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Forecasting Urban Rail Transit Vehicle Interior Noise and Its Applications in Railway Alignment Design
Joint Authors
Li, Zihan
Wang, Yifeng
Chen, Zhengxing
He, Qing
Wang, Ping
Source
Journal of Advanced Transportation
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-13, 13 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-06-23
Country of Publication
Egypt
No. of Pages
13
Main Subjects
Abstract EN
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.
American Psychological Association (APA)
Wang, Yifeng& Wang, Ping& Li, Zihan& Chen, Zhengxing& He, Qing. 2020. Forecasting Urban Rail Transit Vehicle Interior Noise and Its Applications in Railway Alignment Design. Journal of Advanced Transportation،Vol. 2020, no. 2020, pp.1-13.
https://search.emarefa.net/detail/BIM-1175812
Modern Language Association (MLA)
Wang, Yifeng…[et al.]. Forecasting Urban Rail Transit Vehicle Interior Noise and Its Applications in Railway Alignment Design. Journal of Advanced Transportation No. 2020 (2020), pp.1-13.
https://search.emarefa.net/detail/BIM-1175812
American Medical Association (AMA)
Wang, Yifeng& Wang, Ping& Li, Zihan& Chen, Zhengxing& He, Qing. Forecasting Urban Rail Transit Vehicle Interior Noise and Its Applications in Railway Alignment Design. Journal of Advanced Transportation. 2020. Vol. 2020, no. 2020, pp.1-13.
https://search.emarefa.net/detail/BIM-1175812
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1175812