Research on elevated orbit noise propagation based on AI algorithm and propagation path analysis

Frontiers in Physics

Physics

Lei Xiao-Yan¹  Luo Kun¹  Weng Ling-Xiao² 

[1] Engineering Research Center of Railway Environment Vibration and Noise Ministry of Education, Nanchang, China;Engineering Research Center of Railway Environment Vibration and Noise Ministry of Education, Nanchang, China;Nanchang Normal College of Applied Technology, Nanchang, China;

关键词: artificial intelligence algorithm;    path analysis;    noise analysis;    noise reduction processing;    noise transmission;   

DOI  :  10.3389/fphy.2023.1161977

 received in 2023-02-09, accepted in 2023-05-09,  发布年份 2023

来源: Frontiers

【 摘 要 】

With the rapid development of high-speed railway, noise reduction is becoming more and more important. At the same time, the study of elevated rail noise is also very important for the engineering field. The noise reduction of elevated rail noise is a part of the engineering construction, which is conducive to the economic development and the improvement of people’s life, and the reduction of noise has an impact on residents’ life. This article aims to investigate the analysis of the vibration and noise transmission path of the elevated railway. An optimized transmission path analysis method, which is based on the artificial intelligence algorithms, is used to optimize the path analysis, so as to trace the source of the noise and analyze the noise reduction. This method performs well in the analysis of vibration and noise of elevated railways. After this optimization, the contribution degree and frequency response function in the path analysis have better analysis performance. Through the actual measurement and analysis of the noise of the elevated railway, it can be proved that the traditional path method can better analyze the noise source. The environmental noise caused by high-speed trains passing bridges easily exceeds the acoustic environmental standards. After noise reduction, it can be reduced by about 5–10 dB.

【 授权许可】

Unknown   
Copyright © 2023 Ling-Xiao, Xiao-Yan and Kun.