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Details of Grant 

EPSRC Reference: GR/L43565/01
Title: PREDICTING VECHICLE PASS-BY NOISE USING NEURAL NETS
Principal Investigator: Jennings, Professor P
Other Investigators:
Researcher Co-Investigators:
Project Partners:
Pre Nexus Migration Rover Ltd
Department: Sch of Engineering
Organisation: University of Warwick
Scheme: LINK
Starts: 06 October 1997 Ends: 05 October 1999 Value (£): 67,791
EPSRC Research Topic Classifications:
Transport Ops & Management
EPSRC Industrial Sector Classifications:
Transport Systems and Vehicles
Related Grants:
Panel History:  
Summary on Grant Application Form
Noise emitted by new vehicles is measured during a statutory pass-by noise test at the end of their development to ensure compliance with legislation. Progress in reducing this level has necessarily made further improvement increasingly more difficult - it is no longer obvious which noise source should be tackled to obtain the optimum reduction. A predictive technique for use early in the development of a new vehicle would be a significant benefit, allowing satisfactory levels of pass-by noise to be achieved without affecting vehicle weight (hence feul economy), function or cost due to any last minute quick fixes .The research programme will use a neural computing approach to generate knowledge and tools to enable the pass-by noise behaviour of new vehicles to be considered early in their development. Both noise level and quality will be predicted. The optimum inputs to a neural network for predicting vehicle pass-by noise levels will be evaluated. This will lead to the development of modelling tools which can both: predict maximum pass-by noise level, as required by European Directive 92/97EEC, to a known statistical tolerance from design information; and predict a relative annoyance level of the noise emitted by a production vehicle.
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Organisation Website: http://www.warwick.ac.uk