• 한국소음진동공학회논문집
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• 제14권12호
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• pp.1241-1248
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• 2004

This paper presents an acoustic source localization technique on 2D cavity model in flow using a phased microphone array. Investigation was performed on cavity flows of open and closed types. The source distributions on 2D cavity flow were investigated in an anechoic open-jet wind tunnel. The array of microphones was placed outside the flow to measure the far field acoustic signals. The optimum sensor placement was decided by varying the relative location of the microphones to improve the spatial resolution. Pressure transducers were flush-mounted on the cavity surface to measure the near-filed pressures. It is shown that the propagated far field acoustic pressures are closely correlated to the near-field pressures and their spectral contents are affected by the cavity parameter L/D.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2003년도 춘계학술대회논문집
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• pp.701-708
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• 2003

This paper presents an acoustic source localization technique on 2D cavity model in flow using a phased microphone way. Investigation was performed on cavity flows of open and closed types. The source distributions on 2D cavity flow were investigated in anechoic open-jet wind tunnel. The array of microphones was placed outside the flow to measure the far field acoustic signals. The optimum sensor placement was decided by varying the relative location of the microphones to improve the spatial resolution. Pressure transducers were flush-mounted on the cavity surface to measure the near-filed pressures. It is shown that the propagated far field acoustic pressures are closely correlated to the near-field pressures. It is also shown that their spectral contents are affected by the cavity parameter L/D.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권10호
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• pp.4971-4987
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• 2019

Node localization is the basic task of underwater wireless sensor networks (UWSNs). Most of the existing underwater localization methods rely on ranging accuracy. Due to the special environment conditions in the ocean, beacon nodes are difficult to deploy accurately. The narrow bandwidth and high delay of the underwater acoustic communication channel lead to large errors. In order to reduce the ranging error and improve the positioning accuracy, we propose a localization algorithm based on ranging correction and inertial coordination. The algorithm can be divided into two parts, Range Correction based Localization algorithm (RCL) and Inertial Coordination based Localization algorithm (ICL). RCL uses the geometric relationship between the node positions to correct the ranging error and obtain the exact node position. However, when the unknown node deviates from the deployment area with the movement of the water flow, it cannot communicate with enough beacon nodes in a certain period of time. In this case, the node uses ICL algorithm to combine position data with motion information of neighbor nodes to update its position. The simulation results show that the proposed algorithm greatly improves the positioning accuracy of unknown nodes compared with the existing localization methods.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2002년도 학술대회지
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• pp.759-762
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• 2002

Automobile aeroacoustics Is a developing area of technology where experimental and theoretical tools are being continuously refined to understand, analyze and modify the noise-generating mechanisms in the vehicle flow. Main sources of ground vehicle exterior noise are the tires (tire/road interaction) and the unsteady flow field around the vehicle. In this study, the sound source localization of a rolling tire was applied to the measurement of radiated sound by using an acoustic mirror system. A possible flow pattern that develops is suggested based on detailed wind tunnel investigations with a rotating wheel in contact with a moving belt.

• International Journal of Control, Automation, and Systems
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• 제2권4호
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• pp.485-493
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• 2004

Open-loop position estimation methods are commonly used in mobile robot applications. Their strength lies in the speed and simplicity with which an estimated position is determined. However, these methods can lead to inaccurate or unreliable estimates. Two position estimation methods are developed in this paper, one using a single optical flow sensor and a second using two optical sensors. The first method can accurately estimate position under ideal conditions and also when wheel slip perpendicular to the axis of the wheel occurs. The second method can accurately estimate position even when wheel slip parallel to the axis of the wheel occurs. Location of the sensors is investigated in order to minimize errors caused by inaccurate sensor readings. Finally, a method is implemented and tested using a potential field based navigation scheme. Estimates of position were found to be as accurate as dead-reckoning in ideal conditions and much more accurate in cases where wheel slip occurs.

• 제어로봇시스템학회논문지
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• 제20권1호
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• pp.70-77
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• 2014

This paper proposes a novel localization algorithm based on ego-motion which used Lucas-Kanade Optical Flow and warping image obtained through fish-eye lenses mounted on the robots. The omnidirectional image sensor is a desirable sensor for real-time view-based recognition of a robot because the all information around the robot can be obtained simultaneously. The preprocessing (distortion correction, image merge, etc.) of the omnidirectional image which obtained by camera using reflect in mirror or by connection of multiple camera images is essential because it is difficult to obtain information from the original image. The core of the proposed algorithm may be summarized as follows: First, we capture instantaneous $360^{\circ}$ panoramic images around a robot through fish-eye lenses which are mounted in the bottom direction. Second, we extract motion vectors using Lucas-Kanade Optical Flow in preprocessed image. Third, we estimate the robot position and angle using ego-motion method which used direction of vector and vanishing point obtained by RANSAC. We confirmed the reliability of localization algorithm using ego-motion based on fisheye warping image through comparison between results (position and angle) of the experiment obtained using the proposed algorithm and results of the experiment measured from Global Vision Localization System.

• 한국HCI학회:학술대회논문집
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• 한국HCI학회 2008년도 학술대회 1부
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• pp.517-521
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• 2008

Hand motion classification problem is considered as basis for sign or gesture recognition. We promote optical flow as main feature extracted from images sequences to simultaneously segment the motion's area by its magnitude and characterize the motion' s directions by its orientation. We manage the flow orientation histogram as motion descriptor. A motion is encoded by concatenating the flow orientation histogram from several frames. We utilize simple histogram matching to classify the motion sequences. Attempted experiments show the feasibility of our method for hand motion localization and classification.

• Computers and Concrete
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• 제1권4호
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• pp.433-455
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• 2004

The paper presents results of FE-calculations on shear localizations in quasi-brittle materials during both an uniaxial plane strain compression and uniaxial plane strain extension. An elasto-plastic model with a linear Drucker-Prager type criterion using isotropic hardening and softening and non-associated flow rule was used. A non-local extension was applied in a softening regime to capture realistically shear localization and to obtain a well-posed boundary value problem. A characteristic length was incorporated via a weighting function. Attention was focused on the effect of mesh size, mesh alignment, non-local parameter and imperfections on the thickness and inclination of shear localization. Different methods to calculate plastic strain rates were carefully discussed.

• 대한전자공학회논문지SP
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• 제41권5호
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• pp.23-34
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• 2004

본 논문에서는 사전학습이 필요 없는 능동 특징점 모델(non-prior training active feature model; NPT AFM) 기반에서 광류(optical flow)를 이용한 객체추적 기술을 제안한다. 제안한 알고리듬은 비정형 객체에 대한 분석[1]에 초점을 두고 있으며, 실시간에서 NPT-AFM을 사용한 강건한 추적을 가능하게 한다. NPT-AFM 알고리듬은 관심 객체의 위치를 파악하는 과정 (localization)과 이전 프레임 정보와 현재 프레임 정보를 이용하여, 객체의 위치를 예측(prediction), 보정(correction)하는 과정으로 나눌 수 있다 위치 파악 과정에서는 움직임 분할(motion segmentation)을 수행한 후 개선된 Shi-Tomasi의 특징점 추적 알고리듬[2]을 사용 하였다. 예측 및 보정 과정에서는 광류 정보를 사용하여 특징점을 추적하고[3] 만약, 특징점이 적절히 추적 되지 않거나 추적에 실패하면 특징점들의 시간(temporal), 공간(spatial)적 정보를 이용하여 예측, 보정하게 된다. 객체의 형태 (shape)대신 특징점을 사용하였으며, 객체를 추적하는 과정에서 특징점들은 능동 특징점 모델(active feature model; AFM)을 위한 학습 집합(training sets)의 요소로 갱신된다. 실험결과, 제안한 NPT-AF% 기반 추적 알고리듬은 실시간에서 비정형 객체를 추적하는데 강건함을 보석준다.

• Computers and Concrete
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• 제4권5호
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• pp.377-402
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• 2007

The paper presents quasi-static plane strain FE-simulations of strain localization in reinforced concrete beams without stirrups. The material was modeled with two different isotropic continuum crack models: an elasto-plastic and a damage one. In case of elasto-plasticity, linear Drucker-Prager criterion with a non-associated flow rule was defined in the compressive regime and a Rankine criterion with an associated flow rule was adopted in the tensile regime. In the case of a damage model, the degradation of the material due to micro-cracking was described with a single scalar damage parameter. To ensure the mesh-independence and to capture size effects, both criteria were enhanced in a softening regime by nonlocal terms. Thus, a characteristic length of micro-structure was included. The effect of a characteristic length, reinforcement ratio, bond-slip stiffness, fracture energy and beam size on strain localization was investigated. The numerical results with reinforced concrete beams were quantitatively compared with corresponding laboratory tests by Walraven (1978).