EMD-Based Fatigue Simulation Analysis Method, Device, Terminal, and Medium for Structural Components

Abstract

The present application provides a fatigue simulation analysis method, device, terminal and medium based on EMD. The method includes: (a) obtaining a load signal; (b) performing EMD decomposition on the load signal and screening effective IMF component signals; (c) performing finite element simulation on the structural member to obtain the modal results of the structural member, the stress results of the unit load, and the modal stress results under the swept frequency state; (d) classifying the screened effective IMF component signals according to whether they cover the modal points of the structural member; (e) performing fatigue damage calculation on the classified component signals respectively; (f) solving the total fatigue damage. The present application classifies the original signal according to whether it covers the structural modal points, considers the influence of different frequency bands and structural modes, and realizes a hybrid algorithm for fatigue calculation.

Description

Technical Field

[0001] This application belongs to the technical field of structural component fatigue simulation analysis, and specifically relates to a method, device, terminal, and medium for structural component fatigue simulation analysis based on EMD. Background Art

[0002] The traditional time-domain fatigue simulation analysis methods mainly include the quasi-static method and the transient method, each with its own advantages and disadvantages. The quasi-static method has a fast calculation speed, but it ignores the structural dynamics characteristics and does not consider the influence of modes on fatigue results; the transient method considers the influence of resonance when the load excitation frequency covers the modal points of the structural component, but the solution time and calculation scale are large.

[0003] In 1998, the American Chinese engineer N.E. Huang et al. creatively proposed the empirical mode decomposition method, abbreviated as EMD decomposition. It is a new type of adaptive signal time-frequency analysis method, especially suitable for the analysis and processing of non-linear and non-stationary signals. It has been widely used in aspects such as ocean data analysis, speech recognition, condition monitoring, and fault diagnosis of mechanical equipment. Summary of the Invention

[0004] In view of this, this application provides a method, device, terminal, and medium for structural component fatigue simulation analysis based on EMD to implement a hybrid algorithm for fatigue calculation based on EMD and overcome the defects in the existing fatigue algorithms.

[0005] To achieve the above object, the technical solutions adopted in this application are as follows:

[0006] In the first aspect, this application provides a method for structural component fatigue simulation analysis based on EMD, including:

[0007] (a) Obtain a load signal;

[0008] (b) Perform EMD decomposition on the load signal and screen the effective IMF component signals;

[0009] (c) Perform finite element simulation on the structural component to obtain the modal results of the structural component, the stress results of the unit load, and the modal stress results under the swept frequency state;

[0010] (d) Classify the screened effective IMF component signals according to whether they cover the modal points of the structural component;

[0011] (e) Perform fatigue damage calculation on the classified component signals respectively;

[0012] (f) Solve the total fatigue damage.

[0013] Optionally, after obtaining the load signal, preprocessing the load signal is further included; specifically, performing EMD decomposition on the load signal means performing EMD decomposition on the preprocessed load signal; the preprocessing includes filtering, deburring, and drift removal on the obtained load signal.

[0014] Optionally, the specific method for performing EMD decomposition on the load signal and screening effective IMF component signals is as follows:

[0015] Perform EMD decomposition on the obtained load signal to obtain each order of IMF component signal c i (t) and the corresponding Fourier spectrum;

[0016] Calculate the correlation coefficient between each order of IMF component signal c i (t) obtained by EMD decomposition and the original signal x(t) respectively, and calculate the energy proportion of each order of IMF component signal c i (t) obtained by EMD decomposition and the original signal x(t) respectively;

[0017] Screen effective IMF signal components according to the calculated correlation coefficient and energy proportion.

[0018] Optionally, the specific method for calculating fatigue damage for the classified signal components respectively is as follows:

[0019] Sum up the IMF component signals that do not cover the modal points and reconstruct them into a new signal x 1 (t), and use the quasi-static method to solve the fatigue damage D1 caused by x 1 (t) according to the stress result of the unit load;

[0020] Sum up the IMF component signals that cover the modal points and reconstruct them into a new signal x 2 (t), and use the modal superposition method to solve the fatigue damage D2 caused by x 2 (t) according to the modal stress result under the swept-frequency state;

[0021] The specific method for solving the total fatigue damage is as follows:

[0022] Sum up the fatigue damage D1 caused by x 1 (t) and the fatigue damage D2 caused by x 2 (t).

[0023] In a second aspect, the present application provides a structural member fatigue simulation analysis device based on EMD, including:

[0024] An acquisition module, configured to acquire a load signal;

[0025] A decomposition module for performing EMD decomposition on the load signal and screening effective IMF component signals;

[0026] A simulation module for performing finite element simulation on the structural member to obtain the modal results of the structural member, the stress results of the unit load, and the modal stress results under the swept-frequency state;

[0027] A classification module for classifying the screened effective IMF component signals according to whether they cover the modal points of the structural member;

[0028] A first calculation module for separately performing fatigue damage calculations on the classified component signals;

[0029] A second calculation module for solving the total fatigue damage.

[0030] Optionally, the device further includes:

[0031] A preprocessing module for preprocessing the load signal, where the preprocessing includes filtering, deburring, and detrending the obtained load signal.

[0032] Optionally, the decomposition module is specifically configured to:

[0033] Perform EMD decomposition on the obtained load signal to obtain each-order IMF component signal c i (t) and the corresponding Fourier spectrum;

[0034] Calculate the correlation coefficient between each-order IMF component signal c i (t) obtained by EMD decomposition and the original signal x(t) respectively, and calculate the energy proportion between each-order IMF component signal c i (t) obtained by EMD decomposition and the original signal x(t) respectively;

[0035] Screen the effective IMF component signals according to the calculated correlation coefficient and energy proportion.

[0036] Optionally, the first calculation module is specifically configured to:

[0037] Sum and reconstruct the IMF component signals that do not cover the modal points into a new signal x 1 (t), and use the quasi-static method to solve the fatigue damage D1 caused by x 1 (t) according to the stress results of the unit load;

[0038] Sum and reconstruct the IMF component signals that cover the modal points into a new signal x 2 (t), and use the modal superposition method to solve the fatigue damage D2 caused by x 2 (t) according to the modal stress results under the swept-frequency state;

[0039] The second calculation module is specifically configured to:

[0040] Sum the fatigue damage D1 caused by x 1 (t) and the fatigue damage D2 caused by x 2 (t).

[0041] In a third aspect, an embodiment of the present application further provides a terminal, including: a processor, a memory, and a communication unit;

[0042] The memory stores machine-readable instructions executable by the processor. When the device runs, the processor communicates with the memory through the communication unit;

[0043] Wherein, the processor executes the machine-readable instructions to execute the methods described in the above aspects.

[0044] In a fourth aspect, an embodiment of the present application further provides a computer-readable storage medium. A computer program is stored on the computer-readable storage medium, and when the computer program is run by a processor, it executes the methods described in the above aspects.

[0045] Compared with the prior art, the present application has the following beneficial technical effects:

[0046] 1. Using the EMD decomposition method to eliminate the false components in the original signal, adaptively filtering, suppressing interference signals, and improving the signal-to-noise ratio;

[0047] 2. Classifying the original signal according to whether it covers the structural modal points, considering the influence of different frequency bands and structural modes, and implementing a hybrid algorithm for fatigue calculation;

[0048] 3. The result is more accurate than the traditional quasi-static method, and compared with the modal transient superposition method, it has higher efficiency and shorter fatigue simulation calculation time. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following will briefly introduce the drawings required for the embodiments. It should be understood that the following drawings only show some embodiments of the present application, and therefore should not be regarded as limiting the scope. For those of ordinary skill in the art, other related drawings can be obtained based on these drawings without creative efforts.

[0050] Figure 1 It is a flowchart of the method for fatigue simulation analysis of structural components based on EMD of the present application;

[0051] Figure 2This is the flow chart of the fatigue simulation analysis algorithm for structural components based on EMD in this application;

[0052] Figure 3 This is the application schematic diagram of the cantilever beam in this application;

[0053] Figure 4 This is the IMF signal component diagram after EMD decomposition in this application;

[0054] Figure 5 This is the frequency spectrum diagram corresponding to the IMF signal component in this application;

[0055] Figure 6 This is the structural block diagram of the fatigue simulation analysis device for structural components based on EMD in this application. Specific implementation mode

[0056] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions in the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of this application. Obviously, the described embodiments are some, but not all, of the embodiments of this application.

[0057] As Figure 1 and 2 shown, the first aspect of this application provides a fatigue simulation analysis method for structural components based on EMD, including:

[0058] (a) Obtain the load signal;

[0059] Obtain the load signal x(t) received by the structural component. The load signal can be obtained through actual measurement or by loading a multi-body dynamics model and obtaining it through virtual iteration. When obtaining it through virtual iteration, multi-body simulation software such as Adams can be used to build the structure of the entire or part of the system, simulate the motion state of real objects in the multi-body analysis software, and obtain the load signal through continuous iteration with the target signal.

[0060] As an optional implementation mode, after obtaining the load signal, the load signal can also be preprocessed, such as filtering, deburring, or detrending the load signal, etc.

[0061] (b) Perform EMD decomposition on the load signal and screen the effective IMF component signals;

[0062] After obtaining the load signal or preprocessing the load signal, the EMD decomposition work is then carried out to obtain the IMF component signals c i (t) and the corresponding Fourier spectrum;

[0063] Reconstruct and represent the load signal x(t) through EMD decomposition:

[0064]

[0065] The original load signal can be successively expressed as a multi - order IMF (Intrinsic Mode Function) c i (t) and a residual term r n (t) from high frequency to low frequency.

[0066] The specific decomposition process is as follows:

[0067] First, find the local maxima and minima of the signal x(t). After obtaining all the extreme points, all the local maxima are interpolated with a cubic spline interpolation function to form the upper envelope of the data. Similarly, all the local minima are interpolated to form the lower envelope of the data. The average value of the upper envelope and the lower envelope is denoted as m 1 (t). The original signal x(t) minus m 1 (t) gives h 1 (t):

[0068] h 1 (t) = x(t) - m 1 (t) (2)

[0069] Then, regard h 1 (t) as the new x(t), and m 11 (t) is the average value of its upper and lower envelope lines, so there is

[0070] h 11 (t) = h 1 (t) - m 11 (t) (3)

[0071] If h 11 (t) still does not meet the requirements, repeat this process k times to get

[0072] h 1k (t) = h 1(k-1) (t) - m 1k (t) (4)

[0073] If the standard deviation SD between h 1k (t) and h 1(k-1) (t) is within a predetermined range, then stop repeating this process. At this time, h 1k (t) is the first - order IMF component signal of the original load signal x(t), denoted as c 1 (t) = h 1k (t), and the calculation formula for the standard deviation SD is:

[0074]

[0075] In the formula, T is the total time length of the load signal x(t);

[0076] Specifically, the predetermined range of the standard deviation SD is generally 0.2 ≥ SD ≥ 0.3, but it is not limited to this, and the predetermined range can also be adjusted differently according to the actual situation.

[0077] Let r 1 (t) = x(t) - c 1 (t), and regard r 1 (t) as the new x(t), repeat the process of formulas (2) - (5) to obtain other IMF component signals of each order, which are respectively denoted as c 2 (t), c 3 (t) …… c i (t), until r i (t) is a monotonic function and no longer can be decomposed into IMF, and the decomposed IMF component signals can be seen in Figure 4 .

[0078] After decomposition, perform Fourier transform on each decomposed IMF component and output the spectrogram, as Figure 5 shown.

[0079] Calculate the correlation coefficient between each order IMF component signal c i (t) obtained by EMD decomposition and the original signal x(t) respectively, and calculate the energy proportion of each order IMF component signal c i (t) obtained by EMD decomposition and the original signal x(t) respectively;

[0080] The correlation coefficient ρ i is:

[0081]

[0082] where E(c i (t)) is the energy of each IMF component signal c i (t);

[0083]

[0084] Then, calculate the total energy E of all effective signals:

[0085]

[0086] Calculate the energy proportion, that is, the percentage of the energy E(c i (t)) of a single IMF component in the total energy E, which is E(c i (t)) / E.

[0087] Screen the effective IMF signal components according to the calculated correlation coefficient and energy proportion.

[0088] In a specific embodiment, effective IMF signal components can be screened according to whether the correlation coefficient is greater than 0.8 and whether the energy ratio is greater than 0.1. The 0.8 and 0.1 can also be changed to other values according to actual needs, and the present application does not limit this.

[0089] It should be noted that for the obtained IMF components, the larger the correlation coefficient between it and the original signal, the greater the correlation between this IMF component and the original signal, and vice versa.

[0090] The present application uses the EMD decomposition method to eliminate the false components in the original signal, adaptively filters, suppresses interference signals, and improves the signal-to-noise ratio.

[0091] (c) Perform finite element simulation on the structural member to obtain the modal results of the structural member, the stress results of the unit load, and the modal stress results under the swept-frequency state;

[0092] Perform finite element modeling and simulation on the structural member through simulation software. Establish a finite element model, output the modal results, the stress results of the unit load, and the modal stress result files under the swept-frequency state. Separate load steps need to be established, and the result files are not subordinate to each other; the modal results are output in a readable result file format in common formats such as op2 or rst of finite element analysis software; the modal results include the modal points of the structural member, and the modal points refer to the natural frequencies of each order of the structural member obtained through finite element simulation or actual modal test.

[0093] The unit load refers to unit force load, torque load, and acceleration load. The swept-frequency state refers to performing frequency response analysis at a certain frequency step within a certain bandwidth of frequency range under the excitation of the unit load to obtain the structural stress corresponding to each frequency and output it in a readable structural file format;

[0094] Under the swept-frequency state, the determination of the certain bandwidth of frequency range depends on the maximum frequency in the actual working environment of the structural member. For example, the upper limit of the implementation frequency range can be 20% higher than the maximum frequency, and the lower limit can usually be taken as 1 Hz. In specific implementation, the certain frequency step can be determined according to the principle that the minimum is 1 Hz and the maximum does not exceed 5 Hz.

[0095] (d) Classify the screened effective IMF component signals according to whether they cover the modal points of the structural member;

[0096] Specifically, based on the modal results obtained from the aforementioned finite element simulation and the spectrogram corresponding to each IMF component, according to each order of IMF component signal c i(t) and the peak value of the corresponding Fourier spectrum coincide with the modal points of the structural member, and the IMF component signals whose corresponding spectra contain the modal points of the structural member are classified into one category, while those whose corresponding spectra do not contain the modal points of the structural member are classified into another category.

[0097] For the category of IMF component signals that do not cover the modal frequency points, reorder them in ascending order according to the original IMF subscripts, forming a total of m groups, and reconstruct all the IMF functions in this category into a new load x 1 (t),

[0098]

[0099] For the category of IMF component signals that cover the modal frequency points, reorder them in ascending order according to the original IMF subscripts, forming a total of l groups, and reconstruct all the IMF functions into a new load x 2 (t),

[0100]

[0101] l + m = n - n ex-imf , where n ex-imf is the number of invalid IMF components that have been filtered out.

[0102] The fatigue load of the structural member can be composed of the load x 2 (t) that covers the modal points and the load x 1 (t) that does not contain the modal points.

[0103] (e) Perform fatigue damage calculations on the classified signal components respectively;

[0104] Sum and reconstruct the IMF signal components that do not cover the modal points into a new signal x 1 (t), and according to the stress result of the unit load, use the quasi-static method to solve the fatigue damage D1 caused by x 1 (t);

[0105] As Figure 3 shown in the cantilever beam, a load x(t) is applied to the end. Sum and reconstruct the IMF signals that do not cover the modal points into a new signal x 1 (t). First, apply a unit load of 1 N at the end to obtain the stress distribution σ 1 , and then multiply the obtained stress by x 1 (t) to get the stress history σ 1 x 1 (t). Use this stress history combined with the S-N curve for rainflow counting and fatigue calculation. S is the stress amplitude, and N is the corresponding fatigue life, that is, after undergoing N cycles of cyclic stress of magnitude S, the structural member will be damaged.

[0106] Sum up the IMF signal components covering the modal points and reconstruct them into a new signal x 2 (t). According to the modal stress results under the swept-frequency state, use the modal superposition method to solve the fatigue damage D2 caused by x 2 (t);

[0107] Solve for each IMF component signal c 2 (t) contained in x k (t) corresponding to the modal stress σ k of the modal point. After multiplying each IMF component signal by the corresponding modal stress and summing them up, obtain the local stress history Then perform rainflow counting on this stress and conduct fatigue solution.

[0108] (f) to solve for the total fatigue damage.

[0109] Sum up the fatigue damage D1 caused by x 1 (t) and the fatigue damage D2 caused by x 2 (t).

[0110] The overall fatigue damage D = D1 + D2.

[0111] Example:

[0112] For the Figure 3 shown cantilever beam, assume that there are two modal points within 100 Hz for this cantilever beam, and the natural frequencies of its first two orders are 10 Hz and 50 Hz. The effective IMFs after decomposing and screening the actual load x(t) are as Figure 4 shown. According to the frequency spectra decomposed by each IMF, as Figure 5 shown, the IMF2 and IMF3 components cover the modal points 10 Hz and 50 Hz. Since the original signal x(t) in the given example decomposes into 3 IMF signals, IMF1, IMF2, and IMF3, and the signals covering the modal points are IMF2 and IMF3, these two signals can be reconstructed into x 2 (t) according to formula (10), and IMF1 can be reconstructed into the signal x 1 (t) according to formula (9). At this time, use the CAE analysis software to first establish a finite element analysis model of the beam, apply a unit force of 1 N load at the end of the beam, conduct static calculation, and obtain the stress σ 1 of the cantilever beam under this load, and multiply it by the reconstructed load x 1 (t) to obtain the stress history σ 1 x 1(t), rain flow counting and fatigue solution are carried out to obtain the loss D1. Then, using finite element analysis software, a 1N, 0 - 120Hz sweep frequency (the sweep frequency range is determined according to 120% of the maximum frequency of the force load signal) calculation is performed to obtain the modal stresses σ 2 and σ 3 corresponding to 10Hz and 50Hz. Finally, the local stress history σ 2 c 2 (t) + σ 3 c 3 (t) is obtained. Rain flow counting and fatigue solution are carried out on this stress history to obtain the loss D2. Finally, the total damage is solved, and the overall fatigue damage D = D1 + D2.

[0113] In this application, the original signals are classified according to whether they cover the structural modal points. Considering the influence of different frequency bands and structural modes, a hybrid algorithm for fatigue calculation is implemented, which is more accurate than the traditional quasi - static method and more efficient than the modal transient superposition method, with a shorter fatigue simulation calculation time.

[0114] In a second aspect, this application provides a structural component fatigue simulation analysis device based on EMD, as Figure 6 shown, including:

[0115] An acquisition module 610, configured to acquire a load signal;

[0116] The acquisition module 610 acquires the load signal x(t) applied to the structural component. The load signal can be obtained through actual measurement or by virtual iteration with a multi - body dynamics model. When obtaining it by virtual iteration, multi - body simulation software such as Adams can be used to build the structure of the whole or part of the system, simulate the motion state of real objects in the multi - body analysis software, and obtain the load signal through continuous iteration with the target signal.

[0117] As an optional implementation manner, the device further includes:

[0118] A pre - processing module, configured to pre - process the load signal, and the pre - processing includes filtering, de - burring, and drift removal processing on the acquired load signal.

[0119] A decomposition module 620, configured to perform EMD decomposition on the load signal and screen the effective IMF component signals;

[0120] After acquiring the load signal or pre - processing the load signal, the decomposition module 620 then performs EMD decomposition work to obtain each order of IMF component signals c i (t) and the corresponding Fourier spectra;

[0121] The load signal x(t) is reconstructed through EMD decomposition as:

[0122]

[0123] The original load signal can be successively represented as a multi - order IMF (Intrinsic Mode Function) c i (t) and a residual term r n (t) from high frequency to low frequency, and their sum is

[0124] The specific decomposition process is as follows:

[0125] First, find the local maxima and minima of the signal x(t). After obtaining all the extreme points, all the local maxima are interpolated with a cubic spline interpolation function to form the upper envelope of the data. Similarly, all the local minima are interpolated to form the lower envelope of the data. The average value of the upper envelope and the lower envelope is denoted as m 1 (t). Subtract m 1 (t) from the original signal x(t) to get h 1 (t):

[0126] h 1 (t) = x(t) - m 1 (t) (2)

[0127] Then, regard h 1 (t) as the new x(t), and m 11 (t) is the average value of its upper and lower envelope lines, so we have

[0128] h 11 (t) = h 1 (t) - m 11 (t) (3)

[0129] If h 11 (t) still does not meet the requirements, repeat this process k times to get

[0130] h 1k (t) = h 1(k-1) (t) - m 1k (t) (4)

[0131] If the standard deviation SD between h 1k (t) and h 1(k-1) (t) is within a predetermined range, then stop repeating this process. At this time, h 1k (t) is the first - order IMF component signal of the original load signal x(t), denoted as c 1 (t) = h 1k (t), and the formula for the standard deviation SD is:

[0132]

[0133] In the formula, T is the total time length of the load signal x(t);

[0134] Specifically, the predetermined range of the standard deviation SD is generally 0.2 ≥ SD ≥ 0.3, but it is not limited thereto, and the predetermined range can also be adjusted differently according to the actual situation.

[0135] Let r 1 (t) = x(t) - c 1 (t). Regarding r 1 (t) as the new x(t), repeat the process of formulas (2)-(5) to obtain the other IMF component signals of each order, which are respectively denoted as c 2 (t), c 3 (t) …… c i (t), until r i (t) is a monotonic function and no more IMF can be separated. For the decomposed IMF component signals, refer to Figure 4 .

[0136] After decomposition, perform Fourier transform on each of the decomposed IMF components and output the spectrogram, as Figure 5 shown.

[0137] Calculate the correlation coefficient between each order of IMF component signal c i (t) obtained by EMD decomposition and the original signal x(t) respectively, and calculate the energy proportion of each order of IMF component signal c i (t) obtained by EMD decomposition and the original signal x(t) respectively;

[0138] The correlation coefficient ρ i is:

[0139]

[0140] where E(c i (t)) is the energy of each IMF component signal c i (t);

[0141]

[0142] Then, calculate the total energy E of all effective signals:

[0143]

[0144] Calculate the energy proportion, that is, the percentage of the energy E(c i (t)) of a single IMF component in the total energy E, which is E(c i (t)) / E.

[0145] Screen the effective IMF signal components according to the calculated correlation coefficient and energy proportion.

[0146] In a specific embodiment, effective IMF signal components can be screened according to whether the correlation coefficient is greater than 0.8 and whether the energy ratio is greater than 0.1. The 0.8 and 0.1 can also be changed to other values according to actual needs, and the present application does not limit this.

[0147] It should be noted that for the obtained IMF components, the greater the correlation coefficient between it and the original signal, the greater the correlation between the IMF component and the original signal, and vice versa.

[0148] The present application uses the EMD decomposition method to eliminate the false components in the original signal, adaptively filters, suppresses interference signals, and improves the signal-to-noise ratio.

[0149] The simulation module 630 is used to perform finite element simulation on the structural member to obtain the modal results of the structural member, the stress results of the unit load, and the modal stress results under the swept-frequency state.

[0150] The simulation module 630 performs finite element modeling and simulation on the structural member through simulation software. The finite element model is established, and the modal results, the stress results of the unit load, and the modal stress result files under the swept-frequency state are output. It is necessary to separately establish load steps, and the result files are not subordinate to each other. The modal results are output in a readable result file format in a common format such as op2 or rst of finite element analysis software. The modal results include the modal points of the structural member, and the modal points refer to the natural frequencies of each order of the structural member obtained through finite element simulation or actual modal test.

[0151] The unit load refers to unit force load, torque load, and acceleration load. The swept-frequency state refers to performing frequency response analysis at a certain frequency step within a certain bandwidth of frequencies under the excitation of the unit load to obtain the structural stress corresponding to each frequency and output it in a readable structural file format.

[0152] In the swept-frequency state, the determination of the frequency range of the certain bandwidth depends on the maximum frequency in the actual working environment of the structural member. For example, the upper limit of the implementation frequency range can be 20% higher than the maximum frequency, and the lower limit can usually be taken as 1 Hz. In specific implementation, the certain frequency step can be determined according to the principle that the minimum is 1 Hz and the maximum does not exceed 5 Hz.

[0153] The classification module 640 is used to classify the screened effective IMF component signals according to whether they cover the modal points of the structural member.

[0154] Specifically, based on the modal results obtained from the aforementioned finite element simulation and the spectrogram corresponding to each IMF component, according to each order of IMF component signal c i(t) and the peak of the corresponding Fourier spectrum are classified into one category if they coincide with the modal points of the structural member, and the IMF component signals whose corresponding spectra contain the modal points of the structural member are classified into one category, while the IMF signals whose corresponding spectra do not contain the modal points of the structural member are classified into another category.

[0155] For the category of IMF component signals that do not cover the modal frequency points, reorder them in ascending order according to the original IMF subscripts, forming a total of m groups, and reconstruct all the IMF functions in this category into a new load x 1 (t),

[0156]

[0157] For the category of IMF component signals that cover the modal frequency points, reorder them in ascending order according to the original IMF subscripts, forming a total of l groups, and reconstruct all the IMF functions into a new load x 2 (t),

[0158]

[0159] l + m = n - n ex-imf , where n ex-imf is the number of invalid IMF components that have been screened out.

[0160] The fatigue load of the structural member can be composed of the load x 2 (t) that covers the modal points and the load x 1 (t) that does not contain the modal points.

[0161] The first calculation module 650 is used to calculate the fatigue damage of the classified component signals respectively;

[0162] Sum and reconstruct the IMF signal components that do not cover the modal points into a new signal x 1 (t), and according to the stress result of the unit load, use the quasi-static method to solve the fatigue damage D1 caused by x 1 (t);

[0163] As Figure 3 shown in the cantilever beam, a load x(t) is applied to the end. Sum the IMF signals that do not cover the modal points and reconstruct them into a new signal x 1 (t). First, apply a unit load of 1 N at the end to obtain the stress distribution σ 1 , and then multiply the obtained stress by x 1 (t) to get the stress history σ 1 x 1 (t). Use this stress history combined with the S-N curve for rainflow counting and fatigue calculation. S is the stress amplitude, and N is the corresponding fatigue life, that is, after being subjected to N cyclic stress actions of magnitude S, the structural member will be damaged.

[0164] Sum up the IMF signal components covering the modal points and reconstruct them into a new signal x 2 (t). According to the modal stress results under the swept-frequency state, use the modal superposition method to solve the fatigue damage D2 caused by x 2 (t);

[0165] Solve each IMF component signal c 2 contained in x k (t) corresponding to the modal stress σ k at the modal point. After multiplying each IMF component signal by the corresponding modal stress and summing them up, obtain the local stress history Then perform rainflow counting on this stress and conduct fatigue solution.

[0166] The second calculation module 660 is used to solve the total fatigue damage.

[0167] Sum up the fatigue damage D1 caused by x 1 (t) and the fatigue damage D2 caused by x 2 (t).

[0168] The overall fatigue damage D = D1 + D2.

[0169] In a third aspect, an embodiment of the present application further provides a terminal, including: a processor, a memory, and a communication unit;

[0170] The memory stores machine-readable instructions executable by the processor. When the device runs, the processor communicates with the memory through the communication unit;

[0171] Wherein, the processor executes the machine-readable instructions to execute the methods described in the above aspects.

[0172] The memory can be used to store the execution instructions of the processor. The memory can be implemented by any type of volatile or non-volatile storage terminal or a 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 disk, or optical disk. When the execution instructions in the memory are executed by the processor, the device can execute some or all of the steps in the above method embodiments.

[0173] The processor is the control center of the storage terminal, connecting various parts of the entire electronic terminal through various interfaces and circuits. By running or executing software programs and / or modules stored in the memory, and by invoking data stored in the memory, it performs various functions of the electronic terminal and / or processes data. The processor may be composed of an integrated circuit (IC for short), for example, it may be composed of a single packaged IC, or it may be composed of multiple packaged ICs with the same or different functions connected together. For example, the processor may only include a central processing unit (CPU for short). In the embodiments of the present application, the CPU may be a single arithmetic core or may include multiple arithmetic cores.

[0174] A communication unit, configured to establish a communication channel, so that the storage device can communicate with other terminals. It receives user data sent by other terminals or sends user data to other terminals.

[0175] In a fourth aspect, embodiments of the present application further provide a computer storage medium. The computer storage medium may store a program, and when the program is executed, it may include some or all of the steps in the embodiments provided by the present application. The storage medium may be a magnetic disk, an optical disk, a read-only memory (ROM for short) or a random access memory (RAM for short), etc.

[0176] The present application uses the EMD decomposition method to eliminate false components in the original signal, adaptively filters, suppresses interference signals, and improves the signal-to-noise ratio; classifies the original signal according to whether it covers the structural modal points, and considering the influence in different frequency bands and structural modes, a hybrid algorithm for fatigue calculation is realized. Compared with the traditional quasi-static method, the result is more accurate, and compared with the modal transient superposition method, the efficiency is higher and the fatigue simulation calculation time is shorter.

[0177] In the embodiments provided by the present application, it should be understood that the disclosed system and method can be implemented in other ways. For example, the node embodiments described above are only illustrative. For example, the division of the modules is only a logical function division. In actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another device, or some features may be ignored or not executed. Another point is that the displayed or discussed coupling or direct coupling or communication connection between each other may be through some interfaces, and the indirect coupling or communication connection of the device or unit may be in an electrical, mechanical or other form.

[0178] The module described as a separation component may or may not be physically separated. The component shown as a unit may or may not be a physical unit, that is, it may be located in one place or distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0179] In addition, each functional module in the embodiments of the present application can be integrated into a processing unit, or each unit can exist physically alone, or two or more units can be integrated into one unit. The above integrated unit can be implemented in the form of hardware, or in the form of a combination of hardware and software functional units.

[0180] The above is only the specific implementation manner of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present application can easily think of changes or substitutions, which should all be covered within the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

Claims

1. EMD-based fatigue simulation analysis method for structural components, characterized in that, it includes: (a) Obtain load signals; (b) Perform EMD decomposition on the load signals and screen effective IMF component signals; (c) Conduct finite element simulation on the structural components to obtain the modal results of the structural components, the stress results under unit load, and the modal stress results under swept frequency conditions; (d) Classify the screened effective IMF component signals according to whether they cover the modal points of the structural components; (e) Calculate the fatigue damage for the classified component signals respectively; (f) Solve the total fatigue damage; The specific method for calculating the fatigue damage for the classified signal components respectively is: Sum the IMF component signals that do not cover the modal points and reconstruct them into a new signal x 1 (t). According to the stress results of the unit load, use the quasi-static method to solve the fatigue damage D1 caused by x 1 (t); Sum the IMF component signals covering the modal points and reconstruct them into a new signal x 2 (t). According to the modal stress results under the swept-frequency state, use the modal superposition method to solve the fatigue damage D2 caused by x 2 (t); The specific method for solving the total fatigue damage is: Sum the fatigue damage D1 caused by x 1 (t) and the fatigue damage D2 caused by x 2 (t).

2. The EMD-based fatigue simulation analysis method for structural components according to claim 1, characterized in that, after obtaining the load signals, it further includes preprocessing the load signals; the EMD decomposition of the load signals is specifically performed on the preprocessed load signals; the preprocessing includes filtering, de-burring, and drift removal processing on the obtained load signals.

3. The EMD-based fatigue simulation analysis method for structural components according to claim 2, characterized in that, the specific method for performing EMD decomposition on the load signals and screening effective IMF component signals is: Perform EMD decomposition on the acquired load signal to obtain the IMF component signals c i (t) and the corresponding Fourier spectra; The signals c of each order IMF component obtained by EMD decomposition i (t) are respectively calculated for the correlation coefficient with the original signal x(t), and the signals c i (t) of each order IMF component obtained by EMD decomposition are respectively calculated for the energy proportion with the original signal x(t); Screen effective IMF signal components according to the calculated correlation coefficient and energy ratio.

4. EMD-based fatigue simulation analysis device for structural components, characterized in that, it includes: An acquisition module for obtaining load signals; A decomposition module for performing EMD decomposition on the load signals and screening effective IMF component signals; A simulation module for conducting finite element simulation on the structural components to obtain the modal results of the structural components, the stress results under unit load, and the modal stress results under swept frequency conditions; A classification module for classifying the screened effective IMF component signals according to whether they cover the modal points of the structural components; A first calculation module for calculating the fatigue damage for the classified component signals respectively; A second calculation module for solving the total fatigue damage; The first calculation module is specifically used for: Sum the IMF component signals that do not cover the modal points and reconstruct them into a new signal x 1 (t). According to the stress results of the unit load, use the quasi-static method to solve the fatigue damage D1 caused by x 1 (t); Sum the IMF component signals covering the modal points and reconstruct them into a new signal x 2 (t). According to the modal stress results in the swept frequency state, use the modal superposition method to solve the fatigue damage D2 caused by x 2 (t); The second calculation module is specifically used for: Sum the fatigue damage D1 caused by x 1 (t) and the fatigue damage D2 caused by x 2 (t).

5. The EMD-based fatigue simulation analysis device for structural components according to claim 4, characterized in that, the device further includes: A preprocessing module for preprocessing the load signals, and the preprocessing includes filtering, de-burring, and drift removal processing on the obtained load signals.

6. The EMD-based fatigue simulation analysis device for structural components according to claim 5, characterized in that, the decomposition module is specifically used for: Perform EMD decomposition on the acquired load signal to obtain the IMF component signals c i (t) and the corresponding Fourier spectra; The signals c of each order IMF component obtained by EMD decomposition i (t) are respectively calculated for the correlation coefficient with the original signal x(t), and the signals c of each order IMF component obtained by EMD decomposition i (t) are respectively calculated for the energy proportion with the original signal x(t); Screen effective IMF component signals according to the calculated correlation coefficient and energy ratio.

7. A terminal, characterized in that, it includes: A processor, a memory, and a communication unit; The memory stores machine-readable instructions executable by the processor, and when the device runs, the processor communicates with the memory through the communication unit; Wherein, the processor executes the machine-readable instructions to execute the method according to any one of claims 1 to 3.

8. A computer-readable storage medium, characterized in that a computer program is stored on the computer-readable storage medium, and when the computer program is run by a processor, the method according to any one of claims 1 to 3 is executed.

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