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Design of new sound metric and its application for quantification of an axle gear whine sound by utilizing artificial neural network
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  • Design of new sound metric and its application for quantification of an axle gear whine sound by utilizing artificial neural network
  • Design of new sound metric and its application for quantification of an axle gear whine sound by utilizing artificial neural network
저자명
Lee. Hyun-Hoo,Kim. Sung-Jong,Lee. Sang-Kwon
간행물명
Journal of mechanical science and technology
권/호정보
2009년|23권 4호|pp.1182-1193 (12 pages)
발행정보
대한기계학회
파일정보
정기간행물|ENG|
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이 논문은 한국과학기술정보연구원과 논문 연계를 통해 무료로 제공되는 원문입니다.
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기타언어초록

The gear whine sound of an axle system is one of the most important sound qualities in a sport utility vehicle (SUV). Previous work has shown that, because of masking effects, it is difficult to evaluate the gear whine sound objectively by using only the A-weighted sound pressure level. In this paper, a new objective evaluation method for this sound was developed by using new sound metrics, which are developed based on the increment of signal to noise ration and the psychoacoustic parameters in the paper, and the artificial neural network (ANN) used for the modeling of the correlation between objective and subjective evaluation. This model developed by using ANN was applied to the objective evaluation of the axle-gear whine sound for real SUVs and the output of the model was compared with subjective evaluation. The results indicate a good correlation of over 90 percent between the subjective and objective evaluations.