• 한국ITS학회 논문지
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• 제8권2호
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• pp.60-66
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• 2009

Acceleration Noise는 교통류의 안정성을 진단하는데 중요한 지표이다. 하지만, 기존의 연구에서는 개별차량의 Acceleration Noise에 대해서만 수행되었고, 거시적 관점에서의 Acceleration Noise에 대해서는 연구가 이루어지지 않은 실정이다. 본 논문에서는 거시적 교통류 모니터링 지표인 Network Acceleration Noise를 제안하고, 이를 분석하여 거시 교통류 모니터링 활용방안에 대한 연구를 수행하였다.

• 한국정보과학회:학술대회논문집
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• 한국정보과학회 2004년도 가을 학술발표논문집 Vol.31 No.2 (3)
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• pp.142-144
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• 2004

To provide more qualified data service on the HFC(Hybrid-Fiber Coaxial) access network, the channel characteristics of upstream transmission band should be carefully investigated and analysed. It will be easier to do network management if the monitoring system for noise measurement in the network is available, In this paper, noise analysis method and the frequency selection method in the upstream band for duplex transmission are suggested. And, Data aquisition device for the signal measurement Is implemented. With this network monitoring system, field test and the result from the collected data are described.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2003년도 춘계학술대회논문집
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• pp.950-955
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• 2003

This paper introduces an enhanced condition monitoring and diagnosis system recently developed for rotating machinery. In the system, the data aquisition/monitoring signal processing, machine condition classifier, case-based reasoning and demonstration modules are effectively integrated with user-friendliness so that machine operators can easily monitor and diagnose the status of rotating machinery in operation. Some of the new features include the directional spectrum, case-based reasoning and neural network techniques. And the demonstrator modules for fault diagnosis of a Bear driving system and for basic understanding of the rotor dynamics are provided to help the potential users better understand the system.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2003년도 춘계학술대회논문집
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• pp.1187-1192
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• 2003

The railroad noise has been considered as one of environment pollution and complaints about it have been increasing every you. Therefore, the establishment of railroad noise monitoring network is necessary. It will be designed for monitoring railroad noise, storing data of railroad noise continuously and providing the fundamental knowledge for the measures of railroad noise. For this, we investigated the actual condition of railroad noise and status of noise level by floor in apartments around the capital region, Daejeon, Daegu, Gwangju, and Busan. Additionally, we present the basic data that will be used for predicting the noise level near railroad in the environmental impact assessment

• 한국소음진동공학회논문집
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• 제15권5호
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• pp.511-518
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• 2005

The railroad noise has been considered as one of environment pollution and complaints about it have been increasing every year. Therefore, the establishment of railroad noise monitoring network is necessary. It will be designed for monitoring railroad noise, storing data of railroad noise continuously and providing the fundamental knowledge for the measures of railroad noise. For this, we investigated the actual condition and status of railroad noise according to distance around Daejeon, Daegu, Gwangju, and Busan. This paper shows the basic data that will be used for predicting the noise level near railroad in the environmental impact assessment.

• 대한공간정보학회지
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• 제18권3호
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• pp.91-96
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• 2010

도시는 유기체와 같이 외형적 확산과 내부공간구조가 끊임없이 변화하며, 교통 정보 통신기술의 발달에 따라 변화의 속도와 형태를 달리해 왔다. 특히 교통의 발달은 도시 외형적 성장에 있어서 가장 중요한 원인이 되었으며 이러한 교통체계는 토지이용의 변화에서 비롯되었고 소음 등 각종 환경문제를 야기하였다. 본 논문은 국가소음정보시스템에서 제공되는 소음측정망 자료를 이용하여 용도지역별 소음변화특성을 분석하였다. 그 결과 도시공간상의 용도지역별 소음분포를 파악할 수 있었으며 이를 이용하여 용도지역별 소음지도를 제작할 수 있는 기반을 조성 할 수 있었다.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2004년도 추계학술대회논문집
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• pp.619-624
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• 2004

In this research, the structural health monitoring method using wavelet packet analysis and artificial neural network (ANN) is developed. Wavelet packet Transform (WPT) is applied to the response acceleration of a 3 element-cantilever beam which is subjected to impulse load and Gaussian random load to decompose the response signal, then the energy of each component is calculated. The first ten largest components in magnitude among the decomposed components are selected as input to an ANN to identify the damage location and severity. This method successfully predicted the amount of damage in the structure when the structure is subjected to impulse load. However, when the beam is subjected to Gaussian random load which can be considered as ambient vibration it did not yield satisfactory results. This method is applicable to structures such as machinery gears that are subjected to repetitive loads.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제2권2호
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• pp.95-99
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• 2002

The Loose Part Monitoring System(LPMS) has been designed to detect. locate and evaluate detached or loosened parts and foreign objects in the reactor coolant system. In this paper, at first, we presents an application of the back propagation neural network. At the preprocessing step, the moving window average filter is adopted to reject the reject the low frequency background noise components. And then, extracting the acoustic signature such as Starting point of impact signal. Rising time. Half period. and Global time, they are used as the inputs to neural network . Secondly, we applied the neural network algorithm to LPMS in order to estimate the mass of loose parts. We trained the impact test data of YGN3 using the backpropagation method. The input parameter for training is Rising clime. Half Period amplitude. The result shored that the neural network would be applied to LPMS. Also, applying the neural network to thin practical false alarm data during startup and impact test signal at nuclear power plant, the false alarms are reduced effectively.

• 한국소음진동공학회논문집
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• 제20권2호
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• pp.166-171
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• 2010

Wired monitoring systems have been used for damage detection and dynamic analysis of large structures(bridges, dams, plants, etc.). However, the real-world applications still remain limited, mainly due to time and cost issues inherent to wired systems. In recent years, an increasing number of researchers have adopted WSN(wireless sensor network) technologies to the field of SHM(structural health monitoring). Accurate time synchronization is most critical for the wireless approach to be feasible for SHM purpose, along with sufficient wireless bandwidth and highly precise measuring resolution. To satisfy technical criteria stated above, a wireless vibration monitoring system that uses high-precision MEMS(micro-electro-mechanical system) sensors and A/D convertor is discussed in detail. It was found experimentally that the level of time synchronization fell within $200\;{\mu}sec$.

• 한국대기환경학회지
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• 제30권3호
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• pp.233-244
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• 2014

The objective of this study was to explore the characteristics of concentration of indoor air pollutants, such as $PM_{10}$, $CO_2$, and $NO_2$, measured by tele-monitoring system in a Seoul Metropolitan underground railway station from January 1, 2008 to December 31, 2012. The annual average concentration of indoor air pollutants actually varied over a wide range and was found to exhibit marked variation with time and measurement sites (tunnel inlet, platform, and concourse). After installing platform screen doors, the average $PM_{10}$ concentration on platform and concourse was decreased by 43.8% and 31.2%, respectively during the study periods. The relationship between the concentration of $PM_{10}$ and meteorological parameters (relative humidity and rainfall) or the Asian dust events was regarded as statistically significant. The correlations between the number of boarding/alighting passengers and $PM_{10}$, $CO_2$, and $NO_2$ were calculated. A p-value of less than 0.01 was regarded as significant except $NO_2$. The I/O ratio of $PM_{10}$ concentration was elevated after a congested time (about 08:00 am). The average I/O ratios of $NO_2$ were observed in concourse and platform on 03:00 am with $1.76{\pm}0.91$ and $1.50{\pm}0.51$, respectively. The average daily variation of standard excess rate of $PM_{10}$ and $NO_2$ concentration in concourse and platform was investigated. The highest standard excess rate was observed on 21:00 (09:00 pm).