A stress simulation method for super-large cable bridges based on digital twins

Abstract

The present disclosure relates to a stress simulation method for a super-large cable bridge based on digital twins, and relates to the field of computer technology; using non-standard erection data that has a negative impact on the stress of a super-large cable bridge, a variety of super-large cable bridge erection data are constructed, and based on the various super-large cable bridge erection data, a plurality of stress simulation models are constructed, so that the plurality of stress simulation models can reflect the super-large cable bridge conditions under different negative impact erection data, thereby improving the diversity of stress simulation models. By combining a diverse stress simulation model with real operation monitoring data, a stress simulation analysis of a super-large cable bridge is performed, and stress simulation of a super-large cable bridge based on digital twins is realized, thereby improving the diversity and applicability of stress simulation.

Description

Technical Field

[0001] The present disclosure relates to the field of computer technology, and in particular to a stress simulation method for a super-large cable bridge based on digital twins. Background Art

[0002] With the development of computer technology, simulation technology has also developed. In more and more scenarios, simulation technology is used to achieve data analysis. Taking digital twin technology as an example, digital twin technology can combine virtual and real, for example, real data can be applied to virtual simulation models to achieve data analysis. In the field of bridges, digital twin technology can be used to simulate some data of bridges. Summary of the invention

[0003] The purpose of the present disclosure is to provide a stress simulation method for a super-large cable bridge based on digital twins.

[0004] In order to achieve the above-mentioned purpose, the present disclosure provides a stress simulation method for a super-large cable bridge based on digital twins, comprising: obtaining a variety of super-large cable bridge erection data, the various super-large cable bridge erection data including irregular erection data that have a negative impact on the stress of the super-large cable bridge, and the irregular erection data in different super-large cable bridge erection data are different; constructing a plurality of stress simulation models according to the plurality of super-large cable bridge erection data, each stress simulation model corresponding to a super-large cable bridge erection data; obtaining operation monitoring data of the super-large cable bridge, and determining simulation data corresponding to the plurality of stress simulation models respectively according to the operation monitoring data; performing stress simulation according to the plurality of stress simulation models and the simulation data corresponding to the plurality of stress simulation models respectively, to obtain stress simulation results.

[0005] Optionally, the obtaining of multiple super-large cable bridge erection data includes: obtaining real erection data of the super-large cable bridge; if the real erection data includes target real erection data having a negative impact on the stress of the super-large cable bridge, generating the multiple super-large cable bridge erection data according to the real erection data, the irregular erection data in the various super-large cable bridge erection data includes the target real erection data and / or associated real erection data of the target real erection data, and the associated real erection data is the real erection data having an impact on the target real erection data; if the real erection data does not include the target real erection data having a negative impact on the stress of the super-large cable bridge, obtaining preset simulated irregular erection data having a negative impact on the stress of the super-large cable bridge, and generating the multiple super-large cable bridge erection data according to the simulated irregular erection data and the real erection data.

[0006] Optionally, constructing multiple stress simulation models according to the multiple super-large cable bridge erection data includes: constructing multiple original stress simulation models according to the multiple super-large cable bridge erection data, each original stress simulation model corresponds to a super-large cable bridge erection data; obtaining preset simulation model test data; performing simulation tests on the multiple original stress simulation models according to the simulation model test data to obtain simulation test results, and the simulation test results are used to characterize whether the multiple original stress simulation models are feasible; constructing the multiple stress simulation models according to the simulation test results and the multiple original stress simulation models.

[0007] Optionally, constructing the multiple stress simulation models according to the simulation test results and the multiple original stress simulation models includes: determining the number of feasible original stress simulation models according to the simulation test results; if the number of feasible original stress simulation models is greater than or equal to a preset number, determining the feasible original stress simulation models as the final multiple stress simulation models; if the number of feasible original stress simulation models is less than the preset number, screening out some original stress simulation models from unfeasible original stress simulation models, adjusting the some original stress simulation models to obtain adjusted stress simulation models, and constructing the multiple stress simulation models according to the adjusted stress simulation models and the feasible original stress simulation models.

[0008] Optionally, the operation monitoring data includes real-time operation monitoring data and historical operation monitoring data, and determining the simulation data corresponding to the multiple stress simulation models respectively according to the operation monitoring data includes: determining first simulation data corresponding to the multiple stress simulation models respectively according to the real-time operation monitoring data, the first simulation data being used to simulate the real-time stress situation; determining second simulation data corresponding to the multiple stress simulation models respectively according to the real-time operation monitoring data and the historical operation monitoring data, the second simulation data being used to simulate the stress change situation; determining the simulation data corresponding to the multiple stress simulation models respectively according to the first simulation data corresponding to the multiple stress simulation models respectively and the second simulation data corresponding to the multiple stress simulation models respectively.

[0009] Optionally, determining the second simulation data respectively corresponding to the multiple stress simulation models based on the real-time operation monitoring data and the historical operation monitoring data includes: determining first operation monitoring data from the historical operation monitoring data, the difference between which is greater than a preset difference with the real-time operation monitoring data; determining second operation monitoring data adjacent to the first operation monitoring data from the historical operation monitoring data; determining target operation monitoring data based on the first operation monitoring data, the monitoring time corresponding to the first operation monitoring data, the second operation data, and the monitoring time corresponding to the second operation monitoring data; and determining the second simulation data respectively corresponding to the multiple stress simulation models based on the target operation monitoring data.

[0010] Optionally, the simulation data corresponding to each of the stress simulation models include first simulation data and second simulation data, the first simulation data is used to simulate the real-time stress situation, and the second simulation data is used to simulate the stress change situation, and the stress simulation is performed according to the multiple stress simulation models and the simulation data corresponding to the multiple stress simulation models to obtain a stress simulation result, including: performing stress simulation according to the first simulation data corresponding to the multiple stress simulation models to obtain a first stress simulation result, the first stress simulation result is used to characterize whether each stress simulation model has an abnormal real-time stress situation; performing stress simulation according to the first stress simulation result and the second simulation data corresponding to the multiple stress simulation models to obtain a second stress simulation result, the second stress simulation result is used to characterize whether at least part of the stress simulation models has an abnormal stress change situation; determining a final stress simulation result according to the first stress simulation result and the second stress simulation result, the final stress simulation result is used to characterize whether the super-large cable bridge has stress abnormality.

[0011] Optionally, performing stress simulation according to the first stress simulation result and the second simulation data corresponding to the multiple stress simulation models respectively to obtain a second stress simulation result includes: determining, according to the stress simulation result, a first stress simulation model with an abnormal real-time stress situation and a second stress simulation model without an abnormal real-time stress situation; determining, from the first stress simulation model, a third stress simulation model corresponding to the specified non-standard erection data; performing stress simulation on the second stress simulation model according to the second simulation data corresponding to the second stress simulation model to obtain a stress simulation result of the second stress simulation model; performing stress simulation on the third stress simulation model according to the second simulation data corresponding to the third stress simulation model to obtain a stress simulation result of the third stress simulation model; determining the second stress simulation result according to the stress simulation result of the second stress simulation model and the stress simulation result of the third stress simulation model.

[0012] Optionally, the stress simulation result is used to characterize whether there is stress anomaly in the super-large cable bridge, and the operation monitoring data is data obtained from a monitoring device. The stress simulation method also includes: if the stress simulation result characterizes that there is stress anomaly in the super-large cable bridge, the stress simulation result and the irregular erection data corresponding to the multiple stress simulation models are fed back to the monitoring device, so that the monitoring device determines the stress monitoring result according to the stress simulation result, the irregular erection data corresponding to the multiple stress simulation models, and the operation monitoring data; receives the stress monitoring result fed back by the monitoring device, and the stress monitoring result is used to characterize whether there is stress anomaly in the super-large cable bridge; and optimizes the multiple stress simulation models according to the stress monitoring result and the stress simulation result.

[0013] Optionally, the multiple stress simulation models are optimized according to the stress monitoring result, including: if the stress monitoring result indicates that the super-large cable bridge has stress anomaly, optimizing some stress simulation models in the multiple stress simulation models to optimize the non-standard erection data corresponding to the some stress simulation models; if the stress monitoring result indicates that the super-large cable bridge has no stress anomaly, reducing the number of the multiple stress simulation models and / or reducing the frequency of stress simulation.

[0014] Through the above technical scheme, the non-standard erection data that has a negative impact on the stress of the super-large cable bridge is used to construct a variety of super-large cable bridge erection data. Based on the various super-large cable bridge erection data, multiple stress simulation models are constructed, so that multiple stress simulation models can reflect the super-large cable bridge conditions under different negative impact erection data, thereby improving the diversity of stress simulation models. By obtaining operation monitoring data, the simulation data corresponding to multiple stress simulation models are determined, and stress simulation is performed, and the operation monitoring data is analyzed through the stress simulation model, so that the applicability of the stress simulation results is relatively high. Therefore, the technical scheme combines a diverse stress simulation model with real operation monitoring data to perform stress simulation analysis of super-large cable bridges, realizes stress simulation of super-large cable bridges based on digital twins, and improves the diversity and applicability of stress simulation.

[0015] Other features and advantages of the present disclosure will be described in detail in the following detailed description. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] The accompanying drawings are used to provide a further understanding of the present disclosure and constitute a part of the specification. Together with the following specific embodiments, they are used to explain the present disclosure but do not constitute a limitation of the present disclosure. In the accompanying drawings:

[0017] Figure 1The figure is an example diagram of an application scenario according to an exemplary embodiment.

[0018] Figure 2 It is a flow chart of a stress simulation method of a super-large cable bridge based on digital twin according to an exemplary embodiment.

[0019] Figure 3 is a schematic diagram of a stress simulation process provided according to an exemplary embodiment.

[0020] Figure 4 is a stress simulation application flow chart provided according to an exemplary embodiment.

[0021] Figure 5 It is a structural block diagram of a stress simulation device for a super-large cable bridge based on digital twins provided according to an exemplary embodiment.

[0022] Figure 6 It is a block diagram of an electronic device according to an exemplary embodiment. DETAILED DESCRIPTION

[0023] The specific implementation of the present disclosure is described in detail below in conjunction with the accompanying drawings. It should be understood that the specific implementation described herein is only used to illustrate and explain the present disclosure, and is not used to limit the present disclosure.

[0024] With the development of computer technology, simulation technology has also developed. In more and more scenarios, simulation technology is used to achieve data analysis. Taking digital twin technology as an example, digital twin technology can combine virtual and real, for example, real data can be applied to virtual simulation models to achieve data analysis. In the field of bridges, digital twin technology can be used to simulate some data of bridges.

[0025] For super-large cable bridges, their design faces the influence of various factors such as weight, lateral stiffness, earthquake, ship collision, temperature, wind, etc. Therefore, after the super-large cable bridge is built, relevant monitoring of the super-large cable bridge is required to ensure its operational stability and safety.

[0026] Therefore, the application scenario of the technical solution of the embodiment of the present disclosure can be the monitoring scenario of a super-large cable bridge.

[0027] In some embodiments, after the construction of the super-large cable bridge, stress simulation can be used to analyze whether there are any problems with the construction of the super-large cable bridge. Therefore, the application scenario of the technical solution of the embodiment of the present disclosure can also be the maintenance scenario of the super-large cable bridge.

[0028] In different application scenarios, stress simulation may have different effects, which are not limited in the embodiments of the present disclosure.

[0029] In the related art, the stress simulation of super-large cable bridges is realized by applying simulated data. This stress simulation method makes the stress simulation data single and not combined with the real data, which makes the diversity and applicability of the stress simulation poor.

[0030] Based on this, the embodiment of the present disclosure provides a technical solution, in which stress simulation of a super-large cable bridge is performed based on digital twin technology. By using non-standard erection data that has a negative impact on the stress of the super-large cable bridge, a variety of super-large cable bridge erection data are constructed, and based on the various super-large cable bridge erection data, a plurality of stress simulation models are constructed, so that the plurality of stress simulation models can reflect the super-large cable bridge conditions under different negative impact erection data, thereby improving the diversity of stress simulation models. By acquiring operation monitoring data, the simulation data corresponding to the plurality of stress simulation models are determined, and stress simulation is performed, so that the operation monitoring data can be analyzed through the stress simulation model, so that the applicability of the stress simulation results is higher. Furthermore, stress simulation of super-large cable bridges based on digital twins is realized, and diversity and applicability are improved.

[0031] Regarding digital twin technology, the virtual and the real can be combined. In the embodiments of the present disclosure, virtual data refers to the virtual simulation model, and real data refers to the real operation monitoring data.

[0032] Figure 1 is an example diagram of an application scenario according to an exemplary embodiment. Figure 1 As shown, the application scenario involves stress simulation equipment, monitoring equipment and data acquisition equipment, wherein the monitoring equipment can be connected to the data equipment through the Internet of Things, and the stress simulation equipment can be connected to the monitoring equipment through communication (the connection method is not limited).

[0033] The data acquisition device may involve multiple data acquisition devices, which respectively collect different operating data.

[0034] This application scenario can correspond to the monitoring scenario of a super-large cable bridge, so it involves monitoring equipment and data acquisition equipment.

[0035] In some embodiments, the data acquisition device can be used to collect the actual operation data of the super-large cable bridge and send it to the monitoring device.

[0036] In some embodiments, the monitoring device can generate operation monitoring data based on the real operation data. The operation monitoring data can be sent to the stress simulation device and can also be used to perform abnormal analysis on the super-large cable bridge.

[0037] Furthermore, for stress simulation equipment, the operation monitoring data can be used to perform stress simulation analysis and feed back to the monitoring equipment.

[0038] Figure 2 is a flow chart of a stress simulation method for a super-large cable bridge based on digital twins according to an exemplary embodiment. Figure 2 As shown, the method includes:

[0039] Step S21, obtaining various super-large cable bridge erection data, wherein the various super-large cable bridge erection data include irregular erection data having a negative impact on the stress of the super-large cable bridge, and the irregular erection data in different super-large cable bridge erection data are different.

[0040] Step S22, constructing a plurality of stress simulation models according to a plurality of super-large cable bridge erection data, wherein each stress simulation model corresponds to a type of super-large cable bridge erection data.

[0041] Step S23, obtaining operation monitoring data of the super-large cable bridge, and determining simulation data corresponding to a plurality of stress simulation models respectively according to the operation monitoring data.

[0042] Step S24, performing stress simulation according to the multiple stress simulation models and the simulation data respectively corresponding to the multiple stress simulation models to obtain stress simulation results.

[0043] In some embodiments, step S21 and step S22 may be pre-executed steps, that is, the plurality of stress simulation models may be pre-built models.

[0044] In some embodiments, the super-large cable bridge erection data involves a variety of erection data, such as weight, material, stiffness, length, width, structural parameters, elastic modulus, etc. These erection data determine the final erection result of the super-large cable bridge. At the same time, these erection data can also be used to construct a virtual super-large cable bridge model.

[0045] In some embodiments, a stress simulation model can be constructed for each super-large cable bridge erection data.

[0046] In some embodiments, the non-standard erection data that has a negative impact on the stress of the super-large cable bridge may be data that causes a safety hazard to the super-large cable bridge that is finally erected, for example, excessive weight data, inappropriate stiffness data, wrong material data, inappropriate structure data, etc.

[0047] Therefore, if a super-large cable bridge model (i.e., a stress simulation model) is constructed based on the super-large cable bridge erection data, various actual negative impact erection data of the super-large cable bridge can be simulated to simulate a variety of super-large cable bridge models.

[0048] In some embodiments, various super-large cable bridge erection data may be directly provided by stress simulation engineers.

[0049] In some embodiments, the super-large cable bridge erection data may be determined based on actual erection data.

[0050] Therefore, as an optional implementation, step S21 includes: obtaining real erection data of the super-large cable bridge; if the real erection data includes target real erection data that has a negative impact on the stress of the super-large cable bridge, generating a variety of super-large cable bridge erection data based on the real erection data, and the irregular erection data in the various super-large cable bridge erection data include the target real erection data and / or the associated real erection data of the target real erection data, and the associated real erection data is the real erection data that has an impact on the target real erection data; if the real erection data does not include the target real erection data that has a negative impact on the stress of the super-large cable bridge, obtaining preset simulated irregular erection data that has a negative impact on the stress of the super-large cable bridge, and generating a variety of super-large cable bridge erection data based on the simulated irregular erection data and the real erection data.

[0051] In this implementation, the super-large cable bridge corresponds to real erection data, and the real erection data may be erection data provided by engineers.

[0052] In some embodiments, it is possible to detect whether the real erection data includes target real erection data that has a negative impact on the stress of the super-large cable bridge. For example, the real erection data includes multiple data items, each of which corresponds to a normal data range. If it is within the normal data range, there is no negative impact, and if it is not within the normal data range, there is a negative impact.

[0053] Furthermore, based on the existence of target real erection data, various super-large cable bridge erection data can be directly generated using the real erection data, so that the non-standard erection data in various super-large cable bridge erection data include the target real erection data and / or the associated real erection data of the target real erection data, and the associated real erection data is the real erection data that has an impact on the target real erection data.

[0054] In some embodiments, generating a variety of super-large cable bridge erection data based on actual erection data can be achieved by performing data transformation on the actual erection data.

[0055] For example, the real erection data includes data A, data B, data C and data D. Among them, the erection data with negative impact is data A, and the associated data of data A is data D. Then, a super-large cable bridge erection data can be directly generated based on data A, data B, data C and data D, and data A is the non-standard erection data. And, after determining the transformation data A1 of data A and the transformation data D1 of data D, a super-large cable bridge erection data can also be generated based on data A1, data B, data C and data D, a super-large cable bridge erection data can be generated based on data A, data B, data C and data D1, and a super-large cable bridge erection data can be generated based on data A1, data B, data C and data D1.

[0056] Through this implementation method, not only can the real erection data that originally had non-standard erection data be retained, but also the simulated erection data corresponding to more non-standard erection data can be expanded to improve the diversity of super-large cable bridge erection data.

[0057] In some embodiments, if the actual erection data does not include the target actual erection data that has a negative impact on the stress of the super-large cable bridge, there are two possibilities: one is that the erection of the super-large cable bridge is relatively in line with the specifications, and the other is that the engineer concealed the data that does not meet the specifications, that is, data falsification. Moreover, even if the initial erection is in accordance with the specifications, the erection data may change due to use in the later stage, and it is necessary to simulate the situation where there is a negative impact.

[0058] Then, a variety of super-large cable bridge erection data can be generated by combining the preset simulated non-standard erection data that have a negative impact on the stress of the super-large cable bridge and the real erection data.

[0059] In this embodiment, the preset simulated irregular erection data having a negative impact on the stress of the super-large cable bridge may be data set by a simulation engineer, or may be data determined by collecting a large amount of irregular erection data.

[0060] In some embodiments, simulated non-standard erection data can be used to replace corresponding data in real erection data to generate a variety of super-large cable bridge erection data.

[0061] For example, the actual erection data includes data A, data B, data C and data D, and the preset simulated non-standard erection data includes: data A2, data B2, data C2 and data D2. Then the generated various super-large cable bridge erection data may include: data A2, data B, data C and data D; data A, data B2, data C and data D; data A, data B, data C2 and data D; data A, data B, data C and data D2; data A2, data B2, data C and data D, data A, data B2, data C2 and data D, etc. They are not listed one by one here, and the number of data replaced each time can be configured according to needs.

[0062] In step S22, a plurality of stress simulation models may be constructed according to a plurality of super-large cable bridge erection data, so that each stress simulation model corresponds to a type of super-large cable bridge erection data.

[0063] Regarding the construction method of the stress simulation model, reference may be made to mature simulation technologies in the art, and different implementation methods may be adopted depending on the simulation software used.

[0064] In some embodiments, the constructed stress simulation model may be tested to ensure the feasibility of the simulation operation.

[0065] Therefore, as an optional implementation, step S22 includes: constructing multiple original stress simulation models based on multiple super-large cable bridge erection data, each original stress simulation model corresponds to a super-large cable bridge erection data; obtaining preset simulation model test data; performing simulation tests on multiple original stress simulation models based on the simulation model test data to obtain simulation test results, and the simulation test results are used to characterize whether the multiple original stress simulation models are feasible; and constructing multiple stress simulation models based on the simulation test results and multiple original stress simulation models.

[0066] In some embodiments, the simulation model test data can be used to verify whether the original stress simulation model is feasible. Thus, the simulation model test data can include multiple test items, and the original stress simulation model is run using multiple test items. If the original stress simulation model can run normally, it indicates that it is feasible, and if it cannot run normally, it indicates that it is not feasible.

[0067] For example, for a super-large cable bridge erection model, it needs to bear a certain weight. Therefore, the test data can be a weight within a normal range applied to the bridge deck of the original stress simulation model. If the simulation test results indicate that the original stress simulation model can bear a weight within the normal range, it means that it is feasible.

[0068] Alternatively, the original stress simulation model may also be tested according to other test items for evaluating feasibility, which are not limited here.

[0069] Further, constructing multiple stress simulation models according to the simulation test results and multiple original stress simulation models may include: determining the number of feasible original stress simulation models according to the simulation test results; if the number of feasible original stress simulation models is greater than or equal to a preset number, determining the feasible original stress simulation models as the final multiple stress simulation models; if the number of feasible original stress simulation models is less than the preset number, screening out some original stress simulation models from the unfeasible original stress simulation models, adjusting some original stress simulation models to obtain adjusted stress simulation models, and constructing multiple stress simulation models according to the adjusted stress simulation models and the feasible original stress simulation models.

[0070] In some embodiments, the preset number may be the minimum number of stress simulation models to ensure diversity, and is set according to requirements in different application scenarios and is not limited here.

[0071] In some embodiments, if the quantity does not meet the requirement, some of the original stress simulation models may be adjusted to meet the preset quantity requirement, wherein the adjustment method may be: reducing non-standard erection data, or changing other erection data that may make the model unfeasible.

[0072] In some embodiments, when making adjustments, testing can be performed while making adjustments until the test results are feasible, and then the adjusted stress simulation model is considered to be obtained.

[0073] Then, the adjusted stress simulation model and the feasible original stress simulation model are used as the final multiple stress simulation models.

[0074] In step S23, operation monitoring data of the super-large cable bridge is obtained to generate simulation data corresponding to a plurality of stress simulation models.

[0075] In some embodiments, the operation monitoring data may involve multiple aspects of monitoring data, such as: load weight data, external environment data. The external environment data may involve wind data, temperature data, etc. These data can be collected through Internet of Things technology. For details, please refer to the mature technology in the field and will not be introduced in detail here.

[0076] In some embodiments, the operation monitoring data of the super-large cable bridge can be directly used as the simulation data corresponding to each stress simulation model.

[0077] In some embodiments, the operation monitoring data includes real-time operation monitoring data and historical operation monitoring data. Based on these two types of operation monitoring data, two types of simulation data can be constructed.

[0078] Therefore, step S13 may include: determining first simulation data corresponding to multiple stress simulation models respectively according to real-time operation monitoring data, the first simulation data being used to simulate real-time stress conditions; determining second simulation data corresponding to multiple stress simulation models respectively according to real-time operation monitoring data and historical operation monitoring data, the second simulation data being used to simulate stress changes; determining simulation data corresponding to multiple stress simulation models respectively according to the first simulation data corresponding to multiple stress simulation models respectively and the second simulation data corresponding to multiple stress simulation models respectively.

[0079] In this implementation, the real-time operation monitoring data can be determined as the first simulation data corresponding to each stress simulation model. If the real-time operation monitoring data only involves one data item, the first simulation data corresponding to each stress simulation model can be the same; if the real-time operation monitoring data involves multiple data items, the first simulation data corresponding to each stress simulation model can be different, for example, some stress simulation models have different corresponding data items.

[0080] In some embodiments, the second simulation data is used to simulate stress variation, so the second simulation data needs to involve variation data rather than data at a single time point.

[0081] As an optional implementation, second simulation data corresponding to multiple stress simulation models are determined based on real-time operation monitoring data and historical operation monitoring data, including: determining first operation monitoring data from historical operation monitoring data, the difference between which and real-time operation monitoring data is greater than a preset difference; determining second operation monitoring data adjacent to the first operation monitoring data from historical operation monitoring data; determining target operation monitoring data based on the first operation monitoring data, the monitoring time corresponding to the first operation monitoring data, the second operation data, and the monitoring time corresponding to the second operation monitoring data; and determining second simulation data corresponding to multiple stress simulation models based on the target operation monitoring data.

[0082] In this implementation, the preset difference value can be configured according to different data items, which can represent more obvious data changes.

[0083] Therefore, the first operation monitoring data is operation monitoring data having a large difference from the real-time operation monitoring data.

[0084] The second operation monitoring data adjacent to the first operation monitoring data may be data collected at adjacent times, which may be a turning point of data change.

[0085] Furthermore, by sorting them according to the collection time, the target operation monitoring data representing the changes over time can be obtained.

[0086] Furthermore, the target operation monitoring data may be used as the second simulation data.

[0087] For example, if the current time point is t, the corresponding real-time operation monitoring data is represented as Xt. Through analysis, the target operation monitoring data includes: X(t-10), X(t-9), X(t-8), X(t-5), X(t-4), X(t-3), then X(t-9) and X(t-4) can be the first operation monitoring data, and the other data can be the second operation monitoring data.

[0088] Furthermore, the first simulation data and the second simulation data may be integrated as simulation data corresponding to a plurality of stress simulation models, for example, by performing format standardization processing and integration on the data.

[0089] In step S24, stress simulation is performed according to the multiple stress simulation models and the simulation data respectively corresponding to the multiple stress simulation models to obtain a stress simulation result.

[0090] In some embodiments, step S24 may include: performing stress simulation according to first simulation data corresponding to multiple stress simulation models, obtaining a first stress simulation result, the first stress simulation result is used to characterize whether each stress simulation model has abnormal real-time stress conditions; performing stress simulation according to the first stress simulation result and second simulation data corresponding to multiple stress simulation models, obtaining a second stress simulation result, the second stress simulation result is used to characterize whether at least part of the stress simulation model has abnormal stress changes; determining a final stress simulation result based on the first stress simulation result and the second stress simulation result, the final stress simulation result is used to characterize whether the super-large cable bridge has stress anomalies.

[0091] In some embodiments, since the simulation data corresponds to the operation monitoring data, when performing stress simulation, the simulation operation data corresponding to the stress simulation model is changed, and the stress situation is analyzed.

[0092] For example, when the stress simulation model is initially constructed, there is no corresponding operating data. According to the actual operating data, the corresponding operating data is applied to the stress simulation model, and the situation of the stress simulation model will change accordingly.

[0093] In some embodiments, abnormal stress simulation data may be pre-configured. After stress simulation, if stress simulation data that meets the pre-configured requirements is detected, the simulation software will give a prompt to determine whether the stress simulation model has abnormal stress conditions.

[0094] In some embodiments, the stress change condition can be understood as the stress conditions corresponding to multiple time points. Similarly, abnormal stress simulation change data can be pre-configured. After performing stress simulation on multiple operating data in sequence, if stress simulation change data that meets the pre-configured requirements is detected, the simulation software will prompt, thereby determining whether the stress simulation model has abnormal stress change conditions.

[0095] In some embodiments, real-time stress conditions may be used to simulate stress changes.

[0096] As an optional implementation, stress simulation is performed according to the first stress simulation result and the second simulation data corresponding to the plurality of stress simulation models to obtain a second stress simulation result, including: determining, according to the stress simulation result, a first stress simulation model with an abnormal real-time stress situation and a second stress simulation model without an abnormal real-time stress situation; determining, from the first stress simulation model, a third stress simulation model corresponding to the specified non-standard erection data; performing stress simulation on the second stress simulation model according to the second simulation data corresponding to the second stress simulation model to obtain a stress simulation result of the second stress simulation model; performing stress simulation on the third stress simulation model according to the second simulation data corresponding to the third stress simulation model to obtain a stress simulation result of the third stress simulation model; and determining the second stress simulation result according to the stress simulation result of the second stress simulation model and the stress simulation result of the third stress simulation model.

[0097] In this embodiment, according to the stress simulation result, a first stress simulation model in which an abnormal real-time stress situation exists and a second stress simulation model in which an abnormal real-time stress situation does not exist are first divided.

[0098] Then, a third stress simulation model corresponding to the specified irregular erection data is determined from the first stress simulation model. The specified irregular erection data may be data that has a high impact on the operational safety of the super-large cable bridge and may be specified by an engineer.

[0099] Then, the second stress simulation model and the third stress simulation model are simulated respectively to obtain respective stress simulation results.

[0100] Finally, the stress simulation results of the second stress simulation model and the stress simulation results of the third stress simulation model are integrated to obtain the final second stress simulation results.

[0101] In some embodiments, the stress simulation result of the second stress simulation model and the stress simulation result of the third stress simulation model may be directly integrated as the final second stress simulation result.

[0102] Figure 3 is a schematic diagram of a stress simulation process according to an exemplary embodiment. Figure 3 As shown, first use the real-time operation monitoring data to perform stress simulation on all stress simulation models to obtain the corresponding stress simulation results. Then, two types of stress simulation models are divided, those with abnormalities and those without abnormalities. Next, for the two types of stress simulation models, for the stress simulation models without abnormalities, all stress simulations are performed based on the changing operation monitoring data, and for the stress simulation models with abnormalities, only the specified models are used to perform stress simulation based on the changing operation monitoring data. Finally, the stress simulation results obtained separately are aggregated to obtain the final stress simulation results that characterize whether the stress change is abnormal.

[0103] In some embodiments, the first stress simulation result is used to characterize whether each stress simulation model has abnormal real-time stress conditions, and the second stress simulation result is used to characterize whether at least part of the stress simulation models has abnormal stress change conditions.

[0104] Therefore, when the first stress simulation result and the second stress simulation result are integrated, the final stress simulation result can be determined according to the proportion of models with abnormal real-time stress conditions and the proportion of models with abnormal stress change conditions.

[0105] In some embodiments, the proportions of two models that characterize the presence of stress anomalies in super-large cable bridges can be pre-configured. If the current proportions of the two models meet the pre-configured conditions, it is considered that there is a stress anomaly. Otherwise, it is considered that there is no stress anomaly. Generally speaking, if the proportions of the two models are high, the possibility of anomalies is high.

[0106] In some embodiments, the proportion of models with abnormal real-time stress conditions and the proportion of models with abnormal stress changes can be compared. If the difference between the proportion of models with abnormal real-time stress conditions and the proportion of models with abnormal stress changes is too large, it is considered that there is no stress abnormality. If the difference between the proportion of models with abnormal real-time stress conditions and the proportion of models with abnormal stress changes is small, it is further determined whether the two proportions are higher. If they are higher, it is considered that there is a stress abnormality.

[0107] It can be understood that in this way, it is possible to analyze whether the operation monitoring data will cause stress anomalies under different negative impact situations. If the operation monitoring data will cause stress anomalies under most negative impact situations, it means that the probability of stress anomalies is high.

[0108] After the stress simulation results are obtained, they can be applied. Figure 1In the application scenario shown, the method also includes: if the stress simulation result indicates that there is stress anomaly in the super-large cable bridge, the stress simulation result and the irregular erection data corresponding to the multiple stress simulation models are fed back to the monitoring equipment, so that the monitoring equipment determines the stress monitoring result according to the stress simulation result, the irregular erection data corresponding to the multiple stress simulation models and the operation monitoring data; receives the stress monitoring result fed back by the monitoring equipment, and the stress monitoring result is used to characterize whether there is stress anomaly in the super-large cable bridge; and optimizes the multiple stress simulation models according to the stress monitoring result and the stress simulation result.

[0109] In this embodiment, the stress simulation results and the irregular installation data corresponding to the multiple stress simulation models are fed back to the monitoring device, and the user of the monitoring device can choose whether to use the stress simulation results as a reference based on the irregular installation data corresponding to the multiple stress simulation models.

[0110] For example, if the user of the monitoring device believes that most of the non-standard installation data corresponding to multiple stress simulation models do not conform to the actual installation situation, then they can choose not to use them as a reference; if most of the installation data conform to the actual installation situation, then they can choose to use them as a reference.

[0111] Furthermore, based on the selection as a reference, the stress anomaly assessment result is obtained by using the operating monitoring data through the monitoring equipment. The assessment method of the monitoring equipment can refer to the mature technology in the field, for example: assessment through a neural network model, etc.

[0112] Then, the stress monitoring result is determined by combining the stress anomaly assessment result and the stress simulation result. For example, if both results indicate an anomaly, the stress monitoring result also indicates an anomaly. If the stress anomaly assessment result indicates normality, while the stress simulation result indicates an anomaly, the stress anomaly assessment result shall prevail. However, a reminder message needs to be added to the stress monitoring result to indicate that an anomaly may occur and that continuous monitoring is required over a period of time.

[0113] In some embodiments, the monitoring device may also perform corresponding processing based on the stress monitoring results, for example, informing maintenance personnel to conduct on-site inspections, etc.

[0114] In some embodiments, if the stress simulation result indicates that there is no stress anomaly in the super-large cable bridge, it is possible to wait for the next operation monitoring data and perform analysis again.

[0115] In some embodiments, the monitoring device may feed back stress monitoring results, and model optimization may be performed based on the fed-back stress monitoring results and stress simulation results.

[0116] In some embodiments, multiple stress simulation models are optimized based on stress monitoring results, including: if the stress monitoring results indicate that there is stress anomaly in the super-large cable bridge, some stress simulation models in the multiple stress simulation models are optimized to optimize the non-standard erection data corresponding to some stress simulation models; if the stress monitoring results indicate that there is no stress anomaly in the super-large cable bridge, the number of multiple stress simulation models is reduced and / or the frequency of stress simulation is reduced.

[0117] In some embodiments, optimizing some stress simulation models among multiple stress simulation models may be performed by changing irregular installation data of randomly sampled stress simulation models, for example, adding irregular installation data to further enhance the diversity of stress simulation models.

[0118] In some embodiments, reducing the frequency of stress simulation can be achieved by increasing the time interval between two stress simulations based on operation monitoring data. For example, before optimization, the next stress simulation is performed 1 hour later, and after optimization, the next stress simulation is performed 2 hours later.

[0119] In the embodiments of the present disclosure, regarding stress simulation analysis, reference may be made to mature technologies in the art, for example, the stress conditions at specific super-large cable bridge locations may be analyzed by simulation, and the specific super-large cable bridge locations may be both sides of the bridge, the center of the bridge, etc. Alternatively, the deformation conditions at the super-large cable bridge locations may be analyzed by simulation, which is not limited herein.

[0120] Figure 4 is a stress simulation application flow chart provided according to an exemplary embodiment. Figure 4 As shown, the simulation device and the monitoring device interact with each other to realize the monitoring of the super-large cable bridge.

[0121] exist Figure 4 In the application process shown, the simulation device first constructs multiple super-large cable bridge models (i.e., multiple stress simulation models). Different super-large cable bridge models may have different negative impact erection parameters.

[0122] Then, after the monitoring device obtains the operation monitoring data, it feeds it back to the simulation device. Based on the operation monitoring data, the simulation device performs stress simulation on multiple super-large cable bridge models to obtain corresponding stress simulation results.

[0123] Next, the simulation equipment integrates the stress simulation results of multiple super-large cable-bridge models to obtain integrated stress simulation results, and feeds them back to the monitoring equipment together with the negative impact erection parameters corresponding to the super-large cable-bridge models.

[0124] The monitoring device determines the stress monitoring result based on the information fed back by the simulation device, and performs corresponding monitoring and maintenance processing, and feeds back the stress monitoring result to the simulation device.

[0125] Furthermore, the simulation equipment optimizes multiple super-large cable-bridge models based on the stress monitoring results.

[0126] Figure 5 is a structural block diagram of a stress simulation device for a super-large cable bridge based on digital twins according to an exemplary embodiment, such as Figure 5 As shown, the device comprises:

[0127] The acquisition module 501 is configured to acquire various super-large cable bridge erection data, wherein the various super-large cable bridge erection data include irregular erection data having a negative impact on the stress of the super-large cable bridge, and the irregular erection data in different super-large cable bridge erection data are different.

[0128] The construction module 502 is configured to construct a plurality of stress simulation models according to the plurality of super-large cable bridge erection data, each stress simulation model corresponding to a type of super-large cable bridge erection data.

[0129] The acquisition module 501 is further configured to: acquire operation monitoring data of the super-large cable bridge, and determine simulation data corresponding to the multiple stress simulation models respectively according to the operation monitoring data.

[0130] The simulation module 503 is configured to perform stress simulation according to the multiple stress simulation models and the simulation data respectively corresponding to the multiple stress simulation models to obtain stress simulation results.

[0131] Regarding the device in the above embodiment, the specific manner in which each module performs operations has been described in detail in the embodiment of the method, and will not be elaborated here.

[0132] Figure 6 FIG. 6 is a block diagram of an electronic device 600 according to an exemplary embodiment. Figure 6 As shown, the electronic device 600 may include: a processor 601 , a memory 602 . The electronic device 600 may also include one or more of a multimedia component 603 , an input / output (I / O) interface 604 , and a communication component 605 .

[0133] The processor 601 is used to control the overall operation of the electronic device 600 to complete all or part of the steps in the stress simulation method of the super-large cable bridge based on digital twins. The memory 602 is used to store various types of data to support the operation of the electronic device 600, and these data may include instructions for any application or method used to operate on the electronic device 600, and application-related data, such as contact data, sent and received messages, pictures, audio, video, etc. The memory 602 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (Static Random Access Memory, referred to as SRAM), electrically erasable programmable read-only memory (Electrically Erasable Programmable Read-Only Memory, referred to as EEPROM), erasable programmable read-only memory (Erasable Programmable Read-Only Memory, referred to as EPROM), programmable read-only memory (Programmable Read-Only Memory, referred to as PROM), read-only memory (Read-Only Memory, referred to as ROM), magnetic memory, flash memory, disk or optical disk. The multimedia component 603 may include a screen and an audio component. The screen may be, for example, a touch screen, and the audio component is used to output and / or input audio signals. For example, the audio component may include a microphone, which is used to receive external audio signals. The received audio signal may be further stored in the memory 602 or sent through the communication component 605. The audio component also includes at least one speaker for outputting audio signals. The I / O interface 604 provides an interface between the processor 601 and other interface modules, and the above-mentioned other interface modules may be a keyboard, a mouse, buttons, etc. These buttons may be virtual buttons or physical buttons. The communication component 605 is used for wired or wireless communication between the electronic device 600 and other devices. Wireless communication, such as Wi-Fi, Bluetooth, Near Field Communication (NFC), 2G, 3G or 4G, or a combination of one or more of them, so the corresponding communication component 605 may include: Wi-Fi module, Bluetooth module, NFC module.

[0134] In an exemplary embodiment, the electronic device 600 can be implemented by one or more application specific integrated circuits (ASIC), digital signal processors (DSP), digital signal processing devices (DSPD), programmable logic devices (PLD), field programmable gate arrays (FPGA), controllers, microcontrollers, microprocessors or other electronic components to execute the above-mentioned stress simulation method of the ultra-large cable bridge based on digital twins.

[0135] In another exemplary embodiment, a computer-readable storage medium including program instructions is also provided, and when the program instructions are executed by a processor, the steps of the stress simulation method of a super-large cable bridge based on digital twin are implemented. For example, the computer-readable storage medium can be the memory 602 including the program instructions, and the program instructions can be executed by the processor 601 of the electronic device 600 to complete the stress simulation method of a super-large cable bridge based on digital twin.

[0136] In another exemplary embodiment, a computer program product is also provided, which includes a computer program that can be executed by a processor, and when the computer program is executed by the processor, the steps of the above-mentioned stress simulation method of a super-large cable bridge based on digital twin are implemented.

[0137] The preferred embodiments of the present disclosure are described in detail above in conjunction with the accompanying drawings; however, the present disclosure is not limited to the specific details in the above embodiments. Within the technical concept of the present disclosure, a variety of simple modifications can be made to the technical solution of the present disclosure, and these simple modifications all fall within the protection scope of the present disclosure.

[0138] It should also be noted that the various specific technical features described in the above specific embodiments can be combined in any suitable manner without contradiction. In order to avoid unnecessary repetition, the present disclosure will not further describe various possible combinations.

[0139] In addition, various embodiments of the present disclosure may be arbitrarily combined, and as long as they do not violate the concept of the present disclosure, they should also be regarded as the contents disclosed by the present disclosure.

Claims

1. A stress simulation method for a super-large cable bridge based on digital twin, characterized in that: include: Acquire various super-large cable bridge erection data, wherein the various super-large cable bridge erection data include irregular erection data that have a negative impact on the stress of the super-large cable bridge, and the irregular erection data in different super-large cable bridge erection data are different; Constructing a plurality of stress simulation models according to the plurality of super-large cable bridge erection data, each stress simulation model corresponding to a type of super-large cable bridge erection data; Acquiring operation monitoring data of the super-large cable bridge, and determining simulation data corresponding to the multiple stress simulation models respectively according to the operation monitoring data; Perform stress simulation according to the multiple stress simulation models and the simulation data respectively corresponding to the multiple stress simulation models to obtain stress simulation results; The acquisition of various super-large cable bridge erection data includes: Acquiring actual erection data of the super-large cable bridge; If the real erection data include target real erection data having a negative impact on the stress of the super-large cable bridge, the multiple super-large cable bridge erection data are generated according to the real erection data, and the non-standard erection data in the various super-large cable bridge erection data include the target real erection data and / or the associated real erection data of the target real erection data, and the associated real erection data is the real erection data having an impact on the target real erection data; If the real erection data does not include target real erection data having a negative impact on the stress of the super-large cable bridge, obtain preset simulated irregular erection data having a negative impact on the stress of the super-large cable bridge, and generate the plurality of super-large cable bridge erection data according to the simulated irregular erection data and the real erection data; The method of constructing a plurality of stress simulation models based on the plurality of super-large cable bridge erection data includes: According to the multiple super-large cable bridge erection data, multiple original stress simulation models are constructed, each original stress simulation model corresponds to a super-large cable bridge erection data; Obtaining preset simulation model test data; According to the simulation model test data, a simulation test is performed on the multiple original stress simulation models to obtain a simulation test result, wherein the simulation test result is used to characterize whether the multiple original stress simulation models are feasible; The multiple stress simulation models are constructed according to the simulation test results and the multiple original stress simulation models.

2. The stress simulation method according to claim 1, characterized in that: The constructing the multiple stress simulation models according to the simulation test results and the multiple original stress simulation models comprises: Determine the number of feasible original stress simulation models according to the simulation test results; If the number of feasible original stress simulation models is greater than or equal to a preset number, the feasible original stress simulation models are determined as the final multiple stress simulation models; If the number of feasible original stress simulation models is less than the preset number, some original stress simulation models are screened out from the unfeasible original stress simulation models, and the some original stress simulation models are adjusted to obtain adjusted stress simulation models; and the multiple stress simulation models are constructed according to the adjusted stress simulation models and the feasible original stress simulation models.

3. The stress simulation method according to claim 1, characterized in that: The operation monitoring data includes real-time operation monitoring data and historical operation monitoring data, and the step of determining the simulation data corresponding to the plurality of stress simulation models respectively according to the operation monitoring data includes: Determine, according to the real-time operation monitoring data, first simulation data corresponding to the multiple stress simulation models respectively, wherein the first simulation data is used to simulate the real-time stress situation; Determine, according to the real-time operation monitoring data and the historical operation monitoring data, second simulation data corresponding to the plurality of stress simulation models respectively, wherein the second simulation data is used to simulate stress changes; The simulation data respectively corresponding to the multiple stress simulation models are determined according to the first simulation data respectively corresponding to the multiple stress simulation models and the second simulation data respectively corresponding to the multiple stress simulation models.

4. The stress simulation method according to claim 3, characterized in that: The determining, according to the real-time operation monitoring data and the historical operation monitoring data, second simulation data corresponding to the plurality of stress simulation models respectively comprises: Determine, from the historical operation monitoring data, first operation monitoring data whose difference with the real-time operation monitoring data is greater than a preset difference; Determining second operation monitoring data adjacent to the first operation monitoring data from the historical operation monitoring data; determining target operation monitoring data according to the first operation monitoring data, the monitoring time corresponding to the first operation monitoring data, the second operation monitoring data, and the monitoring time corresponding to the second operation monitoring data; According to the target operation monitoring data, second simulation data corresponding to the multiple stress simulation models are determined.

5. The stress simulation method according to claim 1, characterized in that: The simulation data corresponding to each of the stress simulation models include first simulation data and second simulation data, the first simulation data is used to simulate the real-time stress situation, and the second simulation data is used to simulate the stress change situation, and the stress simulation is performed according to the multiple stress simulation models and the simulation data corresponding to the multiple stress simulation models to obtain the stress simulation result, including: Perform stress simulation according to the first simulation data respectively corresponding to the multiple stress simulation models to obtain a first stress simulation result, wherein the first stress simulation result is used to characterize whether each stress simulation model has an abnormal real-time stress condition; Performing stress simulation according to the first stress simulation result and second simulation data respectively corresponding to the plurality of stress simulation models to obtain a second stress simulation result, wherein the second stress simulation result is used to characterize whether at least part of the stress simulation models has abnormal stress changes; A final stress simulation result is determined according to the first stress simulation result and the second stress simulation result, and the final stress simulation result is used to characterize whether there is stress anomaly in the super-large cable bridge.

6. The stress simulation method according to claim 5, characterized in that: The performing stress simulation according to the first stress simulation result and the second simulation data respectively corresponding to the plurality of stress simulation models to obtain a second stress simulation result includes: Determine, according to the stress simulation result, a first stress simulation model in which an abnormal real-time stress condition exists and a second stress simulation model in which an abnormal real-time stress condition does not exist; Determining a third stress simulation model corresponding to the specified irregular erection data from the first stress simulation model; Performing stress simulation on the second stress simulation model according to the second simulation data corresponding to the second stress simulation model to obtain a stress simulation result of the second stress simulation model; Performing stress simulation on the third stress simulation model according to the second simulation data corresponding to the third stress simulation model to obtain a stress simulation result of the third stress simulation model; The second stress simulation result is determined according to the stress simulation result of the second stress simulation model and the stress simulation result of the third stress simulation model.

7. The stress simulation method according to claim 1, characterized in that: The stress simulation result is used to characterize whether the super-large cable bridge has stress anomaly, the operation monitoring data is data obtained from the monitoring equipment, and the stress simulation method further includes: If the stress simulation result indicates that the super-large cable bridge has stress anomaly, the stress simulation result and the irregular erection data corresponding to the multiple stress simulation models are fed back to the monitoring device, so that the monitoring device determines the stress monitoring result according to the stress simulation result, the irregular erection data corresponding to the multiple stress simulation models and the operation monitoring data; receiving a stress monitoring result fed back by the monitoring device, wherein the stress monitoring result is used to characterize whether the super-large cable bridge has stress anomaly; The multiple stress simulation models are optimized according to the stress monitoring results and the stress simulation results.

8. The stress simulation method according to claim 7, characterized in that: The optimizing the multiple stress simulation models according to the stress monitoring results includes: If the stress monitoring result indicates that the super-large cable bridge has stress anomaly, optimizing some of the multiple stress simulation models to optimize the irregular erection data corresponding to the some of the stress simulation models; If the stress monitoring result indicates that there is no stress anomaly in the super-large cable bridge, the number of the multiple stress simulation models is reduced and / or the stress simulation frequency is reduced.

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