CN114544194B - Vehicle road noise evaluation method based on spectrum analysis - Google Patents
Vehicle road noise evaluation method based on spectrum analysis Download PDFInfo
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Abstract
The invention discloses a vehicle road noise evaluation method based on spectrum analysis, which comprises the steps of carrying out subjective evaluation on road noise manually and acquiring road noise data through acquisition equipment; and then carrying out frequency spectrum analysis on the road noise data, dividing the road noise data into a plurality of frequency bands, calculating the root mean square value of the road noise data by frequency division, carrying out normalization processing on the root mean square value of the road noise data, carrying out linear regression analysis on the normalized data and the subjectively evaluated data, and further obtaining the influence degree of the road noise of different frequency bands on the subjective evaluation.
Description
Technical Field
The invention relates to the field of road noise spectrum analysis, in particular to a vehicle road noise evaluation method based on spectrum analysis.
Background
Road noise is the most common noise in vehicle driving, and road noise performance development is the most common item in vehicle NVH performance development. In road noise evaluation, an A weight-counting root mean square value in the whole frequency band of test sound is usually used as a development index, namely an A weight-counting OA value, but in practice, the size of the road noise OA value is not completely consistent with the road noise perception of a driver, and the road noise level of a vehicle cannot be represented, so that the frequency components of road noise are required to be analyzed, an accurate relation between the subjective evaluation of the road noise and objective test frequency spectrum is established, the key frequency of road noise development can be clarified, and the road noise performance meeting the requirement is developed.
Disclosure of Invention
The invention aims to provide a vehicle road noise evaluation method based on spectrum analysis, which is used for accurately calculating the difference of contribution amounts of different frequency band noises in road noise to subjective feelings of people.
In order to solve the technical problems, the invention provides a technical scheme that: a vehicle road noise evaluation method based on spectrum analysis comprises the following steps,
s1, enabling a plurality of test vehicles to run on a test pavement, enabling test personnel to be located in a passenger cabin, and giving subjective evaluation data according to road noise when the vehicles run; collecting road noise data of a driving position by using collecting equipment; each test vehicle collects a plurality of groups of road noise data and subjective evaluation data;
for the test data of each test vehicle, the following steps are performed,
s101, preprocessing subjective evaluation data to obtain final subjective evaluation data;
s102, screening road noise data, carrying out spectrum analysis on each group of screened road noise data, dividing a plurality of frequency bands, and calculating root mean square values of the road noise data of each frequency band; averaging the root mean square value frequency bands of the road noise data of each group as the root mean square value of the road noise data of each frequency band of the test vehicle;
s2, normalizing root mean square values of road noise data of all the tested vehicles in each frequency range;
s3, performing multiple linear regression analysis according to final subjective evaluation data of all the test vehicles and normalized root mean square values of the road noise data of each frequency band, and obtaining a functional relation and a linear correlation coefficient between the final subjective evaluation data and the normalized root mean square values of the road noise data of each frequency band;
s4, obtaining the sensitivity degree of the passenger to noise in different frequency bands according to the functional relation obtained in the S3;
the normalization processing for a certain frequency band in S2 is as follows:
wherein: x is X i ' is the normalized result of test vehicle i in that band, X i To test the road noise of vehicle iRoot mean square value of data, X min Is the minimum value of the root mean square value of the road noise data of the frequency band, X max The maximum value of the root mean square value of the road noise data of the frequency band.
According to the scheme, the test pavement is a rough asphalt pavement, and the running speed during the test is 60km/h.
According to the scheme, the acquisition equipment comprises LMS data acquisition equipment and a B & K microphone, and the set noise analysis frequency is 8000Hz.
According to the scheme, the number of the test vehicles is 15, and each test vehicle is provided with 5 groups of subjective evaluation data and road noise data.
According to the above scheme, the preprocessing process for subjective evaluation data in S101 specifically includes removing the maximum value and the minimum value in all subjective evaluation data of a certain test vehicle, calculating the average value of the remaining values, and taking the average value as the final subjective evaluation data of the vehicle.
According to the above scheme, the screening process of the road noise data in S102 specifically includes selecting 3 sets of data with highest consistency from the 5 sets of road noise data measured by each test vehicle.
According to the scheme, the frequency bands comprise low frequency, medium and high frequency and the corresponding frequencies are respectively 10-100 Hz, 100-500 Hz, 500-1600 Hz and 1600-8000 Hz.
The beneficial effects of the invention are as follows: dividing road noise data into different frequency bands, respectively calculating root mean square values of the frequency bands, and solving a functional relation between the root mean square values of the frequency bands and subjective evaluation data, so as to obtain the sensitivity degree of passengers to road noise of the different frequency bands; compared with the function relation between the calculated full-frequency-band root mean square value and the subjective evaluation data in the prior art, the method improves the linear relation degree between the road noise data and the subjective evaluation, so that the road noise frequency band which is more sensitive to passengers can be focused in the subsequent vehicle development process.
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Fig. 1 is a flowchart of a vehicle road noise evaluation method based on spectrum analysis according to an embodiment of the present invention.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present disclosure more apparent, the technical solutions of the embodiments of the present disclosure will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present disclosure. It will be apparent that the described embodiments are some, but not all, of the embodiments of the present disclosure. All other embodiments, which can be made by one of ordinary skill in the art without the need for inventive faculty, are within the scope of the present disclosure, based on the described embodiments of the present disclosure.
Referring to fig. 1, a vehicle road noise evaluation method based on spectrum analysis includes the steps of,
s1, enabling a plurality of test vehicles to run on a test pavement, enabling test personnel to be located in a passenger cabin, and giving subjective evaluation data according to road noise when the vehicles run; collecting road noise data of a driving position by using collecting equipment; each test vehicle collects a plurality of groups of road noise data and subjective evaluation data;
for the test data of each test vehicle, the following steps are performed,
s101, preprocessing subjective evaluation data to obtain final subjective evaluation data;
s102, screening road noise data, carrying out spectrum analysis on each group of screened road noise data, dividing a plurality of frequency bands, and calculating root mean square values of the road noise data of each frequency band; averaging the root mean square value frequency bands of the road noise data of each group as the root mean square value of the road noise data of each frequency band of the test vehicle;
s2, normalizing root mean square values of road noise data of all the tested vehicles in each frequency range;
s3, performing multiple linear regression analysis according to final subjective evaluation data of all the test vehicles and normalized root mean square values of the road noise data of each frequency band, and obtaining a functional relation and a linear correlation coefficient between the final subjective evaluation data and the normalized root mean square values of the road noise data of each frequency band;
and S4, obtaining the sensitivity degree of the passenger to the noise of different frequency bands according to the functional relation obtained in the step S3.
Further, the test pavement is a rough asphalt pavement, and the running speed during the test is 60km/h.
Further, the acquisition device comprises an LMS data acquisition device and a B & K microphone, and the set noise analysis frequency is 8000Hz.
Further, the number of the test vehicles is 15, and each test vehicle is provided with 5 groups of subjective evaluation data and road noise data.
Further, the preprocessing process for subjective evaluation data in S101 specifically includes removing the maximum value and the minimum value in all subjective evaluation data of a certain test vehicle, and calculating an average value of the remaining values, where the average value is used as final subjective evaluation data of the vehicle.
Further, the screening process of the road noise data in S102 specifically includes selecting 3 sets of data with highest consistency from the 5 sets of road noise data measured by each test vehicle.
Further, the frequency bands comprise low frequency, medium and high frequency and the corresponding frequencies are respectively 10-100 Hz, 100-500 Hz, 500-1600 Hz and 1600-8000 Hz.
Further, the normalization processing for a certain frequency band in S2 is as follows:
wherein: x is X i ' is the normalized result of test vehicle i in that band, X i To test the root mean square value, X, of road noise data of vehicle i min Is the minimum value of the root mean square value of the road noise data of the frequency band, X max The maximum value of the root mean square value of the road noise data of the frequency band.
According to the scheme, root mean square data of each frequency band of road noise data of 15 test vehicles are shown in the following table:
after normalizing the data in the table, the following results are obtained:
in the prior art, unitary linear regression analysis is carried out on normalized full-band root mean square values and final subjective evaluation data, and the obtained functional relationship is as follows:
Y 1 ＝-0.21X OA +7.32
R 1 2 ＝0.78
wherein Y is 1 For final subjective evaluation data, X OA Road noise data root mean square value of 10-8000 Hz full frequency band, R 1 2 Is Y 1 And X is OA Linear relation coefficient between the two.
In this embodiment, the normalized root mean square value of each frequency band and the final subjective evaluation data are subjected to multiple linear regression analysis, and the obtained functional relationship is as follows:
Y 2 ＝-0.11X RMS1 -0.09X RMS2 -0.02X RMS3 -0.07X RMS4 +7.67
R 2 2 ＝0.85
wherein Y is 2 For final subjective evaluation data, X RMS1 、X RMS2 、X RMS3 、X RMS4 Road noise data root mean square value R of 10-100 Hz frequency band, 100-500 Hz frequency band, 500-1600 Hz frequency band, 1600-8000 Hz frequency band 2 2 Root mean square value and Y for the path noise data of each frequency band 2 Linear relation coefficient between the two. It can be seen that the obtained functional relationship has a higher linear dependence compared to the prior art by using the method of the present embodiment.
By mixing the above Y 2 And (3) carrying out duty ratio analysis on coefficients of all variables in the function to obtain the contribution degree of the road noise data of all frequency bands to subjective evaluation:
10～100contribution a of the Hz frequency band 1 ：
Contribution a in the 100-500 Hz frequency band 2 ：
Contribution a of 500-1600 Hz frequency band 3 ：
Contribution a in 1600-8000 Hz frequency band 4 ：
From the above contribution, it can be known that the occupant is more sensitive to low frequency noise of 10-100 Hz and medium-low frequency noise of 100-500 Hz, then high frequency noise of 1600-8000 Hz, and finally medium-high frequency noise; the conclusion can guide the road noise in the subsequent vehicle research and development process to pay attention to the frequency band.
The foregoing description is only illustrative of the present invention and is not intended to limit the scope of the invention, and all equivalent structures or equivalent processes or direct or indirect application in other related technical fields are included in the scope of the present invention.
Claims (7)
1. A vehicle road noise evaluation method based on spectrum analysis is characterized in that: comprises the steps of,
s1, enabling a plurality of test vehicles to run on a test pavement, enabling test personnel to be located in a passenger cabin, and giving subjective evaluation data according to road noise when the vehicles run; collecting road noise data of a driving position by using collecting equipment; each test vehicle collects a plurality of groups of road noise data and subjective evaluation data;
for the test data of each test vehicle, the following steps are performed,
s101, preprocessing subjective evaluation data to obtain final subjective evaluation data;
s102, screening road noise data, carrying out spectrum analysis on each group of screened road noise data, dividing a plurality of frequency bands, and calculating root mean square values of the road noise data of each frequency band; averaging the root mean square value frequency bands of the road noise data of each group as the root mean square value of the road noise data of each frequency band of the test vehicle;
s2, normalizing root mean square values of road noise data of all the tested vehicles in each frequency range;
s3, performing multiple linear regression analysis according to final subjective evaluation data of all the test vehicles and normalized root mean square values of the road noise data of each frequency band, and obtaining a functional relation and a linear correlation coefficient between the final subjective evaluation data and the normalized root mean square values of the road noise data of each frequency band;
s4, obtaining the sensitivity degree of the passenger to noise in different frequency bands according to the functional relation obtained in the S3;
the normalization processing for a certain frequency band in S2 is as follows:
wherein: x is X i ' is the normalized result of test vehicle i in that band, X i To test the root mean square value, X, of road noise data of vehicle i min Is the minimum value of the root mean square value of the road noise data of the frequency band, X max The maximum value of the root mean square value of the road noise data of the frequency band.
2. The method for evaluating vehicle road noise based on spectrum analysis according to claim 1, wherein: the test pavement is a rough asphalt pavement, and the running speed in the test is 60km/h.
3. The method for evaluating vehicle road noise based on spectrum analysis according to claim 1, wherein: the acquisition equipment comprises LMS data acquisition equipment and a B & K microphone, and the set noise analysis frequency is 8000Hz.
4. The method for evaluating vehicle road noise based on spectrum analysis according to claim 1, wherein: the number of the test vehicles is 15, and each test vehicle is provided with 5 groups of subjective evaluation data and road noise data.
5. The method for evaluating vehicle road noise based on spectrum analysis according to claim 1, wherein: the preprocessing process for subjective evaluation data in S101 specifically includes removing the maximum value and the minimum value in all subjective evaluation data of a certain test vehicle, calculating an average value of the rest values, and taking the average value as final subjective evaluation data of the vehicle.
6. The method for evaluating vehicle road noise based on spectrum analysis according to claim 4, wherein: the screening process of the road noise data in S102 specifically includes selecting 3 groups of data with highest consistency from 5 groups of road noise data measured by each test vehicle.
7. The method for evaluating vehicle road noise based on spectrum analysis according to claim 1, wherein: the frequency bands comprise low frequency, medium and high frequency, and the corresponding frequencies are respectively 10-100 Hz, 100-500 Hz, 500-1600 Hz and 1600-8000 Hz.
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