• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.39 no.2
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• pp.162-169
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• 2011

The flight control system utilize RSS(Relaxed Static Stability) criteria in both longitudinal axes to achieve performance enhancements and improve stability. The aircraft using digital flight-by-wire flight control system receives aircraft flight conditions such as pitch, roll and yaw rate, normal acceleration from RSA(Rate Sensor Assembly) and ASA(Acceleration Sensor Assembly). These sensors has permissible measurement error related to system safety of an aircraft but, unexpected flight motions are happened by sensing errors such as offset, noise and etc. The unexpected pitch down tendency occurred by ASA sensor bias in 1g level flight with pilot hands-off. This paper addresses the design and verification of flight control law to improve of pitch down or up tendency caused by ASA sensor bias. The result of analysis and flight test reveals that pitch down tendency can be improved by pitch attitude feedback system.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.8
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• pp.2900-2922
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• 2021

In this paper, the power spectral density(PSD) for Multilevel Minimum Shift Keyed signal with modulation index h = 1/2 (M-ary MSK) are derived using the mathematical method of the Markov Chain model. At first, according to an essential requirement of the phase continuity characteristics of MSK signals, a complete model of the whole process of signal generation is built. Then, the derivations for autocorrelation functions are carried out precisely. After that, we verified the correctness and accuracy of the theoretical derivation by comparing the derived results with numerical simulations using MATLAB. We also divided the spectrum into four components according to the derivation. By analyzing these figures in the graphic, each component determines the characteristics of the spectrum. It is vital for enhanced spectral characteristics. To more visually represent the energy concentration of the main flap and the roll-down speed of the side flap, the specific out-of-band power of M-ary MSK is given. OMLCD(Optimum Maximum Likelihood Coherent Detection) of M-ary MSK is adopted to compare the signal received with prepared in advance in a code element T to go for the best. And M-ary MSK BER(Bit Error Rate) is compared with the same ary PSK (Phase Shift Keying) with M=2,4,6,8. The results show the detection method could improve performance by increasing the length of L(memory inherent) in the phase continuity.

• Journal of Convergence for Information Technology
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• v.8 no.6
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• pp.135-142
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• 2018

In recent years, researches utilizing UAV for military purposes such as precision tracking and batting have been actively conducted. In order to track the preceding flight, there has been a previous research on estimating the attitude information of the flight such as roll, pitch, and yaw using images taken from the rear UAV. In this study, we propose a method to estimate the attitude information more precisely by applying the Kalman filter to the existing image processing technique. By applying the Kalman filter to the estimated attitude data using image processing, we could reduce the estimation error of the attitude angle significantly. Through the simulation experiments, it was confirmed that the estimation using the Kalman filter can estimate the posture information of the aircraft more accurately.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.4
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• pp.464-469
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• 2019

Tapered roller bearings are used widely in vans, trucks, and trains because they can support the vehicle in a stable manner even under a heavy load. The cage of a tapered roller bearing maintains the gap between the rollers, which prevents friction wear and suppresses heating. If the cage is severely deformed due to resonance, the roller may not be able to roll smoothly and even leave the cage. Consequently, it is very important to analyze the dynamic characteristics of the cage for reliable performance of a bearing. The cage essentially has geometrical tolerance in the manufacturing process. In this paper, the effects of those geometrical imperfections on the dynamic characteristics of the cage were investigated. As a result, natural frequency separation occurred near the natural frequency of the ideal cage due to geometrical imperfections. In addition, the interval was proportional to the magnitude of the geometric error, and the interval increased with increasing mode number.

• Journal of the Korea Institute of Military Science and Technology
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• v.24 no.4
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• pp.435-448
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• 2021

This study describes the depth and straight motion control performance depending on control surface combinations of a supercavitating underwater vehicle. When an underwater vehicle experiences supercavitation, friction resistance can be minimized, thus achieving the effect of super-high-speed driving. Six degrees of freedom modeling of the underwater vehicle are performed and the guidance and control loops are designed with not only a cavitator and an elevator, but also a rudder and a differential elevator to improve the stability of the roll and yaw axis. The control performance based on the combination of control surfaces is analyzed by the root-mean-square error for keeping depth and straight motion.

• Journal of the Korea Society of Computer and Information
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• v.27 no.11
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• pp.115-121
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• 2022

In surface mount technology (SMT), the screen printer, which is an equipment for applying solder cream, has a lot of poor coating as the pad becomes smaller. To solve this problem, a jet printer is being used recently. However, if the nozzle at the end of the valve applied to the jet printer head is not cleaned, solder cream remains or an error occurs. To prevent this, the nozzles should be cleaned periodically. In this paper, a more stable cleaning method than the existing technology is presented for the stable application of solder cream on a jet printer. In this method, cut a 35mm wide mujin cloth, wrap it in a roll, and rotate it with a DC geared motor on the other side to clean it. As a result, it was confirmed that the solder paste was not left on the nozzle surface and was well wiped when cleaning with about 2,000 dotting cycles.

• Journal of radiological science and technology
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• v.36 no.2
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• pp.123-129
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• 2013

This study investigated the rate of setup variance by the rotating unbalance of gantry in image-guided radiation therapy. The equipments used linear accelerator(Elekta Synergy TM, UK) and a three-dimensional volume imaging mode(3D Volume View) in cone beam computed tomography(CBCT) system. 2D images obtained by rotating $360^{\circ}$and $180^{\circ}$ were reconstructed to 3D image. Catpan503 phantom and homogeneous phantom were used to measure the setup errors. Ball-bearing phantom was used to check the rotation axis of the CBCT. The volume image from CBCT using Catphan503 phantom and homogeneous phantom were analyzed and compared to images from conventional CT in the six dimensional view(X, Y, Z, Roll, Pitch, and Yaw). The variance ratio of setup error were difference in X 0.6 mm, Y 0.5 mm Z 0.5 mm when the gantry rotated $360^{\circ}$ in orthogonal coordinate. whereas rotated $180^{\circ}$, the error measured 0.9 mm, 0.2 mm, 0.3 mm in X, Y, Z respectively. In the rotating coordinates, the more increased the rotating unbalance, the more raised average ratio of setup errors. The resolution of CBCT images showed 2 level of difference in the table recommended. CBCT had a good agreement compared to each recommended values which is the mechanical safety, geometry accuracy and image quality. The rotating unbalance of gentry vary hardly in orthogonal coordinate. However, in rotating coordinate of gantry exceeded the ${\pm}1^{\circ}$ of recommended value. Therefore, when we do sophisticated radiation therapy six dimensional correction is needed.

• Journal of Korea Water Resources Association
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• v.49 no.6
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• pp.469-480
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• 2016

The present study aims to develop a real-time surface image velocimeter (SIV) using an Android smartphone. It can measure river surface velocity by using its built-in sensors and processors. At first the SIV system figures out the location of the site using the GPS of the phone. It also measures the angles (pitch and roll) of the device by using its orientation sensors to determine the coordinate transform from the real world coordinates to image coordinates. The only parameter to be entered is the height of the phone from the water surface. After setting, the camera of the phone takes a series of images. With the help of OpenCV, and open source computer vision library, we split the frames of the video and analyzed the image frames to get the water surface velocity field. The image processing algorithm, similar to the traditional STIV (Spatio-Temporal Image Velocimeter), was based on a correlation analysis of spatio-temporal images. The SIV system can measure instantaneous velocity field (1 second averaged velocity field) once every 11 seconds. Averaging this instantaneous velocity measurement for sufficient amount of time, we can get an average velocity field. A series of tests performed in an experimental flume showed that the measurement system developed was greatly effective and convenient. The measured results by the system showed a maximum error of 13.9 % and average error less than 10 %, when we compared with the measurements by a traditional propeller velocimeter.

• Journal of Korean Society for Atmospheric Environment
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• v.27 no.2
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• pp.201-208
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• 2011

Recently, a real-time, pocket-sized aethalometer (microAeth$^{(R)}$ model AE51) has been developed by Magee Scientific Inc. for measuring the concentration of black carbon in the atmosphere. In this study, two aethalometers, models AE-16 and AE-51, which measure the optical absorption of carbon particles at infrared 880 nm, were operated at time interval of 5-min between January 9 and February 10, 2010 at an urban site of Gwangju, to compare the accuracy of black carbon (BC) concentrations reported from the AE-51 model and to investigate reasonable sampling time of filter media in the AE-51. The air samples in the AE-51 and AE-16 models are collected on T60 (Teflon coated glass fiber) filter media (filter spot area: 0.07 $cm^2$) and quartz fiber roll-tape filter (filter spot area: 1.67 $cm^2$), respectively. Real-time measurement results indicate that when the filters were clean, the AE-51 BC was greater than or similar to the AE-16 BC data. However as the filter spots become darker, the AE-16 BC concentrations were higher than the AE-51 BC data and the difference in the BC concentrations from two AE models becomes gradually increased. Relative error in the AE-51 and AE-16 BC concentrations showed significance difference depending on used time of the filter in the AE-51 model, weather pattern, levels of air pollution, etc, ranging from 11.5% (used time of the filter in AE-51: 1,595 min) to 52.5% (used time of the filter in AE-51: 2,085 min). When considering the used time of one filter ticket in the AE-51 model and difference (or relative error %) between AE-16 and AE-51 BC concentrations, it is recommended that the standard sampling time per one filter ticket within the AE-51 model be less than approximately 24 hr (1,440 min) under the normal weather conditions except for severe haze and mist events.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.14 no.3
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• pp.201-207
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• 2021

Deep learning, a type of machine learning, performs learning while changing the weights as it progresses through each learning process. Tensor Flow and Keras provide the results of the end of the learning in graph form. Thus, If an error occurs, the result must be discarded. Consequently, existing technologies provide a function to roll back learning results, but the rollback function is limited to results up to five times. Moreover, they applied the concept of MLOps to track the deep learning process, but no rollback capability is provided. In this paper, we construct a system that manages the intermediate value of the learning process by blockchain to record the intermediate learning process and can rollback in the event of an error. To perform the functions of blockchain, the deep learning process and the rollback of learning results are designed to work by writing Smart Contracts. Performance evaluation shows that, when evaluating the rollback function of the existing deep learning method, the proposed method has a 100% recovery rate, compared to the existing technique, which reduces the recovery rate after 6 times, down to 10% when 50 times. In addition, when using Smart Contract in Ethereum blockchain, it is confirmed that 1.57 million won is continuously consumed per block creation.