Modelling for sound annoyance evaluation of vehicle noise based on neural network

• Autorzy: Wang Y. , Shen G. , Guo H.

Warianty tytułu

PL

Modelowanie dźwięków drażniących pochodzących od pojazdów mechanicznych z wykorzystaniem sieci neuronowych

• Języki publikacji: EN

Abstrakty

EN

Based on the neural network (NN) technique, a new sound quality evaluation (SQE) model for synthetical annoyance of vehicle noises is proposed in this paper. Based on the measured noise signals of a sample vehicle, the psychoacoustical models for loudness, sharpness and roughness are investigated. Annoyance values of the measured vehicle noises are estimated by a jury test following an anchor-scaled scoring method. A NN-based model for annoyance evaluation of vehicle noise, so-called VNA-NNM, is carried out. Finally, the VNA-NNM model is verified by the leave-one-out algorithm. The results suggest that the VNA-NNM model is accurate and effective for estimating sound quality of vehicle interior noises, which is instructive and useful for vehicle acoustical designs.

PL

Zaproponowano model oceny jakości dźwięku i rozdrażnienia dźwiękiem szumu samochodowego. Model bazuje na sieciach neuronowych i wykorzystuje zmierzony sygnał szumu samochodowego oraz model psychoakustyczny.

Słowa kluczowe

EN

vehicle noise; sound quality evaluation; synthetical annoyance; neural network

PL

szum samochodowy; sieci neuronowe

• Wydawca: Wydawnictwo SIGMA-NOT
• Czasopismo: Przegląd Elektrotechniczny
• Rocznik: 2012
• Tom: R. 88, nr 7b
• Strony: 303--306
• Opis fizyczny: Bibliogr. 15 poz., schem., tab., wykr.

Twórcy

autor

Wang Y.

• School of Automotive Engineering, Shanghai University of Engineering Science, No. 333, Loneteng Road, Songjiang District, Shanghai, 201620, China

autor

Shen G.

• Shanghai University of Engineering Science

autor

Guo H.

• School of Automotive Engineering, Shanghai University of Engineering Science

Bibliografia

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• [3] Trapenskas D., Sound Quality Assessment Using Binaural Technology, PhD Thesis, Lulea University of Technology, 2002.
• [4] Zwicker E., Fastl H., Psychoacoustics, Facts and Models, Springer Verlag, Berlin, 1990.
• [5] Fastl H., The Psychoacoustics of Sound-quality Evaluation, Acustica, 83 (1997), No. 5, 754-764.
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• [8] Aures W., A Procedure for Calculating Auditory Roughness, Acustica, 58 (1985), No. 5, 268-281.
• [9] Zwicker E., Fastl H., Widmann U., Kurakata K., Kuwano S., Namba S., Program for Calculating Loudness According to DIN 45631 (ISO 532B), Journal of Acoustic Society of Japan (E) 12 (1991), No.1, 39-42.
• [10] Bisping R., Car Interior Sound Quality: Experimental Analysis by Synthesis, Acustica, 83 (1997), No. 5, 813-818.
• [11] Wang Y. S., Lee C.-M., Kim D.-G., Xu Y., Sound-quality Prediction for Nonstationary Vehicle Interior Noise Based on Wavelet Pre-Processing Neural Network Model, Journal of Sound and Vibration, 299 (2007), No. 4-6, 933-947.
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• [13] GB/T 18697-2002: Acoustics -- Method for measuring vehicle interior noise, 2002.
• [14] ISO 532B: Acoustics -- Method for calculating loudness level, 1975.
• [15] Terhardt E., Calculating Virtual Pitch, Hearing Research, 1 (1979), No. 2, 155-182.