CN116258032A - Fatigue life prediction method, device, electronic equipment and storage medium - Google Patents

Fatigue life prediction method, device, electronic equipment and storage medium Download PDF

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CN116258032A
CN116258032A CN202211104718.6A CN202211104718A CN116258032A CN 116258032 A CN116258032 A CN 116258032A CN 202211104718 A CN202211104718 A CN 202211104718A CN 116258032 A CN116258032 A CN 116258032A
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curve
result
fatigue
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周俊丞
祁超
刘卫国
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Chongqing Changan New Energy Automobile Technology Co Ltd
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Chongqing Changan New Energy Automobile Technology Co Ltd
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Abstract

The application relates to a fatigue life prediction method, a device, electronic equipment and a storage medium, wherein the method comprises the following steps: determining a weld heat affected zone of the material to be analyzed, and calculating a modal stress result and a transfer function result of the material to be analyzed based on the weld heat affected zone; obtaining a frequency response result of the material to be analyzed according to the modal stress result, the transfer function result and the preset random vibration psd spectrum; and fitting the fatigue strength according to the tensile strength of the material to be analyzed based on the frequency response result, obtaining a welding seam region material S-N curve of the material to be analyzed, and obtaining a fatigue damage result of the material to be analyzed in a welding seam heat affected zone according to the welding seam region material S-N curve and a preset survival rate, so as to predict the fatigue life of the material to be analyzed according to the fatigue damage result. Therefore, the problems that the calculated damage value of the related technology is larger, the cost is increased and the performance is reduced due to over design are solved, the fatigue life of the welding seam can be predicted relatively accurately, and the test cost is saved.

Description

Fatigue life prediction method, device, electronic equipment and storage medium
Technical Field
The present disclosure relates to the field of CAE (Computer Aided Engineering, computer aided engineering in engineering design) simulation technologies, and in particular, to a fatigue life prediction method, a device, an electronic apparatus, and a storage medium.
Background
With the popularization of new energy automobiles, the problem of structural durability of electric automobiles is becoming a focus of attention. Among other things, in structural members such as battery packs or electric drive systems, welds are often high risk points therein. Because of the very many factors that affect the accuracy of the life simulation of the weld, such as the yield strength, tensile strength, S-N curve, surface roughness, weld heat affected zone range, modal accuracy, modeling of the weld in finite elements, etc., these factors lead to life prediction of the weld as an industry commonality problem.
The calculation methods of the fatigue life prediction modes in the related technologies are all conservative, and the calculated damage values are all large, so that the product is designed for meeting the design requirement, the cost is increased, and the performance is greatly reduced.
Disclosure of Invention
The application provides a fatigue life prediction method, a device, electronic equipment and a storage medium, which are used for solving the problems that the calculated damage value of the related technology is large, the cost is increased, the performance is greatly reduced due to over design, the fatigue life of a welding line can be predicted relatively accurately, and the test cost is saved.
An embodiment of a first aspect of the present application provides a fatigue life prediction method, including the steps of: determining a weld heat affected zone of a material to be analyzed, and calculating a modal stress result and a transfer function result of the material to be analyzed based on the weld heat affected zone; obtaining a frequency response result of the material to be analyzed according to the modal stress result, the transfer function result and a preset random vibration psd (Power Spectral Density ) spectrum; and fitting fatigue strength according to the tensile strength of the material to be analyzed based on the frequency response result to obtain a welding seam region material S-N (stress-life) curve of the material to be analyzed, and obtaining a fatigue damage result of the material to be analyzed in the welding seam heat affected zone according to the welding seam region material S-N curve and a preset survival rate to predict the fatigue life of the material to be analyzed according to the fatigue damage result.
According to the technical means, the problems that the calculated damage value of the related technology is large, the cost is increased and the performance is reduced due to over design can be solved, the fatigue life of the welding seam can be predicted relatively accurately, and the test cost is saved.
Optionally, in some embodiments, the fitting fatigue strength according to the tensile strength of the material to be analyzed to obtain a weld region material S-N curve of the material to be analyzed includes: fitting fatigue strength according to the tensile strength of the material to be analyzed to obtain an initial weld joint region material S-N curve; and if the intercept of the initial weld joint area material S-N curve on the vertical axis is larger than the tensile strength, taking the initial weld joint area material S-N curve as the weld joint area material S-N curve of the material to be analyzed, otherwise, obtaining the weld joint area material S-N curve of the material to be analyzed according to the tensile strength and the fatigue front.
According to the technical means, the S-N curve of the material can be directly fitted through the tensile strength of the material, so that the test cost is saved.
Optionally, in some embodiments, after obtaining the weld zone material S-N curve of the material to be analyzed, further comprising: and correcting the welding line area material S-N curve of the material to be analyzed based on a preset correction strategy.
According to the technical means, the fatigue life of the welding seam can be predicted more accurately.
Optionally, in some embodiments, the determining a weld heat affected zone of the material to be analyzed includes: modeling a weld joint of the material to be analyzed based on a preset structural grid model; and (3) moving all grids at the joint of the welding lines to a target group to obtain a welding line heat affected zone of the material to be analyzed.
According to the technical means, the method can be used for defining the weld heat affected zone by modeling and moving the grid at the joint of the weld to the target group.
Optionally, in some embodiments, the preset survival rate is 90%.
According to the technical means, the survival rate can be set, and the fatigue loss value of the weld heat affected zone can be calculated.
Embodiments of a second aspect of the present application provide a fatigue life prediction apparatus, comprising: the calculation module is used for determining a weld heat affected zone of the material to be analyzed and calculating a modal stress result and a transfer function result of the material to be analyzed based on the weld heat affected zone; the acquisition module is used for acquiring a frequency response result of the material to be analyzed according to the modal stress result, the transfer function result and a preset random vibration psd spectrum; and the analysis module is used for fitting the fatigue strength according to the tensile strength of the material to be analyzed based on the frequency response result, obtaining a welding seam region material S-N curve of the material to be analyzed, and obtaining a fatigue damage result of the material to be analyzed in the welding seam heat affected zone according to the welding seam region material S-N curve and a preset survival rate so as to predict the fatigue life of the material to be analyzed according to the fatigue damage result.
Optionally, in some embodiments, the analysis module is further configured to: fitting fatigue strength according to the tensile strength of the material to be analyzed to obtain an initial weld joint region material S-N curve; and if the intercept of the initial weld joint area material S-N curve on the vertical axis is larger than the tensile strength, taking the initial weld joint area material S-N curve as the weld joint area material S-N curve of the material to be analyzed, otherwise, obtaining the weld joint area material S-N curve of the material to be analyzed according to the tensile strength and the fatigue front.
Optionally, in some embodiments, after obtaining the weld zone material S-N curve of the material to be analyzed, the analysis module is further configured to: and correcting the welding line area material S-N curve of the material to be analyzed based on a preset correction strategy.
Optionally, in some embodiments, the computing module is further configured to: modeling a weld joint of the material to be analyzed based on a preset structural grid model; and (3) moving all grids at the joint of the welding lines to a target group to obtain a welding line heat affected zone of the material to be analyzed.
Optionally, in some embodiments, the preset survival rate is 90%.
An embodiment of a third aspect of the present application provides an electronic device, including: a memory, a processor, and a computer program stored on the memory and executable on the processor, the processor executing the program to implement the fatigue life prediction method as described in the above embodiments.
An embodiment of a fourth aspect of the present application provides a computer-readable storage medium having stored thereon a computer program for execution by a processor for implementing the fatigue life prediction method as described in the above embodiment.
The method comprises the steps of determining a weld joint heat affected zone of a material to be analyzed, calculating a modal stress result and a transfer function result of the material to be analyzed based on the weld joint heat affected zone, obtaining a frequency response result of the material to be analyzed according to the modal stress result, the transfer function result and a preset random vibration psd spectrum, fitting fatigue strength according to tensile strength of the material to be analyzed based on the frequency response result, obtaining a weld joint region material S-N curve of the material to be analyzed, and obtaining a fatigue damage result of the material to be analyzed in the weld joint heat affected zone according to the weld joint region material S-N curve and a preset survival rate, so as to predict fatigue life of the material to be analyzed according to the fatigue damage result. Therefore, the problems that the calculated damage value of the related technology is larger, the cost is increased and the performance is reduced due to over design are solved, the fatigue life of the welding seam can be predicted relatively accurately, and the test cost is saved.
Additional aspects and advantages of the application will be set forth in part in the description which follows and, in part, will be obvious from the description, or may be learned by practice of the application.
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The foregoing and/or additional aspects and advantages of the present application will become apparent and readily appreciated from the following description of the embodiments, taken in conjunction with the accompanying drawings, in which:
FIG. 1 is a flow chart of a fatigue life prediction method provided according to an embodiment of the present application;
FIG. 2 is a tensile schematic diagram of weld performance provided in accordance with one embodiment of the present application;
FIG. 3 is a schematic S-N plot of a material provided in accordance with one embodiment of the present application;
FIG. 4 is a schematic diagram of a fatigue life prediction apparatus provided according to an embodiment of the present application;
fig. 5 is a schematic diagram of an electronic device according to an embodiment of the present application.
Reference numerals illustrate: 10-fatigue life prediction device, 100-calculation module, 200-acquisition module and 300-analysis module.
Detailed Description
Embodiments of the present application are described in detail below, examples of which are illustrated in the accompanying drawings, wherein the same or similar reference numerals refer to the same or similar elements or elements having the same or similar functions throughout. The embodiments described below by referring to the drawings are exemplary and intended for the purpose of explaining the present application and are not to be construed as limiting the present application.
The fatigue life prediction method, the device, the electronic equipment and the storage medium according to the embodiment of the application are described below with reference to the accompanying drawings. Aiming at the problems that the calculated damage value of the related technology mentioned in the background art is larger, the cost is increased and the performance is reduced due to over design, the application provides a fatigue life prediction method, in the method, a mode stress result and a transfer function result of a material to be analyzed are calculated based on a weld heat affected zone through determining the weld heat affected zone of the material to be analyzed, a frequency response result of the material to be analyzed is obtained according to the mode stress result, the transfer function result and a preset random vibration psd spectrum, a fatigue strength is fitted according to the tensile strength of the material to be analyzed based on the frequency response result, a weld area material S-N curve of the material to be analyzed is obtained, and a fatigue damage result of the material to be analyzed in the weld heat affected zone is obtained according to the weld area material S-N curve and a preset survival rate, so that the fatigue life of the material to be analyzed is predicted according to the fatigue damage result. Therefore, the problems that the calculated damage value of the related technology is larger, the cost is increased and the performance is reduced due to over design are solved, the fatigue life of the welding seam can be predicted relatively accurately, and the test cost is saved.
Specifically, fig. 1 is a schematic flow chart of a fatigue life prediction method according to an embodiment of the present application.
As shown in fig. 1, the fatigue life prediction method includes the steps of:
in step S101, a weld heat affected zone of the material to be analyzed is determined, and a modal stress result and a transfer function result of the material to be analyzed are calculated based on the weld heat affected zone.
Optionally, in some embodiments, determining the weld heat affected zone of the material to be analyzed includes: modeling a weld joint of a material to be analyzed based on a preset structural grid model; and (3) moving all grids at the joint of the welding lines to the target group to obtain a welding line heat affected zone of the material to be analyzed.
As can be appreciated by those skilled in the art, due to such welding positions of the welding seam, the welding seam body is often not broken in the structural stress process, but the peripheral heat affected zone is broken, and the embodiment of the application can specifically define the heat image zone of the welding seam in modeling, and then the fatigue analysis is performed on the heat affected zone. The method can be used for modeling the welding line of the material to be analyzed based on a preset structural network model, after the structural grid model is established and a welding line heat affected zone is defined, firstly, nastran is used for calculating modal stress and transfer function of the welding line, then the result and random vibration psd spectrum are led into Femfat, and the modal stress result and transfer function result of the material to be analyzed are calculated.
Specifically, the embodiment of the application can firstly obtain the material performance of the weld affected zone, the performances such as the elastic modulus, the poisson ratio and the like are kept consistent with the base material, and the yield strength and the tensile strength are obtained through a tensile test. First, a sample piece is manufactured in the mode of fig. 2, and then a tensile test is carried out until the sample piece breaks, so that the yield strength and the tensile strength of the material are obtained, namely the yield strength and the tensile strength of the material in a weld heat affected zone. And modeling the welding seam in a grid model of the structure, wherein the lap angle of the welding seam is 90 degrees, the grid size of the welding seam is consistent with the grid size of the structural member, and the thickness of the welding seam is 2 times of the minimum connecting plate thickness. Next, the mesh in contact with the weld is moved entirely into a group, which is defined as the heat affected zone of the weld.
In step S102, a frequency response result of the material to be analyzed is obtained according to the modal stress result, the transfer function result and the preset random vibration psd spectrum.
Specifically, in the embodiment of the application, the frequency range, the modal stress and the transfer function required by the working condition can be set through Nastran, the modal stress result op2 and the transfer function result pch of the structure can be obtained through calculation, the grid of the heat affected zone of the welding seam, the modal stress op2, the transfer function pch and the random vibration working condition psd are imported into software femfat, and the frequency response result of the structure in the set frequency range is calculated.
In step S103, based on the frequency response result, fitting the fatigue strength according to the tensile strength of the material to be analyzed to obtain a weld joint region material S-N curve of the material to be analyzed, and obtaining a fatigue damage result of the material to be analyzed in the weld joint heat affected zone according to the weld joint region material S-N curve and a preset survival rate, so as to predict the fatigue life of the material to be analyzed according to the fatigue damage result.
Optionally, in some embodiments, fitting the fatigue strength to the tensile strength of the material to be analyzed to obtain a weld zone material S-N curve of the material to be analyzed includes: fitting fatigue strength according to the tensile strength of the material to be analyzed to obtain an initial weld joint region material S-N curve; and if the intercept of the initial welding seam area material S-N curve on the longitudinal axis is larger than the tensile strength, taking the initial welding seam area material S-N curve as the welding seam area material S-N curve of the material to be analyzed, otherwise, obtaining the welding seam area material S-N curve of the material to be analyzed according to the tensile strength and the fatigue strength.
Optionally, in some embodiments, after obtaining the weld zone material S-N curve of the material to be analyzed, further comprising: and correcting the welding line area material S-N curve of the material to be analyzed based on a preset correction strategy.
Optionally, in some embodiments, the preset survival rate is 90%.
In general, the S-N curve of a material needs to be input analytically before the fatigue life of the material is predicted. The S-N curve of the material, i.e. the material is subjected to cyclic tests at different stress levels, the number of cycles at which failure occurs at each stress is recorded.
Because the S-N curves of all materials are different, the application establishes a fitting method through the tensile strength of the materials based on the German FKM standard, namely fitting the fatigue strength according to the tensile strength, calculating the intercept of the S-N curve on the vertical axis according to the slope, and finally determining the S-N curve of the materials according to the comparison of the intercept and the tensile strength. As shown in fig. 3:
the point A is the intercept of the S-N curve on the vertical axis, if the stress value exceeds the tensile strength, the point A is selected as the point corresponding to the tensile strength, and if the stress value is smaller than the tensile strength, the point is unchanged; the stress value at the point B is the fatigue strength of the material, and the corresponding cycle number is Npl.
(1) For aluminum alloys, based on the tensile strength σal of the material, the fatigue strength σalpl=0.3×σal is estimated, npl =1e7; under the logarithmic scale, the AB point slope is bal= -1/11, so that an aluminum alloy S-N curve can be obtained;
(2) For steel, based on the tensile strength σsl of the material, the fatigue strength σslpl=0.45×σsl is estimated, npl =2e6; under the logarithmic scale, the slope of the AB point is bsl= -1/12, so that a steel S-N curve can be obtained;
the S-N curve of the material was simulated by its tensile strength for fatigue life calculation based on the German FKM standard method described above.
Specifically, basic parameters of the material, such as elastic modulus, yield strength, tensile strength, poisson ratio and the like, are input into software, an S-N curve of the material is simulated based on the tensile strength, and the S-N curve is corrected through a module of the software. Finally, setting the survival rate, preferably 90%, activating Gaussian distribution, and calculating the fatigue loss value of the heat affected zone of the welding seam.
Therefore, the S-N curve of the welding line area material is fitted through the German FKM standard through the tensile strength of the material, the S-N curve is corrected through software, the survival rate is set finally, the fatigue damage result of the welding line heat affected zone is obtained through calculation, the fatigue life of the welding line can be predicted relatively accurately, the S-N curve of the material is directly fitted through the tensile strength of the material, and the test cost is saved.
According to the fatigue life prediction method provided by the embodiment of the application, the modal stress result and the transfer function result of the material to be analyzed are calculated based on the weld heat affected zone by determining the weld heat affected zone of the material to be analyzed, the frequency response result of the material to be analyzed is obtained according to the modal stress result, the transfer function result and the preset random vibration psd spectrum, the fatigue strength is fitted according to the tensile strength of the material to be analyzed based on the frequency response result, the S-N curve of the weld area material of the material to be analyzed is obtained, and the fatigue damage result of the material to be analyzed in the weld heat affected zone is obtained according to the S-N curve of the weld area material and the preset survival rate, so that the fatigue life of the material to be analyzed is predicted according to the fatigue damage result. Therefore, the problems that the calculated damage value of the related technology is larger, the cost is increased and the performance is reduced due to over design are solved, the fatigue life of the welding seam can be predicted relatively accurately, and the test cost is saved.
Next, a fatigue life predicting device according to an embodiment of the present application will be described with reference to the accompanying drawings.
Fig. 4 is a block schematic diagram of a fatigue life prediction device according to an embodiment of the present application.
As shown in fig. 4, the fatigue life prediction apparatus 10 includes: a calculation module 100, an acquisition module 200 and an analysis module 300.
The calculation module 100 is configured to determine a weld heat affected zone of the material to be analyzed, and calculate a modal stress result and a transfer function result of the material to be analyzed based on the weld heat affected zone; the obtaining module 200 is configured to obtain a frequency response result of the material to be analyzed according to the modal stress result, the transfer function result and a preset random vibration psd spectrum; and the analysis module 300 is used for fitting the fatigue strength according to the tensile strength of the material to be analyzed based on the frequency response result, obtaining a welding line area material S-N curve of the material to be analyzed, and obtaining a fatigue damage result of the material to be analyzed in a welding line heat affected zone according to the welding line area material S-N curve and the preset survival rate, so as to predict the fatigue life of the material to be analyzed according to the fatigue damage result.
Optionally, in some embodiments, the analysis module 300 is further configured to: fitting fatigue strength according to the tensile strength of the material to be analyzed to obtain an initial weld joint region material S-N curve; and if the intercept of the initial welding seam area material S-N curve on the longitudinal axis is larger than the tensile strength, taking the initial welding seam area material S-N curve as the welding seam area material S-N curve of the material to be analyzed, otherwise, obtaining the welding seam area material S-N curve of the material to be analyzed according to the tensile strength and the fatigue strength.
Optionally, in some embodiments, after obtaining the weld zone material S-N curve of the material to be analyzed, the analysis module is further configured to: and correcting the welding line area material S-N curve of the material to be analyzed based on a preset correction strategy.
Optionally, in some embodiments, the computing module 100 is further configured to: modeling a weld joint of a material to be analyzed based on a preset structural grid model; and (3) moving all grids at the joint of the welding lines to the target group to obtain a welding line heat affected zone of the material to be analyzed.
Optionally, in some embodiments, the preset survival rate is 90%.
It should be noted that the foregoing explanation of the embodiment of the fatigue life prediction method is also applicable to the fatigue life prediction method of this embodiment, and will not be repeated here.
According to the fatigue life prediction method provided by the embodiment of the application, the modal stress result and the transfer function result of the material to be analyzed are calculated based on the weld heat affected zone by determining the weld heat affected zone of the material to be analyzed, the frequency response result of the material to be analyzed is obtained according to the modal stress result, the transfer function result and the preset random vibration psd spectrum, the fatigue strength is fitted according to the tensile strength of the material to be analyzed based on the frequency response result, the S-N curve of the weld area material of the material to be analyzed is obtained, and the fatigue damage result of the material to be analyzed in the weld heat affected zone is obtained according to the S-N curve of the weld area material and the preset survival rate, so that the fatigue life of the material to be analyzed is predicted according to the fatigue damage result. Therefore, the problems that the calculated damage value of the related technology is larger, the cost is increased and the performance is reduced due to over design are solved, the fatigue life of the welding seam can be predicted relatively accurately, and the test cost is saved.
Fig. 5 is a schematic structural diagram of an electronic device according to an embodiment of the present application. The electronic device may include:
memory 501, processor 502, and a computer program stored on memory 501 and executable on processor 502.
The fatigue life prediction method provided in the above embodiment is implemented when the processor 502 executes a program.
Further, the electronic device further includes:
a communication interface 503 for communication between the memory 501 and the processor 502.
Memory 501 for storing a computer program executable on processor 502.
The memory 501 may include high speed RAM (Random Access Memory ) memory, and may also include non-volatile memory, such as at least one disk memory.
If the memory 501, the processor 502, and the communication interface 503 are implemented independently, the communication interface 503, the memory 501, and the processor 502 may be connected to each other via a bus and perform communication with each other. The bus may be an ISA (Industry Standard Architecture ) bus, a PCI (Peripheral Component, external device interconnect) bus, or EISA (Extended Industry Standard Architecture ) bus, among others. The buses may be divided into address buses, data buses, control buses, etc. For ease of illustration, only one thick line is shown in fig. 5, but not only one bus or one type of bus.
Alternatively, in a specific implementation, if the memory 501, the processor 502, and the communication interface 503 are integrated on a chip, the memory 501, the processor 502, and the communication interface 503 may perform communication with each other through internal interfaces.
The processor 502 may be a CPU (Central Processing Unit ) or ASIC (Application Specific Integrated Circuit, application specific integrated circuit) or one or more integrated circuits configured to implement embodiments of the present application.
The embodiments of the present application also provide a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, implements the fatigue life prediction method as above.
In the description of the present specification, a description referring to terms "one embodiment," "some embodiments," "examples," "specific examples," or "some examples," etc., means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the present application. In this specification, schematic representations of the above terms are not necessarily directed to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or N embodiments or examples. Furthermore, the different embodiments or examples described in this specification and the features of the different embodiments or examples may be combined and combined by those skilled in the art without contradiction.
Furthermore, the terms "first," "second," and the like, are used for descriptive purposes only and are not to be construed as indicating or implying a relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defining "a first" or "a second" may explicitly or implicitly include at least one such feature. In the description of the present application, the meaning of "N" is at least two, such as two, three, etc., unless explicitly defined otherwise.
Any process or method descriptions in flow charts or otherwise described herein may be understood as representing modules, segments, or portions of code which include one or more N executable instructions for implementing specific logical functions or steps of the process, and further implementations are included within the scope of the preferred embodiment of the present application in which functions may be executed out of order from that shown or discussed, including substantially concurrently or in reverse order, depending on the functionality involved, as would be understood by those reasonably skilled in the art of the embodiments of the present application.
It is to be understood that portions of the present application may be implemented in hardware, software, firmware, or a combination thereof. In the above-described embodiments, the N steps or methods may be implemented in software or firmware stored in a memory and executed by a suitable instruction execution system. As with the other embodiments, if implemented in hardware, may be implemented using any one or combination of the following techniques, as is well known in the art: discrete logic circuits having logic gates for implementing logic functions on data signals, application specific integrated circuits having suitable combinational logic gates, programmable gate arrays, field programmable gate arrays, and the like.
Those of ordinary skill in the art will appreciate that all or a portion of the steps carried out in the method of the above-described embodiments may be implemented by a program to instruct related hardware, where the program may be stored in a computer readable storage medium, and where the program, when executed, includes one or a combination of the steps of the method embodiments.
Although embodiments of the present application have been shown and described above, it will be understood that the above embodiments are illustrative and not to be construed as limiting the application, and that variations, modifications, alternatives, and variations may be made to the above embodiments by one of ordinary skill in the art within the scope of the application.

Claims (10)

1. A fatigue life prediction method, comprising the steps of:
determining a weld heat affected zone of a material to be analyzed, and calculating a modal stress result and a transfer function result of the material to be analyzed based on the weld heat affected zone;
obtaining a frequency response result of the material to be analyzed according to the modal stress result, the transfer function result and a preset random vibration psd spectrum; and
and fitting fatigue strength according to the tensile strength of the material to be analyzed based on the frequency response result to obtain a welding seam region material S-N curve of the material to be analyzed, and obtaining a fatigue damage result of the material to be analyzed in the welding seam heat affected zone according to the welding seam region material S-N curve and a preset survival rate to predict the fatigue life of the material to be analyzed according to the fatigue damage result.
2. The method of claim 1, wherein said fitting fatigue strength to said tensile strength of said material to be analyzed to obtain a weld zone material S-N curve of said material to be analyzed comprises:
fitting fatigue strength according to the tensile strength of the material to be analyzed to obtain an initial weld joint region material S-N curve;
and if the intercept of the initial weld joint area material S-N curve on the vertical axis is larger than the tensile strength, taking the initial weld joint area material S-N curve as the weld joint area material S-N curve of the material to be analyzed, otherwise, obtaining the weld joint area material S-N curve of the material to be analyzed according to the tensile strength and the fatigue front.
3. The method of claim 2, further comprising, after obtaining the weld zone material S-N curve for the material to be analyzed:
and correcting the welding line area material S-N curve of the material to be analyzed based on a preset correction strategy.
4. The method of claim 1, wherein the determining a weld heat affected zone of the material to be analyzed comprises:
modeling a weld joint of the material to be analyzed based on a preset structural grid model;
and (3) moving all grids at the joint of the welding lines to a target group to obtain a welding line heat affected zone of the material to be analyzed.
5. The method of any one of claims 1-4, wherein the predetermined survival rate is 90%.
6. A fatigue life predicting device, comprising:
the calculation module is used for determining a weld heat affected zone of the material to be analyzed and calculating a modal stress result and a transfer function result of the material to be analyzed based on the weld heat affected zone;
the acquisition module is used for acquiring a frequency response result of the material to be analyzed according to the modal stress result, the transfer function result and a preset random vibration psd spectrum; and
the analysis module is used for fitting fatigue strength according to the tensile strength of the material to be analyzed based on the frequency response result, obtaining a welding seam area material S-N curve of the material to be analyzed, and obtaining a fatigue damage result of the material to be analyzed in the welding seam heat affected zone according to the welding seam area material S-N curve and a preset survival rate, so as to predict the fatigue life of the material to be analyzed according to the fatigue damage result.
7. The apparatus of claim 6, wherein the analysis module is further configured to:
fitting fatigue strength according to the tensile strength of the material to be analyzed to obtain an initial weld joint region material S-N curve;
and if the intercept of the initial weld joint area material S-N curve on the vertical axis is larger than the tensile strength, taking the initial weld joint area material S-N curve as the weld joint area material S-N curve of the material to be analyzed, otherwise, obtaining the weld joint area material S-N curve of the material to be analyzed according to the tensile strength and the fatigue front.
8. The apparatus of claim 7, wherein after obtaining the weld zone material S-N curve of the material to be analyzed, the analysis module is further configured to:
and correcting the welding line area material S-N curve of the material to be analyzed based on a preset correction strategy.
9. An electronic device, comprising: a memory, a processor and a computer program stored on the memory and executable on the processor, the processor executing the program to implement the fatigue life prediction method according to any of claims 1-5.
10. A computer-readable storage medium, on which a computer program is stored, characterized in that the program is executed by a processor for implementing the fatigue life prediction method according to any of claims 1-5.
CN202211104718.6A 2022-09-09 2022-09-09 Fatigue life prediction method, device, electronic equipment and storage medium Pending CN116258032A (en)

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CN202211104718.6A CN116258032A (en) 2022-09-09 2022-09-09 Fatigue life prediction method, device, electronic equipment and storage medium

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CN202211104718.6A CN116258032A (en) 2022-09-09 2022-09-09 Fatigue life prediction method, device, electronic equipment and storage medium

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CN116258032A true CN116258032A (en) 2023-06-13

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