• Journal of Korea Foresty Energy
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• v.7 no.1
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• pp.28-36
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• 1987

To know the possibility of fuel substitution for Diesel engine with the seed oil of Evodia daniellii, which is one of the native oil seed trees in Korea. the refined seed oil mixed with light oil in the various rates was tested in the 8 PS Diesel engine: the output, the fuel consumption rate, the governor performance, the rpm stability in the total loading condition. the content of graphite in the burned gas, and the traction coefficients at the different gear stages were maintained The following results were discussed. 1. The output at the normal revolution (2200rpm)was increased as the percent seed oil increased. At the lower rpm (2000-1500rpm )there were no consistent difference in the outputs among fuels of the different percent seed oil 2. The rate of fuel consumption was inclosed as the percent seed oil increased in each loading condition. 3. The more percent sud oil was mixed in the fuel. the better governor performance appeared at both the instantaneous and stable speed. 4. The more percent seed oil was mixed In the fuel, the more stable rpm ratio was maintained 5. The graphite content In the burned gas was increased as the load increased, but there was no apparent difference in the content at each load among the 100$\%$ seed oil, the 100$\%$ light oil, and the mixtures in various rates. 6. In all fuel mixtures the maximam traction coefficent appeared at the third transmission gear stage. Generally in over all transmission gear stages the fuel mixtures of the seed oil:light oil ratio from 7:3 to 5:5 resulted greater traction force than the other fuels.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.3C
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• pp.295-301
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• 2010

In this paper, we propose a new mouthpiece model for the electronic wind instrument using a propeller and linear analysis for fast tracking wind velocity blown. This method is a modification of the velocity anemometer for fast tracking wind velocity by the propeller's angular velocity (speed of revolution). In the case of velocity anemometer, wind velocity is calculated using the property that wind velocity is in proportion to the propeller's angular velocity. However, wind velocity and angular velocity of the propeller are not in one-one correspondence because wind velocity takes some transitional time for the expected wind velocity to be calculated from angular velocity. To resolve this problem, we propose a method for finding the impulse response of the system which can be considered as a linear system, and for estimating the wind velocity by deconvolving the propeller's angular velocity with the impulse response. To experiment and to prove the validity of the proposed system, we designed a mouthpiece model which consists of a motor, a propeller and an encoder. The result of estimated wind velocity in this method showed that this system is about eightfold faster than the method by the conventional velocity anemometer.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2005.10a
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• pp.181-185
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• 2005

The treated ballast water from previous treatment contains microorganisms and pathogenic organisms in an filtration treatment system. The advantage of this process can be filtrated to minimize the demage to screen clogging of drum filter with sweeping the solids off rotating the surface of the filter. Another advantage is to drop off the solids with controlling revolution of drum screen in pretreatment filtration process. Also the fact that it is easy to attach and detach a several type of screen for getting the expected water quality is another advantage, too. Filter rotation speed at 20rpmis 40.5cmHg and 40rpm is 36.6cmHg. Filter out impurities from ballast water over 60rpm is 35cmHg. Filtration system removal aquatic organism over $80{\mu}m$ in ballast water. This study shows that the filtration treatment system has a potential for the removal of ballast water.

• Korean Journal of Metals and Materials
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• v.50 no.12
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• pp.949-953
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• 2012

$MgH_2$ was employed as a starting material instead of Mg in this work. A sample with a composition of 94 wt% $MgH_2-6$ wt% Ni (called $MgH_2-6Ni$) was prepared by reactive mechanical grinding. The hydriding and dehydriding properties were then examined. An $MgH_2-Ni$ hydrogen storage alloy that does not require an activation process was developed. The alloy was prepared in a planetary ball mill by grinding for 4 h at a ball disc revolution speed of 250 rpm under a hydrogen pressure of about 12 bar. The sample absorbed 3.74 wt% H for 5 min, 4.07 wt% H for 10 min, and 4.41 wt% H for 60 min at 573 K under 12 bar $H_2$, and desorbed 0.93 wt% H for 10 min, 1.99 wt% H for 30 min, and 3.16 wt% H for 60 min at 573 K under 1.0 bar $H_2$. $MgH_2-6Ni$ after reactive mechanical grinding contained ${\beta}-MgH_2$ (a room temperature form of $MgH_2$), Ni, ${\gamma}-MgH_2$ (a high pressure form of $MgH_2$), and a very small amount of MgO. Reactive mechanical grinding of Mg with Ni is considered to facilitate nucleation, and to reduce the particle size of Mg. $Mg_2Ni$ formed during reactive mechanical grinding also increases the hydriding and dehydriding rates of the sample.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.18 no.9
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• pp.29-35
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• 2019

The structure of the machinery industry due to the 4th industrial revolution is changing from precision and durability to intelligent and smart machinery through sensing and interconnection(IoT). There is a growing need for research on prognostics and health management(PHM) that can prevent abnormalities in processing machines and accurately predict and diagnose conditions. PHM is a technology that monitors the condition of a mechanical system, diagnoses signs of failure, and predicts the remaining life of the object. In this study, the vibration generated during machining is measured and a classification algorithm for normal and fault signals is developed. Arbitrary fault signal is collected by changing the conditions of un stable supply cutting oil and fixing jig. The signal processing is performed to apply the measured signal to the learning model. The sampling rate is changed for high speed operation and performed machine learning using raw signal without FFT. The fault classification algorithm for 1D convolution neural network composed of 2 convolution layers is developed.

• Journal of the Korea Convergence Society
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• v.10 no.11
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• pp.15-21
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• 2019

The fourth industrial revolution is noted. It is a smarter factory. At present, research on CNC (Computerized Numeric Controller) is actively underway in the manufacturing field. Domestic CNC equipment, acoustic sensors, vibration sensors, etc. This study can improve efficiency through CNC. Collect various data such as X-axis, Y-axis, Z-axis force, moving speed. Data exploration of the characteristics of the collected data. You can use your data as Random Forest (RF), Extreme Gradient Boost (XGB), and Support Vector Machine (SVM). The result of this study is CNC equipment.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.5
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• pp.83-99
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• 2021

With the advent of the fourth industrial revolution, studies on driving management and driving strategies of autonomous vehicles are emerging. While obtaining microscopic traffic data on vehicles is essential for such research, we also see that conventional traffic data collection methods cannot collect the driving behavior of individual vehicles. In this study, UAV videos were used to collect traffic data from the viewpoint of the aerial base that is microscopic. To overcome the limitations of the related research in the literature, the micro-traffic data were estimated using the multiple object tracking of deep learning and an image registration technique. As a result, the speed obtained error rates of MAE 3.49 km/h, RMSE 4.43 km/h, and MAPE 5.18 km/h, and the traffic obtained a precision of 98.07% and a recall of 97.86%.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.6
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• pp.1-9
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• 2018

In the fourth industrial revolution, which has become an issue now, we have been able to receive instant analysis results faster than the existing slow speed through various Big Data technologies, and to conduct real-time monitoring on mobile and web. First, various irregular sensor Data is generated using IoT device, Raspberry Pi. Sensor Data is collected in real time, and the collected data is distributed and stored using several nodes. Then, the stored Sensor Data is processed and refined. Visualize and output the analysis result after analysis. By using these methods, we can train the human resources required for Big Data and mobile related fields using IoT, and process data efficiently and quickly. We also provide information that can confirm the reliability of research results through real time monitoring.

• Journal of Advanced Navigation Technology
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• v.23 no.3
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• pp.245-250
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• 2019

Inertial navigation system has navigation errors because of the error of inertial measurement unit (IMU) and misalignment over time. In order to solve this problem, aided navigation system is performed using global navigation satellite system (GNSS), speedometer, etc. The inertial navigation system equipped with underwater vehicle mainly uses speedometer and performed aided navigation because satellite signals do not pass through underwater. There are DVL, EM-Log, and RPM in the speedometer, and the sensors are applied according to the system environment. This paper describes velocity aided navigation using RPM of inertial navigation system operating in high speed and deep water environment. In addition, we proposes an algorithm to compensate the limit of RPM with straight direction and the current velocity error. There are results of monte-calo simulation to prove performance of the proposed algorithm.

• Journal of the Korea Society for Simulation
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• v.28 no.1
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• pp.23-39
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• 2019

The use of drone-bots is demanded in times regarding the reduction of military force, the spread of the life-oriented thought, and the use of innovative technology in the defense through the fourth industrial revolution. Especially, the drone's surveillance and reconnaissance are expected to play a big role in the future battlefield. However, there are not many cases in which the concept of operation is studied scientifically. In this study, We propose search algorithms for reconnaissance drone through simulation analysis. In the simulation, the drone and target move linearly in continuous space, and the target is moving adopting the Random-walk concept to reflect the uncertainty of the battlefield. The research investigates the effectiveness of existing search methods such as Parallel and Spiral Search. We analyze the probabilistic analysis for detector radius and the speed on the detection probability. In particular, the new detection algorithms those can be used when an enemy moves toward a specific goal, PS (Probability Search) and HS (Hamiltonian Search), are introduced. The results of this study will have applicability on planning the path for the reconnaissance operations using drone-bots.