Deepwater jacket digital twinborn database correction method based on measured data

Abstract

The invention discloses a deepwater jacket digital twinborn database correction method based on measured data, and belongs to the field of ocean engineering structures. Calculating the axial force response of the deepwater jacket platform measuring points and other concerned rods, and establishing a database containing the mapping relation between the simulated sea condition and the stress condition of the deepwater jacket platform rods; the response of all the rod pieces in the database and the mapping relation with the sea condition are corrected according to the distribution rule of the actual measurement and simulation response of specific measurement points and different types of rod pieces on the deepwater jacket. According to the method, on the basis of a database formed by sea conditions and simulation responses of the deepwater jacket digital twinning system, the database is gradually corrected by utilizing distribution rules of actual measurement and simulation responses on the deepwater jacket and combining actual measurement response data accumulated after system operation, and the accuracy of the deepwater jacket digital twinning system is improved.

Description

Technical Field

[0001] This invention relates to a method for correcting a digital twin database of deep-water jacket structures based on measured data. It is applicable to the digital construction and data-driven operation and management of deep-water jacket structures and belongs to the field of marine engineering structures. Background Technology

[0002] Deepwater jacket structures are complex, typically operating at depths of 300 meters or more. The harsh and complex sea conditions in deep water place higher demands on the jacket structure's stress resistance, corrosion resistance, durability, and resistance to fatigue damage. To ensure the long-term safe operation of deepwater jacket platforms, the platform's builders and operators are eager to upgrade the operation and maintenance of deepwater jackets intelligently through digital twin technology. Digital twins have the ability to bridge the digital and physical worlds, integrating physical data with twin models to form comprehensive decisions and then feeding them back to the physical world, providing a new application model for enterprises to carry out intelligent upgrades.

[0003] Implementing digital twin technology on deep-water jackets requires real-time calculation and display of the stress state at various points on the structure based on actual loads. Simulation calculations struggle to reflect the dynamic response of the real jacket structure, and the jacket is subject to corrosion, aging, and marine organism attachment during service, causing structural changes. Therefore, existing load-response patterns are not entirely suitable for the current structural constitutive model.

[0004] Therefore, to realize digital technology for deep-water jackets, it is urgent to solve the problem of correcting simulation data and previous data in the database with measured data from limited measuring points, and to expand the data, that is, to construct a more accurate load-response mapping relationship. Summary of the Invention

[0005] To address the aforementioned problems, this invention proposes a method for correcting a digital twin database of deep-water jacket structures based on measured data. By comparing the measured load and response data collected from the monitoring end with the data in the simulation database, dynamic correction coefficients are calculated. Furthermore, based on the distribution patterns of different member types and height directions, all response data in the database and their mapping relationship with sea state are corrected.

[0006] To achieve the above objectives, the present invention adopts the following technical solution: A method for correcting a digital twin database of deep-water jacket structures based on measured data, the method comprising the following steps: S1. Data search: For a specific measured load, search the database for the six sets of load data and corresponding response data that are closest to it. S2. Response data interpolation: Call the six sets of response data from step S1 and use the inverse distance weighted interpolation method to calculate the response data corresponding to the current measured load; S3. Calculation of dynamic correction coefficient for measuring point: Calculate the dynamic correction coefficient for measuring point using the measured response data corresponding to the current measured load and the response data in step S2. S4. Dynamic correction coefficient fitting: Using the dynamic correction coefficients of the measuring points, the relationship between the dynamic correction coefficients of the main leg, diagonal brace and horizontal brace and the height of the jacket structure is fitted respectively. S5. Response data correction: The response data of the measuring point is replaced with the actual measured response data of the measuring point. For non-measuring points, the corresponding dynamic correction coefficient is calculated according to the structure type and height, combined with the fitting relationship in step S4, and the data is corrected. S6. Store the measured loads used for correction, the corresponding corrected response data, and their mapping relationships in the digital twin system database.

[0007] Furthermore, the database construction method in step S1 is as follows: The measured data obtained from the monitoring terminal is used to correct and expand the digital twin system database obtained from the simulation terminal; the measured data includes measured load data and measured response data. The monitoring end includes data transmission from an anemometer, wave radar, ocean current meter, and load signal demodulation module, as well as data transmission from fiber optic strain sensor response signal demodulation module. Between the monitoring end and the measured data, the data from the load signal demodulation module is processed and stored as measured load data, and the data from the response signal demodulation module is processed and stored as measured response data; the digital twin system database includes response data and load data. The historical wind speed data, historical wave data, and historical ocean current data from the simulation end are jointly sampled from the sea state and stored as load data in the digital twin system database. The load data is used to apply loads to the simulation model at the simulation end, and the simulation output response is stored as response data in the digital twin system database.

[0008] Furthermore, the digital twin system database includes measured load data and load data and mapping relationships. The load data is formed by joint sampling of loads from past wind speed data, past wave data and past ocean current data, and is periodically supplemented based on measured load data. The response data is calculated by the simulation model and is corrected and expanded based on measured response data.

[0009] Furthermore, the measured response data categorizes the structural components of the deep-water jacket into three types: main legs, diagonal braces, and horizontal braces. For each type of structure, three fiber optic strain sensors are arranged at each measuring point along the height direction of the jacket. The measured data are demodulated to form the measured response data.

[0010] Furthermore, the load data in step S1 includes six dimensions: wind direction, wind speed, significant wave height, spectral peak period, flow direction, and surface flow velocity.

[0011] Furthermore, in step S3, the dynamic correction coefficient is a correction coefficient characterizing the measured response and the response data obtained from the simulation at the corresponding location:

[0012] in: To focus on the dynamic correction coefficient of the member under load; This represents the measured response value of the rod under this sea state; This represents the response values ​​of the rods under the corresponding sea conditions in the database. Furthermore, in step S5, the calculation process of the corrected data is as follows: under a specific sea state, combined with dynamic correction coefficients... Calculate the dynamic correction factor for the members based on the relationship of height variation along the jacket structure. Under this sea state, the corrected response value of the rod is:

[0013] in, This represents the response value of the rod under the corresponding sea state in the database.

[0014] The beneficial effects of this invention are as follows: This invention corrects the digital twin database by using measured axial force data of deep-water jacket platform members; it calculates the axial force response of measuring points and other members of interest on the deep-water jacket platform using SACS static simulation and ANSYS dynamic simulation, and establishes a database containing the mapping relationship between simulated sea conditions and the stress conditions of deep-water jacket platform members; it corrects the response of all members in the database and the mapping relationship with sea conditions by using the distribution law of measured and simulated responses of specific measuring points and different types of members on the deep-water jacket platform.

[0015] This method studies the distribution patterns of measured and simulated responses on deep-water jackets. Based on the database of sea state and simulated responses of the deep-water jacket digital twin system, the database is gradually corrected by combining the distribution patterns with the measured response data accumulated after the system's operation, thereby improving the accuracy of the deep-water jacket digital twin system.

[0016] This method interpolates the response data based on the inverse distance weighted interpolation (IDW) method; fits the correlation between rod type and jacket height through dynamic correction coefficients; and dynamically expands the database to achieve adaptive optimization of the data. Attached Figure Description

[0017] Figure 1 This diagram illustrates the data interaction and database construction between the monitoring and simulation ends.

[0018] Figure 2 A flowchart of the overall process for correcting the digital twin database of deep-water jacket structures.

[0019] Figure 3 This is a graph showing the relationship between the dynamic correction factor and the height of the jacket.

[0020] In the diagram: 1. Anemometer, 2. Wave radar, 3. Current meter, 4. Fiber optic strain sensor, 5. Load signal demodulation module, 6. Response signal demodulation module, 7. Measured load data, 8. Measured response data, 9. Historical wind speed data, 10. Historical wave data, 11. Historical ocean current data, 12. Joint sea state sampling, 13. Simulation model, 14. Load data, 15. Response data, 16. Monitoring terminal, 17. Measured data, 18. Simulation terminal, 19. Digital twin system database. Detailed Implementation

[0021] The specific embodiments of the present invention will now be described in further detail with reference to the accompanying drawings. However, it should be understood that the drawings are provided only for a better understanding of the present invention and should not be construed as limiting the present invention.

[0022] like Figure 1 As shown, the correction method employs a data interaction and database construction approach between the monitoring end and the simulation end: the measured data 17 acquired by the monitoring end 16 is used to correct and expand the digital twin system database 19 acquired by the simulation end 18; wherein, the measured data 17 includes measured load data 7 and measured response data 8; the monitoring end 16 includes data transmission between the anemometer 1, wave radar 2, current meter 3 and the load signal demodulation module 5, and data transmission between the fiber optic strain sensor 4 and the response signal demodulation module 6; between the monitoring end 16 and the measured data 17, the data from the load signal demodulation module 5 is processed... The processed data is stored as measured load data 7, and the data from the response signal demodulation module 6 is stored as measured response data 8. The digital twin system database 19 includes response data 15 and load data 14. The past wind speed data 9, past wave data 10, and past ocean current data 11 from the simulation terminal 18 are stored as load data 14 in the digital twin system database 19 after sea state joint sampling 12. The load data 14 applies load to the simulation model 13 at the simulation terminal 18, and the simulation output response is stored as response data 15 in the digital twin system database 19.

[0023] The deep-water jacket digital twin system database 19 includes load data 14 and response data 15, as well as mapping relationships. The load data 14 is formed by joint sampling of loads such as past wind speed data 9, past wave data 10, and past ocean current data 11, and will be supplemented periodically based on measured load data 7. The response data 15 is calculated by the simulation model 13 and will be corrected and expanded based on measured response data 8.

[0024] like Figure 2As shown, a flowchart of a method for correcting a digital twin database of deep-water jackets based on measured data is presented.

[0025] To achieve the above objectives, the present invention adopts the following technical solution: A method for correcting a deep-water jacket digital twin database based on measured data includes the following steps: A. Data search: For a specific measured load, search the database for the six sets of load data that are closest to it and the corresponding response data; B. Response data interpolation: Call the six sets of response data in A and use the inverse distance weighted interpolation (IDW) method to calculate the response data corresponding to the current measured load; C. Calculation of dynamic correction coefficient for measuring point: Using the measured response data corresponding to the current measured load and the response data in B, calculate the "dynamic correction coefficient" for the measuring point;

[0026] in: This is the dynamic correction factor for a specific member under a certain load; This represents the measured response value of the rod under this sea state; This represents the response value of the rod under the corresponding sea state in the database. D. Dynamic Correction Coefficient Fitting: Under a specific sea state, the dynamic correction coefficients of similar members (main legs, vertical braces, and horizontal braces) exhibit a stable correlation along their height. Using the dynamic correction coefficients at measuring points, graphs are plotted showing the relationship between the dynamic correction coefficients of the main legs, vertical braces, and horizontal braces and the height of the jacket structure. Figure 3 In the process, linear interpolation is used to calculate the dynamic correction coefficient at the height of the structure of interest; E. Response Data Correction: The response data of the measuring points are replaced with the measured response data of the measuring points. For non-measuring points, the dynamic correction coefficients for the members are calculated according to the structure type and height, combined with the fitting relationship in D, and denoted as... Under this sea state, the corrected response value of the rod is:

[0027] F. Database Expansion: The measured loads used for correction, along with the corresponding corrected response data and their mapping relationships, are stored in the digital twin system database.

[0028] The above embodiments are only used to illustrate the present invention. Any equivalent transformations and improvements made on the basis of the technical solutions of the present invention should not be excluded from the protection scope of the present invention.

Claims

1. A method for correcting a digital twin database of deep-water jacket structures based on measured data, characterized in that, The method includes the following steps: S1. Data search: For a specific measured load, search the database for the six sets of load data and corresponding response data that are closest to it. S2. Response data interpolation: Call the six sets of response data from step S1 and use the inverse distance weighted interpolation method to calculate the response data corresponding to the current measured load; S3. Calculation of dynamic correction coefficient for measuring point: Calculate the dynamic correction coefficient for measuring point using the measured response data corresponding to the current measured load and the response data in step S2. S4. Dynamic correction coefficient fitting: Using the dynamic correction coefficients of the measuring points, the relationship between the dynamic correction coefficients of the main leg, diagonal brace and horizontal brace and the height of the jacket structure is fitted respectively. S5. Response data correction: The response data of the measuring point is replaced with the actual measured response data of the measuring point. For non-measuring points, the corresponding dynamic correction coefficient is calculated according to the structure type and height, combined with the fitting relationship in step S4, and the data is corrected. S6. Store the measured loads used for correction, the corresponding corrected response data, and their mapping relationships in the digital twin system database to complete the correction.

2. The deep-water jacket digital twin database based on measured data according to claim 1, characterized in that, The database construction method in step S1 is as follows: The measured data obtained from the monitoring terminal is used to correct and expand the digital twin system database obtained from the simulation terminal; the measured data includes measured load data and measured response data. The monitoring end includes data transmission from an anemometer, wave radar, ocean current meter, and load signal demodulation module, as well as data transmission from fiber optic strain sensor response signal demodulation module. Between the monitoring end and the measured data, the data from the load signal demodulation module is processed and stored as measured load data, and the data from the response signal demodulation module is processed and stored as measured response data; the digital twin system database includes response data and load data. The historical wind speed data, historical wave data, and historical ocean current data from the simulation end are jointly sampled from the sea state and stored as load data in the digital twin system database. The load data is used to apply loads to the simulation model at the simulation end, and the simulation output response is stored as response data in the digital twin system database.

3. The method for correcting a deepwater jacket digital twin database based on measured data according to claim 2, characterized in that: The digital twin system database includes measured load data and load data and mapping relationships. The load data is formed by joint sampling of loads from past wind speed data, past wave data and past ocean current data, and is periodically supplemented based on measured load data. The response data is calculated by the simulation model and is corrected and expanded based on measured response data.

4. The method for correcting a deepwater jacket digital twin database based on measured data according to claim 3, characterized in that: The measured response data is as follows: The structural components of the deep-water jacket are divided into three categories: main legs, diagonal braces, and horizontal braces. For each type of structure, three measuring points are set up with fiber optic strain sensors along the height direction of the jacket. The measured data are demodulated to form the measured response data.

5. The method for correcting a deepwater jacket digital twin database based on measured data according to claim 1, characterized in that: The load data in step S1 consists of six dimensions, including wind direction, wind speed, significant wave height, spectral peak period, flow direction, and surface flow velocity.

6. The method for correcting a deepwater jacket digital twin database based on measured data according to claim 1, characterized in that: In step S3, the dynamic correction coefficient is a correction coefficient that characterizes the measured response and the response data obtained from the simulation at the corresponding location: ， in: To focus on the dynamic correction coefficient of the member under load; This represents the measured response value of the rod under this sea state; This represents the response values ​​of the rods under the corresponding sea conditions in the database.

7. The method for correcting a deepwater jacket digital twin database based on measured data according to claim 1, characterized in that: In step S5, the calculation process of the corrected data is as follows: under a specific sea state, combined with dynamic correction coefficients... Calculate the dynamic correction factor for the members based on the relationship of height variation along the jacket structure. Under this sea state, the corrected response value of the rod is: ， in, This represents the response value of the rod under the corresponding sea state in the database.

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