• Journal of the Korea Institute of Military Science and Technology
• /
• v.25 no.3
• /
• pp.267-274
• /
• 2022

The Republic of Korea has a close cooperative relationship with NATO, of which the United States is a member. NATO is encouraged to follow UHF coalition waveforms for military air operations(SATURN) as defined in STANAG 4372. SATURN is a high-speed frequency hopping waveform with enhanced anti-jamming and security functions. Plans to improve the performance of existing military aircraft with air to ground radios to which SATURN function is applied. IFF case analysis and MRT evaluation plan were established to present an efficient test and evaluation plan for air to ground radios.

• Proceedings of the Korean Institute of Building Construction Conference
• /
• 2021.11a
• /
• pp.146-147
• /
• 2021

In this study, the deterioration of concrete subjected to high temperature was evaluated using harmonics. When concrete is exposed to high temperatures, its mechanical properties deteriorate. In order to evaluate this deterioration, a method of analyzing the waveform of elastic waves was applied. As the heating temperature increased, the fundamental wave of the 50 kHz elastic wave passing through the concrete decreased. In addition, harmonics were generated at each temperature, and the higher the heating temperature, the greater the ratio of harmonics. The higher the compressive strength, the greater the amplitude of the fundamental wave, and this phenomenon is thought to be due to the internal structure of concrete.

• Structural Engineering and Mechanics
• /
• v.84 no.2
• /
• pp.253-268
• /
• 2022

Using non-destructive Acoustic Emission (AE) and optical Digital Image Correlation (DIC) methods, the moment-curvature behavior of steel and GFRP bars reinforced concrete beams under flexure was explored in this study. In the tension zone, laboratory studies were carried out on steel-RC and GFRP-RC beams with varying percentages of longitudinal reinforcement ratios of 0.33 %, 0.52%, and 1.11%. The distinct mechanism of cracking initiation and fracture progression of failure in steel-RC and GFRP-RC beams were effectively correlated and picked up using AE waveform characteristics of the number of AE hits and their amplitudes, AE energy as well as average frequency and duration. AE XY event plots and longitudinal strain profiles using DIC gives an online and real-time visual display of progressive AE activity and strains respectively to efficaciously depict the crack evolution and their advancement in steel-RC and GFRP-RC beams. They display a close matching with the micro and macro-cracks visually observed in the actual beams at various stages of loading.

• Journal of the Korean Society for Nondestructive Testing
• /
• v.27 no.6
• /
• pp.531-540
• /
• 2007

While determination of the solid propellant burning rates by ultrasound, it has been reported that the frequent data scatters were caused by two major factors; 1) variation in the acoustical properties, and 2) non-linear burning of a solid propellant sample under investigation. This work is carried out for the purpose of investigating the effect of non-linear burning of solid propellant samples. Specifically, we propose an ultrasonic measurement model that can predict the reflections from solid propellant surfaces with non-linear burning by the combination of two ingredients; 1) a pulse-echo ultrasonic measurement model for a planar, circular reflector imbedded in the second medium in an immersion set-up, and 2) an efficient model of non-linear burning surfaces with a number of small, planar circles. Then, we demonstrate the capability of the proposed measurement model by simulation of the surface echo signals from four different burning surfaces that have been generated by the combination of two factors; the base shape (flat or paraboloidal) and the surface roughness (perfectly smooth or randomly rough). From the simulation presented here, we can confirm the fact that the non-linear burning of the propellant can cause the waveform change of the burning surface echo and the corresponding spectrum variation.

• Journal of Biomedical Engineering Research
• /
• v.41 no.2
• /
• pp.107-119
• /
• 2020

The deep neural networks (DNN) that can replicate the behavior of the human expert who recognizes the characteristics of ECG waveform have been developed and studied to analyze ECG. However, although the existing DNNs can not provide the explanations for their decisions, those trials have attempted to determine whether patients have certain diseases or not and those decisions could not be accepted because of the absence of relating theoretical basis. In addition, these DNNs required a lot of training data to obtain sufficient accuracy in spite of the difficulty in the acquisition of relating clinical data. In this study, a small-sized continuous data processing DNN (C-DNN) was suggested to determine the simple characteristics of ECG wave that were not required additional explanations about its decisions and the C-DNN can be easily trained with small training data. Although it can analyze small input data that was selected in narrow region on whole ECG, it can continuously scan all ECG data and find important points such as start and end points of P, QRS and T waves within a short time. The star and end points of ECG waves determined by the C-DNNs were compared with the results performed by human experts to estimate the accuracies of the C-DNNs. The C-DNN has 150 inputs, 51 outputs, two hidden layers and one output layer. To find the start and end points, two C-DNNs were trained through deep learning technology and applied to a parameter acquisition algorithms. 12 lead ECG data measured in four patients and obtained through PhysioNet was processed to make training data by human experts. The accuracy of the C-DNNs were evaluated with extra data that were not used at deep learning by comparing the results between C-DNNs and human experts. The averages of the time differences between the C-DNNs and experts were 0.1 msec and 13.5 msec respectively and those standard deviations were 17.6 msec and 15.7 msec. The final step combining the results of C-DNN through the waveforms of 12 leads was successfully determined all 33 waves without error that the time differences of human experts decision were over 20 msec. The reliable decision of the ECG wave's start and end points benefits the acquisition of accurate ECG parameters such as the wave lengths, amplitudes and intervals of P, QRS and T waves.

• Journal of the Korean Society of Marine Environment & Safety
• /
• v.25 no.6
• /
• pp.802-808
• /
• 2019

DC motors are used extensively on shipboard, including as the ship's winch operating motor, owing to their simple speed control and excellent output torque characteristics. Moreover, they were used as propulsion motors in the early days of electric propulsion ships. However, mechanical rectifiers, such as brushes, used in DC motors have certain disadvantages. Hence, brushless DC (BLDC) motors are increasingly being used instead. While the electrical characteristics of both types of motors are similar, BLDC motors employ electronic rectifying devices, which use semiconductor elements, instead of mechanical rectifying devices. The inverter system for driving conventional BLDC motors uses a two-phase excitation method so that the waveform of the back electromotive force becomes trapezoidal. This causes harmonics and torque ripple in the phase current switching period in which the winding wire through which the current flows is changed. Researchers have studied and presented various methods to reduce the harmonics and torque ripple. This study applies a cascaded H-bridge multilevel inverter, which implements a proportional-integral speed current controller algorithm in the driving circuit of the BLDC motor for electric propulsion ships using a power analysis program. The simulation results of the modeled BLDC motor show that the driving method of the proposed BLDC motor improves the voltage waveform of the input side of the motor and remarkably reduces the harmonics and torque ripple compared with the conventional driving method.

• Journal of the Korean Society for Precision Engineering
• /
• v.19 no.5
• /
• pp.133-138
• /
• 2002

The technique of high speed machining is widely studied in machining fields, because the high efficiency and accuracy in machining can be obtained in high speed machining. Unfortunately the development of tool fur high speed machining in not close behind that of machine tool. In this study, 10 types flat endmill is prepared for obtaining data according to tool shape. Especially, we concentrated in helix angle, number of cutting edge and rake angle. Cutting condition is selected for several experiments and measuring cutting farce, tool life, tool wear and chip shape according to cutting length. 3-axis cutting farces are acquired from the tool dynamometer with high natural frequency, as the conventional tool dynamometer (9257B, Kistler) has cannot measure the state of high frequency force. Particularly, we found out that the axial cutting force waveform has a good relation with tool wear features. And flow is interrupted at the beginning of cutting by the decrease of rake angle. By above results. it is suggested the endmill tool with 45$^{\circ}$helix angle, 6 cutting edge and -15$^{\circ}$rake angle is suitable for high speed machining.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
• /
• v.29 no.2
• /
• pp.138-141
• /
• 2018

In this paper, we describe the designed digital waveform of a linear frequency-modulated (FM) chirp signal using field-programmable gate arrays (FPGAs) for image radar, and this signal is modulated with an I-Q modulator, and multiplied by 24 frequency multipliers to obtain a 94-GHz W-band wideband chirp generator. The developed chirp generator is an FM signal with a 94-GHz carrier frequency and a 960-MHz bandwidth, and the flatness is less than 1.0 dB at intermediate frequency (IF) (3.9 GHz), 2.0 dB in the W-band, and it has a 0.3-W output power in the W-band.

• Journal of the Korean Society of Mechanical Technology
• /
• v.13 no.1
• /
• pp.17-22
• /
• 2011

As the quality of a weld joint is strongly influenced by process parameters the welding process, an intelligent algorithms that can predict the bead geometry and shape to accomplish the desired mechanical properties of the weldment should be developed. In this study, prepared by ${\Phi}1.6mm$ GMA welding of metal wire nose Advice jowelui 350A 600A grade level inverter welder and DAIHEN SCR's were carried out using welding. Welding conditions were 5.5m/min wire feed rate the welding current is rapidly transmit approximately 260A, welding voltage was about 30V. CTWD a 22mm, shielding gas was Ar 20L/min and the welding speed was a 240mm/min. Using data collected during welding equipment welding current and welding voltage waveform was analyzed by measuring the volume of the transition mode. Addition of $CaCO_3$ as a loss of the spread of the weld bead dilution rate decreased, suggesting that, GMA in the overlay welding bead shape control, dilution control and may be used as a welding flux is considered. Stabilizing effect of the arc by the Ca-containing $CaF_2$, $CaCO_3$, $CaMg(CO_3)_2$, respectively, welding flux 0.1wt.% added GMA welding and weld overlay were evaluated with dilution, $CaF_2$, and $CaMg(CO_3)_2$ added to the dilution of Seemed to increase.

• Journal of Biomedical Engineering Research
• /
• v.18 no.4
• /
• pp.429-438
• /
• 1997

Mechanical valve is one of the most widely used implantable artificial organs of which the reliability is so important that its failure means the death of patient. Therefore early noninvasive detection is essentially required, though mechanical valve failure with thrombosis is the most common. The objective of this paper is to detect the thrombosis formation by spectral analysis and neural network. Using microphone and amplifier, we measured the sound from the mechanical valve which is attached to the pneumatic ventricular assist device. The sound was sampled by A/D converter(DaqBook 100) and the periodogram is the main algorithm for obtaining spectrum. We made the thrombosis models using pellethane and silicon and they are thrombosis model on the valvular disk, around the sewing ring and fibrous tissue growth across the orifice of valve. The performance of the measurment system was tested firstly using 1 KHz sinusoidal wave. The measurement system detected well 1KHz spectrum as expected. The spectrum of normal and 5 kinds of thrombotic valve were obtained and primary and secondary peak appeared in each spectrum waveform. We find that the secondary peak changes according to the thrombosis model. So to distinguish the secondary peak of normal and thrombotic valve quantatively, 3 layer back propagation neural network, which contains 7, 000 input node, 20 hidden layer and 1 output was employed The trained neural network can distinguish normal and valve with more than 90% probability. As a conclusion, the noninvasive monitoring of implanted mechanical valve is possible by analysing the acoustical spectrum using neural network algorithm and this method will be applied to the performance evaluation of other implantable artificial organs.