• Smart Structures and Systems
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• v.25 no.2
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• pp.123-133
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• 2020

Compressive sensing (CS) is a newly developed data acquisition and processing technique that takes advantage of the sparse structure in signals. Normally signals in their primitive space or format are reconstructed from their compressed measurements for further treatments, such as modal analysis for vibration data. This approach causes problems such as leakage, loss of fidelity, etc., and the computation of reconstruction itself is costly as well. Therefore, it is appealing to directly work on the compressed data without prior reconstruction of the original data. In this paper, a direct approach for modal analysis of damped systems is proposed by decomposing the compressed measurements with an appropriate dictionary. The damped free vibration function is adopted to form atoms in the dictionary for the following sparse decomposition. Compared with the normally used Fourier bases, the damped free vibration function spans a space with both the frequency and damping as the control variables. In order to efficiently search the enormous two-dimension dictionary with frequency and damping as variables, a two-step strategy is implemented combined with the Orthogonal Matching Pursuit (OMP) to determine the optimal atom in the dictionary, which greatly reduces the computation of the sparse decomposition. The performance of the proposed method is demonstrated by a numerical and an experimental example, and advantages of the method are revealed by comparison with another such kind method using POD technique.

• Korean Journal of Remote Sensing
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• v.29 no.3
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• pp.315-324
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• 2013

Spatial information of snow cover and depth distribution is a key component for snowmelt runoff modeling. Wide snow cover areas can be extracted from NOAA AVHRR or Terra MODIS satellite images. In this study eight sets of annual snow cover data (1997-2006) in two mountainous watersheds (A: Chungju-Dam and B: Soyanggang-Dam) were extracted using NOAA AVHRR images. The distribution of snow depth within the Snow Cover Area (SCA) was generated using snowfall data from ground meteorological observation stations. Snow depletion characteristics for the two watersheds were analyzed snow distribution time series data. The decreased pattern of SCA can be expressed as a logarithmic function; the determination coefficients were 0.62 and 0.68 for the A and B watersheds, respectively. The SCA decreased over 70% within 10 days from the time of maximum SCA.

• Korean Journal of Remote Sensing
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• v.26 no.6
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• pp.629-644
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• 2010

A real-time image georeferencing system requires all inputs to be determined in real-time. The intrinsic camera parameters can be identified in advance from a camera calibration process while other control information can be derived instantaneously from real-time GPS/INS data. The bottleneck process is tie point acquisition since manual operations will be definitely obstacles for real-time system while the existing extraction methods are not fast enough. In this paper, we present a fast-and-automated image matching technique based on the KLT tracker to obtain a set of tie-points in real-time. The proposed work accelerates the KLT tracker by supplying the initial guessed tie-points computed using the GPS/INS data. Originally, the KLT only works effectively when the displacement between tie-points is small. To drive an automated solution, this paper suggests an appropriate number of depth levels for multi-resolution tracking under large displacement using the knowledge of uncertainties the GPS/INS data measurements. The experimental results show that our suggested depth levels is promising and the proposed work can obtain tie-points faster than the ordinary KLT by 13% with no less accuracy. This promising result suggests that our proposed algorithm can be effectively integrated into the real-time image georeferencing for further developing a real-time surveillance application.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.477-477
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• 2000

A multifunctional sensor is designed to measure viscosity, cleanness, temperature and capacitance of engine oil to make a clear decision on its condition. The simple structure helps easy fabrication and low cost while measuring four parameters by one sensor. The operation is described theoretically and is supported by experimental data. A fuzzy based algorithm to fuse the four kinds of data from multi-functional sensor in order to make a decision on the best time to change the oil is proposed.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.5
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• pp.481-486
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• 2007

Wireless Sensor Network(WSNs) consists of small sensor nodes with sensing, computation, and wireless communication capabilities. The large number of sensor nodes in a WSN means that there will often be some nodes which give erroneous sensor data owing to several reasons such as power shortage and transmission error. Generally, these sensor data are gathered by a sink node to monitor and diagnose the current environment. Therefore, this can make it difficult to get an effective monitoring and diagnosis. In this paper, to overcome the aforementioned problems, intelligent sensor data validation method based on PCA(Principle Component Analysis) is utilized. Furthermore, a practical implementation using embedded system is given to show the feasibility of the proposed scheme.

• JSTS:Journal of Semiconductor Technology and Science
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• v.2 no.3
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• pp.197-204
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• 2002

DRAM, SRAM, and FLASH memory are three major memory devices currently used in most electronic applications. But, they have very distinct attributes, therefore, each memory could be used only for limited applications. MRAM (Magneto-resistive Random Access Memory) is a promising candidate for a universal memory that meets all application needs with non-volatile, fast operational speed, and low power consumption. The simplest architecture of MRAM cell is a series of MTJ (Magnetic Tunnel Junction) as a data storage part and MOS transistor as a data selection part. To be a commercially competitive memory device, scalability is an important factor as well. This paper is testing the actual electrical parameters and the scaling factors to limit MRAM technology in the semiconductor based memory device by an actual integration of MRAM core cell. Electrical tuning of MOS/MTJ, and control of resistance are important factors for data sensing, and control of magnetic switching for data writing.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2006.05a
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• pp.328-331
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• 2006

In Ubiquitous age, data collection that using wireless sensor node is increasing necessity. In this paper, collect data because uses PIC16F877 and Bluetooth, and constructs database in PC. The PIC16F877 is control radio sensor node. The PC construct to propose algorithm that updates control data with table. It is changes sensing cycle time of node into intelligence style because compare collected data of DB. Result of study inexpensive , and practical, and I can apply to industry spot constructing system briefly.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.2325-2330
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• 2005

A potential field method for solving the problem of path planning based on global and local information for a mobile robot moving among a set of stationary obstacles is described. The concept of various method used path planning is used design a planning strategy. A real human living area is constructed by many moving and imminence obstacles. Home service mobile robot must avoid many obstacles instantly. A path that safe and attraction towards the goal is chosen. The potential function depends on distance from the goal and heuristic function relies on surrounding environments. Three additional combined methods are proposed to apply to human living area, calibration robots position by measured surrounding environment and adapted home service robots. In this work, we proposed the application of various path planning theory to real area, human living. First, we consider potential field method. Potential field method is attractive method, but that method has great problem called local minimum. So we proposed intermediate point in real area. Intermediate point was set in doorframe and between walls there is connect other room or other area. Intermediate point is very efficiency in computing path. That point is able to smaller area, area divided by intermediate point line. The important idea is intermediate point is permanent point until destruction house or apartment house. Second step is move robot with sensing on front of mobile robot. With sensing, mobile robot recognize obstacle and judge moving obstacle. If mobile robot is reach the intermediate point, robot sensing the surround of point. Mobile robot has data about intermediate point, so mobile robot is able to calibration robots position and direction. Third, we gave uncertainty to robot and obstacles. Because, mobile robot was motion and sensing ability is not enough to control. Robot and obstacle have uncertainty. So, mobile robot planed safe path planning to collision free. Finally, escape local minimum, that has possibility occur robot do not work. Local minimum problem solved by virtual obstacle method. Next is some supposition in real living area.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.05a
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• pp.607-608
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• 2016

Recently using a variety of sensors sensing the virtual(Virtual Sensing) technology that extracts specific data has been applied to IoT service interface. The utilization of such sensors while increasing IoT (Internet of Things) environmental sensor is an essential element. However, used in the IoT to the environment, while the increase in utilization of a specific sensor utilization falling sensors is generated. In this paper, we design unnecessary sensors removal algorithm as a way to solve this problem. Through the utilization of poor power to block the sensor can reduce the power consumption and user sensor control service through the monitoring by blocking the use of the sensor is considered that there can be provided a more effective and convenient.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.3
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• pp.207-214
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• 2010

This paper proposes about decentralized control approach based Leader-Follower formation control using LOS (Line of Sight) algorithm and unknown input observer. The position of robots which is a basic information in multi-robot or single robot motion control is determined by localization algorithm fusing UPS (Ultrasonic Position System) and kinematics model. For formation control, a decentralized control approach individually installing a local controller in leader and follower robot is adopted. Leader robot is controlled to track a specified trajectory by LOS algorithm, and the other robots follow the leader by local controller based on tracking platoon level function, self-sensing data and estimated information from unknown input observer. The performance of proposed method is proven through the formation experiment of two vehicle models.