• Journal of the Optical Society of Korea
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• v.15 no.2
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• pp.174-181
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• 2011

An airborne sensor is developed for remote sensing on an aerial vehicle (UV). The sensor is an optical payload for an eletro-optical/infrared (EO/IR) dual band camera that combines visible and IR imaging capabilities in a compact and lightweight package. It adopts a Ritchey-Chr$\'{e}$tien telescope for the common front end optics with several relay optics that divide and deliver EO and IR bands to a charge-coupled-device (CCD) and an IR detector, respectively. The EO/IR camera for dual bands is mounted on a two-axis gimbal that provides stabilized imaging and precision pointing in both the along and cross-track directions. We first investigate the mechanical deformations, displacements and stress of the EO/IR camera through finite element analysis (FEA) for five cases: three gravitational effects and two thermal conditions. For investigating gravitational effects, one gravitational acceleration (1 g) is given along each of the +x, +y and +z directions. The two thermal conditions are the overall temperature change to $30^{\circ}C$ from $20^{\circ}C$ and the temperature gradient across the primary mirror pupil from $-5^{\circ}C$ to $+5^{\circ}C$. Optical performance, represented by the modulation transfer function (MTF), is then predicted by integrating the FEA results into optics design/analysis software. This analysis shows the IR channel can sustain imaging performance as good as designed, i.e., MTF 38% at 13 line-pairs-per-mm (lpm), with refocus capability. Similarly, the EO channel can keep the designed performance (MTF 73% at 27.3 lpm) except in the case of the overall temperature change, in which the EO channel experiences slight performance degradation (MTF 16% drop) for $20^{\circ}C$ overall temperate change.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.05a
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• pp.487-489
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• 2016

In this paper, quad copter provides a method for preventing the possibility of accident in the air during a formation flight. The existing studies had a few studies upon the falls because quad copter formation flight was generally implemented indoors. Therefore, in this paper, we provide a self-diagnosis system to prevent a secondary accident for mismatching the Proportional-Integral-Derivative(PID) and detecting an abnormal communication modules each others in formation flying system. Scheme to be proposed, a system is that when one of the node meets a problem, the header node is sending the information of the current state to the server in the first and making a diagnosis itself in order to avoid the problems caused by dropping from the air. Therefore, if the difference between PID value of header node and slave node is greater than specified values or if it detects a defective sensors and communication modules, the proposed system is set to provide for moving toward a safe place. As a result, we expect that this proposed system is possible to minimize additional incidents by self adjusting the height through a self-diagnosis discovering flawed the acceleration sensor, gyro sensor and various attached sensors.

• Smart Structures and Systems
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• v.20 no.5
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• pp.549-562
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• 2017

The US railroad network carries 40% of the nation's total freight. Railroad bridges are the most critical part of the network infrastructure and, therefore, must be properly maintained for the operational safety. Railroad managers inspect bridges by measuring displacements under train crossing events to assess their structural condition and prioritize bridge management and safety decisions accordingly. The displacement of a railroad bridge under train crossings is one parameter of interest to railroad bridge owners, as it quantifies a bridge's ability to perform safely and addresses its serviceability. Railroad bridges with poor track conditions will have amplified displacements under heavy loads due to impacts between the wheels and rail joints. Under these circumstances, vehicle-track-bridge interactions could cause excessive bridge displacements, and hence, unsafe train crossings. If displacements during train crossings could be measured objectively, owners could repair or replace less safe bridges first. However, data on bridge displacements is difficult to collect in the field as a fixed point of reference is required for measurement. Accelerations can be used to estimate dynamic displacements, but to date, the pseudo-static displacements cannot be measured using reference-free sensors. This study proposes a method to estimate total transverse displacements of a railroad bridge under live train loads using acceleration and tilt data at the top of the exterior pile bent of a standard timber trestle, where train derailment due to excessive lateral movement is the main concern. Researchers used real bridge transverse displacement data under train traffic from varying bridge serviceability levels. This study explores the design of a new bridge deck-pier experimental model that simulates the vibrations of railroad bridges under traffic using a shake table for the input of train crossing data collected from the field into a laboratory model of a standard timber railroad pile bent. Reference-free sensors measured both the inclination angle and accelerations of the pile cap. Various readings are used to estimate the total displacements of the bridge using data filtering. The estimated displacements are then compared to the true responses of the model measured with displacement sensors. An average peak error of 10% and a root mean square error average of 5% resulted, concluding that this method can cost-effectively measure the total displacement of railroad bridges without a fixed reference.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.5C
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• pp.355-364
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• 2012

Target processing mechanisms are necessary to collect target information, real-time data fusion, and tactical environment recognition for cooperative engagement ability. Among these mechanisms, the target tracking starts from predicting state of speed, acceleration, and location by using sensors' measurements. However, it can be a problem to give the reliability because the measurements have a certain uncertainty. Thus, a technique which uses multiple sensors is needed to detect the target and increase the reliability. Also, data fusion technique is necessary to process the data which is provided from heterogeneous sensors for target tracking. In this paper, a target tracking algorithm is proposed based on probabilistic data association(PDA) by fusing radar and ESM sensor measurements. The radar sensor's azimuth and range measurements and the ESM sensor's bearing-only measurement are associated by the measurement fusion method. After gating associated measurements, state estimation of the target is performed by PDA filter. The simulation results show that the proposed algorithm provides improved estimation under linear and circular target motions.

• Journal of the Korean Institute of Gas
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• v.3 no.2 s.7
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• pp.17-23
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• 1999

The wire and/or wireless data communication system for anti-disaster system of natural gas governor station was developed. In oder to prevent accidents of governor station, the operator was replaced by RTU(Remote Terminal Unit) which gather and transmit safety situation of governor station. The database and MMI(Man Machine Interface) were also developed to analyze the situation of governor station. The data communication between server and RTU was designed to switch automatically from wire to wireless communication and vice versa when one of them failed communication. We also have developed the patrol car management system which was applied GPS(Global Position System)/GIS(Geometric Information System), and the earthquake detection/transmission system which was adopted three dimension acceleration sensor. When a earthquake may occur, the earthquake detection/transmission system monitors data such as PGA(Peak Ground Acceleration), Sl(Spectrum Intensity) and orders the emergency shutoff valve close immediately.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.5
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• pp.1564-1572
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• 2010

In this study, the falls detection and direction classification system was implemented using 3-axial acceleration signal. The acceleration signals were acquired from the 3-axial accelerometer(MMA7260Q, Freescale, USA), and then transmitted to the computer through USB interface. The implemented system can detect falls using the newly proposed algorithm, and also classify the direction of falls using fuzzy classifier. The 6 subjects was selected for experiment and the accelerometer was attached on each subject's chest. Each subject walked in normal pace for 5 seconds, and then the fall down according to the four direction(front_fall, back_fall, left_fall and right_fall) during at least 2 second. The falls was easily detect using the newly proposed algorithm in this study. The acquired signals were analyzed after 1 second from generating falls. The fuzzy classifier was used to classify the direction of falls. The mean value of the falls detection rate was 94.79%. The classifier rate according to falls direction were 95.83% in case of front falls, 100% incase of back falls, 87.5% in case of left falls, and 95.83% in case of right falls.

• Design & Manufacturing
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• v.14 no.3
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• pp.8-16
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• 2020

In this study, the vibration signal of the mold was measured and analyzed to monitoring the process time and characteristics during injection molding. A 5 inch light guide plate mold was used to injection molding and the vibration signal was measured by MPU6050 acceleration sensor module attached the surface of fixed mold base. Conditions except for injection speed and packing pressure were set to the same value and the change of the vibration signal of the mold according to injection speed and packing pressure was analyzed. As a result, the vibration signal had a large change at three points: "Injection start", "V/P switchover", and "Packing end". The time difference between "injection start" and "V/P switchover" means the injection time in the injection molding process, and the time difference between "V/P switchover" and "Packing end" means the packing time. When the injection time and packing time obtained from the vibration signal of the mold are compared with the time recorded in the injection molding machine, the error of the injection time was 2.19±0.69% and the error of the packing time was 1.39±0.83%, which was the same level as the actual value. Additionally, the amplitude at the time of "injection start" increased as the injection speed increased. In "V/P switchover", the amplitude tended to be proportional to the pressure difference between the maximum injection pressure and the packing pressure and the amplitude at the "packing end" tended to the pressure difference between the packing pressure and the back pressure. Therefore, based on the result of this study, the injection time and packing time of each cycle can be monitored by measuring the vibration signal of the mold. Also, it was confirmed that the level and trend of process variables such as the injection speed, maximum injection pressure, and packing pressure can be evaluated as the change of the mold vibration during injection molding.

• Journal of the Korea institute for structural maintenance and inspection
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• v.23 no.7
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• pp.87-94
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• 2019

Recently, the advance of accurate dynamic displacement measurement devices, such as GPS, computer vision, and optic laser sensor, has enhanced the structural monitoring technology. In this study, the dynamic displacement data was used to verify the applicability of the structural physical parameter estimation method through subspace system identification. The subspace system identification theory for estimating state-space model from measured data and physics-based interpretation for deriving the physical parameter of the estimated system are presented. Three-degree-freedom steel structures were fabricated for the experimental verification of the theory in this study. Laser displacement sensor and accelerometer were used to measure the displacement data of each floor and the acceleration data of the shaking table. Discrete state-space model generated from measured data was verified for precision. The discrete state-space model generated from the measured data extracted the floor stiffness of the building after accuracy verification. In addition, based on the story stiffness extracted from the state space model, five column stiffening and damage samples were set up to extract the change rate of story stiffness for each sample. As a result, in case of reinforcement and damage under the same condition, the stiffness change showed a high matching rate.

• Journal of rehabilitation welfare engineering & assistive technology
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• v.11 no.3
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• pp.271-277
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• 2017

The purpose of this study was to develop a balance chair for improving pelvic correction and postural balance through postural balance training using tactile feedback by a vibration motor provided in real time according to the user's attitude. We built a body frame using mono cast(MC) Nylon, Touch thin film transistor(TFT) for user interface, a main control module using Arduino, a 9-axis acceleration sensor for user's posture determination, and a vibration module for tactile feedback. The prototype of the Balance Chair which surrounds the outside was made with cushion for sitting conformability. In order to verify the effectiveness of the postural balance training system using the built prototype, the muscle activity (% MVIC) of the left and right iliocostalis lumborum those are the main muscles of the spinal movement was measured with ten female subjects. And the balance ability before and after training was measured using Spine Balance 3D, a posture balance ability evaluation device. The muscular activities of the left and right iliocostalis lumborum showed the balance activation according to vibration feedback during exercise protocol and postural balance improved after balance exercise training using balance chair. This study could be apply to use the fundamental research for developing the various postural balance product.

• Journal of Internet Computing and Services
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• v.13 no.4
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• pp.23-31
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• 2012

Nowadays, recognizing human activities is an important subject; it is exploited widely and applied to many fields in real-life, especially in health care and context aware application. Research achievements are mainly focused on activities of daily living which are useful for suggesting advises to health care applications. Falling event is one of the biggest risks to the health and well-being of the elderly especially in independent living because falling accidents may be caused from heart attack. Recognizing this activity still remains in difficult research area. Many systems equipped wearable sensors have been proposed but they are not useful if users forget to wear the clothes or lack ability to adapt themselves to mobile systems without specific wearable sensors. In this paper, we develop a novel method based on analyzing the change of acceleration, orientation when the fall occurs and measure their similarity to featured fall patterns. In this study, we recruit five volunteers in our experiment including various fall categories. The results are effective for recognizing fall activity. Our system is implemented on G1 smart phone which are already plugged accelerometer and orientation sensors. The popular phone is used to get data from accelerometer and results showthe feasibility of our method and significant contribution to fall detection.