• International Journal of Highway Engineering
• /
• v.15 no.6
• /
• pp.79-91
• /
• 2013

PURPOSES : The methods of measuring the sound from the noise source are Pass-by method and NCPX (Noble Close Proximity) method. These measuring methods were used to determine the linkage of TAPL (Total Acoustic Pressure Level) and SPL (Sound Pressure Level) in terms of frequencies. METHODS : The frequency analysis methods are DFT (Discrete Fourier Transform) and FFT (Fast Fourier Transform), CPB (Constant Percentage Bandwidth). The CPB analysis was used in this study, based on the 1/3 octave band option configured for the frequency analysis. Furthermore, the regression analysis was used at the condition related to the sound attenuation effect. The MPE (Mean Percentage Error) and RMSE (Root Mean Squared Error) were utilized for calculating the error. RESULTS : From the results of the CPB frequency analysis, the predicted SPL along the frequency has 99.1% maximum precision with the measured SPL, resulting in roughly 1 dB(A) error. The TAPL results have precision by 99.37% with the measured TAPL. The predicted TAPL results at this study by using the SPL prediction model along the frequency have the maximum precision of 98.37% with the vehicle velocity. CONCLUSIONS : The Predicted SPL model along the frequency and the TAPL result by using the predicted SPL model have a high level of accuracy through this study. But the vehicle velocity-TAPL prediction model from the previous study by using the log regression analysis cannot be consistent with the TAPL result by using the predicted SPL model.

• International Journal of Highway Engineering
• /
• v.15 no.6
• /
• pp.93-101
• /
• 2013

PURPOSES : The rumble strip installed at the highway near the tollgate has the purpose to reduce the vehicle velocity or prevent sleepiness by awakening people to the danger. These rumble strip has different vibration decibel from the rumble strip shapes, resulting in some fatigue damage to human because a driver suffers from a lot of stress and displeasure. In this connection, the objective of this paper is to analyze the vibration decibel perceived by a driver in the vehicle under some conditions. METHODS : The vibration decibel conveyed from the tire can be analyzed. The frequency analysis methods were used according to DFT (Discrete Fourier Transform) analysis, FFT (Fast Fourier Transform) analysis, CPB (Constant Percentage Bandwidth) analysis. But the frequency analysis method in this paper is the 1/24 OCT(Octave) band analysis because of the convenience of the analysis and the overall vibration amplitude along the frequency. RESULTS : By using the results of the vibration decibel after analyzing the 1/24 OCT band analysis, these results can be compared from some conditions (e.g., rumble strip shape, uniform velocity of a vehicle, road condition, mass of a vehicle). As a result, the numerical values of decibel are not directly proportional to the vehicle velocity. CONCLUSIONS : At the condition that a vehicle is passing by the rumble strip, the value of a vibration decibel at the rumble strip of the cylinder shape is smaller than the rumble strip of rectangular shape regardless of the rumble strip depth and width. At the mass condition, the more a vehicle is massive, the more the vibration decibel increases. At the road condition, the vibration decibel at the wet road is smaller than the value at dry road condition.

• International Journal of Highway Engineering
• /
• v.16 no.5
• /
• pp.59-66
• /
• 2014

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.

• International Journal of Highway Engineering
• /
• v.15 no.4
• /
• pp.31-42
• /
• 2013

PURPOSES : The purpose of this study is to eliminate the noise of the vehicle after measuring the friction noise obtained from the NCPX (Noble Close ProXimity) method. The pure friction noise between the tire and road pavement could be determined from filtering the compositeness of sound and the influence of the vehicle noise. METHODS: The noise magnitude could be determined by analyzing the sound pressure level (SPL) and sound power level (PWL) along with the noise frequency of a FFT (Fast Fourier Transform) analysis as well as CPB (Constant Percentage Bandwidth) analysis. RESULTS: When the test for measuring the friction noise originated somewhere between tire and road pavement is performed with NCPX method, it must be fulfilled by attaching the surface microphone near the tire. In this condition, the surface microphone can measure the friction noise occurred at between tire and pavement, the chassis noise from the engine and power transfer units, the fluctuating aerodynamic noise, and the turbulence noise directly affected to the surface microphone. By using the NCPX method, the noise occurred at the vehicle must be eliminated for measuring the friction noise between tire and pavement from the traffic noise. CONCLUSIONS: The vehicle's testing engine noise depends on the vehicle and road types. The effect of vehicle's engine noise is less than the friction noise occurred at between tire and pavement at less than 1% effect.

• International Journal of Highway Engineering
• /
• v.17 no.6
• /
• pp.11-18
• /
• 2015

PURPOSES : The purpose of this thesis is to evaluate the effectiveness of an active noise cancellation (ANC) system in reducing the traffic noise level against frequencies from the predictive model developed by previous research. The predictive model is based on ISO 9613-2 standards using the Noble close proximity (NCPX) method and the pass-by method. This means that the use of these standards is a powerful tool for analyzing the traffic noise level because of the strengths of these methods. Traffic noise analysis was performed based on digital signal processing (DSP) for detecting traffic noise with the pass-by method at the test site. METHODS : There are several analysis methods, which are generally divided into three different types, available to evaluate traffic noise predictive models. The first method uses the classification standard of 12 vehicle types. The second method is based on a standard of four vehicle types. The third method is founded on 5 types of vehicles, which are different from the types used by the second method. This means that the second method not only consolidates 12 vehicle types into only four types, but also that the results of the noise analysis of the total traffic volume are reflected in a comparison analysis of the three types of methods. The constant percent bandwidth (CPB) analysis was used to identify the properties of different frequencies in the frequency analysis. A-weighting was applied to the DSP and to the transformation process from analog to digital signal. The root mean squared error (RMSE) was applied to compare and evaluate the predictive model results of the three analysis methods. RESULTS : The result derived from the third method, based on the classification standard of 5 vehicle types, shows the smallest values of RMSE and max and min error. However, it does not have the reduction properties of a predictive model. To evaluate the predictive model of an ANC system, a reduction analysis of the total sound pressure level (TSPL), dB(A), was conducted. As a result, the analysis based on the third method has the smallest value of RMSE and max error. The effect of traffic noise reduction was the greatest value of the types of analysis in this research. CONCLUSIONS : From the results of the error analysis, the application method for categorizing vehicle types related to the 12-vehicle classification based on previous research is appropriate to the ANC system. However, the performance of a predictive model on an ANC system is up to a value of traffic noise reduction. By the same token, the most appropriate method that influences the maximum reduction effect is found in the third method of traffic analysis. This method has a value of traffic noise reduction of 31.28 dB(A). In conclusion, research for detecting the friction noise between a tire and the road surface for the 12 vehicle types needs to be conducted to authentically demonstrate an ANC system in the Republic of Korea.