Interior Noise Prediction in High-Speed Rolling Stock Driver’s Cab: Focus on Structure-Borne Paths (Mechanical and Aero Sources)
Interior noise in rolling stock is an important parameter in the evaluation of global comfort perceived by passengers and train crew. This paper describes the methods proposed for interior noise prediction in high-speed trains focusing on structure-borne paths that includes interior noise produced by the vibration of components (bogie, traction motor, gearbox...) and aero-acoustic sources due to the airflow at high speed around the driver’s cab.
An experimental analysis of the different noise transfer paths and contributing sources is applied following panel contribution and transfer path analysis techniques. In order to obtain a model covering a wide frequency range, hybrid FE/SEA methodologies are chosen. Different loads measured in dynamic conditions are applied at the interfaces between equipment and structure to evaluate the contribution of each equipment to interior noise. Finally, the contributions are compared with the ones measured experimentally. The model obtained is also used to compute the aero-acoustic contribution to interior noise, mainly considered as a structural excitation.
KeywordsComputational Fluid Dynamics Computational Fluid Dynamics Simulation Interior Noise Direct Transfer Function Statistical Energy Analysis
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