CN107644149B - Consider the multi-pass trace equalization correlating method of load distribution and damage consistency - Google Patents
Consider the multi-pass trace equalization correlating method of load distribution and damage consistency Download PDFInfo
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Abstract
The present invention discloses a kind of multi-pass trace equalization correlating method for considering load distribution and damage consistency, includes the following steps: 1) to convert by stages loading spectrum for test site and each channel load history of user using rain-flow counting and zero-mean conversion method；2) fatigue damage is converted for each channel by stages loading spectrum according to fatigue life prediction theory, constructs multichannel by stages equivalent damage correlation model；3) damage of each channel by stages in test site and the damage of user's corresponding channel are normalized using method for normalizing.The present invention has comprehensively considered load distribution consistency and the damage consistency principle, can either guarantee test field and the distribution of user's load it is consistent, again can guarantee test field test it is consistent with user trial fatigue damage, it solves the problems, such as that the matching as caused by each channel signal type and magnitude differences is harmonious poor using normalized method simultaneously, the priority match of important channel is realized using the method for assigning different weights to each channel.
Description
Technical Field
The invention relates to a vehicle reliability strengthening test technology, in particular to a new method for associating a test yard with a user reliability test by simultaneously considering load distribution consistency, damage consistency and multichannel balance.
Background
The reliability is the basic guarantee of the safe operation of the vehicle and also the necessary condition for guaranteeing the transportation efficiency. In the running process of the vehicle, the sudden fatigue failure of key parts can cause road traffic accidents of vehicle damage and people death. The automobile test field is responsible for testing and evaluating the reliability of the whole automobile product. The relevance between the test field test and the user determines the scientificity of the test field reliability test and evaluation to a certain extent, and the relevance research of the test field test and the user is widely regarded at home and abroad.
The research on the relevance between a test field and a user can be divided into two categories, namely a fault statistics method and a fatigue life prediction method. Because the fault statistical method needs a large amount of fault data which can be obtained after vehicles are put on the market for years, the method is obviously not suitable for testing and evaluating new vehicle models. In recent years, fatigue life prediction matching methods are widely researched and applied, and are mainly classified into an equal damage principle and an equal load principle.
The relevance research of a test field and user working conditions is carried out by firstly carrying out data acquisition and processing on a user road and a test field road, and the basic steps are as follows:
1) various sensors are arranged on the measured position of the vehicle, the signals of the sensors are accessed into a data acquisition unit, the sensor in each direction is 1 channel, for example, a longitudinal sensor of a shaft head is a channel, a three-way sensor of the shaft head is 3 channels, and the sensors also comprise sensors of force, strain, displacement, torque and the like;
2) road tests are carried out in a user and a test field, and load time histories of running of a vehicle on various roads of the user and the test field, namely the histories of changes of signals such as acceleration, strain, displacement and torque acquired by various sensors along with time are acquired respectively.
3) The measured load time history of a single or multiple channels is irregular and random, and is generally converted into a load cycle consisting of different amplitudes and different cycle times through a rain flow counting method, namely a load spectrum (for example, a two-dimensional graph is used for representing the amplitude of the load such as corresponding acceleration or stress on an x axis, and the corresponding action frequency on a y axis).
After the data acquisition and processing are completed to form a user load spectrum and a test field road load spectrum, the user load spectrum and the test field road load spectrum can be matched by using a method of equal load or equal damage.
1) The equal load matching is to divide the load amplitude values of the user load spectrum and the test field load spectrum into a plurality of intervals by taking load distribution consistency as a matching target, and the corresponding times of each interval are consistent (namely load distribution consistency) through matching; the equal load matching can ensure that the failure mode is consistent with the user to a certain degree, but because the cycle times of the general large amplitude are small but large damage can be generated, the cycle times of the small amplitude are large but the damage is small, and the consistency of the damage and the user is difficult to ensure during matching.
2) The equal damage matching is that on the basis of load spectrums of each channel of a user and a test field, the damage of each channel of the user and the test field is calculated respectively by using a fatigue prediction theory, and the corresponding damage of each channel is consistent through matching; the equal damage principle only concerns whether the accumulated total damage of the user and the test field test vehicle and parts is equal, but the structure (load amplitude, mean value and frequency distribution) of the load used by the user and the test field test load is not related.
3) When a plurality of channels are matched, the equal-damage equal-input matching method does not consider the problem of unbalanced matching caused by different signal types and different orders of magnitude of each channel (some channel test fields are well matched with users, and some channel test fields are poorly matched with users).
Disclosure of Invention
Aiming at the problems, in order to further improve the relevance between the automobile test field and the user reliability test, the invention provides a new method for relevance between the test field and the user, which comprehensively considers the load distribution consistency, the damage consistency and the multi-channel balance.
The invention adopts the following technical scheme: a new multichannel balance association method considering load distribution and damage consistency is characterized by comprising the following steps:
1) respectively converting the load time history of each channel on a test field road and a user road into an interval load spectrum by adopting a rain flow counting and zero-mean conversion method;
2) based on fatigue prediction and Miner criterion, converting the load spectrum between the partitions of each channel into fatigue damage, and constructing a multi-channel partition equal damage correlation model;
3) taking a single channel as a unit, carrying out normalization on the whole channels: and carrying out normalization processing on the fatigue damage between certain subareas of a certain channel on a certain road of the test field and the fatigue damage between corresponding subareas of a channel corresponding to the user, and the sum of the fatigue damage between the certain subareas of the channel corresponding to the user.
The specific implementation method of the step 1) comprises the following steps:
assuming that a test field has k strengthening roads in total, setting a test to take m channels in total, and dividing any one channel into n load amplitude intervals, then:
for a single channel, the load spectrum matrix of this channel isElement FijThe number of load cycles of the ith interval of the channel on the jth road of the test field is i-1-n, and j-1-k;
and the user load spectrum matrix isElement HiThe number of load cycles in the ith section of the channel on the user road.
The specific implementation method of the step 2) comprises the following steps:
according to the fatigue characteristics of the material, calculating the fatigue damage corresponding to different stress amplitude intervals on different roads of a test field by adopting Miner criterion:
the damage component or the fatigue life component of the loss in the stress amplitude interval is as follows:
in the formula, NiIs the interval sigma of the S-N curve corresponding to the stress amplitudeaiThe number of cycles of destruction of; n isiIn the stress amplitude interval sigmaaiActual number of cycles of operation;
let N0To correspond to fatigue limit σ-1W is a constant, and according to the Basquin relation of the S-N curve, the fatigue limit life of (1) is as follows:
the available damage component or fatigue life component of the stress amplitude interval is:
converting the test field load spectrum matrix and the user load spectrum matrix into the fatigue damage of the test field subareas and the fatigue damage of the user by using a formula (4)
Wherein,
assuming that a test field has k strengthening roads in total, dividing any channel into n stress amplitude intervals, FijThe number of load cycles in the ith section of a certain channel on the jth road of a test field is 1-n, j is 1-k, HiThe load cycle number of the ith interval of the channel on the user channel is shown;
assuming that m channels are taken in the test, establishing the equal damage correlation model of each interval of the m channels as follows:
in the formula (5), matrixElement(s)The fatigue damage of the jth road in the ith section test field of the ith channel is expressed, r is 1-m, and the distribution matrix of the test times of various roads in the test field isElement alphajThe test cycle number of the jth road of the test field,
and the user fatigue damage matrix isElement(s)Fatigue damage of users in the ith channel interval.
The specific implementation method of the step 3) is to establish a relational expression:
the test field multi-channel interval damage matrix with the channel being normalized is recorded as:
element(s)The sum of fatigue damage of the users in n intervals of the r channel is obtained.
After normalization, different weight coefficients are given according to the importance degrees of different channels, so that better matching of the important channels is realized:
the multi-channel interval damage matrix of the test field endowed with different weight coefficients is recorded asElement(s)krIs the weight coefficient of the r channel.
By adopting the technical scheme, the invention has the following advantages:
1. the invention provides a multi-channel user and test field correlation model with equal damage among partitions, which comprehensively considers the principles of load distribution consistency (partition matching according to amplitude) and damage consistency (equal damage), and performs correlation matching according to the model, thereby ensuring the consistency of test field tests and user load distribution and the consistency of test field tests and user fatigue damage.
2. Aiming at the simultaneous matching of a plurality of channels, the invention adopts a normalization method to solve the problem of poor matching balance caused by the difference of signal types and orders of magnitude of each channel. It should be noted that, during normalization, each interval is not normalized, but the channel is taken as a unit to be normalized integrally, so that the scientificity of weight distribution of each interval in the channel is ensured, the weight with large damage is great, and otherwise, matching distortion is caused; and the problem of imbalance caused by different signals or different orders of magnitude among different channels is also considered.
3. The invention can also give different weight coefficients according to the importance degree of the channel, thereby realizing better matching of the important channel.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by the practice of the invention.
Drawings
FIG. 1 shows the load distribution and damage matching results of the channel 1 of the embodiment;
FIG. 2 shows the load distribution and damage matching results of the channel 2 of the embodiment;
FIG. 3 shows the load distribution and damage matching results for channel 3 of the embodiment;
FIG. 4 shows the experimental field damage of the three channels of the example in comparison with the user's damage.
Detailed Description
The present invention is described in detail with reference to the following examples, but it should be understood by those skilled in the art that the following examples are not intended to limit the technical scope of the present invention, and any equivalent changes or modifications made within the spirit of the technical scope of the present invention should be considered as falling within the scope of the present invention.
The invention provides a new method for associating a test yard with a user by comprehensively considering load distribution consistency, damage consistency and multichannel balance, which comprises the following steps:
1) and converting the actually measured load time histories of the test field and each channel of the user into load spectrums by adopting methods such as rain flow counting, zero-mean value conversion and the like.
Dividing a single channel into n load amplitude subareas; if the test field has k types of roads in total, the load spectrum matrix of the road isElement FijFor this purpose, the number of load cycles of the ith section of the channel on the jth road of the test field is 1 to n, and j is 1 to k.
The user has only one road, and the user load spectrum matrix isElement HiFor the number of load cycles in the ith section of the lane on the customer road, i is 1 to n.
2) And converting the load spectrum among the partitions into fatigue damage based on fatigue prediction and a Miner accumulated damage rule, and constructing a multi-channel partition equal damage correlation model.
And calculating the corresponding fatigue damage under different stress amplitude intervals on different reinforced roads in a test field by adopting Miner criterion according to the fatigue characteristics of the material.
The damage component or the fatigue life component of the loss in the stress amplitude interval is as follows:
in the formula, NiIs the stress amplitude interval sigma on the S-N curve (stress-life curve)aiThe number of cycles (life) of occurrence of fatigue failure; n isiIn the stress amplitude interval sigmaaiActual number of duty cycles.
Let N0To correspond to fatigue limit σ-1W is a constant, and according to the Basquin relation of the S-N curve, the fatigue limit life of (1) is as follows:
the available damage component or fatigue life component of the stress amplitude interval is:
using equation (4), test field loading spectrum matrix is formedAnd user load spectrum matrixConverted into fatigue damage matrix of test field intervalAnd user fatigue damage matrixWherein,
assuming that m channels are provided in total, establishing an equal damage correlation model among m channel partitions as follows:
in the formula (5), matrixElement(s)The fatigue damage of the ith section of the ith channel in the jth road of the test field is expressed, wherein r is 1-m, i is 1-n, and j is 1-k. The distribution matrix of the test times of various roads in the test field isElement alphajThe test cycle number of the jth road of the test field.
And the user fatigue damage matrix isElement(s)Fatigue damage on the user road for the ith section of the r channel.
3) The method adopts a normalization method, normalizes the damage of each road, each channel and each partition of the test field and the damage of the channel corresponding to the user by taking the channel as a unit, and solves the problem of poor matching balance caused by inconsistent multi-system signal types or difference of signal orders of each channel.
The normalization process enables the weight of each channel in the correlation regression to be consistent, and the matching of the equilibrium is achieved. The method is characterized in that normalization processing (such as formula 6) is not performed on each interval of each channel, but normalization processing (such as formula 7) is performed on the whole channel, so that the scientificity of weight distribution of each interval in the channel is guaranteed, the weight with large damage is great, and otherwise, matching distortion is caused; and the problem of imbalance caused by different signals or different orders of magnitude among different channels is also considered.
As shown in the formula (6), the multi-channel interval damage matrix of the test field with each interval of each channel normalized is recorded asElements thereofThe rest is in accordance with equation (5).
As shown in formula (7), the multi-channel inter-partition damage matrix of the test field with the channel being normalized is recorded asElement(s)The sum of the fatigue injuries of the users in n intervals of the r channel is the rest is consistent with the formula (5).
4) After normalization, different weight coefficients can be flexibly given according to the importance degrees of different channels, so that better matching of the important channels is realized, as shown in formula (8).
As shown in the formula (8), the multi-channel inter-partition damage matrix of the test field given different weight coefficients is recorded as Element(s)krThe weight coefficient of the r-th channel is the same as the formula (5).
5) Solving the established association model formula (7) or formula (8) to obtain the test times of various roads in the test field
Example (b):
table 1, table 2, table 3 show the stress amplitude interval of 3 channels and the corresponding cycle number, respectively, as follows.
TABLE 1 channel 1 test data
Table 2 channel 2 test data
Table 3 channel 3 test data
Taking channel 1 as an example, as shown in table 1, when the test field is divided into 16 sections, r is 1, n is 16, and the test field has 5 roads in total, the load spectrum matrix of the test field of channel 1 is:
the user load spectrum matrix is:
converting the test field load spectrum matrix and the user load spectrum matrix into test field interval fatigue damage and user fatigue damage by using a formula (4), and giving w to 11.75 and N according to the formula (4)0＝106,σ-1＝1494。
The damage matrix for the channel 1 test field is then:
the user impairment matrix is;
in the same way, a channel 2 test field and a user damage matrix can be obtained, so that a multi-channel partition equal damage correlation model is constructed as follows:
channel normalization was performed according to equation (7) as shown below.
Solving equation (10) yields:
the matching results of the three channels are shown in FIGS. 1-3.
From the analysis of FIGS. 1-3, the three channels are not of the same order of magnitude (stress amplitude of channel 1 is of the order of 10)-8The stress amplitude of the channel 2 is of the order of 10-5The stress amplitude of the channel 3 is of the order of 10-3). The mean square error of the matching among the three channel partitions is 1.0232e-09 (the user impairment order of channel 1 is 10)-8) 4.6174e-07 (stress amplitude of channel 2 is of the order of 10)-5) 6.8486e-05 (stress amplitude of the channel 3 is of the order of 10)-3) The error is 1-2 orders of magnitude lower than the damage of the user, and the matching effect between the test field and the user partition is good.
As can be seen from FIG. 4, the damage contrast ranges of the test field and the user are 0.959-1.001, which are all around 1, and the fluctuation range is small, namely the balance is good.
Therefore, the invention not only ensures that the test field test is consistent with the user load distribution, but also ensures that the test field test is consistent with the user fatigue damage, thereby achieving good matching effect.
Claims (3)
1. A multi-channel equilibrium association method considering load distribution and damage consistency is characterized by comprising the following steps:
1) respectively converting the load time history of each channel on a test field road and a user road into an interval load spectrum by adopting a rain flow counting and zero-mean conversion method;
2) based on fatigue prediction and Miner criterion, converting the load spectrum between the partitions of each channel into fatigue damage, and constructing a multi-channel partition equal damage correlation model;
3) taking a single channel as a unit, carrying out normalization on the whole channels: the fatigue damage between certain subareas of a certain channel on a certain road of a test field and the fatigue damage between corresponding subareas of a channel corresponding to a user are subjected to normalization processing after the two are subjected to quotient processing with the sum of the damages between all the subareas of the channel corresponding to the user;
wherein, the specific implementation method for the step 1) comprises the following steps:
assuming that a test field has k strengthening roads in total, setting a test to take m channels in total, and dividing any one channel into n load amplitude intervals, then:
for a single channel, the load spectrum matrix of this channel isElement FijThe number of load cycles of the ith interval of the channel on the jth road of the test field is i-1-n, and j-1-k; the user load spectrum matrix isElement HiThe load cycle number of the ith interval of the channel on the user channel is shown;
based on this, the specific implementation method for the step 2) is as follows:
according to the fatigue characteristics of the material, calculating the fatigue damage corresponding to different stress amplitude intervals on different roads of a test field by adopting Miner criterion:
the damage component or the fatigue life component of the loss in the stress amplitude interval is as follows:
in the formula, NiIs the interval sigma of the S-N curve corresponding to the stress amplitudeaiThe number of cycles of destruction of; n isiIn the stress amplitude interval sigmaaiActual number of cycles of operation;
let N0To correspond to fatigue limit σ-1W is a constant, and according to the Basquin relation of the S-N curve, the fatigue limit life of (1) is as follows:
the available damage component or fatigue life component of the stress amplitude interval is:
using equation (4), test field loading spectrum matrix is formedAnd user load spectrum matrixConversion to fatigue damage in test field intervalsAnd fatigue damage of users
Wherein,
then, establishing the equal damage correlation models of each interval of the m channels as follows:
in the formula (5), matrixElement(s)The fatigue damage of the jth road in the ith section test field of the ith channel is expressed, r is 1-m, and the distribution matrix of the test times of various roads in the test field isElement alphajThe test cycle number of the jth road of the test field,
and the user fatigue damage matrix isElement Yi rFatigue damage of users in the ith channel interval.
2. The multi-channel balanced correlation method considering load distribution and damage uniformity as claimed in claim 1, wherein the specific implementation method of step 3) is to establish a relation:
the test field multi-channel interval damage matrix with the channel being normalized is recorded as:
element(s) The sum of fatigue damage of the users in n intervals of the r channel is obtained.
3. The multi-channel balanced correlation method considering load distribution and damage uniformity as claimed in claim 2, wherein after normalization, different weighting coefficients are given according to the importance degrees of different channels, and formula (8) shows:
the multi-channel interval damage matrix of the test field endowed with different weight coefficients is recorded asElement(s)krIs the weight coefficient of the r channel.
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| CN109977459B (en) * | 2019-02-11 | 2022-10-28 | 中国第一汽车股份有限公司 | Method for improving accuracy of reinforced load spectrum by applying CAE technology |
| CN110069875A (en) * | 2019-04-28 | 2019-07-30 | 江铃汽车股份有限公司 | A kind of generation method of the load modal data of dynamic load emulation |
| CN110455650A (en) * | 2019-07-10 | 2019-11-15 | 河海大学 | A method of quickly determining prefabricated cracked concrete beam fatigue life |
| CN111460370B (en) * | 2020-03-11 | 2024-01-19 | 中国汽车技术研究中心有限公司 | Automobile transmission system test field association method, system, storage medium and equipment |
| CN111680409B (en) * | 2020-05-27 | 2023-02-17 | 中国汽车技术研究中心有限公司 | Test field association method for automobile structure endurance program |
| CN112861702B (en) * | 2021-02-04 | 2024-05-07 | 中车齐齐哈尔车辆有限公司 | Load signal processing method, device, storage medium and equipment |
| CN113435018A (en) * | 2021-06-09 | 2021-09-24 | 中国汽车技术研究中心有限公司 | Damage calculation method for road load spectrum of automobile user |
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