• Design & Manufacturing
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• 제15권1호
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• pp.14-20
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• 2021

The objective of this study is to introduce the new possibility of sensing technology based on inductive displacement sensors to monitor the status of wheel position in the hot forging process. In order to validate effectiveness of proposed sensing technology, the indirect forging force measurement with displacement sensor was applied into a typical closed hot forging die-set used for the manufacturing of flange bolts. The locations to implement the displacement sensor were selected carefully by simulating forming process and static structural. From the measurement results of the forging force change during one hot forging cycle, it was found that the proposed monitoring system can provide useful information to understand the detailed behaviors of die-set in the closed hot forging process.

• 한국멀티미디어학회논문지
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• 제24권8호
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• pp.1138-1148
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• 2021

In this study, we developed a 'shared-use mobility'-mounted local particulate matter monitoring terminal technology to measure the actual particulate matter concentration around me. As a mobile terminal device in the form of an IoT sensor platform, it is designed to be separated into a control module and a sensor module to minimize interference between sensors and to consider the optimal observation position of each sensor. As a result of the field test, it was confirmed that particulate matter was locally different depending on time and space even within the same area. In addition, it was confirmed that the concentration of particulate matter in the relevant section differed by up to 100 times compared to the surrounding area due to specific sources of particulate matter such as unpaved roads. In addition, we positively reviewed the applicability of the service in the real-time metaverse environment using this result. Through technological advancement and application of multiple shared-use mobilities, we expect to be able to provide new services for practical smart city air environment monitoring, such as localized particulate matter information, air pollution event information, and identification of causes of particulate matter.

• 대한안전경영과학회지
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• 제23권4호
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• pp.93-104
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• 2021

In this paper, we propose a method for diagnosing overload and working load of collaborative robots through performance analysis of machine learning algorithms. To this end, an experiment was conducted to perform pick & place operation while changing the payload weight of a cooperative robot with a payload capacity of 10 kg. In this experiment, motor torque, position, and speed data generated from the robot controller were collected, and as a result of t-test and f-test, different characteristics were found for each weight based on a payload of 10 kg. In addition, to predict overload and working load from the collected data, machine learning algorithms such as Neural Network, Decision Tree, Random Forest, and Gradient Boosting models were used for experiments. As a result of the experiment, the neural network with more than 99.6% of explanatory power showed the best performance in prediction and classification. The practical contribution of the proposed study is that it suggests a method to collect data required for analysis from the robot without attaching additional sensors to the collaborative robot and the usefulness of a machine learning algorithm for diagnosing robot overload and working load.

• International Journal of Naval Architecture and Ocean Engineering
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• 제13권1호
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• pp.223-235
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• 2021

The Vortex-Induced Vibration (VIV) test system on deepwater riser based on Bare Fiber Bragg Grating (BFBG) sensor technology was designed. Meanwhile, a riser VIV response numerical model was established based on the work-energy principle. The results show that the first-order vibration frequency dominates the vibration of the riser, and as the velocity increases, the dominant frequency of the riser gradually increases under the effect of different top tensions. At the same velocity, as the top tension increases step by step, the dominant frequency and fatigue damage at the same position along the axial length of the riser both gradually decreases. The model test and numerical simulation show a relatively consistent change, maintaining a high degree of agreement. The process control system based on BFBG of model test has excellent performance, and FBG sensors have great advantages in VIV test of a vertical riser in water.

• International Journal of Korean Welding Society
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• 제2권1호
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• pp.45-51
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• 2002

In the multi-pass welding of pressure vessels or ships, the mechanical touch sensor system is generally used together with a manipulator to measure the gap and depth of the narrow gap to perform seam tracking. Unfortunately, such mechanical touch sensors may commit measuring errors caused by the deterioration of the measuring device. An automation system of narrow gap multi-pass welding using a laser vision system which can track the seam line of narrow gap and which can control welding power has been developed. The joint profile of the narrow gap, with 250mm depth and 28mm width, can be captured by laser vision camera. The image is then processed for defining tracking positions of the torch during welding. Then, the real-time correction of lateral and vertical position of the torch can be done by the laser vision system. The adaptive control of welding conditions like welding currents and welding speeds, can also be performed by the laser vision system, which cannot be done by conventional mechanical touch systems. The developed automation system will be adopted to reduce the idle time of welders, which happens frequently in conventional long welding processes, and to improve the reliability of the weld quality as well.

• 센서학회지
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• 제32권2호
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• pp.67-74
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• 2023

A microfluidic paper-based analytical device (µPAD) is proposed for the selective detection of ammonia in water by using the modified Berthelot reagent and a fluidic channel consisting of hollow paper. The modified Berthelot reagents were uniformly dispersed in cyclohexane and then immobilized in a detection zone of the µPAD. The loading position of the reagents and the type of a sample flow channel were optimized to achieve a sensitive ammonia detection within a short analytical time. The NH₃ µPAD exhibits a linear colorimetric response to the concentration of ammonia dissolved in water in the range of 1-100 mg L^-1, and its limit-of-detection is 1.75 mg L^-1. In addition, the colorimetric response was not influenced by the addition of 100 mg L^-1 nitrogen containing compounds (sodium nitrate, sodium nitrite, uric acid, hydroxylamine, butylamine, diethylamine) or inorganic salts (NaCl, Na₂HPO₄), presenting the enough selectivity in the detection of water-dissolved ammonia against possible interferents.

• Advances in aircraft and spacecraft science
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• 제10권1호
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• pp.67-82
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• 2023

Linear array imaging sensors are widely used in remote sensing satellites. The final products of an imaging sensor can only be used when they are geometrically, radiometrically, and spectrally calibrated. Therefore, at the first stages of sensor design, a detailed calibration procedure must be carefully planned based on the accuracy requirements. In this paper, focusing on inherent optical distortion, a step-by-step procedure for laboratory geometric calibration of a typical push-broom satellite imaging sensor is simulated. The basis of this work is the simulation of a laboratory procedure in which a linear imager mounted on a rotary table captures images of a pin-hole pattern at different angles. By these images and their corresponding pinhole approximation, the correction function is extracted and applied to the raw images to give the corrected ones. The simulation results illustrate that using this approach, the nonlinear effects of distortion can be minimized and therefore the accuracy of the geometric position of this method on the image screen can be improved to better than the order of sub-pixel. On the other hand, the analyses can be used to proper laboratory facility selection based on the imaging sensor specifications and the accuracy.

• 한국가시화정보학회지
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• 제21권1호
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• pp.18-25
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• 2023

In these days, high dimensional data prediction technology based on neural network shows compelling results in many different kind of field including engineering. Especially, a lot of variants of convolution neural network are widely utilized to develop pixel level prediction model for high dimensional data such as picture, or physical field value from the sensors. In this study, velocity vector field of ideal flow on ship surface is estimated on pixel level by Unet. First, potential flow analysis was conducted for the set of hull form data which are generated by hull form transformation method. Thereafter, four different neural network with a U-shape structure were conFig.d to train velocity vectors at the node position of pre-processed hull form data. As a result, for the test hull forms, it was confirmed that the network with short skip-connection gives the most accurate prediction results of streamlines and velocity magnitude. And the results also have a good agreement with potential flow analysis results. However, in some cases which don't have nothing in common with training data in terms of speed or shape, the network has relatively high error at the region of large curvature.

• 센서학회지
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• 제33권3호
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• pp.139-146
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• 2024

Surface-enhanced Raman scattering (SERS) enables the detection of various types of π-conjugated biological and chemical molecules owing to its exceptional sensitivity in obtaining unique spectra, offering nondestructive classification capabilities for target analytes. Herein, we demonstrate an innovative strategy that provides significant machine learning (ML)-enabled predictive SERS platforms through surface-engineered graphene via complementary hybridization with Au nanoparticles (NPs). The hybridized Au NPs/graphene SERS platforms showed exceptional sensitivity (10^-7 M) due to the collaborative strong correlation between the localized electromagnetic effect and the enhanced chemical bonding reactivity. The chemical and physical properties of the demonstrated SERS platform were systematically investigated using microscopy and spectroscopic analysis. Furthermore, an innovative strategy employing ML is proposed to predict various analytes based on a featured Raman spectral database. Using a customized data-preprocessing algorithm, the feature data for ML were extracted from the Raman peak characteristic information, such as intensity, position, and width, from the SERS spectrum data. Additionally, sophisticated evaluations of various types of ML classification models were conducted using k-fold cross-validation (k = 5), showing 99% prediction accuracy.

• 생물환경조절학회지
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• 제23권2호
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• pp.158-166
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• 2014

본 연구는 FDR(Frequency Domain Reflectometry) 센서를 이용하여 코코넛 코이어 배지에서 급액 공급관리에 적합한 수분측정 장소를 찾고 보다 정밀한 측정 방안을 제시하기 위한 기초 실험으로 급액구에서의 측정거리와 위치 그리고 노이즈 필터 사용에 따른 수분변화와 편차를 조사하였다. 시판되는 코코넛 코이어 슬라브 중 coir dust와 chip의 함량이 10:0, 7:3, 5:5, 3:7인 배지들을 사용했고 배지 윗면과 측면에 급액구부터 5, 10, 20, 30cm의 거리를 두어 센서를 설치하여 동일한 급액을 공급한 후 수분변화를 측정하였으며, 노이즈 필터 사용 여부에 따른 수분변화는 내부가 균일한 인공토양인 글라스 비드를 포수하여 설치간격 0, 6, 12, 21cm에서 측정하였다. 배지조성에 상관없이 센서가 급액구에 가까울수록 높은 수분함량 증가를 나타내었다. 배지 조성 3:7과 10:0에서는 윗면과 측면 측정에 따른 배지 수분함량 변화 특성이 차이를 보이지 않았으나 5:5와 7:3에서는 윗면을 측정시 보다 높은 수분함량 증가를 보였다. Chip 함량이 상대적으로 많은 3:7 배지에서는 다른 배지들보다 수분함량 증가가 낮았다. 노이즈 필터를 사용하게 되면 측정치 변동과 편차가 감소하였다. 따라서, 코코넛 코이어 배지에서 FDR센서를 이용해 배지 수분 계측시 급액구에 가까운 거리의 윗면을 측정하는 것이 급액 이후 배지내 변화를 관측이 용이하다. 다수의 센서를 사용하여 측정할 경우에는 센서간 간격을 21cm 이상으로 넓게 설치하도록 하며, 노이즈 필터는 측정 안정성 향상을 위해 사용을 권장한다.