• Journal of Navigation and Port Research
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• v.46 no.1
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• pp.1-10
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• 2022

This study aims to investigate changes in the demand for ship officers in response to changes in the shipping industry environment in which Maritime Autonomous Surface Ships (MASS) emerge according to the application of the fourth industrial revolution technology to ships, and it looks into changes in the skill of ship officer. It also analyzes and proposes a plan for nurturing ship officers accordingly. As a result of the degree of recognition and AHP analysis, this study suggests that a new training system is required because the current training and education system may cover the job competencies of emergency response, caution and danger navigation, general sailing, cargo handling, seaworthiness maintenance, emergency response, and ship maintenance and management, but tasks such as remote control, monitoring diagnosis, device management capability, and big data analysis require competency for unmanned and shore-based control. By evaluating the importance of change factors in the duties of ship officers in Maritime Autonomous Surface Ships, this study provides information on ship officer educational institutions' response strategies for nurturing ship officers and prioritization of resource allocation, etc. The importance of these factors was compared and evaluated to suggest changes in the duties of ship officers and methods of nurturing ship officers according to the introduction of Maritime Autonomous Surface Ships. It is expected that the findings of this study will be meaningful as it systematically derives the duties and competency factors of ship officers of Maritime Autonomous Surface Ships from a practical point of view and analyzed the perception level of each relevant expert to diagnose expert-level responses to the introduction of Maritime Autonomous Surface Ships.

• Smart Structures and Systems
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• v.16 no.4
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• pp.593-606
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• 2015

This paper presents a novel concept of healing some of the damages in wind turbine blades (WTBs) such as cracks and delamination. This is achieved through an inherent functioning autonomous repairing system. Such wind turbine blades have the benefit of reduced maintenance cost and increased operational period. Previous techniques of developing autonomous healing systems uses hollow glass fibres (HGFs) to deliver repairing fluids to damaged sites. HGFs have been reported with some limitations like, failure to fracture, which undermines their further usage. The self-healing technique described in this paper represents an advancement in the engineering of the delivery mechanism of a self-healing system. It is analogous to the HGF system but without the HGFs, which are replaced by multiple hollow channels created within the composite, inherently in the FRP matrix at fabrication. An in-house fabricated NACA 4412 WTB incorporating this array of network hollow channels was damaged in flexure and then autonomously repaired using the vascular channels. The blade was re-tested under flexure to ascertain the efficiency of the recovered mechanical properties.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 1999.05a
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• pp.340-347
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• 1999

Recently, the progress of industrialization has been taken concern of material handling automation. So far, the conveyor belt has been popular for material handling. However, this system has many disadvantages such as the space, cost, In this paper, a new navigation algorithm using fuzzy is introduced. The mobile robot follows a line installed on the roads. These informations are inputted with three approximate sensors. These obtained informations are analyzed with fuzzy technique for autonomous steering. Therefore, unlike existing systems, high reliability is guaranteed under bad environment conditions. The installation and maintenance of a line is easily made at lower cost. The use of the mobile robot can be extended to materials handing purposes in manufacturing, hospital, inter-of fire documents deliveries.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2003.06a
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• pp.438-442
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• 2003

For an efficient sliding mode control system stability and chattering avoidance should be guaranteed. A continuation method using boundary layer is well known as one solution for this. However since not only model uncertainties and disturbances but also control task itself is variable. it is practically impossible to set controller parameters - control discontinuity, control bandwidth, boundary layer thickness - in advance. In this paper first an adaptation law of control discontinuity is introduced to assure system stability and then fuzzy logic based tuning algorithm of design parameters is applied based on monitored performance indices of tracking error, control chattering, and model precision. In the end maximum control bandwidth not exciting unmodeled dynamics and minimum control discontinuity, boundary layer thickness making system stable and free of chattering are found respectively. This eliminates control chattering and enhances control accuracy as much as possible under given control situation. In order to demonstrate the validity of the proposed algorithm safe headway maintenance control for autonomous transportation system is simulated. The control results show that the proposed algorithm guarantees system stability all the time and tunes control parameters consistently and in consequence implements an efficient control in terms of both accuracy and actuator chattering.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.9
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• pp.883-895
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• 2007

In this work, we present the development of a patrol robot which is intended to navigate outdoor rough terrain. Proposed mechanism consists of six legs for overcoming an obstacle, and six wheels for traveling. Also, in order to absorb vibration in rough terrain effectively, the slide-spring system and tubed type tire are adopted to each leg and each wheel. The control system of robot consists of several imbedded boards for management of lots of diverse devices such as sensors designed for rough terrain, motor controllers, camera, micro controller and so on. And the base system of the robot is designed to operate in real time and to surveille in the vicinity of the robot, and the robot system is controlled by wireless LAN connected to GUI-based remote control system, while CAN communication connects the control board and the device controllers for sensors and motor controllers. For operating this robot system efficiently, we propose the control algorithms for autonomous navigation using GPS, stabilization maintenance by posture control, obstacle-avoidance by impedance control, and obstacle-overcoming with interference-avoidance between wheels. The performance of the robot and the proposed algorithms are tested and proved by a set of experiments in outdoor rough terrain.

• The Journal of Korea Robotics Society
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• v.11 no.2
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• pp.60-72
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• 2016

This study proposes a multi-robot system, using multiple autonomous robots, to explore concrete structures and assist in their maintenance by sealing any cracks present in the structure. The proposed system employed a new self-localization method that is essential for autonomous robots, along with a visualization system to recognize the external environment and to detect and explore cracks efficiently. Moreover, more efficient crack search in an unknown environment became possible by arranging the robots into search areas divided depending on the surrounding situations. Operations with increased efficiency were also realized by overcoming the disadvantages of the infeasible logical behavioral model design with only six basic behavioral strategies based on distributed control-one of the methods to control swarm robots. Finally, this study investigated the efficiency of the proposed multi-robot system via basic sensor testing and simulation.

• Smart Structures and Systems
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• v.29 no.1
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• pp.207-220
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• 2022

Structural health monitoring (SHM) plays a vital role in the maintenance and operation of constructions. In recent years, autonomous inspection has received considerable attention because conventional monitoring methods are inefficient and expensive to some extent. To develop autonomous inspection, a potential approach of crack identification is needed to locate defects. Therefore, this study exploits two deep learning-based segmentation models, DeepLabv3+ and Mask R-CNN, for crack segmentation because these two segmentation models can outperform other similar models on public datasets. Additionally, impacts of label quality on model performance are explored to obtain an empirical guideline on the preparation of image datasets. The influence of image cropping and label refining are also investigated, and different strategies are applied to the dataset, resulting in six alternated datasets. By conducting experiments with these datasets, the highest mean Intersection-over-Union (mIoU), 75%, is achieved by Mask R-CNN. The rise in the percentage of annotations by image cropping improves model performance while the label refining has opposite effects on the two models. As the label refining results in fewer error annotations of cracks, this modification enhances the performance of DeepLabv3+. Instead, the performance of Mask R-CNN decreases because fragmented annotations may mistake an instance as multiple instances. To sum up, both DeepLabv3+ and Mask R-CNN are capable of crack identification, and an empirical guideline on the data preparation is presented to strengthen identification successfulness via image cropping and label refining.

• International Journal of Internet, Broadcasting and Communication
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• v.14 no.1
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• pp.194-200
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• 2022

As of 2020, the cumulative number of electric vehicles worldwide increased 43% from 2019, exceeding 10 million. We surveyed and analyzed important factors when purchasing electric vehicles for consumers who own electric vehicles. Through this, we tried to find an effective way to supply electric vehicles in the future. The purpose of this study is to present customized marketing proposals for companies by empirically analyzing the factors affecting consumers' electric vehicle purchases and deriving market demands for electric vehicles. We identified the market status of electric vehicles through literature research and reviewed previous studies on the factors affecting the purchase intention of electric vehicles. Through empirical studies, differences in electric vehicle purchase factors according to gender, age, and the degree of importance of performance were analyzed. To this end, the SPSS statistics package was used. Factors influencing the purchase of electric vehicles were set to mileage, charging time, new technology, degree of driving autonomous development, design, price, infrastructure for charging, the phase of maintenance and repair, by the government and local governments. In addition, the most important factors were derived, and the average difference analysis was conducted according to gender, age, and performance importance.

• Journal of the Society of Naval Architects of Korea
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• v.60 no.6
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• pp.482-490
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• 2023

With the advent of the Fourth Industrial Revolution, many companies are developing Smart Ships to enable autonomous navigation, unmanned operation, and cost-effective shipping. In order to facilitate the operation of these Smart Ships, significant emphasis is being placed on improving external communication capabilities and developing autonomous navigation systems. Moreover, unmanned ship operation necessitates replacing of all visually observed conditions with sensors, leading to an inevitable increase in the number of sensors and actuators compared to traditional methods. However, in South Korea, the communication network for sensors and actuators primarily relies on the conventional 1:1 hardwired wiring, with the use of higher-level communication networks when necessary. Therefore, in this paper, we introduce the AS-Interface protocol, which is used for monitoring and controlling sensors and actuators, with the expectation that it will greatly contribute to the development of future Smart Ships by reducing production time, costs, and maintenance duration.

• Journal of the Korea institute for structural maintenance and inspection
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• v.28 no.3
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• pp.66-73
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• 2024

Stay-cable is one of the most important load carrying members in cable-stayed bridges. Monitoring structural integrity of stay-cables is crucial for evaluating the structural condition of the cable-stayed bridge. For stay-cables, tension and damping ratio are estimated based on modal properties as a measure of structural integrity. Since the monitoring system continuously measures the vibration for the long-term period, data acquisition systems should be stable and power-efficiency as the hardware system. In addition, massive signals from the data acquisition systems are continuously generated, so that automated analysis system should be indispensable. In order to fulfill these purpose simultaneously, this study presents an autonomous cable monitoring system based on domain-knowledge using IoT for continuous cable monitoring systems of cable-stayed bridges. An IoT system was developed to provide effective and power-efficient data acquisition and on-board processing capability for Edge-computing. Automated peak-picking algorithm using domain knowledge was embedded to the IoT system in order to analyze massive data from continuous monitoring automatically and reliably. To evaluate its operational performance in real fields, the developed autonomous monitoring system has been installed on a cable-stayed bridge in Korea. The operational performance are confirmed and validated by comparing with the existing system in terms of data transmission rates, accuracy and efficiency of tension estimation.