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] The present invention relates to a deepwater jacket digital twin database correction method based on measured data, which is applicable to the digital construction and data-driven operation and management scenarios of deepwater jackets and belongs to the field of marine engineering structures. Background Art

[0002] Deepwater jackets are complex structures, typically operating at depths of 300 meters or more. These harsh and complex deepwater conditions place higher demands on the jacket structure's stress resistance, corrosion resistance, durability, and fatigue damage. To ensure the long-term safe service of deepwater jacket platforms, platform builders and operators are eager to leverage digital twin technology to intelligently upgrade deepwater jacket operations and maintenance. Digital twins bridge the digital and physical worlds, integrating physical data with twin models to generate comprehensive decisions and then feeding them back to the physical world. This provides a new application model for enterprises to implement intelligent upgrades.

[0003] Implementing digital twin technology on deepwater jackets requires real-time calculation and display of the stress states at all locations within the structure, based on actual loads. Simulations struggle to reflect the dynamic response of actual jacket structures. Furthermore, jackets undergo structural changes during service due to corrosion, aging, and marine biofouling. Therefore, previous load-response models are no longer fully applicable to current structural constitutive models.

[0004] Therefore, to realize the digital technology of deepwater jacket, it is urgent to solve the problem of correcting the simulation data and previous data in the database through the measured data of limited measurement points, and to expand the data, that is, to build a more accurate load-response mapping relationship. Summary of the Invention

[0005] To address these issues, this paper proposes a deepwater jacket digital twin database correction method based on measured data. This method compares measured load and response data collected by monitoring terminals with data in a simulation database to calculate dynamic correction coefficients. All response data in the database, including its mapping to sea conditions, is then corrected based on the distribution patterns of different member types and height directions.

[0006] In order to achieve the above object, the present invention adopts the following technical solutions:

[0007] A method for correcting a deepwater jacket digital twin database based on measured data comprises the following steps:

[0008] S1. Data search: For a certain measured load, search the database for the six closest load data and corresponding response data.

[0009] S2. Response data interpolation: Call the six groups of response data in step S1 and use the inverse distance weighted interpolation method to calculate the response data corresponding to the current measured load;

[0010] S3. Calculation of dynamic correction coefficient of measuring point: Calculate the dynamic correction coefficient of the measuring point using the measured response data corresponding to the current measured load and the response data in step S2;

[0011] S4. Dynamic correction coefficient fitting: The dynamic correction coefficients of the measuring points are used to fit the relationship between the dynamic correction coefficients of the three structures, the main legs, the diagonal braces and the horizontal braces, and the jacket height.

[0012] S5. Response data correction: The response data of the measuring point is replaced with the measured response data of the measuring point. The non-measuring point is calculated according to the structural type and height, combined with the fitting relationship in step S4, and the corresponding dynamic correction coefficient is calculated, and the data is corrected;

[0013] S6. Store the measured load used for correction, the corresponding corrected response data, and their mapping relationship in the digital twin system database.

[0014] Furthermore, the database construction method in step S1 is:

[0015] The digital twin system database obtained by the simulation end is corrected and expanded using the measured data obtained by the monitoring end; the measured data includes measured load data and measured response data;

[0016] The monitoring end includes anemometer, wave measuring radar, current meter and load signal demodulation module data transmission, fiber Bragg grating strain sensor response signal demodulation module data transmission;

[0017] 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;

[0018] The past wind speed data, past wave data, and past current data on the simulation end are stored as load data in the digital twin system database after joint sampling of sea conditions; the load data applies load to the simulation model on the simulation end, and the response of the simulation output is stored as response data in the digital twin system database.

[0019] Furthermore, the digital twin system database includes measured load data, load data and mapping relationships, wherein the load data is formed by joint sampling of loads of past wind speed data, past wave data and past current data, and is regularly supplemented based on the measured load data; wherein the response data is formed by calculation of the simulation model and is corrected and expanded based on the measured response data.

[0020] Furthermore, the measured response data divides the structural components of the deepwater jacket into three categories: main legs, diagonal braces and horizontal braces. For each type of structure, fiber Bragg grating strain sensors are arranged at three measuring points along the height direction of the jacket. The monitoring data of the measuring points are demodulated to form the measured response data.

[0021] Furthermore, the load data in step S1 is six-dimensional data including wind direction, wind speed, significant wave height, spectrum peak period, flow direction, and surface flow velocity.

[0022] Furthermore, in step S3, the dynamic correction coefficient is a correction coefficient that characterizes the measured response and the response data obtained by simulation at the corresponding position:

[0023]

[0024] in: is the dynamic correction factor of the member under the load of interest; is the measured response value of the rod under the sea condition; is the response value of the rod under the corresponding sea conditions in the database.

[0025] Furthermore, in step S5, the calculation process of the correction data is as follows: under certain sea conditions, combined with the dynamic correction coefficient Calculate the dynamic correction coefficient of the rod along the change relationship of the jacket height direction , then under this sea condition, the corrected response value of the member is:

[0026]

[0027] in, is the response value of the rod under the corresponding sea conditions in the database.

[0028] The beneficial effects of the present invention are as follows: the present invention corrects the digital twin database through the measured axial force data of the deep-water jacket rods; utilizes SACS static simulation and ANSYS dynamic simulation to calculate the axial force responses of the deep-water jacket platform measuring points and other rods of interest and establishes a database containing the mapping relationship between the simulated sea conditions and the stress conditions of the deep-water jacket platform rods; and corrects the responses of all rods in the database and the mapping relationship with the sea conditions through the distribution patterns of the measured and simulated responses of specific measuring points and different types of rods on the deep-water jacket.

[0029] This method studies the distribution patterns of measured and simulated responses on a deepwater jacket. Based on a database consisting of sea conditions and simulated responses for the deepwater jacket digital twin system, this distribution pattern is combined with measured response data accumulated after system operation to gradually correct the database, thereby improving the accuracy of the deepwater jacket digital twin system.

[0030] This method interpolates response data based on the inverse distance weighted (IDW) method; fits the relationship between rod type and jacket height through dynamic correction coefficients; and dynamically expands the database to achieve adaptive optimization of data. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] Figure 1 Schematic diagram of data interaction and database construction between the monitoring end and the simulation end.

[0032] Figure 2 The overall flow chart of the deepwater jacket digital twin database correction method.

[0033] Figure 3 Figure 2 is a graph showing the relationship between the dynamic correction coefficient and the jacket height.

[0034] In the figure: 1. Anemometer, 2. Wave radar, 3. Current meter, 4. Fiber Bragg grating strain sensor, 5. Load signal demodulation module, 6. Response signal demodulation module, 7. Measured load data, 8. Measured response data, 9. Past wind speed data, 10. Past wave data, 11. Past current data, 12. Joint sampling of sea conditions, 13. Simulation model, 14. Load data, 15. Response data, 16. Monitoring terminal, 17. Measured data, 18. Simulation terminal, 19. Digital twin system database. DETAILED DESCRIPTION

[0035] The specific embodiments of the present invention are described in further detail below in conjunction with 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.

[0036] like Figure 1 As shown, the correction method adopts the data interaction and database construction method between the monitoring end and the simulation end as follows: the measured data 17 obtained by the monitoring end 16 amends and expands the digital twin system database 19 obtained by the simulation end 18; wherein, the measured data 17 includes the measured load data 7 and the measured response data 8; the monitoring end 16 includes the anemometer 1, the wave measuring radar 2, the current meter 3 and the load signal demodulation module 5 data transmission, and the fiber Bragg grating strain sensor 4 and the response signal demodulation module 6 data transmission; between the monitoring end 16 and the measured data 17, the data of the load signal demodulation module 5 is transmitted through After processing, it is stored as measured load data 7, and the data of the response signal demodulation module 6 is stored as measured response data 8 after processing; wherein, 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 current data 11 of the simulation end 18 are stored as load data 14 in the digital twin system database 19 after joint sea condition sampling 12; the load data 14 applies a load to the simulation model 13 at the simulation end 18, and the response of the simulation output is stored as response data 15 in the digital twin system database 19.

[0037] The deepwater jacket digital twin system database 19 includes load data 14, response data 15, and mapping relationships. Load data 14 is generated by jointly sampling historical wind speed data 9, historical wave data 10, and historical current data 11, and is regularly supplemented with measured load data 7. Response data 15 is calculated by the simulation model 13 and is corrected and expanded based on measured response data 8.

[0038] like Figure 2 As shown in the figure, a flow chart of a deepwater jacket digital twin database correction method based on measured data is given.

[0039] To achieve the above objectives, the present invention adopts the following technical solution: A method for correcting a deepwater jacket digital twin database based on measured data comprises the following steps:

[0040] A. Data search: For a certain measured load, search the database for the six closest load data and corresponding response data;

[0041] B. Response data interpolation: call the six groups 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;

[0042] C. Calculation of dynamic correction coefficient of measuring point: Calculate the “dynamic correction coefficient” of the measuring point using the measured response data corresponding to the current measured load and the response data in B;

[0043]

[0044] in: is the dynamic correction factor of a specific member under a certain load; is the measured response value of the member under the sea condition; is the response value of the member under the sea conditions corresponding to the database;

[0045] D. Dynamic correction coefficient fitting: Under certain sea conditions, the dynamic correction coefficients of the same type of members (main legs, vertical braces, horizontal braces) have a stable correlation along the height. Based on the dynamic correction coefficients of the measuring points, the relationship between the dynamic correction coefficients of the three structures of main legs, vertical braces and horizontal braces and the height of the jacket is plotted. Figure 3 In the equation, linear interpolation is used to calculate the dynamic correction coefficient at the height of the structure of interest;

[0046] E. Response data correction: The response data of the measuring point is replaced by the measured response data of the measuring point. The non-measuring point is calculated according to the structural type and the height, combined with the fitting relationship in D, and the dynamic correction coefficient corresponding to the rod is calculated, which is recorded as , then under this sea condition, the corrected response value of the member is:

[0047]

[0048] F. Database expansion: The measured loads used for correction and the corresponding corrected response data and their mapping relationships are stored in the digital twin system database.

[0049] The above embodiments are only used to illustrate the present invention. Any equivalent transformations and improvements based on the technical solution of the present invention should not be excluded from the protection scope of the present invention.

Claims

1. A deepwater jacket digital twin database correction method based on measured data, characterized in that: The method comprises the following steps: S1. Data search: For a certain measured load, search the database for the six closest load data and corresponding response data. S2. Response data interpolation: Call the six groups of response data in 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 of measuring point: Calculate the dynamic correction coefficient of the 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: The dynamic correction coefficients of the measuring points are used to fit the relationship between the dynamic correction coefficients of the three structures, the main legs, the diagonal braces and the horizontal braces, and the jacket height. S5. Response data correction: The response data of the measuring point is replaced with the measured response data of the measuring point. The non-measuring point is calculated according to the structural type and height, combined with the fitting relationship in step S4, and the corresponding dynamic correction coefficient is calculated, and the data is corrected; S6. The measured load used for correction and the corresponding corrected response data and their mapping relationship are stored in the digital twin system database to complete the correction.

2. The deepwater jacket digital twin database based on measured data according to claim 1, characterized in that: The database construction method in step S1 is: The digital twin system database obtained by the simulation end is corrected and expanded using the measured data obtained by the monitoring end; the measured data includes measured load data and measured response data; The monitoring end includes anemometer, wave measuring radar, current meter and load signal demodulation module data transmission, fiber Bragg grating strain sensor response signal demodulation module data transmission; 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 past wind speed data, past wave data, and past current data on the simulation end are stored as load data in the digital twin system database after joint sampling of sea conditions; the load data applies load to the simulation model on the simulation end, and the response of the simulation output 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, load data and mapping relationships, wherein the load data is formed by joint sampling of loads of past wind speed data, past wave data and past current data, and is regularly supplemented based on the measured load data; wherein the response data is formed by calculation of the simulation model and is corrected and expanded based on the 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: The structural components of the deepwater jacket are divided into three categories: main legs, diagonal braces and horizontal braces. Fiber Bragg grating strain sensors are arranged at three measuring points along the height direction of each structure. The monitoring data of the measuring points 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 is six-dimensional data including wind direction, wind speed, significant wave height, spectrum 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 by simulation at the corresponding position: ； in: is the dynamic correction factor of the member under the load of interest; is the measured response value of the rod under the sea condition; is the response value of the rod 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 correction data is as follows: under certain sea conditions, combined with the dynamic correction coefficient Calculate the dynamic correction coefficient of the rod along the change relationship of the jacket height direction , then under this sea condition, the corrected response value of the member is: ； in, is the response value of the rod under the corresponding sea conditions in the database.

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