본 연구에서는 Comfortone 기법 적용 전, 후 음압 수준(sound pressure level, SPL) 변화 정도와 영상의 화질 차이를 정량적으로 비교, 분석하여 소음 감소 기술의 유용성과 임상적으로 유의미한 기준을 제시하고자 하였다. 3.0 T 자기공명영상장비와 ACR 팬텀을 사용하여 Comfortone 적용 전, 후의 T1, T2 강조 영상과 DWI, FLAIR, 3D GE T1 영상을 획득한 후 ACR 정도 관리 가이드라인에 따라 기하학적 정확도, 고대조도 공간분해능, 절편 두께 정확도, 절편 위치 정확도, 영상 강도 균일성, 고스트 신호 백분율, 저대조도 분해능이 적합한지 비교, 평가하였으며 장비 내 표시되는 SPL을 통해 음압 수준의 감소 차이를 비교하였다. Comfortone 기법 적용 여부에 관계없이 DWI 영상은 왜곡이 심해 장비 정도 관리 가이드 라인에는 적합하지 않았으나 나머지 영상에서는 대부분 통계적으로 유의한 차이가 없었다(p>0.05). 몇 개의 항목에서 유의 한 차이가 있더라도(p<0.05) 영상 모두 ACR MRI 팬텀 장비 정도 관리 기준에는 적합했다. 음압 수준 변화는 T1에서 15%, T2와 FLAIR에서 40%, DWI과 3D GE에서 70%의 감소 차이를 보였다. 결론적으로 DWI을 제외하고는 모든 영상에서 검사 시간의 차이 없이 동일한 영상의 화질을 획득할 수 있었다. 따라서 Comfortone 기법을 적용하여 소음은 현저하게 감소시키면서 동시에 임상적으로도 기존의 영상과 동일한 화질의 영상을 제공할 수 있을 것이다.

In the car speaker, because the sound characteristics is changed by the space of car which mount the speaker, the speaker elements must be decide according to sound field. In this study, the nonlinear characteristics, the frequency response and the sound pressure for the same size speakers which is adapted to domestic car model are investigated. The car model is classified to semi-midsize, midsized, full size automobile in order to change the car space. As a results, we can investigate the differences of the force factor and the stiffness of suspension system for speaker. According to the change of the speaker characteristics, the sound pressure is changed, also. In the future, these data will be used to investigate the correlation between the sound quality and measurement data.

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.

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.

PURPOSES : The objective of this study is to provide for the overall SPL (Sound Pressure Level) prediction model by using the NCPX (Noble Close Proximity) measurement method in terms of regression equations. METHODS: Many methods can be used to measure the traffic noise. However, NCPX measurement can powerfully measure the friction noise originated somewhere between tire and pavement by attaching the microphone at the proximity location of tire. The overall SPL(Sound Pressure Level) calculated by NCPX method depends on the vehicle speed, and the basic equation form of the prediction model for overall SPL was used, according to the previous studies (Bloemhof, 1986; Cho and Mun, 2008a; Cho and Mun, 2008b; Cho and Mun, 2008c). RESULTS : After developing the prediction model, the prediction model was verified by the correlation analysis and RMSE (Root Mean Squared Error). Furthermore, the correlation was resulted in good agreement. CONCLUSIONS: If the polynomial overall SPL prediction model can be used, the special cautions are required in terms of considering the interpolation points between vehicle speeds as well as overall SPLs.

본 연구의 목적은 직물 소리의 주관적 감각을 결정하는 객관적 성질 중 가장 밀접한 관계를 지닌 것으로 보고되고 있는 물리적 음압 외에 직물 소리의 미세한 감각 차이를 설명할 수 있는 2차적 물성들을 규명하는 데에 있다. 3dB 이내의 유사 음압을 보이는 전통 견직물 다섯 종을 선택하여, 음향학적 물성치로 음색 요인인 δL과 δf, 심리음향학적 요인인 sharpness[z], roughness[z], fluctuation strength를 측정하고, 직물의 역학적 성질로서 Kawabata Evaluation System (KES)의 17개 물성을 측정하였다. 주관적 감각은 자유식강도측정법에 의하여 부드러움과 시끄러움을 포함한 7개 감각을 평가하였다. 연구 결과, 유사음압의 전통 견직물의 소리에 대한 주관적 감각 중 객관적 물성과 유의한 상관관계를 보이는 감각은 맑음과 거침, 높음이었다. 견직물 소리 간에 차이를 보인 맑음과 거침은 음색 요인인 δL에 의해 영향을 받아서, δL 값이 큰 직물일수록 소리가 더 맑고 덜 거칠게 느껴지는 것으로 나타났다. 또한 주관적인 높음은 roughness[z]와 δf와 유의적 상관관계를 나타내어, roughness[z] 값이 커질수록 또는 δf값이 작아질수록 소리가 더 높게 느껴지는 경향을 보였다. 따라서 유사음압의 전통 견직물의 소리 감각은 음압 외에 roughness[z]와 음색 요인들에 의하여 결정되며, 이를 전통 견직물의 소리 설계에 활용할 수 있을 것으로 기대된다.