• Journal of the Korea Institute of Military Science and Technology
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• v.12 no.2
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• pp.139-145
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• 2009

This paper includes that there is the way to make the prediction of the remaining life of the barrel in small arms using analyzing dispersion. There are some ways to know the period to change the barrel such as the method of detecting the inner surface directly or inspecting the scratch using the optical sensor. However, it is a more easy way to check the dispersion for soldiers and the directors in a logistics command. Therefore, this study is conducted to focusing on the relation between firing round and dispersion. And the simple equation experimentally derives from pre-tests and analyses. Also, this equation is confirmed through the firing tests during the period of developing K11. In that sense, it can be easily applied to know the period of changing the barrel of small arms in the field army.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2019.11a
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• pp.230-232
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• 2019

There is an accelerating need for ocean sensing where autonomous vehicles can play a key role in assisting engineers, researcher and scientists with environmental monitoring and collecting oceanographic data. This paper is performed to develops an autonomous sailing drone to be used as a sensor carrying platform for autonomous data acquisition at Sea. From a sailing drone design viewpoint, it is important to establish reliable prediction methods for sailing drone's resistance. The required power for the propulsion unit depends on the ship resistance and speed. There are three solutions for the prediction of ship resistance as follow analytical methods, model tests in tanks and Computational Fluid Dynamics (CFD). The present paper aims at simulating sailing drone friction resistance using numerical method. The dynamic mesh motion is used to describe the sailing drone movement.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2014.10a
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• pp.267-272
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• 2014

In this paper, we analyze the characteristics for the driving shock resistance of the military vehicle through the bump test. Prior to the experiment, theoretical analysis was performed by using the SRS(shock response spectrum) and VRS(vibration response spectrum) analysis method. And we estimated the characteristics for the driving shock resistance of the military vehicle. Bump test was performed using the acceleration sensor and the driving test at a different speed. We evaluated the characteristics for the driving shock resistance of the military vehicle based on the result. And predicted values were compared with the theoretical analysis. In addition, we evaluated the results of the theoretical prediction of the SRS and the VRS analysis. And we evaluate the suitability of the prediction method at military vehicle shock analysis.

• Journal of Sensor Science and Technology
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• v.2 no.1
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• pp.57-64
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• 1993

In this paper the normalized innovations squared of a Kalman filter is used to detect a bias level in prediction errors due to target accelerations. The probability density function of the normalized innovation squared is obtained for a steady state Kalman filter, and it is used to calculate the detection probability of the bias level. A typical example is given to compute the detection probability and to plot the maneuver detector operating characteristic curves.

• Journal of the Korean Society for Precision Engineering
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• v.15 no.11
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• pp.218-226
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• 1998

In this study a neural network based expert system designed to diagnose operating status of a rotating spindle system supported by ball bearings was introduced. In order to facilitate practical failure situations, five exemplary abnormal status was fabricated. Out of several possible data source locations, seven most effective spots were chosen and proven to be the most successful in predicting single and multiple abnormalities. Increased signal strength was measured around where abnormality was embedded. Signal mea-surement locations producing high prediction rate were also classified. Even though multiple abnormalities were hard to be decoupled into their individual causes, proposed diagnostic system was somewhat effective in predicting such cases under certain combination of sensor locations. Among several abnormal operating conditions, highest prediction rate can be expected when signal is spoiled by the failure or damage in outer race. Proposed diagnostic system was again proven to be the most effective system in analyzing and ranking the importance of data sources.

• Journal of the Korean Society of Systems Engineering
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• v.17 no.2
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• pp.98-105
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• 2021

As the average life expectancy is rising, the population is aging and the number of chronic diseases is increasing. This has increased the importance of healthy life and health management, and interest in mobile health services is on the rise thanks to the development of ICT(Information and communication technologies) and the smartphone use expansion. In order to meet these interests, many mobile services related to daily health are being launched in the market. Therefore, in this study, the characteristics of users who actually use mobile health services were analyzed and a predictive model applied with machine learning modeling was developed. As a result of the study, we developed a prediction model to which the decision tree and ensemble methods were applied. And it was found that the mobile health service users' continued use can be induced by providing features that require frequent visit, suggesting achievable activity missions, and guiding the sensor connection for user's activity measurement.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.2
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• pp.299-306
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• 2016

In this paper, a method of shape prediction of an endoscope handling robot that can imitate a surgeon's behavior using a sensor network is suggested. Unit sensors, which are composed of a 3-axis magnetometer and 3-axis accelerometer pair comprise the network through CAN bus communication. Each unit of the sensor is used to detect the angle of the points in the longitudinal direction of the robot, which is made from a flexible tube. The signals received from the sensor network were filtered using a low pass Butterworth filter. Here, a Butterworth filter was designed for noise removal. Finally, the Euler angles were extracted from the signals, in which the noise was filtered by the low path Butterworth filter. Using this Euler angle, the position of each sensor on the sensor network is estimated. The robot body was assumed to consist of links and joints. The position of each sensor can be assumed to be attached to the center of each link. The position of each link was determined using the Euler angle and kinematics equation. The interpolation was carried out between the positions of the sensors to be able to connect each point smoothly and obtain the final posture of the endoscope in operation. The experimental results showed that the shape of the colonoscope can be visualized using the Euler angles evaluated from the sensor network suggested and the shape of serial link estimated from the kinematics chain model.

• Proceedings of the KSR Conference
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• 2011.05a
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• pp.1661-1667
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• 2011

This study was intended to identify the applicability of energy harvesting technologies for powering a wireless health monitoring sensor system of railroad vehicle. As measuring surrounding energy under the normal operation environment, it is possible to predict amount of the applicable energy. The results of energy prediction represents the feasibility of power sources for wireless sensor systems through energy harvesting technologies under the circumstance in which the thermal energy and vibration energy are generated.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.4 no.2
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• pp.31-37
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• 1995

This study is focused on the prediction of appropriate tool life by clarifying the correlation between progressive tool wear and AE signal. when rcutting SM45C by End mill in machining center. First of all, end mill have a problem that position of sensor sticking because it is revolution tool, but I think that it can be bained specific character according to sticking Sensor in the Vise. Consequently, the following results have been obtained; 1. Each cutting speed of feed rate over 0.1mm had a tendency to increase linearly according to the RMSAE 2. The level of AE signal at the same cutting area was more sensitive to depth of cut tharn the variation of feed rate 3. In the range of cutting duringqr about 75minqr atqr cutting speed 27m/min flankqr wear turns up aboutqr 0.21mm, aboutqr 0.29mm in the caseqr of about 65minqr at 33/min, qr hereby RMSAE increased rapidly at 0.2mm flank wear, also AE-HIT and CUM-CNTS.

• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.1788-1789
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• 2011

In order to develop a one-axis gimbaled acoustic source tracker for mobile robots, a pseudo-linear direction of arrival(DOA) estimator is proposed using a linear ultrasonic sensor array. Under the assumption that the sensor measurement errors are negligible, a linear measurement model is derived using the linear prediction relation of the received sinusoidal acoustic signals. Applying the Kalman filtering technique for this model, the linear recursive DOA estimator is designed. For its linear recursive filter structure, it is preferable for real-time implementation on a commercial DSP. Through the experiments, the effectiveness of the suggested method is demonstrated.