Boiler heating surface early warning method and system based on multi-dimensional dynamic comparison

Abstract

The invention provides a boiler heating surface early warning method and system based on multi-dimensional dynamic comparison. The method comprises the following steps: constructing a multi-dimensional ledger database of a boiler heating surface; based on the multi-dimensional ledger database, utilizing a pre-trained ledger comparison model to carry out multi-dimensional dynamic comparative analysis to obtain a comparative analysis result; and generating corresponding risk early warning information according to the comparative analysis result, and visually displaying the risk early warning information. According to the boiler heating surface standing book comparison method, through real-time / historical data dynamic comparison, hidden defects such as heating surface pipe wall thickness reduction, over-temperature operation and creep over-limit are found in advance, and missing detection of manual troubleshooting is avoided. Meanwhile, the performance difference and the aging degree of the heating surfaces in different areas are quantified, empirical judgment is replaced, and effective data support is provided for maintenance strategies (such as pipe replacement / soot blowing adjustment).

Description

Technical Field

[0001] This invention relates to the field of boiler condition monitoring and fault early warning technology, and in particular to a boiler heating surface early warning method and system based on multi-dimensional dynamic comparison. Background Technology

[0002] Boiler heating surfaces are core components of power plant boilers, and their health directly affects the safe, stable, and economical operation of the unit. In thermal power generating units, boiler heating surfaces (such as water-cooled walls, superheaters, reheaters, economizers, etc.) operate in harsh environments of high temperature, high pressure, and corrosive flue gas for extended periods, making them high-risk areas for failure and malfunction. Therefore, accurate assessment and timely early warning of the heating surface condition are crucial for achieving predictive maintenance, preventing unplanned outages, and improving power generation efficiency. However, existing heating surface management models still have significant shortcomings, failing to fully utilize existing design, operation, and maintenance data, resulting in delayed condition awareness and crude risk assessment. Specifically, existing technologies mainly have the following problems that urgently need to be addressed: 1. Fragmented ledger data: Traditional ledgers are scattered across multiple systems in design, operation, and maintenance, leading to data silos and low comparison efficiency; 2. Delayed anomaly identification; 3. Crude risk assessment. Summary of the Invention

[0003] The purpose of this invention is to provide a boiler heating surface early warning method and system based on multi-dimensional dynamic comparison, aiming to solve the above-mentioned problems in the prior art.

[0004] This invention provides a boiler heating surface early warning method based on multi-dimensional dynamic comparison, comprising: Construct a multi-dimensional ledger database of boiler heating surfaces; Based on the multidimensional ledger database, a pre-trained ledger comparison model is used to perform multidimensional dynamic comparison analysis to obtain the comparison analysis results. Based on the comparative analysis results, corresponding risk warning information is generated and the risk warning information is visualized.

[0005] This invention provides a boiler heating surface early warning system based on multi-dimensional dynamic comparison, comprising: The data management module is used to build a multidimensional ledger database of boiler heating surfaces; The dynamic comparison module is used to perform multi-dimensional dynamic comparison analysis based on the multi-dimensional ledger database using a pre-trained ledger comparison model, and obtain the comparison analysis results. The risk warning module is used to generate corresponding risk warning information based on the comparative analysis results and to visualize the risk warning information.

[0006] This invention also provides an electronic device, including: a memory, a processor, and a computer program stored in the memory and executable on the processor. When the computer program is executed by the processor, it implements the steps of the above-described boiler heating surface early warning method based on multi-dimensional dynamic comparison.

[0007] This invention also provides a computer-readable storage medium storing an information transmission implementation program, which, when executed by a processor, implements the steps of the above-described boiler heating surface early warning method based on multi-dimensional dynamic comparison.

[0008] The embodiments of this invention can include the following beneficial effects: This invention proposes a method for comparing boiler heating surface records. Through dynamic comparison of real-time and historical data, it can detect hidden defects such as thinning of heating surface tube walls, overheating, and excessive creep in advance, avoiding missed inspections during manual checks. Simultaneously, it quantifies the performance differences and aging degrees of heating surfaces in different areas, replacing empirical judgment and providing effective data support for maintenance strategies (such as tube replacement / adjustment of soot blowing). Attached Figure Description

[0009] To more clearly illustrate the technical solutions in one or more embodiments of this specification or in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in this specification. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0010] Figure 1 This is a flowchart of a boiler heating surface early warning method based on multi-dimensional dynamic comparison according to an embodiment of the present invention; Figure 2 This is a schematic diagram of a boiler heating surface early warning system based on multi-dimensional dynamic comparison, according to an embodiment of the present invention. Detailed Implementation

[0011] To enable those skilled in the art to better understand the technical solutions in one or more embodiments of this specification, the technical solutions in one or more embodiments of this specification will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this specification, and not all of the embodiments. Based on one or more embodiments of this specification, all other embodiments obtained by those skilled in the art without creative effort should fall within the protection scope of this document.

[0012] Method Implementation Examples According to embodiments of the present invention, a method for early warning of boiler heating surfaces based on multi-dimensional dynamic comparison is provided. Figure 1 This is a flowchart of a boiler heating surface early warning method based on multi-dimensional dynamic comparison according to an embodiment of the present invention, as shown below. Figure 1 As shown, the boiler heating surface early warning method based on multi-dimensional dynamic comparison according to an embodiment of the present invention specifically includes: Step S101, construct a multidimensional ledger database for the boiler heating surfaces, specifically including: A multi-dimensional ledger database is constructed based on the design parameters of the boiler heating surface, operation monitoring data, and maintenance records. The data structure of the multidimensional ledger database includes at least four levels: system, region, pipe panel, and single pipe. Its data fields include at least pipe specifications, temperature / pressure operating curves, creep deformation, and defect records. The pipe specifications include pipe diameter, wall thickness, and material.

[0013] Step S102: Based on the multidimensional ledger database, a multidimensional dynamic comparative analysis is performed using a pre-trained ledger comparison model to obtain the comparative analysis results. The multi-dimensional dynamic comparative analysis includes at least: longitudinal time-series comparison and horizontal regional comparison; The longitudinal time series comparison involves calculating and analyzing the rate of change of parameters in the same heated surface region at different time points. The horizontal region comparison is a consistency analysis of the parameters of different tube panels or tube groups in the same type of heating surface.

[0014] The parameter change rate in the longitudinal time series comparison includes at least one of the following: wall thickness reduction rate, pipe diameter expansion rate, and temperature deviation trend. The consistency analysis in the lateral region comparison includes at least one of heat absorption deviation analysis and deformation consistency analysis.

[0015] The pre-training process of the ledger comparison model includes: Based on historical normal operation data, statistical learning is used to set normal fluctuation ranges for each parameter in order to calibrate the judgment thresholds used for dynamic comparative analysis.

[0016] Step S103: Generate corresponding risk warning information based on the comparative analysis results, and visualize the risk warning information, specifically including: Based on the risk warning information, one or more of the following can be generated: comparison curve, heat map, and deviation matrix table. It also supports one-click location and risk level labeling of abnormal pipe sections.

[0017] The method also includes a model optimization step: comparing the verification results of on-site non-destructive testing with the model early warning information, and correcting the judgment threshold of the ledger comparison model based on the comparison results.

[0018] The following describes in detail the above-mentioned technical solution of the present invention with reference to the specific circumstances of the boiler heating surface early warning method based on multi-dimensional dynamic comparison in the embodiments of the present invention.

[0019] This invention proposes a method for comparing boiler heating surface records, specifically including: 1. Data initialization: Import boiler heating surface design drawing data, bind equipment codes, and synchronize historical operation / maintenance data to the ledger database.

[0020] 2. Model training: Based on historical normal operation data, set the normal fluctuation range of each parameter (such as the annual growth rate of pipe diameter expansion rate ≤ 0.5%), and calibrate the similarity calculation threshold.

[0021] 3. Dynamic comparison: Automatically captures the latest operating data daily and compares it with the data from the previous day / last week / last month and the design value to generate real-time comparison reports.

[0022] 4. Manual verification: For abnormal pipe sections marked in the model, verify them by combining on-site non-destructive testing (such as ultrasonic thickness measurement) and correct the model parameters (such as adjusting the temperature deviation threshold of a certain high smoke temperature area).

[0023] The key to the embodiments of the present invention lies in: 1. Multi-dimensional ledger system: Construct a ledger architecture for the heated surface that links data throughout the entire lifecycle of "design-operation-maintenance".

[0024] 2. Dynamic comparison model: A dual-dimensional comparison algorithm that integrates temporal changes and regional differences enables automatic identification of abnormal parameters.

[0025] Among them, the core features include: 1. Data Architecture: A multi-dimensional ledger database is built based on boiler heating surface design parameters, operation monitoring data, and maintenance records, including core fields such as pipe specifications (pipe diameter / wall thickness / material), temperature / pressure operating curves, creep deformation, and defect records.

[0026] 2. Comparison Dimensions: Longitudinal time series comparison: parameter changes at different time points in the same heated surface area (such as wall thickness reduction rate, pipe diameter expansion rate, and temperature deviation trend). Horizontal area comparison: Parameter differences (such as heat absorption deviation and deformation consistency) of different tube panels / tube groups of the same type of heating surface (such as high temperature superheater and reheater).

[0027] 3. Visual output: Generates comparison curves, heat map, and deviation matrix table, supports one-click location of abnormal pipe sections, and marks the risk level (green - normal / yellow - warning / red - severe).

[0028] In summary, the main design features of this invention are: 1. Data hierarchy architecture of boiler heating surface ledger (system-region-tube panel-single tube hierarchy relationship).

[0029] 2. Calculation method of time series change rate and algorithm for comparison of mean / standard deviation of regional parameters.

[0030] System Implementation Examples According to embodiments of the present invention, a boiler heating surface early warning system based on multi-dimensional dynamic comparison is provided. Figure 2 This is a schematic diagram of a boiler heating surface early warning system based on multi-dimensional dynamic comparison, according to an embodiment of the present invention. Figure 2 As shown, the boiler heating surface early warning system based on multi-dimensional dynamic comparison according to an embodiment of the present invention specifically includes: Data management module 20 is used to build a multi-dimensional ledger database of boiler heating surfaces; The dynamic comparison module 22 is used to perform multi-dimensional dynamic comparison analysis based on the multi-dimensional ledger database using a pre-trained ledger comparison model, and obtain the comparison analysis results. The risk warning module 24 is used to generate corresponding risk warning information based on the comparative analysis results and to visualize the risk warning information.

[0031] The embodiments of the present invention are system embodiments corresponding to the above method embodiments. The specific operation of each module can be understood by referring to the description of the method embodiments, and will not be repeated here.

[0032] Device Example 1 This invention provides an electronic device, including: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the computer program, when executed by the processor, performs the steps described in the method embodiment.

[0033] Device Example 2 This invention provides a computer-readable storage medium storing an information transmission implementation program, which, when executed by a processor, performs the steps described in the method embodiment.

[0034] The computer-readable storage media described in this embodiment include, but are not limited to, ROM, RAM, disk, or optical disk.

[0035] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features therein. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A boiler heating surface early warning method based on multi-dimensional dynamic comparison, characterized in that, include: Construct a multi-dimensional ledger database of boiler heating surfaces; Based on the multidimensional ledger database, a pre-trained ledger comparison model is used to perform multidimensional dynamic comparison analysis to obtain the comparison analysis results. Based on the comparative analysis results, corresponding risk warning information is generated and the risk warning information is visualized.

2. The method according to claim 1, characterized in that, The construction of a multidimensional ledger database for boiler heating surfaces specifically includes: A multi-dimensional ledger database is constructed based on the design parameters of the boiler heating surface, operation monitoring data, and maintenance records. The data structure of the multidimensional ledger database includes at least four levels: system, region, pipe panel, and single pipe. Its data fields include at least pipe specifications, temperature / pressure operating curves, creep deformation, and defect records. The pipe specifications include pipe diameter, wall thickness, and material.

3. The method according to claim 1, characterized in that, The multi-dimensional dynamic comparative analysis includes at least: longitudinal time-series comparison and horizontal regional comparison; The longitudinal time series comparison involves calculating and analyzing the rate of change of parameters in the same heated surface region at different time points. The horizontal region comparison is a consistency analysis of the parameters of different tube panels or tube groups in the same type of heating surface.

4. The method according to claim 3, characterized in that, The parameter change rate in the longitudinal time series comparison includes at least one of the following: wall thickness reduction rate, pipe diameter expansion rate, and temperature deviation trend. The consistency analysis in the lateral region comparison includes at least one of heat absorption deviation analysis and deformation consistency analysis.

5. The method according to claim 1, characterized in that, The pre-training process of the ledger comparison model includes: Based on historical normal operation data, statistical learning is used to set normal fluctuation ranges for each parameter in order to calibrate the judgment thresholds used for dynamic comparative analysis.

6. The method according to claim 1, characterized in that, The visualization of the aforementioned risk warning information specifically includes: Based on the risk warning information, one or more of the following can be generated: comparison curve, heat map, and deviation matrix table. It also supports one-click location and risk level labeling of abnormal pipe sections.

7. The method according to claim 1, characterized in that, The method also includes a model optimization step: comparing the verification results of on-site non-destructive testing with the model early warning information, and correcting the judgment threshold of the ledger comparison model based on the comparison results.

8. A boiler heating surface early warning system based on multi-dimensional dynamic comparison, characterized in that, include: The data management module is used to build a multidimensional ledger database of boiler heating surfaces; The dynamic comparison module is used to perform multi-dimensional dynamic comparison analysis based on the multi-dimensional ledger database using a pre-trained ledger comparison model, and obtain the comparison analysis results. The risk warning module is used to generate corresponding risk warning information based on the comparative analysis results and to visualize the risk warning information.

9. An electronic device, characterized in that, include: The memory, the processor, and the computer program stored in the memory and executable on the processor, wherein the computer program, when executed by the processor, implements the steps of the boiler heating surface early warning method based on multi-dimensional dynamic comparison as described in any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores an information transmission implementation program, which, when executed by a processor, implements the steps of the boiler heating surface early warning method based on multi-dimensional dynamic comparison as described in any one of claims 1-7.

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