• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
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• pp.151-155
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• 1996

To automate an excavator the control issues resulting from environmental uncertainties must be solved. In particular the interactions between the excavation tool and the excavation environment are dynamic, unstructured and complex. In addition, operating modes of an excavator depend on working conditions, which makes it difficult to derive the exact mathematical model of excavator. Even after the exact mathematical model is established, it is difficult to design of a controller because the system equations are highly nonlinear and the state variable are coupled. The objective of this study is to design a multi-layer neural network which controls the position of excavator's attachment. In this paper, a dynamic controller has been developed based on an error back-propagation(BP) neural network. Computer simulation results demonstrate such powerful characteristics of the proposed controller as adaptation to changing environment, robustness to disturbance and performance improvement with the on-line learning in the position control of excavator attachment.

• 한국통신학회논문지
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• 제27권1B호
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• pp.114-124
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• 2002

본 논문에서는 실내 전파환경에서의 페이딩을 분석하기 위하여 영상법 기반의 3차원 광선추적법에 패치산란모델을 첨가한 모델을 제시하였다. 영상법 기반의 광선추적법은 정확한 경로를 얻을 수 있다는 장점 때문에, 안테나의 빔패턴 및 편파, 그리고 전파의 진행에 따른 편파를 고려함으로써 페이딩 특성 분석이 가능하다. 또한 실내 구조물을 모델링하기 위한 패치산란모델은 패치형태의 직사각형 평면에 대한 RCS (Radar Cross Section)를 이용하여 입사에 대한 산란현상을 정의한 것으로써, 책상이나 테이블 같은 평면적인 실내 구조물에 대한 산란현상을 각각의 구조물에 대한 영상 안테나를 발생시키는 복잡한 과정 없이 간단하게 해석하기 위한 것이다. 제안된 모델은 신호강도 뿐만 아니라 채널의 페이딩 특성을 예측할 수 있기 때문에 안테나 종류별 편파 다이버시티 기법의 성능을 분석하는데 이용될 수 있다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2004년도 심포지엄 논문집 정보 및 제어부문
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• pp.92-94
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• 2004

We become an industry information society which is advanced to the altitude with the today. The information to be loading various goods each other together at a circumstance environment is increasing extremely. The restriction recognizes the data of many Quantity and it follows because the human deals the task to classify. The development of a mathematical formulation for solving a problem like this is often very difficult. But Artificial intelligent systems such as neural networks have been successfully applied to solving complex problems in the area of pattern recognition and classification. So, in this paper a neural network approach is used to recognize and classification problem was broken into two steps. The first step consist of using a neural network to recognize the existence of purpose pattern. The second step consist of a neural network to classify the kind of the first step pattern. The neural network leaning algorithm is to use error back-propagation algorithm and to find the weight and the bias of optimum. Finally two step simulation are presented showing the efficacy of using neural networks for purpose recognition and classification.

• 한국전자파학회논문지
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• 제12권5호
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• pp.772-772
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• 2001

본 논문에서는 영상법 기반의 3차원 광선추적법에 패치산란모델을 이용하여 실내 구조물을 고려할 수 있는 실내 전파모델링 방법을 제시하였다. 실내 구조물을 모델링하기 위한 패치산란모델은 패치형태의 직사각형 평면에 대한 RCS를 이용하여 입사에 대한 산란현상을 정의한 것으로써, 책상이나 테이블 같은 평면적인 실내구조물에 대한 산란현상을 각각의 구조물에 대한 영상 안테나를 발생시키는 복잡한 과정 없이 간단하게 해석하기 위한 것이다. RCS는 간단히 입사 전력에 대한 산란 전력의 비로 정의되며 본 논문에서는 다양한 수신 각도에서 바라보는 bistatic RCS를 물리광학(Physical Optics)을 이용하여 수식적으로 유도하여 패치산란모델에 이용하였다. 또한 실내의 다중경로 성분에 대해 계산하지 않는 패치산란모델을 실내에 적용하기 위하여 복잡한 수식보다는 단순한 보정값인 실내보정값을 정의하였는데, 본 논문에서는 이 값을 다양한 패치 환경의 측정에 의한 경험적 상수로 처리함으로써 RCS의 고려만으로는 실내에 적용할 수 없는 점을 극복하였다.

• 한국전자파학회논문지
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• 제12권5호
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• pp.722-733
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• 2001

본 논문에서는 영상법 기반의 3차원 광선추적법에 패치산란모델을 이용하여 실내 구조물을 고려할 수 있는 실내 전파모델링 방법을 제시하였다. 실내 구조물을 모델링하기 위한 패치산란모델은 패치형태의 직사각형 평면에 대한 RCS를 이용하여 입사에 대한 산란현상을 정의한 것으로써, 책상이나 테이블 같은 평면적인 실내구조물에 대한 산란현상을 각각의 구조물에 대한 영상 안테나를 발생시키는 복잡한 과정 없이 간단하게 해석하기 위한 것이다. RCS는 간단히 입사 전력에 대한 산란 전력의 비로 정의되며 본 논문에서는 다양한 수신 각도에서 바라보는 bistatic RCS를 물리광학(Physical Optics)을 이용하여 수식적으로 유도하여 패치산란모델에 이용하였다. 또한 실내의 다중경로 성분에 대해 계산하지 않는 패치산란모델을 실내에 적용하기 위하여 복잡한 수식보다는 단순한 보정값인 실내보정값을 정의하였는데, 본 논문에서는 이 값을 다양한 패치 환경의 측정에 의한 경험적 상수로 처리함으로써 RCS의 고려만으로는 실내에 적용할 수 없는 점을 극복하였다.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2007년도 Proceedings of ISRS 2007
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• pp.286-289
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• 2007

This study is to develop a cloud detection algorit1un for COMS and it is currently tested by using MODIS level 2B and MTSAT-1R satellite radiance data. Unlike many existing cloud detection schemes which use a threshold method and traditional statistical methods, in this study a feed-forward neural network method with back-propagation algorit1un is used. MODIS level 2B products are matched with feature information of five-band MTSAT 1R image data to form the training dataset. The neural network is trained over the global region for the period of January to December in 2006 with 5 km spatial resolution. The main results show that this model is capable to detect complex cloud phenomena. And when it is applied to seasonal images, it shows reliable results to reflect seasonal characteristics except for snow cover of winter. The cloud detection by the neural network method shows 90% accuracy compared to the MODIS products.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제4권3호
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• pp.243-257
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• 2010

Rapid developments in wireless sensor networks have extended many applications, hence, many studies have developed wireless sensor network positioning systems for indoor environments. Among those systems, the Global Position System (GPS) is unsuitable for indoor environments due to Line-Of-Sight (LOS) limitations, while the wireless sensor network is more suitable, given its advantages of low cost, easy installation, and low energy consumption. Due to the complex settings of indoor environments and the high demands for precision, the implementation of an indoor positioning system is difficult to construct. This study adopts a low-cost positioning method that does not require additional hardware, and uses the received signal strength (RSS) values from the receiver node to estimate the distance between the test objects. Since many objects in indoor environments would attenuate the radio signals and cause errors in estimation distances, knowing the path loss exponent (PLE) in an environment is crucial. However, most studies preset a fixed PLE, and then substitute it into a radio propagation loss model to estimate the distance between the test points; such method would lead to serious errors. To address this problem, this study proposes a Path Loss Exponent Estimation Algorithm, which uses only four beacon nodes to construct a radio propagation loss model for an indoor environment, and is able to provide enhanced positioning precision, accurate positioning services, low cost, and high efficiency.

• 한국산업정보학회논문지
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• 제17권2호
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• pp.19-27
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• 2012

In railway tunnel environment, the reliability of a high-data-rate and real-time train-to-wayside communication should be maintained especially when high-speed train moves along the track. In China and Europe, the communication frequency around 900 MHz is widely used for railway applications. At this carrier frequency band, both of the solutions based on continuously laid leaky coaxial cable (LCX) and discretely installed base-station antennas (BSAs), are applied in tunnel radio coverage. Many available works have concentrated on the radio-wave propagation in tunnels by different kinds of prediction models. Most of them solve this problem as natural propagation in a relatively large hollow waveguide, by neglecting the transmitting/receiving (Tx/Rx) components. However, within such confined areas like railway tunnels especially loaded with train, the complex communication environment becomes an important factor that would affect the quality of the signal transmission. This paper will apply a full-wave numerical method to this case, for considering the BSA or LCX, train antennas and their interacted environments, such as the locomotive body, overhead line for power supply, locomotive pantograph, steel rails, ballastless track, tunnel walls, etc.. Involving finite-difference time-domain (FDTD) method and uni-axial anisotropic perfectly matched layer (UPML) technique, the entire wireless RF downlinks of BSA and LCX to tunnel space to train antenna are precisely modeled (so-called integrative modeling technique, IMT). When exciting the BSA and LCX separately, the field distributions of some cross-sections in a rectangular tunnel are presented. It can be found that the influence of the locomotive body and other tunnel environments is very significant. The field coverage on the locomotive roof plane where the train antennas mounted, seems more homogenous when the side-laying position of the BSA or LCX is much higher. Also, much smoother field coverage solution is achieved by choosing LCX for its characteristic of more homogenous electromagnetic wave radiation.

• Journal of electromagnetic engineering and science
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• 제4권4호
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• pp.175-182
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• 2004

When the M-ary signal experiences the Rayleigh fading, the diversity schemes can reduce the effect of fading since the probability that all the signals components will fade simultaneously is reduced considerably. The symbol error probabilities for various M-ary signals, such as MDPSK(M-ary DPSK) and MPSK(M-ary PSK), are mathematically derived for the Selection Combining 2(SC-2) and Selection Combining 3(SC-3) demodulation system which requires a less complex receiver than Maximum Ratio Combining(MRC). The propagation model used in this paper is the frequency-nonselective slow Rayleigh fading channel corrupted by the Additive White Gaussian Noise(AWGN). The numerical results presented in this paper are expected to provide information for the design of radio system using M-ary modulation method for above mentioned channel environment.

• Ocean Systems Engineering
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• 제2권1호
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• pp.1-16
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• 2012

Offshore wind turbines are complex structural and mechanical systems located in a highly demanding environment. This paper proposes a multi-level system approach for studying the structural behavior of the support structure of an offshore wind turbine. In accordance with this approach, a proper numerical modeling requires the adoption of a suitable technique in order to organize the qualitative and quantitative assessment in various sub-problems, which can be solved by means of sub-models at different levels of detail, both for the structural behavior and for the simulation of loads. Consequently, in a first place, the effects on the structural response induced by the uncertainty of the parameters used to describe the environmental actions and the finite element model of the structure are inquired. After that, a meso-level FEM model of the blade is adopted in order to obtain the detailed load stress on the blade/hub connection.