Emission reduction control system based on boiler flue gas

Abstract

The invention relates to the technical field of coal yard temperature measurement, in particular to an emission reduction control system based on boiler flue gas. Comprising a monitoring unit, a central control unit and an inspection unit, wherein the central control unit is used for performing stage division according to boiler operation to generate a plurality of boiler operation stages and generating corresponding adjusting instructions; the monitoring unit comprises a plurality of monitoring sub-modules, and the monitoring sub-modules are used for collecting monitoring data of all boiler operation stages and generating monitoring data packets of all boiler operation stages; the inspection unit comprises a plurality of inspection sub-modules, and the inspection sub-modules are used for obtaining the operation state of the boiler; through real-time monitoring and accurate fault early warning, problems in boiler operation can be found in time, measures can be taken, fault expansion is avoided, and therefore the maintenance cost is reduced, and the equipment downtime is shortened.

Description

Technical Field

[0001] The present application relates to the technical field of boiler emission reduction control, and in particular to an emission reduction control system based on boiler flue gas. Background Art

[0002] As the world pays more attention to environmental protection, countries have formulated stricter standards for air pollutant emissions. For boiler flue gas emissions, restrictions are imposed on sulfur dioxide (SO2), nitrogen oxides (NO X This has prompted companies to seek effective emission reduction control systems to ensure that boiler flue gas emissions comply with relevant regulations, avoid high fines, and fulfill social responsibilities.

[0003] During the coal combustion phase, different coal types have different combustion efficiencies, flame stability, and pollutant generation. Accurately monitoring and controlling this phase is crucial for emissions reduction. Summary of the Invention

[0004] The purpose of this application is to collect monitoring data from each stage through multiple monitoring submodules of the monitoring unit and generate data packets, providing detailed data support for the central control unit to generate adjustment instructions. This allows timely detection of combustion insufficiency so that combustion conditions such as air supply and combustion speed can be adjusted.

[0005] In some embodiments of the present application, a boiler flue gas emission reduction control system is provided, comprising: Monitoring unit, central control unit and inspection unit; The central control unit is used to generate multiple boiler operation stages according to the stage division of boiler operation and generate corresponding adjustment instructions; The monitoring unit includes a plurality of monitoring submodules, the monitoring submodules are used to collect monitoring data of each boiler operation stage and generate monitoring data packets of each boiler operation stage; The inspection unit includes multiple inspection submodules, which are used to obtain the operating status of the boiler; The central control unit also includes: The first processing module is used to establish the boiler operation stages including: coal pretreatment stage, coal combustion stage and flue gas treatment stage; The second processing module is used to establish a corresponding monitoring sub-model based on each boiler operation stage; The second processing module is further configured to generate corresponding adjustment instructions in combination with the monitoring data packet of the monitoring submodule and the monitoring submodel.

[0006] In some embodiments of the present application, the second processing module is further configured to: Based on the historical operation data of the coal preprocessing stage, the coal types are classified to generate the coal type sequence A, A=(a1, a2…a i …a n ); Among them, a i is the i-th coal type; n is the number of coal types; Establish the i-th coal type a i Coal samples of combustion state set D; Type a of coal type i i The coal samples include: the current i-th coal type a i The combustion state set D, D=(d1,d2…d j …d m ); Among them, d j is the jth combustion state feature, and m is the total number of combustion state features; Combine coal samples of all coal types to generate a monitoring sub-model for the coal pre-processing stage; Establish a coal combustion state sample set based on the historical operation data of the coal combustion stage; The coal combustion state sample set includes the flue gas data set Y generated by the current coal type under various combustion states, Y=(y1,y2…y x …y r ); Among them, y x is the reference value of the xth type of data in the flue gas, and r is the total number of data types in the flue gas; Combine all coal combustion state sample sets to generate a monitoring sub-model for the coal combustion stage; Set the preset value of flue gas status based on the historical operation data of the flue gas treatment stage; Classify the smoke based on the preset value of the smoke state to generate multiple smoke types; Set corresponding adjustment instructions based on flue gas type; A monitoring sub-model for the flue gas treatment stage is generated by combining all flue gas types and corresponding regulation instructions.

[0007] In some embodiments of the present application, when setting the corresponding adjustment instruction based on the flue gas type, the method further includes: Obtain various types of pollutants in flue gas based on historical flue gas data; Obtain the concentration range reference value for each pollutant; The corresponding pollutant concentration preset value H is set based on the current pollutant concentration range reference value, H=(h1,h2); Wherein, h1 is the first preset value of the current pollutant type in the flue gas, and h2 is the second preset value of the current pollutant type in the flue gas; Divide the current pollutant concentration level based on the preset value H of the pollutant concentration; If Hx < h1, the current pollutant concentration is the first-level pollutant concentration; If h1 ≤ Hx ≤ h2, the current pollutant concentration is the second-level pollutant concentration; If h2 < Hx, the current pollutant concentration is the third-level pollutant concentration; Hx is the concentration of the current pollutant actually measured in the flue gas; Based on the pollutant concentration levels of various pollutant types in the current flue gas, set the flue gas type set E, E = (e1, e2…e ai …e an ); Among them, e a1 is the ai-th type of flue gas, and an is the total number of flue gas types; Set the corresponding flue gas treatment instructions based on each type of flue gas.

[0008] In some embodiments of the present application, when generating the corresponding adjustment instructions by combining the monitoring data packet of the monitoring sub-module and the monitoring sub-model, it further includes: Generate the characteristic data set Ti (i = 1, 2, 3) of each boiler operation stage based on the monitoring data packet of each monitoring sub-module at the current monitoring time node; Among them, T1 is the characteristic data set of the coal pretreatment stage, T2 is the characteristic data set of the coal combustion stage, and T3 is the characteristic data set of the flue gas treatment stage; Combine the characteristic data set Ti of each boiler operation stage and the monitoring sub-model of the corresponding boiler operation stage to determine the flue gas type at the current monitoring time node; Combine the flue gas type at the current monitoring time node and the monitoring sub-model of the flue gas treatment stage to generate the corresponding preliminary flue gas treatment instructions; Combine the preliminary flue gas treatment instructions and the characteristic data set T3 of the flue gas treatment stage to generate the flue gas treatment instructions.

[0009] In some embodiments of the present application, when determining the flue gas type at the current monitoring time node, it further includes: Combine the characteristic data set T1 of the coal pretreatment stage and the monitoring sub-model of the coal pretreatment stage to generate the combustion state prediction interval q1 of the coal, q1 = (q1, q2…q j …q m ); Among them, q j = [q ja , q jb , q ja is the left end point of the j-th combustion state prediction interval, q jbis the right endpoint of the j-th combustion state prediction interval, and m is the total number of combustion state features; The monitoring data package of the coal pre-processing stage is verified by combining the obtained combustion state prediction value and the characteristic data set T2 of the coal combustion stage; Based on the characteristic data set T2 of the coal combustion stage and the monitoring sub-model of the coal combustion stage, the first flue gas prediction interval p1 is generated, p1=(p1,p2…p x …p r ); Among them, p x =[p xa ,p xb ],p xa is the left endpoint of the prediction interval of the x-th type of flue gas data, p xb is the right endpoint of the prediction interval of the xth type of smoke data, and r is the total number of smoke data types; The monitoring data package of the coal combustion stage is verified by combining the first flue gas prediction value and the characteristic data set T3 of the flue gas treatment stage; The smoke type at the current monitoring time node is determined in combination with the obtained first smoke prediction interval p1.

[0010] In some embodiments of the present application, the verification of the monitoring data packet of the coal preprocessing stage further includes: Based on the characteristic data set T2 of the coal combustion stage at the current monitoring time node, the corresponding combustion state reference value set q2 is obtained, q2=(q 21 ,q 22 …q 2j …q 2m ); Among them, q 2j is the reference value of the j-th combustion state; Count the number of items m1 of each combustion state reference value in the combustion state reference value set q2 that are within the corresponding combustion state prediction interval q1; Generate a first verification value m3 by combining the number of items m1 and the total number of combustion state features m; m3=k1*m1 / m; k1 is the first fixed coefficient; Compare m3 with the first verification value preset value mk; If m3>mk, it is judged that the monitoring data packet obtained in the coal type preprocessing stage is normal; If m3≤mk, it is determined that the monitoring data packet obtained in the coal type preprocessing stage is abnormal, and a coal type preprocessing warning instruction is generated.

[0011] In some embodiments of the present application, when verifying the monitoring data packet of the coal combustion stage by combining the first flue gas prediction value and the characteristic data set T3 of the flue gas treatment stage, the verification further includes: Based on the characteristic data set T3 of the flue gas treatment stage at the current monitoring time node, the corresponding flue gas data reference value set p2 is obtained, p2=(p 21 ,p 22 …p 2x …p 2r ); Among them, p 2x is the reference value of the xth type of flue gas data; Counting the number r1 of items of each smoke data reference value in the smoke data reference value set p2 that are within the corresponding first smoke prediction interval p1; Generate a first verification value r3 by combining the number of items r1 and the total number of smoke data types r; r3=k2*r1 / r; k2 is the second fixed coefficient; Compare r3 with the first verification value preset value rk; If r3>rk, it is judged that the monitoring data packet obtained during the coal combustion stage is normal; If r3≤rk, it is determined that the monitoring data packet obtained during the coal combustion stage is abnormal, and a coal combustion early warning instruction is generated.

[0012] In some embodiments of the present application, when generating the corresponding preliminary flue gas treatment instruction in combination with the flue gas type at the current monitoring time node and the monitoring sub-model of the flue gas treatment stage, the method further includes: Preset smoke control instructions based on the smoke type obtained at the current monitoring time node; Based on the monitoring data packet of the flue gas treatment stage, the concentration level change data L of various pollutants in the flue gas during the execution of the flue gas control instruction is obtained, where L=(L1, L2); Among them, L1 is the concentration level of various pollutants obtained by the monitoring data packet, and L2 is the time when the corresponding pollutant concentration level changes; Determine whether the time L2 of the change of various pollutant concentration levels meets the preset interval (L aX ,L bX );L aX The left endpoint of the preset interval for the changing data, L bX Preset the right endpoint of the interval for the changing data; If it meets the requirements, keep running; If it does not meet the requirements, a flue gas treatment warning instruction will be generated.

[0013] In some embodiments of the present application, the inspection unit is further configured to: Based on the early warning instructions of each stage obtained by the central control unit, the device detection is carried out separately to determine whether there is any abnormality in the monitoring equipment; If there is no abnormality in the monitoring device, modify the corresponding sub-monitoring model parameters.

[0014] Compared with the prior art, the boiler flue gas emission reduction control system according to the embodiment of the present application has the following beneficial effects: The central control unit divides the boiler operation into stages, enabling precise control based on the characteristics of each stage. This prepares for subsequent combustion, thereby optimizing the entire boiler operation process, improving combustion efficiency, and reducing pollutant generation.

[0015] The second processing module classifies coal types based on the historical operating data of the coal pretreatment stage, establishes coal type series and combustion state set coal samples, and then generates a monitoring sub-model for the coal pretreatment stage, which can predict its combustion characteristics after pretreatment, adjust combustion parameters in advance, reduce incomplete combustion, improve combustion efficiency and reduce pollutant emissions.

[0016] Establishing a combustion status sample set and monitoring sub-model based on historical operating data of the coal combustion stage helps to accurately predict the flue gas conditions generated during the combustion process, and enables the system to prepare for flue gas treatment in advance. For example, according to the predicted flue gas composition and amount, the operating parameters of the desulfurization and denitrification equipment can be adjusted to improve the flue gas treatment effect.

[0017] During the flue gas treatment stage, detailed classification and targeted treatment of flue gas types can improve flue gas treatment efficiency. For high-sulfur flue gas, more intensive desulfurization treatment methods can be used. For high-nitrogen oxide flue gas, the denitrification process can be optimized to more effectively reduce pollutant emissions.

[0018] By generating the combustion state prediction interval and the first flue gas prediction interval of each coal type and verifying them with the characteristic data sets of each stage, the uncertainty of the data can be better considered.

[0019] By comparing with the actual combustion state reference value set, it is possible to accurately determine whether the monitoring data packet is normal, discover potential problems in time and issue early warning instructions.

[0020] During the coal combustion stage, the accuracy of the monitoring data package is also verified by comparing the predicted interval with the actual flue gas data reference value set, which helps to ensure the reliability of the entire system, adjust the operating parameters in a timely manner, and avoid system failures or poor emission reduction effects caused by erroneous data.

[0021] The flue gas type at the current monitoring time node is determined in combination with the prediction interval, and then the corresponding preliminary flue gas treatment instructions are generated, making the flue gas treatment instructions more accurate and able to be adjusted according to the characteristics of the actual flue gas type. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] Figure 1This is a structural diagram of a boiler flue gas emission reduction control system preferred in an embodiment of the present application. DETAILED DESCRIPTION

[0023] The following embodiments are used to illustrate the present invention, but are not intended to limit the scope of the present invention.

[0024] In the description of this application, it should be understood that the terms "center", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", etc., indicating the orientation or position relationship, are based on the orientation or position relationship shown in the accompanying drawings, and are only for the convenience of describing this application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation on this application.

[0025] The terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of the technical features being referred to. Thus, a feature specified as "first" or "second" may explicitly or implicitly include one or more of such features. Throughout this application, unless otherwise specified, "plurality" means two or more.

[0026] In the description of this application, it should be noted that, unless otherwise expressly specified or limited, the terms "mounted," "connected," and "connected" should be understood in a broad sense. For example, they can refer to fixed connections, detachable connections, or integral connections; mechanical connections or electrical connections; direct connections or indirect connections through an intermediate medium; and internal connections between two components. Those skilled in the art will understand the specific meanings of the above terms in this application based on the specific circumstances.

[0027] like Figure 1 As shown, a preferred embodiment of the present application is a boiler flue gas emission reduction control system, comprising: Monitoring unit, central control unit and inspection unit; The central control unit is used to generate multiple boiler operation stages according to the stage division of boiler operation and generate corresponding adjustment instructions; The monitoring unit includes a plurality of monitoring submodules, the monitoring submodules are used to collect monitoring data of each boiler operation stage and generate monitoring data packets of each boiler operation stage; The inspection unit includes multiple inspection submodules, which are used to obtain the operating status of the boiler; The central control unit also includes: The first processing module is used to establish the boiler operation stages including: coal pretreatment stage, coal combustion stage and flue gas treatment stage; The second processing module is used to establish a corresponding monitoring sub-model based on each boiler operation stage; The second processing module is further configured to generate corresponding adjustment instructions in combination with the monitoring data packet of the monitoring submodule and the monitoring submodel.

[0028] Example 2: The second processing module is further configured to: Based on the historical operation data of the coal preprocessing stage, the coal types are classified to generate the coal type sequence A, A=(a1, a2…a i …a n ); Among them, a i is the i-th coal type; n is the number of coal types; Establish the i-th coal type a i Coal samples of combustion state set D; Type a of coal type i i The coal samples include: the current i-th coal type a i The combustion state set D, D=(d1,d2…d j …d m ); Among them, d j is the jth combustion state feature, and m is the total number of combustion state features; Combine coal samples of all coal types to generate a monitoring sub-model for the coal pre-processing stage; Establish a coal combustion state sample set based on the historical operation data of the coal combustion stage; The coal combustion state sample set includes the flue gas data set Y generated by the current coal type under various combustion states, Y=(y1,y2…y x …y r ); Among them, y x is the reference value of the xth type of data in the flue gas, and r is the total number of data types in the flue gas; Combine all coal combustion state sample sets to generate a monitoring sub-model for the coal combustion stage; Set the preset value of flue gas status based on the historical operation data of the flue gas treatment stage; Classify the smoke based on the preset value of the smoke state to generate multiple smoke types; Set corresponding adjustment instructions based on flue gas type; A monitoring sub-model for the flue gas treatment stage is generated by combining all flue gas types and corresponding regulation instructions.

[0029] Example 3: When setting corresponding adjustment instructions based on the flue gas type, it further includes: Obtaining various pollutant types in the flue gas based on historical flue gas data; Obtaining the reference value of the concentration range for each pollutant; Setting the concentration preset value H for the corresponding pollutant based on the reference value of the current pollutant concentration range, H = (h1, h2); Where h1 is the first preset value of the current pollutant type in the flue gas, and h2 is the second preset value of the current pollutant type in the flue gas; Dividing the current pollutant concentration level based on the concentration preset value H of the pollutant; If Hx < h1, the current pollutant concentration is the first - level pollutant concentration; If h1 ≤ Hx ≤ h2, the current pollutant concentration is the second - level pollutant concentration; If h2 < Hx, the current pollutant concentration is the third - level pollutant concentration; Hx is the actually measured concentration of the current pollutant in the flue gas; Setting the flue gas type set E based on the pollutant concentration levels of various pollutant types in the current flue gas, E = (e1, e2…e ai …e an ); Where e a1 is the ai - th flue gas type, and an is the total number of flue gas types; Setting the corresponding flue gas treatment instructions based on each flue gas type.

[0030] In this embodiment, various pollutant types in the flue gas are determined, including sulfur dioxide, nitrogen oxides, particulate matter, etc.

[0031] For each determined pollutant type, obtain the reference value of its concentration range. These reference values are obtained by statistically analyzing historical data to determine a reasonable concentration range.

[0032] For the current pollutant to be treated, set the concentration preset value H = (h1, h2) according to the reference value of its concentration range. Among them, the determination of h1 and h2 is based on a comprehensive consideration of various factors.

[0033] For example, h1 may be the lower concentration limit determined according to environmental emission standards, the optimal efficiency range of equipment operation, or the critical value of environmental impact, etc.; h2 may be the higher concentration limit after considering factors such as equipment treatment capacity, economic cost, and relatively loose environmental impact limits.

[0034] For the actually measured concentration Hx of the current pollutant in the flue gas, compare it with the concentration preset value H to divide the pollutant concentration level.

[0035] If Hx < h1, it indicates that the current pollutant concentration is relatively low, and it is classified as a primary pollutant concentration. This means that the content of this pollutant in the flue gas is at a relatively low level, and the impact on the environment and equipment operation is relatively small.

[0036] If h1 ≤ Hx ≤ h2, at this time the pollutant concentration is at an intermediate level and is classified as a secondary pollutant concentration, which means that a certain degree of attention and treatment are required.

[0037] When h2 < Hx, it indicates that the pollutant concentration is high and is classified as a tertiary pollutant concentration. In this case, more stringent treatment measures may be required to reduce the pollutant concentration.

[0038] For each type of flue gas e a1 , corresponding flue gas treatment instructions are set according to its characteristics.

[0039] For flue gas types with relatively low pollution levels (such as flue gas types with a relatively high proportion of primary pollutant concentration), the flue gas treatment instructions may be relatively simple. For example, only routine filtering and monitoring operations are required.

[0040] Example 4: When generating the corresponding adjustment instructions by combining the monitoring data packet of the monitoring sub-module and the monitoring sub-model, it further includes: Generating characteristic data sets Ti (i = 1, 2, 3) for each boiler operation stage based on the monitoring data packets of each monitoring sub-module at the current monitoring time node; Among them, T1 is the characteristic data set for the coal pretreatment stage, T2 is the characteristic data set for the coal combustion stage, and T3 is the characteristic data set for the flue gas treatment stage; Determining the type of flue gas at the current monitoring time node by combining the characteristic data sets Ti of each boiler operation stage and the monitoring sub-model corresponding to the boiler operation stage; Generating corresponding preliminary flue gas treatment instructions by combining the type of flue gas at the current monitoring time node and the monitoring sub-model in the flue gas treatment stage; Generating flue gas treatment instructions by combining the preliminary flue gas treatment instructions and the characteristic data set T3 in the flue gas treatment stage.

[0041] In this embodiment, based on the characteristic data set T1 for the coal pretreatment stage, this data set contains various parameter information of the coal during the pretreatment process, such as the particle size, humidity, sulfur content, etc. of the coal.

[0042] Through the monitoring sub-model in the coal pretreatment stage, which has learned and analyzed a large amount of coal pretreatment data, it can predict the state of coal combustion based on the characteristic data in the pretreatment stage.

[0043] Example 5: The flue gas type at the current monitoring time node also includes: Combine the characteristic data set T1 of the coal type preprocessing stage and the monitoring sub-model of the coal type preprocessing stage to generate the combustion state prediction interval q1 of the coal type, q1=(q1,q2…q j …q m ); Among them, q j =[q ja ,q jb ],q ja is the left endpoint of the j-th combustion state prediction interval, q jb is the right endpoint of the j-th combustion state prediction interval, and m is the total number of combustion state features; The monitoring data package of the coal pre-processing stage is verified by combining the obtained combustion state prediction value and the characteristic data set T2 of the coal combustion stage; Based on the characteristic data set T2 of the coal combustion stage and the monitoring sub-model of the coal combustion stage, the first flue gas prediction interval p1 is generated, p1=(p1,p2…p x …p r ); Among them, p x =[p xa ,p xb ],p xa is the left endpoint of the prediction interval of the x-th type of flue gas data, p xb is the right endpoint of the prediction interval of the xth type of smoke data, and r is the total number of smoke data types; The monitoring data package of the coal combustion stage is verified by combining the first flue gas prediction value and the characteristic data set T3 of the flue gas treatment stage; The smoke type at the current monitoring time node is determined in combination with the obtained first smoke prediction interval p1.

[0044] Example 6: The verification of the monitoring data packet of the coal pre-processing stage also includes: Based on the characteristic data set T2 of the coal combustion stage at the current monitoring time node, the corresponding combustion state reference value set q2 is obtained, q2=(q 21 ,q 22 …q 2j …q 2m ); Among them, q 2j is the reference value of the j-th combustion state; Count the number of items m1 of each combustion state reference value in the combustion state reference value set q2 that are within the corresponding combustion state prediction interval q1; Generate a first verification value m3 by combining the number of items m1 and the total number of combustion state features m; m3=k1*m1 / m; k1 is the first fixed coefficient; Compare m3 with the first verification value preset value mk; If m3>mk, it is judged that the monitoring data packet obtained in the coal type preprocessing stage is normal; If m3≤mk, it is determined that the monitoring data packet obtained in the coal type preprocessing stage is abnormal, and a coal type preprocessing warning instruction is generated.

[0045] In this embodiment, the combustion state reference value is obtained from the characteristic data set T2 of the coal combustion stage at the current monitoring time node. This characteristic data set T2 contains various key information of the coal combustion process, such as combustion temperature, combustion speed, oxygen content and other data closely related to the combustion state.

[0046] According to the predefined combustion state characteristic types, these data are organized into a combustion state reference value set q2=(q 21 ,q 22 …q 2j …q 2m ). For example, q 21 is the actual value of the current combustion temperature, q 22 is the actual value of the burning velocity, etc., where q 2j is the reference value of the jth combustion state.

[0047] The calculated first verification value m3 is compared with the first verification value preset value mk.

[0048] If m3 > mk, this means that most of the values in the combustion state reference value set q2 are within the corresponding combustion state prediction interval q1. This indicates that the monitoring data package in the coal type preprocessing stage closely matches the actual conditions during the coal type combustion stage, thus judging that the monitoring data package acquired during the coal type preprocessing stage is normal.

[0049] If m3 ≤ mk, the combustion state reference value and the predicted interval are poorly matched, indicating a possible problem with the monitoring data package during the coal pretreatment phase. In this case, the system generates a coal pretreatment warning, prompting personnel to inspect the coal pretreatment process, such as whether the pretreatment equipment is operating normally and whether the pretreatment parameters are appropriate.

[0050] Example 7: When verifying the monitoring data packet of the coal combustion stage by combining the first flue gas prediction value and the characteristic data set T3 of the flue gas treatment stage, the method further includes: Based on the characteristic data set T3 of the flue gas treatment stage at the current monitoring time node, the corresponding flue gas data reference value set p2 is obtained, p2=(p 21 ,p 22 …p2x …p 2r ); Among them, p 2x is the reference value of the xth type of flue gas data; Counting the number r1 of items of each smoke data reference value in the smoke data reference value set p2 that are within the corresponding first smoke prediction interval p1; Generate a first verification value r3 by combining the number of items r1 and the total number of smoke data types r; r3=k2*r1 / r; k2 is the second fixed coefficient; Compare r3 with the first verification value preset value rk; If r3>rk, it is judged that the monitoring data packet obtained during the coal combustion stage is normal; If r3≤rk, it is determined that the monitoring data packet obtained during the coal combustion stage is abnormal, and a coal combustion early warning instruction is generated.

[0051] In this embodiment, flue gas-related data is extracted from the characteristic dataset T3 of the flue gas treatment phase at the current monitoring time point according to pre-set rules. This data covers multiple aspects, such as the flue gas composition content (such as the concentration of sulfur dioxide, nitrogen oxides, and carbon dioxide) and the physical properties of the flue gas (such as temperature, humidity, and flow rate).

[0052] For each type of smoke-related data, there is a corresponding specific reference value. These reference values are combined into a smoke data reference value set p2=(p 21 ,p 22 …p 2x …p 2r ). For example, p 21 is the actual concentration reference value of sulfur dioxide, p 22 It is the actual concentration reference value of nitrogen oxides, etc.

[0053] The calculated first verification value r3 is compared with the first verification value preset value rk.

[0054] If r3 > rk, this means that the actual flue gas data reference values during the flue gas treatment phase are mostly within the first flue gas prediction interval, and the system determines that the monitoring data packets acquired during the coal combustion phase are normal. This indicates that the monitoring data during the coal combustion phase is consistent with the flue gas prediction based on this data, and the combustion process is likely normal.

[0055] If r3 ≤ rk, the actual flue gas data reference value is poorly aligned with the predicted interval, and the system determines that the monitoring data package acquired during the coal combustion phase is abnormal. At this point, the system generates a coal combustion warning instruction, prompting personnel to inspect the coal combustion process. This may involve checking the combustion equipment for proper operation and the appropriate combustion parameters.

[0056] Example 8: When generating the corresponding preliminary flue gas treatment instruction in combination with the flue gas type at the current monitoring time node and the monitoring sub-model of the flue gas treatment stage, the method further includes: Preset smoke control instructions based on the smoke type obtained at the current monitoring time node; Based on the monitoring data packet of the flue gas treatment stage, the concentration level change data L of various pollutants in the flue gas during the execution of the flue gas control instruction is obtained, where L=(L1, L2); Among them, L1 is the concentration level of various pollutants obtained by the monitoring data packet, and L2 is the time when the corresponding pollutant concentration level changes; Determine whether the time L2 of the change of various pollutant concentration levels meets the preset interval (L aX ,L bX );L aX The left endpoint of the preset interval for the changing data, L bX Preset the right endpoint of the interval for the changing data; If it meets the requirements, keep running; If it does not meet the requirements, a flue gas treatment warning instruction will be generated.

[0057] In this embodiment, the preset change data interval (LaX, LbX) is established based on experimental data, previous operating experience, and relevant environmental protection standards. This interval takes into account the reasonable time range that the pollutant concentration level should follow during normal flue gas treatment.

[0058] For example, for a specific flue gas treatment process, after the instruction to increase the treatment power is initiated, the pollutant concentration should theoretically begin to decrease to the next level within a certain period of time. If this time is too long or too short, it may indicate a problem with the flue gas treatment process.

[0059] For each pollutant, the time L2 during which its concentration level changes is compared with the preset interval (LaX, LbX).

[0060] Taking the treatment of nitrogen oxides as an example, if the preset time interval for the nitrogen oxide concentration level to drop from level 2 to level 1 is (5 minutes, 10 minutes), when the actual monitoring detects that this change occurs at 8 minutes, it means that it meets the preset interval. At this time, the system determines that it is normal and can maintain the current operating status.

[0061] However, if this change occurs within 3 minutes or 12 minutes, which exceeds the preset range, it does not meet the requirements.

[0062] When the time L2 for each pollutant concentration level change falls within the preset interval (LaX, LbX) of the flue gas control data, the system determines that the flue gas treatment process is operating normally. At this point, the system continues to operate according to the current flue gas control instructions and continuously monitors various flue gas indicators to promptly identify potential problems.

[0063] If the time L2 for at least one pollutant concentration level change does not conform to the preset range, the system will generate a flue gas treatment warning instruction. This warning instruction will notify the relevant operators or the automated control system, indicating that there may be an abnormality in the flue gas treatment process.

[0064] For example, the early warning instructions may specify in detail which pollutant's concentration level change time does not meet the requirements, so that operators can specifically check the relevant equipment (such as whether there is a treatment equipment failure, insufficient reagent dosage, etc.) or adjust the treatment process parameters.

[0065] Example 9: The inspection unit is further used for: Based on the early warning instructions of each stage obtained by the central control unit, the device detection is carried out separately to determine whether there is any abnormality in the monitoring equipment; If there is no abnormality in the monitoring device, modify the corresponding sub-monitoring model parameters.

[0066] In this embodiment, upon receiving an early warning instruction for the coal pre-processing stage from the central control unit, the inspection unit first determines the monitoring equipment relevant to this stage. This equipment may include a coal quality analyzer (for analyzing coal composition, calorific value, etc.), a moisture sensor (for monitoring coal moisture), and a particle size detector (for detecting coal particle size).

[0067] For coal quality analyzers, the inspection unit checks the operating status of the sensors. For example, it checks whether the sensor connections are functioning properly and whether there are any signal transmission interruptions. It also verifies the analyzer's calibration to check whether the most recent calibration time and calibration parameters meet requirements.

[0068] For humidity sensors, the inspection unit checks the sensor's probe for cleanliness, as impurities like coal dust may cling to the probe and affect measurement accuracy. It also checks the sensor's circuitry for proper function, such as measuring the sensor's resistance to ensure it's within the normal range (according to the sensor's technical specifications).

[0069] For particle size detection devices, check whether their mechanical structure is intact, for example, whether the vibrating screen is damaged or blocked. At the same time, check whether the optical or electrical sensors related to particle size detection are working properly, such as whether the laser emission and reception of the laser particle size analyzer are normal.

[0070] After receiving the early warning instruction for the coal combustion stage, the inspection unit will check the monitoring equipment for this stage. The monitoring equipment at this stage includes temperature sensors (measuring combustion temperature), pressure sensors (monitoring the pressure in the combustion chamber), and flame monitors (monitoring the flame status).

[0071] Temperature sensor testing involves checking the thermocouple or RTD for damage. By measuring the sensor's output voltage or resistance and comparing it to a standard temperature-electrical signal curve, any deviation outside the allowable range could indicate a sensor failure.

[0072] Pressure sensor testing focuses on checking for damage or blockage in the diaphragm. Accuracy is determined by applying a known pressure to the sensor and measuring whether the output signal conforms to the pressure-signal conversion relationship. Also, check the sensor's connecting piping for leaks.

[0073] The flame monitor inspection primarily checks whether its optical components are clean, as smoke and dust from combustion may adhere to them and affect the monitoring effect. It also checks whether its photoelectric conversion circuit is functioning properly to ensure that it can accurately detect the presence, intensity, and stability of the flame.

[0074] When receiving the early warning instruction of the flue gas treatment stage, the inspection unit pays attention to the monitoring equipment related to flue gas treatment, such as flue gas composition analyzer (monitoring sulfur dioxide, nitrogen oxides and other components in the flue gas), smoke concentration monitor, flow sensor (monitoring flue gas flow), etc.

[0075] For flue gas composition analyzers, the inspection unit checks whether the sampling system is functioning properly, including whether the sampling pipeline is blocked and whether the sampling pump is functioning normally. At the same time, the chemical reaction cell or optical detection element inside the analyzer is checked to ensure that it can accurately analyze the flue gas composition.

[0076] Testing of a smoke concentration monitor involves checking the cleanliness of its optical transmitter and receiver, as well as the alignment of the optical path. Accuracy is determined by measuring the stability of its output signal and comparing it with a standard sample of known smoke concentration.

[0077] The flow sensor is mainly inspected to see if its impeller or other flow measuring components are blocked or damaged. By comparing and calibrating it with a standard flow source, the measurement accuracy is checked to see if it is within the allowable range.

[0078] If the monitoring equipment during the coal pretreatment phase detects no anomalies, the inspection unit begins modifying the corresponding sub-monitoring model parameters. For example, if the coal analyzer's test results have been stable and accurate, but certain coal characteristics (such as volatile matter content) have recently changed slightly, the inspection unit can adjust the volatile matter-related parameters in the coal pretreatment monitoring sub-model based on the new coal quality analysis data.

[0079] If the monitoring equipment during the coal combustion phase is normal, the inspection unit will modify the parameters of the sub-monitoring model for that phase. For example, if the temperature and pressure sensors are functioning normally, but the temperature-pressure relationship during combustion deviates from the model's predictions, the inspection unit can adjust the relevant parameters in the combustion phase monitoring sub-model based on the actual measured temperature and pressure data.

[0080] Assume that the monitoring sub-model for the coal combustion phase is built based on a neural network, with the input layer consisting of parameters such as combustion temperature, pressure, and air supply, and the output layer consisting of indicators such as combustion efficiency. If the actual combustion efficiency deviates from the model's prediction, the inspection unit can use the large amount of temperature, pressure, and air supply data obtained by normal monitoring equipment, as well as the corresponding actual combustion efficiency data, to fine-tune the weights and bias of the neural network model, thereby improving the model's prediction accuracy for the combustion process.

[0081] During the flue gas treatment phase, when the monitoring equipment is functioning normally, the inspection unit adjusts the corresponding sub-monitoring model parameters. For example, if the flue gas composition analyzer and flow sensor are functioning normally, but the flue gas treatment effect differs from the model prediction, the inspection unit can modify the monitoring sub-model parameters for the flue gas treatment phase based on the actual flue gas composition and flow data, as well as the processed flue gas emission data.

[0082] If the monitoring sub-model for the flue gas treatment stage is built based on a decision tree, it is used to predict the optimal flue gas treatment process parameters based on factors such as flue gas composition and flow rate. The inspection unit can adjust the branch conditions and leaf node values of the decision tree based on new data, allowing the model to more accurately recommend appropriate flue gas treatment process parameters based on actual flue gas conditions, thereby improving flue gas treatment efficiency and emission reduction effects.

[0083] The above is only a preferred embodiment of the present application. It should be pointed out that for ordinary technicians in this technical field, several improvements and replacements can be made without departing from the technical principles of the present application. These improvements and replacements should also be regarded as the scope of protection of the present application.

Claims

1. A boiler flue gas emission reduction control system, characterized in that: Including: A monitoring unit, a central control unit, and a patrol inspection unit; Among them, the central control unit is used to generate multiple boiler operation stages according to the boiler operation stage division and generate corresponding adjustment instructions; The monitoring unit includes multiple monitoring sub-modules, and the monitoring sub-modules are used to collect the monitoring data of each boiler operation stage and generate the monitoring data packets of each boiler operation stage; The patrol inspection unit includes multiple patrol inspection sub-modules, and the patrol inspection sub-modules are used to obtain the operation status of the boiler; The central control unit further includes: The first processing module is used to establish that the boiler operation stage includes a coal type pretreatment stage, a coal type combustion stage, and a flue gas treatment stage; The second processing module is used to establish corresponding monitoring sub-models based on each boiler operation stage; Among them, the second processing module is further used to generate corresponding adjustment instructions by combining the monitoring data packets of the monitoring sub-modules and the monitoring sub-models.

2. The boiler flue gas emission reduction control system according to claim 1, characterized in that: The second processing module is further used for: Based on the historical operation data of the coal preprocessing stage, the coal types are classified to generate the coal type sequence A, A=(a1, a2…a i …a n ); Among them, a i is the i-th coal type; n is the number of coal types; Establish the i-th coal type a i Coal samples of combustion state set D; Type a of coal type i i The coal samples include: the current i-th coal type a i The combustion state set D, D=(d1,d2…d j …d m ); Among them, d j is the jth combustion state feature, and m is the total number of combustion state features; Combining the coal type samples of all coal type types to generate the monitoring sub-model of the coal type pretreatment stage; Establishing a coal type combustion state sample set based on the historical operation data of the coal type combustion stage; The coal combustion state sample set includes the flue gas data set Y generated by the current coal type under various combustion states, Y=(y1,y2…y x …y r ); Among them, y x is the reference value of the xth type of data in the flue gas, and r is the total number of data types in the flue gas; Combining all coal type combustion state sample sets to generate the monitoring sub-model of the coal type combustion stage; Setting a flue gas state preset value based on the historical operation data of the flue gas treatment stage; Classifying the flue gas based on the flue gas state preset value to generate multiple flue gas types; Setting corresponding adjustment instructions based on the flue gas types; Combining all flue gas types and the corresponding adjustment instructions to generate the monitoring sub-model of the flue gas treatment stage.

3. The boiler flue gas emission reduction control system according to claim 2, characterized in that: When setting the corresponding adjustment instructions based on the flue gas types, it further includes: Obtaining various pollutant types in the flue gas based on the historical flue gas data; Obtaining the concentration range reference value of each pollutant; Setting the corresponding pollutant concentration preset value H, H=(h1, h2) based on the current pollutant concentration range reference value; Among them, h1 is the first preset value of the current pollutant type in the flue gas, and h2 is the second preset value of the current pollutant type in the flue gas; Dividing the current pollutant concentration level based on the pollutant concentration preset value H; If Hx < h1, the current pollutant concentration is the first-level pollutant concentration; If h1 ≤ Hx ≤ h2, the current pollutant concentration is the second-level pollutant concentration; If h2 < Hx, the current pollutant concentration is the third-level pollutant concentration; Hx is the actually measured concentration of the current pollutant in the flue gas; The flue gas type set E is set based on the pollutant concentration levels of various pollutant types in the current flue gas, E=(e1, e2…e ai …e an ); Among them, e a1 is the ai-th flue gas type, and an is the total number of flue gas types; Setting the corresponding flue gas treatment instructions based on each flue gas type.

4. The boiler flue gas emission reduction control system according to claim 3, characterized in that: When generating the corresponding adjustment instructions by combining the monitoring data packets of the monitoring sub-modules and the monitoring sub-models, it further includes: Generating the feature data sets Ti (i = 1, 2, 3) of each boiler operation stage based on the monitoring data packets of each monitoring sub-module at the current monitoring time node; Among them, T1 is the feature data set of the coal type pretreatment stage, T2 is the feature data set of the coal type combustion stage, and T3 is the feature data set of the flue gas treatment stage; Determining the flue gas type at the current monitoring time node by combining the feature data sets Ti of each boiler operation stage and the monitoring sub-model of the corresponding boiler operation stage; Generating the corresponding preliminary flue gas treatment instructions by combining the flue gas type at the current monitoring time node and the monitoring sub-model of the flue gas treatment stage; The flue gas treatment instruction is generated by combining the preliminary flue gas treatment instruction and the characteristic data set T3 of the flue gas treatment stage.

5. The boiler flue gas emission reduction control system according to claim 4, characterized in that: The flue gas type at the current monitoring time node also includes: Combine the characteristic data set T1 of the coal type preprocessing stage and the monitoring sub-model of the coal type preprocessing stage to generate the combustion state prediction interval q1 of the coal type, q1=(q1,q2…q j …q m ); Among them, q j =[q ja ,q jb ],q ja is the left endpoint of the j-th combustion state prediction interval, q jb is the right endpoint of the j-th combustion state prediction interval, and m is the total number of combustion state features; The monitoring data package of the coal pre-processing stage is verified by combining the obtained combustion state prediction value and the characteristic data set T2 of the coal combustion stage; Based on the characteristic data set T2 of the coal combustion stage and the monitoring sub-model of the coal combustion stage, the first flue gas prediction interval p1 is generated, p1=(p1,p2…p x …p r ); Among them, p x =[p xa ,p xb ],p xa is the left endpoint of the prediction interval of the x-th type of flue gas data, p xb is the right endpoint of the prediction interval of the xth type of smoke data, and r is the total number of smoke data types; The monitoring data package of the coal combustion stage is verified by combining the first flue gas prediction value and the characteristic data set T3 of the flue gas treatment stage; The smoke type at the current monitoring time node is determined in combination with the obtained first smoke prediction interval p1.

6. The boiler flue gas emission reduction control system according to claim 5, characterized in that: The verification of the monitoring data packet of the coal pre-processing stage also includes: Based on the characteristic data set T2 of the coal combustion stage at the current monitoring time node, the corresponding combustion state reference value set q2 is obtained, q2=(q 21 ,q 22 …q 2j …q 2m ); Among them, q 2j is the reference value of the j-th combustion state; Count the number of items m1 of each combustion state reference value in the combustion state reference value set q2 that are within the corresponding combustion state prediction interval q1; Generate a first verification value m3 by combining the number of items m1 and the total number of combustion state features m; m3=k1*m1 / m; k1 is the first fixed coefficient; Compare m3 with the first verification value preset value mk; If m3>mk, it is judged that the monitoring data packet obtained in the coal type preprocessing stage is normal; If m3≤mk, it is determined that the monitoring data packet obtained in the coal type preprocessing stage is abnormal, and a coal type preprocessing warning instruction is generated.

7. The boiler flue gas emission reduction control system according to claim 6, characterized in that: When verifying the monitoring data packet of the coal combustion stage by combining the first flue gas prediction value and the characteristic data set T3 of the flue gas treatment stage, the method further includes: Based on the characteristic data set T3 of the flue gas treatment stage at the current monitoring time node, the corresponding flue gas data reference value set p2 is obtained, p2=(p 21 ,p 22 …p 2x …p 2r ); Among them, p 2x is the reference value of the xth type of flue gas data; Counting the number r1 of items of each smoke data reference value in the smoke data reference value set p2 that are within the corresponding first smoke prediction interval p1; Generate a first verification value r3 by combining the number of items r1 and the total number of smoke data types r; r3=k2*r1 / r; k2 is the second fixed coefficient; Compare r3 with the first verification value preset value rk; If r3>rk, it is judged that the monitoring data packet obtained during the coal combustion stage is normal; If r3≤rk, it is determined that the monitoring data packet obtained during the coal combustion stage is abnormal, and a coal combustion early warning instruction is generated.

8. The boiler flue gas emission reduction control system according to claim 7, characterized in that: When generating the corresponding preliminary flue gas treatment instruction in combination with the flue gas type at the current monitoring time node and the monitoring sub-model of the flue gas treatment stage, the method further includes: Preset smoke control instructions based on the smoke type obtained at the current monitoring time node; Based on the monitoring data packet of the flue gas treatment stage, the concentration level change data L of various pollutants in the flue gas during the execution of the flue gas control instruction is obtained, where L=(L1, L2); Among them, L1 is the concentration level of various pollutants obtained by the monitoring data packet, and L2 is the time when the corresponding pollutant concentration level changes; Determine whether the time L2 of the change of various pollutant concentration levels meets the preset interval (L aX ,L bX );L aX The left endpoint of the preset interval for the changing data, L bX Preset the right endpoint of the interval for the changing data; If it meets the requirements, keep running; If it does not meet the requirements, a flue gas treatment warning instruction will be generated.

9. The boiler flue gas emission reduction control system according to claim 8, characterized in that: The inspection unit is further used for: Based on the early warning instructions of each stage obtained by the central control unit, the device detection is carried out separately to determine whether there is any abnormality in the monitoring equipment; If there is no abnormality in the monitoring device, modify the corresponding sub-monitoring model parameters.

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