CN115346560A - Sound level weighting method for subjective annoyance degree comparison of train station hall - Google Patents
Sound level weighting method for subjective annoyance degree comparison of train station hall Download PDFInfo
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Abstract
The invention discloses a sound level weighting method for subjective annoyance comparison of a train station hall, which is characterized by comprising the following steps of: s1: acquiring a traffic track noise data set to produce an experimental signal; s2: subjective annoyance evaluation is carried out on the experimenters by using the experimental signals; s3: carrying out mathematical modeling on the annoyance evaluation data; s4: verifying the evaluation index; s5: a new evaluation network is proposed. The invention provides a method for quantifying the annoyance degree of the supervisor for improving the waiting environment, and is beneficial to the noise management of the train exhibition hall.
Description
Technical Field
The invention relates to the technical field of noise management, in particular to a sound level weighting method for subjective annoyance comparison of a train station hall.
Background
With the continuous expansion of urban scale and the increasing busy urban traffic, the influence of traffic noise on the health of people is generally concerned.
The rail transit noise evaluation research is to carry out prediction and evaluation on the construction process of a rail construction project and the sound environment caused by the construction process, and provide various prevention and control strategies according to the evaluation result to provide decision bases for relevant departments, and the basic purpose of the rail transit noise evaluation research is to reduce the noise pollution caused by the road construction project to the level allowed by the current standard, improve the living environment of residents, and provide scientific bases for optimizing site selection, building material selection, reasonable layout and urban planning of the construction project. The influence of noise on residents is manifold, and the hearing is reduced when the residents are exposed to a strong noise environment, and meanwhile, the influence on the physiology, the psychology and the normal life of people is generated. The traffic noise is random noise with large sound level fluctuation, and how to correctly evaluate and measure the annoyance caused by the random noise is always a difficult point for the research of acoustics workers in various countries.
In the related art, the a-weighted sound level significantly underestimates the influence of the low-frequency component of noise on the annoyance level, which cannot correctly reflect the subjective annoyance level of a resident when evaluating noise radiation caused by rail vibration. Therefore, the degree of low-frequency noise caused by rail vibration should be particularly studied to establish an evaluation parameter that can appropriately reflect the degree of low-frequency noise.
Disclosure of Invention
In view of the above problems, the present invention provides a sound level weighting method for subjective annoyance level comparison in a train station hall, and proposes a new method for quantifying the annoyance level of a supervisor to solve the above problems.
The invention provides the following technical scheme:
a sound level weighting method for subjective annoyance comparison of a train station hall is characterized by comprising the following steps: s1: acquiring a traffic track noise data set to produce an experimental signal; s2: subjective annoyance evaluation is carried out on the experimenters by using the experimental signals; s3: carrying out mathematical modeling on the annoyance evaluation data; s4: verifying the evaluation index; s5: a new evaluation network is proposed.
The step S1 specifically comprises the following steps: the noise data sets are filtered at different frequencies by filters and the filtered signals are adjusted to corresponding loudness levels. The loudness level after the corresponding adjustment of the filter filtering frequency band from 100Hz to 1000Hz is from 55phon to 80phon. Preferably, the experimental signal length is 4-6s.
The step S2 specifically comprises the following steps: and adjusting the angle and the distance between a loudspeaker playing the experimental signal and the subject, and recording the annoyance evaluation value of the subject under the experimental signal.
The step S3 specifically comprises the following steps: selecting a psychoacoustic index: and performing linear regression analysis on loudness, sharpness, roughness, fluctuation intensity and linear sound pressure level, respectively drawing fitting curves of noise loudness level and annoyance level of each frequency and noise frequency and annoyance level of each loudness level under different frequency conditions, and calculating corresponding Pearson correlation coefficients.
The step S4 specifically comprises the following steps: and obtaining an evaluation value of the non-calculated noise sample through the mathematical model obtained in the step S3, and comparing the result with a subjective evaluation value.
Step S4 is represented by the formula:
unbiased form of the predictive mathematical model and predictive accuracy, where y k The actual experimental value is the original annoyance degree; z is a radical of formula k Is the predicted value of the built model; k =1,2 … …, n is the number of noise samples.
The step S5 specifically comprises the following steps: and calculating different loudness levels and linear sound levels of the noise with the same annoyance degree under different frequencies according to the fitted curves of the loudness level and the annoyance degree of the noise with each frequency and the noise frequency and the annoyance degree of each loudness level, and subtracting the sound pressure level measured by the test signal with other frequencies by taking the sound pressure level of 1000Hz as a reference to obtain a new weight.
The beneficial technical effects of the invention are as follows:
compared with the existing A-weighted sound pressure level, the technical scheme provided by the invention can reflect the influence of low-frequency noise on the annoyance degree; in addition, the noise evaluation research of the exhibition hall based on the psychoacoustic indexes is beneficial to quantitatively evaluating the traffic noise and provides a basis for sound environment management.
Drawings
FIG. 1 is a schematic flow chart of a sound level weighting method for subjective annoyance level comparison in a train station hall according to an embodiment of the present invention;
fig. 2 is a fitting curve of the loudness level of each frequency noise and the average value of the annoyance degree in the sound level weighting method for the subjective annoyance degree comparison of the train station hall according to the embodiment of the present invention;
fig. 3 is a fitting curve of each loudness noise frequency and an average value of the annoyance degree in the sound level weighting method for train station hall subjective annoyance degree comparison according to the embodiment of the present invention.
Detailed Description
The following examples are given to illustrate the present invention in detail, and the following examples are given to illustrate the detailed embodiments and specific procedures of the present invention, but the scope of the present invention is not limited to the following examples. All other embodiments obtained by a person of ordinary skill in the art based on the embodiments in the present application without making any creative effort belong to the protection scope of the present application.
Reference herein to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment can be included in at least one embodiment of the application. The appearances of the phrase in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. Those skilled in the art will explicitly and implicitly appreciate that the embodiments described herein may be combined with other embodiments without conflict.
Examples
As shown in fig. 1, in a preferred embodiment of the present invention, a sound level weighting method for subjective annoyance level comparison in a train station hall is provided, which comprises the following steps: s1: acquiring a traffic track noise data set to produce an experimental signal; s2: subjective annoyance evaluation is carried out on the experimenters by using the experimental signals; s3: carrying out mathematical modeling on the annoyance evaluation data; s4: verifying the evaluation index; s5: a new evaluation network is proposed.
The step S1 specifically comprises the following steps: the noise data sets are filtered at different frequencies by filters and the filtered signals are adjusted to corresponding loudness levels. The loudness levels after corresponding adjustment of the filter filtering frequency bands at 100Hz, 160Hz, 200Hz, 250Hz, 500Hz and 1000Hz are 55phon, 60phon, 65phon, 70phon, 75phon and 80phon. The experimental signal length was 5s.
The step S2 specifically comprises the following steps: and adjusting the angle and the distance between a loudspeaker playing the experimental signal and the subject, and recording the annoyance evaluation value of the subject under the experimental signal. As shown in table 1:
table 1: subjective noise annoyance degree scoring table
| Score value | Description of the invention |
| 1 | Without |
| 2 | Slightly worried but does not affect |
| 3 | Annoying, but acceptable |
| 4 | Is very annoying and causes strong |
| 5 | Completely unacceptable, the subject does not want to be exposed to such noise |
As shown in fig. 2 and 3, step S3 specifically includes: selecting a psychoacoustic index: and performing linear regression analysis on the loudness, the acutance, the roughness, the fluctuation intensity and the linear sound pressure level, respectively drawing a fitting curve of the loudness level and the annoyance degree of each frequency noise and the noise frequency and the annoyance degree of each loudness level under different frequency conditions, and calculating corresponding Pearson correlation coefficients. The calculation process of the fitting curve is shown in tables 2 and 3:
table 2: fitting equation of loudness level and annoyance degree of noise of each frequency
| Experimental signals | Fitting curve | Fitting equation | Pearson's correlation coefficient |
| 100Hz | Linear fitting | Y＝0.1726x-8.3608 | 0.8863 |
| 160Hz | Linear fitting | Y＝0.1790x-8.4190 | 0.8995 |
| 200Hz | Linear fitting | Y＝0.2019x-9.8507 | 0.8943 |
| 250Hz | Linear fitting | Y＝0.1453x-6.9439 | 0.8802 |
| 500Hz | Linear fitting | Y＝0.1682x-7.5978 | 0.8554 |
| 1000Hz | Linear fitting | Y＝0.1885x-9.1915 | 0.8883 |
Table 3: fitting curve of noise frequency and annoyance degree of each loudness level
| Experimental signals | Fitting curve | Fitting equation | Pearson's correlation coefficient |
| 100Hz | Linear fitting | Y＝0.0323x-0.7968 | 0.7173 |
| 160Hz | Linear fitting | Y＝0.0457x-1.6412 | 0.7855 |
| 200Hz | Linear fitting | Y＝0.0552x-2.0063 | 0.8448 |
| 250Hz | Linear fitting | Y＝0.0285x-0.6507 | 0.7858 |
| 500Hz | Linear fitting | Y＝0.0380x-1.1269 | 0.88273 |
| 1000Hz | Linear fitting | Y＝0.0438x-2.1238 | 0.72065 |
TABLE 3
And obtaining an evaluation value of the non-calculated noise sample through the mathematical model obtained in the step S3, and comparing the result with the subjective evaluation value.
Step S4 is represented by the formula:
unbiased form of the predictive mathematical model and predictive accuracy, where y k The actual experimental value is the original annoyance degree; z is a radical of k Is the predicted value of the built model; k =1,2 … …, n is the number of noise samples.
Step S5 specifically includes: and calculating different loudness levels and linear sound levels of the noise with the same annoyance degree under different frequencies according to the fitted curves of the loudness level and the annoyance degree of the noise with each frequency and the noise frequency and the annoyance degree of each loudness level, and subtracting the sound pressure level measured by the test signal with other frequencies by taking the sound pressure level of 1000Hz as a reference to obtain a new weight. Where Y =3, that is, when the quantization annoyance degree is 3, the new weighting network of the annoyance degree is shown in table 4:
table 4: noise loudness level of each frequency under equal annoyance
The embodiment of the invention provides a method for quantifying the annoyance degree of a supervisor for improving the waiting environment, and is favorable for noise management of a train exhibition hall.
The foregoing detailed description of the preferred embodiments of the invention has been presented. It should be understood that numerous modifications and variations could be devised by those skilled in the art in light of the present teachings without departing from the inventive concepts. Therefore, the technical solutions available to those skilled in the art through logic analysis, reasoning and limited experiments based on the prior art according to the concept of the present invention should be within the scope of protection defined by the claims.
Claims (9)
1. A sound level weighting method for subjective annoyance comparison of a train station hall is characterized by comprising the following steps:
s1: acquiring a traffic track noise data set to produce an experimental signal;
s2: subjective annoyance evaluation is carried out on the experimenters by using the experimental signals;
s3: performing mathematical modeling on the annoyance evaluation data;
s4: verifying the evaluation index;
s5: a new evaluation network is proposed.
2. The sound level weighting method for the subjective annoyance level comparison of the train station hall according to claim 1, wherein the step S1 specifically comprises: the noise data sets are filtered at different frequencies by filters and the filtered signals are adjusted to corresponding loudness levels.
3. The method for weighting the sound level of the subjective annoyance level comparison in the train station hall according to claim 2, wherein the filter band has a loudness level of 55-80 phon when adjusted from 100Hz to 1000 Hz.
4. The method for weighting the sound level of the subjective annoyance level of the train station hall according to claim 3, wherein the experimental signal length is 4-6s.
5. The sound level weighting method for the subjective annoyance level comparison of the train station hall according to claim 1, wherein the step S2 is specifically as follows: and adjusting the angle and the distance between a loudspeaker playing the experimental signal and the subject, and recording the annoyance evaluation value of the subject under the experimental signal.
6. The sound level weighting method for the subjective annoyance level comparison of the train station hall according to claim 1, wherein the step S3 is specifically: selecting a psychoacoustic index: and performing linear regression analysis on the loudness, the acutance, the roughness, the fluctuation intensity and the linear sound pressure level, respectively drawing a fitting curve of the loudness level and the annoyance degree of each frequency noise and the noise frequency and the annoyance degree of each loudness level under different frequency conditions, and calculating corresponding Pearson correlation coefficients.
7. The sound level weighting method for the subjective annoyance level comparison of the train station hall according to claim 1, wherein the step S4 is specifically: and obtaining an evaluation value of the non-calculated noise sample through the mathematical model obtained in the step S3, and comparing the result with a subjective evaluation value.
8. The sound level weighting method for train station hall subjective annoyance level comparison according to claim 7, wherein the step S4 is implemented by the formula:
unbiased form of the predictive mathematical model and predictive accuracy, where y k The actual experimental value is the original annoyance degree; z is a radical of k Is the predicted value of the built model; k =1,2 … …, n is the number of noise samples.
9. The sound level weighting method for the subjective annoyance level comparison of the train station hall according to claim 1, wherein the step S5 specifically comprises: and calculating different loudness levels and linear sound levels of the noise with the same annoyance degree under different frequencies according to the fitted curves of the loudness level and the annoyance degree of the noise with each frequency and the noise frequency and the annoyance degree of each loudness level, and subtracting the sound pressure level measured by the test signal with other frequencies by taking the sound pressure level of 1000Hz as a reference to obtain a new weight.
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