A method, system, device and readable storage medium for determining a stress monitoring point of an offshore platform jacket structure

Abstract

This invention provides a method, system, device, and readable storage medium for determining stress monitoring points on a offshore platform jacket structure, belonging to the technical field of offshore platform structural safety monitoring. The method includes: establishing a finite element simulation analysis model of the offshore platform jacket structure; performing scenario sampling to obtain finite element stress simulation results for candidate monitoring points; calculating the correlation index and sensitivity index of the candidate monitoring points to extract a preliminary sample set of monitoring points; generating multiple vectors of the same dimension as the number of target monitoring points to obtain multiple monitoring point combination schemes; calculating the fitness of the monitoring point combination schemes; iterating according to a set search strategy, continuously updating the fitness after iteration until the iteration is complete; and determining the location of the target monitoring point based on the fitness after the iteration. This invention, through iterative optimization of the stress monitoring point layout scheme, can improve the targeting of sensor placement and save sensor placement costs.

Description

Technical Field

[0001] This invention relates to the field of marine platform structural safety monitoring technology, and in particular to a method, system, equipment, and readable storage medium for determining stress monitoring points of marine platform jacket structures. Background Technology

[0002] Offshore platform jacket structures are used to support offshore platforms and play a crucial role in offshore oil and gas exploration. However, exposure to environmental factors such as sea winds, waves, and currents causes long-term vibrations in offshore platforms, reducing their structural strength and impacting their safety. Therefore, to ensure safe operation of offshore platforms, it is necessary to conduct reasonable, scientific, and real-time vibration monitoring of the platform structure.

[0003] Vibration monitoring of offshore platform jacket structures is achieved by deploying sensors on the platform structure to acquire various information. However, factors such as the number of sensors and their placement on the structure can affect the accuracy of the sensor data, leading to deviations between the monitoring results and the actual situation. Currently, in production practice, the EI method (Effective Independence Method) is often used to deploy sensors. For example, CN118260894A discloses a sensor optimization placement method based on the assembled effective independence method, and CN116522709A discloses a sensor optimization placement method based on the two-dimensional effective independence method.

[0004] The EI method selects and discards measurement points by comparing their contributions to modal linear independence. It uses the diagonal elements of the E matrix to prioritize candidate points, and an iterative algorithm eliminates points with the smallest diagonal elements each time, repeating the iteration until a satisfactory number of points is obtained. However, the EI method does not consider environmental sensitivity factors when deploying sensors, resulting in a lack of specificity. Summary of the Invention

[0005] To address the above problems, this invention provides a method, system, device, and readable storage medium for determining stress monitoring points on a marine platform jacket structure.

[0006] This invention provides a method for determining stress monitoring points in a offshore platform jacket structure, comprising: Establish a finite element simulation analysis model for the jacket structure of an offshore platform; Based on the established finite element simulation analysis model of the offshore platform jacket structure, scenario sampling was performed to obtain the dynamic simulation results of the offshore platform finite element structure and the finite element stress simulation results of the candidate monitoring points. Based on the obtained finite element stress simulation results of the candidate monitoring points, the correlation index and sensitivity index of the candidate monitoring points are calculated, and a sample set of preliminary monitoring points is extracted according to the calculation results. Based on the extracted sample set of the initial monitoring points, multiple vectors with the same dimension as the number of target monitoring points are generated to obtain multiple monitoring point combination schemes. Based on the finite element stress simulation results of the candidate monitoring points in the finite element simulation analysis model of the offshore platform jacket structure, the fitness of the monitoring point combination scheme is calculated. Based on the fitness of the monitoring point combination scheme, the multiple monitoring point combination schemes are iterated according to the set search strategy, and the fitness of the multiple monitoring point combination schemes after the iteration is continuously updated until the iteration is completed. The location of the target monitoring point is determined based on the fitness of multiple monitoring point combination schemes after the iteration is completed.

[0007] As a further improvement of the present invention, the establishment of the finite element simulation analysis model of the offshore platform jacket structure includes the use of pipe elements to simulate the pile legs and diagonal braces of the offshore platform jacket structure, shell elements to simulate the platform deck, and mass elements to simulate the equipment load.

[0008] As a further improvement of the present invention, the step of sampling the scenario working conditions based on the established finite element simulation analysis model of the offshore platform jacket structure, obtaining the finite element structural dynamic simulation results of the offshore platform and the finite element stress simulation results of the candidate monitoring points, includes determining P types of environmental influencing factors and Q factor levels under each environmental influencing factor, and using the orthogonal experimental method to sample the scenario working conditions.

[0009] As a further improvement of the present invention, the calculation of the correlation index and sensitivity index of the candidate monitoring points includes calculating the correlation index of the candidate monitoring points using the following formula:

[0010] In the formula, , , The resolution coefficient, The stress value at the critical point under a certain factor. The stress value at the monitoring point under a certain factor, P This indicates the number of environmental factors, and Q represents the number of values ​​for each environmental category.

[0011] As a further improvement of the present invention, the calculation of the correlation index and sensitivity index of the candidate monitoring points includes calculating the sensitivity index of the candidate monitoring points using the following formula:

[0012] In the formula, , , This represents the magnitude of the stress value in a finite element simulation at a certain level for a given factor.P This indicates the number of environmental factors, and Q represents the number of values ​​for each environmental category.

[0013] As a further improvement of the present invention, based on the finite element stress simulation results of the alternative monitoring points in the finite element simulation analysis model of the offshore platform jacket structure, the fitness of the monitoring point combination scheme is calculated by using the following formula:

[0014] In the formula, This is a position correction factor; it is set to 1 for nodes above the sea surface and 0 for nodes below the sea surface. These are the modal weighting coefficients. For sensitivity weighting coefficients, This refers to the correlation weighting coefficient; in, , , The fitness of the monitoring point combination scheme is a comprehensive representation of the combination modal index K3, sensitivity index K2, and correlation index K1.

[0015] As a further improvement of the present invention, the combined modal index is:

[0016] In the formula, For the modal parameters of the monitoring points;

[0017] In the formula, This represents the column vector of mode shapes for the i-th principal vibration of an offshore platform. This represents the column vector of mode shapes for the j-th principal vibration of the offshore platform; the maximum values ​​of both i and j are equal to the mode order.

[0018] As a further improvement of the present invention, the maximum number of iterations maxIter and the number of search bodies FindN are determined, and the counter Counter=0 is initialized. FindN n-dimensional vectors are generated by random sorting, each vector being a search body object representing a feasible combination scheme of monitoring points, resulting in a total of FindN combination schemes of monitoring points. The combination modal index K3 and the fitness F value of FindN combination schemes of monitoring points are obtained according to the combination modal index K3 and the fitness calculation formula.

[0019] As a further improvement of the present invention, the fitness F values ​​of the FindN monitoring point combination schemes are sorted in descending order. The first third of feasible solutions with higher fitness are marked as the first type of search body, the last third of feasible solutions with lower fitness are marked as the third type of search body, and the other feasible solutions are marked as the second type of search body. The FindN search bodies use different search strategies according to the classification to find new feasible solutions and calculate the fitness F value of the new feasible solution. If it is greater than the fitness of the original search body, the feasible solution corresponding to the original search body is replaced; otherwise, the feasible solution corresponding to the original search body is not updated. After completing the iteration of all search bodies, Counter = Counter + 1 is set until Counter equals the preset maximum number of iterations maxIter, and the iteration stops.

[0020] As a further improvement of the present invention, the first type of search body adopts two search strategies: strategy one is to randomly search for an encoding position in the corresponding feasible solution, add 1 or subtract 1 to it, and ensure that there are no duplicate numbers in the result sequence; strategy two is to randomly search for an encoding position in the corresponding feasible solution, and randomly replace it with an integer different from other integers in the sequence. The second type of search body adopts two search strategies: Strategy 1 is to randomly search for two coding positions in the corresponding feasible solution and randomly replace them with integers different from other integers in the sequence; Strategy 2 is to randomly search for two coding positions in the feasible solution, randomly replace one of them with an integer different from other integers in the sequence, and add or subtract 1 to the other one, while ensuring that there are no duplicate numbers in the result sequence. The search strategy used in the third type of search body is the same as the method for generating the initial feasible solution. Both use a random sorting method, which involves randomly arranging integers from 1 to m and taking the first n integers as a new feasible solution sequence.

[0021] The present invention provides a system for determining stress monitoring points of a jacket structure on an offshore platform, comprising a finite element simulation analysis model establishment module, a scenario working condition sampling module, a preliminary monitoring point sample set extraction module, a monitoring point combination scheme acquisition module, a monitoring point combination scheme fitness calculation module, a monitoring point combination scheme iteration module, and a target monitoring point location determination module. The finite element simulation analysis model establishment module is used to establish a finite element simulation analysis model of the offshore platform jacket structure. The scenario working condition sampling module is used to perform scenario working condition sampling based on the established finite element simulation analysis model of the offshore platform jacket structure, and to obtain the dynamic simulation results of the offshore platform finite element structure and the finite element stress simulation results of the candidate monitoring points. The preliminary monitoring point sample set extraction module is used to calculate the correlation index and sensitivity index of the candidate monitoring points based on the finite element stress simulation results of the acquired candidate monitoring points, and extract the preliminary monitoring point sample set according to the calculation results. The monitoring point combination scheme acquisition module is used to generate multiple vectors with the same dimension as the number of target monitoring points based on the extracted initial selected monitoring point sample set, thereby obtaining multiple monitoring point combination schemes. The fitness calculation module of the monitoring point combination scheme is used to calculate the fitness of the monitoring point combination scheme based on the finite element stress simulation results of the candidate monitoring points in the finite element simulation analysis model of the offshore platform jacket structure. The monitoring point combination scheme iteration module is used to iterate multiple monitoring point combination schemes based on the fitness of the monitoring point combination schemes and according to a set search strategy, and continuously update the fitness of the multiple monitoring point combination schemes after iteration until the iteration is completed. The target monitoring point location determination module is used to determine the location of the target monitoring point based on the fitness of multiple monitoring point combination schemes after the iteration is completed.

[0022] The present invention provides an apparatus comprising a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program to implement the steps of the above-described method.

[0023] The present invention provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the steps of the above-described method.

[0024] This invention provides a method, system, device, and readable storage medium for determining stress monitoring points in the jacket structure of an offshore platform, and has at least one of the following technical effects: 1. By combining finite element modeling, scenario sampling, generation and iterative optimization of monitoring point combination schemes, and index evaluation, the monitoring point combination methods are compared and optimized to determine the location of stress monitoring points for the offshore platform jacket structure, thereby improving the targeting of monitoring point selection; 2. The calculation formulas for the correlation index, sensitivity index, combined modal index, and combined fitness index of the monitoring points were determined, which can provide a quantitative evaluation basis for the selection of stress monitoring points for the jacket structure of offshore platforms. 3. A combined iterative optimization algorithm for stress monitoring of offshore platform jacket structures has been developed, which includes four modes of local optimization strategies and a combined fitness representation, and can efficiently search for the optimal combination of stress monitoring points. Attached Figure Description

[0025] Figure 1This is a flowchart illustrating the method for determining stress monitoring points in the jacket structure of an offshore platform according to an embodiment of the present invention.

[0026] Figure 2 This is a schematic diagram of four local search strategies for determining stress monitoring points of a marine platform jacket structure according to an embodiment of the present invention.

[0027] Figure 3 This is a schematic diagram of the overall structural model of an offshore platform.

[0028] Figure 4 This is a schematic diagram showing the locations of alternative monitoring points for offshore platforms.

[0029] Figure 5 This is a schematic diagram showing the location of target monitoring points determined by the marine platform. Detailed Implementation

[0030] The following describes specific embodiments and appendices. Figure 1-5 The invention is described in detail so that those skilled in the art can more fully understand its purpose, features and effects.

[0031] Unless otherwise specified, all technical and scientific terms used in this invention have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains. In the event of any discrepancy between the definitions of terms in this invention and their commonly understood meaning by one of ordinary skill in the art to which this invention pertains, the definitions set forth herein shall prevail.

[0032] To address the stress monitoring challenges faced by offshore platform jacket structures during long-term service, this invention provides a method, system, equipment, and readable storage medium for determining stress monitoring points in offshore platform jacket structures. This supports the optimization of sensor placement on offshore platforms, ensuring the stability and safety of the platform structure and avoiding significant economic losses and adverse environmental impacts caused by structural failure.

[0033] Example 1 As a specific embodiment of the present invention, this embodiment provides a method for determining stress monitoring points of a offshore platform jacket structure, the specific steps of which are as follows: S100. Establish a finite element simulation analysis model for the offshore platform jacket structure. Specifically, a finite element simulation analysis model of the offshore platform jacket structure was established, taking into account the jacket structure and environmental load characteristics of the offshore platform where sensors are to be deployed. Piles and braces were simulated using pipe elements, the platform deck using shell elements, and equipment loads using mass elements.

[0034] S200. Based on the established finite element simulation analysis model of the offshore platform jacket structure, scenario working condition sampling is performed to obtain the finite element dynamic simulation results of the offshore platform structure and the finite element stress simulation results of the alternative monitoring points. Specifically, based on the platform's operating environment, P types of environmental influencing factors and Q factor levels for each factor are determined. For example, in the case of ocean current velocity, the Q factor levels refer to Q different ocean current velocities. Orthogonal experimental design is used to sample scenario conditions and perform structural response analysis under these conditions, obtaining the structural dynamic simulation results of the finite element model of the offshore platform. Since underwater monitoring is difficult, monitoring is conducted at surface locations, with monitoring points on the platform's surface serving as alternative monitoring points. Finite element stress simulation results are then obtained from these alternative monitoring points. S300. Based on the finite element stress simulation results of the candidate monitoring points, calculate the correlation index k1 and sensitivity index k2 of the candidate monitoring points, and extract the initial sample set of monitoring points according to the calculation results. Specifically, the correlation index represents the degree of correlation between the structural response parameters of a candidate monitoring point and the structural response parameters of a hazardous point. The correlation index k1 of the candidate monitoring points is expressed by the following formula:

[0035] In the formula, , , The resolution coefficient, The stress value at the critical point under a certain factor. The stress value at the monitoring point under a certain factor, P This indicates the number of environmental factors, and Q represents the number of values ​​for each environmental category.

[0036] The sensitivity index represents the degree to which the structural response parameters of a candidate monitoring point are sensitive to the environment. The sensitivity index k2 of the candidate monitoring point is expressed by the following formula:

[0037] In the formula, , , This represents the magnitude of the stress value in a finite element simulation at a certain level for a given factor. P This indicates the number of environmental factors, and Q represents the number of values ​​for each environmental category.

[0038] Based on the calculation results of the correlation index k1 and sensitivity index k2 of the candidate monitoring points, the k1 and k2 values ​​of the candidate monitoring points are summed, the summation results are sorted in descending order, and a set number of the top-ranked candidate monitoring points are extracted to form the initial monitoring point sample set.

[0039] Preferably, a preliminary monitoring point sample set is formed by extracting more than three times the number of target monitoring points n. Assuming that the preliminary monitoring point sample set contains m monitoring points, then m>3n.

[0040] S400. Based on the extracted sample set of preliminary monitoring points, generate multiple vectors of the same dimension as the number of target monitoring points to obtain multiple monitoring point combination schemes. Specifically, the maximum number of iterations (maxIter) and the number of search bodies (FindN) are determined. The counter (Counter) is initialized to 0. A random sorting method is used to generate FindN n-dimensional vectors, each of which is a search body object representing a feasible combination scheme of monitoring points. A total of FindN combination schemes of monitoring points are obtained.

[0041] S500. Based on the finite element stress simulation results of the candidate monitoring points in the finite element simulation analysis model of the offshore platform jacket structure, calculate the fitness of the monitoring point combination scheme. Specifically, the fitness F of the monitoring point combination scheme is a comprehensive representation of the combination modal index K3, sensitivity index K2, and correlation index K1, expressed as:

[0042] In the formula, This is the location correction factor; it is set to 1 for nodes above the sea surface and 0 for nodes below the sea surface. These are the modal weighting coefficients. For sensitivity weighting coefficients, The preferred coefficient is the correlation weight coefficient. Take 0.1, Take 0.1, Take 0.8; , .

[0043] Among them, the combined modal index is an index based on the principal vibration mode direction of the platform modal nodes, and the expression of the combined modal index K3 is:

[0044] In the formula, These are the modal parameters of the monitoring points.

[0045]

[0046] In the formula, This represents the column vector of mode shapes for the i-th principal vibration of an offshore platform. This represents the column vector of mode shapes for the j-th principal vibration of the offshore platform; the maximum values ​​of both i and j are equal to the mode order.

[0047] Based on the above scheme and the analysis of the finite element stress simulation results of the candidate monitoring points in the finite element simulation analysis model of the offshore platform jacket structure, the combined modal index K3 and fitness F value of the FindN monitoring point combination scheme are determined.

[0048] S600. Based on the fitness of the monitoring point combination scheme, iterate through multiple monitoring point combination schemes according to the set search strategy, continuously updating the fitness of the multiple monitoring point combination schemes after the iteration, until the iteration is completed. Specifically, the fitness F values ​​of the FindN monitoring point combination schemes are sorted in descending order. The top third of feasible solutions (monitoring point combination schemes) with higher fitness are marked as the first type of search entity, the bottom third of feasible solutions with lower fitness are marked as the third type of search entity, and the other feasible solutions are marked as the second type of search entity. The FindN search entities are used with different search strategies according to their classification to find new feasible solutions, and the fitness F value of the new feasible solution is calculated. If the fitness of the new feasible solution is greater than that of the original search entity, the feasible solution corresponding to the original search entity is replaced; otherwise, the feasible solution corresponding to the original search entity is not updated. After all search entities have been iterated, Counter = Counter + 1 is set until Counter equals the preset maximum number of iterations maxIter, at which point the iteration stops.

[0049] Furthermore, the first type of search body employs two search strategies: Strategy one involves randomly searching for an encoded position within the corresponding feasible solutions, incrementing or decrementing it by 1, and ensuring that there are no duplicate numbers in the resulting sequence, as shown in the reference. Figure 2 (a) Strategy two involves randomly searching for an encoded position in the corresponding feasible solution and randomly replacing it with an integer different from other integers in the sequence, as shown in the reference. Figure 2 (b)

[0050] The second type of search body employs two search strategies: Strategy one involves randomly searching for two encoded positions in the corresponding feasible solutions and randomly replacing them with integers different from other integers in the sequence, as shown in the reference. Figure 2 (c); Strategy two involves randomly searching for two encoding positions in the feasible solution, randomly replacing one of them with an integer different from the other integers in the sequence, and incrementing or decrementing the other by 1, while ensuring that there are no duplicate numbers in the resulting sequence. (Refer to...) Figure 2 (d)

[0051] The search strategy used by the third type of search body is consistent with the method for generating the initial feasible solution (i.e., the initial monitoring point combination scheme obtained in S400). Both are generated by random sorting, that is, the integers from 1 to m are randomly arranged and the first n integers are taken as a new feasible solution sequence.

[0052] S700. Determine the location of the target monitoring point based on the fitness of the combination scheme of multiple monitoring points after the iteration.

[0053] After the iteration stops when Counter equals the preset maximum number of iterations maxIter, the feasible solution vector corresponding to the one with the highest fitness among the final FindN search bodies is the optimal solution (the optimal combination of monitoring points), which is the recommended location of the stress monitoring points of the offshore platform jacket structure.

[0054] This invention comprehensively considers combined modal indices, sensitivity indices, and correlation indices, and optimizes the selection of stress monitoring point layout schemes through iterative optimization, thereby improving the targeting of sensor placement, saving sensor placement costs, and ensuring the safety of marine platforms.

[0055] Example 2 As a specific embodiment of the present invention, this embodiment provides a method for determining the stress monitoring points of a jacket structure of an offshore platform, and determines the location of stress monitoring points of a jacket structure of an offshore platform, with a target of 5 monitoring points.

[0056] 1. Establish a finite element simulation analysis model for the jacket structure of an offshore platform. Based on the structural drawings of a certain offshore platform, a finite element simulation analysis model of the offshore platform jacket structure was established using ANSYS finite element analysis software. The finite element simulation analysis model of the offshore platform jacket structure is as follows: Figure 3 As shown.

[0057] 2. Based on the platform's operating environment, scenario-based sampling was conducted to obtain the finite element structural dynamic simulation results of the offshore platform and the finite element stress simulation results of the alternative monitoring points. For the established finite element simulation analysis model of the offshore platform jacket structure, orthogonal experiments were conducted based on the basic environmental impact parameters of the offshore platform. These parameters included seven environmental factors: ocean current velocity (0.54 m / s–1.43 m / s), wave height (0.1 m–6.8 m), wave period (5.5 s–9.0 s), wind direction (0°–315°), current direction (0°–315°), wave direction (0°–315°), and wind speed (7.1 m / s–11.4 m / s). An orthogonal array was constructed based on these seven environmental factors and eight horizontal parameters for each factor, resulting in 64 experimental schemes. The finite element stress simulation results for candidate monitoring points were then obtained. The locations of the candidate monitoring points are shown below. Figure 4 As shown.

[0058] 3. Calculate the correlation index k1 and sensitivity index k2 of the candidate monitoring points, and extract the initial sample set of monitoring points based on the calculation results. Specifically, the k1 and k2 values ​​of the candidate monitoring points are summed, and the summation results are sorted in descending order to determine the initial sample set of monitoring points.

[0059] In this embodiment, there are 5 target monitoring points. Points with a number more than three times the number of target monitoring points are selected as the initial monitoring point sample set. In this embodiment, the top 20 candidate monitoring points are determined by descending order of the sum of the k1 and k2 values ​​of the candidate monitoring points to form the initial monitoring point sample set. The correlation index and sensitivity index of the initial monitoring points are shown in Table 1, where the resolution coefficient in the correlation index is... Take 0.5.

[0060]

[0061] 4. The maximum number of iterations was set to 100, the number of search volumes to 12, and the counter was initialized to 0. Based on the finite element stress simulation results of the candidate monitoring points in the finite element simulation analysis model of the offshore platform jacket structure, 12 5-dimensional vectors were generated using a random sorting method for the data in the initial selected monitoring point sample set. Each vector represents a search volume object, signifying a feasible monitoring point combination scheme. For example, [181213114] indicates monitoring at monitoring points 18, 12, 13, 1, and 14. Based on the third-order modal results of the candidate monitoring points in the finite element simulation analysis model of the offshore platform jacket structure, the combined modal index and fitness of the combination scheme were calculated. The modal index and fitness of the monitoring point layout schemes are shown in Table 2.

[0062]

[0063] The fitness value of monitoring point layout scheme 12 is the highest, at 0.60, and it is used as the initial monitoring point layout scheme.

[0064] The fitness values ​​of the monitoring point layout schemes were sorted in descending order, and the specific results are shown in Table 3. Based on the fitness values, the first third of feasible solutions with higher fitness were marked as Class I search bodies, the last third of feasible solutions with lower fitness were marked as Class III search bodies, and the other feasible solutions were marked as Class II search bodies.

[0065]

[0066] 5. The local search strategy adopted by the first type of search body is as follows: Figure 2 (a) and Figure 2 As shown in (b): Strategy 1 is to randomly search for an encoding position in the corresponding feasible solution, increment or decrement it by 1, and ensure that there are no duplicate numbers in the resulting sequence. Figure 2 (a)); Strategy two is to randomly search for an encoded position in the corresponding feasible solution and randomly replace it with an integer different from other integers in the sequence. Figure 2(b) Strategy 1 and Strategy 2 compare the fitness of the new individual in the neighborhood search with the fitness of the original individual. If the new individual's fitness is greater than that of the original individual, the feasible solution corresponding to the original individual is replaced; otherwise, the feasible solution corresponding to the original individual is not updated. The feasible solutions and fitness values ​​after the local search are shown in Table 4. Meanwhile, Counter = Counter + 1.

[0067]

[0068] 6. Each second-type search entity randomly follows a first-type search entity, using a local search strategy in its neighborhood to discover new feasible solutions. The local search strategy used by the second-type search entity is as follows: Figure 2 (c) and Figure 2 As shown in (d): Strategy 1 is to randomly search for two encoding positions in the corresponding feasible solutions and randomly replace them with integers different from other integers in the sequence. Figure 2 (c)); Strategy two involves randomly searching for two encoding positions in the feasible solution, randomly replacing one of them with an integer different from other integers in the sequence, and incrementing or decrementing the other by 1, while ensuring that there are no duplicate numbers in the resulting sequence. Figure 2 (d) The fitness of the new individual in the neighborhood search of Strategy 1 and Strategy 2 is compared with the fitness of the original individual. If the fitness of the new individual is greater than that of the original second-type search entity, the feasible solution corresponding to the original second-type search entity is replaced. Otherwise, the feasible solution corresponding to the original second-type search entity is not updated, as shown in Table 5.

[0069]

[0070] 7. Each third-type search entity randomly follows a second-type search entity and uses a local search strategy in its neighborhood to discover new feasible solutions. The search strategy used by the third-type search entity is the same as the method used to generate the initial feasible solution, which is generated by random sorting. The fitness of the new search entity is compared with the fitness of the original entity. If the fitness of the new search entity is greater than that of the original third-type search entity, the feasible solution corresponding to the original third-type search entity is replaced. If the fitness of the new search entity is greater than that of the original second-type search entity, the feasible solution corresponding to the original third-type search entity is not updated, as shown in Table 6.

[0071]

[0072] 8. Repeat steps 5-7 until Counter equals 100. The feasible solution [6 11 18 12 17] corresponding to the highest fitness among the final 12 search bodies represents the specific locations of the stress monitoring points on the offshore platform jacket structure. Monitoring points 1 and 2 are located near the water surface, monitoring points 3 and 4 are located near the connection between the main pile leg and the horizontal brace, and monitoring point 5 is located at the connection between the pile leg and the deck. The target monitoring point locations are as follows: Figure 5 As shown.

[0073] The optimization results and the fitness information of the initial monitoring location were compared and analyzed, and the results are shown in Table 7.

[0074]

[0075] As shown in Table 7, the correlation index, sensitivity index, modal index, and combined fitness index of the optimized monitoring point layout scheme are all greater than those of the initial monitoring point layout scheme, which indicates that the optimized marine platform stress monitoring point layout scheme is superior.

[0076] The method for determining stress monitoring points of the offshore platform jacket structure of the present invention analyzes the vibration frequency and stress variation characteristics of the offshore platform jacket structure under different external loads of wind, waves and currents, obtains different sets of calculated loads based on orthogonal experiments, and determines the location of stress intensity danger points and platform vibration frequency response sensitive points through correlation index, sensitivity index, combined modal index and combined fitness index, thereby completing the selection of stress monitoring points of the jacket structure.

[0077] Example 3 As a specific embodiment of the present invention, this embodiment provides a system for determining stress monitoring points of a jacket structure on an offshore platform, including a finite element simulation analysis model establishment module, a scenario working condition sampling module, a preliminary monitoring point sample set extraction module, a monitoring point combination scheme acquisition module, a monitoring point combination scheme fitness calculation module, a monitoring point combination scheme iteration module, and a target monitoring point location determination module.

[0078] Among them, the finite element simulation analysis model establishment module is used to establish a finite element simulation analysis model of the offshore platform jacket structure; The scenario working condition sampling module is used to perform scenario working condition sampling based on the established finite element simulation analysis model of the offshore platform jacket structure, and to obtain the dynamic simulation results of the finite element structure of the offshore platform and the finite element stress simulation results of the candidate monitoring points. The preliminary monitoring point sample set extraction module is used to calculate the correlation index and sensitivity index of the candidate monitoring points based on the finite element stress simulation results of the acquired candidate monitoring points, and extract the preliminary monitoring point sample set according to the calculation results. The monitoring point combination scheme acquisition module is used to generate multiple vectors with the same dimension as the number of target monitoring points based on the extracted initial selected monitoring point sample set, thereby obtaining multiple monitoring point combination schemes. The fitness calculation module for the monitoring point combination scheme is used to calculate the fitness of the monitoring point combination scheme based on the finite element stress simulation results of the candidate monitoring points in the finite element simulation analysis model of the offshore platform jacket structure. The monitoring point combination scheme iteration module is used to iterate multiple monitoring point combination schemes based on the fitness of the monitoring point combination scheme and according to the set search strategy, and continuously update the fitness of the multiple monitoring point combination schemes after iteration until the iteration is completed. The target monitoring point location determination module is used to determine the location of the target monitoring point based on the fitness of multiple monitoring point combination schemes after the iteration is completed.

[0079] The method and system for determining stress monitoring points of offshore platform jacket structures of the present invention are simple, fast, reliable and effective, which can reduce the cost of stress monitoring of offshore platform jacket structures and improve the convenience and accuracy of monitoring of offshore platform jacket structures.

[0080] Example 4 As a specific embodiment of the present invention, this embodiment provides an apparatus, including a memory, a processor, and a computer program stored in the memory. The processor executes the computer program to implement the steps of the method for determining stress monitoring points of the offshore platform jacket structure described in Embodiment 1.

[0081] Example 5 As a specific embodiment of the present invention, this embodiment provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps of the method for determining stress monitoring points of the offshore platform jacket structure described in Embodiment 1.

[0082] This invention relates to the selection of stress monitoring points for long-term service offshore platform jacket structures, so as to deploy sensors to monitor the stress and vibration of the offshore platform jacket structure, thereby ensuring the service safety of the entire offshore platform jacket structure.

[0083] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention in any other way. Any modifications or equivalent changes made based on the technical essence of the present invention shall still fall within the scope of protection claimed by the present invention.

Claims

1. A method for determining stress monitoring points in a jacket structure of an offshore platform, characterized in that, The method includes: Establish a finite element simulation analysis model for the jacket structure of an offshore platform; Based on the established finite element simulation analysis model of the offshore platform jacket structure, scenario sampling was performed to obtain the dynamic simulation results of the offshore platform finite element structure and the finite element stress simulation results of the candidate monitoring points. Based on the obtained finite element stress simulation results of the candidate monitoring points, the correlation index and sensitivity index of the candidate monitoring points are calculated, and a sample set of preliminary monitoring points is extracted according to the calculation results. Based on the extracted sample set of the initial monitoring points, multiple vectors with the same dimension as the number of target monitoring points are generated to obtain multiple monitoring point combination schemes. Based on the finite element stress simulation results of the candidate monitoring points in the finite element simulation analysis model of the offshore platform jacket structure, the fitness of the monitoring point combination scheme is calculated. Based on the fitness of the monitoring point combination scheme, the multiple monitoring point combination schemes are iterated according to the set search strategy, and the fitness of the multiple monitoring point combination schemes after the iteration is continuously updated until the iteration is completed. The location of the target monitoring point is determined based on the fitness of multiple monitoring point combination schemes after the iteration is completed.

2. The method for determining stress monitoring points of offshore platform jacket structures according to claim 1, characterized in that, The establishment of the finite element simulation analysis model of the offshore platform jacket structure includes the use of pipe elements to simulate the pile legs and diagonal braces of the offshore platform jacket structure, shell elements to simulate the platform deck, and mass elements to simulate the equipment load.

3. The method for determining stress monitoring points of a offshore platform jacket structure according to claim 1, characterized in that, Based on the established finite element simulation analysis model of the offshore platform jacket structure, scenario sampling is performed to obtain the finite element structural dynamic simulation results of the offshore platform and the finite element stress simulation results of the candidate monitoring points. This includes determining P types of environmental influencing factors and Q factor levels under each environmental influencing factor, and using the orthogonal experimental method to perform scenario sampling.

4. The method for determining stress monitoring points of offshore platform jacket structures according to claim 1, characterized in that, The calculation of the correlation index and sensitivity index of the candidate monitoring points includes calculating the correlation index of the candidate monitoring points using the following formula: In the formula, , , The resolution coefficient, The stress value at the critical point under a certain factor. The stress value at the monitoring point under a certain factor, P This indicates the number of environmental factors, and Q represents the number of values ​​for each environmental category.

5. The method for determining stress monitoring points of offshore platform jacket structures according to claim 4, characterized in that, The calculation of the correlation index and sensitivity index of the candidate monitoring points includes calculating the sensitivity index of the candidate monitoring points using the following formula: In the formula, , , This represents the magnitude of the stress value in a finite element simulation at a certain level for a given factor. P This indicates the number of environmental factors, and Q represents the number of values ​​for each environmental category.

6. The method for determining stress monitoring points of a offshore platform jacket structure according to claim 5, characterized in that, Based on the finite element stress simulation results of the candidate monitoring points in the finite element simulation analysis model of the offshore platform jacket structure, the fitness of the monitoring point combination scheme is calculated using the following formula: In the formula, This is a position correction factor; it is set to 1 for nodes above the sea surface and 0 for nodes below the sea surface. These are the modal weighting coefficients. For sensitivity weighting coefficients, This refers to the correlation weighting coefficient; in, , , The fitness of the monitoring point combination scheme is a comprehensive representation of the combination modal index K3, sensitivity index K2, and correlation index K1.

7. The method for determining stress monitoring points of offshore platform jacket structures according to claim 6, characterized in that, The combined modal index is: In the formula, For the modal parameters of the monitoring points; In the formula, This represents the column vector of mode shapes for the i-th principal vibration of an offshore platform. This represents the column vector of mode shapes for the j-th principal vibration of the offshore platform; the maximum values ​​of both i and j are equal to the mode order.

8. A system for determining stress monitoring points in a offshore platform jacket structure, characterized in that, It includes modules for establishing finite element simulation analysis models, sampling scenarios, extracting sample sets of initial monitoring points, obtaining monitoring point combination schemes, calculating the fitness of monitoring point combination schemes, iterating monitoring point combination schemes, and determining the location of target monitoring points. The finite element simulation analysis model establishment module is used to establish a finite element simulation analysis model of the offshore platform jacket structure. The scenario working condition sampling module is used to perform scenario working condition sampling based on the established finite element simulation analysis model of the offshore platform jacket structure, and to obtain the dynamic simulation results of the offshore platform finite element structure and the finite element stress simulation results of the candidate monitoring points. The preliminary monitoring point sample set extraction module is used to calculate the correlation index and sensitivity index of the candidate monitoring points based on the finite element stress simulation results of the acquired candidate monitoring points, and extract the preliminary monitoring point sample set according to the calculation results. The monitoring point combination scheme acquisition module is used to generate multiple vectors with the same dimension as the number of target monitoring points based on the extracted initial selected monitoring point sample set, thereby obtaining multiple monitoring point combination schemes. The fitness calculation module of the monitoring point combination scheme is used to calculate the fitness of the monitoring point combination scheme based on the finite element stress simulation results of the candidate monitoring points in the finite element simulation analysis model of the offshore platform jacket structure. The monitoring point combination scheme iteration module is used to iterate multiple monitoring point combination schemes based on the fitness of the monitoring point combination schemes and according to a set search strategy, and continuously update the fitness of the multiple monitoring point combination schemes after iteration until the iteration is completed. The target monitoring point location determination module is used to determine the location of the target monitoring point based on the fitness of multiple monitoring point combination schemes after the iteration is completed.

9. An apparatus comprising a memory, a processor, and a computer program stored in the memory, characterized in that, The processor executes the computer program to implement the steps of the method according to any one of claims 1-7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1-7.

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