Sparsity-driven separation of railway rolling noise with a microphone array

Overview & Synopsis

In this paper we propose the use of sparse reconstruction methods to characterize the pass- by noise of rail-bound transportation vehicles. European trains are homologated with the TSI- NOISE legislation, which specifies the quantification of the vehicle noise alone; that is, irrespective of the track on which the vehicle is running. However, some tracks contribute significantly to the pass-by noise in mid-frequencies, leading to geographically dependent noise emissions of the same vehicle. To remove this dependency from the homologation, the track and vehicle contributions must be separated. This paper proposes the use of sparse regularization methods to distinguish between vehicle and rail noise. The approach is based on measurements with a microphone array near the track, and the use of dictionaries of plane waves and moving equivalent sources. Compared with reference results predicted with the TWINS software, we show that both contributions can be separated more accurately than present state-of-the-art methods.