Oxygen regulation method and system for oxygen-enriched combustion system

Abstract

The present application relates to the technical field of industrial furnace intelligent regulation, and particularly relates to an oxygen regulation method and system for an oxygen-enriched combustion system. The method comprises the following steps: obtaining limited measurement point operation data and fuel feeding state data of an oxygen-enriched combustion furnace; performing furnace space measurement point scope matching according to the limited measurement point operation data to obtain furnace space correlation data; positioning a fuel reaction interval in combination with the fuel feeding state data to obtain fuel reaction interval data; performing oxygen consumption space backstepping according to the limited measurement point operation data, the furnace space correlation data and the fuel reaction interval data to obtain furnace oxygen consumption distribution data; identifying local oxygen deficiency risk based on the furnace oxygen consumption distribution data to obtain local oxygen deficiency risk data; and generating partitioned oxygen supply control data according to the local oxygen deficiency risk data. The present application can improve the local oxygen deficiency risk identification accuracy and the oxygen regulation pertinence under the condition of limited measurement points, and reduce excessive oxygen supply and insufficient combustion.

Description

Technical Field

[0001] This invention relates to the field of intelligent regulation technology for industrial furnaces and kilns, and in particular to an oxygen distribution regulation method and system for an oxygen-enriched combustion system. Background Technology

[0002] Existing oxygen-enriched combustion systems mostly employ fixed oxygen concentration thresholds or total oxygen supply regulation for control. Controllers typically adjust the overall oxygen supply based on data from a limited number of measuring points, making it difficult to generate zoned control parameters according to the oxygen consumption differences in different furnace spatial units. Due to the complex coupling relationship between fuel feeding status, furnace spatial structure, and the measuring point's domain of action, traditional control methods are prone to problems such as failure to promptly identify localized oxygen deficiency, mismatch between control commands and actual oxygen-deficient areas, and lack of spatial targeting in actuator adjustments. Summary of the Invention

[0003] To address the aforementioned technical problems, this invention proposes an oxygen distribution adjustment method and system for an oxygen-enriched combustion system, thereby resolving at least one of the aforementioned technical problems.

[0004] This application provides a method for oxygen distribution adjustment in an oxygen-enriched combustion system, comprising the following steps: S1. Obtain limited measurement point operation data and fuel feeding status data of the oxygen-enriched combustion furnace; S2. Match the domain of measurement points in the furnace space based on the limited measurement point operation data to obtain furnace space correlation data; S3. Based on the fuel feeding status data and furnace space correlation data, locate the fuel reaction zone and obtain the fuel reaction zone data; S4. Based on the limited measurement point operation data, furnace space correlation data and fuel reaction zone data, oxygen consumption spatial back-inference is performed to obtain furnace oxygen consumption distribution data; S5. Based on the oxygen consumption distribution data in the furnace, identify the risk of local oxygen deficiency and obtain local oxygen deficiency risk data; S6. Generate the basis for zonal oxygen allocation adjustment based on local hypoxia risk data to obtain zonal oxygen allocation control data.

[0005] This invention integrates the limited measurement point operation data of the oxygen-enriched combustion furnace, fuel feeding status data, and the spatial correlation of the furnace into the same control link, so that the controller no longer relies solely on a single oxygen concentration threshold or total oxygen supply for coarse adjustment. By matching the measurement point's domain of action and locating the fuel reaction interval, a calculable state observation basis can be established for different spatial units of the furnace. Through spatial back-calculation of oxygen consumption and identification of local oxygen deficiency risks, discrete measurement point signals are transformed into spatially directional oxygen consumption distributions and risk states. Based on this result, zoned oxygen distribution control data is generated, enabling the matching of execution parameters such as oxygen flow rate, valve opening, nozzle opening / closing, or oxygen supply ratio with specific risk areas. This improves the adaptive capability, closed-loop response accuracy, and operational stability of oxygen distribution control, reducing control lag, local oxygen deficiency, and overall excessive oxygen supply problems.

[0006] Optionally, S1 specifically refers to: S11. Collect temperature data, oxygen concentration data, flue gas composition data and furnace pressure data through preset measurement points in the oxygen-enriched combustion furnace, and integrate them to obtain limited measurement point operation data. S12. Acquire data on fuel feed rate, feed start / stop status, feed rate, fuel feed location, fuel moisture content, fuel particle size distribution, and fuel lower heating value, and integrate them to obtain fuel feed status data.

[0007] This invention collects temperature, oxygen concentration, flue gas composition, and furnace pressure data by setting up measuring points. This provides the controller with multi-dimensional feedback signals reflecting furnace thermal state, oxygen supply state, changes in combustion products, and pressure disturbances, avoiding control judgment errors caused by relying solely on a single oxygen concentration parameter for oxygen distribution control. Simultaneously, integrating fuel feed rate, feed location, moisture content, particle size distribution, and lower heating value into fuel feed state data allows the control system to synchronously perceive changes in fuel-side load, heat release capacity, and potential oxygen consumption demand. The resulting input data covers both furnace operation feedback and fuel disturbance sources, providing a stable data foundation for subsequent spatial measuring point domain matching, oxygen consumption back-calculation, and generation of zoned oxygen distribution control parameters, thus improving the adaptability and closed-loop control accuracy of oxygen-enriched combustion oxygen distribution regulation.

[0008] Optionally, S2 specifically refers to: S21. Obtain furnace structure data and divide the space according to the furnace structure data to obtain furnace space data; S22. Obtain the data of the deployed measuring points, and process the measuring point scope based on the data of the deployed measuring points to obtain the measuring point scope data. S23. Perform measurement point correlation on furnace space data and measurement point action area data to obtain measurement point correlation data; S24. Based on the correlation data of measuring points and the operation data of limited measuring points, spatial observation is constructed to obtain the correlation data of furnace space.

[0009] This invention utilizes spatial division based on furnace structure data to transform the continuous and complex internal furnace space into recognizable and calculable spatial units for the controller, providing a clear target for zoned control. By processing the measurement point domains based on the deployed measurement point data, the effective observation range and influence boundaries of each measurement point for different furnace spatial units can be determined, preventing the control system from simply equating local measurement point signals with the overall furnace state. Through measurement point association and spatial observation construction, the operating data of a limited number of measurement points can be mapped to corresponding spatial units, forming spatially directional furnace spatial association data. Therefore, the controller can generate subsequent oxygen consumption back-calculation and oxygen distribution control basis based on the observation reliability and state differences of different regions, improving the state perception capability, parameter generation accuracy, and closed-loop regulation stability of zoned oxygen distribution control.

[0010] Optionally, the space observation construction is specifically as follows: S241. Based on the measurement point association data, the measurement points are divided into layers to obtain the measurement point layer data; S242. Extract the measurement point response features from the limited measurement point operation data to obtain the measurement point response feature data; S243. Based on the layered data of the measuring points and the response characteristic data of the measuring points, the observation reliability is evaluated to obtain the observation reliability data; S244. Based on the furnace structure data, the observation reliability data is corrected for observation transfer to obtain spatial observation transfer data. S245. Based on the layered data of measuring points, the observation reliability data, and the spatial observation transmission data, spatial observation configuration is performed to obtain the furnace space correlation data.

[0011] This invention employs a hierarchical approach to the data from interconnected measurement points, enabling the controller to differentiate the roles of primary, auxiliary, and boundary measurement points in furnace spatial observation and preventing the equal processing of signals from different points. Extracting response characteristics from the limited measurement point operational data reflects the sensitivity of temperature, oxygen concentration, flue gas composition, and pressure to changes in combustion state. Combining the measurement point hierarchy with observation reliability assessment reduces the interference of abnormal fluctuations and weak responses from measurement points on control decisions. By using furnace structure data to correct the observation reliability, spatial observation results conform to furnace structure, flow channels, and zone boundary constraints. The resulting furnace spatial correlation data provides more reliable state input for oxygen consumption estimation and the generation of zoned oxygen distribution parameters, improving the control system's anti-interference capability, spatial perception accuracy, and closed-loop regulation stability.

[0012] Optionally, S3 specifically refers to: S31. Determine the fuel distribution based on the fuel feeding status data and furnace space correlation data to obtain fuel distribution data; S32. Determine the fuel stage based on furnace space correlation data and fuel distribution data to obtain fuel stage data; S33. Based on the furnace space correlation data, fuel distribution data, and fuel stage data, the reaction position is mapped to obtain the reaction position data; S34. Perform reaction domain convergence processing based on the reaction location data to obtain fuel reaction interval data.

[0013] This invention combines fuel feeding status data with furnace space correlation data, enabling the controller to obtain the fuel distribution status in different furnace space units, avoiding oxygen allocation judgment based solely on the feed port or total feed amount. By determining the fuel's reaction stage based on spatial observation and fuel distribution results, differences in processes such as drying, volatilization, ignition, combustion, and burnout can be transformed into state information recognizable by the control system. Through reaction location mapping and reaction domain convergence processing, scattered fuel reaction locations can be organized into relatively stable fuel reaction intervals. Therefore, subsequent oxygen consumption estimation and generation of zoned oxygen allocation control parameters can be based on the actual fuel reaction area, improving the matching accuracy between control commands and oxygen consumption requirements, and enhancing the spatial targeting and closed-loop control stability of oxygen allocation adjustment.

[0014] Optionally, the reaction domain convergence processing specifically includes: S341. Based on the reaction location data, the reaction seed units are screened to obtain the reaction seed unit data; S342. Perform stage similarity neighborhood expansion on the reaction seed unit data to obtain neighborhood expansion data; S343. Perform a reaction continuity check on the neighborhood expansion data to obtain continuous active domain data; S344. Weak response boundaries are removed based on continuous active domain data to obtain effective active domain data; S345. Encapsulate the effective active domain data into active domain intervals to obtain fuel reaction interval data.

[0015] This invention, by screening reaction seed units from reaction location data, can identify core control reference regions with clear reaction characteristics and strong oxygen consumption response for the controller, avoiding the misuse of transient disturbances or measurement point noise as the basis for oxygen allocation. Neighborhood expansion based on fuel stage similarity allows spatial units at similar combustion stages to be included in the same control analysis range, ensuring continuity and process consistency within the fuel reaction interval. Through reaction continuity verification and weak response boundary elimination, spurious expansion regions can be compressed, reducing the interference of weak boundary responses on control parameter generation. The encapsulated fuel reaction interval data provides stable boundaries for subsequent oxygen consumption back-calculation and zoned oxygen allocation correction, enabling oxygen allocation control commands to more accurately correspond to the actual fuel reaction region, improving the spatial positioning accuracy and closed-loop regulation reliability of the control system.

[0016] Optionally, S4 specifically refers to: S41. Based on the limited measurement point operation data, the combustion response is extracted to obtain the combustion response data; S42. Perform combustion response mapping based on combustion response data and furnace space correlation data to obtain combustion response mapping data; S43. Based on the fuel reaction range data, the combustion response mapping data is corrected to obtain the space oxygen consumption data; S44. Perform oxygen consumption interpolation on the space oxygen consumption data to obtain the implicit oxygen consumption unit data. S45. The spatial oxygen consumption data and the implicit oxygen consumption unit data are fused to obtain the furnace oxygen consumption distribution data.

[0017] This invention extracts combustion response data from limited measurement point operating data, transforming temperature changes, oxygen concentration decay, flue gas composition fluctuations, and furnace pressure disturbances into oxygen consumption characterization signals usable by the controller. Combustion response mapping, combined with furnace spatial correlation data, maps discrete measurement point responses to specific furnace spatial units, establishing spatialized state inputs for zonal control. Reaction correction of the mapping results using fuel reaction interval data highlights the oxygen consumption contribution of the actual fuel reaction area, reducing the impact of non-reaction disturbances on control decisions. Subsequent interpolation of spatial oxygen consumption data supplements the implicit oxygen consumption state in areas not covered by the measurement points. The fused furnace oxygen consumption distribution data provides a precise basis for the controller to generate zonal oxygen distribution correction values, improving the spatial accuracy, response consistency, and closed-loop regulation stability of oxygen distribution control.

[0018] Optionally, S5 specifically refers to: S51. Calculate the oxygen consumption concentration based on the furnace oxygen consumption distribution data to obtain oxygen consumption concentration data; S52. Based on the furnace oxygen consumption distribution data and furnace space correlation data, conduct an oxygen supply accessibility assessment to obtain oxygen supply accessibility data. S53. Identify the mismatch between oxygen consumption and demand by analyzing the accumulated oxygen consumption data and the oxygen supply accessibility data to obtain oxygen supply imbalance data. S54. Determine the hypoxia precursor data from the oxygen supply imbalance data to obtain hypoxia precursor data. S55. Identify the risk spread trend based on hypoxia precursor data to obtain hypoxia risk diffusion data; S56. Based on the data on oxygen supply imbalance, hypoxia precursors, and hypoxia risk diffusion, local hypoxia risk data are obtained.

[0019] This invention calculates oxygen concentration based on furnace oxygen consumption distribution data, enabling the controller to identify high-oxygen-consuming spatial units and continuous oxygen-consuming areas, thus clarifying the key targets for oxygen distribution regulation. By combining furnace space correlation data with oxygen supply accessibility assessment, the oxygen supply capacity of existing oxygen supply channels, nozzle ranges, or zone loops for corresponding areas can be determined, avoiding the generation of control commands solely based on oxygen consumption intensity. By identifying oxygen supply imbalance states through oxygen consumption concentration data and oxygen supply accessibility data, and determining precursors and risk propagation trends of oxygen deficiency, localized oxygen deficiency can be transformed from a reactive alarm to a feedforward control basis. The resulting localized oxygen deficiency risk data can simultaneously characterize the risk location, risk identifier, and diffusion direction, improving the predictive ability, response accuracy, and closed-loop operation stability of oxygen distribution control.

[0020] Optionally, S6 specifically refers to: S61. Determine the spatial units to be adjusted based on local hypoxia risk data, and obtain the data of the areas to be oxygenated; S62. Obtain oxygen supplementation configuration data, and match it with the data of the area to be supplemented with oxygen and the oxygen supplementation configuration data to obtain oxygen supplementation execution association data; S63. Calculate the zonal oxygenation correction amount based on the local hypoxia risk data and the oxygenation execution correlation data to obtain the zonal oxygenation correction data. S64. Generate oxygen distribution control parameters based on the zoned oxygen distribution correction data to obtain zoned oxygen distribution control data.

[0021] This invention determines the adjustable spatial units based on localized hypoxia risk data, enabling the controller to limit oxygen distribution to specific risk areas rather than uniformly adjusting the oxygen supply to the entire furnace. By matching this with supplemental oxygen configuration data, the execution correspondence between the areas requiring oxygen distribution and oxygen nozzles, regulating valves, zoned air ducts, or oxygen supply circuits can be clearly defined, avoiding inconsistencies between control parameters and the actual effective range. Subsequently, based on the risk level, diffusion trend, and the correlation between oxygen distribution execution, the zoned oxygen distribution correction amount is calculated, ensuring that the supplemental oxygen range is adapted to localized oxygen consumption demands and execution capabilities. The generated zoned oxygen distribution control data can be directly used to adjust oxygen flow rate, valve opening, nozzle opening / closing, or oxygen supply ratio, improving the execution accuracy, closed-loop response efficiency, and zoned regulation stability of the control system.

[0022] Optionally, this application also provides an oxygen-enriched combustion system oxygen distribution regulation system for performing the oxygen-enriched combustion system oxygen distribution regulation method described above, wherein the oxygen-enriched combustion system oxygen distribution regulation includes: The oxygen-enriched combustion furnace data acquisition module is used to acquire limited measurement point operating data and fuel feeding status data of the oxygen-enriched combustion furnace. The furnace space measuring point scope matching module is used to match the furnace space measuring point scope based on the limited measuring point operation data to obtain furnace space associated data. The fuel reaction zone positioning module is used to locate the fuel reaction zone based on fuel feeding status data and furnace space correlation data, and obtain fuel reaction zone data. The oxygen consumption spatial back-calculation module is used to perform oxygen consumption spatial back-calculation based on limited measurement point operating data, furnace space correlation data and fuel reaction zone data to obtain furnace oxygen consumption distribution data. The local hypoxia risk identification module is used to identify local hypoxia risk based on furnace oxygen consumption distribution data and obtain local hypoxia risk data. The zoned oxygen distribution adjustment basis generation module is used to generate zoned oxygen distribution adjustment basis based on local hypoxia risk data, and obtain zoned oxygen distribution control data.

[0023] The beneficial effects of this invention are as follows: It uses limited measurement point operating data and fuel feeding status data of an oxygen-enriched combustion furnace as the basis for control input. Instead of relying solely on empirical adjustments based on a single oxygen concentration measurement point or total oxygen supply, it incorporates data such as temperature, oxygen concentration, flue gas composition, furnace pressure, fuel feed rate, feed location, moisture content, particle size, and lower heating value into a unified automatic control analysis chain. Through furnace space measurement point domain matching, limited measurement point signals can be mapped to specific furnace space units, forming a spatially directional furnace status observation basis. Furthermore, combined with fuel feeding status to locate the fuel reaction zone, the controller can identify actual high oxygen consumption reaction areas, avoiding a disconnect between the controlled object and the fuel reaction location. By reverse-engineering oxygen consumption space to form furnace oxygen consumption distribution data and identifying local oxygen deficiency risks, discrete measurement point feedback can be transformed into control state quantities such as oxygen consumption intensity, oxygen supply imbalance location, oxygen deficiency precursors, and risk diffusion trends. Based on the risk of localized oxygen deficiency, zoned oxygen distribution control data is generated, ensuring that oxygen flow rate, valve opening, nozzle opening and closing, or zoned oxygen supply ratio are matched with specific risk areas and the effective range of actuators. This improves the state perception accuracy, zoned control targeting, and closed-loop regulation stability of the oxygen-enriched combustion system, reducing problems such as control lag, localized oxygen deficiency, incomplete combustion, and overall excessive oxygen supply. Attached Figure Description

[0024] Other features, objects, and advantages of this application will become more apparent from the following detailed description of the non-limiting embodiments, taken with reference to the accompanying drawings: Figure 1 A flowchart illustrating the steps of an oxygen-enriched combustion system oxygen distribution adjustment method according to an embodiment is shown. Figure 2 A flowchart illustrating the steps of a furnace space measuring point domain matching method according to an embodiment is shown. Figure 3 A flowchart illustrating the steps of a fuel reaction zone location method according to one embodiment is shown. Figure 4A flowchart illustrating the steps of an embodiment of a spatial back-calculation method for oxygen consumption is shown. Figure 5 A flowchart illustrating the steps of a method for identifying the risk of local hypoxia according to one embodiment is shown. Figure 6 A flowchart illustrating the steps of a method for generating a regional oxygen allocation regulation basis according to an embodiment is shown. Detailed Implementation

[0025] The technical method of the present invention will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without inventive effort are within the scope of protection of the present invention.

[0026] Furthermore, the accompanying drawings are merely illustrative of the invention and are not necessarily drawn to scale. Functional entities can be implemented in software, in one or more hardware modules or integrated circuits, or in different network and / or processor methods and / or microcontroller methods.

[0027] It should be understood that although the terms "first," "second," etc., may be used herein to describe various units, these units should not be limited by these terms. These terms are used merely to distinguish one unit from another. For example, without departing from the scope of the exemplary embodiments, a first unit may be referred to as a second unit, and similarly, a second unit may be referred to as a first unit. The term "and / or" as used herein includes any and all combinations of one or more of the associated listed items.

[0028] An industrial oxygen-enriched combustion furnace with a rated capacity of 50t / h to 100t / h is equipped with 12 temperature measuring points, 8 oxygen concentration measuring points, 6 CO measuring points, 4 pressure measuring points, and 4 flue gas velocity measuring points, with a sampling period of 30s. The system divides the furnace into 48 furnace space units along the height, width, and combustion flow directions, and matches the limited measuring point data to the corresponding space units based on the measuring point installation position, effective radius of action, and furnace obstruction relationship.

[0029] At a certain operating moment, the system detected several spatial units near the second feed port exhibiting phenomena such as increased temperature, decreased residual oxygen concentration, and increased CO concentration. Specifically, the residual oxygen concentration decreased from 6.2% in the previous sampling period to 3.1%, and the CO concentration increased to 620 ppm, with the corresponding fuel feed rate consistently greater than 0. Based on this, the system located the fuel reaction zone and calculated the oxygen consumption intensity by combining the oxygen concentration changes and flue gas velocity from adjacent sampling periods. When the oxygen consumption intensity in this area reached 1.35 times the historical average under stable operating conditions, and the residual oxygen concentration was below 4%, the system identified it as a localized oxygen deficiency risk area.

[0030] The system matches the oxygen regulating valve and combustion air valve of the second execution zone according to the spatial unit number corresponding to the local hypoxia risk area, and generates oxygen distribution control data for the zone, setting the oxygen flow rate setpoint of the execution zone from 1200 Nm³. 3 / h increased to 1320Nm 3 The oxygen supply was increased by 10% per hour, while maintaining no increase in oxygen supply to adjacent low-risk zones. After three sampling cycles, the residual oxygen concentration in the risk area recovered to 4.8%, and the CO concentration decreased to 320 ppm, thus eliminating the risk of local hypoxia. In this way, the system can deduce the local oxygen consumption distribution under limited measurement points and transform the overall oxygenation method into zoned oxygen allocation regulation for risk areas, improving the stability of the oxygen-enriched combustion process.

[0031] Please see Figures 1 to 6 This application provides a method for adjusting the oxygen distribution in an oxygen-enriched combustion system, comprising the following steps: S1. Obtain limited measurement point operation data and fuel feeding status data of the oxygen-enriched combustion furnace; In one embodiment, the system collects limited operational data from temperature, oxygen concentration, CO concentration, furnace pressure, and flue gas velocity measurement points already deployed within the furnace, denoted as... ,in Let i be the installation position of the i-th measuring point in the furnace space. For measuring the temperature, Oxygen concentration, CO concentration, For furnace pressure, Let t be the flue gas velocity and t be the sampling time. For measurement point sequence number, The number of measuring points. The system synchronously acquires fuel feeding status data, denoted as... ,in Let j be the fuel feed rate at the j-th feed port. This indicates the material feeding start / stop status. For the feeding rate, For the location of the feed inlet, Here is the feed port sequence number, and t is the sampling time. This refers to the number of feed inlets.

[0032] S2. Match the domain of measurement points in the furnace space based on the limited measurement point operation data to obtain furnace space correlation data; In one embodiment, the system is based on a pre-defined set of spatial units in the furnace structure: ,in Let l be the k-th furnace space unit, and l be the number of space units. spatial unit The geometric center or preset control center. The system calculates the position of the measuring point. With the center position of the space unit Spatial distance: ,when When matching the i-th measuring point to the k-th furnace space unit, the set of matching measuring point numbers is used to obtain the associated measuring point number, and the corresponding spatial distance is regarded as the effective distance. The effective radius of the i-th measuring point is denoted in advance based on the measuring point type, installation location, and the obstruction range of the furnace structure. The system aggregates the measuring point data matched within the same spatial unit according to the sampling time t to form the spatial unit operating status: , This represents the operating state of the k-th furnace space unit at sampling time t. Let be the temperature value of the i-th measuring point at sampling time t. Let be the oxygen concentration value at the i-th measuring point at sampling time t. Let be the CO concentration value at the i-th measuring point at sampling time t. Let be the furnace pressure value at the i-th measuring point at sampling time t. Let k be the flue gas velocity value at the i-th measuring point at sampling time t, and encapsulate the spatial unit number k, the associated measuring point number, the action distance, and the spatial unit operating status into furnace space associated data.

[0033] The measurement point type, installation location, and furnace structure obstruction range are pre-calibrated. Specifically, the system determines the foundation radius of action according to the measurement point type. The basic radius of action for temperature measuring points is set at 0.8m, for oxygen concentration measuring points at 1.0m, for CO concentration measuring points at 1.0m, for furnace pressure measuring points at 1.5m, and for flue gas velocity measuring points at 1.0m. The system then adjusts the basic radius of action based on the measuring point installation location: when the measuring point installation depth is less than 10% of the furnace width, [the radius is adjusted accordingly]. Multiply by 0.7; when the installation depth is equal to the width of the furnace chamber. At that time, Multiply by 0.85; when the installation depth is greater than 30% of the furnace width, maintain... Unchanged. If the measuring point is located at a furnace corner, behind the burner nozzle, or near a protruding structure on the furnace wall, and the angle between it and the target spatial unit is greater than... Then multiply by 0.6. The system performs a secondary correction based on the furnace structure's obstruction range: when the measuring point position With the center position of the space unit If there are partition walls, baffles, material bed accumulation areas, or burner body obstructions, and the obstruction height exceeds 30% of the connection line height, the effective radius in the corresponding direction is multiplied by 0.5; if the obstruction height exceeds 60% of the connection line height, the effective radius in the corresponding direction is multiplied by 0.3; if the obstruction height exceeds 80% of the connection line height, it is determined that the measuring point has no effective domain for this spatial unit, and no matching relationship is established. The system obtains the effective effective radius: ,in This is the installation location correction factor, with values ​​of 0.7, 0.85, or 1.0. This is the occlusion correction factor, with values ​​of 0.3, 0.5, 0.6, or 1.0. When... If no invalid occlusion condition is triggered, the i-th measurement point is matched to the k-th furnace space unit.

[0034] S3. Based on the fuel feeding status data and furnace space correlation data, locate the fuel reaction zone and obtain the fuel reaction zone data; In one embodiment, the system uses fuel feed status data. Feed port position Feed rate Feeding start / stop status and feeding rate The j-th feed port is mapped to the furnace space element set U. The system calculates the feed port position. With the center position of the space unit Distance: ,when ( The value is taken as 1m (the specific value can be determined according to expert knowledge or experience data). (When the feeding start / stop state is the feeding start state), the k-th furnace space unit is determined as the fuel influence unit of the j-th feed port, where The system determines the fuel diffusion distance at the j-th feed port. The system then retrieves the spatial unit operating status from the furnace space association data. Read the average temperature value corresponding to the space unit. Average oxygen concentration value Average CO concentration and flue gas velocity value When the spatial unit satisfies , , ( =750℃, =4%, =200ppm (the specific value can be determined based on expert knowledge or experience data), and corresponds to the feed port. , At that time, the spatial unit is marked as a candidate unit for fuel reaction. The reaction temperature threshold. The oxygen concentration consumption threshold, A CO generation threshold is set. The system merges consecutively adjacent fuel reaction candidate units to form a fuel reaction region. ,in The system assigns the spatial unit numbers to the h-th fuel reaction zone as follows: , Let h be the k-th furnace space unit, and let h be the fuel reaction interval number and h be the corresponding space unit number set. The corresponding feed port number j, the reaction determination time t, and the reaction state data. Encapsulated as fuel reaction range data Among them, reaction state data Includes spatial unit number set Representative temperature of each space unit , representing oxygen concentration , representing CO concentration , representing the flue gas velocity And the feed rate at the corresponding feed port. Feeding start / stop status and feed rate .

[0035] In one embodiment, the system uses fuel feed status data. Feed port position Feed rate Feeding start / stop status and feeding rate Combined with the spatial unit center position in the furnace space correlation data and the operating status of space units Determine the fuel-affected units and, based on the representative temperature of the space unit. , representing oxygen concentration , representing CO concentration and represents the flue gas velocity Determine the fuel reaction stage and obtain the fuel stage identifier. The system will be located at the center of the space unit where the activation combustion phase or the oxygen-deficient reaction phase is taking place. The reaction positions are recorded, and based on the adjacency relationship between furnace space units, consecutively adjacent reaction positions corresponding to the same feed port number j are merged to form a fuel reaction zone. The system assigns the fuel reaction zone number h and the spatial unit number set. Fuel reaction zone , corresponding feed port number j, reaction determination time t, and set of fuel stage identifiers within the interval and reaction state data Encapsulated as fuel reaction range data: ,in Among them, reaction state data Includes spatial unit number set Representative temperature of each space unit , representing oxygen concentration , representing CO concentration , representing the flue gas velocity And the feed rate at the corresponding feed port. Feeding start / stop status and feed rate .

[0036] S4. Based on the limited measurement point operation data, furnace space correlation data and fuel reaction zone data, oxygen consumption spatial back-inference is performed to obtain furnace oxygen consumption distribution data; In one embodiment, the system operates based on data from a limited number of measurement points. The system uses furnace space correlation data and fuel reaction zone data to perform spatial back-calculation of oxygen consumption. It reads the representative oxygen concentration of the k-th furnace space unit at the current sampling time t from the furnace space correlation data. , representing CO concentration and represents the flue gas velocity and the spatial unit operating state from the previous sampling time. Reading the oxygen concentration ,in This represents the sampling interval between adjacent sampling times. The system determines the set of spatial unit numbers corresponding to the h-th fuel reaction interval based on the fuel reaction interval data: ,in Let be the set of spatial cell numbers corresponding to the h-th fuel reaction interval at sampling time t. For The spatial unit is used to calculate the decrease in oxygen concentration: ,when , and When this occurs, it is determined that the space unit has effective oxygen consumption, and the oxygen consumption intensity is calculated: ,in Let k be the oxygen consumption intensity of the k-th furnace space unit at sampling time t. The system assigns the space unit number k, the fuel reaction interval number h, and the oxygen concentration decrease amount... Oxygen consumption intensity The sampling time t is packaged into furnace oxygen consumption distribution data: .

[0037] S5. Based on the oxygen consumption distribution data in the furnace, identify the risk of local oxygen deficiency and obtain local oxygen deficiency risk data; In one embodiment, the system is based on furnace oxygen consumption distribution data. Local hypoxia risk identification is performed. The system reads the oxygen concentration decrease of the k-th furnace space unit at sampling time t. and oxygen consumption intensity It also retrieves the representative oxygen concentration of the corresponding spatial unit from the furnace space correlation data. and represent CO concentration When the following conditions are met: At that time, the system marks the k-th furnace space unit as a unit with local oxygen deficiency risk. The oxygen concentration threshold for hypoxia risk is set at 2%. The oxygen consumption intensity threshold is taken as 1.2 times the average oxygen consumption intensity under historical stable combustion conditions. The CO concentration threshold associated with hypoxia is set to 300 ppm. The system denotes the set of spatial unit numbers that meet the hypoxia risk conditions as follows: ,in Sampling time The system assigns a set of unit numbers to areas of localized oxygen deficiency risk. Based on the adjacency relationships between furnace space units, the system... Consecutive adjacent risk units merge to form localized hypoxia risk areas: ,in For the first A set of spatial unit numbers corresponding to a region of local hypoxia risk. The system assigns numbers to areas at risk of localized hypoxia. Spatial Unit Numbering Set Fuel reaction zone number h, oxygen concentration decrease Oxygen consumption intensity , representing oxygen concentration , representing CO concentration The risk assessment time t is packaged into local hypoxia risk data: ,in This data represents the risk of localized hypoxia.

[0038] S6. Generate the basis for zonal oxygen allocation adjustment based on local hypoxia risk data to obtain zonal oxygen allocation control data.

[0039] In one embodiment, the system is based on local hypoxia risk data. Generate zoned oxygen distribution control data. The system reads the set of spatial unit numbers corresponding to the g-th local hypoxia risk zone. And obtain the representative oxygen concentration of each spatial unit. Oxygen consumption intensity , representing CO concentration And the fuel reaction zone number h. The system is based on the oxygen concentration threshold for the risk of oxygen deficiency. Calculate the oxygen demand index for the k-th spatial unit: ,when season The system sums the oxygen demand indices of each spatial unit within the same local hypoxia risk area to obtain the regional oxygen demand index: ,in This represents the oxygen demand index for the g-th local hypoxia risk area. The system calls the preset oxygen allocation execution partition mapping table: ,in This is an oxygen distribution execution zone mapping table. An execution zone refers to a control area in an oxygen-enriched combustion furnace controlled by one or more oxygen inlets, oxygen regulating valves, combustion air valves, or fuel coordination regulating mechanisms. It is used to convert local oxygen deficiency risk areas into executable oxygen distribution regulation objects. Each execution zone corresponds to at least one furnace space unit and is mapped to the corresponding oxygen flow regulating valve, oxygen inlet, or combustion air regulating mechanism. c is the execution zone number, and k is the space unit number. To perform partitioning The corresponding oxygen nozzle, oxygen regulating valve, or combustion air valve number. The preset oxygen distribution execution zone mapping table is established by the system before commissioning based on the furnace structure, spatial unit division results, and the layout of the oxygen actuators. The system obtains the installation location, injection direction, rated flow range, and control loop number of the oxygen nozzle, oxygen regulating valve, and combustion air valve, and calculates the distance and injection angle between each nozzle and the center of the spatial unit. When the center of the spatial unit is within the effective oxygen supply distance and effective injection angle range of the nozzle, a mapping relationship is established between the spatial unit and the corresponding oxygen nozzle, oxygen regulating valve, or combustion air valve, forming the preset oxygen distribution execution zone mapping table. .

[0040] The system according to Query the corresponding execution partition number And the regional oxygen demand index Convert to oxygen flow rate setting increment for the execution partition . ,in To perform partitioning Current oxygen flow rate setting To perform partitioning The upper limit of oxygen flow rate, Set a conversion factor for the incremental change from the oxygen demand index to the oxygen flow rate. This is the function that takes the minimum value. When Any spatial unit within the space satisfies and Not less than At that time, the system sets a priority oxygen allocation indicator: During oxygen distribution adjustment, the system prioritizes adjusting the oxygen nozzle, oxygen regulating valve, or combustion air valve corresponding to the execution zone; otherwise: The system is based on the regional oxygen demand index. Adjust in descending order; if multiple execution partitions... If they are the same, then follow the partition number. Adjust in ascending order, among which... To perform partitioning Priority oxygen allocation identifier. The system will execute partition numbering. Local hypoxia risk area number g, fuel reaction zone number h, regional oxygen demand index Oxygen flow rate setting increment Priority oxygen supply sign The generation time t is encapsulated as zoned oxygen distribution control data: ,in This is data for zoned oxygen distribution control.

[0041] Optionally, S1 specifically refers to: S11. Collect temperature data, oxygen concentration data, flue gas composition data and furnace pressure data through preset measurement points in the oxygen-enriched combustion furnace, and integrate them to obtain limited measurement point operation data. In one embodiment, the system collects limited operational data from temperature, oxygen concentration, CO concentration, furnace pressure, and flue gas velocity measurement points already deployed within the furnace, denoted as... ,in Let i be the installation position of the i-th measuring point in the furnace space. For measuring the temperature, Oxygen concentration, CO concentration, For furnace pressure, Let t be the flue gas velocity and t be the sampling time. For measurement point sequence number, This represents the number of measurement points.

[0042] S12. Acquire data on fuel feed rate, feed start / stop status, feed rate, fuel feed location, fuel moisture content, fuel particle size distribution, and fuel lower heating value, and integrate them to obtain fuel feed status data.

[0043] In one embodiment, the system synchronously acquires fuel feeding status data, denoted as... ,in Let j be the fuel feed rate at the j-th feed port. This indicates the material feeding start / stop status. For the feeding rate, For feed port location / fuel feed location, Let be the moisture content of the fuel corresponding to the j-th feed port at sampling time t. For fuel particle size distribution, For fuel with low heating value, Here is the feed port sequence number, and t is the sampling time. This refers to the number of feed inlets.

[0044] Optionally, S2 specifically refers to: S21. Obtain furnace structure data and divide the space according to the furnace structure data to obtain furnace space data; In one embodiment, the system acquires furnace structure data, including furnace length, width, height, burner position, flue gas flow direction, furnace wall protrusions, and baffle structures, and divides the space according to the height direction, width direction, and combustion flow direction to obtain furnace space data: ,in A collection of furnace space units. This refers to the k-th furnace space unit, where k is the space unit number. Number of spatial units; system calculation The geometric center or preset control center, denoted as .

[0045] In one embodiment, the system uses the direction from the bottom to the top of the furnace as the height direction, the direction between the furnace walls on both sides as the width direction, and the main direction of flue gas flow or combustion propulsion after fuel entry as the combustion flow direction. Then, based on the furnace structural dimensions, burner arrangement, feed port location, and main flue gas passages, the furnace is divided into several layers along the height direction, several transverse zones along the width direction, and several flow segments along the combustion flow direction. The division can be proportional, or based on proportional division and further subdivision according to structural similarity. For example, by comparing parameters in the design drawings, structural parameters within a small area (within 1m) that are similar (parameter variation rate less than one percent or three percent) are considered the same space. The intersection of each layer, transverse zone, and flow segment forms a furnace space unit. Each furnace space unit together constitutes the furnace space data U. For example, the furnace can be divided along the height direction into the upper burnout zone, the middle main combustion zone, and the lower feeding reaction zone; along the width direction into the left side zone, the middle zone, and the right side zone; and along the combustion flow direction into the inlet section, the reaction section, and the outlet section, thus forming space units.

[0046] S22. Obtain the data of the deployed measuring points, and process the measuring point scope based on the data of the deployed measuring points to obtain the measuring point scope data. In one embodiment, the system acquires data on the deployment of measuring points, including measuring point number, measuring point type, and measuring point installation location. Installation depth, orientation, and effective radius The system calculates the location of the measuring point. With the center position of the space unit Distance: ,when At that time, the spatial unit By incorporating the data into the scope of the i-th measurement point, we obtain the measurement point scope data: ,in Let i be the scope of the i-th measurement point.

[0047] S23. Perform measurement point correlation on furnace space data and measurement point action area data to obtain measurement point correlation data; In one embodiment, the system compares the furnace space data U with the measurement point's domain data. Perform measurement point correlation. When the k-th furnace space unit The scope of the i-th measurement point At that time, the measurement point number i is associated with the spatial unit number k, and the following is obtained: ,in This is the set of associated measurement point numbers corresponding to the k-th furnace space unit.

[0048] S24. Based on the correlation data of measuring points and the operation data of limited measuring points, spatial observation is constructed to obtain the correlation data of furnace space.

[0049] In one embodiment, the system uses measurement point association data. Retrieving operational data from a limited number of measuring points The temperature, oxygen concentration, CO concentration, furnace pressure, and flue gas velocity values ​​at the corresponding measuring points are used to construct the spatial unit's operating status based on the sampling time t. ,in This represents the spatial observation state of the k-th furnace space unit at sampling time t. The system associates the space unit number k with the set of associated measurement point numbers. , action distance set and space observation status Encapsulated as furnace space-related data: .

[0050] Optionally, the space observation construction is specifically as follows: S241. Based on the measurement point association data, the measurement points are divided into layers to obtain the measurement point layer data; In one embodiment, the system uses measurement point association data. The effective distance from the measuring point to the spatial unit And the effective radius of action of the i-th measuring point on the k-th furnace space unit. The associated measurement points of the k-th furnace space unit are layered. When When, measuring point i is divided into core observation measuring points; when At that time, measuring point i is divided into auxiliary observation measuring points to obtain the stratified measuring point data: ,in For the layered data of the measuring points in the k-th furnace space unit, For the core set of observation points, This is a set of auxiliary observation points.

[0051] S242. Extract the measurement point response features from the limited measurement point operation data to obtain the measurement point response feature data; In one embodiment, the system runs data from a limited number of measurement points. Read the temperature value of the i-th measuring point at sampling time t. Oxygen concentration value CO concentration value Furnace pressure value and flue gas velocity value And calculate the change in response at adjacent sampling times: , , , This represents the temperature change between adjacent time points. This is the temperature value from the previous moment. This represents the change in oxygen concentration between adjacent time points. This represents the oxygen concentration value at the previous moment. This represents the change in CO concentration between adjacent time points. This represents the CO concentration value at the previous moment. This represents the sampling interval between adjacent sampling times. The system encapsulates these parameters into measurement point response characteristic data: .

[0052] S243. Based on the layered data of the measuring points and the response characteristic data of the measuring points, the observation reliability is evaluated to obtain the observation reliability data; In one embodiment, the system stratifies data based on measurement points. and measurement point response characteristic data Evaluate the reliability of the initial observations from the i-th measuring point to the k-th furnace space element. When measuring point When there are no missing data, out-of-range, or sudden changes, set When measuring point When there are no missing data, out-of-range, or sudden changes, set When there are missing data, out-of-range measurements, or sudden changes at the measurement points, set... Among them, mutations can be caused by , or determination.

[0053] S244. Based on the furnace structure data, the observation reliability data is corrected for observation transfer to obtain spatial observation transfer data. In one embodiment, the system assesses the reliability of initial observations based on the baffle structure, furnace wall protrusions, burner obstruction positions, and flue gas flow direction in the furnace structure data. Perform observation propagation correction. The system sets the observation propagation correction coefficient. When measuring point i and spatial unit When there is no obstruction between them and they are located in the same flue gas flow channel When the occupancy height is 3 / 4 of the connecting line height hour, When the occlusion height exceeds the connection height hour, The system calculates the reliability of the corrected space observation transmission: ,in To transmit data for space observation.

[0054] S245. Based on the layered data of measuring points, the observation reliability data, and the spatial observation transmission data, spatial observation configuration is performed to obtain the furnace space correlation data.

[0055] In one embodiment, the system stratifies data based on measurement points. Initial observation reliability and the credibility of space observation transmission Filter to meet The measurement point is used as the effective observation point for the k-th furnace space unit. When a valid observation point exists for the core observation point, it is used first. When all core observation points fail, auxiliary observation points are activated. The system constructs the space observation status based on the effective observation points: And the spatial unit number k and the measurement point layer data are divided. Set of associated measurement point numbers Credibility of space observation transmission and space observation status Encapsulated as furnace space-related data: Among them, the measurement point layered data It can be excluded from encapsulation.

[0056] Optionally, S3 specifically refers to: S31. Determine the fuel distribution based on the fuel feeding status data and furnace space correlation data to obtain fuel distribution data; In one embodiment, the system uses fuel feed status data. Feed port position Feed rate Feeding start / stop status and feeding rate And combined with furnace space correlation data The center position of the spatial unit in Calculate the distance between the j-th feed port and the k-th furnace space unit: ,when , , and At that time, the k-th furnace space unit is determined as the fuel influence unit of the j-th feed port, and fuel distribution data is generated: ,in The data represents the fuel distribution at sampling time t. The fuel diffusion determination distance for the j-th feed port can be pre-calibrated based on the feed port injection direction, feed rate range, and furnace size, with a value range of 0.8m. When the furnace width is less than 3m, Take 0.8m; when the furnace width is hour, Take 1.5m; when the furnace width is greater than 8m, Take 3.0m. Within the same furnace size range, if the fuel feed rate is greater than the rated feed rate... ,but Take the upper limit of this range; if the fuel feed rate is less than the rated feed rate. ,but Take the lower limit of the range; otherwise, take the midpoint of the range.

[0057] S32. Determine the fuel stage based on furnace space correlation data and fuel distribution data to obtain fuel stage data; In one embodiment, the system is based on fuel distribution data. Identify spatial units affected by fuel and correlate data from the furnace space. Read the space observation status of the corresponding space unit The system denotes the set of effective observation points for the k-th spatial unit as: ,in For an effective set of observation points, To ensure the reliability of space observations, the system calculates the arithmetic mean of temperature, oxygen concentration, and CO concentration values ​​from the set of valid observation points, yielding: , , ,in , , These represent the representative temperature, representative oxygen concentration, and representative CO concentration of the k-th furnace space unit at sampling time t, respectively. The system makes a stage determination based on these representative states: when... When this occurs, it is determined to be the preheating stage of the space unit; when , and When, it is determined to be the activation and combustion stage of the space unit; when and At that time, it was determined to be the oxygen-deficient reaction stage of the space unit, and the fuel stage data was obtained: ,in This is the fuel stage identifier for the k-th furnace space unit at sampling time t; This is the fuel activation temperature threshold, with a value range of [value missing]. , The threshold value for the oxygen concentration at each stage is [value range missing]. , The threshold value for CO concentration in a given stage is [value range missing]. The threshold value can be pre-calibrated based on fuel type, furnace type, and historical stable operating conditions. When the fuel volatile content is higher than... hour, Take 600℃; when the volatile matter content of the fuel is not higher than hour, Take 900℃. When the target residual oxygen concentration in the oxygen-enriched combustion furnace is higher than... hour, Take 8%; when the target residual oxygen concentration is not higher than hour, Take 4%. When the average CO concentration under historical stable operating conditions is below 200 ppm, Take 200 ppm; when fuel fluctuations are large or the average CO concentration under historically stable operating conditions is not lower than 100 ppm. hour, Take 600 ppm.

[0058] S33. Based on the furnace space correlation data, fuel distribution data, and fuel stage data, the reaction position is mapped to obtain the reaction position data; In one embodiment, the system is based on fuel distribution data. Set of unit numbers affected by fuel extraction: ,in This is the set of fuel-affected unit numbers at sampling time t. The system uses fuel stage data... fuel stage identifier Space units in the activated combustion stage or the oxygen-deficient reaction stage are screened. ,and At that time, the center position of the space unit Record the reaction locations to obtain reaction location data: ,in For reaction location data, To indicate the activation combustion stage, This serves as a marker for the hypoxic response stage. This represents the center position of the k-th furnace space unit.

[0059] S34. Perform reaction domain convergence processing based on the reaction location data to obtain fuel reaction interval data.

[0060] In one embodiment, the system is based on reaction location data. The spatial unit number k and the center position of the spatial unit. Corresponding feed port number j and fuel stage identifier The system performs reaction domain convergence processing. Based on the adjacency relationships between furnace space units, the system merges consecutively adjacent space units corresponding to the same feed port number j in the reaction location data; where consecutive adjacency means that the two space units share an edge, a plane, or a preset flue gas connection. The system denotes the set of space unit numbers corresponding to the h-th fuel reaction zone as... , and form: ,in Let h be the h-th fuel reaction zone, where h is the fuel reaction zone number. The system sets the fuel reaction zone number h and the spatial unit number. Fuel reaction zone The corresponding feed port number j, reaction determination time t, and fuel stage identifier set within the interval. Encapsulated as fuel reaction range data: ,in , represents the set of fuel stage identifiers corresponding to each spatial unit within the h-th fuel reaction interval, and can optionally include reaction state data. Encapsulated fuel reaction zone data, reaction state data Includes spatial unit number set Representative temperature of each space unit , representing oxygen concentration , representing CO concentration , representing the flue gas velocity And the feed rate at the corresponding feed port. Feeding start / stop status and feed rate .

[0061] Optionally, the reaction domain convergence processing specifically includes: S341. Based on the reaction location data, the reaction seed units are screened to obtain the reaction seed unit data; In one embodiment, the system obtains data from the reaction location. Read the space unit number k and the center position of the space unit. Corresponding feed port number j, fuel stage identifier and the reaction determination time t. When the fuel stage of a space unit is identified as the oxygen-deficient reaction stage. Or, if both sampling times are in the activation combustion phase. At that time, this spatial unit is used as the reaction seed unit to obtain the reaction seed unit data: ,in For reaction seed unit data, This represents the sampling interval between adjacent sampling times.

[0062] S342. Perform stage similarity neighborhood expansion on the reaction seed unit data to obtain neighborhood expansion data; In one embodiment, the system uses reaction seed unit data Spatial units in To expand the starting point, query adjacent spatial units that share an edge, coplanarity, or have a pre-defined flue gas connectivity with this spatial unit. When adjacent spatial units The feed port number j corresponds to the reaction seed unit, and its fuel stage identifier is... For the activation combustion stage or hypoxia response stage When this happens, the adjacent spatial unit is included in the extended neighborhood, and the extended neighborhood data is obtained: ,in Expanding data for the neighborhood Number the adjacent spatial units. The location is the center of the adjacent spatial unit.

[0063] S343. Perform a reaction continuity check on the neighborhood expansion data to obtain continuous active domain data; In one embodiment, the system uses neighborhood expansion data. Spatial unit numbering in Spatial unit center location And the corresponding feed port number j, and perform connectivity verification on the expanded spatial units. If multiple spatial units can form a continuous connection link through sharing edges, coplanarity, or a preset flue gas connection relationship, and the spatial units within this connection link correspond to the same feed port number j, then this group of spatial units is determined as a continuous active domain, and the continuous active domain data is obtained: ,in This is continuous active domain data, used to represent the set of spatial unit numbers that pass the reaction continuity check.

[0064] S344. Weak response boundaries are removed based on continuous active domain data to obtain effective active domain data; In one embodiment, the system uses continuous active domain data Weak response elimination is performed on boundary space cells. If a boundary space cell is adjacent to only one active space cell, and that boundary space cell does not appear in the response location data at the current sampling time. In the middle, or its fuel stage is identified as the preheating stage. If the boundary spatial cell is not found to be active, it will be removed from the continuous active domain. The system will then denote the set of spatial cell numbers after the removal as the effective active domain data. ,in For effective active domain data, it is used to represent the set of reactive spatial unit numbers after removing weak response boundaries.

[0065] S345. Encapsulate the effective active domain data into active domain intervals to obtain fuel reaction interval data.

[0066] In one embodiment, the system uses valid active domain data. The system divides consecutively adjacent spatial units corresponding to the same feed port number j into a fuel reaction interval. The set of spatial unit numbers corresponding to the h-th fuel reaction interval is denoted as: ,in To effectively activate domain data The h-th group of consecutive adjacent spatial unit numbers. The system forms the fuel reaction zone based on the spatial unit number set: ,in Let h be the h-th fuel reaction interval, where h is the fuel reaction interval number. The system denotes the set of fuel stage identifiers within the interval as: The reaction state data are recorded as follows: ,in This is the reaction state data for the h-th fuel reaction zone. , , , These represent the representative temperature, representative oxygen concentration, representative CO concentration, and representative flue gas velocity of the k-th furnace space unit, respectively. , , These represent the fuel feed rate, feed start / stop status, and feed rate at the corresponding feed inlet. The system assigns the fuel reaction zone number h and the spatial unit number set. Fuel reaction zone , corresponding feed port number j, reaction determination time t, and set of fuel stage identifiers within the interval and reaction state data Encapsulated as fuel reaction range data: ,in This is data for the fuel reaction range.

[0067] Optionally, S4 specifically refers to: S41. Based on the limited measurement point operation data, the combustion response is extracted to obtain the combustion response data; In one embodiment, the system operates based on data from a limited number of measurement points. Read the data at sampling time t and the previous sampling time of the i-th measurement point. oxygen concentration value , CO concentration value and flue gas velocity value Calculate the decrease in oxygen concentration at the measuring point: ,when , and At that time, the i-th measuring point is marked as the combustion response measuring point, and combustion response data is generated: ,in For combustion response data, The CO generation threshold is set at 200 ppm. 600ppm This represents the sampling interval between adjacent sampling times.

[0068] S42. Perform combustion response mapping based on combustion response data and furnace space correlation data to obtain combustion response mapping data; In one embodiment, the system uses furnace space correlation data. The set of associated measurement point numbers in Combustion response data Mapped to the corresponding furnace space unit. If the measuring point number... And measurement point i exists in the combustion response data. In the middle, the decrease in oxygen concentration at that measuring point is... CO concentration value and flue gas velocity value The combustion response mapping data is obtained by incorporating it into the k-th furnace space unit: ,in This represents the combustion response mapping data, where k is the spatial unit number and i is the associated measurement point number.

[0069] S43. Based on the fuel reaction range data, the combustion response mapping data is corrected to obtain the space oxygen consumption data; In one embodiment, the system uses fuel reaction range data. Read the set of spatial unit numbers corresponding to the h-th fuel reaction zone. and the combustion response mapping data China belongs to The spatial units are modified accordingly. For a spatial unit, the system determines its set of response measurement points: ,in Let be the set of response measurement points for the k-th furnace space element at sampling time t. When not empty, the system calculates the decrease in oxygen concentration in the space unit and the representative value of flue gas velocity: , And calculate the space oxygen consumption intensity: The system will assign space unit number k, fuel reaction zone number h, and space unit oxygen concentration decrease amount to the space unit. Space oxygen consumption intensity And the sampling time t is packaged into space oxygen consumption data: ,in This is space oxygen consumption data.

[0070] S44. Perform oxygen consumption interpolation on the space oxygen consumption data to obtain the implicit oxygen consumption unit data. In one embodiment, the system performs oxygen consumption interpolation back-calculation for spatial units within the fuel reaction zone where no spatial oxygen consumption data has been generated. If the spatial unit... satisfy And it does not exist. However, if there are adjacent spatial units with existing spatial oxygen consumption data, then the set of adjacent oxygen consumption unit numbers is denoted as: ,when When the value is not empty, the system performs an arithmetic average of the decrease in oxygen concentration and the oxygen consumption intensity of adjacent spatial units to obtain the data of the implicit oxygen consumption unit: , , ,in This is data from the implicit oxygen consumption unit. For the first The set of adjacent oxygen-consuming unit numbers corresponding to each spatial unit.

[0071] S45. The spatial oxygen consumption data and the implicit oxygen consumption unit data are fused to obtain the furnace oxygen consumption distribution data.

[0072] In one embodiment, the system will use space oxygen consumption data. Data from implied oxygen consumption units The data is then fused. For spatial cells with direct spatial oxygen consumption data, the system sets the final oxygen concentration decrease and final oxygen consumption intensity as follows: , And set up oxygen consumption source labels. For the implicit oxygen consumption unit obtained through interpolation, the system sets the final oxygen concentration decrease and the final oxygen consumption intensity as follows: , And set up oxygen consumption source identification. The system assigns space unit number k, fuel reaction zone number h, and final oxygen concentration decrease amount to the space unit k. Final oxygen consumption intensity Sampling time t and oxygen consumption source identifier Encapsulated as furnace oxygen consumption distribution data: ,in This is data on the distribution of oxygen consumption in the furnace; when When, it indicates that the oxygen consumption data of this space unit comes from the combustion response measurement point mapping; when When the oxygen consumption data of the spatial unit is obtained by interpolation from adjacent oxygen consumption units, it indicates that the oxygen consumption data of that spatial unit is derived from the interpolation of adjacent oxygen consumption units.

[0073] Optionally, S5 specifically refers to: S51. Calculate the oxygen consumption concentration based on the furnace oxygen consumption distribution data to obtain oxygen consumption concentration data; In one embodiment, the system is based on furnace oxygen consumption distribution data. Read the final oxygen consumption intensity of the k-th furnace space unit at sampling time t. And determine the set of adjacent unit numbers of the k-th furnace space unit based on the adjacency relationship between the furnace space units. The system calculates the oxygen consumption concentration degree of the k-th furnace space unit and its adjacent units: ,in Let r be the oxygen consumption concentration of the k-th furnace space unit at sampling time t, and r be the adjacent space unit number. Let be the final oxygen consumption intensity of the r-th furnace space unit at sampling time t. This is the set of space unit numbers adjacent to the k-th furnace space unit. The system combines the space unit number k, the fuel reaction zone number h, and the oxygen consumption concentration. And the sampling time t is packaged into oxygen consumption aggregated data: ,in This is accumulated data on oxygen consumption.

[0074] S52. Based on the furnace oxygen consumption distribution data and furnace space correlation data, conduct an oxygen supply accessibility assessment to obtain oxygen supply accessibility data. In one embodiment, the system reads the representative oxygen concentration of the k-th furnace space unit at sampling time t based on furnace space correlation data. And represents the flue gas velocity And from furnace oxygen consumption distribution data Read the corresponding final oxygen consumption intensity The system calculates the oxygen supply accessibility of the k-th furnace space unit: ,in Let be the oxygen supply accessibility value of the k-th furnace space unit at sampling time t; when The smaller the value, the weaker the oxygen supply capacity of the space unit relative to its oxygen consumption demand. The system assigns the space unit number k, the fuel reaction zone number h, and the oxygen supply accessibility value... , representing oxygen concentration , representing the flue gas velocity And the sampling time t is packaged into oxygen supply accessibility data: ,in Data on oxygen supply accessibility.

[0075] S53. Identify the mismatch between oxygen consumption and demand by analyzing the accumulated oxygen consumption data and the oxygen supply accessibility data to obtain oxygen supply imbalance data. In one embodiment, the system accumulates oxygen consumption data. and oxygen supply accessibility data Identify the mismatch between oxygen supply and demand. For the same spatial unit number k, when its oxygen consumption clustering degree... Not lower than the oxygen consumption accumulation threshold And its oxygen supply availability value Not higher than the oxygen accessibility threshold When the oxygen supply to the space unit is deemed to be unbalanced, the following conditions are met: The system will assign spatial unit number k, fuel reaction zone number h, and oxygen consumption concentration degree. Oxygen supply accessibility value And the sampling time t is packaged into oxygen supply imbalance data: ,in For oxygen supply imbalance data, The oxygen consumption accumulation threshold can be taken as the average oxygen consumption accumulation degree under historical stable combustion conditions. times, The oxygen supply accessibility threshold can be set to 0, or the average oxygen supply accessibility value under historical stable combustion conditions. .

[0076] S54. Determine the hypoxia precursor data from the oxygen supply imbalance data to obtain hypoxia precursor data. In one embodiment, the system uses oxygen supply imbalance data. The spatial unit number k in the data retrieves the representative oxygen concentration of the corresponding spatial unit from the furnace space association data. and represent CO concentration When the k-th furnace space unit satisfies: At that time, the system marks the spatial unit as a hypoxia precursor unit and generates hypoxia precursor data: ,in This is data indicating an early sign of hypoxia. The oxygen concentration threshold for hypoxia risk is set at 2%. The threshold for CO concentration accompanying hypoxia is set at 300 ppm.

[0077] S55. Identify the risk spread trend based on hypoxia precursor data to obtain hypoxia risk diffusion data; In one embodiment, the system is based on hypoxia precursor data. Given a spatial unit number k, query the set of adjacent unit numbers of the k-th furnace spatial unit. If the adjacent cell r is at the current sampling time t or the previous sampling time... If a unit has been marked as a precursor to oxygen deficiency, then the k-th furnace space unit is determined to have a risk of oxygen deficiency spreading, and a risk diffusion neighborhood is formed: or ,in Let the risk diffusion neighborhood of the k-th furnace space element at sampling time t be... Let be the oxygen consumption concentration of the r-th adjacent spatial unit at sampling time t. Let be the oxygen accessibility value of the r-th adjacent spatial cell at sampling time t. Let be the representative oxygen concentration of the r-th adjacent spatial cell at sampling time t. Let be the representative CO concentration of the r-th adjacent spatial cell at sampling time t. For the r-th adjacent spatial unit at the previous sampling time Oxygen consumption concentration For the r-th adjacent spatial unit at the previous sampling time The oxygen supply achievable value, For the r-th adjacent spatial unit at the previous sampling time The value represents the oxygen concentration. For the r-th adjacent spatial unit at the previous sampling time The value represents the CO concentration. This is the set of hypoxia precursor data from the previous sampling time of the system. The system uses spatial unit number k, fuel reaction interval number h, and risk diffusion neighborhood. And the sampling time t is packaged into hypoxia risk diffusion data: ,in This data represents the spread of hypoxia risk.

[0078] S56. Based on the data on oxygen supply imbalance, hypoxia precursors, and hypoxia risk diffusion, local hypoxia risk data are obtained.

[0079] In one embodiment, the system uses oxygen supply imbalance data. Precursor data on hypoxia and data on the spread of hypoxia risk The system integrates these elements. Spatial units exhibiting both oxygen supply imbalance and precursors to hypoxia are identified as local hypoxia risk units. Spatial units with a hypoxia risk diffusion neighborhood are included as risk extension units in the risk identification scope, resulting in a set of local hypoxia risk unit numbers: ,in This is the set of unit numbers representing localized hypoxia risk areas at sampling time t. The system assigns these units based on their adjacency relationships within the furnace space. Consecutive adjacent risk units merge to form localized hypoxia risk areas: ,in Let g be the set of spatial unit numbers corresponding to the g-th local hypoxia risk region, where g is the local hypoxia risk region number. The system will combine the local hypoxia risk region number g and the set of spatial unit numbers. Fuel reaction zone number h, oxygen consumption concentration Oxygen supply accessibility value , representing oxygen concentration , representing CO concentration Final oxygen consumption intensity Risk diffusion neighborhood The risk assessment time t is packaged into local hypoxia risk data: ,in This data represents the risk of localized hypoxia.

[0080] Optionally, S6 specifically refers to: S61. Determine the spatial units to be adjusted based on local hypoxia risk data, and obtain the data of the areas to be oxygenated; In one embodiment, the system reads local hypoxia risk data. Local hypoxia risk area number g, spatial unit number set Fuel reaction zone number h represents oxygen concentration , representing CO concentration Final oxygen consumption intensity and the risk assessment time t. When the spatial unit number And satisfy At that time, the spatial unit is identified as the spatial unit to be adjusted, and the data of the region to be oxygenated are obtained: ,in Data for the area requiring oxygen supply. The oxygen concentration threshold is the risk threshold for hypoxia.

[0081] S62. Obtain oxygen supplementation configuration data, and match it with the data of the area to be supplemented with oxygen and the oxygen supplementation configuration data to obtain oxygen supplementation execution association data; In one embodiment, the system acquires oxygen supplementation configuration data, which includes a preset oxygen supplementation execution partition mapping table: ,in This is the preset oxygen distribution execution zone mapping table; c is the execution zone number; Number the spatial units; The number of the oxygen nozzle, oxygen regulating valve, or combustion air valve corresponding to partition c; The current oxygen flow rate setpoint for partition c at sampling time t; To set the oxygen flow rate limit for partition c; A conversion factor is set for the incremental oxygen demand index to oxygen flow rate. The system uses data from the area to be oxygenated. Query the preset oxygen allocation execution partition mapping table for spatial unit number k. Obtain the oxygen supply execution related data: ,in To perform correlation data for oxygen supply, This is the execution partition number corresponding to the area to be oxygenated. To perform partitioning The corresponding oxygen nozzle, oxygen regulating valve, or combustion air valve number.

[0082] S63. Calculate the zonal oxygenation correction amount based on the local hypoxia risk data and the oxygenation execution correlation data to obtain the zonal oxygenation correction data. In one embodiment, the system uses data from the region to be oxygenated. Calculate the oxygen demand index for the k-th spatial unit to be regulated: ,in Let be the oxygen demand index for the k-th spatial unit to be adjusted. The system will consider the same local hypoxia risk area. The oxygen demand index of the region is obtained by summing the oxygen demand indices of each spatial unit to be regulated within the region: ,in This represents the oxygen demand index for the g-th local hypoxia risk area. The system correlates data based on oxygen allocation execution. The regional oxygen demand index is converted into the oxygen flow rate setting increment for the execution zone: ,in To perform partitioning The oxygen flow rate is set to increment. To perform partitioning Current oxygen flow rate setting To perform partitioning The maximum oxygen flow rate. The system assigns the local hypoxia risk area number g and the execution zone number. Fuel reaction zone number h, regional oxygen demand index Oxygen flow rate setting increment And the sampling time t is packaged into zoned oxygen allocation correction data: ,in Correct the data for zoned oxygen allocation.

[0083] S64. Generate oxygen distribution control parameters based on the zoned oxygen distribution correction data to obtain zoned oxygen distribution control data.

[0084] In one embodiment, the system corrects the oxygen distribution data based on the zone allocation data. Data on areas requiring oxygen supply And risk assessment thresholds are used to generate oxygenation control parameters. When any spatial unit within the g-th local hypoxia risk region satisfies: , To represent CO concentration, The threshold for CO concentration accompanying hypoxia is set at 300 ppm. For the final oxygen consumption intensity, The oxygen consumption intensity threshold for the risk of oxygen deficiency is taken as 1.2 times the average oxygen consumption intensity under historical stable combustion conditions, and this state must be sustained for at least [duration missing]. At that time, the system sets a priority oxygen allocation indicator: Otherwise, set: ,in To perform partitioning Priority oxygen allocation indicator; when When this occurs, it indicates that the execution partition is a priority oxygen allocation partition. When multiple execution partitions simultaneously have oxygen allocation needs, the system prioritizes generating and issuing the oxygen flow rate setting increment for this execution partition. When this occurs, it indicates that the execution zone is a normal oxygen distribution zone. After completing the priority oxygen distribution zone adjustment, the system will adjust the oxygen distribution according to the regional oxygen demand index. The oxygen flow rate setting increments for the corresponding execution partitions are generated in descending order; if there are multiple execution partitions... If they are the same, then follow the partition number. Adjustments are generated in ascending order. The system will execute partition numbering. Local hypoxia risk area number g, fuel reaction zone number h, regional oxygen demand index Oxygen flow rate setting increment Priority oxygen supply sign The generation time t is encapsulated as zoned oxygen distribution control data: ,in This is data for zoned oxygen distribution control.

[0085] Optionally, this application also provides an oxygen-enriched combustion system oxygen distribution regulation system for performing the oxygen-enriched combustion system oxygen distribution regulation method described above, wherein the oxygen-enriched combustion system oxygen distribution regulation includes: The oxygen-enriched combustion furnace data acquisition module is used to acquire limited measurement point operating data and fuel feeding status data of the oxygen-enriched combustion furnace. The furnace space measuring point scope matching module is used to match the furnace space measuring point scope based on the limited measuring point operation data to obtain furnace space associated data. The fuel reaction zone positioning module is used to locate the fuel reaction zone based on fuel feeding status data and furnace space correlation data, and obtain fuel reaction zone data. The oxygen consumption spatial back-calculation module is used to perform oxygen consumption spatial back-calculation based on limited measurement point operating data, furnace space correlation data and fuel reaction zone data to obtain furnace oxygen consumption distribution data. The local hypoxia risk identification module is used to identify local hypoxia risk based on furnace oxygen consumption distribution data and obtain local hypoxia risk data. The zoned oxygen distribution adjustment basis generation module is used to generate zoned oxygen distribution adjustment basis based on local hypoxia risk data, and obtain zoned oxygen distribution control data.

[0086] Therefore, the embodiments should be regarded as exemplary and non-limiting in all respects, and the scope of the invention is defined by the appended application documents rather than the foregoing description. Thus, it is intended that all variations falling within the meaning and scope of the equivalents of the application documents be incorporated into the invention.

[0087] The above description is merely a specific embodiment of the present invention, enabling those skilled in the art to understand or implement the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the present invention is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features of the invention herein.

Claims

1. A method for adjusting oxygen distribution in an oxygen-enriched combustion system, characterized in that, Includes the following steps: S1. Obtain limited measurement point operation data and fuel feeding status data of the oxygen-enriched combustion furnace; S2. Match the domain of measurement points in the furnace space based on the limited measurement point operation data to obtain furnace space correlation data; S3. Based on the fuel feeding status data and furnace space correlation data, locate the fuel reaction zone and obtain the fuel reaction zone data; S4. Based on the limited measurement point operation data, furnace space correlation data and fuel reaction zone data, oxygen consumption spatial back-inference is performed to obtain furnace oxygen consumption distribution data; S5. Based on the oxygen consumption distribution data in the furnace, identify the risk of local oxygen deficiency and obtain local oxygen deficiency risk data; S6. Generate the basis for zonal oxygen allocation adjustment based on local hypoxia risk data to obtain zonal oxygen allocation control data.

2. The method according to claim 1, characterized in that, S1 specifically refers to: S11. Collect temperature data, oxygen concentration data, flue gas composition data and furnace pressure data through preset measurement points in the oxygen-enriched combustion furnace, and integrate them to obtain limited measurement point operation data. S12. Acquire data on fuel feed rate, feed start / stop status, feed rate, fuel feed location, fuel moisture content, fuel particle size distribution, and fuel lower heating value, and integrate them to obtain fuel feed status data.

3. The method according to claim 1, characterized in that, S2 specifically refers to: S21. Obtain furnace structure data and divide the space according to the furnace structure data to obtain furnace space data; S22. Obtain the data of the deployed measuring points, and process the measuring point scope based on the data of the deployed measuring points to obtain the measuring point scope data. S23. Perform measurement point correlation on furnace space data and measurement point action area data to obtain measurement point correlation data; S24. Based on the correlation data of measuring points and the operation data of limited measuring points, spatial observation is constructed to obtain the correlation data of furnace space.

4. The method according to claim 3, characterized in that, The specific construction of space observation is as follows: S241. Based on the measurement point association data, the measurement points are divided into layers to obtain the measurement point layer data; S242. Extract the measurement point response features from the limited measurement point operation data to obtain the measurement point response feature data; S243. Based on the layered data of the measuring points and the response characteristic data of the measuring points, the observation reliability is evaluated to obtain the observation reliability data; S244. Based on the furnace structure data, the observation reliability data is corrected for observation transfer to obtain spatial observation transfer data. S245. Based on the layered data of measuring points, the observation reliability data, and the spatial observation transmission data, spatial observation configuration is performed to obtain the furnace space correlation data.

5. The method according to claim 1, characterized in that, S3 specifically refers to: S31. Determine the fuel distribution based on the fuel feeding status data and furnace space correlation data to obtain fuel distribution data; S32. Determine the fuel stage based on furnace space correlation data and fuel distribution data to obtain fuel stage data; S33. Based on the furnace space correlation data, fuel distribution data, and fuel stage data, the reaction position is mapped to obtain the reaction position data; S34. Perform reaction domain convergence processing based on the reaction location data to obtain fuel reaction interval data.

6. The method according to claim 5, characterized in that, The reaction domain convergence process is as follows: S341. Based on the reaction location data, the reaction seed units are screened to obtain the reaction seed unit data; S342. Perform stage similarity neighborhood expansion on the reaction seed unit data to obtain neighborhood expansion data; S343. Perform a reaction continuity check on the neighborhood expansion data to obtain continuous active domain data; S344. Weak response boundaries are removed based on continuous active domain data to obtain effective active domain data; S345. Encapsulate the effective active domain data into active domain intervals to obtain fuel reaction interval data.

7. The method according to claim 1, characterized in that, S4 specifically refers to: S41. Based on the limited measurement point operation data, the combustion response is extracted to obtain the combustion response data; S42. Perform combustion response mapping based on combustion response data and furnace space correlation data to obtain combustion response mapping data; S43. Based on the fuel reaction range data, the combustion response mapping data is corrected to obtain the space oxygen consumption data; S44. Perform oxygen consumption interpolation on the space oxygen consumption data to obtain the implicit oxygen consumption unit data. S45. The spatial oxygen consumption data and the implicit oxygen consumption unit data are fused to obtain the furnace oxygen consumption distribution data.

8. The method according to claim 1, characterized in that, S5 specifically refers to: S51. Calculate the oxygen consumption concentration based on the furnace oxygen consumption distribution data to obtain oxygen consumption concentration data; S52. Based on the furnace oxygen consumption distribution data and furnace space correlation data, conduct an oxygen supply accessibility assessment to obtain oxygen supply accessibility data. S53. Identify the mismatch between oxygen consumption and demand by analyzing the accumulated oxygen consumption data and the oxygen supply accessibility data to obtain oxygen supply imbalance data. S54. Determine the hypoxia precursor data from the oxygen supply imbalance data to obtain hypoxia precursor data. S55. Identify the risk spread trend based on hypoxia precursor data to obtain hypoxia risk diffusion data; S56. Based on the data on oxygen supply imbalance, hypoxia precursors, and hypoxia risk diffusion, local hypoxia risk data are obtained.

9. The method according to claim 1, characterized in that, S6 specifically refers to: S61. Determine the spatial units to be adjusted based on local hypoxia risk data, and obtain the data of the areas to be oxygenated; S62. Obtain oxygen supplementation configuration data, and match it with the data of the area to be supplemented with oxygen and the oxygen supplementation configuration data to obtain oxygen supplementation execution association data; S63. Calculate the zonal oxygenation correction amount based on the local hypoxia risk data and the oxygenation execution correlation data to obtain the zonal oxygenation correction data. S64. Generate oxygen distribution control parameters based on the zoned oxygen distribution correction data to obtain zoned oxygen distribution control data.

10. An oxygen distribution and regulation system for an oxygen-enriched combustion system, characterized in that, For performing the oxygen distribution adjustment method of the oxygen-enriched combustion system as described in claim 1, the oxygen distribution adjustment of the oxygen-enriched combustion system includes: The oxygen-enriched combustion furnace data acquisition module is used to acquire limited measurement point operating data and fuel feeding status data of the oxygen-enriched combustion furnace. The furnace space measuring point scope matching module is used to match the furnace space measuring point scope based on the limited measuring point operation data to obtain furnace space associated data. The fuel reaction zone positioning module is used to locate the fuel reaction zone based on fuel feeding status data and furnace space correlation data, and obtain fuel reaction zone data. The oxygen consumption spatial back-calculation module is used to perform oxygen consumption spatial back-calculation based on limited measurement point operating data, furnace space correlation data and fuel reaction zone data to obtain furnace oxygen consumption distribution data. The local hypoxia risk identification module is used to identify local hypoxia risk based on furnace oxygen consumption distribution data and obtain local hypoxia risk data. The zoned oxygen distribution adjustment basis generation module is used to generate zoned oxygen distribution adjustment basis based on local hypoxia risk data, and obtain zoned oxygen distribution control data.

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