• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2013.06a
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• pp.180-181
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• 2013

해상에서 사고 선박을 신속하게 예인하는 것은 현장에서 일어날 수 있는 2차적인 피해를 사전에 예방할 수 있는 중요한 조치이다. 이를 위해서는 예인선을 이용하여 사고선박을 이동시켜야 하고 예인선과 피 예인 선박은 예인삭에 의해 연결되게 된다. 자력운항이 불가능한 상태에서 피 예인 선박은 예인선의 예인력에 의해 거동이 좌우되고 예인력은 해상환경 및 피예인 선박의 저항력을 고려하여 결정되어야 한다. 본 연구에서는 피 예인 선박 예인 시 예인저항과 이로 인해 예인삭에 걸리는 장력해석법에 대해 검토한다. 본 연구를 통해 얻어진 결과는 사고선박 예인지원시스템에 효율적으로 활용 가능할 것이다.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2023.05a
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• pp.15-16
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• 2023

해상교통관제 구역은 항만 시설을 사용하기 위한 입·출항 선박, 연안 해역을 이동하는 선박 등이 서로 복잡하게 운항하는 교통 패턴을 가지고 있다. 이를 안전하고 효과적으로 관리하기 위해 해상교통관제센터(VTS)에서는 선박을 실시간 모니터링하며 관제 업무를 수행하고 있지만, 교통 혼잡 상황에서는 업무 로드의 증가로 인해 관제 공백이 발생하기도 한다. 이에 교통 혼잡도 및 혼잡 구역을 예측한다면보다 효율적인 관제가 가능하지만 현재는 관제사의 경험에 전적으로 의존하고 있는 실정이다. 본 논문에서는 VTS 관점에서의 교통 혼잡을 정의하고, 과거 항적 데이터를 이용하여 항내 선박 교통 혼잡도 및 혼잡 구역을 예측하는 방법을 제안하였다. 또한, 실해역 데이터(대산항 VTS)를 적용하여 제안된 기술이 관제지원 도구로서 활용될 수 있는지 검토하였다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.4
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• pp.804-810
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• 2017

Distress accidents occur annually by and failure of sea rescue and time delay lead to fatal accident. In the event of maritime distress, most of the equipments used for search and rescue are in responsible for the position of ships. An MOB equipment is a representative equipment for lifesaving and uses AIS communication method. However, the MOB equipment has problems of interference with existing vessel traffic process and it is difficult to apply because there is no proper certification standard. Therefore, this paper proposes a maritime search and rescue supporting system using smartphone. Utilizing the widely constructed IT infrastructure, it collects position information of the fishing boat and leisure ship using GPS embedded in the smartphone. Also the developed system supports to participate in the rescue by sending the information about the occurrence of the survivor in a certain area to the ship operator.

• Journal of Navigation and Port Research
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• v.46 no.6
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• pp.562-569
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• 2022

The alarm monitoring technology applied to existing operating ships manages data items such as temperature and pressure with AMS (Alarm Monitoring System) and provides an alarm to the crew should these sensing data exceed the normal level range. In addition, the maintenance of existing ships follows the Planned Maintenance System (PMS). whereby the sensing data measured from the equipment is monitored and if it surpasses the set range, maintenance is performed through an alarm, or the corresponding part is replaced in advance after being used for a certain period of time regardless of whether the target device has a malfunction or not. To secure the reliability and operational safety of ship engine operation, it is necessary to enable advanced diagnosis and prediction based on real-time condition monitoring data. To do so, comprehensive measurement of actual ship data, creation of a database, and implementation of a condition diagnosis monitoring system for condition-based predictive maintenance of auxiliary equipment and piping must take place. Furthermore, the system should enable management of auxiliary equipment and piping status information based on a responsive web, and be optimized for screen and resolution so that it can be accessed and used by various mobile devices such as smartphones as well as for viewing on a PC on board. This update cost is low, and the management method is easy. In this paper, we propose CBM (Condition Based Management) technology, for autonomous ships. This core technology is used to identify abnormal phenomena through state diagnosis and monitoring of pumps and purifiers among ship auxiliary equipment, and seawater and steam pipes among pipes. It is intended to provide performance diagnosis and failure prediction of ship auxiliary equipment and piping for convergence analysis, and to support preventive maintenance decision-making.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2010.10a
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• pp.180-181
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• 2010

An estimation algorithm of collision risk among multiple ships has been developed in order to reduce human error and prevent collision accidents. The algorithm is designed to calculate the collision risk among ships based on Fuzzy theory by using AIS data as traffic information. In this paper, to validate the algorithm, the AIS data of actual collision accident, which occurred between a product carrier and a cargo carrier in Busan harbor in 2009 are collected. The replay simulation is carried out on the actual AIS data and the collision risk is calculated in real time. In this paper, the features of the estimation algorithm of collision risk and the results of replay simulation based on AIS data of actual collision accident are discussed.

• Journal of the Korean Society of Marine Environment & Safety
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• v.24 no.1
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• pp.1-9
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• 2018

All ships should ensure stability in accordance with IMO regulations. However, GM is only used to determine ship stability because it takes a lot of time to validate all regulations. This is a problem given that the safety of vessels cannot be guaranteed, potentially leading to accidents. There is a need for a more intuitive and comprehensive method of confirming the stability of ships. This study developed a stability index that expresses ship stability in one value. An index equation is defined based on the 6 stability criteria for ships prescribed by IMO and the result of calculating the ship stability of a model ship. A stability index has been derived for each loading condition by applying the index equation to the same ship. It can clearly be seen that this stability index appropriately explains the criteria. In other words, it is possible to assess ship stability with one value and confirm whether the ship stability satisfies IMO regulations. This index will help masters and officers more easily and accurately check ship stability.

• Journal of Navigation and Port Research
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• v.34 no.10
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• pp.727-733
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• 2010

An estimation algorithm of collision risk among multiple ships has been developed in order to reduce human error and prevent collision accidents. The algorithm is designed to calculate the collision risk among ships based on Fuzzy theory by using AIS data as traffic information. In this paper, to validate the algorithm, the AIS data of actual collision accident, which occurred between a product carrier and a cargo carrier in Busan harbor in 2009 are collected. The replay simulation is carried out on the actual AIS data and the collision risk is calculated in real time. In this paper, the features of the estimation algorithm of collision risk and the results of replay simulation based on AIS data of actual collision accident are discussed.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.10a
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• pp.274-276
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• 2017

Korean e-Navigation is a system that introduced to reduce maritime accidents. In order to reduce marine accidents, Korean e-Navigation provides the following services-"Vulnerable Vessel Monitoring", "Vulnerable Vessel support & monitoring", "Optimal safety route", "ENC Streaming for Small Vessel", "Tug & Barge Support", "Maritime Safety Information Providing". Each Service is a system separated into finctional units and integrated into Korean e-Navigation. Korean e-Navigation is introducing data middleware to integrate each service and the DDS(Data Distribution Service) is judged to be effective. Thus, this paper analyzed the characteristics of DDS middleware types suitable for each service of e-Navigation.

• Journal of the Korean Society of Marine Environment & Safety
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• v.27 no.1
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• pp.53-59
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• 2021

The marine transport industry generally applies new technologies later than other transport industries, such as airways and railways. Vessels require efficient operation, and their performance and lifespan depend on the level of maintenance and management. Many studies have shown that corrective maintenance (CM) and time-based maintenance (TBM) have restrictions with respect to enabling efficient maintenance of workload and cost to improve operational efficiency. Predictive maintenance (PdM) is an advanced technology that allows monitoring the condition and performance of a target machine to predict its time of failure and helps maintain the key machinery in optimal working conditions at all times. This study presents the development of a marine predictive maintenance (MPdM; maritime predictive maintenance) method based on applying PdM to the marine environment. The MPdM scheme is designed by considering the special environment of the marine transport industry and the extreme marine conditions. Further, results of the study elaborates upon the concept of MPdM and its necessity to advancing marine transportation in the future.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.8
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• pp.1831-1838
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• 2015

In this paper, a method of implementing a communication network in ship, which exploits a powerline-based legacy-line communication system (LLC), is presented. We develop an inductive coupling unit and a multi-interface device to connect a data communication terminal to the powerline. As a result of operation tests for the ship under working, the implemented LLC shows a transmission rate of at least 25.8 Mbps in the distance of 200 m away with 100% success rate. Thus, the system can be a useful alternative to implement a communication network in ship without additional channels. Being easy to be implemented and supporting various interfaces for data communication, the presented system will be very effective when a real-time monitoring system is launched in future digital ship.