Prediction of high-speed train full-spectrum interior noise using statistical vibration and acoustic energy flow

Dai, Wenqiang; Zheng, Xu; Luo, Le; Zhou, Hao; Qiu, Yi

doi:10.1016/j.apacoust.2018.10.010

Cited by 19 publications

(12 citation statements)

References 19 publications

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“…In terms of transmission loss (TL), Figure 20 compares the experimental results with other published works on other materials that are commonly used in train cabin fabrication [57]. Given that unfilled samples show low values of transmission loss, only flexible foam-filled samples were used for comparison purposes.…”

Section: Comparison With Other Materialsmentioning

confidence: 99%

Vibration Damping and Acoustic Behavior of PU-Filled Non-Stochastic Aluminum Cellular Solids

Carneiro

Puga

Meireles

2021

Metals

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Aluminum-based cellular solids are promising lightweight structural materials considering their high specific strength and vibration damping, being potential candidates for future railway vehicles with enhanced riding comfort and low fuel consumption. The filling of these lattices with polymer-based (i.e., polyurethane) foams may further improve the overall vibration/noise-damping without significantly increasing their density. This study explores the dynamic (i.e., frequency response) and acoustic properties of unfilled and polyurethane-filled aluminum cellular solids to characterize their behavior and explore their benefits in terms of vibration and noise-damping. It is shown that polyurethane filling can increase the vibration damping and transmission loss, especially if the infiltration process uses flexible foams. Considering sound reflection, however, it is shown that polyurethane filled samples (0.27–0.30 at 300 Hz) tend to display lower values of sound absorption coefficient relatively to unfilled samples (0.75 at 600 Hz), is this attributed to a reduction in overall porosity, tortuosity and flow resistivity. Foam-filled samples (43–44 dB at 700–1200 Hz) were shown to be more suitable to reduce sound transmission rather than reflection than unfilled samples (21 dB at 700 Hz). It was shown that the morphology of these cellular solids might be optimized depending on the desired application: (i) unfilled aluminum cellular solids are appropriate to mitigate internal noises due to their high sound absorption coefficient; and (ii) PU filled cellular solids are appropriate to prevent exterior noises and vibration damping due to their high transmission loss in a wide range of frequencies and vibration damping.

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Section: Comparison With Other Materialsmentioning

confidence: 99%

Vibration Damping and Acoustic Behavior of PU-Filled Non-Stochastic Aluminum Cellular Solids

Carneiro

Puga

Meireles

2021

Metals

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“…Currently, numerous investigations have been conducted regarding the analysis of noise characteristics [20], sound quality evaluations [21], and noise level prediction [22]. For forecasting vehicle interior noise, typically used methods include the finite element method (FEM) [23], boundary element method (BEM) [24], and statistical energy analysis method (SEAM) [3]. As each method has its limitations, these approaches can only be applied to specific situations.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Generally, train noise can be divided into two categories: external and interior noises [2]. e interior noise is a complex sound field resulting from external acoustics and mechanical excitation sources transmitting, attenuating, and radiating inward through the carriage structure [3]. e interior noise of trains primarily comes from the electrical equipment, aerodynamic, and wheel-rail noises of the train [2].…”

Section: Introductionmentioning

confidence: 99%

Forecasting Urban Rail Transit Vehicle Interior Noise and Its Applications in Railway Alignment Design

Wang

Chen

et al. 2020

Journal of Advanced Transportation

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In this study, a data-driven interior noise prediction model is developed for vehicles on an urban rail transit system based on random forest (RF) and a vehicle/track coupling dynamic model (VTCDM). The proposed prediction model can evaluate and optimize the sustainability of railway alignment from the perspective of interior noise. First, a data collection framework via embedded sensors of onboard smartphones was developed. Then, for establishing the mapping relationship between the dynamic responses of the car body and interior noise, the collected dataset was fed to the RF. Parameter, error distribution, and feature importance analyses were conducted for evaluating and optimizing the performance of the RF. With the optimized parameters, the probability of prediction errors being within 5 dB was 86.9%. Next, the VTCDM was established using an existing industry multibody simulation tool and verified through a comparison between the simulated and field dynamic responses. Finally, a case study that extends the application of this interior noise prediction model to railway alignment design is presented.

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“…Some researchers have studied the airborne noise transmission of rolling noise to the vehicle interior, but they did not specifically study the acoustic environment below the vehicle. For instance, Dai et al [10] and Zheng et al [11] proposed a statistical energy flow method to predict the full spectrum sound inside a railway vehicle but the acoustic behaviour beneath the train floor was not explained and the sound power incident on the train floor was calculated by using commercial software. Zheng et al [12] also used an energy finite element analysis method to study the noise inside a railway vehicle considering rolling noise as one of its main sources.…”

Section: Introductionmentioning

confidence: 99%

Investigation of acoustic transmission beneath a railway vehicle by using statistical energy analysis and an equivalent source model

Thompson

Squicciarini

et al. 2021

Mechanical Systems and Signal Processing

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An approach is presented for modelling the noise propagation beneath the train floor and this is applied to rolling noise sources. It is assumed that the sound incident on the train floor is made up of a direct and a reverberant component. A combination of two numerical modelling approaches is considered to deal with these: an equivalent source model, to represent the direct component, and statistical energy analysis (SEA) for the reverberant part. In the equivalent source model, the wheel is replaced by monopole and dipole sources, which represent its radial and axial radiation. The rail vertical vibration and the sleepers are replaced by arrays of monopole sources while the rail lateral vibration is replaced by an array of lateral dipoles. The sound power of the rolling noise is obtained by using the TWINS model. In the SEA model, the region beneath the train floor is divided into several volumes and the power input to these subsystems is assumed to be due to the first reflections from the train floor and the ground. The reverberant and direct sound have very similar contributions to the total sound power incident on the train floor although this depends on how the equipment is arranged beneath the train. The modelling approach is verified by comparing the predicted sound pressure levels with laboratory measurements and with field tests.

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Prediction of high-speed train full-spectrum interior noise using statistical vibration and acoustic energy flow

Cited by 19 publications

References 19 publications

Vibration Damping and Acoustic Behavior of PU-Filled Non-Stochastic Aluminum Cellular Solids

Vibration Damping and Acoustic Behavior of PU-Filled Non-Stochastic Aluminum Cellular Solids

Forecasting Urban Rail Transit Vehicle Interior Noise and Its Applications in Railway Alignment Design

Investigation of acoustic transmission beneath a railway vehicle by using statistical energy analysis and an equivalent source model

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