Statistical analysis of field data of railway noise and vibration collected in an urban area

Abstract

The effects of various factors on railway noise and vibration were studied through multiple regression analysis of the field data at 79 sites along 8 railway lines in an urban area. The results show that peak and sound exposure levels of railway noise can be explained fairly well by distance from track, railway structure, train speed, train length and so on. Because of the close relationship between peak and sound exposure levels, the main factors such as distance from track and railway structure give similar contributions to both noise levels. Train speed gives a greater contribution to peak level than to sound exposure level, while train length gives less. Regarding the vibration level, it was found that the contribution of background vibration is greater than that of railway structure and train speed. The results were applied to predict railway noise and vibration, and were also compared with the results of the Shinkansen Super Express railway which have already been reported.