scholarly journals Vehicle Interior Noise Prediction Based on Elman Neural Network

2021 ◽  
Vol 11 (17) ◽  
pp. 8029
Author(s):  
Min Li ◽  
Wei Zhou ◽  
Jiang Liu ◽  
Xilong Zhang ◽  
Fuquan Pan ◽  
...  
Keyword(s):  
Neural Network ◽  
Sound Pressure Level ◽  
Sound Pressure ◽  
Pressure Level ◽  
The Body ◽  
Side Impact ◽  
Vehicle Body ◽  
Target Point ◽  
Vehicle Interior ◽  
Elman Neural Network

Vehicle interior noise is an important factor affecting ride comfort. To reduce the noise inside the vehicle at the vehicle body design stage, a finite element model of the vehicle body must be established. While taking the first-order global modal of the body-in-white, the maximum sound pressure level of the target point in the vehicle, the body mass, and the side impact conditions into account, the thickness of the body panel as determined via sensitivity analysis is treated as the input variable, and the sample is determined by following the Hamersley experimental design. Specifically, the Elman neural network predicts the noise value in the vehicle, and a vehicle body structure optimization method that comprehensively considers NVH performance and side impact safety is established. The prediction errors of the Elman neural network algorithm were within 3%, which meets the prediction accuracy requirements. To achieve satisfactory restraint performance, the maximum sound pressure level of the target point in the vehicle is reduced by 5.92 dB, and the maximum intrusions of the two points on the B-pillar inner panel are reduced by 31.1 mm and 33.71 mm, respectively. The side impact performance is improved while the noise inside the vehicle is reduced. This study provides a reference method for multidisciplinary research aiming to optimize the design of vehicle body structures.

scholarly journals Sound Levels Forecasting in an Acoustic Sensor Network Using a Deep Neural Network

Sensors ◽  
2020 ◽  
Vol 20 (3) ◽  
pp. 903 ◽  
Author(s):  
Juan M. Navarro ◽  
Raquel Martínez-España ◽  
Andrés Bueno-Crespo ◽  
Ramón Martínez ◽  
José M. Cecilia
Keyword(s):  
Neural Network ◽  
Sensor Network ◽  
Sound Pressure Level ◽  
Deep Neural Network ◽  
Sound Pressure ◽  
Noise Pollution ◽  
Pressure Level ◽  
Acoustic Sensor ◽  
Short Term ◽  
Sound Levels

Wireless acoustic sensor networks are nowadays an essential tool for noise pollution monitoring and managing in cities. The increased computing capacity of the nodes that create the network is allowing the addition of processing algorithms and artificial intelligence that provide more information about the sound sources and environment, e.g., detect sound events or calculate loudness. Several models to predict sound pressure levels in cities are available, mainly road, railway and aerial traffic noise. However, these models are mostly based in auxiliary data, e.g., vehicles flow or street geometry, and predict equivalent levels for a temporal long-term. Therefore, forecasting of temporal short-term sound levels could be a helpful tool for urban planners and managers. In this work, a Long Short-Term Memory (LSTM) deep neural network technique is proposed to model temporal behavior of sound levels at a certain location, both sound pressure level and loudness level, in order to predict near-time future values. The proposed technique can be trained for and integrated in every node of a sensor network to provide novel functionalities, e.g., a method of early warning against noise pollution and of backup in case of node or network malfunction. To validate this approach, one-minute period equivalent sound levels, captured in a two-month measurement campaign by a node of a deployed network of acoustic sensors, have been used to train it and to obtain different forecasting models. Assessments of the developed LSTM models and Auto regressive integrated moving average models were performed to predict sound levels for several time periods, from 1 to 60 min. Comparison of the results show that the LSTM models outperform the statistics-based models. In general, the LSTM models achieve a prediction of values with a mean square error less than 4.3 dB for sound pressure level and less than 2 phons for loudness. Moreover, the goodness of fit of the LSTM models and the behavior pattern of the data in terms of prediction of sound levels are satisfactory.

Influence of Crosswind to Automobile Interior Aerodynamic Noise

2012 ◽  
Vol 503-504 ◽  
pp. 1164-1168
Author(s):  
Yin Zhi He ◽  
Zhi Gang Yang
Keyword(s):  
Sound Pressure Level ◽  
Pressure Fluctuation ◽  
Sound Pressure ◽  
Window Glass ◽  
Pressure Level ◽  
Aerodynamic Noise ◽  
Vehicle Interior ◽  
Side Window ◽  
Transmission Mechanisms ◽  
Yaw Angle

After a brief introduction about aerodynamic noise generation and transmission mechanisms, the influence of crosswind to vehicle interior aerodynamic noise for a production automobile sedan was investigated through full-scale aeroacoustic wind tunnel tests. Through analysis of sound pressure level of vehicle interior driver ear position and pressure fluctuation level on vehicle side window glass under different yaw angles, the following results are obtained: The frequency characteristics of vehicle interior aerodynamic noise vary as yaw angle changes under one certain wind speed. Whether on the leeside or by windward, sound pressure level increases as yaw angle goes up. Under the same yaw angle, interior noise level on the leeside is higher than that by windward. Test results between pressure fluctuation level on side window glass and vehicle interior aerodynamic noise of driver ear position show good correlation

scholarly journals Field Study of the Interior Noise and Vibration of a Metro Vehicle Running on a Viaduct: A Case Study in Guangzhou

2020 ◽  
Vol 17 (8) ◽  
pp. 2807
Author(s):  
Lei Yan ◽  
Zhou Chen ◽  
Yunfeng Zou ◽  
Xuhui He ◽  
Chenzhi Cai ◽  
...  
Keyword(s):  
Sound Pressure Level ◽  
Sound Pressure ◽  
Pressure Level ◽  
Interior Noise ◽  
Vehicle Body ◽  
Frequency Noise ◽  
Data Set ◽  
Noise And Vibration ◽  
Acceleration Level ◽  
Frequency Peak

The interior noise and vibration of metro vehicles have been the subject of increasing concern in recent years with the development of the urban metro systems. However, there still is a lack of experimental studies regarding the interior noise and vibration of metro vehicles. Therefore, overnight field experiments of the interior noise and vibration of a standard B-type metro train running on a viaduct were conducted on metro line 14 of Guangzhou (China). Both the A-weighted sound pressure level and linear sound pressure level were used to evaluate the interior noise signals in order to revel the underestimation of the low-frequency noise components. The results show that the interior noise concentrates in the low-to-middle frequency range. Increasing train speeds have significant effects on the sound pressure level inside the vehicle. However, two obvious frequency ranges (125–250 Hz and 400–1000 Hz) with respective corresponding center frequencies (160 Hz and 800 Hz) of the interior noise are nearly independent of train speed. The spectrum analysis of the vehicle body vibration shows that the frequency peak of the floor corresponds to the first frequency peak of the interior noise spectrum. There are two frequency peaks around 40 Hz and 160 Hz of the sidewall’s acceleration level. The frequency peaks of the acceleration level are also independent of the train speeds. It hopes that the field measurements in this paper can provide a data set for researchers for further investigations and can contribute to the countermeasures for reducing interior noise and vibration of a metro vehicle.

Nonlinear modeling and prediction of forklift acoustic annoyance based on the improved neural networks

SIMULATION ◽  
2021 ◽  
pp. 003754972110648
Author(s):  
Enlai Zhang ◽  
Jiading Lian ◽  
Jingjing Zhang ◽  
Jiahe Lin
Keyword(s):  
Neural Network ◽  
Sound Pressure Level ◽  
Sound Pressure ◽  
Evaluation Method ◽  
Comprehensive Evaluation ◽  
Nonlinear Modeling ◽  
Subjective Evaluation ◽  
Pressure Level ◽  
Subjective Perception ◽  
Artificial Neural Network Ann

Aiming at the characteristics of high decibels and multiple samples for forklift noise, a subjective evaluation method of rank score comparison (RSC) based on annoyance is presented. After pre-evaluation, comprehensive evaluation and data tests on collected 50 noise samples, the annoyance grades of all noise samples were obtained, and seven psycho-acoustic parameters including linear sound pressure level (LSPL), A-weighted sound pressure level (ASPL), loudness, sharpness, roughness, impulsiveness and articulation index (AI) were determined by correlation calculation. Considering the nonlinear characteristics of human ear subjective perception, objective parameters, and annoyance were used as input and output variables correspondingly and then three nonlinear mathematical models of forklift acoustic annoyance were established using traditional artificial neural network (ANN), genetic-algorithm neural network (GANN), and particle-swarm-optimization neural network (PSONN). Moreover, the prediction accuracy of the three models was tested and compared by sample data. The results indicate that the average relative error (ARE) between the experimental and predicted values of acoustic annoyance based on PSONN model is 3.893%, which provides an effective technical support for further optimization and subjective evaluation.

scholarly journals A Technology for Increasing the Functional Reserves of the Body Based on Bioacoustic Stimulation of the Respiratory System

Biomeditsina ◽  
2021 ◽  
Vol 17 (3) ◽  
pp. 39-47
Author(s):  
S. P. Dragan ◽  
S. M. Razinkin ◽  
G. G. Erofeev
Keyword(s):  
Respiratory System ◽  
Sound Pressure Level ◽  
Sound Pressure ◽  
Pressure Level ◽  
The Body ◽  
Control Group ◽  
Breath Hold ◽  
Exposure Group ◽  
Functional Reserves ◽  
Stimulation Of

A technology based on the effect of low-frequency vibrations on the respiratory system is a promising approach to increasing the functional reserves of the human body. To implement such a technology, it is necessary to justify the optimal modes of bioacoustic stimulation of the respiratory system. Therefore, the aim of the study was a theoretical and experimental justification of the technology to increase the functional reserves of the body based on bioacoustic stimulation of the respiratory system. Acoustic impedance was measured on a polyharmonic sound signal in the frequency range from 3 Hz to 51 Hz with a step of 3 Hz in all three phases of respiration: a full breath with a breath hold, a deep breath with a breath hold and free nasal surface breathing without a delay. After determining the resonant frequencies of the respiratory tract for two weeks, six sessions of bioacoustic stimulation were conducted on a group of 20 testers, including placebo exposure. In the exposure group, the sound pressure level was 130 dB, and in the control group - 60 dB, which is below the audibility threshold at these frequencies. Six-fold exposure to a scanning tone signal with a sound pressure level of 130 dB led to an increase in the resonant frequency of the respiratory system, a decrease in the absorption coefficient of sound vibrations by the respiratory system, and an increase in the resistance of the respiratory system to the sound wave. These effects can be explained by the fact that, as a result of exposure, reserve alveoli were discovered and the cross-sectional area of the alveolar passages and respiratory bronchioles increased. An analysis of the results of experiments in both groups in the dynamics of six stimulation sessions suggests that their values for the control group of testers practically did not change at all periods of observation. At the same time, similar indicators in the exposure group have a significant difference from the background values. It was shown that, in order to increase the functional reserves of the body, two bioacoustic stimulation treatments can be sufficient.

Acoustical absorptive properties of meltblown nonwovens for textile machinery

2020 ◽  
pp. 004051752098046
Author(s):  
Magdi El Messiry ◽  
Gajanan Bhat ◽  
Affaf Eloufy ◽  
Samar Abdel Latif ◽  
Yasmin Ayman
Keyword(s):  
Sound Pressure Level ◽  
Sound Absorption ◽  
Sound Pressure ◽  
Noise Exposure ◽  
Fiber Diameter ◽  
Noise Pollution ◽  
Pressure Level ◽  
The Body ◽  
Poly Lactic Acid ◽  
Average Fiber Diameter

Noise pollution is one of the harmful physical sources in the textile industry, which is among those industries that are faced with noise exposure problems. The results of environmental sound measurements at modern textile mills have shown that the sound pressure level varied from 95 to 130 dB, where the highest sound pressure level was at weaving machines. Textile insulation materials can be fitted in order to decrease sound pollution at a low cost. The objective of this work is to design a sound absorber that can be fixed to the body of the machines, at the point of the noise generation, to reduce noise pollution. Poly(lactic acid) (PLA), which is an environmentally friendly material, was used to produce different samples of meltblown nonwoven absorbers to be used for damping the noise of textile machinery. PLA meltblown nonwoven fabric with the areal density of 16.7 g/m2, average fiber diameter of 1.1 µm, mean pore diameter of 9.8 µm and thickness of 0.27 mm exhibited significant sound absorption. The sample with the smallest average fiber diameter among those investigated had the highest damping effect: 23.95, 41.29 and 29.32 dBA at frequencies of 400, 1000 and 1500 Hz, respectively. Our goal is to have a practical tool that accurately evaluates the absorber sound damping under the actual running conditions of the textile machinery. The design of the absorber from one layer of the PLA meltblown nonwoven over a rigid polyurethane foam sheet had an excellent sound absorption property.

Contributions of Voice and Nonverbal Communication to Perceived Masculinity–Femininity for Cisgender and Transgender Communicators

2020 ◽  
Vol 63 (4) ◽  
pp. 931-947
Author(s):  
Teresa L. D. Hardy ◽  
Carol A. Boliek ◽  
Daniel Aalto ◽  
Justin Lewicke ◽  
Kristopher Wells ◽  
...  
Keyword(s):  
Fundamental Frequency ◽  
Sound Pressure Level ◽  
Sound Pressure ◽  
Vocal Tract ◽  
Presentation Mode ◽  
Pressure Level ◽  
Presentation Modes ◽  
Audiovisual Stimuli ◽  
Vocal Tract Resonance ◽  
Point Light

Purpose The purpose of this study was twofold: (a) to identify a set of communication-based predictors (including both acoustic and gestural variables) of masculinity–femininity ratings and (b) to explore differences in ratings between audio and audiovisual presentation modes for transgender and cisgender communicators. Method The voices and gestures of a group of cisgender men and women ( n = 10 of each) and transgender women ( n = 20) communicators were recorded while they recounted the story of a cartoon using acoustic and motion capture recording systems. A total of 17 acoustic and gestural variables were measured from these recordings. A group of observers ( n = 20) rated each communicator's masculinity–femininity based on 30- to 45-s samples of the cartoon description presented in three modes: audio, visual, and audio visual. Visual and audiovisual stimuli contained point light displays standardized for size. Ratings were made using a direct magnitude estimation scale without modulus. Communication-based predictors of masculinity–femininity ratings were identified using multiple regression, and analysis of variance was used to determine the effect of presentation mode on perceptual ratings. Results Fundamental frequency, average vowel formant, and sound pressure level were identified as significant predictors of masculinity–femininity ratings for these communicators. Communicators were rated significantly more feminine in the audio than the audiovisual mode and unreliably in the visual-only mode. Conclusions Both study purposes were met. Results support continued emphasis on fundamental frequency and vocal tract resonance in voice and communication modification training with transgender individuals and provide evidence for the potential benefit of modifying sound pressure level, especially when a masculine presentation is desired.

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