• 소음진동
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• 제19권1호
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• pp.16-25
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• 2009

• 환경영향평가
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• 제25권3호
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• pp.175-189
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• 2016

철도소음지도는 환경부 고시 소음 진동관리법에 따라서 그 작성방법이 고시되어 있고, 소음지도 작성 시에 철도소음원 관련 영향인자에 대하여 적용 예측식 별 열차구분을 제시하고 있으며, 열차 특성 입력 시에 브레이크 흡음율을 "0"으로 설정할 것을 제시한다. 소음지도 작성방법이 고시 된 이후 국내의 고속철도차량은 그 구조가 변경되어 가고 있고, 고시된 작성방법에서 제시되지 않은 신규 열차유형도 생겨나고 있다. 따라서 현재의 시점에서 국외의 철도소음 예측식을 활용하여 고시된 소음지도 작성방법에 의하여 철도소음을 예측하는 경우 열차의 유형과 관련된 입력인자에 따른 예측결과를 검토할 필요가 있다. 본 논문에서는 철도소음을 예측할 시에 국내에서 통상적으로 가장 빈번히 사용되는 Schall03을 활용하여 철도소음을 예측하였으며, 열차의 유형 선택, 열차의 특성 중 디스크브레이크 사용율 입력, 레일의 이음매 여부에 의한 예측결과에의 영향을 파악하고자 하였다. 2013년 이후 추가된 신규 국내의 열차에 대하여 대응하는 국외 열차의 유형을 검토하였고, 디스크브레이크사용율 설정은 실측값과 예측값의 차이에 적지 않은 비중을 차지함을 파악할 수 있었으며, 이뿐 아니라, 레일표면의 조도(roughness)레벨 수준도 함께 고찰하고자 하였다. 또한 레일의 이음매가 존재하는 구간에 대하여 예측 시에 이를 고려하지 않았을 경우에의 실측값과의 차이에 대한 분석을 수행하였다.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2008년도 춘계학술대회논문집
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• pp.882-888
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• 2008

The increase in logistics and the emergence of high speed vehicles are aggravating the noise problem, and disturbing large numbers of people. Therefore, growing attention is being paid to the creation and utilization of a noise map in order to grasp and predict the influence of noise, and to establish a policy that effectively reduces noise. However, so far there has been little progress in developing a predictive formula for railway noise, and a noise prediction program suitable for the domestic environment. Therefore, there is a need for a method to apply the overseas prediction formula to domestic railway vehicles. This study evaluated the prediction method, the result of which is similar to that of a real measurement, using a noise map. It also employed a commercial software program, SoundPlan, to predict noise.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2007년도 춘계학술대회논문집
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• pp.882-886
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• 2007

People living in the large cities are exposed to high level noise due to road-traffic, railway-traffic and aircraft. Nowadays, some researches are ongoing to reduce the noise by using noise map. However it has to be decided which prediction model is the most suitable in Korea. In this study, it has been focused on railway noise prediction models which are employed in a commercial software(Sound Plan) and developed by Korea Railroad Research Institute, and comparative study of the prediction models has been made.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2008년도 춘계학술대회논문집
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• pp.500-504
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• 2008

Residents in an area where both trains and cars pass through are exposed to not only road traffic noise but also railway noise. Nevertheless, the degree of annoyance the caused to the residents is being under evaluated as the noises have been evaluated separately. Therefore, this study aimed at evaluating the integrated noise of road traffic and railway, and proving the accuracy of the evaluation result.

• 한국소음진동공학회논문집
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• 제18권7호
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• pp.741-745
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• 2008

Residents in an area where both trains and cars pass through are exposed to not only road traffic noise but also railway noise. Nevertheless, the degree of annoyance the caused to the residents is being under evaluated as the noises have been evaluated separately. Therefore, this study aimed at evaluating the integrated noise of road traffic and railway, and proving the accuracy of the evaluation result.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2011년도 춘계학술대회 논문집
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• pp.618-626
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• 2011

Recent development of related technologies and efficient utilization of the entire country for the purpose of railway construction, and plans are being accelerated. the railway noise has been improved by increasing the high speed railway station, and accelerating the existing trains. Nord2000 which is an overseas noise prediction equation could not be applied directly to the domestic railway vehicles. So the specific vehicles in the Nordic countries which is a similar specification to domestic trains should be selected. Nord2000's accuracy was compared to Schall03, CRN's. Prediction of Ground impedance and Roughness class were carried out at different. In this paper, the result of selected vehicles for Nord2000 was as follows. S-1aX2 was for express trains, N-$^*2c$-3b was for Mugunghwa, S-Pass/wood was for Saemaul, N-4a was for freight trains, N-3a was for subway, the calculation time for Nord2000 took longer than others, in addition, Ground absorption was indispensable to calculate a noise map for Nord2000. As a result, CRN's prediction noise levels at Wonju-si was closest to the measurements. However, the predicted noise levels of Nord2000 was the most accurate.

• 한국철도학회논문집
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• 제15권1호
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• pp.23-28
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• 2012

본 논문에서는 고속 철도 차량의 주행 속도 150~300km/h에서 발생하는 음압을 마이크로폰을 이용하여 측정하고, 주행 속도의 증가에 따라 발생하는 음압의 특성을 분석하였다. 분석된 결과를 통해서 고속철도 차량의 속도 증가와 음압의 관계식을 도출하였으며, 주파수 영역에서 속도 증가에 따른 음압의 증가 특성을 검토하였다. 또한 주행소음 분석을 통해서 고속철도 차량의 주요 소음 발생 위치를 추정하였으며, 마이크로폰 어레이를 활용한 소음지도 분석을 통해서 고속철도 차량의 소음원의 위치를 도출하였다.

• 한국소음진동공학회논문집
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• 제23권4호
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• pp.295-300
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• 2013

The noise map can be applied to predict the effect of noise and establish the noise reduction measure. But the predicted value in the noise map can vary depending on the input variables. Thus, we surveyed the several prediction models and analyzed the changes corresponding to the variables for obtaining the coherency and accuracy of prediction results. As a result, we know that the Schall03 and CRN model can be applied to predict the railway noise in Korea and the correction value, such as bridges correction, multiple reflection correction, curve correction must be used for reflecting the condition of the prediction site. Also, we know that the prediction guideline is an essential prerequisite in order to obtain the unified and accurate predicted value for railway noise.

• 한국소음진동공학회논문집
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• 제20권2호
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• pp.172-178
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• 2010

The multiple regression analysis and path analysis in each dominant area of noise source are conducted to analyze the relationship between dependent variables like annoyance and independent ones such as noise and non-noise factors. The multiple regression analysis shows that impact of noise factors is the highest to annoyance in dominant areas of road traffic and railway noise. Meanwhile, impact of non-noise factors such as sensitivity and satisfaction of environment on annoyance is also high in these areas. The path analysis result for multivariate analysis between various independent and dependent variables is similar to that of the multiple regression analysis. However, noise factor is the greatest factor influent on annoyance in the dominant areas of the combined noise, and relationship between annoyance and sensitivity is the highest in combined area exposed to road traffic noise and railway noise.