• Proceedings of the KIEE Conference
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• 2000.07c
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• pp.1966-1968
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• 2000

Globally, oil-filled paper-insulated cables and cross-linked polyethylene-insulated cables have been mainly applied for a underground power transmission line. The oil-filled cable has the hydraulic system in which insulating oil, expanded and contracted by temperature changes, is absorbed and supplied. This system enable us to detect oil leakages from the cable. But it has some problems such as difficulty in detecting minor leakages and a relatively long period of fault detecting. And so, this paper introduce a new leakage detection system, improved from the current one.

• Proceedings of the KIEE Conference
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• 2003.11a
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• pp.361-363
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• 2003

To reduce the effect of fault on underground power cable, we need exact and fast fault location detection technique. In this thesis, we describe on filter design technique that can be applied to on-line fault defection technique. To design fitter for fault location defection on Power cable, we should analysis fault signal. So we designed test bed for fault generation and measured fault signals for analysis. Through the analysis of signals, we found that ANC filter can be applied to separate fault signals and we designed a ANC filter. We tested on the designed filter through computer simulation, and we describe its results in this paper.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2011.04a
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• pp.128-129
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• 2011

• Tunnel and Underground Space
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• v.30 no.1
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• pp.76-86
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• 2020

In this study, a small autonomous driving robot was developed for underground mines using the Light Detection and Ranging (LiDAR) sensor. The developed robot measures the distances to the left and right wall surfaces using the LiDAR sensor, and automatically controls its steering to drive along the centerline of mine tunnel. A field experiment was conducted in an underground amethyst mine to test the driving performance of developed robot. During five repeated driving tests, the robot showed stable driving performance overall. There were no collision accidents with the wall of mine tunnel.

• The Journal of Engineering Geology
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• v.5 no.2
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• pp.181-192
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• 1995

The discrimination studies between earthquakes and underground nuclear explosions have been carried out by various seismologists(Nuttli and Kim, 1976; Dahiman and Israelson, 1977; Masse, 1981). The discrimination between local microearthquakes and artificial underground explosions(epicentral distance not greater than 400Km), however, has not been actively studied so far in the light of seismological aspects. Futhermore this kind of research has never been performed in Korea even if it is of great importance for IAEA (International Atomic Energy Agency) to clearly analyze the military nuclear power of North Korea at present. This research has been carried out by using some of the artificial underground explosions(about 100 events) have occurred in North Korea for the last six years. The azimuths, apparent incidence angles, epicentral distances and locations are determined using a single station of 3 - component data. The detection, location and identification are performed through the polarization and the bandpass filtering. This technique can be also applied to study the inhomogeneous crustal structure finding the converted waves.

• Journal of Korean Tunnelling and Underground Space Association
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• v.20 no.6
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• pp.1161-1175
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• 2018

An unexpected event could be easily followed by a large secondary accident due to the limitation in sight of drivers in road tunnels. Therefore, a series of automated incident detection systems have been under operation, which, however, appear in very low detection rates due to very low image qualities on CCTVs in tunnels. In order to overcome that limit, deep learning based tunnel incident detection system was developed, which already showed high detection rates in November of 2017. However, since the object detection process could deal with only still images, moving direction and speed of moving vehicles could not be identified. Furthermore it was hard to detect stopping and reverse the status of moving vehicles. Therefore, apart from the object detection, an object tracking method has been introduced and combined with the detection algorithm to track the moving vehicles. Also, stopping-reverse discrimination algorithm was proposed, thereby implementing into the combined incident detection processes. Each performance on detection of stopping, reverse driving and fire incident state were evaluated with showing 100% detection rate. But the detection for 'person' object appears relatively low success rate to 78.5%. Nevertheless, it is believed that the enlarged richness of image big-data could dramatically enhance the detection capacity of the automatic incident detection system.

• Journal of the Society of Disaster Information
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• v.19 no.3
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• pp.665-672
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• 2023

Purpose: Underground utility tunnel is facility that is jointly house infrastructure such as electricity, water and gas in city, causing condensation problems due to lack of airflow. This paper aims to prevent electricity leakage fires caused by condensation by detecting whether the control panel door in the underground utility tunnel is open using a deep learning model. Method: YOLO, a deep learning object recognition model, is trained to recognize the opening and closing of the control panel door using video data taken by a robot patrolling the underground utility tunnel. To improve the recognition rate, image augmentation is used. Result: Among the image enhancement techniques, we compared the performance of the YOLO model trained using mosaic with that of the YOLO model without mosaic, and found that the mosaic technique performed better. The mAP for all classes were 0.994, which is high evaluation result. Conclusion: It was able to detect the control panel even when there were lights off or other objects in the underground cavity. This allows you to effectively manage the underground utility tunnel and prevent disasters.

• Journal of the Korea Institute of Military Science and Technology
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• v.15 no.1
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• pp.9-15
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• 2012

This paper shows an effective scanning trajectory for a mine detection device that is one of the mission equipments of unmanned ground vehicle. The mine detection device is composed of a mine-detection sensor, and a 4 DOF manipulator enabling sensor position control. There are three modes that manage the mine detection device: passive, semi-automatic, and automatic. The automatic mode is used the most. This paper suggests a scanning method that makes shape of 8. This method prevents missing target area and enhances scanning speed when the mine detection device scans the ground surface in automatic mode. The suggested method is verified by simulations and experiments.

• Proceedings of the KIEE Conference
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• 2001.05a
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• pp.226-229
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• 2001

The combined transmission lines with the underground power cables are continuously expanded in power systems. So the fault of combined transmission line is increased every year as the complication of underground transmission line. In this paper. traveling wave theory and DWT wavelet transform are used for fast and accurate detection of fault location at the combined transmission line. Traveling wave travels to each bus like surge and repeats reflection and transmission till transient signal is completely disappeared. When fault is occurred on overhead and underground tine, the fault location detecting algorithm was performed with using continuous peak value time-delay of traveling wave reflected from A bus.

• Journal of Korean Tunnelling and Underground Space Association
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• v.19 no.5
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• pp.813-827
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• 2017

Surveillance cameras installed in tunnels capture the various video frames effected by dynamic and variable factors. In addition, localizing and managing the cameras in tunnel is not affordable, and quality of capturing frame is effected by time. In this paper, we introduce a new method to detect and track the vehicles in tunnel by using surveillance cameras installed in a tunnel. It is difficult to detect the video frames directly from surveillance cameras due to the motion blur effect and blurring effect on lens by dirt. In order to overcome this difficulties, two new methods such as Differential Frame/Non-Maxima Suppression (DFNMS) and Haar Cascade Detector to track cars are proposed and investigated for their feasibilities. In the study, it was shown that high precision and recall values could be achieved by the two methods, which then be capable of providing practical data and key information to an automatic accident detection system in tunnels.