• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2011년도 추계학술대회 논문집
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• pp.418-429
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• 2011

Researches using time reversal acoustics (TRA) for impact localization have been paid attention to recently. Dispersion characteristics of Lamb waves, which restrict the utility of classical nondestructive evaluation based on time-of-flight information, can be compensated through the application of TRA to Lamb waves on a plate. This study investigates the spatial focusing performance of time reversal Lamb waves on a plate using finite element analysis. In particular, the virtual sensor effect caused by multiple wave reflections at the boundaries of the plate is shown to enable the spatial focusing of Lamb waves though a very small number of surface-bonded piezoelectric (PZT) sensors are available. The time window size of forward response signals, are normalized with respect to the number of virtual active sensors. Then their effects on the spatial focusing performance of Lamb waves are investigated.

• 한국정밀공학회지
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• 제9권4호
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• pp.22-35
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• 1992

In highly automated machining centers, intelligent sensor fddeback systems are indispensable on order to monitor their operations, to ensure efficient metal removal, and to initate remedial action in the event of accident. In this study, an on-line tool wear detection system for thrning operations is developed, and experimentally evaluated. The system employs multiple sensors and the signals from these sensors are processed using a multichannel autoegressive (AR) series model. The resulting output from the signal processing block is then fed to a previously tranied artificial neural network (multiayered perceptron) to make a final decision on the state of the cutting tool. To learn the necessary input/output mapping for tool wear detection, the weithts and thresholds of the network are adjusted according to the back propagation (BP) method during off-line training. The results of experimental evaluation show that the system works well over a wide range of cutting conditions, and the ability of the system to detect tool wear is improved due to the generalization, fault-tolearant and self-ofganizing properties of the neural network.

• 센서학회지
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• 제21권3호
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• pp.211-216
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• 2012

Fires are the most common disaster and early fire detection is of great importance to minimize the consequent damage. Simple sensors including smoke detectors are widely used for the purpose but they are able to sense fires only at close proximity. Recently, due to the rapid advances of relevant technologies, vision-based fire sensing has attracted growing attention. In this paper, a novel visual sensing technique to automatically detect fire is presented. The proposed technique consists of multiple steps of image processing: pixel-level, block-level, and frame level. At the first step, fire flame pixel candidates are selected based on their color values in YIQ space from the image of a camera which is installed as a vision sensor at a fire scene. At the second step, the dynamic parts of flames are extracted by comparing two consecutive images. These parts are then represented in regularly divided image blocks to reduce pixel-level detection error and simplify following processing. Finally, the temporal change of the detected blocks is analyzed to confirm the spread of fire. The proposed technique was tested using real fire images and it worked quite reliably.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제9권8호
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• pp.2948-2963
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• 2015

In the field of computer vision, visual surveillance systems have recently become an important research topic. Growth in this area is being driven by both the increase in the availability of inexpensive computing devices and image sensors as well as the general inefficiency of manual surveillance and monitoring. In particular, the ultimate goal for many visual surveillance systems is to provide automatic activity recognition for events at a given site. A higher level of understanding of these activities requires certain lower-level computer vision tasks to be performed. So in this paper, we propose an intelligent activity recognition model that uses a structure learning method and a classification method. The structure learning method is provided as a K2-learning algorithm that generates Bayesian networks of causal relationships between sensors for a given activity. The statistical characteristics of the sensor values and the topological characteristics of the generated graphs are learned for each activity, and then a neural network is designed to classify the current activity according to the features extracted from the multiple sensor values that have been collected. Finally, the proposed method is implemented and tested by using PETS2013 benchmark data.

• 대한전기학회논문지:시스템및제어부문D
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• 제54권3호
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• pp.156-165
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• 2005

Human being recognizes the physical world by integrating a great variety of sensory inputs, the information acquired by their own action, and their knowledge of the world using hierarchically parallel-distributed mechanism. In this paper, authors propose the sensor fusion system that can recognize multiple 3D objects from 2D projection images and tactile informations. The proposed system focuses on improving recognition performance of 3D objects. Unlike the conventional object recognition system that uses image sensor alone, the proposed method uses tactual sensors in addition to visual sensor. Neural network is used to fuse the two sensory signals. Tactual signals are obtained from the reaction force of the pressure sensors at the fingertips when unknown objects are grasped by four-fingered robot hand. The experiment evaluates the recognition rate and the number of learning iterations of various objects. The merits of the proposed systems are not only the high performance of the learning ability but also the reliability of the system with tactual information for recognizing various objects even though the visual sensory signals get defects. The experimental results show that the proposed system can improve recognition rate and reduce teeming time. These results verify the effectiveness of the proposed sensor fusion system as recognition scheme for 3D objects.

• Transactions on Electrical and Electronic Materials
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• 제6권6호
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• pp.262-271
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• 2005

In order to achieve timely and accurate fault detection of plasma etching process, neural network based time series modeling has been applied to reactive ion etching (RIE) using two different in-situ plasma-monitoring sensors called optical emission spectroscopy (OES) and residual gas analyzer (RGA). Four different subsystems of RIE (such as RF power, chamber pressure, and two gas flows) were considered as potential sources of fault, and multiple degrees of faults were tested. OES and RGA data were simultaneously collected while the etching of benzocyclobutene (BCB) in a $SF_6/O_2$ plasma was taking place. To simulate established TSNNs as incipient fault detectors, each TSNN was trained to learn the parameters at t, t+T, ... , and t+4T. This prediction scheme could effectively compensate run-time-delay (RTD) caused by data preprocessing and computation. Satisfying results are presented in this paper, and it turned out that OES is more sensitive to RF power and RGA is to chamber pressure and gas flows. Therefore, the combination of these two sensors is recommended for better fault detection, and they show a potential to the applications of not only incipient fault detection but also incipient real-time diagnosis.

• 스마트미디어저널
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• 제1권4호
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• pp.18-26
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• 2012

스마트폰 어플리케이션 수의 증가는 새로운 유저인터페이스에 대한 중요성을 증대시켰으며, 다양한 센서를 융합한 유저인터페이스 개발 연구의 관심을 유도하고 있다. 본 논문에서는 스마트폰에 있는 가속도 센서, 자계 센서, 자이로 센서 정보를 융합하여 사용자 모션 제스처를 인식할 수 있는 새로운 유저인터페이스를 제안한다. 제안 방법은 유합 센서 정보로부터 스마트폰의 3차원 방위 정보를 구하고, HMM(Hidden Markov Model)을 이용하여 손동작 제스처를 인식한다. 특히 제안된 스마트폰의 3차원 방위 좌표계를 구면 좌표계로 변환하는 양자화 방법은 기본 축 회전에 더욱 민감한 인식이 이루어지도록 하였다. 실험을 통하여 제안한 방법이 93%로의 인식률을 보였다.

• 제어로봇시스템학회논문지
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• 제17권4호
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• pp.353-361
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• 2011

A precise embedded ultrasonic localization system is developed for autonomous mobile robots in indoor environments, which is essential for autonomous navigation of mobile robots with various tasks. Although ultrasonic sensors are more cost-effective than other sensors such as LRF (Laser Range Finder) and vision, they suffer inaccuracy and directional ambiguity. First, we apply the matched filter to measure the distance precisely. For resolving the computational complexity of the matched filter for embedded systems, we propose a new matched filter algorithm with fast computation in three points of view. Second, we propose an accurate ultrasonic localization system which consists of three ultrasonic receivers on the mobile robot and two or more transmitters on the ceiling. Last, we add an extended Kalman filter to estimate position and orientation. Various simulations and experimental results show the effectiveness of the proposed system.

• 한국항해항만학회:학술대회논문집
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• 한국항해항만학회 2014년도 추계학술대회
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• pp.219-221
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• 2014

The objective of this paper is to simulate the dynamic behavior of a floating structure model, using image processing and close-range photogrammetry, instead of the contact sensors. Previously, the movement of structure was presented through the exterior orientation estimation of a single camera by space resection. The inverse resection yields the 6 orientation parameters of the floating structure, with respect to the camera coordinate system. The single camera solution is of interest in applications characterized by restriction in term of costs, unfavorable observation conditions, or synchronization demands when using multiple cameras. This article discusses the theoretical determinations of camera exterior orientation based on Direct Linear Transformation and photogrammetric resection using least squares adjustment. The proposed method was used to monitor the motion of a floating model. The results of six degrees of freedom (6-DOF) by inverse resection show that the appropriate initial values by DLT can be effectually applied in least squares adjustment, to obtain the precision of exterior orientation parameters. Additionally, a comparison between the close-range photogrammetry and total station results was feasibly verified. Therefore, the proposed method can be considered as an efficient solution to simulating the movement of floating structure.

• Journal of Power Electronics
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• 제9권4호
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• pp.631-642
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• 2009

The sun is a useful reference direction because of its brightness relative to other astronomical objects and its relatively small apparent radius as viewed by spacecrafts near the Earth. Most satellites use solar power as a source of energy, and so need to make sure that solar panels are oriented correctly with respect to the sun. Also, some satellites have sensitive instruments that must not be exposed to direct sunlight. For all these reasons, sun sensors are important components in spacecraft attitude determination and control systems. To minimize components and structural mass, some components have multiple purposes. The solar cells will provide power and also be used as coarse sun sensors. A coarse Sun sensor is a low-cost attitude determination sensor suitable for a wide range of space missions. The sensor measures the sun angle in two orthogonal axes. The Sun sensor measures the sun angle in both azimuth and elevation. This paper presents the development of a model to determine the attitude of a small cube-shaped satellite in space relative to the sun's direction. This sensor helps small cube-shaped Pico satellites to perform accurate attitude determination without requiring additional hardware.