CN106546436B - A kind of auto parts and components loading spectrum is effectively compressed method - Google Patents
A kind of auto parts and components loading spectrum is effectively compressed method Download PDFInfo
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- CN106546436B CN106546436B CN201610913188.8A CN201610913188A CN106546436B CN 106546436 B CN106546436 B CN 106546436B CN 201610913188 A CN201610913188 A CN 201610913188A CN 106546436 B CN106546436 B CN 106546436B
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- 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
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Abstract
The invention discloses a kind of auto parts and components loading spectrums to be effectively compressed method, comprising steps of 1), input part original load spectrum；2) processing before, reducing to loading spectrum；3) wavelet decomposition, is carried out to part original load spectrum, obtains the high-frequency wavelet coefficient under a low-frequency wavelet coefficients and N number of different scale；4), high-frequency wavelet coefficient is reconstructed to obtain Wavelet Component；5) threshold value, is arranged to Wavelet Component and obtains damage and contributes big signal segment；6), signal segment is spliced, obtains compressed signal；7) statistical parameter for, calculating compressed signal, when statistical parameter error is greater than 10%, then circulation step 5), conversely, then jumping out circulation；8) the reduction work of signal, is completed.The present invention can carry out reduction processing to uniaxial and multiaxis part loading spectrum respectively, and obtained reduction signal keeps almost the same with original signal, and load effect identical with original signal may be implemented.
Description
Technical field
It is especially that auto parts and components are subjected to indoor road mould the present invention relates to the road spectral editing method of auto parts and components
The method that the quasi- loading spectrum time is compressed.
Background technique
The realization of auto parts and components laboratory road simulation test reappears loaded under the practical road traveling of part out indoors
Situation has the characteristics that the test period is short, test efficiency is high, repdocutbility is good and is widely used in the durable Journal of Sex Research of part.
Auto parts and components load Spectral editing is an important link for carrying out the research of part laboratory road simulation test, the reality of part
Border loading spectrum more can accurately reflect its actual life compared with experience loading spectrum, but the complete real road load for applying part
Spectrum, it will take a substantial amount of time and experimentation cost.It is necessary to carry out acceleration editor to the part loading spectrum of acquisition, guaranteeing to carry
Under the premise of lotus spectrum load effect is identical, time shorter loading spectrum is obtained, is used for the experimental study of part fatigue durability.It protects
Card reduction loading spectrum is identical as load effect of the original load spectrum to part, it is necessary to make to reduce loading spectrum in amount of damage, statistics
Parameter (mean value, root-mean-square value and peak factor), power spectral density and wear grade count etc. it is almost the same with original signal.
There are many ways to part load spectral editing, basic principle are all little to damage contribution amount in erasure signal
Circulation guarantees that the damage carrying amount of signal and original signal are almost the same to shorten test period, the difference between edit methods
It is different to be mainly reflected in amount of damage identification and the method deleted.The amount of damage of signal is and right usually with amplitude direct proportionality
The part that amplitude changes greatly in signal, wavelet transformation can be identified effectively.Signal edit based on wavelet transformation
Method, cardinal principle is to identify and contributes part injury big part in stick signal, reduces front and back by contrast signal
Statistical parameter (root mean square, peak factor) determine final reduction signal.
In the prior art, the loading spectrum accelerated durability edit methods of auto parts and components have: utilizing Ncode software, setting
Damage the reduction that reserved carries out loading spectrum.This method can reduce the loading spectrum of auto parts and components, but obtained
Reduction signal statistical parameter (mean value, root-mean-square value and peak factor) and in terms of and original signal have it is larger
Difference.It is therefore proposed that a kind of auto parts and components loading spectrum based on wavelet transformation is effectively compressed method, make to reduce signal not only
It is almost the same with original signal on damage maintenance dose, and in statistical parameter (mean value, root-mean-square value and peak factor) and function
Rate spectrum density etc. keeps almost the same with original signal.
Summary of the invention
The technical problems to be solved by the present invention are: it is effective to provide a kind of auto parts and components loading spectrum based on wavelet transformation
Compression method, this method enable to compressed signal and original signal in amount of damage, statistical parameter (mean value, root-mean-square value and peak
Value coefficient), power spectral density and wear grade and count etc. and be consistent with original signal, to realize with original signal there is phase
Same load effect.
In order to solve the above technical problems, the technical scheme adopted by the invention is as follows:
A kind of auto parts and components loading spectrum is effectively compressed method, comprising the following steps:
1) original load spectrum of part, is inputted；
2) processing before, reducing to loading spectrum, including resampling, filter, singular value is gone to handle；
3) number of plies N for, specifying wavelet type and decomposition carries out wavelet decomposition to the original load spectrum of part, obtains one
High-frequency wavelet coefficient under low-frequency wavelet coefficients and N number of different scale；
4), high-frequency wavelet coefficient is reconstructed, obtains the Wavelet Component under N number of different scale；
5) threshold value, is arranged to Wavelet Component, according to set threshold value, damages ingredient method of identification, identification using envelope
Higher than the data of threshold value, and position the time point of corresponding data.It will correspond in original load spectrum at time point, damage can be obtained
Contribute big signal segment；
6), signal segment is spliced, obtains compressed signal；
7) statistical parameter of compressed signal, including root-mean-square value and peak factor, are calculated, it, will due to taking different threshold values
Different compressed signals is obtained, therefore when the statistical parameter error of compressed signal and original signal is greater than 10%, then circulation step
5) threshold value for, resetting Wavelet Component is then jumped out until the statistical parameter error of compressed signal and original signal is less than 10%
Circulation；
8) the reduction work of signal, is completed.
Further, the wavelet type includesdbN, Meyr wavelet function, the Decomposition order is according to wavelet function
Depending on.
Further, being specifically included the step of threshold value is set to Wavelet Component in the step 5): for uniaxial vapour
The loading spectrum of vehicle components reduces, then threshold value is respectively set to the Wavelet Component under N number of different scale；For the automobile zero of multiaxis
Components ' load spectrum reduction, then carry out accumulation square summation to the Wavelet Component under N number of different scale, to the knot of accumulation square summation
Threshold value is arranged in fruit.
Further, being specifically included the step of splicing to signal segment in the step 6): to uniaxial automobile
For the loading spectrum of components, several signal segments will be extracted based on the Wavelet Component under each scale, these signal patch
The section corresponding time, there are intersections, and caused signal segment to exist and repeat to extract, therefore, for the load of uniaxial auto parts and components
Lotus is composed when carrying out signal splicing, takes union to handle the signal segment for repeating to extract under each scale；For the automobile zero of multiaxis
For components ' load spectrum, each channel is based on accumulative wavelet coefficient, and there are intersections with extracted signal segment, in order to guarantee to lead to
Phase relation between road needs to carry out the loading spectrum in each channel deleting simultaneously, therefore, for the load of multi-wheeler components
Lotus is composed when carrying out signal splicing, takes union to handle each channel signal segments extracted all more.
Further, each type of wavelet decomposition includes an optimal Decomposition order, enables to final pressure
For contracting signal compression than minimum, damage maintenance dose is maximum, and statistical parameter and power spectral density etc. keep basic with original signal
Unanimously, the statistical parameter includes mean value, root-mean-square value and peak factor.
Further, the single shaft has been all made of the method for taking union with the extracted signal segment of multiaxis and has been spliced,
It is closest with original signal to obtain compressed signal.
Compared with prior art, the present invention having the advantage that
1) the damage maintenance dose ratio of the compressed signal obtained based on wavelet transformation edit methods is based on damage reservation editing side
The compressed signal that method obtains it is big, and be able to maintain 99% or more；
2) statistical parameter (mean value, root mean square and peak factor) of the compressed signal obtained based on wavelet transformation edit methods
Error than retaining the big of the obtained compressed signal of edit methods based on damage, be able to maintain below 10%；
3) power spectral density plot of the compressed signal obtained based on wavelet transformation edit methods retains volume with based on damage
The compressed signal that the method for collecting obtains is compared, the former curve and original signal is closer；
4) grade analysis of accounts of wearing of the compressed signal obtained based on wavelet transformation edit methods retains editor with based on damage
The compressed signal that method obtains is compared, the former curve and original signal is closer；
5) all road surface operating conditions of original signal are able to maintain based on wavelet transformation edit methods, but retained based on damage
Edit methods will lose certain road surface operating mode features.
Detailed description of the invention
Fig. 1 is flow chart of the present invention.
Fig. 2 is uniaxial envelope damage ingredient identification figure in the present invention.
Fig. 3 is that multiaxis envelope damages ingredient identification figure in the present invention.
Fig. 4 is uniaxial signal spliced map in the present invention.
Fig. 5 is multiaxis signal spliced map in the present invention.
Specific embodiment
The present invention will be described in further detail below with reference to the embodiments of the drawings.
As shown in Figure 1, a kind of auto parts and components loading spectrum is effectively compressed method, comprising the following steps:
1) original load spectrum of part, is inputted；
2) processing before, reducing to loading spectrum, including resampling, filter, singular value is gone to handle；
3) number of plies N for, specifying wavelet type and decomposition carries out wavelet decomposition to the original load spectrum of part, obtains one
High-frequency wavelet coefficient under low-frequency wavelet coefficients and N number of different scale；
4), high-frequency wavelet coefficient is reconstructed, obtains the Wavelet Component under N number of different scale；
5) threshold value, is arranged to Wavelet Component, according to set threshold value, damages ingredient method of identification, identification using envelope
Higher than the data of threshold value, and the time point of corresponding data is positioned, will correspond in original load spectrum at time point, damage can be obtained
Contribute big signal segment (see Fig. 2, Fig. 3)；
6), signal segment is spliced, obtains compressed signal；
7) statistical parameter of compressed signal, including root-mean-square value and peak factor, are calculated, it, will due to taking different threshold values
Different compressed signals is obtained, therefore when the statistical parameter error of compressed signal and original signal is greater than 10%, then circulation step
5) threshold value for, resetting Wavelet Component is then jumped out until the statistical parameter error of compressed signal and original signal is less than 10%
Circulation；
8) the reduction work of signal, is completed.
Specifically, the wavelet type includesdbN, Meyr wavelet function, the Decomposition order is according to wavelet function
Depending on.
Specifically, being specifically included the step of threshold value is arranged to Wavelet Component in the step 5): for uniaxial vapour
The loading spectrum of vehicle components reduces, then threshold value is respectively set to the Wavelet Component under N number of different scale；For the automobile zero of multiaxis
Components ' load spectrum reduction, then carry out accumulation square summation to the Wavelet Component under N number of different scale, to the knot of accumulation square summation
Threshold value is arranged in fruit.
Specifically, being specifically included the step of splicing to signal segment in the step 6): to uniaxial automobile
For the loading spectrum of components, several signal segments will be extracted based on the Wavelet Component under each scale, these signal patch
The section corresponding time, there are intersections, and caused signal segment to exist and repeat to extract, therefore, for the load of uniaxial auto parts and components
Lotus is composed when carrying out signal splicing, takes union to handle (see Fig. 4) signal segment for repeating to extract under each scale；For multiaxis
For auto parts and components loading spectrum, each channel is based on accumulative wavelet coefficient and extracted signal segment there are intersection, in order to
The phase relation for guaranteeing interchannel needs to carry out the loading spectrum in each channel deleting simultaneously, therefore, for multi-wheeler zero
The loading spectrum of part takes union to handle (see Fig. 5) when carrying out signal splicing, by the signal segment that each channel extracts more.
Specifically, each type of wavelet decomposition includes an optimal Decomposition order, final pressure is enabled to
For contracting signal compression than minimum, damage maintenance dose is maximum, and statistical parameter and power spectral density etc. keep basic with original signal
Unanimously, the statistical parameter includes mean value, root-mean-square value and peak factor.
Specifically, the single shaft has been all made of the method for taking union with the extracted signal segment of multiaxis and has been spliced,
It is closest with original signal to obtain compressed signal.
The above embodiment of the present invention be only to clearly illustrate example of the present invention, and not be to the present invention
Embodiment restriction.For those of ordinary skill in the art, it can also make on the basis of the above description
Other various forms of variations or variation.There is no necessity and possibility to exhaust all the enbodiments.It is all of the invention
Made any modifications, equivalent replacements, and improvements etc., should be included in the protection of the claims in the present invention within spirit and principle
Within the scope of.
Claims (6)
1. a kind of auto parts and components loading spectrum is effectively compressed method, it is characterised in that: the following steps are included:
1) original load spectrum of part, is inputted；
2) processing before, reducing to loading spectrum, including resampling, filter, singular value is gone to handle；
3) number of plies N for, specifying wavelet type and decomposition carries out wavelet decomposition to the original load spectrum of part, obtains a low frequency
High-frequency wavelet coefficient under wavelet coefficient and N number of different scale；
4), high-frequency wavelet coefficient is reconstructed, obtains the Wavelet Component under N number of different scale；
5) threshold value, is arranged to Wavelet Component, according to set threshold value, damages ingredient method of identification using envelope, identification is higher than
The data of threshold value, and the time point of corresponding data is positioned, it will correspond in original load spectrum at time point, damage contribution can be obtained
Big signal segment；
6), signal segment is spliced, obtains compressed signal；
7) statistical parameter of compressed signal, is calculated, including root-mean-square value and peak factor will be obtained due to taking different threshold values
Different compressed signals, therefore when the statistical parameter error of compressed signal and original signal is greater than 10%, then circulation step 5),
The threshold value for resetting Wavelet Component is then jumped out and is followed until the statistical parameter error of compressed signal and original signal is less than 10%
Ring；
8) the reduction work of signal, is completed.
2. auto parts and components loading spectrum according to claim 1 is effectively compressed method, it is characterised in that: the small echo class
Type includesdbN, Meyr wavelet function, the Decomposition order is depending on wavelet function.
3. auto parts and components loading spectrum according to claim 1 is effectively compressed method, it is characterised in that: in the step 5)
Specifically included the step of to Wavelet Component, threshold value is set: the loading spectrum of uniaxial auto parts and components is reduced, then to it is N number of not
Threshold value is respectively set with the Wavelet Component under scale；Auto parts and components loading spectrum reduction for multiaxis, then to N number of different scale
Under Wavelet Component carry out accumulation square summation, to accumulation square summation a result be arranged a threshold value.
4. auto parts and components loading spectrum according to claim 1 is effectively compressed method, it is characterised in that: in the step 6)
Specifically included the step of splicing to signal segment: for the loading spectrum of uniaxial auto parts and components, be based on each ruler
Wavelet Component under degree will extract several signal segments, these signal segments corresponding time, there are intersections, and led to letter
Number segment, which exists, to be repeated to extract, therefore, for uniaxial auto parts and components loading spectrum when carrying out signal splicing, by each scale
The lower signal segment for repeating to extract takes union to handle；For the auto parts and components loading spectrum of multiaxis, each channel is based on tired
There are intersections to need to guarantee the phase relation of interchannel to each channel for meter wavelet coefficient and extracted signal segment
Loading spectrum carry out simultaneously delete, therefore, for multi-wheeler components loading spectrum when carrying out signal splicing, by each channel
The signal segment more extracted takes union to handle.
5. auto parts and components loading spectrum according to claim 2 is effectively compressed method, it is characterised in that: each type of small
Wave Decomposition includes an optimal Decomposition order, enables to final compressed signal compression ratio minimum, and damage maintenance dose is most
Greatly, statistical parameter and power spectral density aspect and original signal holding are almost the same, and the statistical parameter includes mean value, root mean square
Value and peak factor.
6. auto parts and components loading spectrum according to claim 4 is effectively compressed method, it is characterised in that: described uniaxial and more
The extracted signal segment of axis has been all made of the method for taking union and has been spliced, and obtains compressed signal and connects the most with original signal
Closely.
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| 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 |
| CN111581715B (en) * | 2020-03-23 | 2023-08-08 | 中国农业大学 | Rapid compression method for accelerating load spectrum of tractor part |
| CN112539942B (en) * | 2020-11-24 | 2023-06-20 | 上海电机学院 | Characteristic load identification and acceleration test load spectrum compiling method |
| CN114577487A (en) * | 2020-11-30 | 2022-06-03 | 宝能汽车集团有限公司 | Method for simplifying vehicle test conditions, storage medium and electronic device |
| CN114034492B (en) * | 2021-11-03 | 2024-04-05 | 交通运输部公路科学研究所 | Hilbert-Huang transform-based rapid compression method for load spectrum of automobile part |
| CN114235445A (en) * | 2021-11-26 | 2022-03-25 | 华南理工大学 | Vibration isolator road load spectrum time compression method based on S transformation |
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