A method, system, device and medium for pre-warning blockage of an air preheater

Abstract

The application discloses a kind of air preheater blockage early warning method, system, equipment and medium, wherein method includes: obtaining the historical operation data of thermal power generating unit in preset time period, and establish operation data correlation model according to the historical operation data;The operation data correlation model is used to indicate the relationship between the static pressure difference of air preheater inlet and outlet flue gas and the main steam flow in the thermal power generating unit in the preset time period;According to the operation data correlation model, the blockage monitoring evaluation standard of the air preheater is calculated, and the blockage coefficient of the air preheater is obtained;According to the blockage coefficient of the air preheater, the early warning level is determined.The application does not need additional equipment, by the establishment of air preheater operation key index historical correlation data model, real-time and accurately obtains air preheater blockage condition and predicts future any time blockage condition, and utilizes preset air preheater blockage operation mode expert experience model, timely guides adjustment operation mode.

Description

Technical Field

[0001] This invention relates to the field of equipment fault early warning technology, and in particular to a blockage early warning method, system, device and medium for air preheaters. Background Technology

[0002] Air preheaters are crucial equipment in coal-fired power plant boilers. Specifically, they are heat exchange surfaces where flue gas from the boiler's tail flue preheats the air entering the boiler to a specific temperature through internal heat exchange elements. This improves the boiler's heat exchange performance and reduces energy consumption. Nationwide, numerous coal-fired power units are undergoing ultra-clean emission retrofits to meet new environmental emission standards. However, while these units are operating at ultra-clean levels, varying degrees of air preheater blockage have occurred. The blockage is caused by the significant increase in unreacted ammonia during the ultra-clean reduction process. This escaped ammonia reacts with SO3 in the flue gas to form ammonium bisulfate. Liquid ammonium bisulfate is highly viscous and readily attracts fly ash from the flue gas, leading to accumulation and blockage within the air preheater, severely impacting the unit's normal operation.

[0003] Currently, air preheater blockage and early warning methods rely primarily on the following data signal sources: displacement signal sensors (CN111044275B), flue gas composition sensors (CN113217941 B), temperature signal sensors, and pressure signal sensors. However, the air preheater blockage monitoring method based on displacement signal sensors utilizes displacement sensors arranged in the flue gas flow direction at the air preheater inlet or outlet to monitor changes in the displacement signal of each pore in the air preheater heat exchange element, in order to determine whether the pore is currently blocked. This type of displacement signal sensor is greatly affected by the scouring effect of air or flue gas flow, and is prone to offset, resulting in inaccurate alignment with the pores of the air preheater heat exchange element, thus causing signal distortion. Secondly, the heat exchange element has numerous pores, requiring the installation of a large number of sensors, which inevitably affects the original structure of the air preheater. In contrast, the air preheater blockage monitoring method based on flue gas composition sensors and temperature sensors typically uses flue gas composition sensors located in the flue between the denitrification system outlet and the air preheater inlet, mainly measuring the content of NH3 (ammonia slip) and SO3. The degree of air preheater blockage is determined by establishing a correlation data model of parameters such as SO3 concentration, NH3 concentration, and flue gas temperature. This method requires real-time and accurate flue gas composition analysis, which can be achieved either by installing numerous online flue gas sensors for real-time analysis or by installing a flue gas extraction device for real-time extraction and analysis. The former is extremely costly, while the latter suffers from poor real-time performance due to rapid changes in flue gas composition.

[0004] Therefore, there is an urgent need for a solution to monitor the blockage of air preheaters in real time and effectively. Summary of the Invention

[0005] This invention provides a method, system, device, and medium for early warning of air preheater blockage, which aims to obtain the blockage status of air preheater in real time and accurately, and to predict the blockage status at any future time.

[0006] To achieve the above objectives, the first aspect of the present invention provides a method for early warning of blockage in an air preheater, comprising:

[0007] Historical operating data of the thermal power unit within a preset time period is obtained, and an operating data association model is established based on the historical operating data; the operating data association model is used to represent the relationship between the static pressure difference of the flue gas at the inlet and outlet of the air preheater and the main steam flow rate in the thermal power unit within the preset time period.

[0008] The blockage monitoring and evaluation criteria of the air preheater are calculated based on the operational data association model to obtain the blockage coefficient of the air preheater;

[0009] The warning level is determined based on the blockage coefficient of the air preheater.

[0010] Furthermore, historical operating data of thermal power units within a preset time period is acquired, and an operating data association model is established based on the historical operating data, including:

[0011] The inlet air temperature of the air preheater is calculated based on the historical operating data to obtain multiple sets of inlet air temperature data.

[0012] The multiple sets of inlet air temperature data are sorted according to size and classified according to preset temperature ranges to obtain multiple sets of inlet air temperature classification data.

[0013] For each group of inlet air temperature classification data, establish the relationship between the static pressure difference of flue gas at the inlet and outlet of the air preheater and the main steam flow rate in the thermal power unit to obtain the operation data association model.

[0014] Furthermore, based on the operational data association model, the blockage monitoring and evaluation criteria of the air preheater are calculated to obtain the blockage coefficient of the air preheater, including:

[0015] Obtain the real-time operating data of the thermal power unit;

[0016] The real-time operating data is input into the operating data association model for calculation to obtain the real-time air preheater reference flue gas side differential pressure.

[0017] The blockage coefficient of the air preheater is obtained by calculating the blockage monitoring and evaluation criteria of the air preheater based on the real-time reference flue gas differential pressure.

[0018] Furthermore, based on the real-time differential pressure of the reference flue gas side of the air preheater, the blockage monitoring and evaluation criteria of the air preheater are calculated to obtain the blockage coefficient of the air preheater, including:

[0019] Calculate the real-time flue gas differential pressure of the air preheater based on the real-time operating data;

[0020] The blockage coefficient of the air preheater is calculated based on the real-time flue gas differential pressure of the air preheater and the real-time flue gas differential pressure of the air preheater.

[0021] Furthermore, the warning level is determined based on the blockage coefficient of the air preheater, including:

[0022] The real-time clogging rate is calculated based on the clogging coefficient of the air preheater in the first time period and the clogging coefficient in the second time period; wherein the real-time clogging rate is calculated by the following formula:

[0023]

[0024] In the formula, v is the real-time congestion speed; Y is the sampling frequency; S is the congestion coefficient in the first time period; and S′ is the congestion coefficient in the second time period.

[0025] A second blockage coefficient is calculated based on the real-time blockage rate and the first blockage coefficient; wherein the first blockage coefficient is the blockage coefficient at the current moment, and the second blockage coefficient is the blockage coefficient of the air preheater at a future moment;

[0026] The warning level is determined based on the relationship between the second congestion coefficient and the preset threshold.

[0027] Furthermore, the preset thresholds include a first preset threshold, a second preset threshold, and a third preset threshold;

[0028] The step of determining the warning level based on the relationship between the second congestion coefficient and a preset threshold includes:

[0029] If the second congestion coefficient is less than the first preset threshold, then the warning level is the normal level;

[0030] If the second congestion coefficient is greater than the first preset threshold but not greater than the second preset threshold, then the warning level is a minor level.

[0031] If the second congestion coefficient is greater than the second preset threshold and not greater than the third preset threshold, then the warning level is moderate.

[0032] If the second congestion coefficient is greater than the third preset threshold, then the warning level is a severe level.

[0033] Furthermore, after determining the warning level based on the blockage coefficient of the air preheater, the method further includes:

[0034] The first blockage identifier is determined based on the first blockage coefficient;

[0035] The second blockage identifier is determined based on the second blockage coefficient;

[0036] Based on the difference between the first blockage identifier and the second blockage identifier, the corresponding expert recommendations from the expert recommendation model library are output.

[0037] A second aspect of the present invention provides a blockage warning system for an air preheater, comprising:

[0038] The correlation model establishment module is used to acquire historical operating data of thermal power units within a preset time period and establish an operating data correlation model based on the historical operating data; the operating data correlation model is used to represent the relationship between the static pressure difference of flue gas at the inlet and outlet of the air preheater and the main steam flow rate in the thermal power unit within the preset time period.

[0039] The evaluation criteria establishment module is used to calculate the blockage monitoring evaluation criteria of the air preheater based on the operation data association model, and obtain the blockage coefficient of the air preheater;

[0040] The warning level determination module is used to determine the warning level based on the blockage coefficient of the air preheater.

[0041] A third aspect of the present invention provides an electronic device including a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein the processor, when executing the computer program, implements a blockage warning method for an air preheater as described in any of the first aspects above.

[0042] A fourth aspect of the present invention provides a computer-readable storage medium comprising a stored computer program, wherein, when the computer program is executed, it controls the device on which the computer-readable storage medium is located to perform a blockage warning method for an air preheater as described in any one of the first aspects above.

[0043] Compared with the prior art, the beneficial effects of the embodiments of the present invention are as follows:

[0044] This invention provides a method, system, device, and medium for early warning of air preheater blockage. This method requires no additional equipment and, through the establishment of a historical correlation data model of key air preheater operating indicators, accurately and in real-time obtains the air preheater blockage status and predicts the blockage status at any future moment. Utilizing a pre-set expert experience model of air preheater blockage operation modes, it provides timely guidance for adjusting the operating mode. This invention establishes a new air preheater blockage monitoring and evaluation standard by establishing a correlation data model between the air preheater flue gas side differential pressure and the main steam flow rate, enabling real-time monitoring and early warning of air preheater blockage. Furthermore, it allows for both manual and automatic correction of the prediction results, improving prediction accuracy. Attached Figure Description

[0045] To more clearly illustrate the technical solution of the present invention, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0046] Figure 1 This is a flowchart of a blockage early warning method for an air preheater provided in a certain embodiment of the present invention;

[0047] Figure 2 This is a flowchart of step S1 provided in a certain embodiment of the present invention;

[0048] Figure 3 This is a flowchart of step S2 provided in a certain embodiment of the present invention;

[0049] Figure 4 This is a flowchart of step S23 provided in a certain embodiment of the present invention;

[0050] Figure 5 This is a flowchart of step S3 provided in a certain embodiment of the present invention;

[0051] Figure 6 This is a flowchart illustrating the expert advice output process provided in a certain embodiment of the present invention;

[0052] Figure 7 This is a device diagram of a blockage early warning system for an air preheater provided in a certain embodiment of the present invention;

[0053] Figure 8 This is a structural diagram of an electronic device provided in a certain embodiment of the present invention. Detailed Implementation

[0054] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings and examples. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0055] It should be understood that the step numbers used in the text are for ease of description only and are not intended to limit the order in which the steps are performed.

[0056] It should be understood that the terminology used in this specification is for the purpose of describing particular embodiments only and is not intended to limit the invention. As used in this specification and the appended claims, the singular forms “a,” “an,” and “the” are intended to include the plural forms unless the context clearly indicates otherwise.

[0057] The terms “comprising” and “including” indicate the presence of the described feature, whole, step, operation, element and / or component, but do not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components and / or collections thereof.

[0058] The term “and / or” refers to any combination of one or more of the associated listed items, as well as all possible combinations, and includes these combinations.

[0059] The present invention provides a blockage early warning method for air preheaters, which can be applied to, for example... Figure 1 The terminal or server shown. The terminal can be, but is not limited to, various personal computers, laptops, smartphones, tablets, and portable wearable devices, and the server can be a standalone server or a server cluster consisting of multiple servers.

[0060] In one embodiment, such as Figure 1 As shown, the first aspect of the present invention provides a method for early warning of blockage in an air preheater, comprising:

[0061] S1. Obtain historical operating data of the thermal power unit within a preset time period, and establish an operating data correlation model based on the historical operating data; the operating data correlation model is used to represent the relationship between the static pressure difference of the flue gas at the inlet and outlet of the air preheater and the main steam flow rate in the thermal power unit within the preset time period.

[0062] In one specific embodiment, such as Figure 2 As shown, step S1 includes:

[0063] S11. Calculate the inlet air temperature of the air preheater based on historical operating data to obtain multiple sets of inlet air temperature data;

[0064] S12. Sort multiple sets of inlet air temperature data according to size, and classify them according to preset temperature range to obtain multiple sets of inlet air temperature classification data;

[0065] S13. For each group of inlet air temperature classification data, establish the relationship between the static pressure difference of flue gas at the inlet and outlet of the air preheater and the main steam flow in the thermal power unit to obtain the operation data association model.

[0066] The preset time period is preferably one week. Multiple sets of historical operating data are collected within this preset time period. Each set of data includes a timestamp, main steam flow rate of the thermal power unit, static pressure of flue gas at the air preheater inlet, static pressure of flue gas at the air preheater outlet, primary air temperature at the air preheater inlet, secondary air temperature at the air preheater inlet, primary air mass flow rate at the air preheater inlet, and secondary air mass flow rate at the air preheater inlet. The inlet air temperature of the air preheater is calculated based on the historical operating data using the following formula:

[0067]

[0068] In the formula, Tair,in is the inlet air temperature of the air preheater, T1 is the inlet primary air temperature of the air preheater, m1 is the inlet primary air mass flow rate of the air preheater, T2 is the inlet secondary air temperature of the air preheater, and m2 is the inlet secondary air mass flow rate of the air preheater.

[0069] The collected data sets are categorized based on the inlet air temperature of the air preheater. The data sets are classified according to their Tair,in values, with each preset temperature interval ΔT representing the same data interval, for a total of i groups. For each group of categorized data, a relationship between the differential pressure on the flue gas side of the air preheater and the main steam flow rate is established, thus obtaining the operational data correlation model. The operational data correlation model is as follows:

[0070] ΔP = m·exp(aX+b)+n

[0071] In the formula, ΔP is the differential pressure of the flue gas side of the air preheater (i.e., the difference between the static pressure of the flue gas at the inlet of the air preheater and the static pressure of the flue gas at the outlet of the air preheater in each group of historical operating data), X is the main steam flow rate (i.e., the main steam flow rate in each group of historical operating data), and m, a, b, and n are all constants of the fitting function.

[0072] This invention requires no additional equipment installation. It establishes a correlation model based on historical data of key air preheater operating indicators to monitor the blockage of the air preheater, thereby improving the accuracy of early warning. By collecting historical data and classifying the air preheater inlet air temperature, it establishes a relationship between the differential pressure on the flue gas side of the air preheater and the main steam flow rate, and then builds a model. This is a brand-new early warning approach that requires no additional equipment installation and has strong real-time performance.

[0073] S2. Calculate the blockage monitoring and evaluation criteria of the air preheater based on the operation data association model to obtain the blockage coefficient of the air preheater;

[0074] In one specific embodiment, such as Figure 3 As shown, step S2 includes:

[0075] S21. Obtain real-time operating data of thermal power units;

[0076] S22. Input the real-time operating data into the operating data association model for calculation to obtain the real-time air preheater reference flue gas side differential pressure; wherein, the calculation formula for the real-time air preheater reference flue gas side differential pressure is:

[0077] ΔP0=m·exp(aX0+b)+n

[0078] In the formula, ΔP0 is the real-time reference flue gas differential pressure of the air preheater; X0 is the main steam flow rate of the thermal power unit in the real-time operating data;

[0079] S23. Calculate the blockage coefficient of the air preheater based on the real-time differential pressure of the reference flue gas side of the air preheater according to the blockage monitoring and evaluation standard of the air preheater.

[0080] Specifically, such as Figure 4 As shown, step S23 includes:

[0081] S231. Calculate the real-time flue gas differential pressure of the air preheater based on real-time operating data;

[0082] S232. Based on the real-time reference flue gas differential pressure and the real-time flue gas differential pressure of the air preheater, the blockage coefficient of the air preheater is calculated; the formula for calculating the blockage coefficient is:

[0083]

[0084] In the formula, S is the blockage coefficient; ΔP1 is the real-time flue gas differential pressure of the air preheater (i.e., the difference between the static pressure of the flue gas at the air preheater inlet and the static pressure of the flue gas at the air preheater outlet in the real-time data).

[0085] This invention establishes a new air preheater blockage monitoring and evaluation standard, which uses a blockage coefficient to quantify the degree of blockage in the air preheater. By summarizing patterns in historical data, this standard quantifies the real-time blockage of the air preheater and further predicts the blockage situation in the future, thus improving the accuracy of the prediction.

[0086] S3. Determine the warning level based on the blockage coefficient of the air preheater;

[0087] In one specific embodiment, such as Figure 5 As shown, step S3 includes:

[0088] S31. Calculate the real-time blocking velocity based on the blocking coefficients of the air preheater in the first time period and the second time period; the real-time blocking velocity is calculated using the following formula:

[0089]

[0090] In the formula, v is the real-time congestion speed; Y is the sampling frequency; S is the congestion coefficient in the first time period; and S′ is the congestion coefficient in the second time period.

[0091] The real-time congestion rate is the rate of change of the congestion coefficient over time output by the early warning algorithm proposed in this invention after the cumulative running time reaches the running threshold. The running threshold is usually 2 days. Therefore, the first time period is 24-48 hours within the running threshold, and the second time period is 0-24 hours within the running threshold.

[0092] S32. Based on the real-time congestion rate and the first congestion coefficient, calculate the second congestion coefficient; where the first congestion coefficient is the congestion coefficient at the current moment, and the second congestion coefficient is the congestion coefficient of the air preheater at a future moment; the second congestion coefficient is calculated using the following formula:

[0093]

[0094] In the formula, S1 is the second congestion coefficient; S0 is the first congestion coefficient; t1 is a future time; t0 is the current time;

[0095] S33. Determine the warning level based on the relationship between the second congestion coefficient and the preset threshold;

[0096] In one specific embodiment, the preset threshold includes a first preset threshold, a second preset threshold, and a third preset threshold; wherein, step S33 includes:

[0097] If the second congestion coefficient is less than the first preset threshold, the warning level is normal; if the second congestion coefficient is greater than the first preset threshold but not greater than the second preset threshold, the warning level is slight; if the second congestion coefficient is greater than the second preset threshold but not greater than the third preset threshold, the warning level is moderate; if the second congestion coefficient is greater than the third preset threshold, the warning level is severe.

[0098] The early warning algorithm proposed in this invention will issue an early warning at the current time t0 based on the air preheater coefficient S1 at time t1. The early warning level classification is shown in the table below:

[0099]

[0100]

[0101] The present invention establishes a correlation data model between the differential pressure on the flue gas side of the air preheater and the main steam flow rate to establish a new monitoring and evaluation standard for air preheater blockage, and monitors and warns of the air preheater blockage situation in real time; and warns of the blockage situation at a future moment, and can manually and automatically correct the prediction result to improve the prediction accuracy.

[0102] In a specific embodiment, as Figure 6 shown, after step S3, it includes:

[0103] S41. Determine the first blockage identifier according to the first blockage coefficient;

[0104] S42. Determine the second blockage identifier according to the second blockage coefficient;

[0105] S43. Output the corresponding expert advice in the expert advice model library according to the difference between the first blockage identifier and the second blockage identifier;

[0106] The early warning algorithm proposed by the present invention also pre-sets an expert experience model, which contains the expert's response suggestions for the air preheater blockage situation in different situations, and can provide guidance for actual operation. By comparing the real-time blockage coefficient and the predicted value of the blockage coefficient at a future moment with the expert experience model, the expert advice on the current operation mode of the air preheater can be obtained. The specific rules are as follows:

[0107] For the first blockage coefficient S0 at the current t0 moment, its corresponding first blockage identifier K0, and the second blockage coefficient S1 at the future t1 moment, and its corresponding second blockage identifier K1: when K0 = K1, output the expert advice for any corresponding interval of the two; when K0 < K1, it means that the blockage situation at the future moment worsens, and output the expert advice for the interval corresponding to S1; when K0 > K1, it means that the blockage situation at the future moment eases. Further, when K0 - K1 >= 2, no expert advice is output; when K0 - K1 = 1, output the expert advice for the interval corresponding to S0.

[0108] The early warning algorithm proposed by the present invention also has a manual correction function. When the air preheater of the unit is overhauled, or after any modification of the unit that may cause changes in the operating characteristics of the air preheater body, the manual correction function can be started. At this time, the early warning algorithm will automatically obtain the historical data after the change of the unit to update the correlation data model to ensure the accuracy of the evaluation standard.

[0109] This application proposes a blockage warning method for air preheaters, addressing the issues of existing air preheaters lacking a blockage warning mechanism and having inaccurate prediction results. This method achieves real-time monitoring and warning of air preheater blockage without requiring additional equipment. It establishes a correlation data model between the differential pressure on the flue gas side of the air preheater and the main steam flow rate to create a new air preheater blockage monitoring and evaluation standard. This allows for accurate real-time acquisition of air preheater blockage status and prediction of blockage at any future moment. Furthermore, it utilizes a pre-set expert experience model of air preheater blockage operation modes to guide timely adjustments to the operation mode. The method also allows for both manual and automatic correction of prediction results, improving prediction accuracy.

[0110] It should be noted that although the steps in the flowchart above are shown sequentially as indicated by the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified in this document, there is no strict order requirement for the execution of these steps, and they can be executed in other orders.

[0111] In another embodiment, such as Figure 7 As shown, a second aspect of the present invention provides a blockage warning system for an air preheater, comprising:

[0112] The correlation model establishment module 10 is used to acquire historical operating data of thermal power units within a preset time period and establish an operating data correlation model based on the historical operating data; the operating data correlation model is used to represent the relationship between the static pressure difference of flue gas at the inlet and outlet of the air preheater and the main steam flow rate in the thermal power unit within the preset time period.

[0113] The evaluation criteria establishment module 20 is used to calculate the air preheater blockage monitoring evaluation criteria based on the operation data association model, and obtain the air preheater blockage coefficient;

[0114] The warning level determination module 30 is used to determine the warning level based on the blockage coefficient of the air preheater.

[0115] It should be noted that the modules in the aforementioned congestion warning system based on an air preheater can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device, or stored in the memory of a computer device as software, so that the processor can call and execute the corresponding operations of each module. For specific limitations regarding the congestion warning system for an air preheater, please refer to the limitations regarding the congestion warning method for an air preheater described above; both have the same function and role, and will not be repeated here.

[0116] A third aspect of the present invention provides an electronic device comprising:

[0117] Processor, memory, and bus;

[0118] The bus is used to connect the processor and the memory;

[0119] The memory is used to store operation instructions;

[0120] The processor is configured to execute instructions by calling the operation instructions, causing the processor to perform operations corresponding to a blockage warning method for an air preheater as shown in the first aspect of this application.

[0121] In one alternative embodiment, an electronic device is provided, such as Figure 8 As shown, Figure 8 The illustrated electronic device 5000 includes a processor 5001 and a memory 5003. The processor 5001 and the memory 5003 are connected, for example, via a bus 5002. Optionally, the electronic device 5000 may also include a transceiver 5004. It should be noted that in practical applications, the transceiver 5004 is not limited to one type, and the structure of this electronic device 5000 does not constitute a limitation on the embodiments of this application.

[0122] Processor 5001 may be a CPU, a general-purpose processor, a DSP, an ASIC, an FPGA, or other programmable logic device, transistor logic device, hardware component, or any combination thereof. It may implement or execute the various exemplary logic blocks, modules, and circuits described in conjunction with the disclosure of this application. Processor 5001 may also be a combination that implements computational functions, such as including one or more microprocessor combinations, a combination of a DSP and a microprocessor, etc.

[0123] Bus 5002 may include a path for transmitting information between the aforementioned components. Bus 5002 may be a PCI bus or an EISA bus, etc. Bus 5002 can be divided into address bus, data bus, control bus, etc. For ease of representation, Figure 8 The bus is represented by a single thick line, but this does not mean that there is only one bus or one type of bus.

[0124] The memory 5003 may be a ROM or other type of static storage device capable of storing static information and instructions, RAM or other type of dynamic storage device capable of storing information and instructions, or it may be an EEPROM, CD-ROM or other optical disc storage, optical disc storage (including compressed optical discs, laser discs, optical discs, digital universal optical discs, Blu-ray discs, etc.), magnetic disk storage media or other magnetic storage devices, or any other medium capable of carrying or storing desired program code in the form of instructions or data structures and accessible by a computer, but is not limited thereto.

[0125] The memory 5003 is used to store application code that executes the scheme of this application, and its execution is controlled by the processor 5001. The processor 5001 is used to execute the application code stored in the memory 5003 to implement the content shown in any of the foregoing method embodiments.

[0126] Among them, electronic devices include, but are not limited to: mobile terminals such as mobile phones, laptops, digital radio receivers, PDAs (personal digital assistants), PADs (tablet computers), PMPs (portable multimedia players), and in-vehicle terminals (such as in-vehicle navigation terminals), as well as fixed terminals such as digital TVs and desktop computers.

[0127] The fourth aspect of the present invention provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements a blockage warning method for an air preheater as shown in the first aspect of the present application.

[0128] Another embodiment of this application provides a computer-readable storage medium storing a computer program that, when run on a computer, enables the computer to execute the corresponding content in the aforementioned method embodiments.

[0129] Furthermore, embodiments of the present invention also provide a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the above-described method.

[0130] In summary, this invention discloses a method, system, device, and medium for early warning of air preheater blockage. The method includes: acquiring historical operating data of a thermal power unit within a preset time period, and establishing an operating data correlation model based on the historical operating data; the operating data correlation model is used to represent the relationship between the static pressure difference of the flue gas at the inlet and outlet of the air preheater and the main steam flow rate in the thermal power unit within the preset time period; calculating the blockage monitoring and evaluation criteria of the air preheater based on the operating data correlation model to obtain the blockage coefficient of the air preheater; and determining the early warning level based on the blockage coefficient of the air preheater. This invention requires no additional equipment installation. By establishing a historical correlation data model of key air preheater operating indicators, it can accurately and in real time obtain the blockage status of the air preheater and predict the blockage status at any future moment. Furthermore, it utilizes a pre-set expert experience model of air preheater blockage operation mode to guide timely adjustments to the operating mode.

[0131] The various embodiments in this specification are described in a progressive manner. For directly identical or similar parts of the embodiments, refer to each other. Each embodiment focuses on its differences from other embodiments. In particular, the system embodiments are basically similar to the method embodiments, so the description is relatively simple; relevant parts can be referred to the descriptions in the method embodiments. It should be noted that the technical features of the above embodiments can be combined arbitrarily. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as the combination of these technical features does not contradict each other, it should be considered within the scope of this specification.

[0132] The embodiments described above are merely preferred embodiments of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of the invention patent. It should be noted that those skilled in the art can make various improvements and substitutions without departing from the technical principles of this invention, and these improvements and substitutions should also be considered within the scope of protection of this application. Therefore, the scope of protection of this patent application should be determined by the scope of the claims.

Claims

1. A method for early warning of blockage in an air preheater, characterized in that, include: Historical operating data of the thermal power unit within a preset time period is obtained, and an operating data correlation model is established based on the historical operating data. The operating data correlation model is used to represent the relationship between the static pressure difference of the flue gas at the inlet and outlet of the air preheater and the main steam flow rate in the thermal power unit within the preset time period. The operating data correlation model is as follows: In the formula, ΔP is the differential pressure on the flue gas side of the air preheater, which is the difference between the static pressure of the flue gas at the air preheater inlet and the static pressure of the flue gas at the air preheater outlet in each group of historical operating data, X is the main steam flow rate, and m, a, b, and n are all constants of the fitting function. The blockage coefficient of the air preheater is obtained by calculating the blockage monitoring and evaluation criteria of the air preheater according to the operation data association model. This includes: acquiring real-time operation data of the thermal power unit; inputting the real-time operation data into the operation data association model for calculation to obtain the real-time reference flue gas differential pressure of the air preheater; and calculating the blockage coefficient of the air preheater according to the blockage monitoring and evaluation criteria of the air preheater based on the real-time reference flue gas differential pressure of the air preheater. The warning level is determined based on the blockage coefficient of the air preheater.

2. The method for early warning of blockage in an air preheater according to claim 1, characterized in that, The step of acquiring historical operating data of thermal power units within a preset time period and establishing an operating data association model based on the historical operating data includes: The inlet air temperature of the air preheater is calculated based on the historical operating data to obtain multiple sets of inlet air temperature data. The multiple sets of inlet air temperature data are sorted according to size and classified according to preset temperature ranges to obtain multiple sets of inlet air temperature classification data. For each group of inlet air temperature classification data, establish the relationship between the static pressure difference of flue gas at the inlet and outlet of the air preheater and the main steam flow rate in the thermal power unit to obtain the operation data association model.

3. The method for early warning of blockage in an air preheater according to claim 1, characterized in that, The blockage coefficient of the air preheater is calculated based on the real-time reference flue gas differential pressure of the air preheater according to the blockage monitoring and evaluation criteria, including: Calculate the real-time flue gas differential pressure of the air preheater based on the real-time operating data; The blockage coefficient of the air preheater is calculated based on the real-time flue gas differential pressure of the air preheater and the real-time flue gas differential pressure of the air preheater.

4. The method for early warning of blockage in an air preheater according to claim 1, characterized in that, The step of determining the early warning level based on the blockage coefficient of the air preheater includes: The real-time clogging rate is calculated based on the clogging coefficient of the air preheater in the first time period and the clogging coefficient in the second time period; wherein the real-time clogging rate is calculated by the following formula: In the formula, For real-time congestion speed; S is the sampling frequency; S is the congestion coefficient in the first time period. The congestion coefficient during the second time period; A second blockage coefficient is calculated based on the real-time blockage rate and the first blockage coefficient; wherein the first blockage coefficient is the blockage coefficient at the current moment, and the second blockage coefficient is the blockage coefficient of the air preheater at a future moment; The warning level is determined based on the relationship between the second congestion coefficient and the preset threshold.

5. A method for early warning of blockage in an air preheater according to claim 4, characterized in that, The preset thresholds include a first preset threshold, a second preset threshold, and a third preset threshold; The step of determining the warning level based on the relationship between the second congestion coefficient and a preset threshold includes: If the second congestion coefficient is less than the first preset threshold, then the warning level is the normal level; If the second congestion coefficient is greater than the first preset threshold but not greater than the second preset threshold, then the warning level is a minor level. If the second congestion coefficient is greater than the second preset threshold and not greater than the third preset threshold, then the warning level is moderate. If the second congestion coefficient is greater than the third preset threshold, then the warning level is a severe level.

6. A method for early warning of blockage in an air preheater according to claim 4, characterized in that, After determining the warning level based on the blockage coefficient of the air preheater, the method further includes: The first blockage identifier is determined based on the first blockage coefficient; The second blockage identifier is determined based on the second blockage coefficient; Based on the difference between the first blockage identifier and the second blockage identifier, the corresponding expert recommendations from the expert recommendation model library are output.

7. A blockage early warning system for an air preheater, characterized in that, include: The correlation model establishment module is used to acquire historical operating data of the thermal power unit within a preset time period and establish an operating data correlation model based on the historical operating data. The operating data correlation model is used to represent the relationship between the static pressure difference of the flue gas at the inlet and outlet of the air preheater and the main steam flow rate in the thermal power unit within the preset time period. The operating data correlation model is as follows: In the formula, ΔP is the differential pressure on the flue gas side of the air preheater, which is the difference between the static pressure of the flue gas at the air preheater inlet and the static pressure of the flue gas at the air preheater outlet in each group of historical operating data, X is the main steam flow rate, and m, a, b, and n are all constants of the fitting function. The evaluation standard establishment module is used to calculate the blockage monitoring evaluation standard of the air preheater based on the operation data association model to obtain the blockage coefficient of the air preheater. This includes: acquiring real-time operation data of the thermal power unit; inputting the real-time operation data into the operation data association model for calculation to obtain the real-time air preheater reference flue gas side differential pressure; and calculating the blockage monitoring evaluation standard of the air preheater based on the real-time air preheater reference flue gas side differential pressure to obtain the blockage coefficient of the air preheater. The warning level determination module is used to determine the warning level based on the blockage coefficient of the air preheater.

8. An electronic device, characterized in that, It includes a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein the processor, when executing the computer program, implements the congestion warning method for an air preheater as described in any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium includes a stored computer program, wherein, when the computer program is executed, it controls the device on which the computer-readable storage medium is located to perform the air preheater blockage warning method as described in any one of claims 1 to 6.

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