CN112729859A - Electronic parking noise quality evaluation system and method - Google Patents
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Abstract
The invention provides an electronic parking noise quality evaluation system and method, which relate to the field of automobile NVH performance and comprise the following steps: the acquisition module is used for acquiring a plurality of groups of electronic parking noise data; the processing module is used for processing the multiple groups of electronic parking noise data to obtain corresponding psychoacoustic parameters; an evaluation module comprising: the subjective evaluation unit is used for carrying out subjective evaluation on the multiple groups of electronic parking noise data to obtain corresponding multiple groups of subjective scores; the calculation unit is used for calculating a weight coefficient of the psychoacoustic parameter according to the multiple groups of subjective scores and the psychoacoustic parameter; the construction unit is used for constructing a unified model formula according to the weight coefficient and the psychoacoustic parameters; and the prediction scoring unit is used for inputting the psychoacoustic parameters into a unified model formula to obtain multiple groups of prediction scores so as to evaluate the electronic parking noise data. The invention realizes the automatic detection of the electronic parking noise data, and saves manpower and material resources; and the accuracy rate of the prediction scoring is high, the processing efficiency is high, and the evaluation period is short.
Description
Technical Field
The invention relates to the field of vehicle NVH performance, in particular to an electronic parking noise quality evaluation system and method.
Background
Automotive Electronic Park (EPB) acoustic quality is one of the important noises affecting the performance of automotive Noise, Vibration and Harshness (Noise, Vibration, Harshness, NVH). In order to improve the NVH performance of automobiles and improve the product competitiveness, how to improve the acoustic characteristics of automobiles through the research on the EPB sound quality of automobiles becomes the key point of the current research and development of automobile technology. Currently, the method for detecting the EPB sound quality of the automobile with the highest accuracy is subjective evaluation. However, subjective evaluation is time-consuming and labor-consuming, the efficiency is too low, and the mass detection of the EPB sound quality of the automobile cannot be realized. Therefore, in the prior art, the quality of the EPB sound of the automobile is generally detected in a large scale by adopting an evaluation mode based on objective parameters such as A-weighted sound pressure level or loudness. However, the evaluation method using a single objective parameter has a defect of completeness, and cannot completely detect the EPB sound quality of the automobile, so that a technical scheme for completely detecting the EPB sound quality of the automobile in a large batch is lacked.
Disclosure of Invention
Aiming at the problems in the prior art, the invention provides an electronic parking noise quality evaluation system, which comprises:
the acquisition module is used for acquiring a plurality of groups of electronic parking noise data;
the processing module is connected with the acquisition module and used for processing the multiple groups of electronic parking noise data to obtain corresponding psychoacoustic parameters;
the evaluation module is respectively connected with the acquisition module and the processing module and comprises:
the subjective evaluation unit is used for receiving the subjective evaluation of the plurality of groups of electronic parking noise data by the user to obtain a plurality of corresponding groups of subjective scores;
the calculation unit is connected with the subjective scoring unit and used for calculating a weight coefficient of the psychoacoustic parameter according to the multiple groups of subjective scores and the psychoacoustic parameter;
the construction unit is connected with the calculation unit and is used for constructing a uniform model formula according to the weight coefficient and the psychoacoustic parameters;
and the prediction scoring unit is connected with the construction unit and used for inputting the psychoacoustic parameters into the unified model formula to obtain a plurality of groups of prediction scores so as to evaluate the electronic parking noise data.
Preferably, the system further comprises an evaluation output module, connected to the evaluation module, and configured to store the plurality of sets of prediction scores and analyze and process the plurality of sets of prediction scores for display.
Preferably, the evaluation output module includes:
the comparison unit is used for comparing the multiple groups of the predicted scores with a preset one-sound quality evaluation threshold value to obtain a comparison result;
the display processing unit is connected with the comparison unit and used for generating a display instruction according to the comparison result;
and the display unit is connected with the display processing unit and used for displaying the comparison result according to the display instruction.
Preferably, the evaluation output module further includes a storage unit for storing the plurality of sets of prediction scores for calling.
Preferably, the evaluation module further includes an analysis unit, respectively connected to the calculation unit, the subjective evaluation unit and the construction unit, for performing correlation analysis on the multiple sets of subjective evaluation and the psychoacoustic parameters to filter out the psychoacoustic parameters with poor correlation.
Preferably, the psychoacoustic parameters include:
loudness, and/or roughness, and/or pure tone ratio, and/or sharpness, and/or waviness.
Preferably, the unified model formula is:
SQ＝13.327-0.658*L-2.925*R；
wherein SQ is the prediction score, L is the loudness, and R is the coarseness.
Preferably, the acquisition module comprises:
the microphone is used for acquiring and obtaining analog data of a plurality of groups of electronic parking noises;
the data acquisition card is connected with the microphone and used for converting the analog data into digital signals as the electronic parking noise data;
the memory is connected with the data acquisition card and used for storing the electronic parking noise data;
and the calibrator is connected with the microphone and used for calibrating the microphone before data acquisition of the microphone.
An electronic parking noise quality evaluation method is applied to the electronic parking noise quality evaluation system, and comprises the following steps:
step S1, the electronic parking noise quality evaluation system collects multiple groups of electronic parking noise data;
step S2, the electronic parking noise quality evaluation system processes the multiple groups of electronic parking noise data to obtain corresponding psychoacoustic parameters;
step S3, the electronic parking noise quality evaluation system receives subjective evaluation of the multiple groups of electronic parking noise data by a user to obtain corresponding multiple groups of subjective scores, and calculates the weight coefficient of the psychoacoustic parameter according to the multiple groups of subjective scores and the psychoacoustic parameter;
and step S4, the electronic parking noise quality evaluation system constructs a unified model formula according to the weight coefficient and the psychoacoustic parameters, and then the psychoacoustic parameters are input into the unified model formula to obtain multiple groups of prediction scores so as to evaluate the electronic parking noise data.
The technical scheme has the following advantages or beneficial effects:
according to the technical scheme, the weight coefficient of the psychoacoustic parameter is calculated according to the subjective score and the psychoacoustic parameter, a unified model formula is further constructed according to the weight coefficient, the unified model formula only needs to be constructed once for the same project, various operations executed by a subjective score unit, a calculation unit, a construction unit and an analysis unit are skipped in subsequent detection, the psychoacoustic parameter is directly input into the unified model formula to obtain multiple groups of prediction scores, automatic detection of electronic parking noise data can be achieved, and manpower and material resources are saved; meanwhile, the accuracy of prediction scoring is high, the processing efficiency is high, the evaluation period is short, and online scoring can be realized.
Drawings
FIG. 1 is a schematic structural diagram of an electronic parking noise quality evaluation system according to a preferred embodiment of the present invention;
FIG. 2 is a diagram of subjective evaluation results in a preferred embodiment of the invention;
FIG. 3 is a diagram of psychoacoustic parameters in a preferred embodiment of the present invention;
FIG. 4 is a graph of the correlation coefficient between psychoacoustic parameters and subjective scores according to a preferred embodiment of the present invention;
FIG. 5 is a graph of regression results of a linear regression model in accordance with a preferred embodiment of the present invention;
FIG. 6 is a graph of prediction scores and corresponding residuals according to a preferred embodiment of the present invention;
fig. 7 is a flowchart of an electronic parking noise quality evaluation method according to a preferred embodiment of the present invention.
Detailed Description
The invention is described in detail below with reference to the figures and specific embodiments. The present invention is not limited to the embodiment, and other embodiments may be included in the scope of the present invention as long as the gist of the present invention is satisfied.
In accordance with the above-mentioned problems of the prior art, the present invention provides a system for evaluating the quality of electronic parking noise, as shown in fig. 1, comprising:
the acquisition module 1 is used for acquiring a plurality of groups of electronic parking noise data;
the processing module 2 is connected with the acquisition module 1 and is used for processing a plurality of groups of electronic parking noise data to obtain corresponding psychoacoustic parameters;
the evaluation module 3 is respectively connected with the acquisition module 1 and the processing module 2, and comprises:
the subjective evaluation unit 31 is configured to receive subjective evaluation performed by the user on the multiple sets of electronic parking noise data to obtain corresponding multiple sets of subjective scores;
the calculating unit 32 is connected with the subjective scoring unit 31 and used for calculating a weight coefficient of the psychoacoustic parameter according to the multiple groups of subjective scores and the psychoacoustic parameter;
the construction unit 33 is connected with the calculation unit 32 and is used for constructing a uniform model formula according to the weight coefficient and the psychoacoustic parameters;
and the prediction scoring unit 34 is connected with the construction unit 33 and used for inputting the psychoacoustic parameters into a unified model formula to obtain multiple groups of prediction scores so as to evaluate the electronic parking noise data.
Specifically, in the present embodiment, the collection of multiple sets of electronic parking noise data is realized by the collection module 1. And then the processing module 2 calculates a plurality of groups of electronic parking noise data to obtain psychoacoustic parameters. The evaluation module 3 calculates weighting coefficients of the psychoacoustic parameters and adds the weighting coefficients to obtain a plurality of groups of prediction scores so as to evaluate the electronic parking noise data.
In a preferred embodiment, the acquisition module 1 acquires 10 sets of electronic parking noise data. The subjective evaluation unit 11 subjectively evaluates 10 groups of electronic parking noise data acquired by the acquisition module 1 by a scoring system using more than 10 subjective evaluation subgroups, and obtains 10 groups of subjective scores by averaging, as shown in fig. 2.
Where # 1 to # 10 are group numbers, a to J are serial numbers of the electronic parking noise data, and avg is an average value of subjective scores of the electronic parking noise data of each group.
The processing module 2 performs psychoacoustic parameter calculation on the 10 groups of electronic parking noise data acquired by the acquisition module 1 to obtain psychoacoustic parameters. Wherein the psychoacoustic parameters include: loudness, and/or roughness, and/or pure tone ratio, and/or sharpness, and/or waviness, as shown in fig. 3.
Wherein, 1# to 10# are group numbers, L/sones, R/asper, P/^2, S/acum and F/vacil respectively represent loudness, roughness, pure tone ratio, sharpness and fluctuation.
Preferably, the evaluation module 3 further includes an analysis unit 35, which is respectively connected to the calculation unit 32, the subjective score unit 31 and the construction unit 33, and configured to perform correlation analysis on the multiple sets of subjective scores and psychoacoustic parameters to filter out the psychoacoustic parameters with poor correlation.
Specifically, in this embodiment, the analysis unit 35 performs correlation analysis on all the calculated psychoacoustic parameters and the 10 sets of subjective scores to obtain a correlation coefficient between the psychoacoustic parameters and the subjective scores, as shown in fig. 4. And eliminating psychoacoustic parameters with correlation coefficients larger than-0.7 and smaller than 0.7 to obtain the screened psychoacoustic parameters. By screening the psychoacoustic parameters, the evaluation precision and the evaluation efficiency of the evaluation module 3 are effectively improved, and the evaluation period is shortened. Wherein the psychoacoustic parameters after screening include: loudness and roughness.
The calculation unit 32 calculates a weight coefficient of the psychoacoustic parameters after the screening by linear regression using the subjective score as a target function and the psychoacoustic parameters after the screening as target variables. The result of the regression calculation is shown in fig. 5, where Multiple R represents the regression analysis correlation coefficient, Adjusted R Square represents the calibration decision coefficient, R Square represents the accuracy of the fitting of the linear regression model, the closer to 1 the R Square, the higher the degree of fitting, and in fig. 5, the value of R Square is 0.979, which shows that the degree of fitting of the linear regression model is high. P-value is an assumed value of the linear regression model, wherein the closer the P-value is to 0, the more effective the regression calculation result of the linear regression model is. In fig. 5, Coefficients represent weight Coefficients, Intercept represents Intercept, the weight coefficient of loudness is-0.658, and the weight coefficient of coarseness is-2.925. The construction unit 33 adds the corresponding weight coefficient and intercept to the filtered loudness and roughness of the psychoacoustic parameters to obtain a unified model formula:
SQ＝13.327-0.658*L-2.925*R；
where SQ is the prediction score, L is loudness, and R is coarseness.
The prediction scoring unit 34 inputs the collected and processed loudness and roughness into a unified model formula to obtain multiple sets of prediction scores, as shown in fig. 6.
The residual error represents the difference between the subjective score and the prediction score of each group, and when the residual error is closer to 0, the subjective score is closer to the prediction score, and the accuracy of the unified model formula is higher.
According to the technical scheme, the weight coefficient of the psychoacoustic parameter is calculated according to the subjective score and the psychoacoustic parameter, a unified model formula is further constructed according to the weight coefficient, the unified model formula only needs to be constructed once for the same project, various operations executed by the subjective score unit 31, the calculation unit 32, the construction unit 33 and the analysis unit 35 are skipped in subsequent detection, the psychoacoustic parameter is directly input into the unified model formula to obtain multiple groups of prediction scores, automatic detection of electronic parking noise data is further achieved, and manpower and material resources are saved; meanwhile, the accuracy of prediction scoring is high, the processing efficiency is high, the evaluation period is short, and online scoring can be realized.
In a preferred embodiment of the present invention, the system further comprises an evaluation output module 4 connected to the evaluation module 3, for storing the plurality of sets of prediction scores and analyzing and processing the plurality of sets of prediction scores for display.
In a preferred embodiment of the present invention, the evaluation output module 4 includes:
a comparing unit 41, configured to compare the multiple sets of prediction scores with a preset first sound quality evaluation threshold and obtain a comparison result;
the display processing unit 42 is connected with the comparison unit 41 and used for generating a display instruction according to the comparison result;
and the display unit 43 is connected to the display processing unit 42 and is used for displaying the comparison result according to the display instruction.
Specifically, in this embodiment, the evaluation output module 4 may be a computer, the display unit 43 may be a display screen of the computer, and the sound quality evaluation threshold may be pre-stored in a storage container inside the computer. When the comparison result shows that the prediction score is smaller than the sound quality evaluation threshold value, the electronic parking noise corresponding to the prediction score is unqualified, at this time, the display processing unit 42 generates an unqualified display instruction, and the display unit 43 displays that the electronic parking noise is unqualified in quality; when the comparison result indicates that the prediction score is not less than the sound quality evaluation threshold, it indicates that the electronic parking noise corresponding to the prediction score is qualified in quality, and at this time, the display processing unit 42 generates a qualified display instruction, and the display unit 43 displays "the electronic parking noise is qualified in quality".
In the preferred embodiment of the present invention, the evaluation output module 4 further includes a storage unit 44 for storing a plurality of sets of prediction scores for calling.
Specifically, in this embodiment, the storage unit 44 may adopt a computer hard disk, store the multiple sets of prediction scores in the computer hard disk, and call the prediction scores in the computer hard disk when the prediction scores need to be checked.
In a preferred embodiment of the present invention, the acquisition module 1 comprises:
the microphone 11 is used for acquiring analog data of a plurality of groups of electronic parking noises;
the data acquisition card 12 is connected with the microphone 11 and used for converting the analog data into digital signals as electronic parking noise data;
the memory 13 is connected with the data acquisition card 12 and used for storing the electronic parking noise data;
and the calibrator 14 is connected with the microphone 11 and used for calibrating the microphone before data acquisition of the microphone 11.
Specifically, in the present embodiment, the microphone 11 is installed at a 45 ° distance from the horizontal direction of the electronic parking brake system, and analog data of a plurality of sets of electronic parking noise is collected by the microphone 11. The data acquisition card 12 converts the analog data of the electronic parking noise acquired by the microphone 11 into a digital signal as electronic parking noise data and stores the electronic parking noise data in the memory 13. Preferably, the memory 13 may be a computer equipped with data acquisition software, and the electronic parking noise data is recorded and stored by the data acquisition software of the computer. The calibrator 14 calibrates the microphone 11 through the calibrator 14 before the microphone 11 performs data acquisition, so that the accuracy of the acquired data of the electronic parking noise is effectively improved.
An electronic parking noise quality evaluation method is applied to the electronic parking noise quality evaluation system, and as shown in fig. 7, the electronic parking noise quality evaluation method includes the following steps:
step S1, the electronic parking noise quality evaluation system collects multiple groups of electronic parking noise data;
step S2, the electronic parking noise quality evaluation system processes a plurality of groups of electronic parking noise data to obtain corresponding psychoacoustic parameters;
step S3, the electronic parking noise quality evaluation system receives subjective evaluation of a plurality of groups of electronic parking noise data by a user to obtain a plurality of corresponding groups of subjective scores, and calculates a weight coefficient of a psychoacoustic parameter according to the plurality of groups of subjective scores and the psychoacoustic parameter;
and step S4, the electronic parking noise quality evaluation system constructs a unified model formula according to the weight coefficient and the psychoacoustic parameters, and then the psychoacoustic parameters are input into the unified model formula to obtain multiple groups of prediction scores so as to evaluate the electronic parking noise data.
While the invention has been described with reference to a preferred embodiment, it will be understood by those skilled in the art that various changes in form and detail may be made therein without departing from the spirit and scope of the invention.
Claims (9)
1. An electronic parking noise quality evaluation system is characterized by specifically comprising:
the acquisition module is used for acquiring a plurality of groups of electronic parking noise data;
the processing module is connected with the acquisition module and used for processing the multiple groups of electronic parking noise data to obtain corresponding psychoacoustic parameters;
the evaluation module is respectively connected with the acquisition module and the processing module and comprises:
the subjective evaluation unit is used for receiving the subjective evaluation of the plurality of groups of electronic parking noise data by the user to obtain a plurality of corresponding groups of subjective scores;
the calculation unit is connected with the subjective scoring unit and used for calculating a weight coefficient of the psychoacoustic parameter according to the multiple groups of subjective scores and the psychoacoustic parameter;
the construction unit is connected with the calculation unit and is used for constructing a uniform model formula according to the weight coefficient and the psychoacoustic parameters;
and the prediction scoring unit is connected with the construction unit and used for inputting the psychoacoustic parameters into the unified model formula to obtain a plurality of groups of prediction scores so as to evaluate the electronic parking noise data.
2. The system for evaluating the quality of electronic parking noise according to claim 1, further comprising an evaluation output module connected to the evaluation module for saving the plurality of sets of prediction scores and analyzing and displaying the plurality of sets of prediction scores.
3. The electronic parking noise quality evaluation system according to claim 2, wherein the evaluation output module includes:
the comparison unit is used for comparing the multiple groups of the predicted scores with a preset one-sound quality evaluation threshold value to obtain a comparison result;
the display processing unit is connected with the comparison unit and used for generating a display instruction according to the comparison result;
and the display unit is connected with the display processing unit and used for displaying the comparison result according to the display instruction.
4. The system of claim 2, wherein the evaluation output module further comprises a storage unit for storing the plurality of sets of prediction scores for calling.
5. The system according to claim 1, wherein the evaluation module further comprises an analysis unit, respectively connected to the calculation unit, the subjective evaluation unit and the construction unit, for performing correlation analysis on the multiple sets of subjective evaluations and the psychoacoustic parameters to filter out the psychoacoustic parameters with poor correlation.
6. The electronic parking noise quality evaluation system according to claim 1, wherein the psychoacoustic parameters include:
loudness, and/or roughness, and/or pure tone ratio, and/or sharpness, and/or waviness.
7. The electronic parking noise quality evaluation system according to claim 6, wherein the unified model formula is:
SQ＝13.327-0.658*L-2.925*R；
wherein SQ is the prediction score, L is the loudness, and R is the coarseness.
8. The electronic parking noise quality evaluation system according to claim 1, wherein the acquisition module comprises:
the microphone is used for acquiring and obtaining analog data of a plurality of groups of electronic parking noises;
the data acquisition card is connected with the microphone and used for converting the analog data into digital signals as the electronic parking noise data;
the memory is connected with the data acquisition card and used for storing the electronic parking noise data;
and the calibrator is connected with the microphone and used for calibrating the sensor before the microphone acquires data.
9. An electronic parking noise quality evaluation method applied to the electronic parking noise quality evaluation system according to any one of claims 1 to 8, comprising the steps of:
step S1, the electronic parking noise quality evaluation system collects multiple groups of electronic parking noise data;
step S2, the electronic parking noise quality evaluation system processes the multiple groups of electronic parking noise data to obtain corresponding psychoacoustic parameters;
step S3, the electronic parking noise quality evaluation system receives subjective evaluation of the multiple groups of electronic parking noise data by a user to obtain corresponding multiple groups of subjective scores, and calculates the weight coefficient of the psychoacoustic parameter according to the multiple groups of subjective scores and the psychoacoustic parameter;
and step S4, the electronic parking noise quality evaluation system constructs a unified model formula according to the weight coefficient and the psychoacoustic parameters, and then the psychoacoustic parameters are input into the unified model formula to obtain multiple groups of prediction scores so as to evaluate the electronic parking noise data.
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| CN113432888A (en) * | 2021-06-23 | 2021-09-24 | 中国第一汽车股份有限公司 | Method for determining sound evaluation index of wiper system |
| CN113436647A (en) * | 2021-06-23 | 2021-09-24 | 中国第一汽车股份有限公司 | Method and device for determining sound evaluation index of car window lifting system |
| CN113933064A (en) * | 2021-09-18 | 2022-01-14 | 北京车和家信息技术有限公司 | Test evaluation method, device, equipment and storage medium |
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| CN113299261A (en) * | 2021-05-21 | 2021-08-24 | 北京安声浩朗科技有限公司 | Active noise reduction method and device, earphone, electronic equipment and readable storage medium |
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| CN113432888A (en) * | 2021-06-23 | 2021-09-24 | 中国第一汽车股份有限公司 | Method for determining sound evaluation index of wiper system |
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| CN113436647B (en) * | 2021-06-23 | 2022-07-01 | 中国第一汽车股份有限公司 | Method and device for determining sound evaluation index of vehicle window lifting system |
| CN113933064A (en) * | 2021-09-18 | 2022-01-14 | 北京车和家信息技术有限公司 | Test evaluation method, device, equipment and storage medium |
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