The interior noise levels in trains has been reduced considerably during the last decades. However, the acoustic behavior has nowadays an even more important role among the comfort parameters of high speed trains. The FE-SEA hybrid methodologies raised up during the last years have given a new approach to the problem of the structure borne noise, giving the opportunity to deal with the acoustic mid frequency range, where FE and SEA systems were unable to work. However this numerical models depend on several physical parameters and, although most of them are well known in fields like the automotive, they need to be further studied for the rolling stock applications. The present paper deals with the investigation process carried out by ALSTOM to set up a hybrid FE-SEA model of the cabin of a high speed train in order to predict the interior structure borne noise, from its first steps characterizing the most important transmission paths, to the structural responses predicted by given diverse model approaches. The feasibility of the hybrid FE-SEA methodology to the rolling stock is investigated by its application to the case of a high speed train cabin. The investigation process deals with the different production stages in order to obtain information about the correct parameters of every part of the system. That research is still in progress when the paper is presented and the results shown deal only with the dynamic mechanical response of the system. The hybrid FE-SEA partitioning criteria have been set up between 3 and 5 modes per l/3rd octave band. The results obtained show normally a good accuracy for the vibration prediction at the frequency range of [100, 1000] Hz and the discrepancies between the models and the experimental curves are normally below 5 dB. Furthermore, in those cases where the differences between the models and the tests are larger, the hybrid methodology seems to provide a better agreement (with some exceptions).
Interior structure borne noise prediction of the cabin of a high speed train using FE-SEA hybrid methods
2009
9 Seiten, 8 Bilder, 1 Tabelle, 12 Quellen
Conference paper
English
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