Railway noise statistics by monitoring stations - Input for Dutch prediction method RMR and track access charging

Abstract

The infrastructure management organisation ProRail has installed five noise monitoring stations on the railway network in the Netherlands for the purpose of monitoring the progress of the Dutch Noise Innovation Programme. These monitoring stations record noise spectra and rail vibration spectra of train pass-bys. A weather station is integrated to allow the exclusion of data recorded during windy and rainy periods. As the stations are also capable of identifying trains that are equipped with tags. This creates a unique possibility for statistical analysis of the noise of such trains. A statistical data analysis programme has been conducted by Railway Noise Knowledge Centre of ProRail. In this programme, the performance of silent test trains has been monitored. These passenger and freight test trains have been equipped with LL braking blocks, which are expected to keep the running surface of the wheel smooth. The monitoring stations provide information on the long-term performance of these trains in terms of noise reduction. The analysis programme also involves an evaluation of the source parameters of the Dutch railway noise prediction method (RMR). These source parameters which depend on the type of rolling stock have been derived and established in the mid 1990s. It has been established that the average noise emission level of most train types is still close to the RMR values; however, for some train types a significant lower noise emission level has been measured. This will lead to adjustment of source parameters in RMR, which enables a more efficient use of noise abatement resources in the future. Furthermore, the potential usability of the noise monitoring in noise-based railway access charging is considered. For this purpose, the reliability and accuracy of individual pass-by measurements is assessed. Special attention is paid to the measurement uncertainty caused by local track properties, which, of course, should be eliminated before imposing a fine on noisy trains. © 2008 Springer-Verlag Berlin Heidelberg.