoring method uncertainty evaluation model and the accounting method uncertainty evaluation model, carbon emission data quality is analyzed, and improvement measures are put forward. By constructing an uncertainty evaluation model of a monitoring method and an accounting method, various error sources in the whole process of flue gas sampling, analysis, fuel metering, coal quality analysis and the like are comprehensively considered, and a rigorous mathematical method is adopted for synthesis. The quantitative evaluation enables the accuracy of the carbon emission data to have a clear measurement standard.

The invention relates to the technical field of boiler control, and discloses a gas-fired boiler starting control method and system. The method comprises the following steps: acquiring initial operation parameters such as hearth pressure, water inlet temperature, flue gas oxygen content and fuel valve opening of the gas-fired boiler, establishing a thermodynamic state model in a starting stage according to the initial operation parameters, and dividing dynamic response thresholds of different load intervals; and calculating a theoretical fuel supply rate of the combustor based on the model, generating and dynamically updating a fuel supply correction coefficient in combination with a threshold value, synchronously marking key nodes according to abnormal distribution of hearth temperature, and adjusting a spatial air distribution strategy of the combustor. And after the correction coefficient is subjected to multi-stage buffer smoothing, a fuel control instruction is output to an executing mechanism. And switching to steady state control after the boiler reaches the preset load. The method adapts to the characteristics of a power plant unit, so that the starting process is more stable, the damage to a heated surface and pollutant emission are reduced, and rapid grid connection is assisted.

The invention provides a flue gas waste heat recovery variable load working condition self-adaptive control method and system. The method comprises the steps that the boiler load change rate is determined; identifying the characteristics of the current boiler operation condition; adjusting or selecting a system response time constant for calculating the pre-adjustment amount; calculating the pre-adjustment amount of a flow control element of the flue gas waste heat recovery system; control parameters of a feedback control loop of the flue gas waste heat recovery system are adjusted; and the pre-adjustment amount and the adjusted feedback control loop control parameters are fused, a cooperative control instruction is generated, and the opening degree of a flow control element of the flue gas waste heat recovery system is adjusted. The method aims at solving the problem that real-time and dynamic collaboration is difficult to carry out between conflict targets in an existing control method, flue gas waste heat is recycled and effectively utilized to the maximum extent, safe and reliable operation of the system is guaranteed, and the operation cost is reduced.

The invention relates to a boiler flue gas temperature dynamic compensation method based on CFD-reinforcement learning, and belongs to the technical field of boiler operation control. The method comprises the steps that boiler operation parameters and flue gas temperature data are collected in real time, a multi-scale coupling three-dimensional CFD model is constructed, a macroscopic gas-solid two-phase flow-combustion reaction-radiation heat transfer coupling algorithm and a microcosmic pulverized coal particle combustion dynamics algorithm are fused, and hearth and flue temperature distribution is simulated and output; building a CFD-reinforcement learning fusion agent based on a CFD model, taking similar working condition agent parameters as initial values, combining historical and virtual data staged training, and reinforcing the weight of a key temperature measurement point through a focusing regulation and control strategy; an echo state network-predictive control collaborative algorithm is adopted, real-time data are input to obtain an initial adjustment amount, and after security constraint optimization, a compensation execution mechanism is controlled to act. The flue gas temperature is accurately and dynamically compensated, the adaptability to complex working conditions is improved, and equipment safety and operation efficiency are both considered.

The invention discloses a thermal power generating unit, flywheel and compressed air hybrid energy storage system and an operation method, and relates to the technical field of flexibility improvement of novel energy storage and thermal power systems. The system comprises a flywheel energy storage subsystem, a compressed air energy storage subsystem, a thermal power collaborative heat exchange system, a flywheel-CAES switching coupling module and an intelligent control system. The flywheel energy storage subsystem is responsible for millisecond-level frequency modulation response, the compressed air energy storage subsystem provides minute-level stable output, and the flywheel energy storage subsystem and the compressed air energy storage subsystem cooperatively work through an intelligent control system to realize a composite regulation mode of'fast response-high capacity '; a compressed air side is coupled with a thermal power plant turbine steam extraction system, a boiler flue gas system and a condensed water system to improve the energy release efficiency; the flywheel side interacts with a power grid in real time through a bidirectional converter, and rapid frequency support is achieved. The system has the quick response capability and the long-time energy supporting capability, the frequency modulation and peak regulation performance of the thermal power generating unit is remarkably improved, and the system has high engineering popularization value and application prospects.

The invention discloses a multi-mode heat supply energy consumption evaluation method and system, and relates to the technical field of heat supply energy consumption evaluation and dynamic thermal scheduling control, and the method comprises the steps: arranging a multi-source sensor in a high-temperature flue gas path to collect thermal parameters, and building a time sequence mapping model between a unit load and flue gas thermal characteristics; and according to the thermal power data output by the time sequence mapping model and the heat exchange characteristics of all the heat supply modes, a heat energy availability map of the target time period is generated, and heat demand adaptation data is constructed. And selecting a matching path according to energy consumption and switching constraints based on the heat energy availability map and the heat demand adaptive data, and executing mode dynamic switching control. According to the method, a complete technical closed loop from data perception to state evaluation to action execution is formed. In the multi-mode heat supply system, system fusion of three-layer logic of heat load prediction, map expression and dynamic scheduling is realized, and the intelligence, self-adaption and energy efficiency optimization capabilities of the heat supply process are remarkably improved.

The invention belongs to the technical field of industrial flue gas purification, and discloses an ammonia desulfurization optimization control system based on a machine learning algorithm, which comprises a feature extraction module, a working condition clustering module, a dynamic optimization module and a self-adaptive feedback module, the feature extraction module is used for collecting multi-dimensional operation parameters in a coal burning process, performing data dimension reduction through a PCA algorithm, and extracting key working condition features; the working condition clustering module identifies different operation working condition modes; the dynamic optimization module can construct a multi-modal optimization neural network based on different operation condition modes, and generates optimal control parameters in real time. Through PCA dimension reduction processing of the feature extraction module and in combination with a working condition clustering algorithm, automatic mode recognition and strategy switching under complex working conditions are achieved, fluctuation of desulfurization efficiency is reduced, and meanwhile the problems that the ammonia water adding amount depends on experience setting, raw material waste and secondary pollution are likely to be caused, and the operation and maintenance cost is large are solved.

The invention discloses a condensation-free efficient heat exchange control method and system for a full-premixing water heater, and the method comprises the steps: collecting the multi-source information, such as air inlet temperature, humidity, gas flow, flue gas oxygen concentration and wall temperature, in real time, calculating a predicted dew point based on a dynamic dew point prediction model, and setting a dynamic safety boundary; the condensation risk is judged by comparing the wall temperature with the safety boundary, and active intervention is carried out in a staged cooperation mode that fuel gas and air volume are continuously adjusted firstly and then a partial combustion zone sectioning valve is rapidly turned off; the system comprises a main controller, a mesh-shaped infrared radiation burner, a sectional valve assembly, a gas proportional valve, a frequency conversion fan and related sensors. According to the invention, the system runs close to the condensation boundary through intelligent control, and the advantage of high operation heat efficiency is realized on the premise of ensuring high reliability.

The invention relates to the technical field of on-line monitoring, in particular to a flue gas cooler leakage monitoring system and method.The method comprises the steps that a multi-source real-time sensing layer module continuously collects tube plate weld joint area temperature data, cooling water flow characteristics and flue gas sulfur-containing gas concentration, and the sampling period is 250 milliseconds; the intelligent feature fusion module performs noise reduction processing and dynamic weight fusion on the multi-source data and outputs a leakage probability vector; the dual-system collaborative early warning module maps the probability vectors into confidence levels, a 65% confidence threshold triggers an acoustic verification system to start, an acoustic emission sensor array captures fractured sound wave features and then compares the fractured sound wave features with a voiceprint library through a convolutional neural network, and an early warning signal is output when the fractured sound wave features exceed a 0.85 similarity threshold; and the dynamic knowledge base updates the case characteristics online according to the early warning result. According to the system, second-level identification and continuously optimized closed-loop monitoring at the initial stage of leakage germination are realized, and the problem of response delay caused by intermittent detection in the prior art is solved.

The invention discloses a flue gas compensation type pulverized coal wide-load stable combustion system based on staged combustion and intelligent regulation and control and a control method, and belongs to the technical field of coal-fired power generation. The system is composed of a combustor, an intelligent control module and a flue gas backflow module, the combustor adopts a double-ring fuel channel design, an inner ring injects high-concentration pulverized coal and is provided with an adjustable swirler, and pulverized coal-flue gas mixed airflow is introduced into an outer ring; the intelligent control module predicts a load through an LSTM neural network, and realizes accurate matching of air and coal in combination with PID adjustment; and the flue gas backflow module adopts an oxygen concentration adjustable technology to maintain the combustion intensity. Under the working condition of 30%-40% low load, the system achieves the stable combustion effect that the flame center temperature is stabilized at 920 + / -20 DEG C by means of optimizing the proportion of inner ring pulverized coal to 75%-85%, increasing the primary air temperature to 145-170 DEG C, compressing the proportion of secondary air to 20%-30%, strengthening a swirling flow field to 45 degrees and the like in cooperation with flue gas backflow with the oxygen concentration of 23%-25%, and has the advantages of efficient combustion and low emission.

The invention relates to the field of atmospheric control and pollution abatement, in particular to high-concentration environment-friendly flue gas desulfurization and dust removal equipment. Comprising a tower shell, the tower shell is provided with an air inlet, the upper side of the tower shell is fixedly connected with a ventilation cylinder through a support, the upper side of the ventilation cylinder is fixedly connected with a top disc, the top disc is provided with an exhaust port, and the lower side of the top disc is provided with liquid spraying pipes distributed in the circumferential direction. The ventilation cylinder and the tower shell form an air inlet cavity communicated with the air inlet, the lower side of the tower shell is provided with a liquid outlet used for discharging liquid in the tower shell, the lower part of the inner wall of the ventilation cylinder is provided with a first filter screen used for removing dust, and the diameter of the ventilation cylinder is gradually reduced from the middle to the bottom. According to the invention, the ventilation cylinder is set to be wide at the top and narrow at the bottom, and is matched with the spiral distribution of the gas guide holes, so that flue gas is uniformly distributed in the ventilation cylinder, the contact area between the flue gas and lime slurry is increased, and the desulfurization efficiency of high-concentration flue gas is improved.

The invention provides a pyrolysis recovery method of a plastic packaging bag, and belongs to the technical field of plastic packaging bag recovery, the pyrolysis recovery method of the plastic packaging bag comprises the following steps: removing impurities from the waste plastic packaging bag, cleaning and drying, and controlling the moisture to be below 5%; the packaging bag is crushed into small blocks with the diameter smaller than 20 mm, so that the pyrolysis efficiency is improved; feeding the crushed plastic into a pyrolyzing furnace through a spiral feeder, adding an auxiliary pyrolyzing component, heating to 300-600 DEG C under an oxygen-free or oxygen-deficient condition, and carrying out thermal cracking; oil gas obtained after pyrolysis is condensed through a cooling system and classified, and solid residues are subjected to tempering treatment; flue gas generated after combustion is subjected to high-temperature degradation through a secondary combustion chamber and then subjected to multistage treatment through a quench tower, dust removal, alkali spraying and activated carbon adsorption, and it is ensured that the flue gas reaches the standard and is discharged; the problems that in the existing pyrolysis recycling process of the plastic packaging bags, the treatment efficiency is low, and the environment is still polluted can be solved.

The invention discloses a novel precise ammonia spraying control system for an SNCR (selective non-catalytic reduction) denitration system. The system comprises an original pipeline, a newly added pipeline, a partitioned solution mother pipe, a first connecting pipe, a main stop valve, a first stop valve and partitioned solution branch mother pipes, a partition solution mother pipe is connected to the newly added pipeline, a main stop valve, a first stop valve and a second stop valve are arranged in the partition solution mother pipe, and the main stop valve is connected with the first stop valve and the second stop valve in parallel; according to the device, a modular design is adopted, dual improvement of denitration accuracy and stability is achieved through monitoring system reconstruction and control logic optimization, on one hand, a closed-loop control system with partition real-time monitoring, trend pre-judgment and hierarchical quantity control is constructed, flue gas analyzers and sampling point probes are arranged at inlets of the three types of cyclone separators respectively, and on the other hand, the flue gas analyzers and the sampling point probes are arranged on the other sides of the three types of cyclone separators respectively; the NOx concentration of the original flue gas of each partition is collected in real time and synchronously passes through a data collection chip arranged in the partition NOx storage early warning device.

The invention discloses an intelligent control system for a high-temperature flue gas regulating valve based on segmented hysteresis and dynamic compensation, which comprises a data acquisition module, a segmented hysteresis interval control module, a dynamic prediction compensation module and a visual interface, and relates to the technical field of RTO waste heat recovery control. According to the high-temperature flue gas regulating valve intelligent control system based on segmented hysteresis and dynamic compensation, the flue gas regulating valve intelligent control system is arranged, and a segmented hysteresis interval control module is used for achieving a segmented temperature interval and setting the number of control times of a control regulating valve through double-threshold hysteresis; the dynamic prediction compensation module is used for predicting the smoke flow in the future to obtain the compensation amount and determining the flow deviation compensation amount, disturbance of smoke flow fluctuation to intelligent control of the regulating valve is effectively avoided, deviation of steam flow fluctuation to intelligent control of the regulating valve is restrained, and the intelligent control accuracy of the regulating valve is improved. Coordinated control operation considering quick response and steady-state precision is realized, and the waste heat recovery rate is effectively improved.

According to the low-concentration flue gas CO2 absorbent screening method, system, equipment and medium disclosed by the embodiment of the invention, the RF for feature screening and the XGBoost for performance prediction are combined to construct a high-precision physical property prediction model, so that the dependence on experimental data is reduced; by introducing an NSGA-II algorithm of an adaptive constraint processing mechanism, weights of key features are dynamically adjusted, a global optimal solution is ensured, the accuracy of the model is effectively improved, and industrial requirements are met. Finally, the low-concentration flue gas CO2 absorbent formula which is excellent in performance and economical and feasible is screened out, an efficient absorbent design scheme is provided for industrial application, the efficiency and economical efficiency of the CO2 capturing process are improved, the industrialization process of the CO2 capturing technology is promoted, and powerful technical support is provided for achieving the purposes of carbon emission reduction and carbon neutralization.

The invention relates to the technical field of smoke exhaust waste heat recovery devices, and discloses a waste heat utilization and recovery device and method applied to boiler combustion smoke, and the waste heat utilization and recovery device applied to the boiler combustion smoke comprises a bottom frame, and a heat absorption mechanism, a middle section partition plate and a heat release assembly which are fixedly mounted at the top of the bottom frame in sequence; through the arrangement of the heat buffering assembly, when the temperature of smoke is high, the heat absorbing fins can absorb part of heat and conduct the heat to the medium storage cavity, a medium in the medium storage cavity absorbs the heat to be evaporated into gas, and the gas is filled with an inflatable heat conduction film through a gas flowing cavity; the inflatable heat conduction film is expanded to store the gaseous medium, the gaseous medium is dissipated when the smoke temperature is low, the gaseous medium is condensed into liquid after heat dissipation, then the liquid is absorbed by the liquid absorption core plate and returns to the medium storage cavity, and therefore heat transfer and buffering are facilitated, and damage of thermal shock to device parts is reduced.

The invention discloses a modeling method and device for a soft measurement model of the flue gas oxygen content of a gas turbine, and the modeling method comprises the following steps: obtaining multi-source operation data of the gas turbine, including a gas turbine combustion chamber pressure pulsation original signal, an operation parameter and an environment parameter; carrying out time-frequency domain feature extraction on the pressure pulsation original signal to obtain a time domain statistical feature and a frequency domain spectrum feature, fusing the time domain statistical feature and the frequency domain spectrum feature with the operation parameters and the environment parameters, and then screening key input variables through variable importance analysis; constructing a cascade hybrid model based on the screened key input variables; and jointly optimizing model parameters of a time sequence feature learning layer, a static feature mapping layer and a dynamic fusion layer in the hybrid model through a gradient descent method until the model converges, and generating a soft measurement model capable of outputting an effective flue gas oxygen content predicted value.

Provided are equipment and methods for intelligent mobile medical waste disposal and flue gas purification, and the equipment includes a vehicle-mounted mobile platform and a skid-mounted standard container; where, the vehicle-mounted mobile platform is composed of a standard semi-trailer truck and a truck carriage base; the vehicle-mounted mobile platform is used for realizing functions of mobile transportation, cargo loading, fuel loading and unloading, power charging and discharging and network information transmission; the skid-mounted standard container is loaded above the truck carriage base of the vehicle-mounted mobile platform; and the skid-mounted standard container consists of a standard container and contents in the standard container; and the contents include: an intelligent collection and transportation feeding system, a medical waste pyrolysis incineration system, an incineration flue gas purification system, and an intelligent management and control system for medical waste disposal.

The invention discloses a precise ammonia spraying system suitable for SNCR denitration, and relates to the technical field of ammonia spraying devices for SNCR denitration, the precise ammonia spraying system comprises a top cover fixedly mounted at the top of a boiler cyclone separator barrel, and a reciprocating pushing mechanism is mounted on the outer wall, located on the outer side of a spray gun, of the boiler cyclone separator barrel; and supporting cylinders which are distributed at equal intervals are fixed on the inner wall, close to the spray gun, of the boiler cyclone separator cylinder body. According to the precise ammonia spraying system suitable for SNCR denitration, the sleeve used for dispersing ammonia sprayed by the spray gun can rapidly rotate and transversely move, dead angles in the spraying process can be reduced, the ammonia is evenly distributed in the boiler cyclone separator barrel, mixing of the ammonia and flue gas is promoted, the working efficiency of the ammonia spraying system is improved, and the service life of the ammonia spraying system is prolonged. Moreover, the sleeve can generate slight vibration during rotation, dust particles in the through holes are vibrated off, the service life of the sleeve is prolonged, meanwhile, gas can be helped to form finer fog drops during spraying, ammonia gas can be better diffused conveniently, and the flue gas reaction efficiency is improved.

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 relates to an SCR system self-adaptive flow guide regulation and control method based on real-time flow field feedback, and belongs to the technical field of flue gas denitration. The method comprises the following steps: acquiring inlet flue gas flow velocity distribution and outlet partition NOx concentration distribution; establishing a flow field and concentration field uniformity online evaluation rule, and constructing an initial knowledge base based on adaptive regulation and control logic; dynamically adjusting the angle of the adjustable guide plate according to the uniformity evaluation result, synchronously recording the state change of the flow field, and iteratively updating the regulation and control knowledge base; and an exclusive data interaction link of diversion regulation and control and partition ammonia spraying control is established, and flow field pre-judgment information sharing and ammonia spraying parameter presetting are achieved. The real-time collaborative optimization of the flow field and the concentration field in the SCR system is realized, the denitration efficiency and the ammonia escape control precision are improved, and the self-adaption and intelligent regulation and control capabilities of the system are enhanced.