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Predicting Automotive Interior Noise Including Wind Noise By Statistical Energy Analysis

Authors: Yoshio Kurosawa;

Predicting Automotive Interior Noise Including Wind Noise By Statistical Energy Analysis

Abstract

{"references": ["Lyon R.H., Statistical Energy of Dynamical System, Theory and Applications, MIT Press, 1975.", "Lyon R.H., Dejong R.G.., Theory and Application of Statistical Energy Analysis, Butterworth-Heinemann, p. 277, 1995.", "Takahashi A., Nakane A., Hashigami S., Kokabu S., Misaji K., Vehicle Interior Acoustic Analysis by Hybrid SEA Method, Review of Automotive Engineering JSAE,No.54-10, 2010, pp.17-22.", "Kurosawa Y., Nakaizumi N., Weight Reduction Technique of Acoustic Insulation for Automobile Using SEA, Society of Damping Technology Symposium 2010, SDT10003, pp.11-16.", "Biot M.A., Theory of propagation of elastic waves in a fluid-saturated porous solid.\u2161. Higher frequency range, Journal of Acoustical Society of America, Vol.28, 1956, pp.179-191.", "Allard J.F., Propagation of Sound in Porous Media, Elsevier Applied Science, London and New York, 1993.", "Utsuno H., Tanaka T., Fujikawa T., Transfer Function Method for Measuring Characteristic Impedance and Propagation Constant of Porous Material, J. Acoust. Soc. Am. Vol.86, No.2, 1989, pp.637.", "Delany M.E., Bazley E.N., Acoustical properties of fibrous absorbent materials, Applied Acoustics 3, 1975, pp.105-116."]}

The applications of soundproof materials for reduction of high frequency automobile interior noise have been researched. This paper presents a sound pressure prediction technique including wind noise by Hybrid Statistical Energy Analysis (HSEA) in order to reduce weight of acoustic insulations. HSEA uses both analytical SEA and experimental SEA. As a result of chassis dynamo test and road test, the validity of SEA modeling was shown, and utility of the method was confirmed.

Keywords

noise, statistical energy analysis., Vibration, car

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This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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