International Journal of Highway Engineering (한국도로학회논문집)

Korean Society of Road Engineers (한국도로학회)
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Estimation of Total Sound Pressure Level for Friction Noise Regarding a Driving Vehicle using the Extended Kalman Filter Algorithm

확장형 칼만필터 알고리즘을 활용한 차량 주행에 따른 마찰소음의 총 음압레벨 예측

  • Dowan, Kim (Department of Civil Engineering, Seoul National University of Science and Technology) ;
  • Beomsoo, Han (Department of Civil Engineering, Seoul National University of Science and Technology) ;
  • Sungho, Mun (Department of Civil Engineering, Seoul National University of Science and Technology) ;
  • Deok-Soon, An
  • 김도완 (서울과학기술대학교 건설시스템공학과) ;
  • 한범수 (서울과학기술대학교 건설시스템공학과) ;
  • 문성호 (서울과학기술대학교 건설시스템공학과) ;
  • 안덕순 (한국건설기술연구원)
  • Received : 2014.09.12
  • Accepted : 2014.10.02
  • Published : 2014.10.16
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Abstract

PURPOSES : This study is to predict the Sound Pressure Level(SPL) obtained from the Noble Close ProXimity(NCPX) method by using the Extended Kalman Filter Algorithm employing the taylor series and Linear Regression Analysis based on the least square method. The objective of utilizing EKF Algorithm is to consider stochastically the effect of error because the Regression analysis is not the method for the statical approach. METHODS : For measuring the friction noise between the surface and vehicle's tire, NCPX method was used. With NCPX method, SPL can be obtained using the frequency analysis such as Discrete Fourier Transform(DFT), Fast Fourier Transform(FFT) and Constant Percentage Bandwidth(CPB) Analysis. In this research, CPB analysis was only conducted for deriving A-weighted SPL from the sound power level in terms of frequencies. EKF Algorithm and Regression analysis were performed for estimating the SPL regarding the vehicle velocities. RESULTS : The study has shown that the results related to the coefficient of determination and RMSE from EKF Algorithm have been improved by comparing to Regression analysis. CONCLUSIONS : The more the vehicle is fast, the more the SPL must be high. But in the results of EKF Algorithm, SPLs are irregular. The reason of that is the EKF algorithm can be reflected by the error covariance from the measurements.

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References

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