• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.2
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• pp.311-317
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• 2014

Buoy has different motion characteristics depends on the sea weather situations. The motion characteristics has an impact on antenna, solar power generation system and etc. installed within a buoy. Therefore, it is important to analyse motion characteristics for management and analyse the buoy conditions. This paper's Buoy motion monitoring system uses gyro sensor to detect motions of a light buoy, and the measured data transfers to the PC on the shore using signal processing algorithm. The aim of this research is to develop monitoring and management mechanism of a buoy by applying motion monitoring system. In this paper, the operation characteristic of movement monitoring system is verified through experiment. Further, in this paper, it can apply such as real-time visibility into the status of the buoy or many ocean facility's motion estimation of the future.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.12
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• pp.2976-2983
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• 2013

Interest in reducing standby power is increasing because of electric power shortages. Most of electric equipment are in standby state that does not use a function of the original, most electronic devices consume a lot of electric power even in standby mode. In many countries, research on the smart plug is advanced in order to prevent power consumption due to standby state. However, due to the nature of the function, expensive in many case. These smart plugs would be to cut the standby power using motion detecting sensor or pattern control of the user. Theses features have no advantages because of malfunction of motion detecting sensor and in accordance with the diversification ot user's pattern. In this study, developing a multi-smart plug system that linked with bluetooth function of user's smart phone. Using smart phone bluetooth function, determination of the position of the user. The suggestion smart plug cutting the standby power of the electronic apparatus. It was confirmed that it is able to reduce the power consumption according to the location of the user.

• Journal of Ocean Engineering and Technology
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• v.31 no.1
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• pp.69-79
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• 2017

This paper presents the operations of a multi-beam echo sounder (MBES) installed on the deep-sea remotely operated vehicle (ROV) Hemire. Hemire explored hydrothermal vents in the Forecast volcano located near the Mariana Trench in March of in 2006. During these explorations, we acquired profiling points on the routes of the vehicle using the MBES. Information on the position, depth, and attitude of the ROV are essential to obtain higher accuracy for the profiling quality. However, the MBES installed on Hemire does not have its own position and depth sensors. Although it has attitude sensors for roll, pitch, and heading, the specifications of these sensors were not clear. Therefore, we had to merge the high-performance sensor data for the motion and position obtained from Hemire into the profiling data of the MBES. Then, we could properly convert the profiling points with respect to the Earth-fixed coordinates. This paper describes the integration of the MBES with Hemire, as well as the coordinate conversion between them. Bathymetric maps near the summit of the Forecast volcano were successfully collected through these processes. A comparison between the bathymetric maps from the MBES and those from the Onnuri Research Vessel, the mother ship of the ROV Hemire for these explorations, is also presented.

• Journal of the Society of Naval Architects of Korea
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• v.50 no.3
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• pp.138-144
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• 2013

New experimental devices and methods to measure shaft forces of ships are proposed in this paper. The strain gauge type six-component load cell was newly designed and installed to the end of the propeller shaft. The signals generated from the sensor in the propeller rotating are transferred to the new data amplifying and processing board on the shaft and the data is transmitted to the self-made wireless receiver. To find out the characteristics of shaft forces during port and starboard turning motions in sea trial, oblique and combined yaw maneuvering tests at straight, transient, maximum yaw rate, steady conditions were performed with the model ship installed the shaft forces measuring device using circular motion tester of Samsung Ship Model Basin. Characteristics of the measured shaft forces in model tests show quantitatively good agreement with the computed values obtained by the CFD programs using the measured wake data in oblique towing conditions. In the near future, It is hoped that the estimated shaft forces for a ship from this experimental method could be validated through comparison with directly measured values of a ship.

• Journal of the Korean Society of Marine Environment & Safety
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• v.20 no.2
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• pp.202-209
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• 2014

In this paper, a developed device for detecting target's location and avoiding collision is proposed. Velocity and acceleration model of target are derived to estimate target's information, i.e. position, velocity and acceleration considering process and measurement noise. Kalman filtering method applied to the estimation process and its results was confirmed by simulation. The distance measurements system using laser sensor for moving target system is also developed to confirm the effectiveness of the proposed scheme. Experiments to get information of moving target with velocity and acceleration model was executed. The data with filtering and without filtering was compared by experiments. Discontinuous measured data was changed to smooth and continuous data by Kalman filtering. It is confirmed that desired data was obtained by applying proposed scheme. UI for measuring and monitoring the target data is developed and visual and auditory alarm function is attached on the system Finally, position estimation system of moving target with good performance is achieved by low price equipments.

• Journal of Advanced Navigation Technology
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• v.24 no.3
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• pp.192-197
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• 2020

Recently, the technologies related to autonomous drive has studying the goal for safe operation and prevent accidents of vehicles. There is radar and camera technologies has used to detect obstacles in these autonomous vehicle research. Now a day, the method for using LiDAR sensor has considering to detect nearby objects and accurately measure the separation distance in the autonomous navigation. It is calculates the distance by recognizing the time differences between the reflected beams and it allows precise distance measurements. But it also has the disadvantage that the recognition rate of object in the atmospheric environment can be reduced. In this paper, point cloud data by triangular functions and Line Regression model are used to implement measurement algorithm, that has improved detecting objects in real time and reduce the error of measuring separation distances based on improved reliability of raw data from LiDAR sensor. It has verified that the range of object detection errors can be improved by using the Python imaging library.

• Journal of IKEEE
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• v.14 no.3
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• pp.244-249
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• 2010

We fabricated optical sensor system that take a measurement particles using a line-CCD in ocean. To measure particles, we used 680nm laser diode which is appropriate. we tested to operate optical system in water tank and ocean. It has performance that detected signal of sensors transfer microprocessor, FPGA as long as move up and down it's motion. The system algorithm also analysis output -pressure, temperature, particle numbers in depth.-For experiment, our particle sensor system has high accuracy counter. therefore, we proposed that a line-CCD is available on optical sensor system in ocean.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.4
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• pp.676-682
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• 2018

In wireless sensor networks, we propose an optimization algorithm in order to minimize the consumed energy of nodes for maritime search and rescue. In the marine environment, search and rescue operations are mainly performed on the surveillance side and passively on the rescued side. A self-configurable wireless sensor network can build a system that can send rescue signals in the operations. A simulated annealing algorithm is proposed to minimize the consumed energy of nodes in the networks with many nodes. As the density of nodes becomes higher, the algorithmic computation will increase highly. To search the good result in a proper execution time, the proposed algorithm proposes a new neighborhood generating operation and improves the efficiency of the algorithm. The proposed algorithm was evaluated in terms of the consumed energy of the nodes and algorithm execution time, and the proposed algorithm performed better than other optimization algorithms in the performance results.

• Journal of the Society of Naval Architects of Korea
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• v.61 no.2
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• pp.115-124
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• 2024

To detect and prevent structural damage caused by various loads on marine structures and ships, structural health monitoring procedure is essential. Estimating loads acting on the structures which are measured by sensors that are mounted properly are crucial for structural health monitoring. However, attaching an excessive number of sensors to the structure without consideration can be inefficient due to the high costs involved and the potential for inducing structural instability. In this study, we introduce a method to determine the optimal number of sensors and their optimized locations for strain measurement sensors, allowing for accurate load estimation throughout the structure using model expansion method. To estimate the loads exerted on the entire structure with minimal sensors, we construct a strain-load interpolation matrix using the strain mode shapes of the finite element (FE) model and select the optimal sensor locations by applying D-Optimal Design and the row exchange algorithm. Finally, we estimate the loads exerted on the entire structure using the model expansion method. To validate the proposed method, we compare the results obtained by applying the optimal sensor placement and model expansion method to an FE model subjected to arbitrary loads with the loads exerted on the entire FE model, demonstrating efficiency and accuracy.

• Ocean and Polar Research
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• v.43 no.4
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• pp.229-243
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• 2021

Quality control (QC) to process observed time series has become more critical as the types and amount of observed data have increased along with the development of ocean observing sensors and communication technology. International ocean observing institutions have developed and operated automatic QC procedures for these observed time series. In this study, the performance of automated QC procedures proposed by U.S. IOOS (Integrated Ocean Observing System), NDBC (National Data Buy Center), and OOI (Ocean Observatory Initiative) were evaluated for observed time-series particularly from the Yellow and East China Seas by taking advantage of a confusion matrix. We focused on detecting additive outliers (AO) and temporary change outliers (TCO) based on ocean temperature observation from the Ieodo Ocean Research Station (I-ORS) in 2013. Our results present that the IOOS variability check procedure tends to classify normal data as AO or TCO. The NDBC variability check tracks outliers well but also tends to classify a lot of normal data as abnormal, particularly in the case of rapidly fluctuating time-series. The OOI procedure seems to detect the AO and TCO most effectively and the rate of classifying normal data as abnormal is also the lowest among the international checks. However, all three checks need additional scrutiny because they often fail to classify outliers when intermittent observations are performed or as a result of systematic errors, as well as tending to classify normal data as outliers in the case where there is abrupt change in the observed data due to a sensor being located within a sharp boundary between two water masses, which is a common feature in shallow water observations. Therefore, this study underlines the necessity of developing a new QC algorithm for time-series occurring in a shallow sea.