Finite element model correction method and equipment

Abstract

According to the finite element model correction method and equipment provided by the invention, the finite element model correction method based on joint static and dynamic multi-target intelligent optimization is adopted, so that static parameters can be fully considered; and in combination with the excellent global optimization capability of multi-target intelligent optimization, the corrected finite element model can be closer to an actual structure, and subsequent simulation analysis is facilitated. According to the method, the objective function is established in the model correction process for iterative optimization, dynamic responses such as modal frequency and vibration mode and static parameters such as displacement and stress are adopted as corrected target responses, and more accurate finite element model correction is achieved; and for the generated multi-objective optimization problem, a globally optimal solution can be obtained in combination with a multi-objective optimization algorithm, and local optimum is avoided.

Description

Technical Field

[0001] The invention relates to a finite element model correction method and equipment. Background Art

[0002] At present, in the process of finite element model modification, most of the target responses for modification are the dynamic parameters of the structure. However, the model modification based on this method does not take into account the static parameters such as displacement and stress of the structure, which makes the shape of the modified finite element model inaccurate. The combination of static and dynamic forces will produce complex multi-objective optimization problems. The iterative optimization based on traditional methods will fall into the situation of local optimal solution, making the solution set incomplete. Summary of the invention

[0003] The object of the present invention is to provide a finite element model correction method and device.

[0004] In order to solve the above problems, the present invention provides a finite element model correction method, comprising:

[0005] Establish an initial finite element model of the building structure according to the architectural drawings, and predict the target response value to be corrected of the initial finite element model;

[0006] Screen out structural parameters whose correlation with the target response value to be corrected is greater than a preset threshold as parameters to be corrected;

[0007] Through dynamic tests and static tests, the acceleration and displacement data of the building structure are obtained; based on the acceleration and displacement data of the building structure, the actual static and dynamic parameters of the building structure are obtained as actual response values;

[0008] Based on the actual response value, the target response value and the value range of the parameter to be corrected, the initial finite element model is iteratively optimized to obtain the corrected finite element model.

[0009] Furthermore, in the above method, the target response values ​​to be corrected include: modal frequency, vibration shape, mid-span deflection and inclination angle of the beam.

[0010] Furthermore, in the above method, the structural parameters whose correlation with the target response value to be corrected is greater than a preset threshold are screened out as the parameters to be corrected, including:

[0011] Through sensitivity analysis, structural parameters whose correlation with the target response value to be corrected is greater than a preset threshold are screened out as parameters to be corrected.

[0012] Furthermore, in the above method, the parameters to be corrected include: material properties, geometric dimensions and cross-sectional properties.

[0013] Furthermore, in the above method, the material properties include: elastic modulus and yield strength

[0014] Furthermore, in the above method, the acceleration and displacement data of the building structure are obtained through dynamic tests and static tests; based on the acceleration and displacement data of the building structure, the actual static and dynamic parameters of the building structure are obtained as actual response values, including:

[0015] Arrange acceleration sensors and displacement sensors at key nodes of the building structure to collect acceleration and displacement data over a period of time; process the acceleration and displacement data to obtain the actual static and dynamic parameters of the building structure as actual response values; the actual static and dynamic parameters of the building structure include: the actual deflection and modal frequency of the building structure.

[0016] Furthermore, in the above method, the acceleration and displacement data of the building structure are obtained through dynamic tests and static tests; based on the acceleration and displacement data of the building structure, the actual static and dynamic parameters of the building structure are obtained as actual response values, including:

[0017] Collect static data of displacement and stress over a period of time, and select static data of displacement and stress;

[0018] Using environmental excitation as the excitation for the building structure, collecting acceleration data within a period of time, filtering and Fourier transforming the acceleration data, and obtaining the actual modal frequency and vibration type dynamic data of the building structure;

[0019] The static and dynamic data are processed to obtain the actual static and dynamic parameters at the key nodes of the building structure as the actual response values.

[0020] Furthermore, in the above method, based on the actual response value, the target response value and the value range of the parameter to be corrected, the initial finite element model is iteratively optimized to obtain a corrected finite element model, including:

[0021] The static and dynamic parameters are combined to establish an optimization objective function for model correction: the difference between the actual response value obtained through static and dynamic tests and the target response value is minimized as the objective function, the value range of the parameter to be corrected is used as the constraint condition, and the initial finite element model is iteratively optimized by combining a multi-objective intelligent optimization algorithm of a multi-objective genetic algorithm and a multi-objective particle swarm algorithm to obtain the corrected structural parameters, so as to obtain the corrected finite element model; by comparing the difference between the target response value and the actual response value of the corrected finite element model, it is judged whether the corrected finite element model meets the accuracy requirement.

[0022] According to another aspect of the present invention, there is further provided a computer-readable storage medium having computer-executable instructions stored thereon, wherein when the computer-executable instructions are executed by a processor, the processor is caused to: adopt any of the methods described above.

[0023] According to another aspect of the present invention, there is also provided a computer device, comprising:

[0024] Processor; and

[0025] A memory arranged to store computer executable instructions which, when executed, cause the processor to: adopt any of the methods described above.

[0026] In summary, the current finite element model correction method mainly uses dynamic responses such as modal parameters as the target correction response, and does not consider static parameters such as displacement and stress. The error between the model correction completed on this basis and the actual structure is large. The present invention adopts a finite element model correction method based on joint static and dynamic multi-objective intelligent optimization to fully consider the above static parameters, and combines the excellent global optimization ability of multi-objective intelligent optimization to make the corrected finite element model closer to the actual structure, which is helpful for subsequent simulation analysis. The present invention establishes a process of iterative optimization of the objective function in the model correction, and simultaneously uses dynamic responses such as modal frequency and vibration shape and static parameters such as displacement and stress as the target response for correction, so as to achieve more accurate finite element model correction; for the generated multi-objective optimization problem, the global optimal solution can be obtained in combination with the multi-objective optimization algorithm to avoid falling into the local optimum.

[0027] Compared with the traditional finite element model correction method, the beneficial effects of the present invention are mainly as follows:

[0028] (1) The model correction is highly accurate. The corrected target response uses not only dynamic parameters but also static parameters such as displacement and stress. This allows the model correction to be corrected in terms of inherent properties and to be closer to the actual structure in appearance.

[0029] (2) Strong global optimization capability. The combined static and dynamic optimization will produce complex multi-objective optimization problems. Combining multi-objective optimization algorithms for iterative optimization can obtain the global optimal solution and make the structural parameters more in line with the actual situation.

[0030] The various embodiments in this specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the various embodiments can be referenced to each other. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] Figure 1 It is a flow chart of a finite element model correction method and device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0032] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the present invention is further described in detail below with reference to the accompanying drawings and specific embodiments.

[0033] like Figure 1 As shown, the present invention provides a finite element model correction method, comprising:

[0034] Step S1, establishing an initial finite element model of the building structure according to the architectural drawings, and predicting the target response value to be corrected of the initial finite element model;

[0035] Preferably, the target response value to be corrected includes: parameters such as modal frequency, vibration shape, mid-span deflection and inclination of the beam;

[0036] Step S2, screening out structural parameters whose correlation with the target response value to be corrected is greater than a preset threshold value as parameters to be corrected;

[0037] Preferably, some structural parameters whose correlation with the target response value to be corrected is greater than a preset threshold can be screened out through sensitivity analysis as parameters to be corrected. By adjusting the parameters to be corrected, the target response value of the finite element model can be effectively changed.

[0038] The selected parameters to be corrected include: material properties, geometric dimensions and cross-sectional properties, etc.; preferably, the material properties include: elastic modulus and yield strength, etc.

[0039] Here, the idea of ​​finite element model correction is to make the output parameters of the finite element model closer to the actual response values ​​of the structure by adjusting these input parameters to be corrected.

[0040] Step S3, obtaining acceleration and displacement data of the building structure through dynamic tests and static tests; based on the acceleration and displacement data of the building structure, obtaining actual static and dynamic parameters of the building structure as actual response values;

[0041] Preferably, the acceleration and displacement data of the building structure are obtained through dynamic tests and static tests, and acceleration sensors, displacement sensors and other equipment are arranged at key nodes of the building structure to collect acceleration and displacement data over a period of time; the acceleration and displacement data are processed to obtain the actual static and dynamic parameters of the building structure as actual response values.

[0042] Preferably, the actual static and dynamic parameters of the building structure include: the actual deflection and modal frequency of the building structure.

[0043] More preferably, step S3 comprises:

[0044] Step S31, collecting static data of displacement and stress within a period of time for static parameters, and selecting static data of displacement and stress;

[0045] Step S32, with respect to the dynamic parameters, using environmental excitation as the excitation for the building structure, collecting acceleration data within a period of time, filtering and Fourier transforming the acceleration data, and obtaining the dynamic data of the actual modal frequency and vibration shape of the building structure;

[0046] Step S33, processing the static data and the dynamic data to obtain actual static and dynamic parameters at key nodes of the building structure as actual response values.

[0047] Step S4, iteratively optimizing the initial finite element model based on the actual response value, the target response value and the value range of the parameter to be corrected, so as to obtain a corrected finite element model.

[0048] Preferably, the static and dynamic parameters are combined to establish an optimization objective function for model correction: the difference between the actual response value obtained through static and dynamic tests and the target response value is minimized as the objective function, the value range of the parameter to be corrected is used as the constraint condition, and the multi-objective intelligent optimization algorithm of the multi-objective genetic algorithm and the multi-objective particle swarm algorithm is combined to iteratively optimize the initial finite element model to obtain the corrected structural parameters, so as to obtain the corrected finite element model; by comparing the difference between the target response value and the actual response value of the corrected finite element model, it is judged whether the corrected finite element model meets the accuracy requirement.

[0049] According to another aspect of the present invention, there is further provided a computer-readable storage medium having computer-executable instructions stored thereon, wherein when the computer-executable instructions are executed by a processor, the processor is caused to: adopt any of the methods described above.

[0050] According to another aspect of the present invention, there is also provided a computer device, comprising:

[0051] Processor; and

[0052] A memory arranged to store computer executable instructions which, when executed, cause the processor to: adopt any of the methods described above.

[0053] In summary, the current finite element model correction method mainly uses dynamic responses such as modal parameters as the target correction response, and does not consider static parameters such as displacement and stress. The error between the model correction completed on this basis and the actual structure is large. The present invention adopts a finite element model correction method based on joint static and dynamic multi-objective intelligent optimization to fully consider the above static parameters, and combines the excellent global optimization ability of multi-objective intelligent optimization to make the corrected finite element model closer to the actual structure, which is helpful for subsequent simulation analysis. The present invention establishes a process of iterative optimization of the objective function in the model correction, and simultaneously uses dynamic responses such as modal frequency and vibration shape and static parameters such as displacement and stress as the target response for correction, so as to achieve more accurate finite element model correction; for the generated multi-objective optimization problem, the global optimal solution can be obtained in combination with the multi-objective optimization algorithm to avoid falling into the local optimum.

[0054] Compared with the traditional finite element model correction method, the beneficial effects of the present invention are mainly as follows:

[0055] (1) The model correction is highly accurate. The corrected target response uses not only dynamic parameters but also static parameters such as displacement and stress. This allows the model correction to be corrected in terms of inherent properties and to be closer to the actual structure in appearance.

[0056] (2) Strong global optimization capability. The combined static and dynamic optimization will produce complex multi-objective optimization problems. Combining multi-objective optimization algorithms for iterative optimization can obtain the global optimal solution and make the structural parameters more in line with the actual situation.

[0057] The various embodiments in this specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the various embodiments can be referenced to each other.

[0058] Professionals may further appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of the two. In order to clearly illustrate the interchangeability of hardware and software, the composition and steps of each example have been generally described in the above description according to function. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professionals and technicians may use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0059] Obviously, those skilled in the art can make various changes and modifications to the invention without departing from the spirit and scope of the invention. Thus, if these modifications and variations of the invention fall within the scope of the claims of the invention and their equivalents, the invention is also intended to include these modifications and variations.

Claims

1. A finite element model updating method, characterized in that: include: Establish an initial finite element model of the building structure according to the architectural drawings, and predict the target response value to be corrected of the initial finite element model; Screen out structural parameters whose correlation with the target response value to be corrected is greater than a preset threshold as parameters to be corrected; Obtain acceleration and displacement data of building structures through dynamic and static tests; Based on the acceleration and displacement data of the building structure, the actual static and dynamic parameters of the building structure are obtained as actual response values; Based on the actual response value, the target response value and the value range of the parameter to be corrected, the initial finite element model is iteratively optimized to obtain the corrected finite element model.

2. The finite element model correction method according to claim 1, characterized in that: The target response values ​​to be corrected include: modal frequency, vibration shape, mid-span deflection and inclination of the beam.

3. The finite element model correction method according to claim 1, characterized in that: Structural parameters whose correlation with the target response value to be corrected is greater than a preset threshold are selected as parameters to be corrected, including: Through sensitivity analysis, structural parameters whose correlation with the target response value to be corrected is greater than a preset threshold are screened out as parameters to be corrected.

4. The finite element model correction method according to claim 1, characterized in that: The parameters to be corrected include: material properties, geometric dimensions and cross-sectional properties.

5. The finite element model updating method according to claim 4, characterized in that: The material properties include elastic modulus and yield strength.

6. The finite element model updating method according to claim 1, characterized in that: Obtain acceleration and displacement data of building structures through dynamic and static tests; Based on the acceleration and displacement data of the building structure, the actual static and dynamic parameters of the building structure are obtained as actual response values, including: Arrange acceleration sensors and displacement sensors at key nodes of the building structure to collect acceleration and displacement data over a period of time; process the acceleration and displacement data to obtain the actual static and dynamic parameters of the building structure as actual response values; the actual static and dynamic parameters of the building structure include: the actual deflection and modal frequency of the building structure.

7. The finite element model updating method according to claim 1, characterized in that: Obtain acceleration and displacement data of building structures through dynamic and static tests; Based on the acceleration and displacement data of the building structure, the actual static and dynamic parameters of the building structure are obtained as actual response values, including: Collect static data of displacement and stress over a period of time, and select static data of displacement and stress; Using environmental excitation as the excitation for the building structure, collecting acceleration data within a period of time, filtering and Fourier transforming the acceleration data, and obtaining the actual modal frequency and vibration type dynamic data of the building structure; The static and dynamic data are processed to obtain the actual static and dynamic parameters at the key nodes of the building structure as the actual response values.

8. The finite element model updating method according to claim 1, characterized in that: Based on the actual response value, the target response value and the value range of the parameter to be corrected, the initial finite element model is iteratively optimized to obtain a corrected finite element model, including: The static and dynamic parameters are combined to establish an optimization objective function for model correction: the difference between the actual response value obtained through static and dynamic tests and the target response value is minimized as the objective function, the value range of the parameter to be corrected is used as the constraint condition, and the initial finite element model is iteratively optimized by combining a multi-objective intelligent optimization algorithm of a multi-objective genetic algorithm and a multi-objective particle swarm algorithm to obtain the corrected structural parameters, so as to obtain the corrected finite element model; by comparing the difference between the target response value and the actual response value of the corrected finite element model, it is judged whether the corrected finite element model meets the accuracy requirement.

9. A computer-readable storage medium having computer-executable instructions stored thereon, wherein: When the computer executable instructions are executed by a processor, the processor is caused to: adopt the method according to any one of claims 1 to 8.

10. A computer device, wherein: include: processor; as well as A memory arranged to store computer executable instructions which, when executed, cause the processor to: employ a method as claimed in any one of claims 1 to 8.

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