Method and system for controlling graded and differentiated soot blowing of boiler

Abstract

The invention relates to a boiler grading differentiation soot blowing control method and system, and the method comprises the steps: obtaining the soot deposition rate grid coordinate distribution of a hearth wall surface, and carrying out the screening through a first threshold value, and obtaining effective statistical data; a dangerous deposition point is screened and determined by using a second threshold value; mapping the effective statistical data and the dangerous deposition points to corresponding soot blowing working areas according to space coordinates; the dangerous deposition proportion of each soot blowing working area is calculated, and whether soot blowing needs to be executed in the corresponding soot blowing working area or not is judged; calculating the average nearest neighbor distance of the dangerous deposition points in the soot blowing working area in which soot blowing needs to be executed, and determining the soot blowing grade; the corresponding soot blowing grades are corrected according to the operation parameters of all the soot blowing working areas; the corresponding soot blowers are controlled to execute differential soot blowing according to the corrected soot blowing grades; and according to a soot blowing execution result, updating each threshold value and soot blowing grade to realize closed-loop optimization. Fine control over soot blowing of the boiler is achieved, and the operation safety and economical efficiency of the boiler are improved.

Description

Technical Field

[0001] This invention relates to the field of boiler soot blowing control technology, specifically to a boiler graded differentiated soot blowing control method and system. Background Technology

[0002] During the operation of coal-fired boilers in power plants, ash particles deposit on the furnace walls, forming ash accumulation and slag. This leads to deterioration of heat exchange on the heating surfaces, increased wall temperature, and decreased boiler efficiency, posing safety risks. To suppress boiler slag formation, power plant boilers use soot blowers fixed to the furnace walls for soot blowing to remove the slag. In actual operation, power plant boilers often perform periodic full-furnace soot blowing, relying heavily on operator experience. This makes it difficult to adjust the soot blowing based on the complex and non-uniform distribution of ash deposits and slag within the furnace. This can easily result in problems such as severely affected areas of slag not being addressed in time, and excessive soot blowing in low-risk areas, leading to increased steam consumption and accelerated wear on the metal tube walls of the heating surfaces. Therefore, it is essential to evaluate boiler slag formation using reasonable and accurate technical indicators. Furthermore, rationally dividing the furnace walls into zones for differentiated soot blowing is also crucial for the safe and stable operation of the boiler.

[0003] In existing technologies, patent CN106352320A divides the furnace into three sections based on combustion characteristics: the main combustion zone, the burnout zone, and the heat exchange zone. It uses the thermal efficiency coefficient of the water-cooled walls in different sections of the furnace as a slagging monitoring indicator to guide soot blowing. Patent CN120145923A uses the wall ash deposition rate as a technical indicator to train a neural network to predict furnace slagging, thus providing a basis for precise soot blowing. These methods primarily focus on the detection and prediction of boiler slagging. However, there are currently no clear strategies or control methods for using technical indicators to determine whether soot blowing is necessary or for conducting graded and differentiated soot blowing. Therefore, soot blowing operations still present challenges in practical operation. Summary of the Invention

[0004] To address the shortcomings of existing technologies, this invention provides a boiler graded differentiated soot blowing control method and system, which solves the problems of lack of specificity in boiler soot blowing control in existing technologies, resulting in ineffective soot blowing and excessive soot blowing, leading to high energy consumption and wear of heating surfaces.

[0005] The technical solution adopted in this invention is as follows: This invention provides a boiler graded differentiated soot blowing control method, comprising: Obtain the grid coordinate distribution of ash deposition rate on the furnace wall surface, and extract the ash deposition rate value R corresponding to each grid point in a unified coordinate space; determine the data that satisfy R≥T1 as effective statistical data, where T1 is a set first threshold value used to characterize the effective starting value of ash deposition; determine the grid points that satisfy R≥T2 as dangerous deposition points, where T2 is a second threshold value determined based on the distribution characteristics of the effective statistical data. Based on the coverage area of ​​the soot blower, the furnace wall is divided into several soot blowing work areas, and the effective statistical data and dangerous deposition points are mapped to the corresponding soot blowing work areas according to spatial coordinates. Calculate the ratio of the number of dangerous deposition points to the number of valid statistical data points in each soot blowing work area to obtain the dangerous deposition ratio P of each soot blowing work area, and compare P with the preset soot blowing threshold to determine whether the corresponding soot blowing work area needs to be soot blown. The average nearest neighbor distance of hazardous deposit points within the soot blowing work area where soot blowing is required. I and will I The soot blowing level is determined by comparing it with multiple preset grading thresholds; The corresponding soot blowing level is adjusted according to the operating parameters of each soot blowing work area; Control each corresponding sootblower to perform differentiated sootblowing according to the revised sootblowing level; Continue to collect the ash deposition rate value R and operating parameters after soot blowing, and update T1, T2, soot blowing threshold, grading threshold and soot blowing level based on the soot blowing results and changes in operating conditions; The average nearest neighbor distance I The calculations include:

[0006] In the formula, N h This represents the total number of hazardous deposition points within the current soot blowing work area; d i For the first i The distance between a dangerous deposition point and its nearest dangerous deposition point.

[0007] The preferred technical solution is: The second threshold T2 is determined by using the effective statistical data of all soot blowing work areas as a sample; or, the second threshold T2 of each corresponding area is determined by using the effective statistical data of each soot blowing work area as a sample.

[0008] The ash deposition rate grid coordinate distribution on the furnace wall is the final result of CFD simulation, experimental test results, or a fusion and correction of CFD simulation and experimental test results. The CFD simulation results were obtained by constructing a boiler CFD model coupled with a wall ash deposition model and calculating them. The experimental test results were obtained through on-site measurements of raw data related to furnace wall deposition, which were then processed and mapped into a gridded distribution.

[0009] The on-site measurements include: measuring the deposition state of the furnace wall to obtain the temperature field, heat flow field, image information, and deposition thickness information of the furnace wall; and converting the obtained information into ash deposition rate values ​​on the corresponding wall grid through image recognition, machine learning, or artificial intelligence inversion.

[0010] The graded differentiated soot blowing includes: adjusting the soot blowing parameters of the corresponding soot blowing working area based on the benchmark soot blowing parameters preset by the soot blower; the soot blowing parameters include the number of soot blowing times, the duration of a single soot blowing, the pressure of the soot blowing medium, the flow rate of the soot blowing medium, and the soot blowing inspection cycle.

[0011] The operating parameters include physical parameters that affect slagging, such as CO concentration, wall temperature difference, and flue gas temperature in the adjacent soot blowing area.

[0012] The changes in operating conditions include one or more changes in coal type, load, fuel entry point, and air distribution method.

[0013] The initial settings for the first threshold T1, the soot blowing threshold, and the grading threshold are set based on the boiler's historical operating data related to ash accumulation.

[0014] The distribution characteristics of the effective statistical data include high quantile characteristics and frequency decay trends.

[0015] This invention also provides a boiler graded differentiated soot blowing control system, applied to the aforementioned boiler graded differentiated soot blowing control method, the system comprising: The acquisition and filtering module is used to acquire the grid coordinate distribution of ash deposition rate on the furnace wall, extract the ash deposition rate value R corresponding to each grid point in a unified coordinate space; determine the data that satisfy R≥T1 as valid statistical data, where T1 is a set first threshold value used to characterize the effective starting value of ash deposition; and determine the grid points that satisfy R≥T2 as dangerous deposition points, where T2 is a second threshold value determined based on the distribution characteristics of the valid statistical data. The coordinate mapping module is used to divide the furnace wall into several soot blowing work areas according to the coverage of the soot blower, and to map the effective statistical data and dangerous deposition points to the corresponding soot blowing work areas according to spatial coordinates. The execution discrimination module is used to calculate the ratio of the number of dangerous deposition points to the number of valid statistical data in each soot blowing work area, obtain the dangerous deposition ratio P of each soot blowing work area, and compare P with the preset soot blowing threshold to determine whether the corresponding soot blowing work area needs to be soot blown. The grading module is used to determine the average nearest neighbor distance of hazardous deposit points within the soot blowing work area where soot blowing is required. I Perform calculations and I The soot blowing level is determined by comparing it with multiple preset grading thresholds; The correction module corrects the corresponding soot blowing level based on the operating parameters of each soot blowing work area; The execution module controls each corresponding sootblower to perform differentiated sootblowing according to the revised sootblowing level; The update module continues to collect the ash deposition rate value R and operating parameters after soot blowing, and updates T1, T2, soot blowing threshold, grading threshold and soot blowing level based on the soot blowing results and changes in operating conditions. The average nearest neighbor distance I The calculations include:

[0016] In the formula, N h This represents the total number of hazardous deposition points within the current soot blowing work area; d i For the first i The distance between a dangerous deposition point and its nearest dangerous deposition point.

[0017] The technical solution of the present invention can achieve at least some of the following beneficial effects: This invention establishes an implementable sootblowing trigger criterion and sootblowing intensity grading strategy on the scale of the sootblowing working area, primarily based on the coverage area of ​​the sootblower, and implements closed-loop control for effect verification and parameter updates after sootblowing. This improves the targeting and precision of boiler sootblowing control, avoids ineffective and excessive sootblowing, reduces energy consumption and wear on heating surfaces, and enhances boiler operating safety and economy. Specifically, it includes the following advantages: (1) This invention uses the ash deposition rate on the furnace wall as the basic index and allows the corresponding gridded distribution results to be obtained through three methods: numerical simulation, field measurement, or a combination of both. Therefore, it has greater applicability and flexibility. On the one hand, when using the CFD method, it is easy to connect with the existing deposition analysis system of large pulverized coal boilers. On the other hand, when using the field measurement method, deposition-related information can be directly obtained through infrared thermography, heat flux density meters, wall temperature measuring points, visual imaging, or deposition thickness detection, and further inverted to form the ash deposition rate grid distribution. Thus, this invention not only improves the diversity of ash deposition rate acquisition methods but also enhances the feasibility of the method in practical engineering.

[0018] (2) The present invention uses a first threshold T1 to effectively remove a large amount of low-deposition background data, avoiding interference with the identification of dangerous deposition points and regional risk analysis, and improving the stability and reliability of subsequent identification results. At the same time, since subsequent statistics, mapping and calculations are only carried out on the effective statistical data set D, the amount of data involved in the calculation is reduced, the calculation scale is reduced, and the efficiency of the method in engineering applications is improved. The present invention uses a second threshold T2 to avoid the dilution of dangerous point identification results by low-deposition background, and also reflects that the criteria for judging dangerous deposition points will be dynamically changed with the effective statistical data set, which is convenient to make corrections in combination with different boiler grades, ash composition characteristics and operation feedback, which is conducive to improving the pertinence and engineering applicability of dangerous deposition point identification. It avoids dangerous deposition judgments that are too high or too low due to factors such as load changes, thus making them unsuitable for actual working conditions. At the same time, the second threshold T2 can be a unified threshold of effective statistical data of the entire wall surface, or a partition threshold when the sample size is sufficient, taking into account the simplicity of engineering implementation and the adaptability to the differences in deposition in different areas, improving the consistency and flexibility of dangerous deposition point identification.

[0019] (3) The present invention defines the dangerous deposition ratio P as the ratio of the number of dangerous deposition points in the soot blowing work area to the number of valid statistical data points, and uses this as the soot blowing trigger criterion. Compared with the method of triggering soot blowing by a single dangerous point, this index does not simply determine whether there is a dangerous point in the area, nor does it compare the number of dangerous points with all grid points. It can better reflect the true risk status of the target soot blowing work area, effectively reduce excessive soot blowing caused by a small number of discrete high values, and improve the engineering rationality of soot blowing trigger judgment; Based on the determination of whether ash blowing is necessary using the hazardous deposition ratio P, the average nearest neighbor distance of hazardous deposition points is further introduced. I Determining the soot blowing level. Compared with methods that determine soot blowing intensity solely based on deposition ratio or single-point high values, this method can directly reflect the spatial concentration of hazardous deposition points within the soot blowing work area, thus more effectively distinguishing between scattered high-value deposition and concentrated contiguous deposition, and improving the rationality and relevance of soot blowing level classification.

[0020] (4) While using the average nearest neighbor distance to determine the soot blowing level, the present invention can also combine operating parameters such as CO concentration, wall temperature difference, and adjacent flue gas temperature to correct the soot blowing level, so that the soot blowing control not only reflects the spatial distribution characteristics of the deposition point, but also takes into account the local combustion state and heat transfer state, thereby improving the matching degree between the soot blowing strategy and the actual slagging risk.

[0021] (5) The present invention is based on the average nearest neighbor distance of the soot blowing area according to the principle of reasonable grading. IThe soot blowing intensity is controlled in a graded and differentiated manner by adjusting parameters such as the flow rate, pressure, duration, and frequency of the soot blowing medium to achieve different levels of soot blowing operations. Compared with a uniform soot blowing intensity control method, this method can promptly implement stronger soot blowing in high-risk areas and avoid excessive soot blowing in medium- and low-risk areas. This reduces steam consumption and wear on heated surfaces while ensuring the soot cleaning effect, thus balancing soot blowing efficiency and equipment safety.

[0022] Other features and advantages of the invention will be set forth in the following description or may be learned by practicing the invention. Attached Figure Description

[0023] Figure 1 This is a flowchart illustrating the method of an embodiment of the present invention. Detailed Implementation

[0024] The specific embodiments of the present invention are described below with reference to the accompanying drawings.

[0025] See Figure 1 This embodiment of a boiler graded differentiated soot blowing control method includes: S1. Obtain the grid coordinate distribution of ash deposition rate on the furnace wall and extract the ash deposition rate value R corresponding to each grid point in a unified coordinate space.

[0026] In one specific implementation, a 350MW tangential coal-fired boiler is taken as the control object. The mature and usable wall temperature measuring device, CO concentration measuring device, ash deposition thickness detection device, infrared flue gas temperature measuring device, heat flux density meter and other devices installed in the boiler can measure various operating data.

[0027] As a preferred embodiment, the ash deposition rate grid coordinate distribution on the furnace wall is the result of CFD simulation, experimental test, or the final result of the fusion and correction of CFD simulation and experimental test results. Specific methods for obtaining this data include: Based on the boiler structure, pulverized coal physicochemical properties, and operating parameters, a CFD combustion model coupled with an ash deposition simulation model was constructed to simulate the ash deposition rate on the furnace wall, and the CFD simulation results of the grid coordinate distribution of the ash deposition rate on the furnace wall were obtained. Alternatively, the ash deposition rate can be obtained using mature measured ash deposition rate testing methods in engineering, which include: using one or more of infrared thermal imaging devices, heat flux meters, wall temperature measuring points, visual imaging devices, and deposition thickness detection devices to measure the deposition state of the furnace wall, obtain the temperature field, heat flux field, image information, and deposition thickness information of the furnace wall, and convert the obtained information into ash deposition rate values ​​on the corresponding wall grid through image recognition, machine learning, or artificial intelligence inversion methods; Alternatively, CFD simulation and field measurements can be performed simultaneously. The results of field experiments can be verified against the CFD simulation results. The CFD model can be continuously adjusted to obtain an accurate distribution of ash deposition rate on the furnace wall. A database can be established based on the grid data in the simulation system, with the unit of ash deposition rate uniformly set to kg / m³. 2 s.

[0028] The furnace wall is divided into grids according to a preset coordinate rule. CFD simulation results and / or experimental test results are mapped to a unified wall grid coordinate space to form the ash deposition rate value R corresponding to each grid point.

[0029] S2. Filter the ash deposition rate value R corresponding to each grid point, and determine the data that satisfy R≥T1 as the effective statistical data D, where T1 is the set first threshold, which is used to characterize the effective starting value of ash deposition. Grid points that satisfy R≥T2 are identified as hazardous deposition points, where T2 is a second threshold determined based on the distribution characteristics of the effective statistical data.

[0030] The first threshold T1 is set to initially screen out effective statistical data D that facilitates more efficient calculations and reduces subsequent computational costs. When the ash deposition rate is lower than T1, the depositional growth at the corresponding location is weak, and its contribution to subsequent slagging analysis and soot blowing determination is limited within a soot blowing evaluation cycle. Therefore, it is not included in subsequent statistics as low depositional background data. When the ash deposition rate is greater than or equal to T1, the location is considered to have entered the effective depositional stage and is defined as effective statistical data for subsequent identification of hazardous deposition points and risk analysis of soot blowing work areas.

[0031] In this embodiment, the first threshold T1 is set to 0.01 based on historical operating data related to boiler ash accumulation.

[0032] Setting a second threshold T2 aims to define grid points in the effective statistical data set D with ash deposition rates greater than or equal to T2 as dangerous deposition points, and to serve as the basis for subsequent risk assessment and soot blowing intensity analysis of the soot blowing work area.

[0033] As a preferred approach, the second threshold T2 is determined using the effective statistical data of all soot blowing work areas as samples; or, after the soot blowing work areas are divided, when the number of samples in each soot blowing work area is large enough, the second threshold T2 of the corresponding area is determined using the effective statistical data corresponding to each soot blowing work area as samples.

[0034] Specifically, the value of the second threshold T2 is determined by analyzing the distribution characteristics of the ash deposition rate of the effective statistical data set D, combined with the uniform requirements for identifying high-risk deposition points in engineering. The distribution characteristics include high quantile characteristics and frequency decay trends. The analysis results of this embodiment show that the effective statistical data D exhibits a significantly right-skewed distribution overall, with a characteristic interval in the high-value range transitioning from the main distribution to the risk tail. Based on the analysis results, the second threshold T2 is determined to be 0.04. During continuous operation and control, T2 can be appropriately adjusted according to safety levels, ash removal costs, etc.

[0035] S3. Divide the furnace wall into several soot blowing work areas according to the coverage of the soot blower, and map the effective statistical data D and dangerous deposition points to the corresponding soot blowing work areas according to spatial coordinates.

[0036] Specifically, in this embodiment, the boiler has 100 sootblowers distributed across all four walls of the furnace, with 25 sootblowers evenly distributed in a 5×5 grid on each wall. All sootblowers have the same model parameters. Based on the sootblower arrangement and coverage area, the furnace wall is divided into 100 equal sootblowing working areas. Then, the effective statistical data D and hazardous deposition points are mapped back to the furnace wall of the divided sootblowing working areas using spatial grid coordinates.

[0037] S4. Calculate the ratio of the number of dangerous deposition points to the number of valid statistical data points in each soot blowing work area to obtain the dangerous deposition ratio P of each soot blowing work area, and compare P with the preset soot blowing threshold Pth to determine whether the corresponding soot blowing work area needs to be soot blown.

[0038] Specifically, the proportion of hazardous deposits P is calculated as follows: P = N1 / N2, where N1 is the number of hazardous deposit points in the target soot blowing area and N2 is the effective statistical data in the target soot blowing area.

[0039] This embodiment sets the soot blowing threshold Pth to 10% based on historical operating data related to boiler ash accumulation, serving as the soot blowing trigger criterion. That is, when the dangerous deposition ratio P in the soot blowing working area is greater than or equal to P... th If the area is cleared, it is determined that the area needs to be cleaned; otherwise, it is determined that the area does not need to be cleaned.

[0040] S5. Calculate the average nearest neighbor distance of hazardous deposit points within the soot blowing work area where soot blowing is required. I and will I The soot blowing level is determined by comparing it with multiple preset grading thresholds.

[0041] Wherein, the average nearest neighbor distance IThe average nearest neighbor distance for all hazardous deposition points within the current soot blowing area is calculated using the following formula:

[0042] In the formula, N h This represents the total number of hazardous deposition points within the current soot blowing work area; d i For the first i The distance between a dangerous deposition point and its nearest dangerous deposition point. I The smaller the value, the more concentrated the dangerous deposition points are, indicating a higher risk of depositional accumulation in the area; I The larger the value, the more dispersed the distribution of dangerous depositional sites, indicating a lower risk of sediment accumulation in the area. Based on this, it can be calculated according to... I The size of the area can be used to divide the soot blowing zone into different soot blowing levels.

[0043] This embodiment sets two tiered thresholds based on historical operating data related to boiler ash accumulation. I 1 and I 2, and I 1> I 2. When I > I At time 1, execute Level 1 soot blowing; I 1≥ I > I At 2 o'clock, perform level 2 soot blowing; when I ≤ I At 2 o'clock, perform level 3 soot blowing.

[0044] S6. Adjust the corresponding soot blowing level according to the operating parameters of each soot blowing work area.

[0045] The operating parameters include physical parameters that affect slagging, such as CO concentration, wall temperature difference, and flue gas temperature in adjacent soot blowing areas. The wall temperature difference is the difference between the current wall temperature and the average wall temperature under normal cleaning conditions.

[0046] In one specific implementation, when the operating parameters indicate an increased risk of dust accumulation, the original soot blowing level is increased by one level; when the relevant operating parameters do not show a significant increase in risk, the original soot blowing level remains unchanged; when the original soot blowing level has already reached the highest level, the original level is maintained.

[0047] S7. Control each corresponding sootblower to perform differentiated sootblowing according to the revised sootblowing level.

[0048] As a preferred method, the graded differentiated soot blowing is based on the baseline soot blowing parameters preset by the soot blower, and the soot blowing parameters of the corresponding soot blowing working area are increased or decreased.

[0049] Preferably, the soot blowing parameters include the number of soot blowing cycles, the duration of a single soot blowing cycle, the pressure of the soot blowing medium, the flow rate of the soot blowing medium, and the soot blowing inspection cycle. Different soot blowing parameters reflect different soot blowing intensities, which can be varied in, but are not limited to, the following ways: Number of soot blowing operations: For each increase in soot blowing level, the number of soot blowing operations performed on the target soot blowing work area within the preset time window increases by 1; Soot blowing duration: For each increase in soot blowing level, the duration of a single soot blowing operation on the target soot blowing area within the preset time window increases by 20%; Soot blowing medium pressure: For each increase in soot blowing level, the pressure of the soot blowing medium per cycle applied to the target soot blowing area within the preset time window increases by 10%; Soot blowing media flow rate: For each increase in soot blowing level, the single soot blowing media flow rate performed on the target soot blowing work area within the preset time window increases by 20%; Preferably, in this embodiment, during soot blowing, a computer system controls each sootblower to generate operation instructions. In engineering operation, the boiler's furnace sootblowers use steam injection for soot blowing, with a steam temperature of 315℃, a steam pressure of 1.5MPa, a steam consumption of 20kg / min, a working time of 5 minutes per cycle, and an overall furnace soot blowing inspection cycle of 8 hours. In this case, the above parameters are set as the baseline soot blowing parameters. When adjusting the soot blowing intensity, adjustments will be made with reference to these baseline parameters, as shown in the following example: When P is greater than P th In this case, if it is determined that soot blowing operations are required in the soot blowing work area, the soot blowing intensity will be adjusted in stages according to the current average nearest neighbor distance: Level 1 soot blowing is performed according to the baseline soot blowing parameters.

[0050] For Level 2 soot blowing, the steam pressure is increased by 20% to 1.8 MPa based on the baseline soot blowing parameters, while other parameters remain unchanged.

[0051] For Level 3 soot blowing, the steam pressure is increased by 40% to 2.1 MPa and the working time is increased by 20% to 6 minutes, based on the baseline soot blowing parameters. The inspection cycle for this area is set to 6 hours.

[0052] S8. Continue to collect the ash deposition rate value R and operating parameters after soot blowing, verify the soot blowing effect, and update T1, T2, soot blowing threshold Pth, grading threshold and soot blowing level according to the verification results and changes in operating conditions, as the basis for the next control cycle, to achieve closed-loop optimization.

[0053] The changes in operating conditions include one or more changes in coal type, load, fuel entry point, and air distribution method.

[0054] This embodiment also provides a boiler graded differentiated soot blowing control system, applied to the method described herein, the system comprising: The acquisition and filtering module is used to acquire the grid coordinate distribution of ash deposition rate on the furnace wall, extract the ash deposition rate value R corresponding to each grid point in a unified coordinate space; determine the data that satisfy R≥T1 as valid statistical data, where T1 is a set first threshold value used to characterize the effective starting value of ash deposition; and determine the grid points that satisfy R≥T2 as dangerous deposition points, where T2 is a second threshold value determined based on the distribution characteristics of the valid statistical data. The coordinate mapping module is used to divide the furnace wall into several soot blowing work areas according to the coverage of the soot blower, and to map the effective statistical data and dangerous deposition points to the corresponding soot blowing work areas according to spatial coordinates. The execution discrimination module is used to calculate the ratio of the number of dangerous deposition points to the number of valid statistical data in each soot blowing work area, obtain the dangerous deposition ratio P of each soot blowing work area, and compare P with the preset soot blowing threshold to determine whether the corresponding soot blowing work area needs to be soot blown. The grading module is used to calculate the average nearest neighbor distance of hazardous deposit points within the soot blowing work area where soot blowing is required. I and will I The soot blowing level is determined by comparing it with multiple preset grading thresholds; The correction module corrects the corresponding soot blowing level based on the operating parameters of each soot blowing work area; The execution module controls each corresponding sootblower to perform differentiated sootblowing according to the revised sootblowing level; The update module continues to collect the ash deposition rate value R and operating parameters after soot blowing, verifies the soot blowing effect, and updates T1, T2, soot blowing threshold, grading threshold and soot blowing level based on the verification results and changes in operating conditions. The average nearest neighbor distance I The calculations include:

[0055] In the formula, N h This represents the total number of hazardous deposition points within the current soot blowing work area; d i For the first i The distance between a dangerous deposition point and its nearest dangerous deposition point.

[0056] This embodiment also provides an electronic device, the device comprising: a memory for storing program instructions; and a processor for calling the program instructions stored in the memory and executing the boiler graded differentiated soot blowing control method according to the obtained program instructions.

[0057] This embodiment also provides a storage medium storing computer-executable instructions for causing a computer to execute the boiler graded differentiated soot blowing control method.

[0058] In summary, this invention, by setting a first threshold T1, initially filters out effective statistical data D that facilitates more efficient computation and reduces subsequent computational costs; by setting a second threshold T2, it provides a quantitative basis for determining hazardous deposits, obtaining hazardous deposit points with higher deposition risk; based on the hazardous deposit points and effective statistical data D within each soot blowing work area, it obtains a quantitative hazardous deposit ratio P, thereby clarifying whether soot blowing is necessary in each area; and finally, it uses the average nearest neighbor distance... I This describes the degree of aggregation of hazardous deposition points in the area, providing a quantitative basis for classifying soot blowing levels. During operation, the above thresholds can be updated based on operating conditions to achieve optimal control.

[0059] It will be understood by those skilled in the art that the above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A boiler graded differentiated soot blowing control method, characterized in that, include: Obtain the grid coordinate distribution of ash deposition rate on the furnace wall surface, and extract the ash deposition rate value R corresponding to each grid point in a unified coordinate space; determine the data that satisfy R≥T1 as effective statistical data, where T1 is a set first threshold value used to characterize the effective starting value of ash deposition; determine the grid points that satisfy R≥T2 as dangerous deposition points, where T2 is a second threshold value determined based on the distribution characteristics of the effective statistical data. Based on the coverage area of ​​the soot blower, the furnace wall is divided into several soot blowing work areas, and the effective statistical data and dangerous deposition points are mapped to the corresponding soot blowing work areas according to spatial coordinates. Calculate the ratio of the number of dangerous deposition points to the number of valid statistical data points in each soot blowing work area to obtain the dangerous deposition ratio P of each soot blowing work area, and compare P with the preset soot blowing threshold to determine whether the corresponding soot blowing work area needs to be soot blown. Calculate the average nearest neighbor distance of hazardous deposit points within the soot blowing work area where soot blowing is required. I and will I The soot blowing level is determined by comparing it with multiple preset grading thresholds; The corresponding soot blowing level is adjusted according to the operating parameters of each soot blowing work area; Control each corresponding sootblower to perform differentiated sootblowing according to the revised sootblowing level; Continue to collect the ash deposition rate value R and operating parameters after soot blowing, and update T1, T2, soot blowing threshold, grading threshold and soot blowing level based on the soot blowing results and changes in operating conditions; The average nearest neighbor distance I The calculations include: In the formula, N h This represents the total number of hazardous deposition points within the current soot blowing work area; d i For the first i The distance between a dangerous deposition point and its nearest dangerous deposition point.

2. The method according to claim 1, characterized in that, The second threshold T2 is determined by using the effective statistical data of all soot blowing work areas as a sample; or, the second threshold T2 of each corresponding area is determined by using the effective statistical data of each soot blowing work area as a sample.

3. The method according to claim 1, characterized in that, The ash deposition rate grid coordinate distribution on the furnace wall is the final result of CFD simulation, experimental test results, or a fusion and correction of CFD simulation and experimental test results. The CFD simulation results were obtained by constructing a boiler CFD model coupled with a wall ash deposition model and calculating them. The experimental test results were obtained through on-site measurements of raw data related to furnace wall deposition, which were then processed and mapped into a gridded distribution.

4. The method according to claim 3, characterized in that, The on-site measurements include: measuring the deposition state of the furnace wall to obtain the temperature field, heat flow field, image information, and deposition thickness information of the furnace wall; and converting the obtained information into ash deposition rate values ​​on the corresponding wall grid through image recognition, machine learning, or artificial intelligence inversion.

5. The method according to claim 1, characterized in that, The graded differentiated soot blowing includes: adjusting the soot blowing parameters of the corresponding soot blowing working area based on the benchmark soot blowing parameters preset by the soot blower; the soot blowing parameters include the number of soot blowing times, the duration of a single soot blowing, the pressure of the soot blowing medium, the flow rate of the soot blowing medium, and the soot blowing inspection cycle.

6. The method according to claim 1, characterized in that, The operating parameters include physical parameters that affect slagging, such as CO concentration, wall temperature difference, and flue gas temperature in the adjacent soot blowing area.

7. The method according to claim 1, characterized in that, The changes in operating conditions include one or more changes in coal type, load, fuel entry point, and air distribution method.

8. The method according to claim 1, characterized in that, The initial settings for the first threshold T1, the soot blowing threshold, and the grading threshold are set based on the boiler's historical operating data related to ash accumulation.

9. The method according to claim 1, characterized in that, The distribution characteristics of the effective statistical data include high quantile characteristics and frequency decay trends.

10. A boiler graded differentiated soot blowing control system, characterized in that, The system, applicable to the method of any one of claims 1 to 9, comprises: The acquisition and filtering module is used to acquire the grid coordinate distribution of ash deposition rate on the furnace wall, extract the ash deposition rate value R corresponding to each grid point in a unified coordinate space; determine the data that satisfy R≥T1 as valid statistical data, where T1 is a set first threshold value used to characterize the effective starting value of ash deposition; and determine the grid points that satisfy R≥T2 as dangerous deposition points, where T2 is a second threshold value determined based on the distribution characteristics of the valid statistical data. The coordinate mapping module is used to divide the furnace wall into several soot blowing work areas according to the coverage of the soot blower, and to map the effective statistical data and dangerous deposition points to the corresponding soot blowing work areas according to spatial coordinates. The execution discrimination module is used to calculate the ratio of the number of dangerous deposition points to the number of valid statistical data in each soot blowing work area, obtain the dangerous deposition ratio P of each soot blowing work area, and compare P with the preset soot blowing threshold to determine whether the corresponding soot blowing work area needs to be soot blown. The grading module is used to calculate the average nearest neighbor distance of hazardous deposit points within the soot blowing work area where soot blowing is required. I and will I The soot blowing level is determined by comparing it with multiple preset grading thresholds; The correction module corrects the corresponding soot blowing level based on the operating parameters of each soot blowing work area; The execution module controls each corresponding sootblower to perform differentiated sootblowing according to the revised sootblowing level; The update module continues to collect the ash deposition rate value R and operating parameters after soot blowing, and updates T1, T2, soot blowing threshold, grading threshold and soot blowing level based on the soot blowing results and changes in operating conditions. The average nearest neighbor distance I The calculations include: In the formula, N h This represents the total number of hazardous deposition points within the current soot blowing work area; d i For the first i The distance between a dangerous deposition point and its nearest dangerous deposition point.

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