CN114791364B - Multi-axial bench vibration durability test method and device - Google Patents

Multi-axial bench vibration durability test method and device Download PDF

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CN114791364B
CN114791364B CN202210715628.4A CN202210715628A CN114791364B CN 114791364 B CN114791364 B CN 114791364B CN 202210715628 A CN202210715628 A CN 202210715628A CN 114791364 B CN114791364 B CN 114791364B
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test
weak
power spectrum
density signal
life
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CN114791364A (en
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丁鼎
韩广宇
张永仁
卢放
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Lantu Automobile Technology Co Ltd
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01M—TESTING STATIC OR DYNAMIC BALANCE OF MACHINES OR STRUCTURES; TESTING OF STRUCTURES OR APPARATUS, NOT OTHERWISE PROVIDED FOR
    • G01M17/00—Testing of vehicles
    • G01M17/007—Wheeled or endless-tracked vehicles
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01M—TESTING STATIC OR DYNAMIC BALANCE OF MACHINES OR STRUCTURES; TESTING OF STRUCTURES OR APPARATUS, NOT OTHERWISE PROVIDED FOR
    • G01M7/00—Vibration-testing of structures; Shock-testing of structures
    • G01M7/02—Vibration-testing by means of a shake table
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
    • Y02T90/00—Enabling technologies or technologies with a potential or indirect contribution to GHG emissions mitigation

Abstract

The invention relates to the technical field of vehicle testing, in particular to a multi-axial bench vibration durability testing method, which comprises the following steps: acquiring a total set of the weak and heavy parts of the service life of the test part in the process of vibrating the test part in the three axial directions under the working condition of the durability test of the whole vehicle road, and acquiring a plurality of one-way weak and heavy parts of the service life of the test part in the process of vibrating the test part in a plurality of one-way directions under the working condition of the durability test of the whole vehicle road; accelerating each unidirectional life weak critical point set in the plurality of unidirectional life weak critical point sets to obtain each unidirectional acceleration power spectrum density signal curve; obtaining a triaxial acceleration power spectrum density signal curve of the test part according to a total set of the weak critical parts of the service life; and performing a vibration endurance test on the test part through each unidirectional acceleration power spectrum density signal curve and the triaxial acceleration power spectrum density signal curve of the test part so as to improve the test precision.

Description

Multi-axial bench vibration durability test method and device
Technical Field
The invention relates to the technical field of vehicle testing, in particular to a method and a device for testing vibration durability of a multi-axial bench.
Background
In the process of the durability test of the whole automobile road, a plurality of parts are excited by loads from all directions of a road surface, and the durability test of the whole automobile road is long in period and expensive in test cost. In order to shorten the development test period and the test cost of the automobile, the whole automobile road endurance test is converted into the bench vibration endurance test, namely, a vibration load excitation signal in the whole automobile road endurance test is converted into a bench vibration load excitation signal, so that the realization of the bench vibration endurance test is important.
At present, the method for realizing the bench vibration endurance test generally accelerates the load of the whole vehicle road in each direction independently and converts the load into the unidirectional bench vibration endurance test load. Therefore, the existing method for realizing the bench vibration endurance test has the problem that when parts of an automobile are subjected to multi-axis vibration, the bench vibration endurance test cannot consider simultaneous vibration in multiple directions, so that the precision of the test result is low.
Disclosure of Invention
The embodiment of the application provides a multi-axial bench vibration endurance test method and device, and solves the technical problem that in the prior art, when parts of an automobile are subjected to multi-axial vibration, the result precision of the bench vibration endurance test is low, the load of a road endurance test of the whole automobile is converted into the acceleration load of the multi-axial bench vibration endurance test, the multi-axial vibration endurance test of the parts of the automobile is implemented, the multi-axial bench vibration endurance test precision is improved, the development verification period is shortened, the test expenditure of the automobile is saved, and the multi-axial bench vibration endurance test method and device have the technical effects of important engineering significance and the like.
In a first aspect, an embodiment of the present invention provides a method for testing vibration durability of a multi-axial table, including:
acquiring a total set of life weak and critical parts of a test part in the process of vibrating the test part in three axial directions under the working condition of a finished automobile road endurance test, and acquiring a plurality of unidirectional life weak and critical part sets in the process of vibrating the test part in a plurality of single directions under the working condition of the finished automobile road endurance test;
accelerating each one-way life weak joint weight part set in the plurality of one-way life weak joint weight part sets to obtain an acceleration power spectrum density signal curve of each one-way life weak joint weight part set;
obtaining a triaxial acceleration power spectrum density signal curve of the test part according to the service life weak critical part total set;
and carrying out a vibration endurance test on the test part through the acceleration power spectrum density signal curve of each unidirectional life weak critical weight part set and the three-axial acceleration power spectrum density signal curve of the test part.
Preferably, the acquiring of the total set of the weak life critical parts of the test part includes:
acquiring triaxial acceleration load signals of the test part in the process of vibrating the test part in the triaxial direction under the working condition of the durability test of the whole vehicle road;
obtaining stress power spectrum signals of a plurality of parts of the test part according to the triaxial acceleration load signal, the finite element model and the stress frequency response functions in a plurality of directions of the test part;
and obtaining the total set of the weak life critical parts according to the stress power spectrum signals of the plurality of parts.
Preferably, the obtaining the total set of the weak life-span critical parts according to the stress power spectrum signals of the multiple parts includes:
obtaining fatigue life damage values of the multiple parts of the test part according to the stress power spectrum signals of the multiple parts, the S-N curve of the test part and the total test duration of the whole vehicle road endurance test;
and obtaining the total set of the weak life critical parts according to the fatigue life damage values of the plurality of parts.
Preferably, the obtaining an acceleration power spectrum density signal curve of each unidirectional life weak critical weight part set by performing accelerated processing on each unidirectional life weak critical weight part set in the plurality of unidirectional life weak critical weight part sets includes:
aiming at each one-way life weak and important part set, obtaining a group of acceleration power spectrum density signal values according to the one-way life weak and important part set; and obtaining the acceleration power spectral density signal curve according to the group of acceleration power spectral density signal values.
Preferably, the obtaining of the triaxial acceleration power spectral density signal curve of the test part according to the total set of the life weak critical weight parts includes:
and carrying out a sparrow search algorithm on the total set of the weak and critical parts of the service life to obtain the three-axial acceleration power spectrum density signal curve.
Preferably, the performing a sparrow search algorithm on the total set of the weak life-span critical parts to obtain the triaxial acceleration power spectral density signal curve includes:
acquiring an initial population of the sparrow search algorithm according to the total set of the weak life and heavy-key parts;
obtaining a finder, a follower and a warner of the initial population according to the initial population;
and respectively updating the positions of the finder, the follower and the alerter until the acceleration power spectrum density signal curve in the three-axis direction is obtained according to the acceleration power spectrum density signal value corresponding to the set updating times when the position updating times of the sparrow searching algorithm reach the set updating times.
Preferably, after obtaining the finder, the follower, and the alerter of the initial population according to the initial population, the method further includes:
and respectively updating the positions of the finder, the follower and the warner until the target function vector of the sparrow search algorithm meets the termination condition of the sparrow search algorithm, and obtaining the three-axial acceleration power spectrum density signal curve according to the acceleration power spectrum density signal value corresponding to the target function vector.
Based on the same inventive concept, in a second aspect, the invention further provides a test apparatus for vibration durability of a multi-axial bench, comprising:
the system comprises an acquisition module, a data processing module and a data processing module, wherein the acquisition module is used for acquiring a total set of life weak critical weight parts of a test part in the process of vibrating the test part simultaneously in a triaxial direction under the working condition of a finished automobile road endurance test, and acquiring a plurality of one-way life weak critical weight part sets in the process of vibrating the test part in a plurality of one-way directions under the working condition of the finished automobile road endurance test;
the unidirectional module is used for accelerating each unidirectional life weak critical weight part set in the plurality of unidirectional life weak critical weight part sets to obtain an acceleration power spectrum density signal curve of each unidirectional life weak critical weight part set;
the triaxial module is used for obtaining triaxial acceleration power spectrum density signal curves of the test part according to the service life weak critical part total set;
and the test module is used for performing vibration endurance test on the test part through the acceleration power spectrum density signal curve of each unidirectional life weak critical weight part set and the three-axial acceleration power spectrum density signal curve of the test part.
Based on the same inventive concept, in a third aspect, the present invention provides a computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the steps of the multi-axial stage vibration endurance test method when executing the program.
Based on the same inventive concept, in a fourth aspect, the present invention provides a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, performs the steps of the multi-axial stage vibration endurance test method.
One or more technical solutions in the embodiments of the present invention have at least the following technical effects or advantages:
in the embodiment of the invention, a total set of the weak critical weight parts of the service life of the test part is obtained in the process of vibrating the test part simultaneously in three axial directions under the working condition of the durability test of the whole vehicle road of the test part, and a plurality of unidirectional weak critical weight part sets are obtained in the process of vibrating the test part in a plurality of unidirectional directions under the working condition of the durability test of the whole vehicle road. And then, performing accelerated processing on each unidirectional life weak critical weight part set in the plurality of unidirectional life weak critical weight part sets to obtain an acceleration power spectrum density signal curve of each unidirectional life weak critical weight part set. And then, obtaining a triaxial acceleration power spectrum density signal curve of the test part according to the total set of the weak critical-weight parts of the service life. And finally, performing a vibration endurance test on the test part through an acceleration power spectrum density signal curve of each unidirectional life weak critical weight part set and an acceleration power spectrum density signal curve of the test part in the three axial directions. Therefore, the whole technical scheme of the embodiment has the following advantages:
1. the method and the device realize the conversion of the load of the durability test of the whole vehicle road into the acceleration load of the vibration durability test of the multi-axial rack, and improve the precision of the vibration durability test of the multi-axial rack.
2. In the process of establishing the acceleration load of the multi-axis rack vibration endurance test of the test part, the actual stress characteristic of the test part and the distribution condition of the weak part of the service life are considered.
3. Through the multi-axial vibration endurance test of the test part, the development verification period of the automobile is really shortened, the test cost is saved, and the method has important engineering significance.
Drawings
Various other advantages and benefits will become apparent to those of ordinary skill in the art upon reading the following detailed description of the preferred embodiments. The drawings are only for purposes of illustrating the preferred embodiments and are not to be construed as limiting the invention. Also, like reference numerals are used to refer to like parts throughout the drawings. In the drawings:
FIG. 1 is a flow chart illustrating the steps of a multi-axial stage vibration endurance testing method in an embodiment of the present invention;
fig. 2 shows a module schematic diagram of a multi-axial bench vibration endurance testing apparatus in an embodiment of the present invention.
Detailed Description
Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.
Example one
The first embodiment of the present invention provides a method for testing vibration durability of a multi-axial table, as shown in fig. 1, including:
s101, acquiring a total set of life weak critical parts of a test part in the process of vibrating the test part in three axial directions under the working condition of a durability test of a whole vehicle road, and acquiring a plurality of unidirectional life weak critical part sets in the process of vibrating the test part in a plurality of single directions under the working condition of the durability test of the whole vehicle road;
s102, performing accelerated processing on each unidirectional life weak joint weight part set in the plurality of unidirectional life weak joint weight part sets to obtain an acceleration power spectrum density signal curve of each unidirectional life weak joint weight part set;
s103, obtaining a triaxial acceleration power spectrum density signal curve of the test part according to the total set of the weak critical-weight parts of the service life;
s104, performing a vibration endurance test on the test part through an acceleration power spectrum density signal curve of each unidirectional life weak critical weight part set and a triaxial acceleration power spectrum density signal curve of the test part.
The following describes in detail specific implementation steps of the multi-axial stage vibration endurance test method provided in this embodiment with reference to fig. 1:
firstly, step S101 is executed, a total set of life weak and heavy parts of the test parts is obtained in the process of vibrating the test parts simultaneously through three axial directions under the working condition of the durability test of the whole vehicle road, and a plurality of one-way life weak and heavy part sets are obtained in the process of vibrating the test parts through a plurality of one-way directions under the working condition of the durability test of the whole vehicle road.
Specifically, the whole vehicle road endurance test working condition of the test part is an endurance test of vibration of the test part in the whole vehicle road endurance test. In the whole vehicle road endurance test working condition of the test part, the mounting point position of the test part can be vibrated in the three axial directions, namely, the test part is vibrated simultaneously in the three axial directions. The mounting position of the test part is a connecting position where the test part is mounted on the whole vehicle and is also a connecting position mounted on the test bed.
The method comprises the following steps of obtaining a total set of weak life critical parts of a test part in the process of vibrating the test part in the three axial directions under the working condition of a durability test of the whole vehicle road, and specifically comprising the following steps: firstly, acquiring triaxial acceleration load signals of the test part in the process of simultaneously vibrating the test part in the triaxial direction under the working condition of the durability test of the whole vehicle road; then obtaining stress power spectrum signals of a plurality of parts of the test part according to the triaxial acceleration load signal, the finite element model and the stress frequency response functions in a plurality of directions of the test part; and then, obtaining the total set of the weak life critical parts according to the stress power spectrum signals of the plurality of parts. The method for obtaining the total set of the weak life critical parts comprises the following steps: obtaining fatigue life damage values of the multiple parts of the test part according to the stress power spectrum signals of the multiple parts, the S-N curve of the test part and the total test duration of the whole vehicle road endurance test; and obtaining the total set of the weak life critical parts according to the fatigue life damage values of the plurality of parts.
The specific implementation process for acquiring the total set of the weak critical parts of the test part in service life is as follows:
1. by arranging the acceleration sensor on the test part, acquiring triaxial acceleration load signals of the mounting point position of the test part of the automobile under 1 cycle running working condition, and solving power spectrums of the acquired triaxial acceleration load signals, corresponding acceleration power spectrum signals can be obtained
Figure 735409DEST_PATH_IMAGE001
（
Figure 607812DEST_PATH_IMAGE002
，
Figure 619630DEST_PATH_IMAGE003
) Wherein:
Figure 443230DEST_PATH_IMAGE004
representing acceleration power in the X directionA spectral signal;
Figure 831486DEST_PATH_IMAGE005
an acceleration power spectrum signal representing the Y direction;
Figure 791351DEST_PATH_IMAGE006
an acceleration power spectrum signal representing the Z direction;
Figure 239650DEST_PATH_IMAGE007
acceleration power spectrum signals representing the X direction and the Y direction;
Figure 550546DEST_PATH_IMAGE008
an acceleration power spectrum signal representing the Y direction and the Z direction,
Figure 476914DEST_PATH_IMAGE009
and represents acceleration power spectrum signals in the Z direction and the X direction. Wherein when
Figure 323909DEST_PATH_IMAGE010
When the temperature of the water is higher than the set temperature,
Figure 677530DEST_PATH_IMAGE011
is a complex signal (including real and imaginary parts); when in use
Figure 475722DEST_PATH_IMAGE012
When the temperature of the water is higher than the set temperature,
Figure 205781DEST_PATH_IMAGE013
is a real signal (containing only the real part).
Figure 140238DEST_PATH_IMAGE014
、
Figure 727078DEST_PATH_IMAGE015
、
Figure 746986DEST_PATH_IMAGE016
、
Figure 516621DEST_PATH_IMAGE017
、
Figure 836744DEST_PATH_IMAGE018
、
Figure 797747DEST_PATH_IMAGE019
The method is to solve the calculation input load signal of the total set of the weak and critical parts of the service life when the test part vibrates in three axial directions simultaneously under the working condition of the durability test of the whole vehicle road. The step is to obtain a calculation input load signal of a total set of the weak critical parts of the service life of the test part.
2. Establishing a finite element model of the test part, and calculating stress frequency response functions of the mounting point position of the test part under unit acceleration excitation in multiple directions by adopting a frequency response algorithm, namely stress frequency response functions in multiple directions. Combining the calculated input load signal of the total set of the weak critical parts of the service life and the stress frequency response functions in multiple directions, solving the stress power spectrum signal of any part of the tested part, wherein the expression formula is as follows:
Figure 304952DEST_PATH_IMAGE020
Figure 376813DEST_PATH_IMAGE021
Figure 551442DEST_PATH_IMAGE022
wherein:
Figure 417767DEST_PATH_IMAGE023
-an acceleration power spectrum signal representing the location of the mounting point of the test part;
lower subscripts m, n — m =1 (n = 1) indicate that the acceleration is in the X direction, m =2 (n = 2) indicates that the acceleration is in the Y direction, and m =3 (n = 3) indicates that the acceleration is in the Z direction;
subscripts a, b — a =1 (b = 1) indicates that the stress is an X-direction positive stress, a =2 (b = 2) indicates that the stress is a Y-direction positive stress, a =3 (b = 3) indicates that the stress is a Z-direction positive stress, a =4 (b = 4) indicates that the stress is an XY in-plane shear stress, a =5 (b = 5) indicates that the stress is a YZ in-plane shear stress, and a =6 (b = 6) indicates that the stress is a ZX in-plane shear stress;
Figure 677847DEST_PATH_IMAGE024
-representing a conjugate operation;
Figure 789285DEST_PATH_IMAGE025
、
Figure 818421DEST_PATH_IMAGE026
a =1 (b = 1), m =1 (n = 1) represents an X-direction positive stress frequency response function at any position j of the test part under the input of the X-direction acceleration power spectrum, a =6 (b = 6), m =3 (n = 3) represents a ZX in-plane shear stress frequency response function at any position j of the test part under the input of the Z-direction acceleration power spectrum, and so on;
Figure 855647DEST_PATH_IMAGE027
the stress power spectrum signal at any position j of the tested part, a =1, b =1 represents the X-direction positive stress power spectrum signal at any position j of the tested part, a =1, b =2 represents the X-direction positive stress and Y-direction positive stress power spectrum signals at any position j of the part, and so on.
Combining stress power spectrum signals at any position j of a test part
Figure 603023DEST_PATH_IMAGE028
And the equivalent stress power spectrum signal of any part j of the tested part can be obtained
Figure 16687DEST_PATH_IMAGE029
The expression formula is as follows:
Figure 900329DEST_PATH_IMAGE030
Figure 374036DEST_PATH_IMAGE031
wherein:
Figure 343129DEST_PATH_IMAGE032
、
Figure 796369DEST_PATH_IMAGE033
-representing the parameters obtained from the corresponding critical plane when the fatigue life damage value is taken to the maximum; subscripts a, b — a =1 (b = 1) indicates that the stress is an X-direction positive stress, a =2 (b = 2) indicates that the stress is a Y-direction positive stress, a =3 (b = 3) indicates that the stress is a Z-direction positive stress, a =4 (b = 4) indicates that the stress is an XY in-plane shear stress, a =5 (b = 5) indicates that the stress is a YZ in-plane shear stress, and a =6 (b = 6) indicates that the stress is a ZX in-plane shear stress;
Figure 800097DEST_PATH_IMAGE034
testing a stress power spectrum signal at any position j of the part;
Figure 179126DEST_PATH_IMAGE035
and the equivalent stress power spectrum signal of any part j of the tested part is represented.
The step is to obtain stress power spectrum signals of a plurality of parts of the tested part.
3. Calculating a stress probability density function of any part of the tested part based on the stress power spectrum signal of any part of the tested part; and then combining a stress probability density function of any part of the tested part, a material S-N curve of the tested part and the total test duration of the whole vehicle road endurance test to obtain a fatigue life damage value of any part of the part, namely the fatigue life damage values of a plurality of parts of the tested part, wherein the expression formula is as follows:
Figure 369936DEST_PATH_IMAGE036
Figure 125402DEST_PATH_IMAGE037
Figure 983637DEST_PATH_IMAGE038
Figure 799146DEST_PATH_IMAGE039
Figure 742832DEST_PATH_IMAGE040
Figure 334612DEST_PATH_IMAGE041
Figure 47353DEST_PATH_IMAGE042
Figure 33764DEST_PATH_IMAGE043
Figure 464745DEST_PATH_IMAGE044
Figure 296435DEST_PATH_IMAGE045
Figure 863682DEST_PATH_IMAGE046
Figure 20994DEST_PATH_IMAGE047
wherein:
Figure 429018DEST_PATH_IMAGE048
-representing a stress probability density function of any part j of the test part;
Figure 64399DEST_PATH_IMAGE049
-the intermediate calculation function is,
Figure 751732DEST_PATH_IMAGE050
from
Figure 79945DEST_PATH_IMAGE051
Calculating to obtain;
Figure 219939DEST_PATH_IMAGE052
、
Figure 721328DEST_PATH_IMAGE053
、
Figure 263168DEST_PATH_IMAGE054
、
Figure 263747DEST_PATH_IMAGE055
、
Figure 891037DEST_PATH_IMAGE056
、
Figure 868221DEST_PATH_IMAGE057
、
Figure 264567DEST_PATH_IMAGE058
、
Figure 934583DEST_PATH_IMAGE059
、
Figure 377065DEST_PATH_IMAGE060
-an intermediate calculation function of
Figure 659404DEST_PATH_IMAGE061
Calculating to obtain;
Figure 175836DEST_PATH_IMAGE062
-a stress value;
Figure 16753DEST_PATH_IMAGE063
、
Figure 353057DEST_PATH_IMAGE064
the constant parameters of the corrected S-N curve of the part material, such as the actual process factors, reliability and the like of the tested part, are considered;
Figure 937622DEST_PATH_IMAGE065
the total test duration of the durability test of the whole vehicle road is long;
Figure 308560DEST_PATH_IMAGE066
and testing the fatigue life damage value of any part j.
If the maximum fatigue damage value of the weak part of the tested part service life is obtained as
Figure 320379DEST_PATH_IMAGE067
Setting a valve coefficient constant
Figure 143978DEST_PATH_IMAGE068
Sequencing the fatigue damage values of the weak parts of the tested parts from large to small in sequence, wherein the fatigue damage value is greater than a numerical value
Figure 830437DEST_PATH_IMAGE069
Front of (2)
Figure 55882DEST_PATH_IMAGE070
The weak part of the life of the test part constitutes the total set of the weak and heavy parts of the life of the test part
Figure 238601DEST_PATH_IMAGE071
The expression formula is as follows, wherein,
Figure 815076DEST_PATH_IMAGE072
the values of (a) are set according to actual requirements:
Figure 741444DEST_PATH_IMAGE073
Figure 821395DEST_PATH_IMAGE074
wherein:
Figure 440596DEST_PATH_IMAGE075
the total set of the weak service life critical parts of the test parts under the whole vehicle road test working condition;
Figure 474673DEST_PATH_IMAGE076
、
Figure 939152DEST_PATH_IMAGE077
、
Figure 139189DEST_PATH_IMAGE078
-test zeroThe fatigue damage values of the weak part of the part life are sequentially ranked from large to small according to the 1 st name, the ith name and the A th name;
Figure 929291DEST_PATH_IMAGE079
the number of the parts with weak service life and heavy weight under the whole vehicle road test working condition is tested.
The principle of the method for acquiring the set of the plurality of unidirectional weak life critical parts is the same as that of the method for acquiring the total set of the weak life critical parts of the test part. Based on the principle of obtaining the specific implementation process of the total set of the life weak critical weight parts of the test parts, the plurality of unidirectional life weak critical weight part sets are obtained in the vibration process of the test parts through a plurality of unidirectional pairs under the working condition of the durability test of the whole vehicle road. The plurality of one-way life weak and heavy part sets comprise an X-direction life weak and heavy part set obtained in the process of vibrating the test parts only in the X direction under the working condition of the whole vehicle road endurance test, a Y-direction life weak and heavy part set obtained in the process of vibrating the test parts only in the Y direction under the working condition of the whole vehicle road endurance test, and a Z-direction life weak and heavy part set obtained in the process of vibrating the test parts only in the Z direction under the working condition of the whole vehicle road endurance test.
Next, step S102 is executed to obtain an acceleration power spectrum density signal curve of each unidirectional life weak critical point set by performing acceleration processing on each unidirectional life weak critical point set in the plurality of unidirectional life weak critical point sets.
Specifically, for each unidirectional weak life-span important part set, a group of acceleration power spectrum density signal values are obtained according to the unidirectional weak life-span important part set; and obtaining the acceleration power spectral density signal curve according to the group of acceleration power spectral density signal values.
The specific implementation process for obtaining the acceleration power spectral density signal curve of each unidirectional life weak critical section set is as follows:
and respectively solving an acceleration power spectrum density signal curve of the bench vibration endurance test in a single direction by adopting a minimum gradient algorithm. Taking the X-direction weak critical point set as an example, the specific method for solving the acceleration power spectrum density signal curve of the X-direction weak critical point set comprises the following steps:
1. the same calculation principle in the step S101 is adopted to respectively calculate and obtain the weak and heavy part set of the service life of the test part in the single vibration direction (X direction) of the whole vehicle road test working condition
Figure 949199DEST_PATH_IMAGE080
The expression formula is as follows:
Figure 482949DEST_PATH_IMAGE081
，
wherein:
Figure 537493DEST_PATH_IMAGE082
representing a life weak critical part set of the test part vibrating in the X direction of the whole vehicle road test working condition;
Figure 232916DEST_PATH_IMAGE083
respectively representing the damage values of the tested parts in a descending order, namely a 1 st damage value, a jth damage value and a Kth damage value;
k is the number of the weak life critical parts of the test part in the X direction under the whole vehicle road test working condition.
2. An acceleration power spectral density signal curve of a bench vibration endurance test is defined, the curve is a polygonal line signal under a double logarithmic coordinate system, and the polygonal line is assumed to be defined by four points, and the expression formula is as follows:
Figure 507165DEST_PATH_IMAGE084
wherein:
Figure 579026DEST_PATH_IMAGE085
、
Figure 488076DEST_PATH_IMAGE086
、
Figure 619980DEST_PATH_IMAGE087
、
Figure 614481DEST_PATH_IMAGE088
respectively representing the acceleration power spectrum density signal values in the X direction, wherein the values are parameters which need to be solved subsequently;
Figure 490033DEST_PATH_IMAGE085
、
Figure 519169DEST_PATH_IMAGE086
、
Figure 556395DEST_PATH_IMAGE087
、
Figure 601974DEST_PATH_IMAGE088
a set of acceleration power spectral density signal values;
Figure 15638DEST_PATH_IMAGE089
、
Figure 899280DEST_PATH_IMAGE090
、
Figure 107408DEST_PATH_IMAGE091
、
Figure 76501DEST_PATH_IMAGE092
-representing the frequency values corresponding to the acceleration power spectral density signal values, respectively, as constants, e.g.
Figure 293855DEST_PATH_IMAGE089
Is composed of
Figure 32004DEST_PATH_IMAGE093
A corresponding frequency value;
Figure 178077DEST_PATH_IMAGE089
and
Figure 634466DEST_PATH_IMAGE092
can be set based on the minimum value and the maximum value of the frequency of the collected acceleration power spectrum signal,
Figure 389933DEST_PATH_IMAGE090
and
Figure 982588DEST_PATH_IMAGE091
the setting may be based on the frequency corresponding to the peak of the stress frequency response function under unit acceleration excitation.
3. Establishing an acceleration power spectrum density signal curve solving formula generated after acceleration of a unidirectional bench vibration endurance test, wherein the expression formula is as follows:
Figure 63676DEST_PATH_IMAGE094
Figure 476203DEST_PATH_IMAGE095
Figure 35361DEST_PATH_IMAGE096
Figure 748102DEST_PATH_IMAGE097
Figure 247696DEST_PATH_IMAGE098
Figure 678677DEST_PATH_IMAGE099
Figure 775946DEST_PATH_IMAGE100
wherein:
Figure 139931DEST_PATH_IMAGE101
-an iterative objective function of a gradient descent algorithm;
Figure 297243DEST_PATH_IMAGE102
-representing the minimum and maximum values of the acceleration power spectral density signal values, respectively;
Figure 684362DEST_PATH_IMAGE103
the total test duration of the durability test of the whole vehicle road is long;
Figure 585322DEST_PATH_IMAGE104
-the total duration of the bench test of the accelerated signals is an initial definition constant;
Figure 774120DEST_PATH_IMAGE105
-an acceleration factor.
Figure 102333DEST_PATH_IMAGE106
Respectively indicating the total test duration of the test part in the X direction of the test working condition of the whole vehicle road
Figure 39065DEST_PATH_IMAGE107
The fatigue damage values of the weak part of the life are sequenced from large to small, the 1 st value damageA value numerical value, a jth damage value numerical value and a Kth damage value numerical value;
Figure 478137DEST_PATH_IMAGE108
respectively representing the total duration of the bench test under the acceleration condition of the vibration endurance test of the test part in the X direction
Figure 19977DEST_PATH_IMAGE109
The fatigue damage values of the weak part of the service life are sequentially ranked from large to small, namely a 1 st damage value numerical value, a jth damage value numerical value and a Kth damage value numerical value; calculating by adopting the same calculation principle in the step S101;
Figure 519091DEST_PATH_IMAGE110
-a weight coefficient constant.
4. An acceleration power spectrum density signal curve of the bench vibration endurance test is solved in a single direction by adopting a gradient descent iterative algorithm, and the expression formula is as follows:
gradient descent iterative algorithm termination condition:
Figure 146382DEST_PATH_IMAGE111
setting up
Figure 890609DEST_PATH_IMAGE112
、
Figure 286955DEST_PATH_IMAGE113
、
Figure 956971DEST_PATH_IMAGE114
、
Figure 805978DEST_PATH_IMAGE115
The iteration initial value of (2):
Figure 852432DEST_PATH_IMAGE116
、
Figure 368864DEST_PATH_IMAGE117
、
Figure 209781DEST_PATH_IMAGE118
、
Figure 546084DEST_PATH_IMAGE119
gradient descent iterative algorithm:
Figure 632114DEST_PATH_IMAGE120
Figure 799790DEST_PATH_IMAGE121
Figure 811609DEST_PATH_IMAGE122
Figure 900787DEST_PATH_IMAGE123
wherein:
Figure 757885DEST_PATH_IMAGE124
-the gradient descent iteration algorithm terminates the iteration error parameter;
Figure 248909DEST_PATH_IMAGE125
、
Figure 431629DEST_PATH_IMAGE126
、
Figure 243989DEST_PATH_IMAGE127
——
Figure 170357DEST_PATH_IMAGE128
the t +1 th iteration value, the t th iteration value and the iteration initial value;
Figure 515888DEST_PATH_IMAGE129
、
Figure 869509DEST_PATH_IMAGE130
、
Figure 667700DEST_PATH_IMAGE131
——
Figure 397759DEST_PATH_IMAGE132
the t +1 th iteration value, the t th iteration value and the iteration initial value;
Figure 394534DEST_PATH_IMAGE133
、
Figure 420521DEST_PATH_IMAGE134
、
Figure 706009DEST_PATH_IMAGE135
——
Figure 239758DEST_PATH_IMAGE136
the t +1 th iteration value, the t th iteration value and the iteration initial value;
Figure 294302DEST_PATH_IMAGE137
、
Figure 989725DEST_PATH_IMAGE138
、
Figure 496930DEST_PATH_IMAGE139
——
Figure 568791DEST_PATH_IMAGE140
(ii) the t +1 th iterationAn algebraic value, a t-th iteration numerical value and an iteration initial numerical value;
Figure 776044DEST_PATH_IMAGE141
-the number of iterations;
Figure 907948DEST_PATH_IMAGE142
-an iteration step size parameter.
And after the gradient descent iterative algorithm is subjected to a termination condition, outputting an acceleration power spectrum density signal curve in the X direction generated after an unidirectional (X-direction) rack vibration endurance test is accelerated, namely outputting an acceleration power spectrum density signal curve of the X-direction weak life weight-related part set.
Then, step S103 is executed to obtain a triaxial acceleration power spectral density signal curve of the test part according to the total set of the weak critical parts of life.
Specifically, a sparrow search algorithm is performed on the total set of the weak and critical parts of the service life to obtain the three-axial acceleration power spectral density signal curve, which specifically comprises the following steps: acquiring an initial population of the sparrow search algorithm according to the total set of the weak life and heavy-key parts; obtaining a finder, a follower and a warner of the initial population according to the initial population; and respectively updating the positions of the finder, the follower and the warner.
And respectively updating the positions of the finder, the follower and the alerter until the acceleration power spectrum density signal curve in the three-axis direction is obtained according to the acceleration power spectrum density signal value corresponding to the set updating times when the position updating times of the sparrow searching algorithm reach the set updating times.
Or respectively updating the positions of the finder, the follower and the alerter until the target function vector of the sparrow search algorithm meets the termination condition of the sparrow search algorithm, and obtaining the triaxial acceleration power spectrum density signal curve according to the acceleration power spectrum density signal value corresponding to the target function vector.
The specific implementation process for obtaining the triaxial acceleration power spectral density signal curve of the test part is as follows: the method is characterized in that a sparrow search algorithm is adopted to solve an acceleration power spectrum curve after acceleration is carried out on a rack vibration endurance test in which three axial directions vibrate simultaneously, namely an acceleration power spectrum density signal curve in the three axial directions, and the method specifically comprises the following steps:
1. defining an acceleration power spectrum density signal curve of a three-axial vibration endurance test of a bench: when the test part is in triaxial and is carried out vibration endurance test simultaneously, 6 inputs are needed in total to rack signal input, namely: acceleration power spectrum signal in X direction
Figure 902449DEST_PATH_IMAGE143
Acceleration power spectrum signal in Y direction
Figure 778001DEST_PATH_IMAGE144
Acceleration power spectrum signal in Z direction
Figure 541558DEST_PATH_IMAGE145
Acceleration power spectrum signal in X direction and Y direction
Figure 844363DEST_PATH_IMAGE146
Acceleration power spectrum signal in Y direction and Z direction
Figure 326160DEST_PATH_IMAGE147
Acceleration power spectrum signal in Z direction and X direction
Figure 474245DEST_PATH_IMAGE148
. Wherein the content of the first and second substances,
Figure 859352DEST_PATH_IMAGE149
、
Figure 333058DEST_PATH_IMAGE150
、
Figure 302152DEST_PATH_IMAGE151
as calculated in the step S102, it is,
Figure 316244DEST_PATH_IMAGE152
、
Figure 54393DEST_PATH_IMAGE153
、
Figure 699001DEST_PATH_IMAGE154
calculated by a sparrow search algorithm. When in use
Figure 889811DEST_PATH_IMAGE155
When the utility model is used, the water is discharged,
Figure 135023DEST_PATH_IMAGE156
is a complex signal (containing real and imaginary parts). Defining:
Figure 993258DEST_PATH_IMAGE157
as acceleration power spectrum signals
Figure 543188DEST_PATH_IMAGE158
The real part of (a) is,
Figure 486873DEST_PATH_IMAGE159
as acceleration power spectrum signals
Figure 842768DEST_PATH_IMAGE160
The real part of (a) is,
Figure 289930DEST_PATH_IMAGE161
as acceleration power spectrum signals
Figure 276340DEST_PATH_IMAGE162
The real part of (a);
Figure 739945DEST_PATH_IMAGE163
as acceleration power spectrum signals
Figure 837214DEST_PATH_IMAGE164
The imaginary part of (a) is,
Figure 404462DEST_PATH_IMAGE165
as acceleration power spectrum signals
Figure 561773DEST_PATH_IMAGE166
The imaginary part of (a) is,
Figure 214472DEST_PATH_IMAGE167
as acceleration power spectrum signals
Figure 912169DEST_PATH_IMAGE168
The imaginary part of (c).
According to the calculation principle of the step S102,
Figure 835388DEST_PATH_IMAGE169
a curve is generally defined as a polyline signal in a log-log coordinate system, and assuming that the polyline is defined by four points, the expression formula is as follows:
Figure 960339DEST_PATH_IMAGE170
Figure 100333DEST_PATH_IMAGE171
Figure 273826DEST_PATH_IMAGE172
wherein:
Figure 815665DEST_PATH_IMAGE173
、
Figure 111518DEST_PATH_IMAGE174
、
Figure 240273DEST_PATH_IMAGE175
、
Figure 217456DEST_PATH_IMAGE176
、
Figure 613802DEST_PATH_IMAGE177
、
Figure 80556DEST_PATH_IMAGE178
、
Figure 195142DEST_PATH_IMAGE179
、
Figure 772754DEST_PATH_IMAGE180
、
Figure 525072DEST_PATH_IMAGE181
、
Figure 100410DEST_PATH_IMAGE182
、
Figure 702292DEST_PATH_IMAGE183
、
Figure 286857DEST_PATH_IMAGE184
respectively representing real part numerical values of the acceleration power spectrum density signals, wherein the real part numerical values are parameters which need to be solved subsequently;
Figure 657796DEST_PATH_IMAGE185
、
Figure 466352DEST_PATH_IMAGE186
、
Figure 555531DEST_PATH_IMAGE187
、
Figure 179672DEST_PATH_IMAGE188
the real part values of the acceleration power spectrum density signals in the X direction and the Y direction,
Figure 936276DEST_PATH_IMAGE189
、
Figure 384575DEST_PATH_IMAGE190
、
Figure 429891DEST_PATH_IMAGE191
、
Figure 356259DEST_PATH_IMAGE192
the real part values of the acceleration power spectrum density signal in the Y direction and the Z direction,
Figure 701789DEST_PATH_IMAGE193
、
Figure 55410DEST_PATH_IMAGE194
、
Figure 151805DEST_PATH_IMAGE195
、
Figure 881863DEST_PATH_IMAGE196
the real part numerical value of the acceleration power spectrum density signal in the Z direction and the X direction;
Figure 816321DEST_PATH_IMAGE197
、
Figure 137581DEST_PATH_IMAGE198
、
Figure 423069DEST_PATH_IMAGE199
、
Figure 691239DEST_PATH_IMAGE200
respectively representing frequency values corresponding to real part values of the acceleration power spectrum density signal, wherein the frequency values are constants; value of frequency
Figure 981668DEST_PATH_IMAGE197
And
Figure 942671DEST_PATH_IMAGE200
setting is carried out based on the minimum value and the maximum value of the frequency of the acquired acceleration power spectrum signal,
Figure 715455DEST_PATH_IMAGE198
and
Figure 318475DEST_PATH_IMAGE199
the frequency setting is based on the frequency corresponding to the peak of the stress frequency response function under the unit acceleration excitation.
According to the calculation principle of the step S102,
Figure 493104DEST_PATH_IMAGE201
a curve is generally defined as a polyline signal in a log-log coordinate system, and assuming that the polyline is defined by four points, the expression formula is as follows:
Figure 93850DEST_PATH_IMAGE202
Figure 663851DEST_PATH_IMAGE203
Figure 8245DEST_PATH_IMAGE204
wherein:
Figure 834118DEST_PATH_IMAGE205
、
Figure 136924DEST_PATH_IMAGE206
、
Figure 149879DEST_PATH_IMAGE207
、
Figure 563543DEST_PATH_IMAGE208
、
Figure 683071DEST_PATH_IMAGE209
、
Figure 953515DEST_PATH_IMAGE210
、
Figure 657029DEST_PATH_IMAGE211
、
Figure 608804DEST_PATH_IMAGE212
、
Figure 143691DEST_PATH_IMAGE213
、
Figure 86501DEST_PATH_IMAGE214
、
Figure 277311DEST_PATH_IMAGE215
、
Figure 829515DEST_PATH_IMAGE216
respectively representing imaginary part numerical values of the acceleration power spectrum density signals, wherein the imaginary part numerical values are parameters which need to be solved subsequently;
Figure 422171DEST_PATH_IMAGE205
、
Figure 972101DEST_PATH_IMAGE206
、
Figure 712524DEST_PATH_IMAGE207
、
Figure 507567DEST_PATH_IMAGE208
the imaginary part values of the acceleration power spectrum density signals in the X direction and the Y direction,
Figure 17045DEST_PATH_IMAGE209
、
Figure 472298DEST_PATH_IMAGE210
、
Figure 700017DEST_PATH_IMAGE211
、
Figure 531706DEST_PATH_IMAGE212
the imaginary part values of the acceleration power spectrum density signals in the Y direction and the Z direction,
Figure 662736DEST_PATH_IMAGE213
、
Figure 288889DEST_PATH_IMAGE214
、
Figure 207166DEST_PATH_IMAGE215
、
Figure 904864DEST_PATH_IMAGE216
the imaginary part numerical value of the acceleration power spectrum density signal in the Z direction and the X direction;
Figure 61039DEST_PATH_IMAGE217
、
Figure 389252DEST_PATH_IMAGE218
、
Figure 827449DEST_PATH_IMAGE219
、
Figure 266521DEST_PATH_IMAGE220
-frequency values corresponding to imaginary part values of the acceleration power spectral density signal are respectively represented as constants; value of frequency
Figure 605098DEST_PATH_IMAGE217
And
Figure 104212DEST_PATH_IMAGE220
setting is carried out based on the minimum value and the maximum value of the frequency of the collected acceleration power spectrum signal,
Figure 465924DEST_PATH_IMAGE218
and
Figure 505424DEST_PATH_IMAGE219
the frequency setting is based on the frequency corresponding to the peak of the stress frequency response function under the unit acceleration excitation.
2. Solving by adopting sparrow searching algorithm
Figure 403235DEST_PATH_IMAGE221
、
Figure 807671DEST_PATH_IMAGE222
、
Figure 718996DEST_PATH_IMAGE223
、
Figure 499870DEST_PATH_IMAGE224
、
Figure 750723DEST_PATH_IMAGE225
、
Figure 388377DEST_PATH_IMAGE226
、
Figure 491725DEST_PATH_IMAGE227
、
Figure 341869DEST_PATH_IMAGE228
、
Figure 712808DEST_PATH_IMAGE229
、
Figure 521364DEST_PATH_IMAGE230
、
Figure 79384DEST_PATH_IMAGE231
、
Figure 467640DEST_PATH_IMAGE232
、
Figure 979569DEST_PATH_IMAGE233
、
Figure 693447DEST_PATH_IMAGE234
、
Figure 269922DEST_PATH_IMAGE235
、
Figure 727448DEST_PATH_IMAGE236
、
Figure 541820DEST_PATH_IMAGE237
、
Figure 459223DEST_PATH_IMAGE238
、
Figure 991835DEST_PATH_IMAGE239
、
Figure 721894DEST_PATH_IMAGE240
、
Figure 453089DEST_PATH_IMAGE241
、
Figure 977612DEST_PATH_IMAGE242
、
Figure 561302DEST_PATH_IMAGE243
、
Figure 829472DEST_PATH_IMAGE244
. Defining an initial population
Figure 618437DEST_PATH_IMAGE245
In an amount of
Figure 376177DEST_PATH_IMAGE246
The maximum number of iterations is
Figure 617803DEST_PATH_IMAGE247
The number of discoverers is
Figure 486402DEST_PATH_IMAGE248
The number of followers is
Figure 896917DEST_PATH_IMAGE249
Then define the number of sparrows as early warning
Figure 763241DEST_PATH_IMAGE250
The early warning value is
Figure 820059DEST_PATH_IMAGE251
Initial population
Figure 164453DEST_PATH_IMAGE252
Any one sparrow position in (2)
Figure 193589DEST_PATH_IMAGE253
The expression of (a) is as follows:
Figure 27552DEST_PATH_IMAGE254
Figure 10814DEST_PATH_IMAGE255
Figure 221216DEST_PATH_IMAGE256
Figure 839279DEST_PATH_IMAGE257
Figure 109723DEST_PATH_IMAGE258
Figure 813237DEST_PATH_IMAGE259
Figure 765013DEST_PATH_IMAGE260
Figure 66943DEST_PATH_IMAGE261
Figure 180393DEST_PATH_IMAGE262
Figure 433519DEST_PATH_IMAGE263
Figure 188986DEST_PATH_IMAGE264
Figure 781641DEST_PATH_IMAGE265
Figure 895353DEST_PATH_IMAGE266
Figure 573459DEST_PATH_IMAGE267
Figure 663775DEST_PATH_IMAGE268
Figure 110937DEST_PATH_IMAGE269
Figure 894085DEST_PATH_IMAGE270
Figure 59487DEST_PATH_IMAGE271
Figure 658221DEST_PATH_IMAGE272
Figure 22206DEST_PATH_IMAGE273
Figure 913939DEST_PATH_IMAGE274
Figure 628954DEST_PATH_IMAGE275
Figure 998755DEST_PATH_IMAGE276
Figure 996010DEST_PATH_IMAGE277
Figure 58644DEST_PATH_IMAGE278
Figure 198638DEST_PATH_IMAGE279
Figure 700027DEST_PATH_IMAGE280
Figure 773025DEST_PATH_IMAGE281
wherein:
Figure 272139DEST_PATH_IMAGE282
-to representAn initial population;
Figure 135315DEST_PATH_IMAGE283
-a transpose operation of the representation matrix;
Figure 909236DEST_PATH_IMAGE284
-representing the position of any sparrow r in the population,
Figure 305582DEST_PATH_IMAGE285
；
Figure 772336DEST_PATH_IMAGE286
-a real component numerical vector representing the position of any sparrow r in the population;
Figure 621343DEST_PATH_IMAGE287
-a vector of imaginary numerical values representing the position of any one of the sparrows r in the population;
Figure 700420DEST_PATH_IMAGE288
、
Figure 951273DEST_PATH_IMAGE289
、
Figure 588927DEST_PATH_IMAGE290
、
Figure 925231DEST_PATH_IMAGE291
、
Figure 306534DEST_PATH_IMAGE292
、
Figure 411893DEST_PATH_IMAGE293
、
Figure 721914DEST_PATH_IMAGE294
、
Figure 279934DEST_PATH_IMAGE295
、
Figure 464928DEST_PATH_IMAGE296
、
Figure 424793DEST_PATH_IMAGE297
、
Figure 607513DEST_PATH_IMAGE298
、
Figure 216611DEST_PATH_IMAGE299
respectively representing the real part numerical component of the acceleration power spectrum density signal corresponding to any sparrow r position in the population;
Figure 939717DEST_PATH_IMAGE300
、
Figure 19668DEST_PATH_IMAGE301
、
Figure 373289DEST_PATH_IMAGE302
、
Figure 437060DEST_PATH_IMAGE303
、
Figure 167119DEST_PATH_IMAGE304
、
Figure 665358DEST_PATH_IMAGE305
、
Figure 455460DEST_PATH_IMAGE306
、
Figure 209789DEST_PATH_IMAGE307
、
Figure 540276DEST_PATH_IMAGE308
、
Figure 329241DEST_PATH_IMAGE309
、
Figure 322867DEST_PATH_IMAGE310
、
Figure 830072DEST_PATH_IMAGE311
-respectively representing the imaginary numerical components of the acceleration power spectral density signal corresponding to any one of the sparrow r positions in the population;
Figure 698670DEST_PATH_IMAGE312
、
Figure 342141DEST_PATH_IMAGE313
、
Figure 270783DEST_PATH_IMAGE314
、
Figure 999705DEST_PATH_IMAGE315
、
Figure 439039DEST_PATH_IMAGE316
、
Figure 999333DEST_PATH_IMAGE317
、
Figure 302138DEST_PATH_IMAGE318
、
Figure 783935DEST_PATH_IMAGE319
、
Figure 463178DEST_PATH_IMAGE320
、
Figure 570987DEST_PATH_IMAGE321
、
Figure 44694DEST_PATH_IMAGE322
、
Figure 13787DEST_PATH_IMAGE323
、
Figure 231142DEST_PATH_IMAGE324
、
Figure 969291DEST_PATH_IMAGE325
、
Figure 817161DEST_PATH_IMAGE326
、
Figure 70288DEST_PATH_IMAGE327
、
Figure 825754DEST_PATH_IMAGE328
、
Figure 185454DEST_PATH_IMAGE329
、
Figure 963DEST_PATH_IMAGE330
、
Figure 679069DEST_PATH_IMAGE331
、
Figure 238226DEST_PATH_IMAGE332
、
Figure 950967DEST_PATH_IMAGE333
、
Figure 671799DEST_PATH_IMAGE334
、
Figure 102780DEST_PATH_IMAGE335
-representing the minimum and maximum values, respectively, of the real component values of the acceleration power spectral density signal in the population.
Figure 465628DEST_PATH_IMAGE336
、
Figure 268761DEST_PATH_IMAGE337
、
Figure 691652DEST_PATH_IMAGE338
、
Figure 344351DEST_PATH_IMAGE339
、
Figure 245311DEST_PATH_IMAGE340
、
Figure 932644DEST_PATH_IMAGE341
、
Figure 464119DEST_PATH_IMAGE342
、
Figure 604114DEST_PATH_IMAGE343
、
Figure 839923DEST_PATH_IMAGE344
、
Figure 883228DEST_PATH_IMAGE345
、
Figure 382342DEST_PATH_IMAGE346
、
Figure 9632DEST_PATH_IMAGE347
、
Figure 252395DEST_PATH_IMAGE348
、
Figure 914320DEST_PATH_IMAGE349
、
Figure 787598DEST_PATH_IMAGE350
、
Figure 636606DEST_PATH_IMAGE351
、
Figure 683059DEST_PATH_IMAGE352
、
Figure 199491DEST_PATH_IMAGE353
、
Figure 541873DEST_PATH_IMAGE354
、
Figure 878177DEST_PATH_IMAGE355
、
Figure 728321DEST_PATH_IMAGE356
、
Figure 99259DEST_PATH_IMAGE357
、
Figure 111078DEST_PATH_IMAGE358
、
Figure 200256DEST_PATH_IMAGE359
-representing the minimum and maximum values, respectively, of the imaginary numerical component of the acceleration power spectral density signal in the population.
Initial population
Figure 322933DEST_PATH_IMAGE360
Any one sparrow position in (2)
Figure 813957DEST_PATH_IMAGE361
The expression formula of the objective function is as follows:
Figure 199939DEST_PATH_IMAGE362
Figure 12300DEST_PATH_IMAGE363
Figure 938668DEST_PATH_IMAGE364
and (3) iteration termination condition:
Figure 284198DEST_PATH_IMAGE365
Figure 637819DEST_PATH_IMAGE366
wherein:
Figure 436011DEST_PATH_IMAGE367
-any sparrow position
Figure 431649DEST_PATH_IMAGE368
The target function vector of (2);
Figure 631686DEST_PATH_IMAGE369
、
Figure 156208DEST_PATH_IMAGE370
、
Figure 943161DEST_PATH_IMAGE371
-objective function vector
Figure 476910DEST_PATH_IMAGE372
Each row of values;
Figure 531454DEST_PATH_IMAGE373
-iterating the error target vector;
Figure 226878DEST_PATH_IMAGE374
、
Figure 202924DEST_PATH_IMAGE375
、
Figure 274785DEST_PATH_IMAGE376
-iterative error target vector
Figure 183835DEST_PATH_IMAGE377
Each row of values;
Figure 315739DEST_PATH_IMAGE378
the number of the parts with weak service life and heavy weight under the whole vehicle road test working condition is tested;
Figure 310240DEST_PATH_IMAGE379
the total test duration of the durability test of the whole vehicle road is long;
Figure 952836DEST_PATH_IMAGE380
-the total duration of the bench test of the accelerated signals is an initial definition constant;
Figure 716393DEST_PATH_IMAGE381
-an acceleration factor;
Figure 19198DEST_PATH_IMAGE382
-the total test duration of the test part under the whole vehicle road test working condition
Figure 500995DEST_PATH_IMAGE383
The ith damage value of the fatigue damage values of the weak part of the life is sequentially ranked from large to small, and the value is calculated in the step S101;
Figure 914659DEST_PATH_IMAGE384
acceleration of the test part in a multiaxial bench vibration endurance testTotal duration of bench test under working condition
Figure 798301DEST_PATH_IMAGE385
The ith damage value of the fatigue damage value of the weak part of the life is obtained by calculation by the algorithm of the step S101.
3. For an initial population
Figure 272008DEST_PATH_IMAGE386
Solving non-dominated solution sorting to obtain a total of M levels of non-dominated solution sets, and performing congestion degree calculation on the non-dominated solution sets of each level to finally finish the initial population
Figure 363522DEST_PATH_IMAGE386
The solution quality is sorted from good to bad. Defining an initial population
Figure 377615DEST_PATH_IMAGE386
In total amount of
Figure 115764DEST_PATH_IMAGE387
Before the ordering of the solution quality from good to bad
Figure 963634DEST_PATH_IMAGE388
Named finder, the solution quality is ranked from good to bad
Figure 216761DEST_PATH_IMAGE389
It is the following one.
By nondominant sorting algorithm pair size of
Figure 175489DEST_PATH_IMAGE390
The population is layered, and the specific steps are as follows:
(1) Is provided with
Figure 33724DEST_PATH_IMAGE391
；
(2) For all of
Figure 85119DEST_PATH_IMAGE392
And is
Figure 28804DEST_PATH_IMAGE393
Comparing individuals
Figure 587961DEST_PATH_IMAGE394
And individuals
Figure 300703DEST_PATH_IMAGE395
Dominant and non-dominant relationships between;
(3) If none exists
Figure 552692DEST_PATH_IMAGE395
Corresponding objective function
Figure 718094DEST_PATH_IMAGE396
Each row number of less than the objective function
Figure 815363DEST_PATH_IMAGE397
Then mark
Figure 648190DEST_PATH_IMAGE398
Is a non-dominant individual;
(4) Order to
Figure 306967DEST_PATH_IMAGE399
And (3) turning to the step (2) until all non-dominant individuals are found.
The set of non-dominant individuals obtained by the above steps is the first level non-dominant layer of the population, and then, ignoring the marked non-dominant individuals (i.e., the individuals are not subjected to the next round of comparison), and following the above steps (1) - (4), the second level non-dominant layer is obtained. And so on until the whole population is layered, and the sequence is the sequence of the solution quality from good to bad.
And sorting the dominant layers of the same level according to a congestion degree calculation formula, wherein the method comprises the following specific steps:
(1) Meter for measuringComputing each sparrow position vector of the same domination level
Figure 959665DEST_PATH_IMAGE400
Target function vector of
Figure 63887DEST_PATH_IMAGE401
Euclidean distance from 0 point
Figure 751221DEST_PATH_IMAGE402
The expression formula is as follows:
Figure 79434DEST_PATH_IMAGE403
wherein:
Figure 219428DEST_PATH_IMAGE404
-sparrow position vector
Figure 658500DEST_PATH_IMAGE400
Target function vector of
Figure 200339DEST_PATH_IMAGE405
Euclidean distance from point 0;
Figure 699454DEST_PATH_IMAGE406
-each line value of the objective function vector;
Figure 828209DEST_PATH_IMAGE407
-the number of rows of the objective function vector.
(2) Reordering is carried out in sequence from small to small according to the Euclidean distance value obtained by calculation, and aiming at any sparrow position vector
Figure 336551DEST_PATH_IMAGE408
Degree of congestion of
Figure 732897DEST_PATH_IMAGE409
The expression formula is as follows:
Figure 402913DEST_PATH_IMAGE410
wherein:
Figure 517500DEST_PATH_IMAGE411
sparrow position vector
Figure 563953DEST_PATH_IMAGE412
A congestion degree value of;
Figure 549226DEST_PATH_IMAGE413
、
Figure 390144DEST_PATH_IMAGE414
-a vector of an objective function
Figure 290229DEST_PATH_IMAGE415
、
Figure 609215DEST_PATH_IMAGE416
The k line value of (1);
Figure 980153DEST_PATH_IMAGE417
-the number of rows of the objective function vector.
Any sparrow position vector obtained by calculation
Figure 788709DEST_PATH_IMAGE418
Degree of congestion of
Figure 877888DEST_PATH_IMAGE419
And sequencing the numerical values from large to small in sequence, namely finishing the sequencing of the population individuals in the same level, wherein the sequencing is the sequencing of the solution quality from excellent to poor.
4. The position updating is carried out aiming at the discoverer in the population, and the expression formula is as follows:
Figure 734985DEST_PATH_IMAGE420
Figure 461895DEST_PATH_IMAGE421
wherein:
Figure 706932DEST_PATH_IMAGE422
-a first step
Figure 17827DEST_PATH_IMAGE422
A finder;
Figure 944195DEST_PATH_IMAGE423
-finder sparrow position vector representing the t +1 th iteration
Figure 289726DEST_PATH_IMAGE424
The k line value of (1);
Figure 643347DEST_PATH_IMAGE425
-finder sparrow position vector representing the tth iteration
Figure 441538DEST_PATH_IMAGE424
The k-th row value of (2);
Figure 407483DEST_PATH_IMAGE426
-representing a globally optimal sparrow position vector in a population
Figure 607520DEST_PATH_IMAGE427
The value of the k-th row of (c),
Figure 132042DEST_PATH_IMAGE427
is defined as a population
Figure 417530DEST_PATH_IMAGE428
The solution quality is sorted from the best to the bad optimal solution;
Figure 685700DEST_PATH_IMAGE429
-an intermediate calculation function;
Figure 835184DEST_PATH_IMAGE430
-a constant;
Figure 592924DEST_PATH_IMAGE431
-a maximum number of iterations;
Figure 365708DEST_PATH_IMAGE432
-the current number of iterations;
Figure 171990DEST_PATH_IMAGE433
、
Figure 346620DEST_PATH_IMAGE434
-the generation of a random number by the processor,
Figure 212945DEST_PATH_IMAGE435
，
Figure 473025DEST_PATH_IMAGE436
；
Figure 572744DEST_PATH_IMAGE437
-the generation of a random number by the processor,
Figure 601880DEST_PATH_IMAGE438
；
Figure 904685DEST_PATH_IMAGE439
-the generation of a random number by the processor,
Figure 386482DEST_PATH_IMAGE440
。
5. and (3) updating the position of a follower in the population according to the following expression formula:
Figure 800146DEST_PATH_IMAGE441
wherein:
Figure 418209DEST_PATH_IMAGE442
-initial population
Figure 891915DEST_PATH_IMAGE443
The number of (2);
Figure 861008DEST_PATH_IMAGE444
-a first step
Figure 314249DEST_PATH_IMAGE444
A follower;
Figure 317977DEST_PATH_IMAGE445
-is a random number;
d-sparrow position vector
Figure 759323DEST_PATH_IMAGE446
The number of rows of (a), 12 in the present embodiment;
Figure 215712DEST_PATH_IMAGE447
-generating a random number between 0 and 1;
Figure 971178DEST_PATH_IMAGE448
-follower sparrow position vector representing the t +1 th iteration
Figure 298254DEST_PATH_IMAGE449
The value of the k-th row of (c),
Figure 113763DEST_PATH_IMAGE450
；
Figure 558914DEST_PATH_IMAGE451
-follower sparrow position vector representing the t-th iteration
Figure 118071DEST_PATH_IMAGE449
The k-th row value of (2);
Figure 519227DEST_PATH_IMAGE452
-representing a globally optimal sparrow position vector in a population
Figure 240059DEST_PATH_IMAGE453
The value of the k-th row of (c),
Figure 671040DEST_PATH_IMAGE453
is defined as a population
Figure 768309DEST_PATH_IMAGE454
The solution quality is sorted from the best to the bad optimal solution;
Figure 397874DEST_PATH_IMAGE455
-representing the globally worst sparrow position vector in the population
Figure 289606DEST_PATH_IMAGE456
The value of the k-th row of (c),
Figure 207884DEST_PATH_IMAGE457
is defined as a population
Figure 344729DEST_PATH_IMAGE454
The quality of the solution is the worst solution ordered from good to bad.
6. Updating the position of the alertor in the population, wherein the alertor randomly selects the initial population
Figure 766483DEST_PATH_IMAGE454
The SD random selection is used for position updating, and the expression formula is as follows:
Figure 360276DEST_PATH_IMAGE458
Figure 500270DEST_PATH_IMAGE459
Figure 204921DEST_PATH_IMAGE460
Figure 746761DEST_PATH_IMAGE461
wherein:
Figure 980296DEST_PATH_IMAGE462
-a first step of
Figure 873165DEST_PATH_IMAGE462
A follower;
Figure 351814DEST_PATH_IMAGE463
-the alert sparrow position vector representing the t +1 th iteration
Figure 748160DEST_PATH_IMAGE464
Number k of lines ofA value;
Figure 214913DEST_PATH_IMAGE465
-an alerter sparrow position vector representing the t-th iteration
Figure 329500DEST_PATH_IMAGE464
The k line value of (1);
Figure 110374DEST_PATH_IMAGE466
-random numbers that fit into a positive distribution;
Figure 361227DEST_PATH_IMAGE467
-preventing a relatively small constant with a denominator of 0;
Figure 500346DEST_PATH_IMAGE468
being a section
Figure 102229DEST_PATH_IMAGE469
Random data of (a);
Figure 686794DEST_PATH_IMAGE470
-representing a globally optimal sparrow position vector in a population
Figure 57733DEST_PATH_IMAGE471
The value of the k-th row of (c),
Figure 803972DEST_PATH_IMAGE471
is defined as a population
Figure 893150DEST_PATH_IMAGE472
The solution quality is sorted from the best to the bad optimal solution;
Figure 15827DEST_PATH_IMAGE473
-representing the globally worst sparrow position vector in the population
Figure 241272DEST_PATH_IMAGE474
The value of the k-th row of (c),
Figure 925457DEST_PATH_IMAGE475
is defined as a population
Figure 95407DEST_PATH_IMAGE472
The worst solution is sorted from the best to the bad solution in the solution quality sequence;
Figure 21775DEST_PATH_IMAGE476
、
Figure 101726DEST_PATH_IMAGE477
、
Figure 720926DEST_PATH_IMAGE478
-separately representing the position vectors
Figure 829039DEST_PATH_IMAGE479
、
Figure 559098DEST_PATH_IMAGE480
、
Figure 493556DEST_PATH_IMAGE481
Corresponding fitness value;
a, the number of weak and heavy parts of the test part under the whole vehicle road test working condition;
Figure 283657DEST_PATH_IMAGE482
、
Figure 569145DEST_PATH_IMAGE483
、
Figure 571736DEST_PATH_IMAGE484
sparrow position vector
Figure 626280DEST_PATH_IMAGE479
、
Figure 88747DEST_PATH_IMAGE480
、
Figure 595952DEST_PATH_IMAGE481
Is calculated for the ith row of the objective function vector.
7. And after the position updating of the finder, the follower and the warner is finished, returning to the calculation steps 3 to 6 again for calculation, and sequentially performing loop iteration calculation. Wherein, the position updating of the finder, the follower and the alerter is carried out once and is recorded as iteration once.
Respectively updating the positions of the finder, the follower and the alerter until the position updating times of the sparrow searching algorithm reach the set updating times
Figure 667813DEST_PATH_IMAGE485
And then, obtaining the three-axial acceleration power spectrum density signal curve according to the acceleration power spectrum density signal value corresponding to the set updating times. Wherein, the set updating times are set according to actual requirements.
Or respectively updating the positions of the finder, the follower and the alerter until the objective function vector of the sparrow search algorithm meets the termination condition of the sparrow search algorithm, namely the objective function vector of the sparrow search algorithm
Figure 842443DEST_PATH_IMAGE486
Relation to iterative error target vector
Figure 708768DEST_PATH_IMAGE487
And if the termination condition is met, obtaining the three-axial acceleration power spectral density signal curve according to the acceleration power spectral density signal value corresponding to the target function vector.
After obtaining the acceleration power spectral density signal curve of each unidirectional life weak weight-off part set and the three-axial acceleration power spectral density signal curve of the test part, executing a step S104, and performing a vibration endurance test on the test part through the acceleration power spectral density signal curve of each unidirectional life weak weight-off part set and the three-axial acceleration power spectral density signal curve of the test part.
Specifically, after an acceleration power spectrum density signal curve of each unidirectional life weak weight-related part set and a triaxial acceleration power spectrum density signal curve of the tested part are obtained, namely after an acceleration power spectrum density signal curve of an X-direction life weak weight-related part set, an acceleration power spectrum density signal curve of a Y-direction life weak weight-related part set, an acceleration power spectrum density signal curve of a Z-direction life weak weight-related part set and a triaxial acceleration power spectrum density signal curve of the tested part are obtained, the tested part is vibrated according to the acceleration power spectrum density signal curve of each unidirectional life weak weight-related part set and the triaxial acceleration power spectrum density signal curve of the tested part, and the durability of the tested part is tested.
One or more technical solutions in the embodiments of the present invention at least have the following technical effects or advantages:
in this embodiment, the triaxial is right simultaneously under the whole car road endurance test operating mode of test part the in-process of test part vibration acquires the weak key position aggregate in life-span of test part, and right through a plurality of unilateral under the whole car road endurance test operating mode the in-process of test part vibration acquires the weak key position aggregate in a plurality of unilateral life-span. And then, performing accelerated processing on each unidirectional life weak critical weight part set in the plurality of unidirectional life weak critical weight part sets to obtain an acceleration power spectrum density signal curve of each unidirectional life weak critical weight part set. And then, obtaining a triaxial acceleration power spectrum density signal curve of the test part according to the total set of the service life weak critical parts. And finally, performing a vibration endurance test on the test part through an acceleration power spectrum density signal curve of each unidirectional life weak critical weight part set and an acceleration power spectrum density signal curve of the test part in the three axial directions. Therefore, the whole technical scheme of the embodiment has the following advantages:
1. the method and the device realize the conversion of the load of the durability test of the whole vehicle road into the acceleration load of the vibration durability test of the multi-axial rack, and improve the precision of the vibration durability test of the multi-axial rack.
2. In the process of establishing the acceleration load of the multi-axis rack vibration endurance test of the test part, the actual stress characteristic of the test part and the distribution condition of the weak part of the service life are considered.
3. Through the multi-axial vibration endurance test of the test part, the development verification period of the automobile is really shortened, the test cost is saved, and the method has important engineering significance.
Example two
Based on the same inventive concept, the second embodiment of the present invention further provides a test apparatus for testing vibration durability of a multi-axial table, as shown in fig. 2, comprising:
the system comprises an acquisition module 201, a data processing module and a data processing module, wherein the acquisition module is used for acquiring a total set of life weak critical parts of a test part in the process of vibrating the test part simultaneously in a triaxial direction under the working condition of a finished automobile road endurance test, and acquiring a plurality of one-way life weak critical part sets in the process of vibrating the test part in a plurality of one-way directions under the working condition of the finished automobile road endurance test;
a unidirectional module 202, configured to obtain an acceleration power spectrum density signal curve of each unidirectional life weak critical weight part set by performing accelerated processing on each unidirectional life weak critical weight part set in the plurality of unidirectional life weak critical weight part sets;
the triaxial module 203 is configured to obtain a triaxial acceleration power spectrum density signal curve of the test part according to the total set of the weak critical weight parts of the service life;
the test module 204 is configured to perform a vibration endurance test on the test part according to the acceleration power spectral density signal curve of each unidirectional life weak critical weight portion set and the three-axial acceleration power spectral density signal curve of the test part.
As an optional embodiment, the obtaining a total set of weak life critical parts of the test part includes:
acquiring triaxial acceleration load signals of the test part in the process of vibrating the test part in the triaxial direction under the working condition of the durability test of the whole vehicle road;
obtaining stress power spectrum signals of a plurality of parts of the test part according to the triaxial acceleration load signal, the finite element model and the stress frequency response functions in a plurality of directions of the test part;
and obtaining the total set of the weak life critical parts according to the stress power spectrum signals of the plurality of parts.
As an alternative embodiment, the obtaining the total set of weak life critical parts according to the stress power spectrum signals of the plurality of parts includes:
obtaining fatigue life damage values of the multiple parts of the test part according to the stress power spectrum signals of the multiple parts, the S-N curve of the test part and the total test duration of the whole vehicle road endurance test;
and obtaining the total set of the weak life critical parts according to the fatigue life damage values of the plurality of parts.
As an optional embodiment, the obtaining an acceleration power spectral density signal curve of each unidirectional life weak critical weight point set by performing accelerated processing on each unidirectional life weak critical weight point set in the plurality of unidirectional life weak critical weight point sets includes:
aiming at each one-way life weak and important part set, obtaining a group of acceleration power spectrum density signal values according to the one-way life weak and important part set; and obtaining the acceleration power spectral density signal curve according to the group of acceleration power spectral density signal values.
As an optional embodiment, the obtaining, according to the total set of the life weak critical weight parts, a triaxial acceleration power spectral density signal curve of the test part includes:
and carrying out a sparrow search algorithm on the total set of the weak life and heavy part to obtain the triaxial acceleration power spectrum density signal curve.
As an optional embodiment, the performing a sparrow search algorithm on the total set of the weak life-span critical weight parts to obtain the triaxial acceleration power spectral density signal curve includes:
acquiring an initial population of the sparrow search algorithm according to the total set of the weak life and heavy-key parts;
obtaining a finder, a follower and a warner of the initial population according to the initial population;
and respectively updating the positions of the finder, the follower and the alerter until the acceleration power spectrum density signal curve in the three-axis direction is obtained according to the acceleration power spectrum density signal value corresponding to the set updating times when the position updating times of the sparrow searching algorithm reach the set updating times.
As an optional embodiment, after obtaining the finder, the follower, and the alerter of the initial population according to the initial population, the method further includes:
and respectively updating the positions of the finder, the follower and the warner until the target function vector of the sparrow search algorithm meets the termination condition of the sparrow search algorithm, and obtaining the three-axial acceleration power spectrum density signal curve according to the acceleration power spectrum density signal value corresponding to the target function vector.
Since the multi-axial stage vibration endurance test apparatus described in this embodiment is an apparatus used for implementing the multi-axial stage vibration endurance test method in the first embodiment of the present application, a person skilled in the art can understand a specific implementation manner and various modifications of the multi-axial stage vibration endurance test apparatus of this embodiment based on the multi-axial stage vibration endurance test method described in the first embodiment of the present application, and therefore, a detailed description of how to implement the method in the first embodiment of the present application by the multi-axial stage vibration endurance test apparatus is not given here. The device used by those skilled in the art to implement the method for testing vibration endurance of multi-axial table in the first embodiment of the present application is all within the protection scope of the present application.
EXAMPLE III
Based on the same inventive concept, the third embodiment of the present invention also provides a computer apparatus comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the steps of any one of the above-mentioned multi-axial stage vibration endurance test methods when executing the program.
Example four
Based on the same inventive concept, a fourth embodiment of the present invention further provides a computer-readable storage medium, having a computer program stored thereon, where the computer program, when executed by a processor, implements the steps of any one of the methods of the multi-axial stage vibration endurance testing method described in the previous embodiment.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
While preferred embodiments of the present invention have been described, additional variations and modifications in those embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. Therefore, it is intended that the appended claims be interpreted as including preferred embodiments and all such alterations and modifications as fall within the scope of the invention.
It will be apparent to those skilled in the art that various changes and modifications may be made in the present invention without departing from the spirit and scope of the invention. Thus, if such modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include such modifications and variations.

Claims (8)

1. A multi-axial bench vibration durability test method is characterized by comprising the following steps:
acquiring a total set of life weak and critical parts of a test part in the process of vibrating the test part simultaneously in three axial directions under the working condition of a finished automobile road endurance test, and acquiring a plurality of unidirectional sets of life weak and critical parts in the process of vibrating the test part in a plurality of unidirectional directions under the working condition of the finished automobile road endurance test;
obtaining an acceleration power spectrum density signal curve of each unidirectional life weak critical weight part set by performing accelerated processing on each unidirectional life weak critical weight part set in the plurality of unidirectional life weak critical weight part sets, including:
aiming at each one-way life weak and important part set, obtaining a group of acceleration power spectrum density signal values according to the one-way life weak and important part set; obtaining the acceleration power spectral density signal curve according to the group of acceleration power spectral density signal values;
obtaining a triaxial acceleration power spectrum density signal curve of the test part according to the service life weak critical weight part total set, wherein the curve comprises the following steps:
carrying out a sparrow search algorithm on the total set of the weak and critical parts of the service life to obtain the three-axial acceleration power spectrum density signal curve;
and carrying out a vibration endurance test on the test part through the acceleration power spectrum density signal curve of each unidirectional life weak critical weight part set and the three-axial acceleration power spectrum density signal curve of the test part.
2. The method of claim 1, wherein said obtaining a total set of weak life critical parts of said test part comprises:
acquiring triaxial acceleration load signals of the test part in the process of vibrating the test part in the triaxial direction under the working condition of the durability test of the whole vehicle road;
obtaining stress power spectrum signals of a plurality of parts of the test part according to the triaxial acceleration load signal, the finite element model and the stress frequency response functions in a plurality of directions of the test part;
and obtaining the total set of the weak life critical parts according to the stress power spectrum signals of the plurality of parts.
3. The method according to claim 2, wherein the obtaining the total set of the life-time weak critical sections according to the stress power spectrum signals of the plurality of sections comprises:
obtaining fatigue life damage values of the multiple parts of the test part according to the stress power spectrum signals of the multiple parts, the S-N curve of the test part and the total test duration of the whole vehicle road endurance test;
and obtaining the total set of the weak life critical parts according to the fatigue life damage values of the plurality of parts.
4. The method of claim 1, wherein performing a sparrow search algorithm on the total set of weak life critical weight parts to obtain the triaxial acceleration power spectral density signal curve comprises:
acquiring an initial population of the sparrow search algorithm according to the total set of the weak life and heavy-key parts;
according to the initial population, a finder, a follower and a warner of the initial population are obtained;
and respectively carrying out position updating on the finder, the follower and the warner until the acceleration power spectrum density signal curve in the three axial directions is obtained according to the acceleration power spectrum density signal value corresponding to the set updating times when the position updating times of the sparrow searching algorithm reach the set updating times.
5. The method of claim 4, further comprising, after obtaining the finder, the follower, and the alerter of the initial population from the initial population:
and respectively updating the positions of the finder, the follower and the warner until the target function vector of the sparrow search algorithm meets the termination condition of the sparrow search algorithm, and obtaining the three-axial acceleration power spectrum density signal curve according to the acceleration power spectrum density signal value corresponding to the target function vector.
6. A multi-axial bench vibration durability test device is characterized by comprising:
the system comprises an acquisition module, a data processing module and a data processing module, wherein the acquisition module is used for acquiring a total set of life weak critical weight parts of a test part in the process of vibrating the test part simultaneously in a triaxial direction under the working condition of a finished automobile road endurance test, and acquiring a plurality of one-way life weak critical weight part sets in the process of vibrating the test part in a plurality of one-way directions under the working condition of the finished automobile road endurance test;
a unidirectional module, configured to obtain an acceleration power spectral density signal curve of each unidirectional life weak critical weight portion set by performing accelerated processing on each unidirectional life weak critical weight portion set in the plurality of unidirectional life weak critical weight portion sets, where the acceleration power spectral density signal curve includes:
aiming at each one-way life weak and important part set, obtaining a group of acceleration power spectrum density signal values according to the one-way life weak and important part set; obtaining the acceleration power spectral density signal curve according to the group of acceleration power spectral density signal values;
the triaxial module is used for obtaining a triaxial acceleration power spectrum density signal curve of the test part according to the service life weak critical weight part total set, and comprises:
carrying out a sparrow search algorithm on the total set of the weak and critical parts of the service life to obtain the three-axial acceleration power spectrum density signal curve;
and the test module is used for carrying out vibration endurance test on the test part through the acceleration power spectrum density signal curve of each unidirectional service life weak weight-related part set and the three-axial acceleration power spectrum density signal curve of the test part.
7. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor implements the method according to any of claims 1-5 when executing the program.
8. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the method according to any one of claims 1-5.
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