Boiler four-tube health management analysis method based on fiber grating array

Abstract

The invention discloses a boiler four-tube health management analysis method based on a fiber grating array. The method comprises the following steps: S1, laying the fiber grating array; s2, constructing a boiler three-dimensional model and an interactive interface; s3, constructing a three-dimensional digital standing book module; s4, boiler four-tube health data acquisition and digital twinning processing; s5, analyzing and managing the health data of the four pipes of the boiler; the design data, historical data and real-time data of the metal tube wall of the boiler are mined, sorted, learned and comprehensively analyzed according to a three-mode-in-one algorithm of'mechanism + data + experience 'based on high-precision optical fiber array temperature measurement fused with digital twinning; a three-dimensional model and a digital ledger are realized, digital management of basic information of equipment is realized, integrity, accuracy and traceability of data are ensured, and the number of times of non-planned shutdown is reduced; pipe explosion and coking caused by long-term partial combustion of the unit are avoided, and the service life of the unit is prolonged.

Description

Technical Field

[0001] This invention relates to the field of industrial automatic control technology, specifically to a boiler four-tube health management analysis method based on fiber optic grating array. Background Technology

[0002] In recent years, coal-fired boilers have dominated power generation. However, the shortcomings of current coal-fired power units in deep peak shaving and low-load operation have gradually become apparent. Monitoring methods lack comprehensiveness, and hidden risks in the peak shaving process are difficult to detect, leading to frequent problems such as boiler heating surface overheating and material aging, which seriously affect the safety and economy of boilers.

[0003] Coal-fired power units are playing an increasingly important role as regulating power sources, and deep peak shaving has become the norm. However, existing coal-fired power unit designs have failed to fully consider this need and lack effective monitoring and protection measures for deep peak shaving. This leaves boilers facing severe challenges such as overheating of heating surfaces and reduced metal life during peak shaving, thereby increasing the risk of safety accidents.

[0004] During deep peak shaving, stress concentration in the peak shaving area can lead to pipe cracking on the heating surface; large temperature fluctuations in the heating surface pipe wall during deep peak shaving can affect metal lifespan; long-term low-load operation can affect the safety of the heating surface and also have an adverse impact on the safety of the entire unit; long-term low-load operation can easily lead to overheating and pipe rupture; frequent load changes can cause significant changes in the heating conditions of various components of the unit, generating thermal stress and thermal deformation, which may cause abnormal expansion and vibration, directly threatening the safety of the unit.

[0005] As a vital force in regional power supply, the existing power plant, comprising two 660MW generating units, faces particularly prominent issues regarding stable combustion and heating surface safety during deep peak shaving. The limitations of existing temperature monitoring methods result in insufficient precise control over heating surface temperatures. Frequent load changes exacerbate temperature fluctuations and the risk of oxide scale shedding from the metal heating surfaces, posing a serious threat to the safe operation of the boilers. Summary of the Invention

[0006] In view of the above situation and to overcome the defects of the prior art, the technical solution adopted by the present invention is as follows: A boiler four-tube health management analysis method based on fiber Bragg grating array, characterized by the following steps: S1. Deploy the fiber optic grating array; S2. Construct a 3D model of the boiler and its interactive interface; S3. Construct a three-dimensional digital ledger module; S4. Boiler four-tube health data acquisition and digital twin processing; S5. Boiler four-tube health data analysis and management.

[0007] Compared with the prior art, the present invention has the following beneficial effects: By installing the most advanced international fiber optic high-temperature multi-point temperature sensor, the system can monitor the frequent fluctuations in the temperature of the heated surface metal during deep peak shaving of the boiler, and solve the difficulty of arranging temperature measuring points over a large area in the small space inside the boiler.

[0008] The measured temperature data is fed back to the system in a unified manner, enabling operators to intuitively and quickly monitor changes in the temperature of the heated surface, reducing analysis time and guiding operators to quickly adjust operational issues.

[0009] This research applies high-precision fiber optic array temperature measurement combined with digital twin, artificial intelligence, and big data technologies to the health analysis and optimization of boiler tubes. Based on a three-model integration algorithm combining "mechanism + data + experience," it mines, organizes, learns, and comprehensively analyzes boiler metal tube wall design data, historical data, and real-time data. This results in a 3D model and digital ledger, enabling digital management of basic equipment information and ensuring data integrity, accuracy, and traceability. This reduces unplanned downtime, prevents tube rupture and coking caused by prolonged uneven burning, and extends the unit's lifespan. Attached Figure Description

[0010] Figure 1 A schematic diagram of the boiler four-tube health management analysis method; Detailed Implementation The present invention will be further described below with reference to the accompanying drawings and embodiments. The embodiments of the present invention include, but are not limited to, the following embodiments.

[0011] It should be noted that when a component is described as "fixed to" another component, it can be directly on the other component or may have a component in between. When a component is described as "connected to" another component, it can be directly connected to the other component or may have a component in between. When a component is described as "set on" another component, it can be directly set on the other component or may have a component in between. The terms "vertical," "horizontal," "left," "right," "top," "bottom," and similar expressions used in this document are for illustrative purposes only.

[0012] A boiler four-tube health management analysis method based on fiber Bragg grating array includes the following steps: S1. Deploy the fiber optic grating array.

[0013] Design and fabricate large-scale fiber Bragg grating arrays to meet the needs of distributed fiber optic sensing. This includes optimizing parameters such as the arrangement, spacing, and length of the fiber Bragg gratings to achieve high-precision and high-sensitivity sensing; and utilizing wavelength division multiplexing (WDM) technology to couple optical signals of different wavelengths into different fiber Bragg gratings to achieve parallel transmission and processing of multiple sensing signals, thereby improving the measurement range and accuracy of the sensor.

[0014] High-temperature tubular packaging and high-temperature annealing are applied to a fiber Bragg grating (FBG) high-temperature sensor to improve its mechanical strength and stability. Simultaneously, temperature response characteristics of the sensor are studied through high-temperature testing, and a temperature response fitting formula applicable to FBGs with different center wavelengths is established. This formula enables accurate measurement and calibration of the sensor at different temperatures, improving its measurement accuracy and reliability.

[0015] Based on historical over-temperature data and operational status of the screen-type superheater and reheater, the outlet positions of the tube panels are selected and evenly distributed along the width of each panel. Fiber optic temperature measuring points must be installed on the outermost tubes closest to the boiler centerline. After a reasonable arrangement of measuring points, the accuracy and efficiency of the analysis are improved by coupling the tube wall temperature with the flue gas temperature deviation on both sides of the horizontal flue, as well as the tube wall temperature rise / fall rate and over-temperature conditions. This provides strong support for optimizing boiler operation and extending pipeline service life.

[0016] S2. Construct a 3D model of the boiler and its interactive interface. Using 3D modeling technology, based on drawings (including drawings provided by equipment manufacturers, design institutes, and construction units) and the actual buildings and equipment on site, an intelligent 3D model is established. This model allows for the intuitive, three-dimensional, and precise representation of source facilities and devices that are structurally complex, have complicated processes, and cannot be accurately located on a graphic plane.

[0017] The system should implement a web-based 3D interactive interface, allowing users to easily select, freely navigate, zoom in and out of the 3D scene using a mouse. This feature will greatly enhance the operator's navigation and positioning experience in 3D space. Precise distance measurement tools should also be integrated into the 3D environment to quickly and accurately calculate the distances between facilities, equipment, and pipelines. Furthermore, operators should be able to draw arbitrary cross-sections in the 3D scene and display the detailed structure of the heated surfaces, while also viewing the coordinate information and other relevant attribute data of each element (such as facilities, equipment, and pipelines). When a specific pipeline or equipment is selected, the system should display detailed attribute information of the corresponding metal pipe, including but not limited to attribute data, images, and electronic construction drawings, thereby achieving a comprehensive visualization of the model and data, and enabling comprehensive visual management of the boiler.

[0018] The specific scope of the modeling should cover: The boiler will be modeled with high precision in 3D, ensuring that the model's detail reaches the weld joint level. Detailed modeling will be performed on each heat-receiving surface metal pipe. The 3D model of the boiler's external piping will be completed. The four main piping systems of the boiler will be modeled. The boiler headers will be modeled. Each boiler support structure will be modeled. The model viewing function should include, but is not limited to, practical operations such as selecting elements, panning the view, rotating the view, centering the display, and measuring the straight-line distance between any two points.

[0019] S3. Construct a three-dimensional digital ledger module.

[0020] To achieve digital management of basic equipment information and ensure data integrity, accuracy, and traceability. The scope of equipment includes key components such as boiler tubes, headers, four main pipelines, and external pipelines. A detailed basic information database will be established for these devices, including essential parameters, operating data, maintenance records, and other critical information.

[0021] In terms of functionality, it supports quick querying of basic parameters for various equipment, enabling users to rapidly obtain detailed information about the equipment they need. It also provides unified archiving and management of equipment-related drawings, modification records, maintenance records, and other documents, ensuring the security and accessibility of this important data. Seamless integration with Excel allows for direct import of Excel files such as power plant anti-wear and explosion-proof regulations, equipment basic ledgers, and maintenance records. This greatly simplifies the data entry process, improves work efficiency, and ensures data accuracy and consistency.

[0022] By combining the ledger module with the boiler's 3D model, users can view various information such as relevant dynamic and static ledgers, pipe replacement data, explosion relief data, and wall temperature monitoring, making it convenient for users to keep abreast of the status and deterioration patterns.

[0023] S4. Boiler four-tube health data acquisition and digital twin processing.

[0024] Data acquisition is typically achieved through various fiber optic sensors installed on the four tubes of the boiler (water-cooled wall, superheater, reheater, and economizer). These sensors can collect temperature information from the surface of the four tubes in real time and transmit the data to the system for processing.

[0025] Digital twin technology is employed to fuse temperature measurement data from fiber optic array temperature sensors with the boiler's 3D model data. By establishing a real-time mapping relationship between the physical entity and the virtual model, it achieves seamless connection and optimized decision-making between the physical and virtual worlds. By integrating the temperature measurement data from the fiber optic array temperature sensors with the boiler's 3D model data, more intuitive and accurate temperature monitoring and management are achieved, thereby improving the safety and efficiency of boiler operation.

[0026] Fiber grating arrays are installed on the walls of the superheater and reheater tubes of the boiler. Through precise spatial positioning, the sensor positions are accurately matched with corresponding positions in the boiler's 3D model. Simultaneously, a real-time data transmission mechanism ensures that temperature measurement data is updated to the 3D model instantly. Operators can intuitively view the real-time temperature distribution and changes in the 3D model, thereby achieving precise monitoring and management of the boiler's temperature status.

[0027] S5. Boiler four-tube health data analysis and management.

[0028] By combining historical temperature measurement data, a deep analysis of temperature change trends is conducted within a 3D model to assess the boiler's operating status, predict potential faults, and develop targeted maintenance plans. Furthermore, by comparing temperature distributions under different operating conditions, boiler operating strategies can be further optimized, such as adjusting combustion parameters and improving feedwater flow methods, to achieve higher operating efficiency and lower emissions.

[0029] In addition, based on the "mechanism + data + experience" three-model integration algorithm, the boiler metal tube wall design data, historical data, and real-time data are mined, organized, learned, and comprehensively analyzed. Wall thickness reduction models are formulated for different heating surfaces, heating areas, and wear of each furnace tube, enabling online monitoring of wear trends and providing risk warnings. Corresponding degradation models are established for the different working environments and material properties of each high-temperature tube panel of water-cooled walls, superheaters, and reheaters. By linking changes in wall thickness, thinning rate, and other data in the maintenance log, the phased life loss value of each heating surface metal tube is calculated, and risk ranking and early warning are provided to improve the reliability of boiler operation.

[0030] Based on the different heating surfaces, heating areas, and wear conditions of each furnace tube, a wall thickness reduction model for each heating surface metal tube is developed to achieve three-dimensional display of wear trends and automatic detection of wear degree, providing risk warnings for wall thickness wear monitoring. In wear management, clicking on the corresponding equipment allows viewing all wear record information and generating dynamic line graphs. Wear records include information such as pipe name, equipment name, measurement point, material, specifications, location, wall thickness, and inspection time. Wear records can be downloaded in EXCEL format. After correctly filling in the basic information in the wear record template table, the wear records are automatically imported into the system.

[0031] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the invention patent. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this patent application should be determined by the appended claims.

Claims

1. A boiler four-tube health management analysis method based on fiber optic grating array, characterized in that, Includes the following steps: S1. Deploy the fiber optic grating array; S2. Construct a 3D model of the boiler and its interactive interface; S3. Construct a three-dimensional digital ledger module; S4. Boiler four-tube health data acquisition and digital twin processing; S5. Boiler four-tube health data analysis and management.

2. The boiler four-tube health management analysis method based on fiber optic grating array according to claim 1, characterized in that, In S1, a large-scale fiber Bragg grating array is designed and fabricated, including optimizing the arrangement, spacing, and length parameters of the fiber Bragg gratings. Wavelength division multiplexing is used to couple optical signals of different wavelengths into different fiber Bragg gratings to achieve parallel transmission and processing of multiple sensing signals, thereby improving the measurement range and accuracy of the sensor.

3. The boiler four-tube health management analysis method based on fiber optic grating array according to claim 1, characterized in that, In S1, through testing under high-temperature conditions, a temperature response fitting formula suitable for fiber optic gratings with different center wavelengths is established based on the temperature response characteristics of the sensor.

4. The boiler four-tube health management analysis method based on fiber optic grating array according to claim 1, characterized in that, In S1, when arranging the measuring points, select the outlet position of the tube screen and arrange them evenly along the width direction on each screen. The outermost tube closest to the center line of the boiler must be equipped with fiber optic temperature measuring points.

5. The boiler four-tube health management analysis method based on fiber optic grating array according to claim 1, characterized in that, In S2, a high-precision 3D model of the boiler is performed to ensure that the model's precision reaches the weld joint level, and detailed modeling is performed for each heat-receiving surface metal tube; the 3D model of the boiler's external piping is completed. Model the four main pipes of the boiler; Model the boiler header section; Model the structure of each boiler support and hanger; The model's interactive features include: selecting elements, panning the view, rotating the view, centering the display, and measuring the straight-line distance between any two points.

6. The boiler four-tube health management analysis method based on fiber optic grating array according to claim 1, characterized in that, In S4, Data is acquired through various fiber optic sensors installed on the four tubes of the boiler and transmitted to the system for processing.

7. The boiler four-tube health management analysis method based on fiber optic grating array according to claim 6, characterized in that, In S4, digital twin technology is used to fuse the temperature measurement data of the fiber optic grating array temperature sensor with the three-dimensional model data of the boiler. The fiber optic grating array is installed on the tube walls of the superheater and reheater of the boiler. Through precise spatial positioning, the position of the sensor is accurately matched with the corresponding position in the three-dimensional model of the boiler. At the same time, based on the real-time data transmission mechanism, it is ensured that the temperature measurement data can be updated to the three-dimensional model in real time.

8. The boiler four-tube health management analysis method based on fiber optic grating array according to claim 1, characterized in that, In S5, By combining historical temperature measurement data, the temperature change trend can be analyzed in depth in the three-dimensional model to assess the boiler's operating status, predict potential faults, and formulate targeted maintenance plans. In addition, by comparing the temperature distribution under different operating conditions, the boiler's operating strategy can be further optimized, such as adjusting combustion parameters and improving the water supply method, to achieve higher operating efficiency and lower emission levels.

9. The boiler four-tube health management analysis method based on fiber optic grating array according to claim 8, characterized in that, In S5, the "mechanism + data + experience" three-model integration algorithm is used to mine, organize, learn and comprehensively analyze the boiler metal tube wall design data, historical data and real-time data. The wall thickness reduction model is formulated for different heating surfaces, heating areas and wear conditions of each furnace tube, so as to realize online monitoring of wear trends and provide risk warnings. For the different working environments and material properties of the high-temperature tube panels of water-cooled walls, superheaters, and reheaters, corresponding degradation models are established. By linking the changes in wall thickness and thinning rate data in the maintenance log, the phased life loss value of each heat-receiving surface metal tube is calculated, and risk ranking and early warning are performed to improve the reliability of boiler operation.

10. The boiler four-tube health management analysis method based on fiber optic grating array according to claim 9, characterized in that, In S5, under Wear Management, clicking on the corresponding device allows you to view all wear record information and generate a dynamic line graph. Wear records include information such as pipe name, equipment name, measurement point, material, specifications, location, wall thickness, and inspection time. Wear records can be downloaded in EXCEL format. Wear records can be automatically imported into the system after the basic information is correctly filled in the wear record template table.

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