• 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.

• 한국소음진동공학회논문집
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• 제22권2호
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• pp.193-197
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• 2012

Road traffic noise map is effective method to save cost and time for environmental noise assessment. Generally, noise is calculated by using theoretical equation of noise prediction, and the calculated result can be influenced by various input factors. Especially, domestic vehicle classification method for traffic flow and heavy vehicle percentage is different from that of foreign countries. Thus, this can cause effect on the noise prediction results. In this study, noise prediction results by using domestic vehicle classification method are compared with those by foreign methods.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2008년도 추계학술대회논문집
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• pp.709-714
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• 2008

The various computer programs are used in computer simulation of the traffic noise prediction. But the difference or problem of calculation method used for road traffic noise prediction is not exactly investigated. In this paper, Road traffic noise is predicted on the specific regions by using four prediction methods such as XPS31-133 model(France), RLS-90 model(Germany), ASJ RTN model(Japan) and FHWA model(U.S.A.), which are operated by a program named SoundPLAN, a program to predict road traffic noise. Those prediction values are compared with a measurement value. The results show that four prediction values for taraffic noise are a little different, because of various input factors according to the prediction methods.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2007년도 춘계학술대회논문집
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• pp.877-881
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• 2007

Recently, noise map is used widely by synthetic estimation method for noise reduction. For correct manufacture of noise map, selection of suitable noise prediction method is important. This study compares XPS31-133 with CRTN, RLS90 which are widely used by foreign commercial noise maps.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2002년도 춘계학술대회 논문집
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• pp.86-89
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• 2002

In NC machining, the ability to automatically generate an optimal process plan is an essential step toward achieving automation, higher productivity, and better accuracy. For this ability, a system that is capable of simulating the actual machining process has to be designed. In this paper, a milling process simulation system for the general NC machining was presented. The system needs first to accurately compute the cutting configuration. ME Z-map(Moving Edge node Z-map) was developed to reduce the entry/exit angle calculation error in cutting force prediction. It was shorn to drastically improve the conventional Z-map model. Experimental results applied to the pocket machining show the accuracy of the milling process simulation system.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1996년도 춘계학술대회 논문집
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• pp.125-129
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• 1996

In this study, a method is proposed for the cutting force prediction of Ball-end milling process using Z-map is proposed. Any types of cutting area generated from previous cutting process can be expressed in z-map data. Cutting edge of a ball-end mill is divided into a set of finite cutting edges and the position of this edge is projected to the cross-section plane normal to the Z-axis. Comparing this projected position with Z-map data of cutting area and determining whether it is in the cutting region, total cutting force can be calculated by means of numerical integration. A series of experiments such as side cutting and upward/downard cutting was performet to verify the simulated cutting force.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2006년도 춘계학술대회논문집
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• pp.750-753
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• 2006

Noise prediction is required as part of an environmental impact assessment. However, there has not been any comprehensive study or review en the major factors of specific vehicles affecting traffic noise so that there is difficulty when trying to figure out the source of noise. This study was to evaluate the noise effect of specific vehicles passing through a certain road by using noise map.

• 한국소음진동공학회논문집
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• 제15권6호
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• pp.635-644
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• 2005

This paper is. a study on relation between road traffic noise(RTN) and sound power level(PWL). At present, many experimental formulae and prediction formulae are used for prediction of RTN. But these formulae are difficult to appiy to the metropolitan area because these formulae are inaccurate in the different condition from reference condition. This paper calculate RTN and PWL of each prediction formula, choose the best one and make a noise map of the subject area. Procedure is as follows. First, calculate $L_{eq}$ of RTN using experimental formulae and prediction formulae. Second, calculate PWL using $L_{eq}$ of RTN and distance attenuation for point source at semi-free field. Third, choose the most accurate formula. And finally, make a noise map of the subject area at present and future. The result using noise map will be able to apply to application field. Noise mapping tool used on this paper is Raynoise program using Ray Tracing Method(RTM), Mirror Image Source Method(MISM) and Hybrid Method(HM).

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1997년도 춘계학술대회 논문집
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• pp.1003-1008
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• 1997

In this paper, the prediction of cutting force and tool deflection in the ball-end milling process are studied. Identifying various cutting region using Z-map, cutting force in the ball-end milling process can be predicted. Cutting force deflects the tool and the tool deflection changes the cutting force. Tool deflection is included in the cutting force prediction. Tool deflecition also causes machining error of the machined surface. A series of experiments were performed to verify the simulated cutting force and machining error.

• 방송공학회논문지
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• 제27권6호
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• pp.906-913
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• 2022

본 논문에서는 희소 깊이 영상과 컬러 영상을 이용해 조밀한 깊이 영상을 추정하는 깊이 완성을 수행하기 위해 최근접 이웃 커널 기술을 사용하는 방식의 네트워크를 제안한다. 먼저 예측하고자 하는 깊이 영상을 대략적인 깊이 정보의 구조 정보를 포함하는 부분과 세밀한 깊이 정보를 가지는 상세 부분으로 분할하여 예측하는 방식을 제안한다. 이 과정에서 깊이 영상의 구조 및 상세 정보는 분류 기법과 회귀 기법을 활용하여 각각 추정하였으며, 특히 분류 과정에서 최근접 이웃 커널 정보를 활용하여 주변 정보를 통해 분류를 진행하는 방식을 제안하였다. 제안 방식은 기존의 희소 깊이 완성 방식과 비교하여 우수한 성능을 나타냈고, 시각적으로도 만족할만한 결과를 보이게 됨을 확인하였다.