• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.4
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• pp.571-576
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• 2022

Due to the epochal development of the unmanned technology, the importance of LDT(: Location Detection Technology), which accurately estimates the location of a user or object, is dramatically increased. TOA(: Time of Arrival), which calculates a location by measuring the arrival time of signals, and TDOA(: Time Difference of Arrival) which calculates it by measuring the difference between two arrival times, are representative LDT methods. Based on the signals received from three or more base stations, TOA calculates an intersection point by drawing circles and TDOA calculates it by drawing hyperbolas. In order to improve the radio shadow area problem, a huge number of repeaters have been installed in the urban area, but the signals received through these repeaters may cause the serious error for estimating a location. In this paper, we propose an efficient location estimation technique using the signal received through the repeater. The proposed approach estimates the location of MS(: Mobile Station) employing TOA and TDOA methods, based on signals received from one repeater and two BS(: Base Station)s.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.12
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• pp.1122-1129
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• 2015

This paper suggests a method of detecting traffic lights for vehicles by combining the HSV(hue saturation value) color model, morphometric characteristics, and location information appearing on consecutive images in daytime. In order to detect the traffic light, the color corresponding to the signal lights should be explored. It is difficult to detect traffic lights among colors of lights from buildings, taillight of cars, leaves, placards, etc. The proposed algorithm searches for the traffic lights from many candidates using morphometric characteristics and location information in consecutive images. The recognition process is divided into three steps. The first step is to detect candidates after converting RGB channel into HSV color model. The second step is to extract the boundaries between the housing of traffic lights and background by exploiting the assumption that the housing has lower brightness than the surrounding background. The last step is to recognize the signal light after eliminating the false candidates using morphometric characteristics and location information appearing on consecutive images. This paper demonstrates successful detection results of traffic lights from various images captured on the city roads.

• Nuclear Engineering and Technology
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• v.51 no.1
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• pp.155-162
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• 2019

To reduce the secondary damage caused by leakage accidents in plant piping systems, a constant surveillance system is necessary. To ensure leaks are promptly addressed, the surveillance system should be able to detect not only the leak itself, but also the location of the leak. Recently, research to develop new methods has been conducted using cameras to detect leakage and to estimate the location of leakage. However, existing methods solely estimate whether a leak exists or not, or only provide two-dimensional coordinates of the leakage location. In this paper, a method using multiple cameras to detect leakage and estimate the three-dimensional coordinates of the leakage location is presented. Leakage is detected by each camera using MADI(Moving Average Differential Image) and histogram analysis. The two-dimensional leakage location is estimated using the detected leakage area. The three-dimensional leakage location is subsequently estimated based on the two-dimensional leakage location. To achieve this, the coordinates (x, z) for the leakage are calculated for a horizontal section (XZ plane) in the monitoring area. Then, the y-coordinate of leakage is calculated using a vertical section from each camera. The method proposed in this paper could accurately estimate the three-dimensional location of a leak using multiple cameras.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1995.10a
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• pp.87-94
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• 1995

In highway bridges robust damage detection exercises are mandatory to secure the safety of the structures from hostile environmental conditions such as fatigue earthquake, wind, and corrosion. This paper presents a damage detection practice in a full-scale highway bridge by utilizing modal response parameters of as-built and damaged states of the structure. first the test structure is described and modal testing procedures are outlined. Next, a damage detection model which yields information on the location of damage directly from changes in mode shapes is outlined. Finally, the damage detection model is implemented to predict the location of damage in the ten structure. From the results, it was found that the damage detection model accurately locates damage in the test structures for which modal parameters of only a single mode are available for pre-damage (as-built) and post-damage stages.

• Proceedings of the KIEE Conference
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• 2003.11c
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• pp.802-805
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• 2003

The aim of this paper is to provide a guide to those methods of train detection which are available, or are likely to become available, to the designer of train control or other relevant systems. In broad terms, train detection may be defined as the process of generating information which describes the location and movement of trains. Train detection information is difficult to define in isolation. Consider, for example, the train detection information required in a modern train control system. This may vary considerably : in a future high performance train control system, it might be necessary to know the precise position, direction of movement, speed, and possibly even the acceleration or braking, of all trains in the control area : in a less demanding application, it might be sufficient to know only the location of trains in terms of the occupation of sections of track.

• Transactions on Electrical and Electronic Materials
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• v.14 no.4
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• pp.187-192
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• 2013

Because of the importance of small target detection in infrared images, many studies have been carried out in this area. Using a Kalman filter and mean shift algorithm, this study proposes an algorithm to track multiple small moving targets even in cases of target disappearance and appearance in serial infrared images in an environment with many noises. Difference images, which highlight the background images estimated with a background estimation filter from the original images, have a relatively very bright value, which becomes a candidate target area. Multiple target tracking consists of a Kalman filter section (target position prediction) and candidate target classification section (target selection). The system removes error detection from the detection results of candidate targets in still images and associates targets in serial images. The final target detection locations were revised with the mean shift algorithm to have comparatively low tracking location errors and allow for continuous tracking with standard model updating. In the experiment with actual marine infrared serial images, the proposed system was compared with the Kalman filter method and mean shift algorithm. As a result, the proposed system recorded the lowest tracking location errors and ensured stable tracking with no tracking location diffusion.

• Structural Engineering and Mechanics
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• v.26 no.3
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• pp.315-341
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• 2007

A sudden change of stiffness in a structure, associated with the events such as weld fracture and brace breakage, will cause a discontinuity in acceleration response time histories recorded in the vicinity of damage location at damage time instant. A new damage index is proposed and implemented in this paper to detect the damage time instant, location, and severity of a structure due to a sudden change of structural stiffness. The proposed damage index is suitable for online structural health monitoring applications. It can also be used in conjunction with the empirical mode decomposition (EMD) for damage detection without using the intermittency check. Numerical simulation using a five-story shear building under different types of excitation is executed to assess the effectiveness and reliability of the proposed damage index and damage detection approach for the building at different damage levels. The sensitivity of the damage index to the intensity and frequency range of measurement noise is also examined. The results from this study demonstrate that the damage index and damage detection approach proposed can accurately identify the damage time instant and location in the building due to a sudden loss of stiffness if measurement noise is below a certain level. The relation between the damage severity and the proposed damage index is linear. The wavelet-transform (WT) and the EMD with intermittency check are also applied to the same building for the comparison of detection efficiency between the proposed approach, the WT and the EMD.

• The Journal of Korea Robotics Society
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• v.14 no.3
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• pp.170-178
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• 2019

This paper proposes a parking space detection method for autonomous parking by using the Around View Monitor (AVM) image and Light Detection and Ranging (LIDAR) sensor fusion. This method consists of removing obstacles except for the parking line, detecting the parking line, and template matching method to detect the parking space location information in the parking lot. In order to remove the obstacles, we correct and converge LIDAR information considering the distortion phenomenon in AVM image. Based on the assumption that the obstacles are removed, the line filter that reflects the thickness of the parking line and the improved radon transformation are applied to detect the parking line clearly. The parking space location information is detected by applying template matching with the modified parking space template and the detected parking lines are used to return location information of parking space. Finally, we propose a novel parking space detection system that returns relative distance and relative angle from the current vehicle to the parking space.

• Journal of the Korean Institute of Gas
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• v.20 no.5
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• pp.40-49
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• 2016

When a leak occurs in the buried pipelines, The leak locations are able to detected by using the vibration sensors. These leak detection system, intended for incompressible fluid, such as water, are of using the wave propagation velocity and a signal arrival time delay between the sensors. In this paper, to develop a leak location detection system for a compressible fluid such as gas, the conventional detection methods have been studied, improved, and verified through the experiment using the compressed air. It confirmed that it is possible to detect the leak location for compressible fluid in the buried pipelines and to be applicable to the development of a leak location detection system in buried pipelines for gas.

• Journal of the Korea institute for structural maintenance and inspection
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• v.17 no.1
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• pp.124-132
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• 2013

Damage location and extent could be detected by the inverse analysis on dynamic response of the damaged structure. In general, detection of damage location is possible by the observation of the mode shape difference between undamaged and damaged structure and assessment of stiffness reduction is possible by the observation of the natural frequency difference of them. The study on damage detection by the dynamic response in civil structures is reported enough and in practical use, but in building structures it is reported seldom due to several problems. The purpose of this study is to present the damage detection method on shear building structures by mode shape. The damage location index using 1st mode shape is observed theoretically to find out damage location. The damage detection method is applied to numerical analysis model such as MATLAB and MIDAS GENw for the verification. Finally the shaking table test on 3 story shear building is performed for the examination of the damage detection method. In shaking table results, as the story stiffness decrease by 25% the 1st mode frequency increase by 12%, and the damage location index represents minus at damaged story.