A method and system for evaluating the life of heating surface tubes of power station boilers

Abstract

The present invention provides a method and system for assessing the life of a heating surface tube of a power station boiler, belonging to the technical field of power station boilers, and specifically comprising: determining the similarity of monitoring data between a heated pipeline and different similar reference models and a monitoring temperature similarity model in the similar reference model based on the temperature monitoring similarity of different temperature monitoring points, obtaining the available life of different monitoring temperature similarity models, and determining the life assessment result of the heated pipeline in combination with the monitoring data similarity and parameter similarity of different monitoring temperature similarity models, thereby further ensuring the accuracy of the life assessment.

Description

Technical Field

[0001] The invention belongs to the technical field of power station boilers, and in particular relates to a method and system for evaluating the life of heating surface tubes of power station boilers. Background Art

[0002] Among the equipment in power plants, boilers occupy an important position. Together with steam turbines and generators, they are called the "three main engines" of power plants. At the same time, boilers are often the equipment that causes frequent accidents in power plants due to their complex structure, many pressure-bearing components, and changeable operating conditions. The accident rate of boilers is more than 40% of the entire thermal power units. Among them, the failure of boiler heating surface tubes is the primary reason for the forced shutdown of boilers. This makes how to achieve the boiler heating surface tubes a technical problem that needs to be solved urgently.

[0003] In order to solve the above technical problems, the invention patent CN202311036760.3 "A method for evaluating the life of a water-cooled wall of a flue-type waste heat boiler" calculates the comprehensive evaluation life of the water-cooled wall tube according to the remaining life of the water-cooled wall after thinning and the fatigue damage degree under fatigue load, thereby evaluating the life of the water-cooled wall of a flue-type waste heat boiler. However, it is not difficult to find the following technical problems through analysis:

[0004] Simply considering the thinning of the pipe wall cannot accurately realize the accurate assessment of the life of the heating surface pipe of the pipeline. Factors such as the thickening of the pipe wall oxide layer and stress inside the pipe will affect the life of the pipe. Therefore, simply considering a certain factor cannot accurately and comprehensively realize the accurate assessment of the actual life of the heating surface pipe.

[0005] In view of the above technical problems, the present invention provides a method and system for evaluating the life of heating surface tubes of a power station boiler. Summary of the invention

[0006] To achieve the purpose of the present invention, the present invention adopts the following technical solutions:

[0007] According to one aspect of the present invention, a method for assessing the life of heating surface tubes of a power station boiler is provided.

[0008] A method for assessing the life of a heating surface tube of a power station boiler, characterized by comprising:

[0009] S1 extracts life impact data of different dimensions of the heated pipe based on historical operation data of the power plant boiler, and determines the parameter similarity between the heated pipe and different reference models in the historical database and similar reference models according to the life impact data of different dimensions;

[0010] S2 obtains the monitored temperatures of different temperature monitoring points of the heated pipeline at different input flue gas temperatures, and determines the temperature monitoring similarities of the heated pipeline at different temperature monitoring points and different similar reference models based on similarities of the monitored temperatures at different input flue gas temperatures;

[0011] S3 determines the similarity of monitoring data of the heated pipeline and different similar reference models and the monitoring temperature similarity model in the similar reference model based on the temperature monitoring similarity of different temperature monitoring points;

[0012] S4: obtaining the available lifespans of different monitoring temperature similarity models, and determining the lifespan assessment result of the heated pipeline in combination with the monitoring data similarities of the different monitoring temperature similarity models and the parameter similarities.

[0013] The beneficial effects of the present invention are:

[0014] 1. According to the life impact data of different dimensions, the similarity of the parameters of the heated pipeline and different reference models in the historical database and the similar reference models are determined, which realizes the similarity of the parameters of the heated pipeline and different reference models from the perspective of life impact data of different dimensions, and lays the foundation for further life assessment of the heated pipeline based on the available life of similar reference models.

[0015] 2. The life assessment result of the heated pipeline is determined by monitoring the available life of the temperature similarity model and the similarity of the monitoring data and parameters of different monitoring temperature similarity models. It not only considers the impact of the accuracy of the available life due to the differences in the similarity of the monitoring data and parameters of different monitoring temperature similarity models, but also improves the accuracy of the life assessment result of the heated pipeline by comprehensively considering the available life of multiple monitoring temperature similarity models.

[0016] A further technical solution is that the dimensions of the life influencing data include overheating operation data in which the flue gas temperature is greater than a preset temperature and temperature mutation operation data in which the temperature drop rate is greater than a preset rate.

[0017] A further technical solution is that the method for determining the temperature monitoring similarity is:

[0018] Determining the temperature deviation of the monitored temperature of the heated pipe and the temperature monitoring point of the similar reference model at different input smoke temperatures based on similar situations of the monitored temperature at different input smoke temperatures;

[0019] The temperature monitoring similarity between the temperature monitoring point of the heated pipeline and the similar reference model is determined by the temperature deviation of the monitored temperature at different input flue gas temperatures.

[0020] A further technical solution is that the method for determining the life assessment result of the heated pipeline is:

[0021] Determining the comprehensive similarity between different monitoring temperature similarity models and the heated pipeline according to the similarity of the monitoring data of different monitoring temperature similarity models and the similarity of the parameters;

[0022] The weight values ​​of different monitoring temperature similarity models are determined based on the comprehensive similarity, and the life assessment result of the heated pipeline is determined in combination with the available lifespans of the different monitoring temperature similarity models.

[0023] A further technical solution is that the weight value of the monitoring temperature similarity model ranges from 0 to 1, wherein the greater the comprehensive similarity of the monitoring temperature similarity model, the greater the weight value of the monitoring temperature similarity model.

[0024] On the other hand, the present invention provides a system for assessing the life of heating surface tubes of a power station boiler, which adopts the above-mentioned method for assessing the life of heating surface tubes of a power station boiler, and is characterized in that it specifically includes:

[0025] Reference model screening module, similarity evaluation module, similar model screening module, result output module;

[0026] The reference model screening module is responsible for extracting life impact data of different dimensions of the heated pipe based on the historical operation data of the heated pipe of the power plant boiler, and determining the parameter similarity between the heated pipe and different reference models in the historical database and similar reference models according to the life impact data of different dimensions;

[0027] The similarity evaluation module is responsible for obtaining the monitored temperatures of different temperature monitoring points of the heated pipeline at different input flue gas temperatures, and determining the temperature monitoring similarities of the heated pipeline at different temperature monitoring points and different similar reference models based on the similarities of the monitored temperatures at different input flue gas temperatures;

[0028] The similarity model screening module is responsible for determining the similarity of the monitoring data of the heated pipeline and different similar reference models and the monitoring temperature similarity model in the similar reference model based on the temperature monitoring similarity of different temperature monitoring points;

[0029] The result output module is responsible for obtaining the available life of different monitoring temperature similarity models, and determining the life assessment result of the heated pipeline in combination with the monitoring data similarity of different monitoring temperature similarity models and the parameter similarity.

[0030] Other features and advantages will be described in the following description, and partly become apparent from the description, or understood by practicing the invention. The purpose and other advantages of the invention are realized and obtained by the structures particularly pointed out in the description and the drawings.

[0031] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, preferred embodiments are given below and described in detail with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] The above and other features and advantages of the present invention will become more apparent by describing in detail exemplary embodiments thereof with reference to the attached drawings.

[0033] Figure 1 It is a flow chart of a method for assessing the life of heating surface tubes of a power station boiler;

[0034] Figure 2 is a flow chart of a method for determining the degree of parameter similarity;

[0035] Figure 3 It is a flow chart of a method for determining the similarity of monitoring data of a heated pipeline and a similar reference model. DETAILED DESCRIPTION

[0036] Example embodiments will now be described more fully with reference to the accompanying drawings. However, example embodiments can be implemented in a variety of forms and should not be construed as limited to the embodiments set forth herein; rather, these embodiments are provided so that the present invention will be comprehensive and complete and fully convey the concepts of the example embodiments to those skilled in the art. The same reference numerals in the figures represent the same or similar structures, and thus their detailed description will be omitted.

[0037] The terms "a", "an", "the", and "said" are used to indicate the presence of one or more elements / components / etc.; the terms "comprising" and "having" are used to express an open-ended inclusive meaning and mean that additional elements / components / etc. may be present in addition to the listed elements / components / etc.

[0038] Example 1

[0039] To solve the above problems, according to one aspect of the present invention, Figure 1 According to one aspect of the present invention, a method for evaluating the life of a heating surface tube of a power plant boiler is provided, which is characterized by specifically comprising:

[0040] S1 extracts life impact data of different dimensions of the heated pipe based on historical operation data of the power plant boiler, and determines the parameter similarity between the heated pipe and different reference models in the historical database and similar reference models according to the life impact data of different dimensions;

[0041] Furthermore, the dimensions of the life-influencing data include overheating operation data in which the flue gas temperature is greater than a preset temperature and temperature mutation operation data in which the temperature drop rate is greater than a preset rate.

[0042] Specifically, Figure 2 As shown, the method for determining the degree of similarity of the parameters is:

[0043] Determining superheating operation data of the heated pipeline based on the life impact data, and determining the similarity of superheating parameters between the heated pipeline and the reference model according to the superheating operation data;

[0044] Acquiring temperature mutation operation data of the heated pipeline, and determining the similarity of mutation parameters between the heated pipeline and the reference model according to the temperature mutation operation data;

[0045] The operation time data of the heated pipeline is obtained, and the parameter similarity between the heated pipeline and the reference model is determined in combination with the superheat parameter similarity and the mutation parameter similarity.

[0046] Further, the overheating operation data includes the operation time at different operation temperatures in the overheating state.

[0047] It should be noted that when the degree of similarity of the parameters of the reference model meets the requirements, the reference model is determined to be a similar reference model.

[0048] It should also be noted that the method for determining the degree of similarity of the parameters is:

[0049] Determine the superheat operation data of the heated pipe based on the life impact data, and determine the cumulative operation time at different superheat temperatures according to the superheat operation data, and judge whether the reference model has a superheat temperature whose cumulative operation time deviation does not meet the requirement, if so, determine that the reference model does not belong to a similar reference model, if not, proceed to the next step;

[0050] Determine the accumulated operation time of the heated pipeline in different change rate intervals based on the temperature mutation operation data of the heated pipeline, and judge whether the reference model has a change rate interval in which the deviation of the accumulated operation time does not meet the requirement, if so, determine that the reference model does not belong to the similar reference model, if not, proceed to the next step;

[0051] Determine the similarity of superheat parameters between the heated pipe and the reference model according to the superheat operation data, and judge whether the superheat parameter similarity meets the requirements, if yes, proceed to the next step, if no, determine that the reference model does not belong to the similar reference model;

[0052] The similarity of the mutation parameters between the heated pipeline and the reference model is determined according to the temperature mutation operation data, the operation time data of the heated pipeline is obtained, and the parameter similarity between the heated pipeline and the reference model is determined in combination with the superheat parameter similarity and the mutation parameter similarity.

[0053] It should also be noted that the method for determining the degree of similarity of the parameters is:

[0054] Acquire the running time data of the heated pipeline, and determine whether the deviation between the running time of the heated pipeline and the reference model meets the requirement, if so, proceed to the next step, if not, determine that the reference model does not belong to the similar reference model;

[0055] Determine the superheat operation data of the heated pipe based on the life impact data, determine the accumulated operation time at different superheat temperatures based on the superheat operation data, determine the data similarity between the heated pipe and the reference model at different superheat temperatures based on the accumulated operation time, and judge whether the number of superheat temperatures whose data similarity does not meet the requirement meets the requirement, if yes, proceed to the next step, if no, determine that the reference model does not belong to the similar reference model;

[0056] Determine the accumulated operation time of the heated pipeline in different change rate intervals based on the temperature mutation operation data of the heated pipeline, and determine the similarity of the mutation parameters of the heated pipeline and the reference model according to the accumulated operation time in different change rate intervals, and judge whether the similarity of the mutation parameters meets the requirements, if yes, proceed to the next step, if not, determine that the reference model does not belong to the similar reference model;

[0057] Determine the similarity of superheat parameters between the heated pipeline and the reference model according to the superheat operation data, determine the similarity of superheat parameters between the heated pipeline and the reference model, and judge whether the similarity of superheat parameters meets the requirements, if yes, proceed to the next step, if no, determine that the reference model does not belong to the similar reference model;

[0058] The operation time data of the heated pipeline is obtained, and the parameter similarity between the heated pipeline and the reference model is determined in combination with the superheat parameter similarity and the mutation parameter similarity.

[0059] S2 obtains the monitored temperatures of different temperature monitoring points of the heated pipeline at different input flue gas temperatures, and determines the temperature monitoring similarities of the heated pipeline at different temperature monitoring points and different similar reference models based on similarities of the monitored temperatures at different input flue gas temperatures;

[0060] Specifically, the method for determining the temperature monitoring similarity is:

[0061] Determining the temperature deviation of the monitored temperature of the heated pipe and the temperature monitoring point of the similar reference model at different input smoke temperatures based on similar situations of the monitored temperature at different input smoke temperatures;

[0062] The temperature monitoring similarity between the temperature monitoring point of the heated pipeline and the similar reference model is determined by the temperature deviation of the monitored temperature at different input flue gas temperatures.

[0063] S3 determines the similarity of monitoring data of the heated pipeline and different similar reference models and the monitoring temperature similarity model in the similar reference model based on the temperature monitoring similarity of different temperature monitoring points;

[0064] Specifically, Figure 3 As shown, the method for determining the similarity between the monitoring data of the heated pipeline and the similar reference model is:

[0065] Determine the deviation temperature monitoring points and similar temperature monitoring points among the temperature monitoring points based on the temperature monitoring similarities of different temperature monitoring points;

[0066] Determine the temperature deviation of the deviation temperature monitoring point by the number of the deviation temperature monitoring points and the temperature monitoring similarity of different deviation temperature monitoring points, and determine the temperature similarity of the similar temperature monitoring points by the number of the similar temperature monitoring points and the temperature monitoring similarity of different similar temperature monitoring points;

[0067] The similarity of the monitoring data between the heated pipeline and a similar reference model is determined by the temperature deviation of the deviation temperature monitoring point and the temperature similarity of the similar temperature monitoring point.

[0068] A further technical solution is that the similarity of the monitoring data of the heated pipeline and a similar reference model is constructed using a prediction model based on a BiLSTM-RF model.

[0069] The following are the basic steps of the BiLSTM-RF model:

[0070] (1) Data preparation: First, the power load data needs to be collected and preprocessed. Preprocessing includes data cleaning, data normalization, data smoothing and other operations. Then the data set is divided into a training set and a test set.

[0071] (2) Feature extraction: The BiLSTM model is used to extract features from input data. The BiLSTM model is a model based on a recurrent neural network (RNN) that can process data with a time series relationship. It can use both forward and backward information for feature extraction and is suitable for processing time series data. The input of the BiLSTM model is the power load time series data, and the output is the extracted feature sequence.

[0072] (3) Feature selection: Since the features extracted by BiLSTM may contain redundancy and noise, feature selection is required. The purpose of feature selection is to remove useless features and improve the prediction accuracy of the model.

[0073] (4) Training the RF model: The features extracted by BiLSTM are used to train the RF model. RF is an integrated learning method based on decision trees, which can be applied to regression, classification and other problems. The input of the RF model is the features extracted by BiLSTM, and the output is the predicted value of the power load.

[0074] (5) Model evaluation: The BiLSTM-RF model is evaluated using the test set.

[0075] Furthermore, the input gate of the LSTM algorithm: controls the input of information. The function of the input gate is to determine which information needs to be input into the memory unit.

[0076] The input gate generates a vector between 0 and 1 based on the current input and the state of the previous moment, representing the importance of the input in each dimension. The greater the importance of the input, the greater the degree of information input into the memory unit.

[0077]

[0078] Further, when the similarity between the similar reference model and the monitoring data of the heated pipeline is greater than a preset similarity threshold, the similar reference model is determined to be a monitoring temperature similarity model.

[0079] In another embodiment, the method for determining the similarity between the monitoring data of the heated pipeline and the similar reference model is:

[0080] Determine the deviation temperature monitoring points and similar temperature monitoring points among the temperature monitoring points based on the temperature monitoring similarity of different temperature monitoring points, and judge whether the number of the deviation temperature monitoring points meets the requirement, if so, proceed to the next step, if not, determine that the similar reference model does not belong to the monitoring temperature similarity model;

[0081] Determine the temperature deviation of the deviation temperature monitoring point by the number of the deviation temperature monitoring points and the temperature monitoring similarity of different deviation temperature monitoring points, and judge whether the temperature deviation of the deviation temperature monitoring point meets the requirement, if so, proceed to the next step, if not, determine that the similar reference model does not belong to the monitoring temperature similarity model;

[0082] Determine the number of deviation temperature monitoring points in different unit length intervals of the heated pipeline based on the distribution of deviation temperature monitoring points in the heated pipeline, and judge whether the number of unit length intervals with deviation temperature monitoring points meets the requirement. If yes, proceed to the next step; if not, determine that the similar reference model does not belong to the monitoring temperature similarity model.

[0083] The temperature similarity of the similar temperature monitoring points is determined by the number of the similar temperature monitoring points and the temperature monitoring similarities of different similar temperature monitoring points, and the similarity of the monitoring data of the heated pipeline and the similar reference model is determined by the temperature deviation of the deviation temperature monitoring point and the temperature similarity of the similar temperature monitoring points.

[0084] In another embodiment, the method for determining the similarity between the monitoring data of the heated pipeline and the similar reference model is:

[0085] Determine the average value of the temperature monitoring similarities of different temperature monitoring points of the heated pipeline and the similar reference model based on the temperature monitoring similarities of different temperature monitoring points, and judge whether the average value of the temperature monitoring similarities of different temperature monitoring points of the heated pipeline and the similar reference model meets the requirements, if yes, proceed to the next step, if not, determine that the similar reference model does not belong to the monitoring temperature similarity model;

[0086] Determine the deviation temperature monitoring points and similar temperature monitoring points among the temperature monitoring points based on the temperature monitoring similarity of different temperature monitoring points, and divide the heated pipe into a plurality of unit length intervals according to the unit length, and judge whether the number of unit length intervals with deviation temperature monitoring points meets the requirement, if yes, proceed to the next step, if not, determine that the similar reference model does not belong to the monitoring temperature similarity model;

[0087] Determine the interval temperature similarity of different unit length intervals according to the number of deviation temperature monitoring points of different unit length intervals and the temperature monitoring similarity of different deviation temperature monitoring points, the number of similar temperature monitoring points and the temperature monitoring similarity of different similar temperature monitoring points, and judge whether the number of unit length intervals whose interval temperature similarity does not meet the requirement meets the requirement, if so, proceed to the next step, if not, determine that the similar reference model does not belong to the monitoring temperature similarity model;

[0088] The number of the deviation temperature monitoring points in different unit length intervals of the heated pipeline is determined by the distribution of the deviation temperature monitoring points in the heated pipeline, the temperature similarity of the similar temperature monitoring points is determined by the number of the similar temperature monitoring points and the temperature monitoring similarity of different similar temperature monitoring points, and the similarity of the monitoring data of the heated pipeline and a similar reference model is determined by the temperature deviation of the deviation temperature monitoring points, the temperature similarity of the similar temperature monitoring points, and the interval temperature similarity of different unit length intervals.

[0089] S4: obtaining the available lifespans of different monitoring temperature similarity models, and determining the lifespan assessment result of the heated pipeline in combination with the monitoring data similarities of the different monitoring temperature similarity models and the parameter similarities.

[0090] Furthermore, the method for determining the life assessment result of the heated pipe is:

[0091] Determining the comprehensive similarity between different monitoring temperature similarity models and the heated pipeline according to the similarity of the monitoring data of different monitoring temperature similarity models and the similarity of the parameters;

[0092] The weight values ​​of different monitoring temperature similarity models are determined based on the comprehensive similarity, and the life assessment result of the heated pipeline is determined in combination with the available lifespans of the different monitoring temperature similarity models.

[0093] It should be noted that the weight value of the monitoring temperature similarity model ranges from 0 to 1, wherein the greater the comprehensive similarity of the monitoring temperature similarity model, the greater the weight value of the monitoring temperature similarity model.

[0094] In another embodiment, the method for determining the life assessment result of the heated pipe is:

[0095] Determining the comprehensive similarity between different monitoring temperature similarity models and the heated pipeline according to the similarity of the monitoring data of different monitoring temperature similarity models and the similarity of the parameters;

[0096] According to the deviation between the usable lifespans of different monitoring temperature similarity models, the monitoring temperature similarity models are divided into different usable life intervals, and it is determined whether there is an usable life interval in which the number of monitoring temperature similarity models accounts for more than a preset number of proportions. If so, the life assessment result of the heated pipe is determined based on the average value of the usable lifespans of different monitoring temperature similarity models in which the number of monitoring temperature similarity models accounts for more than a preset number of proportions. If not, proceed to the next step.

[0097] Determine the credibility of life data of different usable life intervals by the number of monitoring temperature similarity models of different usable life intervals and the comprehensive similarity between different monitoring temperature similarity models and the heated pipe, and judge whether there is a usable life interval whose life data credibility meets the requirement; if so, determine the life assessment result of the heated pipe based on the average value of the usable life of different monitoring temperature similarity models of the usable life interval whose life data credibility meets the requirement; if not, proceed to the next step;

[0098] The weight values ​​of different monitoring temperature similarity models are determined based on the comprehensive similarity, and the life assessment result of the heated pipeline is determined in combination with the available lifespans of the different monitoring temperature similarity models.

[0099] Example 2

[0100] On the other hand, the present invention provides a system for assessing the life of heating surface tubes of a power station boiler, which adopts the above-mentioned method for assessing the life of heating surface tubes of a power station boiler, and is characterized in that it specifically includes:

[0101] Reference model screening module, similarity evaluation module, similar model screening module, result output module;

[0102] The reference model screening module is responsible for extracting life impact data of different dimensions of the heated pipe based on the historical operation data of the heated pipe of the power plant boiler, and determining the parameter similarity between the heated pipe and different reference models in the historical database and similar reference models according to the life impact data of different dimensions;

[0103] The similarity evaluation module is responsible for obtaining the monitored temperatures of different temperature monitoring points of the heated pipeline at different input flue gas temperatures, and determining the temperature monitoring similarities of the heated pipeline at different temperature monitoring points and different similar reference models based on the similarities of the monitored temperatures at different input flue gas temperatures;

[0104] The similarity model screening module is responsible for determining the similarity of the monitoring data of the heated pipeline and different similar reference models and the monitoring temperature similarity model in the similar reference model based on the temperature monitoring similarity of different temperature monitoring points;

[0105] The result output module is responsible for obtaining the available life of different monitoring temperature similarity models, and determining the life assessment result of the heated pipeline in combination with the monitoring data similarity of different monitoring temperature similarity models and the parameter similarity.

[0106] Through the above embodiments, the present application achieves the following technical effects:

[0107] 1. According to the life impact data of different dimensions, the similarity of the parameters of the heated pipeline and different reference models in the historical database and the similar reference models are determined, which realizes the similarity of the parameters of the heated pipeline and different reference models from the perspective of life impact data of different dimensions, and lays the foundation for further life assessment of the heated pipeline based on the available life of similar reference models.

[0108] 2. The life assessment result of the heated pipeline is determined by monitoring the available life of the temperature similarity model and the similarity of the monitoring data and parameters of different monitoring temperature similarity models. It not only considers the impact of the accuracy of the available life due to the differences in the similarity of the monitoring data and parameters of different monitoring temperature similarity models, but also improves the accuracy of the life assessment result of the heated pipeline by comprehensively considering the available life of multiple monitoring temperature similarity models.

[0109] Each embodiment in this specification is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the device, equipment, and non-volatile computer storage medium embodiments, since they are basically similar to the method embodiments, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0110] The above is a description of a specific embodiment of the specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recorded in the claims can be performed in an order different from that in the embodiments and still achieve the desired results. In addition, the processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0111] The above description is only one or more embodiments of this specification and is not intended to limit this specification. For those skilled in the art, one or more embodiments of this specification may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of one or more embodiments of this specification shall be included in the scope of the claims of this specification.

Claims

1. A method for evaluating the life of heating surface tubes of a power station boiler, characterized in that: Specifically include: Extracting life impact data of different dimensions of the heated pipe based on historical operation data of the power station boiler, and determining the parameter similarity between the heated pipe and different reference models in the historical database and similar reference models according to the life impact data of different dimensions; Acquiring monitored temperatures of different temperature monitoring points of the heated pipeline at different input flue gas temperatures, and determining the temperature monitoring similarities of the heated pipeline at different temperature monitoring points and different similar reference models based on similarities of the monitored temperatures at different input flue gas temperatures; Determining the similarity of monitoring data of the heated pipeline and different similar reference models and the monitoring temperature similarity model in the similar reference model based on the temperature monitoring similarity of different temperature monitoring points; Obtaining the available life of different monitoring temperature similarity models, and determining the life assessment result of the heated pipeline in combination with the similarity of the monitoring data of the different monitoring temperature similarity models and the similarity of the parameters; The dimensions of the life-influencing data include overheating operation data where the flue gas temperature is greater than a preset temperature and temperature mutation operation data where the temperature drop rate is greater than a preset rate; The method for determining the life assessment result of the heated pipeline is: Determining the comprehensive similarity between different monitoring temperature similarity models and the heated pipeline according to the similarity of the monitoring data of different monitoring temperature similarity models and the similarity of the parameters; According to the deviation between the usable lifespans of different monitoring temperature similarity models, the monitoring temperature similarity models are divided into different usable life intervals, and it is determined whether there is an usable life interval in which the number of monitoring temperature similarity models accounts for more than a preset number of proportions. If so, the life assessment result of the heated pipe is determined based on the average value of the usable lifespans of different monitoring temperature similarity models in which the number of monitoring temperature similarity models accounts for more than a preset number of proportions. If not, proceed to the next step. Determine the credibility of life data of different usable life intervals by the number of monitoring temperature similarity models of different usable life intervals and the comprehensive similarity between different monitoring temperature similarity models and the heated pipe, and judge whether there is a usable life interval whose life data credibility meets the requirement; if so, determine the life assessment result of the heated pipe based on the average value of the usable life of different monitoring temperature similarity models of the usable life interval whose life data credibility meets the requirement; if not, proceed to the next step; The weight values ​​of different monitoring temperature similarity models are determined based on the comprehensive similarity, and the life assessment result of the heated pipeline is determined in combination with the available lifespans of the different monitoring temperature similarity models.

2. The method for evaluating the life of heating surface tubes of a power plant boiler according to claim 1, characterized in that: The method for determining the degree of similarity of the parameters is: Determining superheating operation data of the heated pipeline based on the life impact data, and determining the similarity of superheating parameters between the heated pipeline and the reference model according to the superheating operation data; Acquiring temperature mutation operation data of the heated pipeline, and determining the similarity of mutation parameters between the heated pipeline and the reference model according to the temperature mutation operation data; The operation time data of the heated pipeline is obtained, and the parameter similarity between the heated pipeline and the reference model is determined in combination with the superheat parameter similarity and the mutation parameter similarity.

3. The method for evaluating the life of heating surface tubes of a power plant boiler according to claim 2, characterized in that: The overheat operation data includes operation durations at different operation temperatures in an overheat state.

4. The method for evaluating the life of heating surface tubes of a power plant boiler according to claim 2, characterized in that: When the degree of similarity of the parameters of the reference model meets the requirement, the reference model is determined to be a similar reference model.

5. The method for evaluating the life of heating surface tubes of a power station boiler according to claim 1, characterized in that: The method for determining the temperature monitoring similarity is: Determining the temperature deviation of the monitored temperature of the heated pipe and the temperature monitoring point of the similar reference model at different input smoke temperatures based on similar situations of the monitored temperature at different input smoke temperatures; The temperature monitoring similarity between the temperature monitoring point of the heated pipeline and the similar reference model is determined by the temperature deviation of the monitored temperature at different input flue gas temperatures.

6. The method for evaluating the life of heating surface tubes of a power plant boiler according to claim 1, characterized in that: The method for determining the similarity between the monitoring data of the heated pipeline and the similar reference model is: Determine the deviation temperature monitoring points and similar temperature monitoring points among the temperature monitoring points based on the temperature monitoring similarities of different temperature monitoring points; Determine the temperature deviation of the deviation temperature monitoring point by the number of the deviation temperature monitoring points and the temperature monitoring similarity of different deviation temperature monitoring points, and determine the temperature similarity of the similar temperature monitoring points by the number of the similar temperature monitoring points and the temperature monitoring similarity of different similar temperature monitoring points; The similarity of the monitoring data between the heated pipeline and a similar reference model is determined by the temperature deviation of the deviation temperature monitoring point and the temperature similarity of the similar temperature monitoring point.

7. The method for evaluating the life of heating surface tubes of a power station boiler according to claim 6, characterized in that: When the similarity between the similar reference model and the monitoring data of the heated pipeline is greater than a preset similarity threshold, the similar reference model is determined to be a monitoring temperature similarity model.

8. The method for evaluating the life of heating surface tubes of a power plant boiler according to claim 1, characterized in that: The weight value of the monitoring temperature similarity model ranges from 0 to 1, wherein the greater the comprehensive similarity of the monitoring temperature similarity model, the greater the weight value of the monitoring temperature similarity model.

9. A power station boiler heating surface tube life assessment system, using a power station boiler heating surface tube life assessment method according to any one of claims 1 to 8, characterized in that: Specifically include: Reference model screening module, similarity evaluation module, similar model screening module, result output module; The reference model screening module is responsible for extracting life impact data of different dimensions of the heated pipe based on the historical operation data of the heated pipe of the power plant boiler, and determining the parameter similarity between the heated pipe and different reference models in the historical database and similar reference models according to the life impact data of different dimensions; The similarity evaluation module is responsible for obtaining the monitored temperatures of different temperature monitoring points of the heated pipeline at different input flue gas temperatures, and determining the temperature monitoring similarities of the heated pipeline at different temperature monitoring points and different similar reference models based on the similarities of the monitored temperatures at different input flue gas temperatures; The similarity model screening module is responsible for determining the similarity of the monitoring data of the heated pipeline and different similar reference models and the monitoring temperature similarity model in the similar reference model based on the temperature monitoring similarity of different temperature monitoring points; The result output module is responsible for obtaining the available life of different monitoring temperature similarity models, and determining the life assessment result of the heated pipeline in combination with the monitoring data similarity of different monitoring temperature similarity models and the parameter similarity.

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