• 한국지구물리탐사학회:학술대회논문집
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• 2007.06a
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• pp.215-218
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• 2007

Tunnel detection is known to be one of the challenging problems in geophysical society. Among various geophysical methods, we tried to examine the applicability of electrical resistivity tomography (ERT) method to detect empty tunnel. In this study, we analyzed the ERT data acquired at the test site for tunnel detection. The inversion results have shown reasonable image of the tunnel although the resolution is quite poor. Moreover, we could obtain the three-dimensional attitude of tunnel through 3-D ERT imaging. Therefore, we expect that ERT can make contribution to the tunnel detection problem and further research effort such as fusion of geophysical methods will provide more reliable tunnel detection capability.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.9
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• pp.1082-1087
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• 2019

Video Incident Detection System is a detection system for the purpose of detection of an emergency in an unexpected situation such as a pedestrian in a tunnel, a falling object, a stationary vehicle, a reverse run, and a fire(smoke and flame). In recent years, the importance of the city center has been emphasized by the construction of underpasses in great depth underground space. Therefore, in order to apply Video Incident Detection System to a Double Deck Tunnel, it was developed to reflect the design characteristics of the Double Deck Tunnel. and In this paper especially, the fire detection technology, which is not it is difficult to apply to the Double Deck Tunnel environment because it is not supported on existing Video Incident Detection System or has a fail detect, we propose fire detection using color image analysis, silhouette spread, and statistical properties, It is verified through a real fire test in a double deck tunnel test bed environment.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2003.05a
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• pp.749-754
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• 2003

In this paper, we introduce the measurement of the underwater noise with 32channel hydrophone array of Samsung CAvitation Tunnel (SCAT) and the detection technique of noise sources by using the beam-forming method. Measurement and way signal Processing under fluid flow are essential works for the underwater acoustics, especially for the detection of noise sources. As the acoustic impedance of the water is relatively high and the tunnel is an enclosed system, we have to consider the interaction between tunnel and water together with the reflection of noise in the beam-forming technique. Also, for a hydrophone array system that is fixed on one side of tunnel wall as done in SCAT is liable to suffer from some limitations in the detection of the noise sources with the array, we discuss these limitations particularly on the frequency range and spacing of noise sources.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.12
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• pp.6089-6097
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• 2012

This study suggested a method of detecting an incident inside tunnel by using camera that is installed within the tunnel. As for the proposed incident detection method, a static object, travel except vehicles, smoke, and contra-flow were detected by extracting the moving object through using the real-time background image differencing after receiving image from the camera, which is installed inside the tunnel. To detect the moving object within the tunnel, the positive background image was created by using the moving information of the object. The incident detection method was developed, which is strong in a change of lighting that occurs within the tunnel, and in influence of the external lighting that occurs in the entrance and exit of the tunnel. To examine the efficiency of the suggested method, the experimental images were acquired from Marae tunnel and Expo tunnel in Yeosu of Jeonnam and from Unam tunnel in Imsil of Jeonbuk. Number of images, which were used in experiment, included 20 cases for static object, 20 cases for travel except vehicles, 4 cases for smoke, and 10 cases for contra-flow. As for the detection rate, all of the static object, the travel except vehicles, and the contra-flow were detected in the experimental image. In case of smoke, 3 cases were detected. Thus, excellent performance could be confirmed. The proposed method is now under operation in Marae tunnel and Expo tunnel in Yeosu of Jeonnam and in Unam tunnel in Imsil of Jeonbuk. To examine accurate efficiency, the evaluation of performance is considered to be likely to be needed after acquiring the incident videos, which actually occur within tunnel.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.9 no.1
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• pp.9-18
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• 2010

Our country has so large mountain area that the tunnel construction is inevitable and the need of incident detection that provides safe management of tunnels is increasing. In this paper, we suggest a tunnel incident detection system using computer vision techniques, which can detect the incidents in a tunnel and provides the information to the tunnel administrative office in order to help safe tunnel operation. The suggested system enhances the processing speed by using simple processing algorithm such as image subtraction, and ensures the accuracy of the system by focused on the incident detection itself rather than its classification. The system is also cost effective because the video data from 4 cameras can be simultaneously analyzed in a single PC-based system. Our system can be easily extended because the PC-based analyzer can be increased according to the number of cameras in a tunnel. Also our web-based structure is useful to connect the other remotely located tunnel incident systems to obtain interoperability between tunnels. Through the experiments the system has successfully detected the incidents in real time including dropped luggage, stoped car, traffic congestion, man walker or bicycle, smoke or fire, reverse driving, etc.

• 한국정보통신설비학회:학술대회논문집
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• 2007.08a
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• pp.176-180
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• 2007

In this study, we deployed the cable tunnel inspection and monitoring system by wireless sensor network. It is shown that the wireless sensor network which is composed of sensor, wireless communication module, and gateway can be applied to cable tunnel monitoring system. Sensors considered herein are flame detection sensor, flood detection sensor, intruder detection sensor, and temperature sensor, etc. It is also found that the wireless sensor network can deliver sensing data reliably by wireless sensing technology. The gateway system that can transmit sensed data to server by CDMA is developed. Monitoring system is constructed by web service technology, and it is observed that this system can monitor the present state of tunnel without difficulties. The system provides an alternative to inspect and monitor the tunnel efficiently where the conventional wired system is infeasible.

• 한국방재학회:학술대회논문집
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• 2008.02a
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• pp.549-552
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• 2008

In this study, we deployed the cable tunnel inspection and monitoring system by wireless sensor network. It is shown that the wireless sensor network which is composed of sensor, wireless communication module, and gateway can be applied to cable tunnel monitoring system. Sensors considered herein are flame detection sensor, flood detection sensor, intruder detection sensor, and temperature sensor, etc. It is also found that the wireless sensor network can deliver sensing data reliably by wireless sensing technology. The gateway system that can transmit sensed data to server by CDMA is developed. Monitoring system is constructed by web service technology, and it is observed that this system can monitor the present state of tunnel without difficulties. The system provides an alternative to inspecting and monitoring the tunnel efficiently where the conventional wired system is infeasible.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.9
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• pp.3797-3822
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• 2020

The inspection of cracks on the surface of tunnel linings is a common method of evaluate the condition of the tunnel. In particular, determining the thickness and shape of a crack is important because it indicates the external forces applied to the tunnel and the current condition of the concrete structure. Recently, several automatic crack detection methods have been proposed to identify cracks using captured tunnel lining images. These methods apply an image-segmentation mechanism with well-annotated datasets. However, generating the ground truths requires many resources, and the small proportion of cracks in the images cause a class-imbalance problem. A weakly annotated dataset is generated to reduce resource consumption and avoid the class-imbalance problem. However, the use of the dataset results in a large number of false positives and requires post-processing for accurate crack detection. To overcome these issues, we propose a crack detection method using a ternary classifier. The proposed method significantly reduces the false positive rate, and the performance (as measured by the F1 score) is improved by 0.33 compared to previous methods. These results demonstrate the effectiveness of the proposed method.

• Structural Monitoring and Maintenance
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• v.5 no.2
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• pp.231-242
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• 2018

Subway tunnel structure has been rapidly developed in many cities for its strong transport capacity. The model-based damage detection of subway tunnel structure is usually difficult due to the complex modeling of soil-structure interaction, the indetermination of boundary and so on. This paper proposes a new data-based method for the damage detection of subway tunnel structure. The root mean square acceleration and cross correlation function are used to derive a statistical pattern recognition algorithm for damage detection. A damage sensitive feature is proposed based on the root mean square deviations of the cross correlation functions. X-bar control charts are utilized to monitor the variation of the damage sensitive features before and after damage. The proposed algorithm is validated by the experiment of a full-scale two-rings subway tunnel lining, and damages are simulated by loosening the connection bolts of the rings. The results verify that root mean square deviation is sensitive to bolt loosening in the tunnel lining and X-bar control charts are feasible to be used in damage detection. The proposed data-based damage detection method is applicable to the online structural health monitoring system of subway tunnel lining.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.7
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• pp.1325-1334
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• 2016

The video incident detection System is a probe for rapid detecting the walker, falling, stopped, backwards, smoke situation in tunnel. Recently, the importance is increases from the downtown double deck tunnel in great depth underground space[1], but the legal basis is weak and the vulnerable situation experimental data. So, In this paper, we introduce a long-term log data analysis information in the tunnenl video incident detection system installed and experimental results in order to verify the feasibility of apply to video incident detection system for the double deck tunnel. It is proposed a few things about derives the problem of existing video incident detection system, improvements and reflect attributes for double deck tunnel. The contents described in this paper will contribute to refine the prototype of video incident detection system will apply to future double deck multi-layer tunnels.