• Journal of Advanced Marine Engineering and Technology
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• v.23 no.5
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• pp.702-710
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• 1999

U-shaped bellows are usually used to piping system pressure sensor and controller for refriger-ator. Bellows subjected to internal pressure are designed for the purpose of absorbing deformation. Internal pressure on the convolution sidewall and end collar will be applied to an axial load tend-ing to push the collar away from the convolutions. To find out deformation behavior of bellow sub-jected to internal pressure the axisymmetric shell theory using the finite element method is adopted in this paper. U-shaped bellows can be idealized by series of conical frustum-shaped ele-ments because it is axisymmetric shell structure. The displacements of nodal points due to small increment of force are calculated by the finite element method and the calculated nodal displace-ments are added to r-z cylindrical coordinates of nodal points. The new stiffness matrix of the sys-tem using the new coordinates of nodal points is adopted to calculate the another increments of nodal displacement that is the step by step method is used in this paper. The force required to deflect bellows axially is a function of the dimensions of the bellows and the materials from which they are made. Spring constant is analyzed according to the changing geometric factors of U-shaped bellows. The FEM results were agreed with experiment. Using developed FORTRAN PROGRAM the internal pressure vs. deflection characteristics of a particu-lar bellows can be predicted by input of a few factors.

• Journal of Advanced Marine Engineering and Technology
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• v.26 no.6
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• pp.695-704
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• 2002

Generally, induction motor controller requires rotor speed sensor for commutation and current control, but it increases cost and size of the motor. So in these days, various researches including speed sensorless vector control have been reported and some of them have been put to practical use. In this paper a new speed estimation method using neural networks is proposed. The optimal neural network structure was tracked down by trial and error, and it was found that the 8-16-1 neural network has given correct results for the instantaneous rotor speed. Supervised learning methods, through which the neural network is trained to learn the input/output pattern presented, are typically used. The back-propagation technique is used to adjust the neural network weights during training. The rotor speed is calculated by weights and eight inputs to the neural network. Also, the proposed method has advantages such as the independency on machine parameters, the insensitivity to the load condition, and the stability in the low speed operation.

• Journal of Advanced Marine Engineering and Technology
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• v.33 no.6
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• pp.918-924
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• 2009

This paper deals with the experimental assessment of the vibration suppression of the smart structures. First, we have presented the paper about the new high-speed active control system that we have developed using the DSP320C6713 microprocessor and a peripheral system composed of a data acquisition system, A/D and D/A converters, piezoelectric (PZT) actuator/sensors, and drivers using PA95. Since fast data processing is very important in the active vibration control of the structures, we utilized the fast processing DSP320C6713 microprocessor as a main processor to the controller and fast peripheral devices for fast control loop. To realize a fast active vibration control, we have analyzed and tested the processing time of the peripheral devices and provided the corresponding test results. Especially, we have focused on achieving the fast signal amplification of the PA95 device since it takes most of loop times of the control system. Finally, we performed numerous experiments of active vibration control of the aluminum plate to validate the superior performance of the developed control system based on previous mode tests of the plate.

• Journal of the Society of Naval Architects of Korea
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• v.45 no.6
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• pp.579-589
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• 2008

In the past few years, there are many studies and researches of the underwater vehicles which are carried out its mission using sonar sensors. MSCL(Marine System Control Lab.) at Inha University developed test-bed small ROV, ISRO. ISRO is an open-frame type and has 4 thrusters. ISRO can control 4 motions i.e surge, sway, yaw and heave with sonar sensors. ISRO is developed for inspection of ship hull, marine structure, plant of lake or river and so on. When ROV ISRO inspects something, it is necessary to control the position of ROV ISRO's for the movement and anti-collision with structures in the underwater. In this paper, we deal with the development of a small ROV and verification of the position control system via simulation and experiment using sonar sensors.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.10a
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• pp.714-715
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• 2017

Much of the interest in ocean radiation detection has been heightened as a lot of radioactivity has leaked to the ocean due to the accident at the Fukushima nuclear power plant in Japan. In the study, MCNP simulation for radiation detection in the ocean was performed. Unlike in the air, the marine environment must ensure the stability of the sensor from water depth, temperature, pressure, and salinity. In the marine environment, too much radiation is shielded. Therefore, it is an object to select a housing with a low radiation shielding ratio.

• Journal of Advanced Marine Engineering and Technology
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• v.28 no.1
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• pp.90-97
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• 2004

DC motor requires a rotor speed sensor for accurate speed control. The speed sensors such as resolvers and encoders are used as speed detectors. but they increase cost and size of the motor and restrict the industrial drive applications. So in these days. many Papers have reported on the sensorless operation or DC motor(3)-(5). This paper Presents a new sensorless strategy using neural networks(6)-(8). Neural network structure has three layers which are input layer. hidden layer and output layer. The optimal neural network structure was tracked down by trial and error and it was found that 4-16-1 neural network has given suitable results for the instantaneous rotor speed. Also. learning method is very important in neural network. Supervised learning methods(8) are typically used to train the neural network for learning the input/output pattern presented. The back-propagation technique adjusts the neural network weights during training. The rotor speed is gained by weights and four inputs to the neural network. The experimental results were found satisfactory in both the independency on machine parameters and the insensitivity to the load condition.

• Korean Journal of Remote Sensing
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• v.18 no.3
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• pp.127-139
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• 2002

A comparison was made between the chlorophyll $\alpha$ and suspended solid (SS) retrievals from OSMI and SeaWiFS sensor to chlorophyll $\alpha$ and SS values determined with the standard method during the NFRDI's research cruises. The percentage of organic and inorganic materials from the SS was calculated to study the contribution of turbid water in the northern part of the East China Sea. The open sea waters in the Kuroshio regions of the East China Sea showed relatively higher concentration of volatile SS. However, towards the northwestern part of the East China Sea, the situation became much more optically different with the non-volatile SS from the Yangtze river and the sea bottom sources in the sea in winter and spring seasons. Furthermore, in order to indirectly detect low salinity water with high turbidity, which related to the Yangtze river using remote sensed data from the satellites, a comparison between the results of the band ratio(nLw 490nm/nLw 555nm) of SeaWiFS(OSMI) and the distribution of low salinity around the Jeju Island was presented.

• Journal of the Korean Society of Marine Environment & Safety
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• v.23 no.6
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• pp.754-758
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• 2017

In this paper, we designed and manufactured an automatic control system to minimize or avoid damage by automatically controlling ship engines in case of fog to allow for safer operation. This automatic power control system uses ATmega128 and an RPM detection circuit to measure RPM changes by artificially generating fog in the fog generator. For this purpose, we have created a complete schematic and applied our source code to an ATmega128 for PWM control using a Hall sensor motor. In future, an experiment and safety evaluation using this automatic power control system with an actual ship will be prepared.

• International Journal of Naval Architecture and Ocean Engineering
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• v.12 no.1
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• pp.691-698
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• 2020

In this study, the effects of hydrodynamic interceptors on a high-speed vessel were investigated to identify the operating principle based on experiments. Model tests were performed using a high-speed towing carriage. The resistance, trim and rise of Center of Gravity (CG) of the high-speed vessel were measured for various ship speeds and interceptor heights. As the interceptor height increased, the trim and rise of CG were reduced. In order to quantitatively analyze these phenomena, the pressure at the stern bottom was measured using tactile sensors. The reliability of the measured results from the tactile sensors was verified through repeat tests. The pressure on the stern bottom increased in proportion to the interceptor height, as the interceptor partially blocked the flow there. Then, the trim was reduced. However, as the ship speed increases, the pressure at the location close to the interceptor decreases when the interceptor height is small, leading to increased trim. Therefore, the interceptor height for running attitude control should be carefully determined considering multiple factors in the operating condition of the high-speed planing hull.

• Journal of Sensor Science and Technology
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• v.31 no.4
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• pp.266-270
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• 2022

Owing to the rising volume of seaborne trade, oil spills damage the marine environment for over 250 yearly. Thus, various analysis methods such as the Fourier-transform infrared (FTIR), Raman spectroscope, and gas chromatography are used to monitor oil spills at sea, but these methods are expensive. Recently, to reduce operational costs, an underwater fluorometer was adopted. However, this approach is not ideal for the remote sensing of oil spills because the device gets submerged in the sea. In this study, we have designed and developed a monitoring system that uses ultraviolet fluorescence to detect spilled oil or water from a distance, as well as proposed an analyzing method defining based on water Raman signal and QF535. Each fluorescence spectrum of water, oil (crude oil), and Bunker A was obtained using the system, and was calculated and analyzed from the spectrum individually. Based on the results of the analysis, we could successfully identity water and oil at a long distance.