Method and system for evaluating and monitoring instability of working fluid flow in boiler heating surface tubes

Abstract

The application discloses a kind of boiler heating surface pipe working medium flow instability evaluation and monitoring method and system, the present application method includes: obtaining the original data of boiler at rated load and below running;According to the data normal range of boiler under stable load, remove abnormal data from original data;The load average in each time window is calculated, and the maximum value T of temperature pulsation period in each time window is obtained max , the relationship curve of different load average and component measuring point temperature pulsation period T max is established for target heating surface component;According to the relationship curve of different load average and component measuring point temperature pulsation period T max , determine the working medium unstable critical load value of target heating surface component.The present application aims to ensure the safe and stable operation of unit boiler by the change condition of heating surface pipe wall temperature pulsation period to the reliable, convenient and fast evaluation and monitoring of working medium flow instability.

Description

Technical Field

[0001] This invention relates to the field of safety operation assessment technology for thermal power units, specifically to a method and system for assessing and monitoring the instability of working fluid flow in boiler heating surface tubes. Background Technology

[0002] In recent years, new power systems have developed rapidly, and new energy power generation has been connected to the grid on a large scale. However, new energy sources are characterized by randomness, intermittency, and instability. Their increasing proportion puts greater pressure on the power grid for peak shaving, requiring thermal power units to fully utilize their peak-shaving capacity. This means that thermal power units need to quickly reduce their operating load from full or high load conditions to low load conditions. However, the unstable flow of the working fluid in the boiler heating tubes under low load conditions may lead to heat transfer deterioration, seriously affecting the safe and stable operation of the unit. Therefore, the problem of unstable working fluid flow in the heating tubes under low load conditions requires special attention.

[0003] The problem of flow instability is quite complex. Changes in the dryness of the working fluid on the heated surface cause changes in parameters such as the flow rate and pressure of the working fluid, which are related to mass flow rate and inlet subcooling. Currently, due to limitations in experimental conditions, it is not possible to conduct in-depth research on the flow instability of the working fluid on each heated surface under the deep peak-shaving condition of the entire boiler. The hydrodynamics of the boiler water-cooled wall has only been studied using empirical formulas, which has the problem of low detection accuracy and makes it difficult to meet the requirements for safe and stable operation of the unit. Summary of the Invention

[0004] The technical problem to be solved by this invention is to provide a method and system for assessing and monitoring the instability of working fluid flow in boiler heating surface tubes, addressing the aforementioned problems in the prior art. This invention uses the instability of the periodic change in the wall temperature pulsation of the heating surface tubes to preliminarily determine whether instability has occurred in the working fluid flow of the heating surface tubes under low-load operation conditions of thermal power unit boilers. It aims to provide a reliable, convenient, and rapid assessment and monitoring method, thus providing a reliable assessment and monitoring method for the safe and stable operation of unit boilers.

[0005] To solve the above-mentioned technical problems, the technical solution adopted by the present invention is as follows:

[0006] A method for assessing and monitoring the instability of working fluid flow in boiler heating surface tubes, comprising:

[0007] Step S1: Obtain raw data of the boiler operating at or below rated load. The raw data includes the corresponding load and the measuring point temperature of the target heating surface component under that load.

[0008] Step S2: Remove abnormal data from the original data based on the normal range of boiler data under stable load.

[0009] Step S3: Calculate the average load within each time window based on the raw data after removing outlier data, and obtain the maximum temperature fluctuation period T within each time window based on the measuring point temperature of the heated surface component within each time window. max Establish the average load value and component temperature fluctuation period T at different load points for the target heated surface component. max Relationship curve;

[0010] Step S4, based on the average value of different loads and the temperature fluctuation period T at the component measuring point. max The relationship curve determines the critical load value of the working fluid instability of the target heated surface component.

[0011] Optionally, step S4 includes:

[0012] Step S4.1, compare the average load of the target heated surface component with the temperature fluctuation period T at the component measuring point. max In the relationship curve, starting from the highest average load value, we iterate downwards, and each time we reach any nth average load value P... n Then calculate the average load P. n The average load P adjacent to this average load n-1 The temperature fluctuation period T at both measurement points max The period difference between them, and the average load P n The average load P adjacent to this average load n-1 The load difference between the two is used to calculate the nth average load P, and the absolute value of the period difference divided by the load difference is taken. n The corresponding absolute ratio Δ n ;

[0013] Step S4.2, for all nth load average values ​​P n The corresponding absolute ratio Δ n The absolute value of the average is taken to obtain the absolute ratio Δ. Avg For each of the nth load average values ​​P n The corresponding absolute ratio Δ n Combined with the average of absolute ratios Δ Avg Calculate the average load P for the nth load respectively. n Corresponding average load point K n ;

[0014] Step S4.3, compare the average load of the target heated surface component with the temperature fluctuation period T at the component measuring point. max In the relationship curve, start from the highest average load and traverse downwards until the first average load point greater than 1 is found, and the average load point corresponding to this average load point is taken as the critical load value of the working fluid instability of the heated surface component.

[0015] Optionally, in step S4.2, the average load point K n The expression for the computation function is:

[0016] K n =(Δ n -Δ Avg ) / Δ Avg ,

[0017] In the above formula, K n The average load P of the nth load n The average load point, Δ n The average load P of the nth load n The corresponding absolute ratio, Δ Avg It is the average of the absolute ratios of all load averages.

[0018] Optionally, removing abnormal data in step S2 refers to removing abnormal data from the original data whose load change rate exceeds a preset threshold, based on the normal range of the load change rate data of the boiler under stable load.

[0019] Optionally, the method further includes: performing steps S1 to S4 respectively for multiple heating surface components of the boiler to obtain the working fluid instability critical load value of the multiple heating surface components; taking the maximum value among the multiple working fluid instability critical load values ​​of the multiple heating surface components as the working fluid instability critical load value of the boiler; if the load of the boiler is lower than the working fluid instability critical load value of the boiler, determining whether to take specified intervention measures for the boiler; if specified intervention measures are taken for the boiler, allowing the boiler to operate under load; otherwise, prohibiting the boiler from operating under load.

[0020] Optionally, the intervention measures specified in step S102 include increasing the operating load or increasing part or all of the working fluid flow rate.

[0021] Optionally, the plurality of heated surface components include some or all of the following: water-cooled wall, wall-mounted superheater, low-temperature superheater, screen-type superheater, high-temperature superheater, low-temperature reheater, high-temperature reheater, and economizer.

[0022] Furthermore, the present invention also provides a system for assessing and monitoring the instability of working fluid flow in boiler heating surface tubes, comprising:

[0023] The raw data acquisition program unit is used to acquire raw data of the boiler operating at or below the rated load. The raw data includes the corresponding load and the measuring point temperature of the target heating surface component under that load.

[0024] The abnormal data filtering program unit is used to remove abnormal data from the original data based on the normal range of data from the boiler under stable load.

[0025] The relationship curve generation program unit is used to calculate the average load within each time window based on the raw data after removing outliers, and to obtain the maximum temperature fluctuation period T within each time window based on the measuring point temperature of the heated surface component within each time window. max Establish the average load value and component temperature fluctuation period T at different load points for the target heated surface component. max Relationship curve;

[0026] The critical load generation program unit is used to generate critical loads based on the average load value and the component measuring point temperature fluctuation period T. max The relationship curve determines the critical load value of the working fluid instability of the target heated surface component.

[0027] In addition, the present invention provides a system for assessing and monitoring the instability of working fluid flow in boiler heating surface tubes, including a microprocessor and a memory interconnected thereto, wherein the microprocessor is programmed or configured to execute the method for assessing and monitoring the instability of working fluid flow in boiler heating surface tubes.

[0028] Furthermore, the present invention also provides a computer-readable storage medium storing a computer program, the computer program being programmed or configured by a microprocessor to execute the method for assessing and monitoring the instability of the working fluid flow in the boiler heating surface tubes.

[0029] Compared with the prior art, the present invention has the following main advantages:

[0030] 1. During load reduction, the pulsation period is linearly related to the load. However, in actual operation, load fluctuations and changes in other parameters affect the working fluid pulsation period. The pulsation period changes slowly with the load, only significantly increasing under unstable conditions. This invention utilizes the fact that the working fluid pulsation period gradually increases as the load decreases from high to low. When the load decreases to a critical value, i.e., the working fluid is in an unstable state, the working fluid pulsation period increases significantly. This significant increase in the pulsation period is used to assess and monitor the unstable state of the working fluid. This invention uses the instability of the pulsation period of the heated surface tube temperature to preliminarily determine whether the working fluid flow in the heated surface tubes of a thermal power unit boiler is unstable under low-load operation conditions. This provides a reliable, convenient, and rapid assessment and monitoring method, offering a reliable assessment and monitoring tool for the safe and stable operation of the unit boiler.

[0031] 2. This invention enables real-time assessment and monitoring of the instability of the working fluid (such as water or steam) flow within the boiler's heating surface tubes by automatically measuring and monitoring the temperature pulsation cycle at all measuring points on the heating surface during boiler operation. This method eliminates the need for complex calculations and experiments to determine the unstable operating conditions of the working fluid flow within the heating surface tubes under deep peak-shaving full-load conditions in in-service boilers, and can accurately assess and monitor the safety of the working fluid flow within the heating surface tubes. Attached Figure Description

[0032] Figure 1 This is a schematic diagram of the basic process of the method in an embodiment of the present invention.

[0033] Figure 2 The load average value of the rear screen superheater and the end screen superheater in this embodiment of the invention is compared with the component measuring point temperature pulsation period T. max A schematic diagram of the relationship curve. Detailed Implementation

[0034] Taking a 300MW sub-regional unit boiler in a power plant in Hunan Province as an example, this invention provides a more detailed explanation of the method and system for assessing and monitoring the instability of working fluid flow in the boiler heating surface tubes.

[0035] like Figure 1 As shown, the method for assessing and monitoring the instability of the working fluid flow in the boiler heating surface tubes in this embodiment includes:

[0036] Step S1: Obtain raw data of the boiler operating at or below rated load. The raw data includes the corresponding load and the measuring point temperature of the target heating surface component under that load.

[0037] Step S2: Remove abnormal data from the original data based on the normal range of boiler data under stable load.

[0038] Step S3: Calculate the average load within each time window based on the raw data after removing outlier data, and obtain the maximum temperature fluctuation period T within each time window based on the measuring point temperature of the heated surface component within each time window. max Establish the average load value and component temperature fluctuation period T at different load points for the target heated surface component. max Relationship curve;

[0039] Step S4, based on the average value of different loads and the temperature fluctuation period T at the component measuring point. max The relationship curve determines the critical load value of the working fluid instability of the target heated surface component.

[0040] In step S1 of this embodiment, when obtaining the original data of the boiler operating at or below the rated load, the rated load of the unit where the boiler is located is 300MW. The original data of the boiler operating at or below the rated load includes the corresponding load and the measuring point temperature of the target heating surface component under the load. The data sampling frequency is 1 data point per minute to obtain the original sample data.

[0041] In step S2 of this embodiment, removing abnormal data refers to removing abnormal data from the original data whose load change rate exceeds a preset threshold, based on the normal range of the boiler's load change rate under stable load. For example, as an optional implementation, this embodiment specifically removes data when the load change rate exceeds 2 MW / min.

[0042] In step S3 of this embodiment, when calculating the average load within each time window based on the original data after removing abnormal data, data within a time window that is stable at 300MW is selected, and the calculated average load is 300.25MW. The TE80 temperature (°C) at the outlet tube wall temperature measurement point of the rear superheater is selected at the corresponding load and time in step S3. A temperature (°C) change curve between any measurement point on the heated surface component and the operating time is established using conventional methods. The maximum value of the temperature pulsation period T is calculated and recorded using conventional methods. max The time was 16 minutes. The above method was repeated to obtain the maximum temperature fluctuation period T corresponding to the average unit loads of 261.22MW, 214.31MW, 179.91MW, 149.88MW, 118.43MW, 103.97MW, and 88.98MW, respectively. max The time intervals are 16 min, 16 min, 19 min, 21 min, 24 min, 26 min, 27 min, and 42 min. The average load value and its corresponding temperature fluctuation period T of the heated surface components are recorded according to the above steps. max Conventional methods were used to establish the relationship between the average value of different loads and the temperature fluctuation period T at component measuring points. max The relationship curve. Figure 2 The load average value of the heat-receiving surface component and the temperature fluctuation period T at the component measuring point are examples in this embodiment of the invention. max The diagram illustrates the relationship between the average load values ​​of the heated surface components, including the rear superheater and the final superheater, and the temperature fluctuation period T at the component measuring points. max The relationship curves are shown, where the wall temperature of the rear superheater was measured at the 2BP-TE80 measuring point, and the wall temperature of the final superheater was measured at the 2BP-TE125 measuring point.

[0043] Step S4 in this embodiment includes:

[0044] Step S4.1, compare the average load of the target heated surface component with the temperature fluctuation period T at the component measuring point. max In the relationship curve, starting from the highest average load value, we iterate downwards, and each time we reach any nth average load value P... n Then calculate the average load P. n The average load P adjacent to this average load n-1 The temperature fluctuation period T at both measurement points maxThe period difference between them, and the average load P n The average load P adjacent to this average load n-1 The load difference between the two is used to calculate the nth average load P, and the absolute value of the period difference divided by the load difference is taken. n The corresponding absolute ratio Δ n ;

[0045] Step S4.2, for all nth load average values ​​P n The corresponding absolute ratio Δ n The absolute value of the average is taken to obtain the absolute ratio Δ. Avg For each of the nth load average values ​​P n The corresponding absolute ratio Δ n Combined with the average of absolute ratios Δ Avg Calculate the average load P for the nth load respectively. n Corresponding average load point K n ;

[0046] Step S4.3, compare the average load of the target heated surface component with the temperature fluctuation period T at the component measuring point. max In the relationship curve, start from the highest average load and traverse downwards until the first average load point greater than 1 is found, and the average load point corresponding to this average load point is taken as the critical load value of the working fluid instability of the heated surface component.

[0047] In step S4.2 of this embodiment, the average load point K n The expression for the computation function is:

[0048] K n =(Δ n -Δ Avg ) / Δ Avg ,

[0049] In the above formula, K n The average load P of the nth load n The average load point, Δ n The average load P of the nth load n The corresponding absolute ratio, Δ Avg This is the average of the absolute ratios of all load averages. Specifically, in this embodiment, the relationship curve established in step S3 is used in step S4, starting from the temperature pulsation period T at the high load point. max Pulsation period T near the average point of low load max The absolute value of the ratio of the difference to the corresponding load average difference is Δ1, which is 0. The pulsation period T between the minimum load and the average point of the adjacent high load is then calculated. maxThe absolute values ​​of the ratios of the differences to the average load values ​​are 0.064, 0.058, 0.1, 0.064, 0.069, and 1.001, respectively. Calculate the average values ​​Δ for all these values. Avg The value is 0.194. All average load points K are calculated in descending order of load. n =(Δ n -Δ Avg ) / Δ Avg The absolute values ​​are 1, 0.67, 0.7, 0.48, 0.67, 0.64, and 4.16, respectively. Among them, the absolute value of K7 is greater than 1. Therefore, the load value of 103.97MW is the critical load value for the instability of the working fluid of the rear screen superheater. When the load is lower than the critical load value of 103.97MW, the working fluid of the rear screen superheater is unstable and there is a serious risk to the operation safety.

[0050] Furthermore, the method in this embodiment also includes: performing steps S1 to S4 respectively for multiple heating surface components of the boiler to obtain the working fluid instability critical load values ​​of the multiple heating surface components; taking the maximum value among the multiple working fluid instability critical load values ​​of the multiple heating surface components as the working fluid instability critical load value of the boiler; if the boiler load is lower than the working fluid instability critical load value of the boiler, then determining whether to take specified intervention measures for the boiler; if specified intervention measures are taken for the boiler, then the boiler is allowed to operate under load; otherwise, the boiler is prohibited from operating under load. The specified intervention measures in step S102 of this embodiment include increasing the operating load and increasing part or all of the working fluid flow rate.

[0051] In this embodiment, multiple heating surface components include some or all of the following: water-cooled wall, wall-mounted superheater, low-temperature superheater, screen-type superheater, high-temperature superheater, low-temperature reheater, high-temperature reheater, and economizer. For different heating surface components, steps S1 to S4 are executed respectively to obtain the critical load values ​​of working fluid instability for multiple heating surface components. This includes establishing relationship curves for all heating surface components, including water-cooled walls, wall-mounted superheaters, low-temperature superheaters, screen-type superheaters, high-temperature superheaters, low-temperature reheaters, high-temperature reheaters, economizers, etc., and calculating and marking all absolute values ​​of Kn in order of load. Among them, only the absolute value of K7 at the outlet of the high-temperature superheater is 5.1, which is greater than 1, and is the same as the critical load value of the rear screen superheater, i.e., 103.97MW. This is the critical load value of working fluid instability for the boiler of this unit. When operating at a load below this critical load value, the working fluid of the boiler heating surface is unstable, which poses a serious operational safety risk. Effective measures should be taken in time to increase the operating load or increase the working fluid flow rate and prevent the heating surface from overheating. Otherwise, operation below this load is prohibited.

[0052] In summary, this embodiment proposes a method for assessing and monitoring the safety of working fluid flow instability, such as that of water or steam, within the heating surface tubes of a power plant boiler, which can lead to large-scale overheating and tube rupture. This method utilizes the pulsation of the working fluid within the heating surface tubes due to mass flow rate and pressure. As the pulsation period of the working fluid within the heating surface tubes changes with the load, this pulsation characteristic is ultimately reflected in the corresponding temperature pulsation at the tube wall measuring points. The pulsation periods of the working fluid within the heating surface tubes and the tube wall temperature are essentially consistent but opposite in phase. When the pulsation period of the tube wall temperature changes significantly, it indicates the severity of the working fluid flow instability. Therefore, the instability of the working fluid flow can be assessed and monitored through changes in the tube wall temperature pulsation period, providing a reliable, convenient, and rapid assessment and monitoring method to ensure the safe and stable operation of the unit boiler. Based on actual unit operating data and following the changes in unit operating conditions, this embodiment better identifies the unstable flow of the working fluid inside the boiler heating surface tubes. It can accurately assess and monitor the instability of the working fluid flow inside the heating surface tubes. The established method for assessing and monitoring the instability of the working fluid flow inside the boiler heating surface tubes by utilizing the periodic changes in the wall temperature pulsation of the heating surface tubes is applicable to the feasibility analysis and safety monitoring of deep peak shaving operation for all thermal power units.

[0053] Furthermore, corresponding entirely to the aforementioned method for assessing and monitoring the instability of working fluid flow in boiler heating surface tubes in this embodiment, this embodiment also provides a system for assessing and monitoring the instability of working fluid flow in boiler heating surface tubes, including:

[0054] The raw data acquisition program unit is used to acquire raw data of the boiler operating at or below the rated load. The raw data includes the corresponding load and the measuring point temperature of the target heating surface component under that load.

[0055] The abnormal data filtering program unit is used to remove abnormal data from the original data based on the normal range of data from the boiler under stable load.

[0056] The relationship curve generation program unit is used to calculate the average load within each time window based on the raw data after removing outliers, and to obtain the maximum temperature fluctuation period T within each time window based on the measuring point temperature of the heated surface component within each time window. max Establish the average load value and component temperature fluctuation period T at different load points for the target heated surface component. max Relationship curve;

[0057] The critical load generation program unit is used to generate critical loads based on the average load value and the component measuring point temperature fluctuation period T. max The relationship curve determines the critical load value of the working fluid instability of the target heated surface component.

[0058] Furthermore, corresponding entirely to the aforementioned method for assessing and monitoring the instability of working fluid flow in boiler heating surface tubes in this embodiment, this embodiment also provides a system for assessing and monitoring the instability of working fluid flow in boiler heating surface tubes, including a microprocessor and a memory interconnected thereto, wherein the microprocessor is programmed or configured to execute the method for assessing and monitoring the instability of working fluid flow in boiler heating surface tubes.

[0059] Furthermore, corresponding entirely to the aforementioned method for assessing and monitoring the instability of working fluid flow in boiler heating surface tubes in this embodiment, this embodiment also provides a computer-readable storage medium storing a computer program, which is used to be programmed or configured by a microprocessor to execute the method for assessing and monitoring the instability of working fluid flow in boiler heating surface tubes.

[0060] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-readable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code. This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create a machine for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to operate in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The functions specified in one or more boxes. These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable apparatus for implementing the process. Figure 1 One or more processes and / or boxes Figure 1The steps of the function specified in one or more boxes.

[0061] The above description is merely a preferred embodiment of the present invention. The scope of protection of the present invention is not limited to the above embodiments. All technical solutions falling within the scope of the present invention's concept are within the scope of protection of the present invention. It should be noted that for those skilled in the art, any improvements and modifications made without departing from the principles of the present invention should also be considered within the scope of protection of the present invention.

Claims

1. A method for assessing and monitoring the instability of working fluid flow in boiler heating surface tubes, characterized in that, include: Step S1: Obtain raw data of the boiler operating at or below rated load. The raw data includes the corresponding load and the measuring point temperature of the target heating surface component under that load. Step S2: Remove abnormal data from the original data based on the normal range of boiler data under stable load. Step S3: Calculate the average load within each time window based on the raw data after removing outlier data, and obtain the maximum temperature fluctuation period T within each time window based on the measuring point temperature of the heated surface component within each time window. max Establish the average load value and the component temperature fluctuation period T at the component measuring point for the target heated surface component. max Relationship curve; Step S4, based on the average value of different loads and the temperature fluctuation period T at the component measuring point. max The relationship curve is used to determine the critical load value of the working fluid instability of the target heated surface component; Step S4 includes: Step S4.1, compare the average load of the target heated surface component with the temperature fluctuation period T at the component measuring point. max In the relationship curve, starting from the highest average load value, we iterate downwards, and each time we reach any nth average load value P... n Then calculate the average load P. n Average load P n Adjacent load average P n-1 The temperature fluctuation period T at both measurement points max The period difference between them, and the average load P n Average load P n Adjacent load average P n-1 The load difference between the two is used to calculate the nth average load P, and the absolute value of the result after dividing the period difference by the load difference is taken. n The corresponding absolute ratio Δ n ; Step S4.2, for all nth load average values ​​P n The corresponding absolute ratio Δ n Take the average value to obtain the average absolute ratio Δ Avg For each of the nth load average values ​​P n The corresponding absolute ratio Δ n Combined with the average of absolute ratios Δ Avg Calculate the average load P for the nth load respectively. n Corresponding average load point K n ; Step S4.3, compare the average load of the target heated surface component with the temperature fluctuation period T at the component measuring point. max In the relationship curve, start from the highest average load and traverse downwards until the first average load point with an absolute value greater than 1 is found, and the average load value corresponding to this average load point is taken as the critical load value for the working fluid instability of the heated surface component.

2. The method for assessing and monitoring the instability of working fluid flow in boiler heating surface tubes according to claim 1, characterized in that, In step S4.2, the average load point K n The expression for the computation function is: K n =(D n -D Avg ) / D Avg , In the above formula, K n The average load P of the nth load n The average load point, Δ n The average load P of the nth load n The corresponding absolute ratio, Δ Avg It is the average of the absolute ratios of all load averages.

3. The method for assessing and monitoring the instability of working fluid flow in boiler heating surface tubes according to claim 1, characterized in that, In step S2, removing abnormal data refers to removing abnormal data from the original data whose load change rate exceeds a preset threshold, based on the normal range of the load change rate data of the boiler under stable load.

4. The method for assessing and monitoring the instability of working fluid flow in boiler heating surface tubes according to any one of claims 1 to 3, characterized in that, Also includes: For multiple heating surface components of the boiler, steps S1 to S4 are executed respectively to obtain the working fluid instability critical load value of multiple heating surface components. The maximum value among the working fluid instability critical load values ​​of multiple heating surface components is taken as the working fluid instability critical load value of the boiler. If the boiler load is lower than the working fluid instability critical load value of the boiler, it is determined whether to take the specified intervention measures for the boiler. If the specified intervention measures are taken for the boiler, the boiler is allowed to operate under load; otherwise, the boiler is prohibited from operating under load.

5. The method for assessing and monitoring the instability of working fluid flow in boiler heating surface tubes according to claim 4, characterized in that, The specified intervention measures include increasing the operating load and increasing part or all of the working fluid flow rate.

6. The method for assessing and monitoring the instability of working fluid flow in boiler heating surface tubes according to claim 4, characterized in that, The plurality of heated surface components include some or all of the following: water-cooled walls, wall-mounted superheaters, low-temperature superheaters, screen-type superheaters, high-temperature superheaters, low-temperature reheaters, high-temperature reheaters, and economizers.

7. A system for assessing and monitoring the instability of working fluid flow in boiler heating surface tubes, characterized in that, include: The raw data acquisition program unit is used to acquire raw data of the boiler operating at or below the rated load. The raw data includes the corresponding load and the measuring point temperature of the target heating surface component under that load. The abnormal data filtering program unit is used to remove abnormal data from the original data based on the normal range of data from the boiler under stable load. The relationship curve generation program unit is used to calculate the average load within each time window based on the raw data after removing outliers, and to obtain the maximum temperature fluctuation period T within each time window based on the measuring point temperature of the heated surface component within each time window. max Establish the average load value and the component temperature fluctuation period T at the component measuring point for the target heated surface component. max Relationship curve; The critical load generation program unit is used to generate critical loads based on the average load value and the component measuring point temperature fluctuation period T. max The relationship curve determines the critical load value for working fluid instability of the target heated surface component, including: step S4.1, comparing the average load of the target heated surface component with the temperature fluctuation period T at the component measuring point. max In the relationship curve, starting from the highest average load value, we iterate downwards, and each time we reach any nth average load value P... n Then calculate the average load P. n Average load P n Adjacent load average P n-1 The temperature fluctuation period T at both measurement points max The period difference between them, and the average load P n Average load P n Adjacent load average P n-1 The load difference between the two is used to calculate the nth average load P, and the absolute value of the result after dividing the period difference by the load difference is taken. n The corresponding absolute ratio Δ n Step S4.2, for all nth load average values ​​P n The corresponding absolute ratio Δ n Take the average value to obtain the average absolute ratio Δ Avg For each of the nth load average values ​​P n The corresponding absolute ratio Δ n Combined with the average of absolute ratios Δ Avg Calculate the average load P for the nth load respectively. n Corresponding average load point K n Step S4.3: The average load of the target heated surface component under different loads and the temperature fluctuation period T at the component measuring point. max In the relationship curve, start from the highest average load and traverse downwards until the first average load point with an absolute value greater than 1 is found, and the average load value corresponding to this average load point is taken as the critical load value for the working fluid instability of the heated surface component.

8. A system for assessing and monitoring the instability of working fluid flow in boiler heating surface tubes, comprising a microprocessor and a memory interconnected, characterized in that, The microprocessor is programmed or configured to perform the boiler heating surface tube working fluid flow instability assessment and monitoring method according to any one of claims 1 to 6.

9. A computer-readable storage medium storing a computer program, characterized in that, The computer program is used to be programmed or configured by a microprocessor to execute the method for assessing and monitoring the instability of working fluid flow in boiler heating surface tubes as described in any one of claims 1 to 6.

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