A maximum noise-level prediction method for high-speed railways in China: A case study using the Baiyun campus of Guangdong polytechnic normal university. (July 2019)

• Record Type: Journal Article
• Authors: Li, Feng; Wu, Mingchuan; Lai, Cong; Chen, Shenchang; Xu, You; Du, Canyi; Cai, Ming; Liu, Jike
• Is Part Of: Applied acoustics. Volume 150(2019)
• Page Start: 124
• Page End: 131
• Publication Date: 2019-07
• Subjects: High-speed railway -- Noise -- Prediction model -- Noise monitoring; Acoustical engineering -- Periodicals; Periodicals; 620.2
• DOI: 10.1016/j.apacoust.2019.01.032
• Languages: English
• ISSNs: 0003-682X

Abstract

Abstract: China's high-speed railway system has made rapid progress in the past 10 years, but at the same time, it has brought noise pollution problems to the surrounding areas. The Baiyun Campus of Guangdong Polytechnic Normal University is located near the Wuhan-Guangzhou high-speed railway. To evaluate the impact of high-speed railway noise on student learning, the sound pressure levels, spectrum of frequencies, window attenuations and other parameters of the noise from the Wuhan-Guangzhou high-speed railway are measured. A maximum noise-level prediction model for high-speed railway noise is established based on the experimental data. The distribution of the maximum noise level in the school district is calculated used the established model and the effect of noise on student learning was discussed. The results show that the model prediction results are consistent with the experimental results, and the average absolute error is less than 2 dBA. Although the hourly equivalent noise level is in accordance with the environment quality standard of noise, the maximum noise level when the train is passing is still high, exceeding 65 dBA inside some classrooms and even exceeding 70 dBA in open space, which has a significant impact on student learning. The results of this study have important application value for assessing the impact of high-speed railway noise in China.