• 한국지능시스템학회:학술대회논문집
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• 한국지능시스템학회 2008년도 춘계학술대회 학술발표회 논문집
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• pp.276-285
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• 2008

교통량조사 방법은 루프검지기와 피에조센서를 주로많이 사용하여 차량의 숫자만을 파악하여 교통주기를 계산하는 방법을 사용하나 교통량을 파악하는 방법은 단순한 교통량에담 국한되는것이 아니라 다중교통특성인 진입로의 길이, 도로의 폭. 보행자의 수, 통과차량수. 지체자량수등 관련되는 교통대안을 총 망라하여 새로운 교통량인 혼잡도라는 개념을 대표대안으로 선정하면 바로 교통주기에 적용할수 있다. 본 논문에서는 서로 관련성이 없는 교통대안들을 AHP 방법을 사용하여 교통주기 계산에 즉시 사용할수 있는 공통 분모인 새로운 교통대안을 찾아내는 알고리즘을 개발하고 이를 새로운 교통량 개념인 혼잡도라는 교통량을 찾아내는 퍼지센서알고리즘을 구성하는데 적용한다. 시뮬레이션을 통해 타 교통제어방법과 비교하여 지체차량시간이 줄어듬을 보여준다.

• 대한전기학회논문지:전력기술부문A
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• 제55권12호
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• pp.505-513
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• 2006

One of the major reasons for recent blackout, like August 14, 2003 blackout in the US and Canada has been insufficient voltage/reactive power support. For the stable reactive power management, a new approach for the voltage monitoring and control structure is required in the market environment. This paper proposes the effective localized-voltage control scheme using the information from pilot buses at each zone. In this paper, the steady state voltage monitoring and control (SSVMC) is adopted and illustrated for the voltage control scheme during steady state because it is thought as the systemic algorithm to explain voltage profile phenomenon before and after contingencies. And the concept of electrical distance is applied to simultaneously achieve both clustering the voltage control zone, and selecting the pilot bus as the representative node at each control zone. Applying SSVMC based on the structure with clustering and pilot bus enables system operators to monitor and understand the system condition much more easily, to monitor and control the voltage in real-time more manageably, and to respond quickly to a disturbance. The proposed voltage control scheme has been tested on the IEEE 14-bus system with the numerical analysis to examine the system reliability and structure efficiency.

• 전자공학회논문지SC
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• 제44권4호통권316호
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• pp.74-78
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• 2007

의료용으로 사용되는 새로운 개념의 환자감시용 센서 매트와 그 신호처리방식을 제시하였다. 제시된 센서 매트와 플라스틱 광섬유를 교차시켜 배치한 구조를 갖는 내부 센서층을 갖는 구조로 제작하였다. 플라스틱 광섬유의 대구경 특성을 이용하여 불필요한 외부환경 요인에 의하여 발생되는 잡음요소들을 평균화하여 신호성분만을 통과시키는 대역통과필터를 구현하였다. 센서 출력단에 신호처리부를 부가하여 추가로 불필요한 성분들을 제거하여 잡음제거 능력을 향상시켰고 지능형 알고리즘을 사용하여 신뢰성 있는 환자호흡감지방식을 구현하였다. 신호와 주변잡음 모두에게 고감도를 보이는 기존의 기계적인 방식을 사용하는 감지방식과는 달리 본 연구에서 제시된 방식은 신뢰성 있는 호흡 감지가 가능함을 보여주었다.

• Nuclear Engineering and Technology
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• 제26권2호
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• pp.294-299
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• 1994

운전중인 Westinghouse형 원자력 발전소에 디지탈 감시계통을 설치하였을 시의 정량적인 여유도 잇점을 계산하였다. 적용된 발전소는 영광 원자력 1호기 6주기이며 참조한 디지탈 감치계통은 ABB-CE 사의 COLSS이다. 고려된 핵연료 설계제한 한계는 DNBR과 LUCA Fq이다. 평가를 위해 기존 CAOC 한계내에서 200가지의 3-D 출력 분포를 계산하였다. 영광 1호기 6주기의 DNB 관련 가장 제한적인 사고인 CEA 인출사고를 해석하였다. 평가결과 DMS를 설치하면 DNB와 LOCA Fq 관점에서 모두 7%출력 증가 효과를 가져올 수 있을 것으로 나타났다. DMS를 설치하면 PCI 한계도 감시할 수 있다.

• 한국철도학회:학술대회논문집
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• 한국철도학회 2006년도 추계학술대회 논문집
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• pp.1354-1363
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• 2006

Until now, NATM(New Austrian Tunneling Method) has been increasingly developed based on concept of making use of ground as support. Also, NATM in its essence is a method of risk based on monitoring behaviour of tunnel. This Monitoring is irreplaceable for the quality construction of tunnel, and safety of tunnel itself. Pre-reinforcement ahead of a tunnel face using long steel pipes in NATM, known as the RPUM(Reinforced Protective Umbrella Method), is the auxiliary method to sustain the stability of a tunnel face and reduce the ground settlements. Since design of RPUM has been dependent on the empirical design, it is necessary to develop the improved design methods. In this study, to understand behaviour of steel pipes, it is monitored displacement of tunnel crown, axial force of rock bolt, displacement and axial stress of steel pipes. Also, in order to clarify the mechanical behaviour and RPUM effects, 3-Dimensional numerical analysis is performed that various cases of different parameter combinations including original length and repeated length of steel pipes, installation width and angle, repeated length of steel. In the results of comparison monitoring with analysis, it is suggested more economical and efficient design technique than empirical design methods.

• 한국항해항만학회:학술대회논문집
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• 한국항해항만학회 2006년도 International Symposium on GPS/GNSS Vol.1
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• pp.455-458
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• 2006

The Real Time Kinematic (RTK) technique is the most productive and accurate GPS positioning method today, as it can be determinate position within few centimeters instantly. This method is widely used for applications such as surveying, structure monitoring and machine guidance etc. In order to perform RTK processing for large scale systems (i.e. precise vehicle monitoring with many rovers), many expensive RTK receivers and same number of bidirectional communication units have to be installed to collect observation data communicate with the reference site and monitor its RTK solutions. Moreover, if applications require remote control or apply sensing instruments, we have to install computers at each rover. To limit expense and complexity of system management with a large number of rovers, we have developed server based RTK processing platform to share RTK function for all rovers. The system can be process many GPS stations with a single personal computer. we have also developed a specialized dual frequency GPS receiver unit without on-board RTK processing capability to reduce receiver cost in order to demonstrate the advantage of our server based RTK platform. This paper describes the concept of our server based RTK platform and specialized GPS receiver unit with existing applications in Japan.

• 전기학회논문지
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• 제65권7호
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• pp.1252-1256
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• 2016

Internet of Things(IoT)-devices are now expanding inter-connecting networking technologies to invent healthcare monitoring system especially for assessing physiological conditions of the chronically-ill patients those with cardiovascular diseases. Hence, IoT system is expected to be utilized for home healthcare by dedicating the original usage of IoT devices to collect the biomedical data such as electrocardiogram(ECG) and photoplethysmography(PPG) signal. The aim of this work is to implement health monitoring system by integrating IoT devices with Raspberry-pi components to measure and analyze ECG and the multi-channel PPG signals. The acquired data and fiducial features from our system can be transmitted to mobile devices via wireless networking technology to support the concept of tele-monitoring services based on IoT devices.

• Smart Structures and Systems
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• 제15권1호
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• pp.191-207
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• 2015

Proper placement of sensors plays a key role in construction and implementation of an effective structural health monitoring (SHM) system. This paper proposes a novel methodology called the distributed monkey algorithm (DMA) for the optimum design of SHM system sensor arrays. Different from the existing algorithms, the dual-structure coding method is adopted for the representation of design variables and the single large population is partitioned into subsets and each subpopulation searches the space in different directions separately, leading to quicker convergence and higher searching capability. After the personal areas of all subpopulations have been finished, the initial optimal solutions in every subpopulation are extracted and reordered into a new subpopulation, and the harmony search algorithm (HSA) is incorporated to find the final optimal solution. A computational case of a high-rise building has been implemented to demonstrate the effectiveness of the proposed method. Investigations have clearly suggested that the proposed DMA is simple in concept, few in parameters, easy in implementation, and could generate sensor configurations superior to other conventional algorithms both in terms of generating optimal solutions as well as faster convergence.

• Nuclear Engineering and Technology
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• 제54권2호
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• pp.644-652
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• 2022

During the pyroprocessing operation, various signals can be collected by process monitoring (PM). These signals are utilized to diagnose process states. In this study, feasibility of using PM for nuclear safeguards of electrorefining operation was examined based on the use of machine learning for detecting off-normal operations. The off-normal operation, in this study, is defined as co-deposition of key elements through reduction on cathode. The monitored process signal selected for PM was cathode potential. The necessary data were produced through electrodeposition experiments in a laboratory molten salt system. Model-based cathodic surface area data were also generated and used to support model development. Computer models for classification were developed using a series of recurrent neural network architectures. The concept of transfer learning was also employed by combining pre-training and fine-tuning to minimize data requirement for training. The resulting models were found to classify the normal and the off-normal operation states with a 95% accuracy. With the availability of more process data, the approach is expected to have higher reliability.

• Smart Structures and Systems
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• 제5권4호
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• pp.415-426
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• 2009

This study focuses on the concept of multi-scale wireless sensor networks for damage detection in civil infrastructure systems by first over viewing the general network philosophy and attributes in the areas of data acquisition, data reduction, assessment and decision making. The data acquisition aspect includes a scalable wireless sensor network acquiring acceleration and strain data, triggered using a Restricted Input Network Activation scheme (RINAS) that extends network lifetime and reduces the size of the requisite undamaged reference pool. Major emphasis is given in this study to data reduction and assessment aspects that enable a decentralized approach operating within the hardware and power constraints of wireless sensor networks to avoid issues associated with packet loss, synchronization and latency. After over viewing various models for data reduction, the concept of a data-driven Bivariate Regressive Adaptive INdex (BRAIN) for damage detection is presented. Subsequent examples using experimental and simulated data verify two major hypotheses related to the BRAIN concept: (i) data-driven damage metrics are more robust and reliable than their counterparts and (ii) the use of heterogeneous sensing enhances overall detection capability of such data-driven damage metrics.