CN114065562A - EMD-based structural part fatigue simulation analysis method, device, terminal and medium - Google Patents
EMD-based structural part fatigue simulation analysis method, device, terminal and medium Download PDFInfo
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Abstract
The application provides a structural member fatigue simulation analysis method, a structural member fatigue simulation analysis device, a structural member fatigue simulation terminal and a structural member fatigue simulation medium based on EMD, wherein the method comprises the following steps: (a) acquiring a load signal; (b) carrying out EMD decomposition and effective IMF component signal screening on the load signal; (c) carrying out finite element simulation on the structural member to obtain a modal result of the structural member, a stress result of unit load and a modal stress result in a frequency sweeping state; (d) classifying the screened effective IMF component signals according to whether the mode points of the structural part are covered or not; (e) respectively carrying out fatigue damage calculation on the classified component signals; (f) and solving the total fatigue damage. According to the method, the original signals are classified according to whether the structure mode points are covered, the influence of different frequency bands and structure modes is considered, and a mixed algorithm of fatigue calculation is achieved.
Description
Technical Field
The application belongs to the technical field of structural member fatigue simulation analysis, and particularly relates to a structural member fatigue simulation analysis method, device, terminal and medium based on EMD.
Background
The traditional time domain fatigue simulation analysis method mainly comprises a quasi-static method and a transient method which have advantages and disadvantages respectively. The quasi-static method is high in calculation speed, but neglects the structural dynamics characteristic, and does not consider the influence of the mode on the fatigue result; the transient method considers the influence of resonance when the load excitation frequency covers the modal point of the structural member, but the solution time length and the operation scale are large.
An empirical mode decomposition method, EMD decomposition for short, is creatively proposed in 1998 by american chinese engineers n.e. huang et al, and is a novel adaptive signal time-frequency analysis method, which is particularly suitable for analysis and processing of nonlinear non-stationary signals, and is currently widely applied to aspects such as marine data analysis, voice recognition, state monitoring of mechanical equipment, fault diagnosis, and the like.
The invention content is as follows:
in view of the above, the present application provides a structural member fatigue simulation analysis method, apparatus, terminal and medium based on EMD, so as to implement a fatigue calculation hybrid algorithm based on EMD, and overcome the defects in the existing fatigue algorithms.
In order to achieve the purpose, the technical scheme adopted by the application is as follows:
in a first aspect, the present application provides an EMD-based structural member fatigue simulation analysis method, including:
(a) acquiring a load signal;
(b) carrying out EMD decomposition and effective IMF component signal screening on the load signal;
(c) carrying out finite element simulation on the structural member to obtain a modal result of the structural member, a stress result of unit load and a modal stress result in a frequency sweeping state;
(d) classifying the screened effective IMF component signals according to whether the mode points of the structural part are covered or not;
(e) respectively carrying out fatigue damage calculation on the classified component signals;
(f) and solving the total fatigue damage.
Optionally, after the load signal is obtained, preprocessing the load signal is further performed; performing EMD on the load signal, specifically performing EMD on the preprocessed load signal; the preprocessing comprises filtering, deburring and deshifting the acquired load signals.
Optionally, the specific method for performing EMD decomposition and effective IMF component signal screening on the load signal includes:
EMD decomposition is carried out on the obtained load signal to obtain IMF component signals c of each orderi(t) and corresponding fourier spectra;
the IMF component signals c of each order obtained by EMD decompositioni(t) performing correlation coefficient calculation with the original signals x (t), respectively, and dividing each order IMF component signal c obtained by EMD decompositioni(t) respectively carrying out energy ratio calculation with the original signals x (t);
and screening effective IMF signal components according to the calculated correlation coefficient and the energy ratio.
Optionally, the specific method for respectively performing fatigue damage calculation on the classified signal components includes:
reconstruction of IMF component signals not covering modal points by summation into new signal x1(t) solving the solution of x by using a quasi-static method according to the stress result of the unit load1(t) fatigue damage caused by D1;
reconstruction of IMF component signals covering modal points by summation into a new signal x2(t) solving the solution x by using a modal superposition method according to the modal stress result in the frequency sweeping state2(t) fatigue damage caused by D2;
the specific method for solving the total fatigue damage comprises the following steps:
will be composed of x1Fatigue damage caused by (t) D1 and by x2(t) the resulting fatigue damage D2 is summed.
In a second aspect, the present application provides an EMD-based structural member fatigue simulation analysis apparatus, including:
the acquisition module is used for acquiring a load signal;
the decomposition module is used for carrying out EMD decomposition and effective IMF component signal screening on the load signal;
the simulation module is used for carrying out finite element simulation on the structural member to obtain a modal result of the structural member, a stress result of unit load and a modal stress result in a frequency sweeping state;
the classification module is used for classifying the screened effective IMF component signals according to whether the modal points of the structural part are covered or not;
the first calculation module is used for respectively performing fatigue damage calculation on the classified component signals;
and the second calculation module is used for solving the total fatigue damage.
Optionally, the apparatus further comprises:
and the preprocessing module is used for preprocessing the load signal, and the preprocessing comprises filtering, deburring and drift removing processing on the acquired load signal.
Optionally, the decomposition module is specifically configured to:
EMD decomposition is carried out on the obtained load signal to obtain IMF component signals c of each orderi(t) and corresponding fourier spectra;
the IMF component signals c of each order obtained by EMD decompositioni(t) performing correlation coefficient calculation with the original signals x (t), respectively, and dividing each order IMF component signal c obtained by EMD decompositioni(t) respectively carrying out energy ratio calculation with the original signals x (t);
and screening effective IMF component signals according to the calculated correlation coefficient and the energy ratio.
Optionally, the first calculating module is specifically configured to:
reconstruction of IMF component signals not covering modal points by summation into new signal x1(t) solving the solution of x by using a quasi-static method according to the stress result of the unit load1(t) fatigue damage caused by D1;
reconstruction of IMF component signals covering modal points by summation into a new signal x2(t) solving the solution x by using a modal superposition method according to the modal stress result in the frequency sweeping state2(t) fatigue damage caused by D2;
the second calculation module is specifically configured to:
will be composed of x1Fatigue damage caused by (t) D1 and by x2(t) the resulting fatigue damage D2 is summed.
In a third aspect, an embodiment of the present application further provides a terminal, including: a processor, a memory and a communication unit;
the memory stores machine-readable instructions executable by the processor, the processor and the memory communicating through the communication unit when the device is operating;
wherein the processor executes the machine-readable instructions to perform the method of the above aspects.
In a fourth aspect, the present application further provides a computer-readable storage medium, on which a computer program is stored, where the computer program is executed by a processor to perform the method in the above aspects.
Compared with the prior art, the method has the following beneficial technical effects:
1. false components in the original signal are removed by using an EMD decomposition method, filtering is carried out adaptively, interference signals are suppressed, and the signal-to-noise ratio is improved;
2. classifying the original signals according to whether the structure modal points are covered, and considering the influence of different frequency bands and structure modes, so as to realize a mixed algorithm of fatigue calculation;
3. compared with the traditional quasi-static method, the method has the advantages of more accurate result, higher efficiency and shorter fatigue simulation calculation time compared with a modal transient superposition method.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are required to be used in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present application and therefore should not be considered as limiting the scope, and for those skilled in the art, other related drawings can be obtained from the drawings without inventive effort.
FIG. 1 is a flow chart of an EMD-based structural member fatigue simulation analysis method according to the present application;
FIG. 2 is a flow chart of an EMD-based structural member fatigue simulation analysis algorithm of the present application;
FIG. 3 is a schematic view of a cantilever beam application of the present application;
FIG. 4 is a graph of the IMF signal components after EMD decomposition according to the present application;
FIG. 5 is a spectrum diagram corresponding to an IMF signal component of the present application;
fig. 6 is a block diagram of the structural member fatigue simulation analysis apparatus based on EMD according to the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are some embodiments of the present application, but not all embodiments.
As shown in fig. 1 and 2, a first aspect of the present application provides an EMD-based structural member fatigue simulation analysis method, including:
(a) acquiring a load signal;
and acquiring a load signal x (t) borne by the structural part, wherein the load signal can be acquired through actual measurement, or can be acquired through virtual iteration by carrying a multi-body dynamic model. When the load signal is obtained through virtual iteration, a whole or partial system structure can be built by utilizing multi-body simulation software such as Adams and the like, the motion state of a real object is simulated in the multi-body analysis software, and the load signal is obtained through continuous iteration with a target signal.
As an alternative embodiment, after acquiring the load signal, the load signal may be preprocessed, for example, the load signal is filtered, deburred, or deshifted.
(b) Carrying out EMD decomposition and effective IMF component signal screening on the load signal;
after acquiring or preprocessing the load signal, EMD decomposition is carried out to obtain IMF component signals c of each orderi(t)And a corresponding fourier spectrum;
reconstructing the representation of the load signal x (t) by EMD decomposition:
the original load signal can be expressed as a multi-order IMF natural mode function c from high frequency to low frequencyi(t) and a residue term rn(t) sum of.
The specific decomposition process is as follows:
firstly, finding out local maximum and minimum of signal x (t), after obtaining all extreme points, all local maximum values are interpolated by using cubic spline interpolation function to form upper envelope of data, and in the same way, all local minimum values are interpolated to form lower envelope of data, and the average value of upper envelope and lower envelope is recorded as m1(t) the original signal x (t) minus m1(t) obtaining h1(t)：
h1(t)＝x(t)-m1(t) (2)
Then h will be1(t) as new x (t), m11(t) is the average of its upper and lower envelopes, having
h11(t)＝h1(t)-m11(t) (3)
If h11(t) if not yet satisfied, repeating the process k times to obtain
h1k(t)＝h1(k-1)(t)-m1k(t) (4)
If h1k(t) and h1(k-1)(t) standard deviation SD between predetermined ranges, stopping repeating the process, at which time h1k(t) is the first order IMF component signal of the original payload signal x (t), denoted c1(t)＝h1k(t), wherein the standard deviation SD is calculated as:
wherein T is the total time length of the load signal x (T);
specifically, the predetermined range of the standard deviation SD is generally 0.2 ≧ SD ≧ 0.3, but the predetermined range is not limited thereto, and the predetermined range may be adjusted differently according to the actual situation.
Let r be1(t)＝x(t)-c1(t) adding r1(t) is regarded as new x (t), the processes of the formulas (2) to (5) are repeated to obtain other IMF component signals of each order, which are respectively marked as c2(t)、c3(t)……ci(t) up to ri(t) is a monotonic function until the IMF can no longer be separated, and the decomposed IMF component signals can be seen in FIG. 4.
After the decomposition, each IMF component obtained by the decomposition is fourier-transformed to output a spectrogram, as shown in fig. 5.
The IMF component signals c of each order obtained by EMD decompositioni(t) performing correlation coefficient calculation with the original signals x (t), respectively, and dividing each order IMF component signal c obtained by EMD decompositioni(t) respectively carrying out energy ratio calculation with the original signals x (t);
correlation coefficient ρiComprises the following steps:
wherein, E (c)i(t)) is each IMF component signal ci(t) energy;
then, the total energy E of all valid signals is calculated:
calculating the energy ratio, i.e. the energy E (c) of the individual IMF componentsi(t)) percentage E (c) of total energy Ei(t))/E。
And screening effective IMF signal components according to the calculated correlation coefficient and the energy ratio.
In a specific embodiment, the effective IMF signal component may be screened according to whether the correlation coefficient is greater than 0.8 and the energy ratio is greater than 0.1, and the values of 0.8 and 0.1 may be changed to other values according to actual needs, which is not limited in this application.
It should be noted that, for the obtained IMF component, the larger the correlation coefficient with the original signal is, the larger the correlation between the IMF component and the original signal is, and vice versa.
According to the method, false components in the original signal are removed by using an EMD decomposition method, filtering is carried out adaptively, interference signals are suppressed, and the signal-to-noise ratio is improved.
(c) Carrying out finite element simulation on the structural member to obtain a modal result of the structural member, a stress result of unit load and a modal stress result in a frequency sweeping state;
carrying out finite element modeling simulation on the structural member through simulation software, establishing a finite element model, outputting a modal result, a stress result of unit load and a modal stress result file in a frequency sweeping state, wherein the load step needs to be established independently, and the result files are not affiliated to each other; outputting the modal result in a readable result file form in a common format of finite element analysis software such as op2 or rst; the modal result comprises a modal point of the structural member, and the modal point refers to each order of natural frequency of the structural member obtained through finite element simulation or actual modal test.
The unit load refers to unit force load, torque load and acceleration load. The frequency sweeping state refers to that under the excitation of unit load, frequency response analysis is carried out within a frequency range of a certain bandwidth according to a certain frequency step length to obtain the structural stress corresponding to each frequency, and the structural stress is output in a readable structural file form;
in the swept frequency regime, the frequency range of the certain bandwidth is determined depending on the maximum frequency in the actual working environment of the structure, for example, 20% above the maximum frequency may be used as the upper limit of the implemented frequency range, and the lower limit may be 1 Hz. In specific implementation, the certain frequency step length may be determined according to a principle that the minimum is 1Hz and the maximum does not exceed 5 Hz.
(d) Classifying the screened effective IMF component signals according to whether the mode points of the structural part are covered or not;
specifically, based on the modal result obtained by the finite element simulation and the spectrogram corresponding to each IMF component, the method is based on the IMF component signals c of each orderi(t) whether the corresponding Fourier spectrum peak value coincides with the modal point of the structural part or not classifies the frequency spectrum corresponding to the IMF component signal as one class including the modal point of the structural part, and classifies the frequency spectrum corresponding to the IMF component signal as another class not including the modal point of the structural part.
For the class of IMF component signals which do not cover modal frequency points, reordering the IMF component signals from small to large according to the original IMF corner marks to form m groups, and reconstructing all IMF functions in the class into a new load x1(t)，
For the class of IMF component signals covering modal frequency points, reordering the IMF component signals from small to large according to the original IMF corner marks to form l groups, and reconstructing all IMF functions into a new load x2(t)，
l+m＝n-nex-imfWherein n isex-imfThe number of invalid IMF components that are to be filtered out.
The fatigue loading of the structure may be represented by a load x encompassing the modal point2(t) and a load x without modal points1(t) composition.
(e) Respectively carrying out fatigue damage calculation on the classified signal components;
reconstruction of IMF signal components not covering modal points by summation into a new signal x1(t) solving the solution of x by using a quasi-static method according to the stress result of the unit load1(t) fatigue damage caused by D1;
in the cantilever beam shown in fig. 3, the end part is loaded with x (t), and IMF signals which do not cover the modal point are summed and reconstructed into a new signal x1(t) first, a unit load of 1N is applied to the end portion to obtain a stress distribution σ of the beam1Then the stress and x are obtained1(t) multiplying to obtain a stress history σ1x1(t) carrying out rain flow counting and fatigue calculation by combining the stress history with an S-N curve, wherein S is the magnitude of stress amplitude, and N is the corresponding fatigue life, namely, the structural part is damaged after N times of cyclic stress action with the magnitude of S is borne.
Reconstruction of IMF signal components covering modal points by summation into a new signal x2(t) solving the solution x by using a modal superposition method according to the modal stress result in the frequency sweeping state2(t) fatigue damage caused by D2;
solving for x2(t) each IMF component signal ck(t) Modal stress σ of corresponding Modal PointkMultiplying and summing each IMF component signal and corresponding modal stress to obtain local stress history
Then, rain flow counting is carried out on the stress, and fatigue solving is carried out.
(f) And solving the total fatigue damage.
Will be composed of x1Fatigue damage caused by (t) D1 and by x2(t) the resulting fatigue damage D2 is summed.
And the overall fatigue damage D is D1+ D2.
Example (c):
for the cantilever beam shown in fig. 3, it is assumed that the cantilever beam has two modal points within 100Hz, the natural frequencies of the first two orders are 10Hz and 50Hz, the effective IMFs after the actual load x (t) decomposition and screening are shown in fig. 4, and according to the frequency spectrums of the respective IMF decompositions, as shown in fig. 5, the components IMF2 and IMF3 cover the modal points 10Hz and 50 Hz. Since the example raw signal x (t) given decomposes 3 IMF signals, IMF1, IMF2, IMF3, where the signals covering the modal points are IMF2 and IMF3, these two signals can be reconstructed as x according to equation (10)2(t), IMF1 may reconstruct signal x according to equation (9)1(t), at the moment, a finite element analysis model of the beam is firstly established by using CAE analysis software, a unit force 1N load is added at the tail end of the beam, static calculation is carried out, and the stress sigma of the cantilever beam under the load is obtained1And combining it with the reconstructed load x1(t) multiplying to obtain a stress history σ1x1(t), carrying out rain flow counting and fatigue solving to obtain loss D1, then carrying out 1N, 0-120Hz frequency sweep (the frequency sweep range is determined according to 120% of the maximum frequency of the force load signal) calculation by utilizing finite element analysis software to obtain modal stress sigma corresponding to 10Hz and 50Hz2And σ3Finally, the local stress history sigma is obtained2c2(t)+σ3c3(t), rain flow counting and fatigue solving are carried out on the stress course to obtain loss D2, and finally, the total damage is solved, and the overall fatigue damage D is D1+ D2.
According to the method, the original signals are classified according to whether the structure modal points are covered, the influence of different frequency bands and structure modes is considered, a fatigue calculation hybrid algorithm is achieved, the result is more accurate compared with the traditional quasi-static method, the efficiency is higher compared with a modal transient superposition method, and the fatigue simulation calculation time is shorter.
In a second aspect, the present application provides an EMD-based structural member fatigue simulation analysis apparatus, as shown in fig. 6, including:
an obtaining module 610, configured to obtain a load signal;
the obtaining module 610 obtains a load signal x (t) borne by the structural member, and the obtaining of the load signal can be through actual measurement, or can be obtained through virtual iteration by carrying a multi-body dynamic model. When the load signal is obtained through virtual iteration, a whole or partial system structure can be built by utilizing multi-body simulation software such as Adams and the like, the motion state of a real object is simulated in the multi-body analysis software, and the load signal is obtained through continuous iteration with a target signal.
As an optional implementation, the apparatus further comprises:
and the preprocessing module is used for preprocessing the load signal, and the preprocessing comprises filtering, deburring and drift removing processing on the acquired load signal.
A decomposition module 620, configured to perform EMD decomposition and effective IMF component signal screening on the payload signal;
after acquiring or preprocessing the load signal, the decomposition module 620 then performs EMD decomposition to obtain each order of IMF component signal ci(t) and corresponding fourier spectra;
reconstructing the representation of the load signal x (t) by EMD decomposition:
the original load signal can be expressed as a multi-order IMF natural mode function c from high frequency to low frequencyi(t) and a residue term rn(t) sum of.
The specific decomposition process is as follows:
firstly, finding out local maximum and minimum of signal x (t), after obtaining all extreme points, all local maximum values are interpolated by using cubic spline interpolation function to form upper envelope of data, and in the same way, all local minimum values are interpolated to form lower envelope of data, and the average value of upper envelope and lower envelope is recorded as m1(t) the original signal x (t) minus m1(t) obtaining h1(t)：
h1(t)＝x(t)-m1(t) (2)
Then h will be1(t) as new x (t), m11(t) is the average of its upper and lower envelopes, having
h11(t)＝h1(t)-m11(t) (3)
If h11(t) if not yet satisfied, repeating the process k times to obtain
h1k(t)＝h1(k-1)(t)-m1k(t) (4)
If h1k(t) and h1(k-1)(t) standard deviation SD between predetermined ranges, stopping repeating the process, at which time h1k(t) is the first order IMF component signal of the original payload signal x (t), denoted c1(t)＝h1k(t) wherein the standard deviation SDThe calculation formula is as follows:
wherein T is the total time length of the load signal x (T);
specifically, the predetermined range of the standard deviation SD is generally 0.2 ≧ SD ≧ 0.3, but the predetermined range is not limited thereto, and the predetermined range may be adjusted differently according to the actual situation.
Let r be1(t)＝x(t)-c1(t) adding r1(t) is regarded as new x (t), the processes of the formulas (2) to (5) are repeated to obtain other IMF component signals of each order, which are respectively marked as c2(t)、c3(t)……ci(t) up to ri(t) is a monotonic function until the IMF can no longer be separated, and the decomposed IMF component signals can be seen in FIG. 4.
After the decomposition, each IMF component obtained by the decomposition is fourier-transformed to output a spectrogram, as shown in fig. 5.
The IMF component signals c of each order obtained by EMD decompositioni(t) performing correlation coefficient calculation with the original signals x (t), respectively, and dividing each order IMF component signal c obtained by EMD decompositioni(t) respectively carrying out energy ratio calculation with the original signals x (t);
correlation coefficient ρiComprises the following steps:
wherein, E (c)i(t)) is each IMF component signal ci(t) energy;
then, the total energy E of all valid signals is calculated:
calculating the energy ratio, i.e. the energy E (c) of the individual IMF componentsi(t)) percentage E (c) of total energy Ei(t))/E。
And screening effective IMF signal components according to the calculated correlation coefficient and the energy ratio.
In a specific embodiment, the effective IMF signal component may be screened according to whether the correlation coefficient is greater than 0.8 and the energy ratio is greater than 0.1, and the values of 0.8 and 0.1 may be changed to other values according to actual needs, which is not limited in this application.
It should be noted that, for the obtained IMF component, the larger the correlation coefficient with the original signal is, the larger the correlation between the IMF component and the original signal is, and vice versa.
According to the method, false components in the original signal are removed by using an EMD decomposition method, filtering is carried out adaptively, interference signals are suppressed, and the signal-to-noise ratio is improved.
The simulation module 630 is configured to perform finite element simulation on a structural component, and obtain a modal result of the structural component, a stress result of a unit load, and a modal stress result in a frequency sweep state;
the simulation module 630 performs finite element modeling simulation on the structural member through simulation software, establishes a finite element model, outputs a modal result, a unit load stress result and a modal stress result file in a frequency sweeping state, and needs to establish a load step independently, wherein the result files are not affiliated to each other; outputting the modal result in a readable result file form in a common format of finite element analysis software such as op2 or rst; the modal result comprises a modal point of the structural member, and the modal point refers to each order of natural frequency of the structural member obtained through finite element simulation or actual modal test.
The unit load refers to unit force load, torque load and acceleration load. The frequency sweeping state refers to that under the excitation of unit load, frequency response analysis is carried out within a frequency range of a certain bandwidth according to a certain frequency step length to obtain the structural stress corresponding to each frequency, and the structural stress is output in a readable structural file form;
in the swept frequency regime, the frequency range of the certain bandwidth is determined depending on the maximum frequency in the actual working environment of the structure, for example, 20% above the maximum frequency may be used as the upper limit of the implemented frequency range, and the lower limit may be 1 Hz. In specific implementation, the certain frequency step length may be determined according to a principle that the minimum is 1Hz and the maximum does not exceed 5 Hz.
The classification module 640 is configured to classify the screened effective IMF component signals according to whether the mode points of the structural component are included;
specifically, based on the modal result obtained by the finite element simulation and the spectrogram corresponding to each IMF component, the method is based on the IMF component signals c of each orderi(t) whether the corresponding Fourier spectrum peak value coincides with the modal point of the structural part or not classifies the frequency spectrum corresponding to the IMF component signal as one class including the modal point of the structural part, and classifies the frequency spectrum corresponding to the IMF component signal as another class not including the modal point of the structural part.
For the class of IMF component signals which do not cover modal frequency points, reordering the IMF component signals from small to large according to the original IMF corner marks to form m groups, and reconstructing all IMF functions in the class into a new load x1(t)，
For the class of IMF component signals covering modal frequency points, reordering the IMF component signals from small to large according to the original IMF corner marks to form l groups, and reconstructing all IMF functions into a new load x2(t)，
l+m＝n-nex-imfWherein n isex-imfThe number of invalid IMF components that are to be filtered out.
The fatigue loading of the structure may be represented by a load x encompassing the modal point2(t) and a load x without modal points1(t) composition.
The first calculation module 650 is configured to perform fatigue damage calculation on the classified component signals respectively;
reconstruction of IMF signal components not covering modal points by summation into a new signal x1(t) solving the solution of x by using a quasi-static method according to the stress result of the unit load1(t) fatigue damage caused by D1;
in the cantilever beam shown in fig. 3, the end part is loaded with x (t), and IMF signals which do not cover the modal point are summed and reconstructed into a new signal x1(t) first, a unit load of 1N is applied to the end portion to obtain a stress distribution σ of the beam1Then the stress and x are obtained1(t) multiplying to obtain a stress history σ1x1(t) carrying out rain flow counting and fatigue calculation by combining the stress history with an S-N curve, wherein S is the magnitude of stress amplitude, and N is the corresponding fatigue life, namely, the structural part is damaged after N times of cyclic stress action with the magnitude of S is borne.
Reconstruction of IMF signal components covering modal points by summation into a new signal x2(t) solving the solution x by using a modal superposition method according to the modal stress result in the frequency sweeping state2(t) fatigue damage caused by D2;
solving for x2(t) each IMF component signal ck(t) Modal stress σ of corresponding Modal PointkMultiplying and summing each IMF component signal and corresponding modal stress to obtain local stress history
Then, rain flow counting is carried out on the stress, and fatigue solving is carried out.
And a second calculation module 660 for solving for total fatigue damage.
Will be composed of x1Fatigue damage caused by (t) D1 and by x2(t) the resulting fatigue damage D2 is summed.
And the overall fatigue damage D is D1+ D2.
In a third aspect, an embodiment of the present application further provides a terminal, including: a processor, a memory and a communication unit;
the memory stores machine-readable instructions executable by the processor, the processor and the memory communicating through the communication unit when the device is operating;
wherein the processor executes the machine-readable instructions to perform the methods of the various aspects described above.
The memory may be used to store instructions for execution by the processor and may be implemented by any type of volatile or non-volatile memory terminal or combination thereof, such as Static Random Access Memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic or optical disk. The execution instructions in the memory, when executed by the processor, enable the apparatus to perform some or all of the steps in the method embodiments described below.
The processor is a control center of the storage terminal, connects various parts of the whole electronic terminal by using various interfaces and lines, and executes various functions of the electronic terminal and/or processes data by operating or executing software programs and/or modules stored in the memory and calling data stored in the memory. The processor may be composed of an Integrated Circuit (IC), for example, a single packaged IC, or a plurality of packaged ICs connected with the same or different functions. For example, a processor may include only a Central Processing Unit (CPU). In the embodiments of the present application, the CPU may be a single arithmetic core or may include multiple arithmetic cores.
A communication unit for establishing a communication channel so that the storage device can communicate with other terminals. And receiving user data sent by other terminals or sending the user data to other terminals.
In a fourth aspect, embodiments of the present application further provide a computer storage medium, where the computer storage medium may store a program, and the program may include some or all of the steps in the embodiments provided in the present application when executed. The storage medium may be a magnetic disk, an optical disk, a read-only memory (ROM) or a Random Access Memory (RAM).
According to the method, false components in the original signal are removed by using an EMD decomposition method, filtering is carried out adaptively, interference signals are suppressed, and the signal-to-noise ratio is improved; the original signals are classified according to whether the structure modal points are covered, the influence of different frequency bands and structure modes is considered, a fatigue calculation hybrid algorithm is achieved, compared with the traditional quasi-static method, the result is more accurate, compared with a modal transient superposition method, the efficiency is higher, and the fatigue simulation calculation time is shorter.
In the embodiments provided in the present application, it should be understood that the disclosed system and method may be implemented in other ways. For example, the above-described node embodiments are merely illustrative, and for example, the division of the modules is only one logical functional division, and in actual implementation, there may be another division, for example, multiple units or components may be combined or integrated into another device, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
The modules described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, each functional module in the embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, or in a form of hardware plus a software functional unit.
The above description is only for the specific embodiments of the present application, but the scope of the present application is not limited thereto, and any person skilled in the art can easily conceive of the changes or substitutions within the technical scope of the present application, and shall be covered by the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.
Claims (10)
1. The structural part fatigue simulation analysis method based on EMD is characterized by comprising the following steps:
(a) acquiring a load signal;
(b) carrying out EMD decomposition and effective IMF component signal screening on the load signal;
(c) carrying out finite element simulation on the structural member to obtain a modal result of the structural member, a stress result of unit load and a modal stress result in a frequency sweeping state;
(d) classifying the screened effective IMF component signals according to whether the mode points of the structural part are covered or not;
(e) respectively carrying out fatigue damage calculation on the classified component signals;
(f) and solving the total fatigue damage.
2. The EMD-based structural member fatigue simulation analysis method of claim 1, further comprising preprocessing the load signal after the obtaining the load signal; performing EMD on the load signal, specifically performing EMD on the preprocessed load signal; the preprocessing comprises filtering, deburring and deshifting the acquired load signals.
3. The EMD-based structural member fatigue simulation analysis method of claim 2, wherein the specific method for EMD decomposition and effective IMF component signal screening of the load signal is as follows:
EMD decomposition is carried out on the obtained load signal to obtain IMF component signals c of each orderi(t) and corresponding Fourier transformA frequency spectrum;
the IMF component signals c of each order obtained by EMD decompositioni(t) performing correlation coefficient calculation with the original signals x (t), respectively, and dividing each order IMF component signal c obtained by EMD decompositioni(t) respectively carrying out energy ratio calculation with the original signals x (t);
and screening effective IMF signal components according to the calculated correlation coefficient and the energy ratio.
4. The EMD-based structural member fatigue simulation analysis method according to claim 3, wherein the specific method for respectively performing fatigue damage calculation on the classified signal components is as follows:
reconstruction of IMF component signals not covering modal points by summation into new signal x1(t) solving the solution of x by using a quasi-static method according to the stress result of the unit load1(t) fatigue damage caused by D1;
reconstruction of IMF component signals covering modal points by summation into a new signal x2(t) solving the solution x by using a modal superposition method according to the modal stress result in the frequency sweeping state2(t) fatigue damage caused by D2;
the specific method for solving the total fatigue damage comprises the following steps:
will be composed of x1Fatigue damage caused by (t) D1 and by x2(t) the resulting fatigue damage D2 is summed.
5. EMD-based structural part fatigue simulation analysis device is characterized by comprising:
the acquisition module is used for acquiring a load signal;
the decomposition module is used for carrying out EMD decomposition and effective IMF component signal screening on the load signal;
the simulation module is used for carrying out finite element simulation on the structural member to obtain a modal result of the structural member, a stress result of unit load and a modal stress result in a frequency sweeping state;
the classification module is used for classifying the screened effective IMF component signals according to whether the modal points of the structural part are covered or not;
the first calculation module is used for respectively performing fatigue damage calculation on the classified component signals;
and the second calculation module is used for solving the total fatigue damage.
6. The EMD-based structural member fatigue simulation analysis device of claim 5, further comprising:
and the preprocessing module is used for preprocessing the load signal, and the preprocessing comprises filtering, deburring and drift removing processing on the acquired load signal.
7. The EMD-based structural member fatigue simulation analysis device of claim 6, wherein the decomposition module is specifically configured to:
EMD decomposition is carried out on the obtained load signal to obtain IMF component signals c of each orderi(t) and corresponding fourier spectra;
the IMF component signals c of each order obtained by EMD decompositioni(t) performing correlation coefficient calculation with the original signals x (t), respectively, and dividing each order IMF component signal c obtained by EMD decompositioni(t) respectively carrying out energy ratio calculation with the original signals x (t);
and screening effective IMF component signals according to the calculated correlation coefficient and the energy ratio.
8. The EMD-based structural member fatigue simulation analysis device of claim 7, wherein the first computing module is specifically configured to:
reconstruction of IMF component signals not covering modal points by summation into new signal x1(t) solving the solution of x by using a quasi-static method according to the stress result of the unit load1(t) fatigue damage caused by D1;
reconstruction of IMF component signals covering modal points by summation into a new signal x2(t) solving the solution x by using a modal superposition method according to the modal stress result in the frequency sweeping state2(t) fatigue damage caused by D2;
the second calculation module is specifically configured to:
will be composed of x1Fatigue damage caused by (t) D1 and by x2(t) the resulting fatigue damage D2 is summed.
9. A terminal, comprising: a processor, a memory and a communication unit;
the memory stores machine-readable instructions executable by the processor, the processor and the memory communicating through the communication unit when the device is operating;
wherein the processor executes the machine readable instructions to perform the method of any of claims 1 to 4.
10. A computer-readable storage medium, having stored thereon a computer program which, when executed by a processor, performs the method of any one of claims 1 to 4.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117828954A (en) * | 2024-03-04 | 2024-04-05 | 质子汽车科技有限公司 | Swing arm fatigue analysis method and system considering contact state and electronic equipment |
| CN118013259A (en) * | 2024-04-09 | 2024-05-10 | 中国人民解放军海军工程大学 | Data analysis method based on non-contact measurement and related equipment thereof |
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117828954A (en) * | 2024-03-04 | 2024-04-05 | 质子汽车科技有限公司 | Swing arm fatigue analysis method and system considering contact state and electronic equipment |
| CN117828954B (en) * | 2024-03-04 | 2024-06-07 | 质子汽车科技有限公司 | Swing arm fatigue analysis method and system considering contact state and electronic equipment |
| CN118013259A (en) * | 2024-04-09 | 2024-05-10 | 中国人民解放军海军工程大学 | Data analysis method based on non-contact measurement and related equipment thereof |
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