• Journal of the Korean Society of Manufacturing Process Engineers
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• v.18 no.9
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• pp.52-57
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• 2019

The key technology of the fourth industrial revolution is artificial intelligence and machine learning. In this study, FMEA was performed on fuel pumps used as key items in most systems to identify major failure components, and artificial neural networks were built using big data. The main failure mode of the fuel pump identified by the test was coil damage due to overheating. Based on the artificial neural network built, machine learning was conducted to predict the failure and the mean error rate was 4.9% when the number of hidden nodes in the artificial neural network was three and the temperature increased to $140^{\circ}C$ rapidly.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2008.03a
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• pp.871-876
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• 2008

The blade vibration problem of bladed disk is the most critical subject to consider since it directly affects the stable performance of the engine as well as life of the engine. Especially, due to complicated vibration pattern of the bladed disk, more effort was required for vibration analysis and test. The research of measuring the vibration of the bladed disk, using NSMS(Non-intrusive stress measurement) instead of Aeromechanics testing method requiring slip ring or telemetry system with strain gauge, was successful. These testing can report the actual stresses seen on the blades; detect synchronous resonances that are the source of high cycle fatigue(HCF) in blades; measure individual blade mis-tuning and coupled resonances in bladed disks. In order to minimize the error being created due to heat expansion, the tip timing sensor is installed parallel to the blade trailing edge, yielding optimal result. Also, when working on finite element analysis, the whole bladed disk has gone through three-dimensional analysis, evaluating the family mode. The result of the analysis matched well with the test result.

• IEMEK Journal of Embedded Systems and Applications
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• v.6 no.1
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• pp.16-24
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• 2011

Automotive Radar Systems are currently under development for various applications to increase accuracy and reliability. The target tracking is most important in single or multiple target environments for accuracy. The tracking algorithm provides smoothed and predicted data for target position and velocity(Doppler). To this end, the fixed gain filter(${\alpha}{\beta}$ filter, ${\alpha}{\beta}{\gamma}$ filter) and dynamic filter(Kalman filter, Singer-Kalman filter, etc) are commonly used. Gating is used to decide whether an observation is assigned to an existing track or new track. Gating algorithms are normally based on computing a statistical error distance between an observation and prediction. The data association takes the observation-to-track pairings that satisfied gating and determines which observation-to-track assignment will actually be made. For data association, NNPDA(Nearest Neighbor Probabilistic Data Association) algorithm is proposed. In this paper, we designed a target tracking system developed for an Automotive Radar System. We show the experimental results of the 77GHz FMCW radar sensor on the roads. Four tracking algorithms(${\alpha}{\beta}$ filter, ${\alpha}{\beta}{\gamma}$ filter, 2nd order Kalman filter, Singer-Kalman filter) have been compared and analyzed to evaluate the performance in test scenario.

• Journal of Information Processing Systems
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• v.14 no.6
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• pp.1347-1360
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• 2018

Owing to limited energy in wireless devices power saving is very critical to prolong the lifetime of the networks. In this regard, we designed a cross-layer optimization mechanism based on power control in which source node broadcasts a Route Request Packet (RREQ) containing information such as node id, image size, end to end bit error rate (BER) and residual battery energy to its neighbor nodes to initiate a multimedia session. Each intermediate node appends its remaining battery energy, link gain, node id and average noise power to the RREQ packet. Upon receiving the RREQ packets, the sink node finds node disjoint paths and calculates the optimal power vectors for each disjoint path using cross layer optimization algorithm. Sink based cross-layer maximal minimal residual energy (MMRE) algorithm finds the number of image packets that can be sent on each path and sends the Route Reply Packet (RREP) to the source on each disjoint path which contains the information such as optimal power vector, remaining battery energy vector and number of packets that can be sent on the path by the source. Simulation results indicate that considerable energy saving can be accomplished with the proposed cross layer power control algorithm.

• Tribology and Lubricants
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• v.35 no.1
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• pp.71-76
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• 2019

The differential planetary gear reducer as a main component of the concrete mixer driving mechanism requires a strong torque to mix concrete compounds. As this component is currently dependent on imports, it is necessary to develop it by conducting a study on vibration analysis and the resonance problem. The noise and vibration of a concrete mixer reducer increase owing to the transmission error of planetary gears, and the damage of components occurs owing to the problems in design and production. In this study, the tooth-passing frequency is calculated to evaluate the noise and vibration of a mixer reducer, and a fast Fourier transform (FFT) analysis is conducted through a vibration test using an acceleration sensor. The vibration of the reducer is measured at three points of input and output of the shaft and planetary gear housing with fixed and variable revolutions per minute. The operating conditions of gears and bearings are evaluated by performing the FFT analysis, and the resonance problem is verified. The results show that No. 1 pinion and ring gears revolve disproportionately. The amplitude values appear high, and the wear of tooth faces occur in tooth-passing frequencies and harmonic components of No. 1 and No. 2 pinion-ring gears. Therefore, we conclude that design changes in the reducer and a correction of tooth profiles are required.

• International journal of advanced smart convergence
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• v.8 no.3
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• pp.78-86
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• 2019

Recently, IoT researches using sensor data based on embedded networks in various fields including healthcare and sports have been continuously attempted. This study analyzes golf ball mobility to support IoT application in golf sports field. Generally, since the difference in density occurs due to the condition of the inner material and the abnormal state at the time of the outer skin joining during the manufacturing of the golf ball, the weight of each subset is equal for any two points with the same radius in the sphere cannot be guaranteed. For this reason, the deflected weight of the sphere has the undesirable effect of hitting the ball in a direction in which the weight of the ball is heavy. In this study, it is assumed that there is a unique center of gravity of the ball, and even if the golf ball cannot be manufactured perfectly, it wants to establish the basic principle to accurately recognize or mark the putting line based on the center of gravity. In addition, it is evaluated how the mobility of the golf ball with a deviation from the center of gravity of the golf ball affects the progress path (or movement direction) and the moving distance (or carry distance) after the golfer hits. The basic model of the mobility of the golf ball can help the golfer exercise model and the correlation analysis. The basic model of the mobility of the golf ball can help the golfer exercise model and the correlation analysis.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.4
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• pp.2223-2242
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• 2019

Distance Vector-Hop (DV-Hop) algorithm is widely used in node localization. It often suffers the wormhole attack. The current researches focus on Double-Wormhole-Node-Link (DWNL) and have limited attention to Multi-Wormhole-Node-Link (MWNL). In this paper, we propose a security DV-Hop algorithm (AMLDV-Hop) to resist MWNL. Firstly, the algorithm establishes the Neighbor List (NL) in initialization phase. It uses the NL to find the suspect beacon nodes and then find the actually attacked beacon nodes by calculating the distances to other beacon nodes. The attacked beacon nodes generate and broadcast the conflict sets to distinguish the different wormhole areas. The unknown nodes take the marked beacon nodes as references and mark themselves with different numbers in the first-round marking. If the unknown nodes fail to mark themselves, they will take the marked unknown nodes as references to mark themselves in the second-round marking. The unknown nodes that still fail to be marked are semi-isolated. The results indicate that the localization error of proposed AMLDV-Hop algorithm has 112.3%, 10.2%, 41.7%, 6.9% reduction compared to the attacked DV-Hop algorithm, the Label-based DV-Hop (LBDV-Hop), the Secure Neighbor Discovery Based DV-Hop (NDDV-Hop), and the Against Wormhole DV-Hop (AWDV-Hop) algorithm.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.10a
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• pp.961-964
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• 2016

This paper describes the implementation of AUSV system for Sonar Image acquisition. The system be controlled by FF-PID algorithm for the thrusters using motion sensor and DGPS. As experimental results, the control performance is that the error distance from the destination positions are under 5m in total survey track of 1km, and the image deviation is under 12 pixel from the manned survey method, which the comparison with the total image quality is almost the same as the manned survey one. Thus the AUSV system is a new method of system can be utilized on the limited survey area as the surveyor should not be able to approach on sea surface.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.4
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• pp.71-76
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• 2019

Research on indoor location tracking technology using smartphone is actively being carried out. Especially, the movement distance of the smartphone should be accurately measured and the movement route of the user should be displayed on the map. Location tracking technology using sensors mounted on smart phones has been used for a long time, but accuracy is not good enough to measure the moving distance of the user using only the sensor. Therefore, when the user moves the smartphone in a certain posture, it must research and develop an appropriate algorithm to measure the distance accurately. In this paper, we propose a method to reduce moving distance estimation error by removing user 's foot shape by limiting the screen of smartphone in pyramid - based optical flow estimation method.

• International Journal of Computer Science & Network Security
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• v.21 no.9
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• pp.275-280
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• 2021

With the development of communication networks, the processes of exchanging and transmitting information rapidly developed. As millions of images are sent via social media every day, also wireless sensor networks are now used in all applications to capture images such as those used in traffic lights, roads and malls. Therefore, there is a need to reduce the size of these images while maintaining an acceptable degree of quality. In this paper, we use Python software to apply K-mean Clustering algorithm to compress RGB images. The PSNR, MSE, and SSIM are utilized to measure the image quality after image compression. The results of compression reduced the image size to nearly half the size of the original images using k = 64. In the SSIM measure, the higher the K, the greater the similarity between the two images which is a good indicator to a significant reduction in image size. Our proposed compression technique powered by the K-Mean clustering algorithm is useful for compressing images and reducing the size of images.