• Journal of information and communication convergence engineering
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• v.22 no.3
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• pp.221-230
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• 2024

The aim of this study is to investigate the automatic recognition and analysis of Jeju marine-life images using artificial intelligence (AI) technology. The dataset of marine-life images was prepared using tools such as Python, TensorFlow, and Google Colab (Google Colaboratory). We also developed models by training deep learning AI in image recognition to automatically recognize the species found in these images and extract their associated information, such as taxonomy, characteristics, and distribution. This study is innovative in that it uses deep learning technology combined with imagerecognition technology for marine biodiversity research. In addition, these results will lead to the development of the marine-life industry in Jeju by supporting marine environment monitoring and marine resource conservation. Furthermore, this study is anticipated to contribute to academic advancement, specifically in the study of marine species diversity.

• Journal of Sensor Science and Technology
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• v.21 no.1
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• pp.46-52
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• 2012

The rapid water pollution in stream, river, lake and sea in recent years raises an urgent need for continuous monitoring and policymaking to conserve the global clean environment. In particular, the increasing water pollution in coastal marine areas adds to the importance of the environmental monitoring systems. In this paper, the mobile server is designed to gathers information of the water quality at coastal areas. The obtained data by the server is transmitted from field servers to the base station via multi-hop communication in wireless sensor network. The information collected includes dissolved oxygen(DO), hydrogen ion exponent(pH), temperature, etc. By the information provided the real-time monitoring of water quality at the coastal marine area. In addition, wireless sensor network-based flooding routing protocol was designed and used to transfer the measured water quality information efficiently. Telosb sensor node is programmed using nesC language in TinyOS platform for small scale wireless sensor network monitoring from a remote server.

• Journal of the Korean Society of Visualization
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• v.20 no.2
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• pp.86-92
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• 2022

Pipe failure due to thermal fatigue and environmental regulations are increasing the importance of pipe monitoring systems in industrial plants. Since most pipe monitoring systems are focus on external crack inspected, it is necessary to temperature and concentration measuring monitoring system inside the pipe. These systems have spatial uncertainty due to sample inspection by one-point measurement. In addition, real-time measurement is not possible due to the limitation of time delay due to contact measurement. In this study, CT-TDLAS (Computed tomography-Tunable diode laser absorption spectroscopy) apply to overcome the limitations of existing methods. Lasers exhibiting an absorption response at a wavelength of 1395 nm were arranged in a lattice pattern on measuring cell. It showed that the inside of the pipe changed to an unstable combustion state over time.

• Nuclear Engineering and Technology
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• v.55 no.6
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• pp.2158-2165
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• 2023

Marine radioactivity monitoring is critical for taking immediate action in case of unexpected nuclear accidents at nuclear facilities located near coastal areas. Especially when the level of contamination is not predictable, mobile monitoring systems will be useful for wide-area ocean radiation survey and for determination of the level of radioactivity. Here, we used a silicon photomultiplier and a high-efficiency GAGG crystal to fabricate a compact, battery-powered gamma spectroscopy that can be used in an ocean environment. The developed spectroscopy has compact dimensions of 6.5 × 6.5× 8 cm³ and weighs 560 g. We used LoRa, a low-power wireless protocol for communication. Successful data transmission was achieved within 1.4 m water depth. The developed gamma spectroscopy was able to detect radioactivity from a ¹³⁷Cs point source (3.7 kBq) at a distance of 20 cm in water. Moreover, we demonstrated an unmanned radioactivity monitoring system in a real sea by combining unmanned surface vehicle with the developed gamma spectroscopy. A hidden ¹³⁷Cs source (3.07 MBq) was detected by the unmanned system at a distance of 3 m. After successfully testing the developed mobile spectroscopy in an ocean environment, we believe that our proposed system will be an effective solution for mobile real-time marine radioactivity monitoring.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.8
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• pp.619-626
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• 2016

This paper proposes the design and performance evaluation of a marine engine fault detection system using a proximity sensor for marine engine. Non-linearity is greatly reduced by using the sensor without increasing the response time by applying the CANopen protocol. The CANopen protocol enables the sensor to send initial values and measurement data. The marine engine fault detection system measures crankshaft deflection and the bottom dead center of the crosshead in real-time, which maintains stability and prevents the serious breakdown of the marine engine by use of an interlocking alarm monitoring system.

• Journal of Advanced Marine Engineering and Technology
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• v.38 no.10
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• pp.1275-1280
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• 2014

In this study, the performance of a real-time micro telescopic monitoring system is evaluated, in which an artificial neural network is adopted for the diagnoses of vibratory bodies, such as solid piping system or machinery. The structural vibration was measured by a non-contact remote sensing method, in which images of a high-speed high-definition camera were used. The structural vibration data that can be obtained by the PIV (particle image velocimetry) technique were used for training the neural network. The structures of the neural network are dynamically changed and their performances are evaluated for the constructed diagnosis system. Optimized structures of the neural network are proposed for real-time diagnosis for the piping system. It was experimentally verified that the performances of the neural network used for real-time monitoring are influenced by the types of the vibration data, such as minimum, maximum and average values of the vibration data. It concludes that the time-mean values are most appropriate for monitoring the piping system.

• Journal of Advanced Marine Engineering and Technology
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• v.28 no.8
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• pp.1291-1298
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• 2004

In development of monitoring and control systems, one of the most important points is to consider a redundancy so that the system can be operated normally although hardware faults are partly occurred. The purpose of this paper is to introduce a monitoring and control system with a redundancy function for I/O servers and communication networks. I/O servers composed with an active server and a standby server. Each server also has 3 communication ports, 2 ports of them were connected to field units and the other 1 port was connected to the other server. Field units have to be constructed to 2 communication ports connected I/O servers through communication lines. Also, server communication module was implemented for analyzing and handling fault elements. and was submodularized for linking easily with a monitoring and control module. An experiment with 2 servers and 2 field units was constructed to demonstrate its effectiveness.

• Journal of Korea Multimedia Society
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• v.19 no.2
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• pp.405-410
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• 2016

Elevator industry is a field that is mechanical, electrical and electronic technology and constantly requires inspection and maintenance considering various applications and various types. Recently, various elevator control and monitoring technologies with IT are developing for elevators on land. But technologies with IT have been hardly done in marine elevator that is consistently assured safety and reliability of life cycle for its parts in poor environment. In this paper, we implemented embedded main controller, floor controller and car controller that meet the requirements and use NMEA network protocol by analyzing home and abroad integrated elevator operation and management systems. Especially, we secured reliability of maintenance by real-time fault diagnosis and control that was implemented with limit switch, gyro sensor, temperature/humidity/barometric pressure sensor and fire detection sensor thinking over the environmental conditions of terrestrial and marine elevator.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.60 no.3
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• pp.277-289
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• 2024

Climate change has led to a significant increase in jellyfish populations globally, causing various problems. For power plants that use nearby seawater for cooling, the intrusion of jellyfish into intake systems can block the flow, leading to reduced output or even shutdowns. This issue is compounded by other small marine organisms like shrimp and salps, making it urgent to develop solutions to prevent their intrusion. This study addressed the problem using the BioSonics DT-X 120 kHz scientific fish finder to conduct preliminary tank experiments. We also deployed underwater acoustic and camera buoys around the intake of nuclear power plant, utilizing a bidirectional communication system between sea and land to collect data. Data collection took place from July 31, 2023 to August 1, 2023. While harmful organisms such as jellyfish and salps were not detected, we successfully gathered acoustic data on small fish measuring backscattering strength (SV). Analysis showed that fish schools were more prominent in the evening than during the day. The highest fish distribution was observed at 3:30 AM on July 31 with an SV of -44.8 dB while the lowest was at 12:30 PM on the same day with an SV of -63.4 dB. Additionally, a solar-powered system was used to enable real-time data acquisition from sea buoys with smooth communication between the land server and the offshore buoy located 1.8 km away. This research developed an acoustic-based monitoring system for detecting harmful organisms around the intake and provided foundational data for preventing marine organism intrusion and planning effective measures.

• Journal of Advanced Marine Engineering and Technology
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• v.35 no.2
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• pp.288-294
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• 2011

In this paper, the FPGA-based SoC board (Xilinx Virtex-4 ML401 EVM) is adopted to control electrical power inverter system. For marine application, its performance is shown on PC-based system for monitoring electrical characteristics of a power inverter using by the NMEA 2000 protocol. This power inverter system is achieved in Real-Time monitoring and control by dual micro-processor operation on embedded FPGA-based SoC board. One micro processor is for control (Control processor) electrical power inverter using by PWM signal. And the other microprocessor (Communication processor) is for communication with PC-based monitoring system. The two-processor is communicating each other using by dual-port ram (DPRAM). PC-based system user can control and monitor information of the electrical power inverter via NMEA 2000 based communication processor. Control and monitoring information includes the inverter status and configuration. SoC board converts this information to Parameter Group Numbers (PGNs) in the NMEA 2000 protocol. This system can be applied to marine power electronics for distributed power generation, transmission or regulation systems on the ship.